Question: Formulation of a social media maturity model using a grounded theory methodology.

This paper introduces a comprehensive framework and set of guidelines for managing social media metrics within organizations. Given the pervasive role of social media and its distinct characteristics, such as a social network structure and democratic nature, a unique measurement strategy is essential for effective analysis and oversight. To address this need, the authors present a toolkit featuring three innovative components. Firstly, a holistic framework is developed, encompassing key aspects of social media drawn from marketing, psychology, and sociology theories. This framework delineates elements including 'motives,' 'content,' 'network structure,' and 'social roles & interactions,' supported by contemporary research. Secondly, nine guidelines are proposed, based on the theoretical framework, literature review, and practical insights, to aid in the creation of suitable social media metrics and the development of a coherent social media dashboard. Lastly, managerial implications are derived from the framework and guidelines, along with recommendations for future research. This contribution is protected under copyright by the Direct Marketing Educational Foundation, Inc., and published by Elsevier Inc. All rights are reserved.

The paper's focus on a grounded theory approach for developing a social media maturity model aligns with the need for a structured and theoretically informed method to assess and improve social media management practices within organizations. The proposed framework and guidelines offer a practical tool for organizations seeking to optimize their social media strategies, ensuring alignment with broader marketing, psychological, and sociological principles. The guidelines are designed to facilitate the measurement and monitoring of social media activities, thereby enabling more informed decision-making and enhanced performance. By integrating theoretical insights with practical applications, the paper provides a roadmap for organizations to mature their social media capabilities, ultimately contributing to the advancement of social media management as a discipline.

There have been considerable advancements in the field of MIS over the years, and it continues to grow and develop in response to the changing needs of the business and marketing environment. Professionals and academicians are contributing and serving the field of MIS through the dissemination of their knowledge and ideas in professional journals. Thus, changes and trends that likely have an impact on MIS concepts, processes, and implementation can be determined by reviewing the articles published in journals. Content of the articles published in journals can also give us an idea about the types of research and themes that are popular during a given period. To see the evolutionary change in the field of MIS, the present study examined the content of articles published in business and marketing journals. [New York Science Journal 2010;3(5):87-95]. (ISSN 1554 – 0200).

One of the key features of social networks is that users are able to share information, and through cascades of sharing information, this information may reach a large number of individuals. The high availability of user-provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. With lack of means to verify information, social media has been accused of becoming a hot bed for sharing of misinformation. Facebook, as one of the largest social networking services, has been facing widespread criticism on how its newsfeed algorithm is designed thus amplifying dissemination of misinformation. In late 2016, Facebook revealed plans to address fake news on Facebook newsfeeds. In this work, we study the methods Facebook has proposed to combat the spread of misinformation and compare it with our previously proposed approach called ‘Right-click Authenticate’. By analyzing the Business Process Modeling and Notation of both approaches, this paper suggests some key weaknesses and improvements social media companies need to consider when tackling the spread of misinformation online.

Although existing models of e-learning effectiveness in information systems (IS) have increased our understanding of how technology can support and enhance learning, most of our models do not take into account the importance of social presence. Thus, this study extends previous research by developing a model of e-learning effectiveness which adds social presence to other oft studied variables including application-specific computer self-efficacy (AS-CSE), perceived usefulness, course interaction, and e-learning effectiveness. Using data from 345 individuals, this model was validated through a field study in an introductory IS survey course. Results indicate that AS-CSE and perceived usefulness were related to course performance, course satisfaction, and course instrumentality. In addition, course interaction was related to course performance and satisfaction. Finally, social presence was related to course satisfaction and course instrumentality. Implications for research and practice are discussed. r 2007 Elsevier Ltd. All rights reserved.

Using recent insights from Cognitive, Affective and Social Neuroscience this paper addresses how affective states in social interactions can be used through social media to analyze and support behaviour for a certain lifestyle. A computational model is provided integrating mechanisms for the impact of one’s emotions on behaviour, and for the impact of emotions of others on one’s own emotion. The model is used to reason about and assess the state of a user with regard to a lifestyle goal (such as exercising frequently), based on extracted information about emotions exchanged in social interaction. Support is provided by proposing ways to affecting these social interactions, thereby indirectly influencing the impact of the emotions of others. An ambient intelligent system incorporating this has been implemented for the social medium Twitter.

Social network analysis (SNA) is not a formal theory in sociology but rather a strategy for investigating social structures. As it is an idea that can be applied in many fields, we study, in particular, its influence in the information sciences. Information scientists study publication, citation and co-citation networks, collaboration structures and other forms of social interaction networks. Moreover, the Internet represents a social network of an unprecedented scale. We are convinced that in all these studies social network analysis can successfully be applied. SNA is further related to recent theories concerning the free market economy, geography and transport networks. The growth of SNA is documented and a co-author network of SNA is drawn. Centrality measures of this network are calculated. * To whom all correspondence should be addressed.

Illicit drug use is a serious problem around the world. Social media has increasingly become an important tool for analyzing drug use patterns and monitoring emerging drug abuse trends. Accurately retrieving illicit drug-related social media posts is an important step in this research. Frequently, hashtags are used to identify and retrieve posts on a specific topic. However hashtags are highly ambiguous. Posts with the same hashtags are not always on the same topic. Moreover, hashtags are evolving, especially those related to illicit drugs. New street names are introduced constantly to avoid detection. In this paper, we employ topic modeling to disambiguate hashtags and track the changes of hashtags using semantic word embedding. Our preliminary evaluation shows the promise of these methods.

This paper presents the case of a non-traditional use of the Delphi method for theory evaluation. On the basis of experience gained through secondary and primary research, a generic decision toolkit for Delphi studies is proposed, comprising of taxonomy of Delphi design choices, a stage model and critical methodological decisions. These research tools will help to increase confidence when adopting the Delphi alternative and allow for a wider and more comprehensive recognition of the method within both scientific and interpretivist studies.

Twitter, the popular microblogging site, has received increasing attention as a unique communication tool that facilitates electronic word-of-mouth (eWOM). To gain greater insight into this potential, this study investigates how consumers’ relationships with brands influence their engagement in retweeting brand messages on Twitter. Data from a survey of 315 Korean consumers who currently follow brands on Twitter show that those who retweet brand messages outscore those who do not on brand identification, brand trust, community commitment, community membership intention, Twitter usage frequency, and total number of postings. 2014 Elsevier Ltd. All rights reserved.

Social Network Analysis (SNA) is a field of study that focuses on analyzing user profiles and participations on social network channels in order to model relationships between people and to predict certain behaviors or knowledge. To achieve their goals, researchers, interested in SNA, have to extract content and structure from the numerous social networks available today. Existing tools, which help in this task, often require substantial pre-processing or good programming skills which may not be available for all SNA researchers. This paper describes RUM, a data extraction tool which allows researchers to easily extract several types of content and structure that are available on Facebook pages. Consequently, the extracted data can be saved and analyzed. RUM Extractor is easy to set up and use, and it gives flexible options to users to specify the type and amount of content and structure they want to retrieve. The paper also demonstrates how RUM can be exploited by collecting and further analyzing data collected from two popular Arabic news pages.

The Korean Wave (K-wave), or Hallyu, referred as “the phenomenon of Korean pop culture, such as TV dramas, films, pop music, fashion, and online games being widely embraced and shared among the people of Japan, China, Hong Kong, Taiwan, and other Asian countries”. After the drama-oriented craze of the first K-wave, Korean pop music (shortly K-pop) took the integral part of the second K-wave. In addition, with the rapid spread of social media like YouTube and Twitter, K-pop has expanded its fandom outside of Asia to the West. The world-wide success of K-pop contributes to improve the `Korea' image and make a positive impact on Korean economy. It is reported that around 1,000 entertainment agencies are active in Korea, while there exist the “big three” record labels and entertainment agencies: SM Entertainment, YG Entertainment and JYP Entertainment. In this case, we address the world-wide phenomenon of K-pop popularity and the role of social media on recent boom of K-pop. Focusing the major agencies above, we present lessons on how to manage social media strategically: align strategic business model with social media; maximize various social media channels; engage customers with on-and offline promotions; and stimulate audience with exclusive contents.


Question: Creation of a social media maturity model utilizing a grounded theory method.

