Question: In-process X-ray visualization of defect and molten pool behavior during laser additive manufacturing

This article offers an extensive review of metal additive manufacturing (AM), a cutting-edge technology that is also known by various names such as direct digital manufacturing, free form fabrication, or 3D printing. The review provides a comprehensive perspective on the current status and rapid advancements in metallic AM. AM holds the promise to fundamentally transform the worldwide landscape of parts manufacturing and logistics. It facilitates localized production and on-demand part creation, with the potential to cut costs, lower energy use, and minimize environmental impact. The paper delves into the material science, manufacturing processes, and commercial aspects essential for harnessing these advantages. It is concluded that a fundamental change in approach is necessary to fully capitalize on the potential of AM.

The paper emphasizes the importance of understanding the material science behind AM processes, as well as the various techniques used in metal additive manufacturing. It highlights the need for a holistic approach that considers the environmental and economic benefits of AM, alongside its technical capabilities. By fostering a new mindset, the manufacturing industry can unlock the full potential of AM, leading to more sustainable and efficient production methods.

In controlled industrial environments, laser triangulation is an effective technique for 3D reconstruction, which is increasingly being used for quality inspection and metrology. In this paper, we propose a method for calibrating a dual laser triangulation system - consisting of a camera, two line lasers, and a linear motion platform designed to perform completeness inspection tasks on an assembly line. Calibration of such a system involves the recovery of two sets of parameters - the plane parameters of the two line lasers, and the translational direction of the linear motion platform. First, we address these two calibration problems separately. While many solutions have been given for the former problem, the latter problem has been largely ignored. Next, we highlight an issue specific to the use of multiple lasers - that small errors in the calibration parameters can lead to misalignment between the reconstructed point clouds of the different lasers. We present two different procedures that can eliminate such misalignments by imposing constraints between the two sets of calibration parameters. Our calibration method requires only the use of planar checkerboard patterns, which can be produced easily and inexpensively.

In this paper, we report a method of low temperature solid diffusion bonding. To investigate bondability of solid diffusion, we examined the effect of bump metals and bump planarization methods. Cu and Au bump were used for bump metals and CMP and ultra-precision cutting were used for bump planarization methods. We found that fine crystal layer could be formed on only cut Cu and Au bumps, and especially cut Cu bumps had a thick fine crystal layer on the surface. The layer on cut Cu bump was found to be easily to recrystallize at low temperature condition of 150 degree C. Moreover, the bonding interface of cut Cu bump disappeared at 200 degree C for 30 min, which means solid diffusion across the interface was realized with the contribution of fine crystal layer. In addition, for Cu-Cu direct bonding, formic acid treatment before bonding is effective because formic acid can react at low temperature without destroying fine crystal layer. That led to achieve high bonding strength between cut Cu bumps.

Field construction can be planned, monitored, and controlled at two distinct levels: 1) the activity or schedule level; and 2) the operation or process level. Graphical 3D visualization can serve as an effective communication method at both levels. Several research efforts in visualizing construction are rooted in scheduling. They typically involve linking activity-based construction schedules and 3D CAD models of facilities to describe discretely-evolving construction “product” visualizations (often referred to as 4D CAD). The focus is on communicating what component(s) are built where and when, with the intention of studying the optimal activity sequence, spatial, and temporal interferences, etc. The construction processes or operations actually involved in building the components are usually implied. A second approach in visualizing construction is rooted in discrete-event simulation that, in addition to visualizing evolving construction products, also concerns the visualization of the operations and processes that are performed in building them. In addition to what is built where and when, the approach communicates who builds it and how by depicting the interaction between involved machines, resources, and materials. This paper introduces the two approaches, and describes the differences in concept, form, and content between activity level and operations level construction visualization. An example of a structural steel framing operation is presented to elucidate the comparison. This work was originally published in the proceedings of the 2002 IEEE Winter Simulation Conference (Kamat and Martinez 2002). This paper expands on the original work, by describing recent advances in both activity and operations level construction visualization.