This paper delves into enhancing New Event Detection (NED), a task that remains ripe for innovation despite extensive prior research. We demonstrate significant performance gains in NED by integrating text classification methods and innovatively utilizing named entities. Our investigation focuses on refining document representation within a vector space-based NED framework. Moreover, we find that prioritizing named entities proves advantageous under specific circumstances. Integrating these findings, we develop a multi-stage NED system that markedly outperforms conventional single-stage systems, showcasing the effectiveness of our approach.

**Question**: The Impact of Blockchain Technology on Supply Chain Management

**Documents**: A blockchain-based architecture for the Internet of Things (IoT)
Blockchain is a distributed ledger technology that is gaining popularity due to its potential to revolutionize the way transactions are conducted. This paper proposes a blockchain-based architecture for the Internet of Things (IoT) that leverages the security and transparency of blockchain to address the challenges faced by IoT systems. The proposed architecture integrates blockchain with IoT to create a secure, transparent, and efficient system for managing IoT devices and data. The architecture is designed to enable secure communication between IoT devices, provide a tamper-proof record of device interactions, and facilitate the management of IoT devices and data. The proposed architecture is also scalable, allowing for the addition of new devices and data sources as needed. The paper discusses the benefits and challenges of using blockchain in IoT systems and provides a detailed description of the proposed architecture.

**Similar Documents**: This paper presents a novel architecture that integrates blockchain technology with the Internet of Things (IoT) to enhance security, transparency, and efficiency in IoT systems. By harnessing the distributed ledger capabilities of blockchain, the proposed framework addresses the critical challenges faced by IoT networks. This architecture facilitates secure communication among IoT devices, ensures an immutable record of device interactions, and streamlines the administration of IoT devices and data. Designed with scalability in mind, it accommodates the seamless addition of new devices and data sources. The paper elaborates on the advantages and hurdles of blockchain in IoT environments, offering a comprehensive blueprint for the integrated architecture.

Social resources like trust and shared identity make it easier for people to work and play together. Such social resources are sometimes referred to as social capital. Thirty years ago, Americans built social capital as a side effect of participation in civic organizations and social activities, including bowling leagues. Today, they do so far less frequently (Putnam 2000). HCI researchers and practitioners need to find new ways for people to interact that will generate even more social capital than bowling together does. A new theoretical construct, SocioTechnical Capital, provides a framework for generating and evaluating technology-mediated social relations.

The application of new technologies in the manufacturing environment is ushering a new era referred to as the 4th industrial revolution, and this digital transformation appeals to companies due to various competitive advantages it provides. Accordingly, there is a fundamental need for assisting companies in the transition to Industry 4.0 technologies/practices, and guiding them for improving their capabilities in a standardized, objective, and repeatable way. Maturity Models (MMs) aim to assist organizations by providing comprehensive guidance. Therefore, the literature is reviewed systematically with the aim of identifying existing studies related to MMs proposed in the context of Industry 4.0. Seven identified MMs are analyzed by comparing their characteristics of scope, purpose, completeness, clearness, and objectivity. It is concluded that none of them satisfies all expected criteria. In order to satisfy the need for a structured Industry 4.0 assessment/maturity model, SPICE-based Industry 4.0-MM is proposed in this study. Industry 4.0-MM has a holistic approach consisting of the assessment of process transformation, application management, data governance, asset management, and organizational alignment areas. The aim is to create a common base for performing an assessment of the establishment of Industry 4.0 technologies, and to guide companies towards achieving a higher maturity stage in order to maximize the economic benefits of Industry 4.0. Hence, Industry 4.0-MM provides standardization in continuous benchmarking and improvement of businesses in the manufacturing industry.

Purpose – Social commerce websites have emerged as new platforms which integrate social media features with traditional commerce aspects to enhance users’ purchasing experience. The purpose of this paper is to examine the role of social factors such as trust toward site members in determining users’ trust and risk evaluations, and the role of social commerce use habit in attenuating users’ rational risk and trust considerations for developing purchase intentions. Design/methodology/approach – Relying on the risk deterrence perspective and rational decision-making models involving trust and habit, this study proposes a set of hypotheses which are tested through analyzing survey data using structural equation modeling techniques. Findings – Results show that commerce risk deters purchasing intentions; trust toward the social commerce website increases users’ purchasing intentions; and trust toward the site members indirectly increases purchasing intentions. Moreover, trust toward site members reduces perceived commerce risk. Findings also show that habit modulates trust and risk effects on use decisions in this context; habit moderates (weakens) the relationships between commerce risk and purchase intentions and between trust toward the social commerce site and purchase intentions. Originality/value – This study extends theories on decision making in social settings such as in the case of social commerce. It does so by accounting for unique modulating effects of habit in social settings in which social aspects such as trust in other members and risk are unique and important.

Our vision is to achieve faster and near real time detection and prediction of the emergence and spread of an influenza epidemic, through sophisticated data collection and analysis of Online Social Networks (OSNs) such as Facebook, MySpace, and Twitter. In particular, we present the design of a system called SNEFT (Social Network Enabled Flu Trends), which will be developed in a 12-month SBIR (Small Business Innovation Research) project funded by the National Institutes of Health (NIH). We describe the innovative technologies that will be developed in this project for collecting and aggregating OSN data, extracting information from it, and integrating it with mathematical models of influenza. One of the monitoring tools used by the Centers for Disease Control and Prevention (CDC) is reports of Influenza-Like Illness (ILI) cases; these reports are authoritative but typically have a delay of one to two weeks due to the largely manual process. We describe the SNEFT prototype in the context of predicting ILI cases well in advance of the CDC reports. We observe that OSN data is individually noisy but collectively revealing, and speculate on other applications that can potentially be enabled by OSN data collection and analysis.

BACKGROUND
Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose.

OBJECTIVE
The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research.

METHODS
We performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals.

RESULTS
The initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis.

CONCLUSIONS
Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques.

User generated content on the microblogging social network Twitter continues to grow with significant amount of information. The semantic analysis offers the opportunity to discover and model latent interests’ in the users’ publications. This article focuses on the problem of uncertainty in the users’ publications that has not been previously treated. It proposes a new approach for users’ interest discovery from uncertain information that augments traditional methods using possibilistic logic. The possibility theory provides a solid theoretical base for the treatment of incomplete and imprecise information and inferring the reliable expressions from a knowledge base. More precisely, this approach used the product-based possibilistic network to model knowledge base and discovering possibilistic interests. DBpedia ontology is integrated into the interests’ discovery process for selecting the significant topics. The empirical analysis and the comparison with the most known methods proves the significance of this approach.

Employees increasingly are expressing ideas and feelings through enterprise social media. Recent work in CHI and CSCW has applied linguistic analysis towards understanding employee experiences. In this paper, we apply dictionary based linguistic analysis to measure 'Employee Engagement'. Employee engagement is a measure of employee willingness to apply discretionary effort towards organizational goals, and plays an important role in organizational outcomes such as financial or operational results. Organizations typically use surveys to measure engagement. This paper describes an approach to model employee engagement based on word choice in social media. This method can potentially complement surveys, thus providing more real-time insights into engagement and allowing organizations to address engagement issues faster. Our results predicting engagement scores on a survey by combining demographics with social media text demonstrate that social media text has significant predictive power compared to demographic data alone. We also find that engagement may be a state than a stable trait since social media posts closer to the administration of the survey had the most predictive power. We further identify the minimum number of social media posts required per employee for the best prediction.

Social network sites (SNSs) provide a new way to organize and navigate an egocentric social network. Are they a fad, briefly popular but ultimately useless? Or are they the harbingers of a new and more powerful social world, where the ability to maintain an immense network—a social "supernet"—fundamentally changes the scale of human society? This article presents signaling theory as a conceptual framework with which to assess the transformative potential of SNSs and to guide their design to make them into more effective social tools. It shows how the costs associated with adding friends and evaluating profiles affect the reliability of users' self-presentation; examines strategies such as information fashion and risk-taking; and shows how these costs and strategies affect how the publicly-displayed social network aids the establishment of trust, identity, and cooperation—the essential foundations for an expanded social world. Grooming, Gossip, and Online Friending Social ties provide many benefits, including companionship, access to information, and emotional and material support (Granovetter, 1983; Wellman, Garton, & Haythornthwaite, 1997; Wellman & Gulia, 1999). Increasing the number of ties increases access to these benefits, although time and cognitive constraints preclude indefinite expansions of one's personal network. Yet if maintaining ties were to become more temporally efficient and cognitively effective, it should be possible to increase the scale of one's social world—to create a "supernet" with many more ties than is feasible without socially assistive tools. The question this article addresses is whether social network sites (SNSs) are a technology that can bring this about. In the wild, apes groom each other, picking through fur to remove parasitic bugs. This behavior helps with hygiene and is relaxing and pleasant for the recipient. Perhaps most importantly, it establishes social bonds: Apes who groom each other are more likely to help each other and not fight. Long grooming sessions are time consuming, however. Since the ape must also spend many hours finding food, sleeping, etc., it is clear that grooming can sustain only a limited number of relationships (Dunbar, 1996). In Grooming, Gossip, and the Evolution of Language, Robin Dunbar (1996) argued eloquently that in human societies, language, especially gossip, has taken over the social function of grooming. Instead of removing lice from each other's hair, people check in with friends and colleagues, ask how they are doing, and exchange a few words about common acquaintances, the news, or the local sports team (Dunbar, 1996, 2004). Language is much more efficient than physical grooming, for one can talk to several people at once. Language also helps people learn about cultural norms, evaluate others' behavior, and keep up with the news and shifting opinions of their surrounding community. It makes reputation possible—individuals benefit from the experience of others in determining who is nice, who does good Signals in Social Supernets http://jcmc.indiana.edu/vol13/issue1/donath.html 2 of 19 4/7/2008 6:26 PM work, and who should be shunned for their dishonest ways. Using language to maintain ties and manage trust, people can form and manage more complex and extensive social networks.1 Communication technologies expand human social reach (Horrigan, Boase, Rainie, & Wellman, 2006). Email makes communication more efficient: Sending a message to numerous recipients is as easy as sending it to one, and its asynchrony means that there is little need to coordinate interaction. Contact management tools, from paper Rolodexes to complex software systems, increase one's ability to remember large numbers of people (Whittaker, Jones, & Terveen 2002). While these technologies provide some of the support an expanded social world needs, they alone are not sufficient. People need to be able to keep track of ever-changing relationships (Dunbar, 1996; Nardi, Whittaker, Isaacs, Creech, Johnson, & Hainsworth, 2002), to see people within the context of their social relationships (Raub & Weesie, 1990), and, most fundamentally, to know whom to trust (Bacharach & Gambetti, 2001; Good, 2000). Email and contact tools help maintain an expanded collection of individual relationships. Are social network sites the solution for placing these relationships into the greater social context? A page on MySpace, filled with flashing logos, obscure comments, poorly focused yet revealing photos, and laced with twinkling animated gifs, may not look to the casual observer like the harbinger of the next stage in human social evolution. But perhaps it is. SNSs locate people in the context of their acquaintances, provide a framework for maintaining an extensive array of friends and other contacts, and allow for the public display of interpersonal commentary (boyd & Ellison, this issue). At the same time, SNSs are still primitive; it is too early in their development to observe clear evidence that they have transformed society. The goal of this article is to present a theoretical framework with which to a) assess the transformative potential of SNSs and b) develop design guidelines for making them into more effective social tools. The foundation for this analysis is signaling theory, which models why some communications are reliably honest and others are not. The argument begins with an introduction to signaling theory. The next section uses this theory to examine how the fundamental structure of SNSs can bring greater trust and reliability to online self-presentations, how specific site design decisions enhance or weaken their trust-conferring ability, and how seemingly pointless or irrational behaviors, such as online fashion and risk taking, actually signal social information. The final section examines the transformative possibilities of social supernets—not only whether SNSs may bring them about, but if so, in what ways they might change our society. An emphasis of this article is on ways of achieving reliable information about identity and affiliations. There are situations where ephemeral, hidden, or multiple identities are desirable. However, minimal online identity has been easy to create, while it is harder to establish more grounded identities in a fluid and nuanced way. A primary goal of this article is to understand how reliability is encouraged or enforced. For designers of future systems such knowledge is a tool, not a blueprint. Depending on the situation, they should choose the appropriate space between anonymous and whimsical and verified and trustworthy identities and communication.

System dynamics depends heavily upon quantitative data to generate feedback models. Qualitative data and their analysis also have a central role to play at all levels of the modeling process. Although the classic literature on system dynamics strongly supports this argument, the protocols to incorporate this information during the modeling process are not detailed by the most influential authors. Data gathering techniques such as interviews and focus groups, and qualitative data analysis techniques such as grounded theory methodology and ethnographic decision models could have a strong, critical role in rigorous system dynamics efforts. This paper describes some of the main qualitative, social science techniques and explores their suitability in the different stages of the modeling process. Additionally, the authors argue that the techniques described in the paper could contribute to the understanding of the modeling process, facilitate

Social media constitute a challenging new source of information for intelligence gathering and decision making. Twitter is one of the most popular social media sites and often becomes the primary source of information. Twitter messages are short and well suited for knowledge discovery. Twitter provides both researchers and practitioners a free Application Programming Interface (API) which allows them to gather and analyse large data sets of tweets. Twitter information aren't solely tweet texts, as Twitter’s API provides a lot of info to perform attention-grabbing analysis studies. The paper concisely describes method of knowledge gathering and therefore the main areas of knowledge mining, information discovery and information visual image from Twitter information. In this paper we can create a twitter app from which we can fetch the real time twitter tweets on a particular topic and stored it into R and then we can apply several text mining steps on the tweets to pre-process the tweets text and than we


Question: Characteristics of a MVC (Model View Controller) architecture web application created using PHP and .NET framework.

This study explores the utilization of design patterns in PHP-based web application frameworks, highlighting the role they play in object-oriented programming for web development. Despite the widespread use of design patterns, there is a notable gap in understanding regarding which patterns are predominantly used, their frequency of application, and the quality of their implementation. To address this, an in-depth analysis was conducted on the documentation and source code of ten PHP-based web application frameworks. The findings revealed that while design patterns are indeed employed in web application development, their usage is not extensive and lacks uniformity. These insights are invaluable for project planning and development, as they allow for the incorporation of past experiences. Additionally, the study identifies design patterns that are either underutilized or avoided altogether, possibly due to their complexity or perceived irrelevance in practical scenarios. This information can aid developers in broadening their knowledge and making more informed decisions about pattern usage in future projects.

Three core imperatives are essential for modern businesses and organizations: seamless integration of customer and operational processes, agility, and the ability to change. These imperatives are thus relevant in view of successfully executing strategic choices, but all too often not satisfied. Businesses and organizations can be viewed as complex adaptive socio-technical systems. Two fundamentally different perspectives on systems play a role: the functional (black-box) perspective and the constructional (white-box) perspective. Management and governance of businesses and organizations regard the functional, black-box perspective, which is inherently ill-suited for addressing the imperatives mentioned. Rather, establishing system integration, agility and change requires a focus on the system’s design, hence entails the constructional perspective. Both perspectives are relevant. The concept of architecture plays a fundamental role for operationalizing the constructional perspective. Next to the more familiar notion of technology architecture, the concepts of business and organizational architecture are formally introduced and elucidated. In view of the important role of information in customer and operational processes, the notion of information architecture will be additionally discussed, specifically the relationships with other architectures. Various domains within these architectures will be highlighted, whereby the importance of coherence and consistency is stressed, especially in view of the ability to change. Collectively, the four architectures are labeled Enterprise Architecture. Finally, enterprise architecture will be positioned as a crucial means for linking strategy development and execution. The functional and constructional perspective Function and construction A system may be defined as an identifiable bounded set of functionally and/or methodically related elements or principles with a certain operational purpose. Within this definition, a plethora of systems can be mentioned: a payment system, an accounting system, a transport

Website phishing is considered one of the crucial security challenges for the online community due to the massive numbers of online transactions performed on a daily basis. Website phishing can be described as mimicking a trusted website to obtain sensitive information from online users such as usernames and passwords. Black lists, white lists and the utilisation of search methods are examples of solutions to minimise the risk of this problem. One intelligent approach based on data mining called Associative Classification (AC) seems a potential solution that may effectively detect phishing websites with high accuracy. According to experimental studies, AC often extracts classifiers containing simple ‘‘If-Then’’ rules with a high degree of predictive accuracy. In this paper, we investigate the problem of website phishing using a developed AC method called Multi-label Classifier based Associative Classification (MCAC) to seek its applicability to the phishing problem. We also want to identify features that distinguish phishing websites from legitimate ones. In addition, we survey intelligent approaches used to handle the phishing problem. Experimental results using real data collected from different sources show that AC particularly MCAC detects phishing websites with higher accuracy than other intelligent algorithms. Further, MCAC generates new hidden knowledge (rules) that other algorithms are unable to find and this has improved its classifiers predictive performance. 2014 Elsevier Ltd. All rights reserved.