A low-temperature sintering technique enabled by a nanoscale silver paste has been developed for attaching large-area (>100 mm2) semiconductor chips. This development addresses the need of power device or module manufacturers who face the challenge of replacing lead-based or lead-free solders for high-temperature applications. The solder-reflow technique for attaching large chips in power electronics poses serious concern on reliability at higher junction temperatures above 125°C. Unlike the soldering process that relies on melting and solidification of solder alloys, the low-temperature sintering technique forms the joints by solid-state atomic diffusion at processing temperatures below 275°C with the sintered joints having the melting temperature of silver at 961°C. Recently, we showed that a nanoscale silver paste could be used to bond small chips at temperatures similar to soldering temperatures without any externally applied pressure. In this paper, we extend the use of the nanomaterial to attach large chips by introducing a low pressure up to 5 MPa during the densification stage. Attachment of large chips to substrates with silver, gold, and copper metallization is demonstrated. Analyses of the sintered joints by scanning acoustic imaging and electron microscopy showed that the attachment layer had a uniform microstructure with micrometer-sized porosity with the potential for high reliability under high-temperature applications.

The design of auxetic structures is traditionally based on engineering experience, see, for instance, refs. [1,2]. The goal of this article is to demonstrate how an existing auxetic structure can be improved by structural optimization techniques and manufactured by a selective electron beam melting (SEBM) system. Auxetic materials possess negative Poisson’s ratios ν which is in contrast to almost all engineering materials (e. g. metals ν ≈ 0.3). The negative Poisson’s ratio translates into the unusual geometric effect that these materials expand when stretched and contract when compressed. This behavior is of interest for example for fastener systems and fi lters. [ 2 , 3 ] It also results in interesting mechanical behavior like increased penetration resistance for large negative Poisson’s ratios [ 4 ] and in the case of isotropy for higher shear strength relative to the Young’s modulus [ 2 ] of the structure. The auxetic behavior can always be traced back to complex mesoor microscopic geometric mechanisms, e. g. unfolding of inverted elements or rotation of star shaped rigid units relative to each other. [ 5 – 7 ] These geometries can be realized on vastly different scales from specifi cally designed polymers to reactor cores. [ 2 , 8 ]


Question: Real-time X-ray observation of defect and molten pool behavior in laser-based additive manufacturing processes.

This paper examines the critical measurement science requirements for real-time control in Additive Manufacturing (AM) Powder Bed Fusion (PBF) processes. Despite growing use in product development, AM faces challenges in achieving consistent part quality due to issues with dimensional tolerances, surface finish, and defects, hindering its widespread adoption for high-stakes applications. Current process control, based on heuristic models and empirical data, falls short in significantly enhancing part quality due to inadequate measurement methods. The overarching objective is to develop measurement science capabilities that enable in-process monitoring and real-time control in AM. This necessitates the creation of traceable dimensional and thermal metrology techniques for closed-loop control during AM processes. As a preliminary step, this document offers a comprehensive review of AM control methodologies, process measurements, and modeling techniques, with a focus on PBF, while also considering findings from other AM techniques. The review's purpose is to pinpoint and synthesize the measurement science needs essential for real-time process control. Our research outcomes are structured to reveal the interconnections between process variables, process indicators, and product quality. This report aims to serve as a foundational reference and a centralized resource for our ongoing efforts to identify the most effective measurement methods and relevant measurands for real-time control. Measurement science, in this context, encompasses a broad spectrum of activities, including the development of performance metrics, measurement and testing procedures, predictive models and simulations, knowledge frameworks, protocols, technical data, and reference materials and artifacts. It also involves conducting inter-comparison studies and calibrations, evaluating technologies, systems, and practices with uncertainty analysis, and contributing to the technical foundation for standards, codes, and practices through collaborations with industry, academia, and standards development organizations.