The LLVM Compiler Infrastructure (http://llvm.cs. uiuc.edu) is a robust system that is well suited for a wide variety of research and development work. This brief paper introduces the LLVM system and provides pointers to more extensive documentation, complementing the tutorial presented at LCPC. 1 Brief Overview and Goals The LLVM Compiler Infrastructure [2] is a language and target-independent compiler system, designed for both static and dynamic compilation. LLVM (Low Level Virtual Machine) can be used to build both traditional optimizing compilers for high performance programming languages as well as compiler-based tools such as Just-In-Time (JIT) translators, profilers, binary translators, memory sandboxing tools, static analysis tools, and others. A major goal of the LLVM development community is to provide a fast, robust, and well-documented core framework to support high-quality compilers and tools. A second major goal is to develop a broad community of contributors to ensure that the software continues to grow and be relevant, and to maintain its robustness and quality. A third goal is to provide a flexible infrastructure for new compiler development and research. 2 Key LLVM Design Features The LLVM system has three main components: the LLVM Virtual Instruction Set, a collection of reusable libraries for analysis, transformation and code generation; and tools built from these libraries. The LLVM framework is characterized by a clean, simple, and modular design, which allows new users to understand the representation, write new analyses, transformations, and tools easily. The LLVM Virtual Instruction Set is the common intermediate representation shared by all of the LLVM subsystems. It is a simple, mid-level, threeaddress code representation that is designed to be both language-independent and target-independent [1]. The instruction set provides explicit control-flow graphs, explicit dataflow information (in SSA form), and a mid-level, language R. Eigenmann et al. (Eds.): LCPC 2004, LNCS 3602, pp. 15–16, 2005. c © Springer-Verlag Berlin Heidelberg 2005 16 C. Lattner and V. Adve independent type system. The type system is rich enough to support sophisticated, language-independent compiler techniques, including pointer analysis, dependence analysis, and interprocedural dataflow analyses, and transformations based on them. Exactly the same instruction set is used both as a persistent, external representation for compiled code and as the internal representation for all mid-level compiler passes. Making this representation persistent enables all LLVM passes to be used at compile-time, link-time, load-time, run-time, and “idle-time” (between program runs). The key design features and the innovative aspects of the code representation are are described in a paper [2], and the complete instruction set is described in an online reference manual [1]. The LLVM source base mostly consists of modular and reusable libraries. These components include analyses and optimizations, native code generators, JIT compiler support, profile-guided feedback, etc. These compiler components reduce the cost and difficulty of building compilers for new platforms, new source languages, and for building new kinds of tools (debuggers, profilers, etc). The LLVM system also includes several complete tools built from these components, including an ANSI-conforming C/C++ compiler (which uses the GNU Compiler Collection (GCC) parsers). The C/C++ compiler applies a large number of module-level (compile-time) and cross-module (link-time) optimizations. Other LLVM tools include programs to manipulate the IR (e.g. convert between ASCII and binary formats, extract functions from a program, etc), a modular optimizer (which can run any LLVM optimization on an program, driven from the command line), automated compiler debugging tools, and others.

E-learning is the synthesis of multimedia and social media platforms powered by Internet and mobile technologies. Great popularity of e-learning is encouraging governments and educational institutions to adopt and develop e-learning cultures in societies in general and universities in particular. In traditional e-learning systems, all components (agents and services) are tightly coupled into a single system. In this study, we propose a new architecture for e-learning with two subsystems, namely, e-learning and e-testing. The motivation of the research is to improve the effectiveness of the learning process by extracting relevant features for elastic learning and testing process. We employ a multi-agent system because it contains five-layer architecture, including agents at various levels. We also propose a novel method for updating content through question and answer between e-learners and intelligent agents. To achieve optimization, we design a system that applies various technologies, which M. Arif (B)· A. Karim · K. A. Alam · S. Farid · S. Iqbal Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia e-mail: arifmuhammad36@siswa.um.edu.my M. Arif · M. Illahi Departmnet of Computer Science, COMSATS Institute of Information Technology Islamabad, Islamabad, Pakistan S. Shamshirband Faculty of Computer Science and Information Technology, Department of Computer System and Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia e-mail: shamshirband1396@gmail.com S. Shamshirband Department of Computer Science, Chalous Branch, Islamic Azad University (IAU), Chalous, 46615-397 Mazandaran, Iran Z. Buang Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia V. E. Balas Department of Automation and Applied Informatics, University of Arad, 310130 Arad, Romania

Customer-centric Web-based systems, such as ecommerce Web sites, or sites that support customer relationship management (CRM) activities, are themselves information systems, but their design and maintenance need to follow vastly different approaches from the traditional systems lifecycle approach. Based on marketing frameworks that are applicable to the online world, and following design science principles, we develop a model to guide the design and the continuous management of such sites. The model makes extensive use of current technologies for tracking the customers and their behaviors, and combines elements of data mining and statistical analyses. A case study based on a financial services Web site is used to provide a preliminary validation and design evaluation of our approach. The case study showed considerable measured improvement in the effectiveness of the companys Web site. In addition, it also highlighted an important benefit of the our approach: the identification of previously unknown or unexpected segments of visitors. This finding can lead to promising new business opportunities.

WordPress is a powerful and extensible platform for webbased information publishing and management. While the WordPress core is targeted to the publication of chronologically ordered textual articles typical of blogs, users have developed plugins as well as themes to support the data management requirements of specific domains such as e-commerce or e-learning. However, the creation of such plugins requires development skills and effort. We present a meta-plugin that automatically generates bespoke plugins for data management based on user-defined ER models. We illustrate the approach using an example of creating a WordPress site for managing information about courses.

Many would argue that future breakthroughs in software productivity will depend on our ability to combine existing pieces of software to produce new applications. An important step towards this goal is the development of new techniques to detect and cope with mismatches in the assembled parts. Some problems of composition are due to low-level issues of interoperability, such as mismatches in programming languages or database schemas. However, in this paper we highlight a different, and in many ways more pervasive, class of problem: architectural mismatch. Specifically, we use our experience in building a family of software design environments from existing parts to illustrate a variety of types of mismatch that center around the assumptions a reusable part makes about the structure of the application in which is to appear. Based on this experience we show how an architectural view of the mismatch problem exposes some fundamental, thorny problems for software composition and suggests possible research avenues needed to solve them.

Several techniques have been recently proposed to automatically generate Web wrappers, i.e., programs that extract data from HTML pages, and transform them into a more structured format, typically in XML. These techniques automatically induce a wrapper from a set of sample pages that share a common HTML template. An open issue, however, is how to collect suitable classes of sample pages to feed the wrapper inducer. Presently, the pages are chosen manually. In this paper, we tackle the problem of automatically discovering the main classes of pages offered by a site by exploring only a small yet representative portion of it. We propose a model to describe abstract structural features of HTML pages. Based on this model, we have developed an algorithm that accepts the URL of an entry point to a target Web site, visits a limited yet representative number of pages, and produces an accurate clustering of pages based on their structure. We have developed a prototype, which has been used to perform experiments on real-life Web sites. 2004 Elsevier B.V. All rights reserved.

For a complete copy of the book, please visit the MorganKaufmann website or Amazon.com.

ÐSoftware architectures shift the focus of developers from lines-of-code to coarser-grained architectural elements and their overall interconnection structure. Architecture description languages (ADLs) have been proposed as modeling notations to support architecture-based development. There is, however, little consensus in the research community on what is an ADL, what aspects of an architecture should be modeled in an ADL, and which of several possible ADLs is best suited for a particular problem. Furthermore, the distinction is rarely made between ADLs on one hand and formal specification, module interconnection, simulation, and programming languages on the other. This paper attempts to provide an answer to these questions. It motivates and presents a definition and a classification framework for ADLs. The utility of the definition is demonstrated by using it to differentiate ADLs from other modeling notations. The framework is used to classify and compare several existing ADLs, enabling us, in the process, to identify key properties of ADLs. The comparison highlights areas where existing ADLs provide extensive support and those in which they are deficient, suggesting a research agenda for the future. Index TermsÐSoftware architecture, architecture description language, component, connector, configuration, definition, classification, comparison.