Due to the high costs of 3D-printing infrastructure, outsourcing the production to third parties specializing in 3D-printing process becomes necessary. The integration of a 3D-printing system with networked communications constitutes a cyber-physical system, bringing new security challenges. Adversaries can explore the vulnerabilities of networks to damage the physical parts of the system. In this paper, we explore the vulnerabilities of 3D-printing systems, and design a cross-layer approach for the system. At the physical layer, we use a Markov jump system to model the system and develop a robust control policy to deal with uncertainties. At the cyber-layer, we apply FlipIt game to model the contention between the defender and attacker for the control of the 3D-printing system. To connect these two layers, we develop a Stackelberg framework to capture the interactions between cyber-layer attacker and defender game and the physical-layer controller and disturbance game, and define a new equilibrium concept that captures interdependence of the zero-sum and FlipIt games. We present numerical examples to better understand the equilibria and design defense strategies for 3D printers as a tradeoff between security and robustness.

This paper reports the demonstration of 2-5 µm embedded trench formation in dry film polymer dielectrics such as Ajinomoto build-up film (ABF) and Polyimide without using chemical mechanical polishing (CMP) process. The trenches in these dielectrics were formed by excimer laser ablation, followed by metallization of trenches by copper plating processes and overburden removal with surface planer tool. The materials and processes integrated in this work are scalable to large panel fabrication at much higher throughput, for interposers and high density fan-out packaging at lower cost and higher performance than silicon interposers.


Question: In-line X-ray observation of flaw and liquid pool kinetics in laser-based additive fabrication process.

This paper introduces a novel, unsupervised, and nonparametric method for automatic threshold selection in the context of image segmentation. The proposed technique selects the optimal threshold by optimizing a discriminant criterion, which aims to maximize the separability of the resulting classes in terms of gray levels. The method is characterized by its simplicity, relying solely on the zeroth and first-order cumulative moments of the gray-level histogram for its operation. Moreover, the approach can be easily adapted to handle multithreshold segmentation problems. The effectiveness of the proposed method is substantiated through various experimental results, which confirm its validity and applicability in image segmentation tasks.

**Question**: The effects of temperature and pressure on the performance of a PEM fuel cell

**Documents**: A Study on the Effects of Temperature and Pressure on the Performance of Proton Exchange Membrane Fuel Cells

This study investigates the impact of temperature and pressure on the performance of proton exchange membrane (PEM) fuel cells, which are widely used in various applications due to their high efficiency and environmental friendliness. The performance of a PEM fuel cell is influenced by several factors, including temperature and pressure. In this paper, a detailed analysis is presented to understand how these variables affect the cell's performance. The study involves experimental measurements and theoretical simulations to explore the effects of temperature and pressure on the cell's voltage, current, and power output. The results show that increasing the temperature can enhance the cell's performance by reducing the internal resistance and accelerating the proton transport across the membrane. However, excessively high temperatures can lead to degradation of the membrane and catalysts. Similarly, increasing the pressure can improve the cell's performance by increasing the concentration of reactants at the electrodes, but excessively high pressures can cause mechanical damage to the cell components. The study provides valuable insights into the optimal operating conditions for PEM fuel cells and highlights the need for careful control of temperature and pressure to achieve high performance and durability.

**Similar Documents**: An Examination of Temperature and Pressure Influences on Proton Exchange Membrane Fuel Cell Performance

This research delves into the critical role that temperature and pressure play in the performance of proton exchange membrane (PEM) fuel cells, a technology renowned for its high efficiency and environmental benefits. The performance of PEM fuel cells is contingent upon various parameters, with temperature and pressure being of particular significance. This paper offers a comprehensive analysis to elucidate the mechanisms by which these variables influence the cell's performance. Through a combination of experimental data and theoretical modeling, the investigation explores the effects of temperature and pressure on the fuel cell's voltage

A new iterative maximum-likelihood reconstruction algorithm for X-ray computed tomography is presented. The algorithm prevents beam hardening artifacts by incorporating a polychromatic acquisition model. The continuous spectrum of the X-ray tube is modeled as a number of discrete energies. The energy dependence of the attenuation is taken into account by decomposing the linear attenuation coefficient into a photoelectric component and a Compton scatter component. The relative weight of these components is constrained based on prior material assumptions. Excellent results are obtained for simulations and for phantom measurements. Beam-hardening artifacts are effectively eliminated. The relation with existing algorithms is discussed. The results confirm that improving the acquisition model assumed by the reconstruction algorithm results in reduced artifacts. Preliminary results indicate that metal artifact reduction is a very promising application for this new algorithm.