Question: Characteristics of MVC (Model View Controller) based web applications developed using PHP and .NET framework.

A PHP FRAMEWORK FOR DATABASE MANAGEMENT UTILIZING THE MVC ARCHITECTURE
PHP, a robust scripting language, excels in developing dynamic and interactive web applications. Among its standout features is the seamless integration and manipulation of databases, facilitated by the provision of specialized functions for database operations. Nonetheless, the intricacies of SQL syntax often pose challenges for less experienced developers. This paper introduces a PHP framework designed to simplify database management, employing the Model-View-Controller (MVC) design pattern. The MVC pattern enhances the architectural clarity of web applications by dividing them into three interconnected components: the model, view, and controller. Our framework encapsulates fundamental database actions—INSERT, UPDATE, DELETE, and SELECT—shielding developers from the complexities of SQL syntax. Instead, they can execute these operations by invoking methods within the model component. To ensure the reliability and accuracy of the model module, we have incorporated White-Box testing for code validation. Furthermore, a practical web application example is provided to demonstrate the workflow and utilization of the proposed PHP framework in a real-world scenario.

**Question**: A Comparative Study on Machine Learning Algorithms for Predicting Financial Market Trends

**Documents**: A COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR FINANCIAL MARKET PREDICTION
The financial market is characterized by high volatility and unpredictability, making accurate prediction a challenging task. This study conducts a comparative analysis of various machine learning algorithms for predicting financial market trends. The algorithms under consideration include Support Vector Machines (SVM), Random Forest, and Neural Networks. Each algorithm is trained on historical financial data, encompassing stock prices, trading volumes, and macroeconomic indicators. Performance is evaluated using metrics such as accuracy, precision, recall, and the F1-score. The results reveal that the Neural Network outperforms the other algorithms in terms of accuracy, with SVM performing well in terms of precision. The study also discusses the limitations of each algorithm and suggests potential improvements. Furthermore, the impact of data preprocessing and feature selection on algorithm performance is investigated.

**Similar Documents**: COMPARATIVE EVALUATION OF MACHINE LEARNING TECHNIQUES IN FINANCIAL MARKET TREND PREDICTION
The financial market, with its inherent volatility and complexity, poses significant challenges for accurate forecasting. This paper presents a detailed comparative evaluation of several machine learning techniques aimed at predicting trends within the financial market. The techniques examined include Support Vector Machines (SVM), Random Forest, and Neural Networks. Each method is trained using a comprehensive dataset that includes historical

Despite the wealth of information contained in the Web of Linked Data, the current limitations and entry barriers of the Semantic Web technologies hinder the users from taking advantage of these information resources. Linked Data visualization can alleviate this problem. In this paper, we adopt a proper Linked Data visualization model, design Linked Data visualization algorithms, and develop a lightweight, easy-to-use prototype tool, LOD Viewer, using the platform independent JavaScript language. LOD Viewer can visualize different sources of RDF data including SPARQL endpoints for Linked Open Data (LOD) sources, and display the data in different graphic illustrations. Our case studies have verified the effectiveness and realizability of the proposed method. The time complexity analysis and experimental test show that the run-time of the proposed algorithms approximately exhibits a linear growth rate as the visualized RDF triples size increases.

Frameworks and libraries offer reusable and customizable functionality through Application Programming Interfaces (APIs). Correctly using large and sophisticated APIs can represent a challenge due to hidden assumptions and requirements. Numerous approaches have been developed to infer properties of APIs, intended to guide their use by developers. With each approach come new definitions of API properties, new techniques for inferring these properties, and new ways to assess their correctness and usefulness. This paper provides a comprehensive survey of over a decade of research on automated property inference for APIs. Our survey provides a synthesis of this complex technical field along different dimensions of analysis: properties inferred, mining techniques, and empirical results. In particular, we derive a classification and organization of over 60 techniques into five different categories based on the type of API property inferred: unordered usage patterns, sequential usage patterns, behavioral specifications, migration mappings, and general information.

Several techniques have been recently proposed to automatically generate Web wrappers, i.e., programs that extract data from HTML pages, and transform them into a more structured format, typically in XML. These techniques automatically induce a wrapper from a set of sample pages that share a common HTML template. An open issue, however, is how to collect suitable classes of sample pages to feed the wrapper inducer. Presently, the pages are chosen manually. In this paper, we tackle the problem of automatically discovering the main classes of pages offered by a site by exploring only a small yet representative portion of it. We propose a model to describe abstract structural features of HTML pages. Based on this model, we have developed an algorithm that accepts the URL of an entry point to a target Web site, visits a limited yet representative number of pages, and produces an accurate clustering of pages based on their structure. We have developed a prototype, which has been used to perform experiments on real-life Web sites. 2004 Elsevier B.V. All rights reserved.

Over the last years, Internet spam content has spread enormously inside web sites mainly due to the emergence of new web technologies oriented towards the online sharing of resources and information. In such a situation, both academia and industry have shown their concern to accurately detect and effectively control web spam, resulting in a good number of anti-spam techniques currently available. However, the successful integration of different algorithms for web spam classification is still a challenge. In this context, the present study introduces WSF2, a novel web spam filtering framework specifically designed to take advantage of multiple classification schemes and algorithms. In detail, our approach encodes the life cycle of a case-based reasoning system, being able to use appropriate knowledge and dynamically adjust different parameters to ensure continuous improvement in filtering precision with the passage of time. In order to correctly evaluate the effectiveness of the dynamic model, we designed a set of experiments involving a publicly available corpus, as well as different simple well-known classifiers and ensemble approaches. The results revealed that WSF2 performed well, being able to take advantage of each classifier and to achieve a better performance when compared to other alternatives. WSF2 is an open-source project licensed under the terms of the LGPL publicly available at https://sourceforge.net/

The adoption of smart phones and the usages of mobile applications are increasing rapidly. Consequently, within limited time-range, mobile Internet usages have managed to take over the desktop usages particularly since the first smart phone-touched application released by iPhone in 2007. This paper is proposed to provide solution and answer the most demandable questions related to mobile application automated and manual testing limitations. Moreover, Mobile application testing requires agility and physically testing. Agile testing is to detect bugs through automated tools, whereas the compatibility testing is more to ensure that the apps operates on mobile OS (Operation Systems) as well as on the different real devices. Moreover, we have managed to answer automated or manual questions through two mobile application case studies MES (Mobile Exam System) and MLM (Mobile Lab Mate) by creating test scripts for both case studies and our experiment results have been discussed and evaluated on whether to adopt test on real devices or on emulators? In addition to this, we have introduced new mobile application testing matrix for the testers and some enterprises to obtain knowledge from.

The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. This paper focuses on online customer reviews of products. It makes two contributions. First, it proposes a novel framework for analyzing and comparing consumer opinions of competing products. A prototype system called Opinion Observer is also implemented. The system is such that with a single glance of its visualization, the user is able to clearly see the strengths and weaknesses of each product in the minds of consumers in terms of various product features. This comparison is useful to both potential customers and product manufacturers. For a potential customer, he/she can see a visual side-by-side and feature-by-feature comparison of consumer opinions on these products, which helps him/her to decide which product to buy. For a product manufacturer, the comparison enables it to easily gather marketing intelligence and product benchmarking information. Second, a new technique based on language pattern mining is proposed to extract product features from Pros and Cons in a particular type of reviews. Such features form the basis for the above comparison. Experimental results show that the technique is highly effective and outperform existing methods significantly.

Web attack detection is the key task for network security. To tackle this hard problem, this paper explores the deep learning methods, and evaluates convolutional neural network, long-short term memory and their combination method. By comparing with the traditional methods, experimental results show that deep learning methods can greatly outperform the traditional methods. Besides, we also analyze the different factors influencing the performance. This work can be a good guidance for researcher to design network architecture and parameters for detecting web attack in practice.

This literature focuses on doing a comparative analysis between Modular Audio Recognition Framework (MARF) and the General Intentional Programming System (GIPSY) with the help of different software metrics. At first, we understand the general principles, architecture and working of MARF and GIPSY by looking at their frameworks and running them in the Eclipse environment. Then, we study some of the important metrics including a few state of the art metrics and rank them in terms of their usefulness and their influence on the different quality attributes of a software. The quality attributes are viewed and computed with the help of the Logiscope and McCabe IQ tools. These tools perform a comprehensive analysis on the case studies and generate a quality report at the factor level, criteria level and metrics level. In next step, we identify the worst code at each of these levels, extract the worst code and provide recommendations to improve the quality. We implement and test some of the metrics which are ranked as the most useful metrics with a set of test cases in JDeodorant. Finally, we perform an analysis on both MARF and GIPSY by doing a fuzzy code scan using MARFCAT to find the list of weak and vulnerable classes.