This paper presents characterization and analysis of liquid crystal polymer materials for microwave and millimeter multi-layer packaging. Processing techniques have been developed to fabricate interconnects on this new LCP material. The experimental results demonstrate that an interconnect on LCP achieves a measured insertion loss of less than 0.1 dB/mm up to 50 GHz. This material is highly suitable for microwave and millimeter wave packaging.

Limitations of current 3D acquisition technology often lead to polygonal meshes exhibiting a number of geometrical and topological defects which prevent them from widespread use. In this paper we present a new method for model repair which takes as input an arbitrary polygonal mesh and outputs a valid two-manifold triangle mesh. Unlike previous work, our method allows users to quickly identify areas with potential topological errors and to choose how to fix them in a userfriendly manner. Key steps of our algorithm include the conversion of the input model into a set of voxels, the use of morphological operators to allow the user to modify the topology of the discrete model, and the conversion of the corrected voxel set back into a two-manifold triangle mesh. Our experiments demonstrate that the proposed algorithm is suitable for repairing meshes of a large class of shapes.

http://dx.doi.org/10.1016/j.displa.2016.07.002 0141-9382/ 2016 Elsevier B.V. All rights reserved. q This paper was recommended for publication by Richard H.Y. So. ⇑ Corresponding author at: University of California, Irvine, 2201 Social & Behavioral Sciences Gateway Building, Irvine, CA 92697-5100, USA. E-mail addresses: mdenniso@uci.edu (M.S. Dennison), awisti@uci.edu (A.Z. Wisti), mdzmura@uci.edu (M. D’Zmura). Mark S. Dennison ⇑, A. Zachary Wisti, Michael D’Zmura

Here we report the first example of a class of additively manufactured carbon fiber reinforced composite (AMCFRC) materials which have been achieved through the use of a latent thermal cured aromatic thermoset resin system, through an adaptation of direct ink writing (DIW) 3D-printing technology. We have developed a means of printing high performance thermoset carbon fiber composites, which allow the fiber component of a resin and carbon fiber fluid to be aligned in three dimensions via controlled micro-extrusion and subsequently cured into complex geometries. Characterization of our composite systems clearly show that we achieved a high order of fiber alignment within the composite microstructure, which in turn allows these materials to outperform equivalently filled randomly oriented carbon fiber and polymer composites. Furthermore, our AM carbon fiber composite systems exhibit highly orthotropic mechanical and electrical responses as a direct result of the alignment of carbon fiber bundles in the microscale which we predict will ultimately lead to the design of truly tailorable carbon fiber/polymer hybrid materials having locally programmable complex electrical, thermal and mechanical response.


Question: In-line X-ray visualization for observing defect and molten pool dynamics during laser additive manufacturing.

This paper presents an innovative method for the additive manufacturing of polymer-derived ceramics, addressing the significant challenges posed by the high melting points of many ceramics. Unlike metals and polymers, ceramics are not easily cast or machined, but 3D printing offers a transformative solution by enhancing geometric versatility. The authors introduce preceramic monomers that can be cured using ultraviolet light in a stereolithography 3D printer or through a patterned mask, resulting in intricate 3D polymer structures with complex shapes and cellular designs. These structures can then be pyrolyzed to convert them into ceramics with uniform shrinkage and negligible porosity. The silicon oxycarbide microlattices and honeycomb cellular materials produced through this technique exhibit superior strength compared to conventional ceramic foams of similar density. The additive manufacturing of these advanced materials holds considerable potential for various applications, including propulsion components, thermal protection systems, porous burners, microelectromechanical systems, and electronic device packaging.