Workflow management systems, a relatively recent technology, are designed to make work more efficient, integrate heterogeneous application systems, and support interorganizational processes in electronic commerce applications. In this paper, we introduce the field of workflow automation, the subject of this special issue of Information Systems Frontiers. In the first part of the paper, we provide basic definitions and frameworks to aid understanding of workflow management technologies. In the remainder of the paper, we discuss technical and management research opportunities in this field and discuss the other contributions to the special issue.

Due to the increasing amount of Linked Data openly published on the Web, user-facing Linked Data Applications (LDAs) are gaining momentum. One of the major entrance barriers for Web developers to contribute to this wave of LDAs is the required knowledge of Semantic Web (SW) technologies such as the RDF data model and SPARQL query language. This paper presents an adaptive componentbased approach together with its open source implementation for creating flexible and reusable SW interfaces driven by Linked Data. Linked Data-driven (LD-R) Web components abstract the complexity of the underlying SW technologies in order to allow reuse of existing Web components in LDAs, enabling Web developers who are not experts in SW to develop interfaces that view, edit and browse Linked Data. In addition to the modularity provided by the LD-R components, the proposed RDF-based configuration method allows application assemblers to reshape their user interface for different use cases, by either reusing existing shared configurations or by creating their proprietary configurations.


Question: Characteristics of MVC (Model View Controller) based web applications developed using PHP and .NET frameworks.

Exploring the Role of Patterns in Software Engineering and their Application in MVC-based Web Applications

Patterns have proven to be a valuable tool for encapsulating and sharing software design knowledge and experience. Yet, their utility extends beyond software design patterns alone. We argue that patterns are applicable across various stages of software development. This paper delves into the essential facets of the pattern concept, highlighting how patterns interrelate with the diverse models created throughout the software design process. We also examine the structure of patterns and propose how they can be organized into comprehensive collections, akin to pattern handbooks.

Specifically, this paper focuses on the behavior of MVC (Model View Controller) based web applications, developed using popular frameworks such as PHP and .NET. The MVC pattern is pivotal in structuring web applications by dividing the application logic into three interconnected components. We analyze how patterns can enhance the design and development of MVC applications, ensuring robustness, maintainability, and scalability. By understanding the principles and practices associated with patterns, developers can better leverage frameworks like PHP and .NET to create efficient and user-friendly web applications.

This paper also discusses the challenges and considerations when applying patterns in MVC-based web applications, providing insights into best practices for integrating patterns into the software development lifecycle. Through case studies and practical examples, we demonstrate the effectiveness of patterns in addressing common issues encountered in MVC development. Ultimately, our goal is to equip software engineers with a deeper understanding of patterns and their role in creating high-quality web applications.

Today web is the best medium of communication in modern business. Many companies are redefining their business strategies to improve the business output. Business over internet provides the opportunity to customers and partners where their products and specific business can be found. Nowadays online business breaks the barrier of time and space as compared to the physical office. Big companies around the world are realizing that e-commerce is not just buying and selling over Internet, rather it improves the efficiency to compete with other giants in the market. For this purpose data mining sometimes called as knowledge discovery is used. Web mining is data mining technique that is applied to the WWW. There are vast quantities of information available over the Internet.

As the core technology of Web 2.0, Ajax has caught more and more attention. Xml, as the traditional data load format, needs to be resolved by DOM (Document Object Model ) both in client-side and server-side, which wastes system resource and makes a great reduction of user-friendliness. In this paper, a light-weightdata-interchanging format-JSON (Java Script Object Notation) will be introduced, which provides a higher level of flexibility and efficiency. We make a comparison between JSON and XML through expriment, then use JSON as data-transfering format in an actual project. Results show that JSON is more suitable as a data-loading tool for Ajax applications.

This paper discusses a model-based approach to software development. It argues that an approach using models as central development artifact needs to be added to the portfolio of software engineering techniques, to further increase efficiency and flexibility of the development as well as quality and reusability of the results. Two major and strongly related techniques are identified and discussed: Test case modeling and an evolutionary approach to model transformation.

The existence of the enterprise architecture is an attempt of managing and planning over the evolution of information systems in the sphere of an enterprise with model-based. In developing the enterprise architecture, there are several tools definition of components in the system. This tool is known as enterprises architecture (EA) framework. In this paper, we present a method to build a model of enterprise architecture in accordance with the needs of the Organization by Understanding the characteristics of the EA framework such as Zachman, TOGAF, and FEAF. They are selected as the EA framework will be used to determine the characteristics of an EA because the framework is most widely used in corporate or Government. In COBIT 5 framework, there is a process associated with enterprise architecture it is APO03 Manage Enterprise Architecture. At this stage of the research, we describe the link between the characteristics of the EA with one process in COBIT 5 framework. The results contribute to give a recommendation how to design EA for organization based on the characteristic of EA in Context Enterprise Governance using COBIT 5 Framework.

In this paper, the use of systems development as a methodology in information systems (is) research is described and defended. A framework to explain the nature of systems development as a research methodology in is research is proposed. Use of this methodology in the engineering field in general is compared with its use specifically in computer science and computer engineering. An integrated program for conducting IS research that incorporates theory building, systems development, experimentation, and observation is proposed. Progress in several application domains is reviewed to provide a basis upon which to argue that systems development is a valid research methodology. A systems development research process is presented from a methodological perspective. Software engineering, which is the basic method of applying the systems development research methodology, is then discussed. It is the authors' belief that systems development and other research methodologies are complementary and that an integrated multi-dimensional and multimethodological approach will generate fruitful is research results. The premise is that research contributions can result from systems development, experimentation, observation, and performance testing of the systems under development and that all of these research approaches are needed to investigate different aspects of the research question. An earlier version of Ihis paper was originally published in the Proceedings of ihe Twenty-Third Hawaii International Conference on System Sciences (IEEE Computer Society Press, 1990). Journal of Management Information Systems I Winter 1990-91, Vol. 7, No, 3, pp. 89-106. Copyright © M. E. Sharpe, Inc., 1991. 90 NUNAMAKER, CHEN. AND PURDIN

The main objective of this study is to create a fast, easy and an efficient algorithm for disease prediction , with less error rate and can apply with even large data sets and show reasonable patterns with dependent variables. For disease identification and prediction in data mining a new hybrid algorithm was constructed. The Disease Identification and Prediction(DIP) algorithm, which is the combination of decision tree and association rule is used to predict the chances of some of the disease hits in some particular areas. It also shows the relationship between different parameters for the prediction. To implement this algorithm using vb.net software was also developed.

For many years, the IT industry has sought to accelerate the software development process by assembling new applications from existing software assets. However, true component-based reuse of the form Douglas Mcllroy envisaged in the 1960s is still the exception rather than the rule, and most of the systematic software reuse practiced today uses heavyweight approaches such as product-line engineering or domain-specific frameworks. By component, we mean any cohesive and compact unit of software functionality with a well-defined interface - from simple programming language classes to more complex artifacts such as Web services and Enterprise JavaBeans.

Detecting and identifying e-banking Phishing websites is really a complex and dynamic problem involving many factors and criteria. Because of the subjective considerations and the ambiguities involved in the detection, Fuzzy Data Mining Techniques can be an effective tool in assessing and identifying e-banking phishing websites since it offers a more natural way of dealing with quality factors rather than exact values. In this paper, we present novel approach to overcome the „fuzziness‟ in the e-banking phishing website assessment and propose an intelligent resilient and effective model for detecting e-banking phishing websites. The proposed model is based on Fuzzy logic combined with Data Mining algorithms to characterize the e-banking phishing website factors and to investigate its techniques by classifying there phishing types and defining six e-banking phishing website attack criteria‟s with a layer structure. A Case study was applied to illustrate and simulate the phishing process. Our experimental results showed the significance and importance of the e-banking phishing website criteria (URL & Domain Identity) represented by layer one, and the variety influence of the phishing characteristic layers on the final e-banking phishing website rate. KeywordsPhishing, Fuzzy Logic, Data Mining, Classification, association, apriori, e-banking risk assessment

Scrum has become one of the most popular agile methodologies, either alone or combined with other agile practices. Besides, CMMI (Capability Maturity Model Integration) is accepted as a suitable model to measure the maturity of the organizations when developing or acquiring software. Although these two approaches are often considered antagonist, the use of an agile approach to reach certain CMMI maturity levels may result beneficial to organizations that develop Web systems, since they would take the advantages of both approaches. In Web community, this union may be very interesting, because agile approaches fits with the special needs of Web development, and they could be a useful tool for companies getting a certain grade of maturity. This work analyzes the goals of CMMI maturity level 2 and the feasibility of achieving them using the practices proposed by Scrum, trying to assess whether the use of this methodology is suitable for meeting the CMMI generic and specific goals or not. Finally, and based on this analysis, this paper raises a possible extension of Scrum, based on agile techniques, to accommodate the CMMI maturity level 2.

This paper reports on the evaluation of wireless Internet news sites using the WebQual/m instrument. From initial application in the domain of traditional Internet Web sites, the instrument has been adapted for sites delivered using the wireless application protocol (WAP). The WebQual approach is to assess the Web-site quality from the perspective of the 'voice of the customer’, an approach adopted in quality function deployment. The WebQual/m instrument is used to assess customer perceptions of information, site and useroriented qualities. In particular, the qualities of three UK-based WAP news sites are assessed via an online questionnaire. The results are reported and analysed and demonstrate considerable variations in the offerings of the news sites. The findings and their implications for mobile commerce are discussed and some conclusions and directions for further research are provided.


Question: Characteristics of a MVC (Model View Controller) architecture-based web application created using PHP and .NET framework.

In the context of Patterns for Enterprise Application Architecture, the Model-View-Controller (MVC) pattern is a fundamental approach to structuring web applications, particularly those developed using PHP and .NET frameworks. This pattern emphasizes the separation of concerns, dividing the application into three interconnected components: the Model, which represents the data and business logic; the View, which is responsible for the user interface; and the Controller, which manages the application's flow and user input. By adhering to the MVC pattern, developers can create more maintainable and scalable applications.

Consider the example of a `PersonMapper` class, which demonstrates how to separate data access logic from the domain model. The `doInsert` method within `PersonMapper` is responsible for inserting a `DomainObject` into the database using a prepared statement. The SQL insert statement is defined in the `insertStatement` method, tailored specifically for the `people` table. When inserting a `Person` object, the `doInsert` method sets the relevant fields—last name, first name, and number of dependents—into the prepared statement.

To further illustrate the MVC pattern, consider the technique of Separated Interfaces, which allows domain objects to invoke finder behavior. By separating finder interfaces from the mappers, as shown in Figure 10.5, the domain layer can access finder methods without direct knowledge of the underlying data access logic. This separation can be achieved by placing finder interfaces in a separate package that's visible to the domain layer or, alternatively, by including them within the domain layer itself. This approach ensures that the domain layer remains decoupled from the persistence layer, promoting a cleaner architecture and easier maintenance.

In summary, the MVC pattern, when applied to web applications developed using PHP and .NET, facilitates a clear separation of concerns, making it easier to manage and scale the application. The use of Separated Interfaces in conjunction with the MVC pattern further enhances the architecture by cleanly separating finder behavior from the domain logic, leading to a more robust and maintainable design.

The "Internet of Things"(IoT) opens opportunities for devices and softwares to share information on an unprecedented scale. However, such a large interconnected network poses new challenges to system developers and users. In this article, we propose a layered architecture of IoT system. Using this model, we try to identify and assess each layer's challenges. We also discuss several existing technologies that can be used make this architecture secure.

Combinatorial Interaction Testing (CIT) is important because it tests the interactions between the many parameters that make up the configuration space of software systems. We apply this testing paradigm to a Python-based framework for rapid development of webbased applications called Django. In particular, we automatically create a CIT model for Django website configurations and run a state-of-the-art tool for CIT test suite generation to obtain sets of test configurations. Our automatic CIT-based approach is able to efficiently detect invalid configurations.

Work on designing and implementing a patient-centric, personal health record cloud platform based on open-source Indivo X system. We adopt cipher text-policy attribute-based encryption to provide privacy protection and fine-grained access control.

Arabic Optical Character Recognition (OCR) as Web Services represents a major challenge for handwritten document recognition. A variety of approaches, methods, algorithms and techniques have been proposed in order to build powerful Arabic OCR web services. Unfortunately, these methods could not succeed in achieving this mission in case of large large quantity Arabic handwritten documents. Intensive experiments and observations revealed that some of the existing approaches and techniques are complementary and can be combined to improve the recognition rate. Designing and implementing these recent sophisticated complementary approaches and techniques as web services are commonly complex; they require strong computing power to reach an acceptable recognition speed especially in case of large quantity documents. One of the possible solutions to overcome this problem is to benefit from distributed computing architectures such as cloud computing. This paper describes the design and implementation of Arabic Handwriting Recognition as a web service (AHRweb service) based on the complementary approach K-Nearest Neighbor (KNN) /Support Vector Machine (SVM) (K-NN/SVM) via Amazon Elastic MapReduce (EMR) model. The experiments were conducted on a cloud computing environment with a real large scale handwriting dataset from the Institute for Communications Technology (IFN)/ Ecole Nationale d’Ingénieur de Tunis (ENIT) IFN/ENIT database. The J-Sim (Java Simulator) was used as a tool to generate and analyze statistical results. Experimental results show that Amazon Elastic MapReduce (EMR) model constitutes a very promising framework for enhancing large AHRweb service performances.

The COCOMO II model was created to meet the need for a cost model that accounted for future software development practices. This resulted in the formulation of three submodels for cost estimation, one for composing applications, one for early lifecycle estimation and one for detailed estimation when the architecture of the product is understood. This paper describes the calibration procedures for the last model, Post-Architecture COCOMO II model, from eighty-three observations. The results of the multiple regression analysis and their implications are discussed. Future work includes further analysis of the PostArchitecture model, calibration of the other models, derivation of maintenance parameters, and refining the effort distribution for the model output.

After a period where implementation speed was more important than integration, consistency and reduction of complexity, architectural considerations have become a key issue of information management in recent years again. Enterprise architecture is widely accepted as an essential mechanism for ensuring agility and consistency, compliance and efficiency. Although standards like TOGAF and FEAF have developed, however, there is no common agreement on which architecture layers, which artifact types and which dependencies constitute the essence of enterprise architecture. This paper contributes to the identification of essential elements of enterprise architecture by (1) specifying enterprise architecture as a hierarchical, multilevel system comprising aggregation hierarchies, architecture layers and views, (2) discussing enterprise architecture frameworks with regard to essential elements, (3) proposing interfacing requirements of enterprise architecture with other architecture models and (4) matching these findings with current enterprise architecture practice in several large companies.

The properties of clouds -- elasticity, pay-per-use, and standardization of the runtime infrastructure -- enable cloud providers and users alike to benefit from economies of scale, faster provisioning times, and reduced runtime costs. However, to achieve these benefits, application architects and developers have to respect the characteristics of the cloud environment.
 To reduce the complexity of cloud application architectures, we propose a pattern-based approach for cloud application design and development. We defined a pattern format to describe the principles of cloud computing, available cloud offerings, and cloud application architectures. Based on this format we developed an architectural pattern language of cloud-based applications: through interrelation of patterns for cloud offering descriptions and cloud application architectures, developers are guided during the identification of cloud environments and architecture patterns applicable to their problems. We cover the proceeding how we identified patterns in various information sources and existing productively used applications, give an overview of previously discovered patterns, and introduce one new pattern. Further, we propose a framework for the organizations of patterns and the guidance of developers during pattern instantiation.

Why VRML and Java together? Over 20 million VRML browsers have been shipped with Web browsers, making interactive 3D graphics suddenly available for any desktop. Java adds complete programming capabilities plus network access, making VRML fully functional and portable. This is a powerful new combination, especially as ongoing research shows that VRML plus Java provide extensive support for building large-scale virtual environments (LSVEs). This article provides historical background, a detailed overview of VRML 3D graphics, sample VRML-Java test programs, and a look ahead at future work.

Software integration is still a challenging and time consuming task and therefore a major part of the development of industrial and domestic service robot applications. The presented toolchain BRIDE is able to streamline this process by the separation of user roles and the separation of developer concerns of software components to ensure a frame-work independent implementation. The impact of the BRIDE toolchain in the development process is demonstrated in a case study on the SyncMM mobile manipulation control framework.

Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the dataset, the specific tools used and the 'mashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here.


Question: Characteristics of MVC (Model View Controller) based web applications developed using PHP and .NET framework.

This paper explores the development of a PHP framework grounded in the Model-View-Controller (MVC) design pattern, addressing the challenges posed by the unstructured nature of conventional PHP web development. Traditionally, PHP development lacks a clear structure, leading to an amalgamation of data access, business logic processing, and presentation layer code, which introduces complexities and hinders the evolution of web applications. To tackle these issues, we propose the Framework Development for PHP (FDF), a robust PHP framework designed specifically for MVC enthusiasts. FDF streamlines web application development by distinctly separating data, view, and control components, facilitating a loosely coupled architecture. This separation not only boosts the efficiency and reliability of the development process but also enhances maintainability and scalability, making it a valuable tool for developers seeking to keep pace with the rapid advancements in web technology. By adopting the FDF framework, developers can enjoy a more organized, flexible, and future-proof approach to building PHP-based web applications.

In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching. 2007 Elsevier Ltd. All rights reserved.

With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems architecture by creating a d e scriptive framework from disciplines quite independent of information systems, then by analogy specifies information systems architecture based upon the neutral , objective framework. Also, some preliminary conclusions about the implications of the resultant descriptive framework are drawn. The discussion is limited to architecture and does not include a strategic planning methodology. T he subject of information systems architecture is beginning to receive considerable attention. The increased scope of design and levels of complexity of information systems implementations are forcing the use of some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. Thirty years ago this issue was not at all significant because the technology itself did not provide for either breadth in scope or depth in complexity in information systems. The inherent limitations of the then-available 4K machines, for example, constrained design and necessitated suboptimal approaches for automating a business. Current technology is rapidly removing both conceptual and financial constraints. It is not hard to speculate about, if not realize, very large, very complex systems implementations, extending in scope and complexity to encompass an entire enterprise. One can readily delineate the merits of the large, complex, enterprise-oriented approaches. Such systems allow flexibility in managing business changes and coher-ency in the management of business resources. However , there also is merit in the more traditional, smaller, suboptimal systems design approach. Such systems are relatively economical, quickly implemented , and easier to design and manage. In either case, since the technology permits " distributing " large amounts of computing facilities in small packages to remote locations, some kind of structure (or architecture) is imperative because decentralization without structure is chaos. Therefore, to keep the business from disintegrating, the concept of information systems architecture is becoming less an option and more a necessity for establishing some order and control in the investment of information systems resources. The cost involved and the success of the business depending increasingly on its information systems require a disciplined approach to the management of those systems. On the assumption that an understanding of information systems architecture …

This paper proposes a hierarchical Software-Defined Networking (SDN) Multi-Domain Orchestration and Control architectural framework to address complex multi-tier governance domain deployments by Carriers, Service Providers (SP), Cloud Service Providers (CSP), large Enterprises, and Network Functions Virtualization (NFV) Infrastructure/Platform as a Service (NFVIaaS/NFVPaaS) providers. The proposed framework allows for simpler networking control and orchestration, more agile development processes, accelerated pace of innovation, and increased speed of deployment, while improving scalability and configuration automation as compared to existing frameworks.

This paper presents a study of the characteristics of viable business models in the field of Mobile Commerce (m-commerce). Mobility has given new dimensions to the way commerce works. All over the world various stakeholder organisations are consistently probing into the areas where m-commerce can be exploited and can generate revenue or value for them, even though some of those implementations are making the business environment more complex and uncertain. This paper proposes a viable business model evaluation framework, based on the VISOR model, which helps in determining the sustainability capabilities of a business model. Four individual cases were conducted with diverse organisations in the Information Technology sector. The four cases discussed dealt with mobile business models and the primary data was collected via semi structured interviews, supplemented by an extensive range of secondary data. A cross-case comparative data analysis was used to review the patterns of different viable business components across the four cases and, finally, the findings and conclusions of the study are presented.

Web application security scanners are a compilation of various automated tools put together and used to detect security vulnerabilities in web applications. Recent research has shown that detecting stored SQL injection, one of the most critical web application vulnerabilities, is a major challenge for black-box scanners. In this paper, we evaluate three state of art black-box scanners that support detecting stored SQL injection vulnerabilities. We developed our custom test bed that challenges the scanners capability regarding stored SQL injections. The results show that existing vulnerabilities are not detected even when these automated scanners are taught to exploit the vulnerability. The weaknesses of black-box scanners identified reside in many areas: crawling, input values and attack code selection, user login, analysis of server replies, miss-categorization of findings, and the automated process functionality. Because of the poor detection rate, we discuss the different phases of black-box scanners' scanning cycle and propose a set of recommendations that could enhance the detection rate of stored SQL injection vulnerabilities.

Rich client-side applications written in HTML5 proliferate diverse platforms such as mobile devices, commodity PCs, and the web platform. These client-side HTML5 applications are increasingly accessing sensitive data, including users’ personal and social data, sensor data, and capability-bearing tokens. To fulfill their security and privacy guarantees, these applications need to maintain certain data-confinement invariants. These invariants are not explicitly stated in today’s HTML5 applications and are enforced using ad-hoc mechanisms. The complexity of web applications, coupled with hard-to-analyze client-side languages, leads to low-assurance data-confinement mechanisms in which the whole application needs to be in the TCB to ensure data-confinement in-

Although web services are becoming business-critical components, they are often deployed with critical software bugs that can be maliciously explored. Web vulnerability scanners allow detecting security vulnerabilities in web services by stressing the service from the point of view of an attacker. However, research and practice show that different scanners have different performance on vulnerabilities detection. In this paper we present an experimental evaluation of security vulnerabilities in 300 publicly available web services. Four well known vulnerability scanners have been used to identify security flaws in web services implementations. A large number of vulnerabilities has been observed, which confirms that many services are deployed without proper security testing. Additionally, the differences in the vulnerabilities detected and the high number of false-positives (35% and 40% in two cases) and low coverage (less than 20% for two of the scanners) observed highlight the limitations of web vulnerability scanners on detecting security vulnerabilities in web services.

Web services based on the service-oriented architecture framework provide a suitable technical foundation for making business processes accessible within enterprises and across enterprises. But to appropriately support dynamic business processes and their management, more is needed, namely, the ability to prescribe how Web services are used to implement activities within a business process, how business processes are represented as Web services, and also which business partners perform what parts of the actual business process. In this paper, the relationship between Web services and the management of business processes is worked out and presented in a tutorial-like manner.

Web pages often contain clutter (such as unnecessary images and extraneous links) around the body of an article that distracts a user from actual content. Extraction of “useful and relevant” content from web pages has many applications, including cell phone and PDA browsing, speech rendering for the visually impaired, and text summarization. Most approaches to making content more readable involve changing font size or removing HTML and data components such as images, which takes away from a webpage’s inherent look and feel. Unlike “Content Reformatting,” which aims to reproduce the entire webpage in a more convenient form, our solution directly addresses “Content Extraction.” We have developed a framework that employs an easily extensible set of techniques. It incorporates advantages of previous work on content extraction. Our key insight is to work with DOM trees, a W3C specified interface that allows programs to dynamically access document structure, rather than with raw HTML markup. We have implemented our approach in a publicly available Web proxy to extract content from HTML web pages. This proxy can be used both centrally, administered for groups of users, as well as by individuals for personal browsers. We have also, after receiving feedback from users about the proxy, created a revised version with improved performance and accessibility in mind.

This paper presents the design and implementation of a Java-based automation system that can monitor and control home appliances via the World Wide Web. The design is based on a stand alone embedded system board integrated into a PC-based server at home. The home appliances are connected to the input/output ports of the embedded system board and their status are passed to the server. The monitoring and control software engine is based on the combination of JavaServer pages, JavaBeans, and interactive C. The home appliances can be monitored and controlled locally via the embedded system board, or remotely through a Web browser from anywhere in the world provided that an Internet access is available. The system is scalable and allows multi-vendor appliances to be added with no major changes to its core. Password protection is used to block unauthorized users from accessing the appliances at home. If the Internet connection is down or the server is not up, the embedded system board still can control and operate the appliances locally.