Various new national advanced manufacturing strategies, such as Industry 4.0, Industrial Internet, and Made in China 2025, are issued to achieve smart manufacturing, resulting in the increasing number of newly designed production lines in both developed and developing countries. Under the individualized designing demands, more realistic virtual models mirroring the real worlds of production lines are essential to bridge the gap between design and operation. This paper presents a digital twin-based approach for rapid individualized designing of the hollow glass production line. The digital twin merges physics-based system modeling and distributed real-time process data to generate an authoritative digital design of the system at pre-production phase. A digital twin-based analytical decoupling framework is also developed to provide engineering analysis capabilities and support the decision-making over the system designing and solution evaluation. Three key enabling techniques as well as a case study in hollow glass production line are addressed to validate the proposed approach.

PURPOSE
The problem of metal artifact reduction (MAR) is almost as old as the clinical use of computed tomography itself. When metal implants are present in the field of measurement, severe artifacts degrade the image quality and the diagnostic value of CT images. Up to now, no generally accepted solution to this issue has been found. In this work, a method based on a new MAR concept is presented: frequency split metal artifact reduction (FSMAR). It ensures efficient reduction of metal artifacts at high image quality with enhanced preservation of details close to metal implants.

METHODS
FSMAR combines a raw data inpainting-based MAR method with an image-based frequency split approach. Many typical methods for metal artifact reduction are inpainting-based MAR methods and simply replace unreliable parts of the projection data, for example, by linear interpolation. Frequency split approaches were used in CT, for example, by combining two reconstruction methods in order to reduce cone-beam artifacts. FSMAR combines the high frequencies of an uncorrected image, where all available data were used for the reconstruction with the more reliable low frequencies of an image which was corrected with an inpainting-based MAR method. The algorithm is tested in combination with normalized metal artifact reduction (NMAR) and with a standard inpainting-based MAR approach. NMAR is a more sophisticated inpainting-based MAR method, which introduces less new artifacts which may result from interpolation errors. A quantitative evaluation was performed using the examples of a simulation of the XCAT phantom and a scan of a spine phantom. Further evaluation includes patients with different types of metal implants: hip prostheses, dental fillings, neurocoil, and spine fixation, which were scanned with a modern clinical dual source CT scanner.

RESULTS
FSMAR ensures sharp edges and a preservation of anatomical details which is in many cases better than after applying an inpainting-based MAR method only. In contrast to other MAR methods, FSMAR yields images without the usual blurring close to implants.

CONCLUSIONS
FSMAR should be used together with NMAR, a combination which ensures an accurate correction of both high and low frequencies. The algorithm is computationally inexpensive compared to iterative methods and methods with complex inpainting schemes. No parameters were chosen manually; it is ready for an application in clinical routine.

Convolutional autoencoders have emerged as popular methods for unsupervised defect segmentation on image data. Most commonly, this task is performed by thresholding a per-pixel reconstruction error based on an `-distance. This procedure, however, leads to large residuals whenever the reconstruction includes slight localization inaccuracies around edges. It also fails to reveal defective regions that have been visually altered when intensity values stay roughly consistent. We show that these problems prevent these approaches from being applied to complex real-world scenarios and that they cannot be easily avoided by employing more elaborate architectures such as variational or feature matching autoencoders. We propose to use a perceptual loss function based on structural similarity that examines inter-dependencies between local image regions, taking into account luminance, contrast, and structural information, instead of simply comparing single pixel values. It achieves significant performance gains on a challenging real-world dataset of nanofibrous materials and a novel dataset of two woven fabrics over state-of-the-art approaches for unsupervised defect segmentation that use per-pixel reconstruction

The security infrastructure is ill-equipped to detect and deter the smuggling of non-explosive devices that enable terror attacks such as those recently perpetrated in western Europe. The detection of so-called “small metallic threats” (SMTs) in cargo containers currently relies on statistical risk analysis, intelligence reports, and visual inspection of X-ray images by security officers. The latter is very slow and unreliable due to the difficulty of the task: objects potentially spanning less than 50 pixels have to be detected in images containing more than 2 million pixels against very complex and cluttered backgrounds. In this contribution, we demonstrate for the first time the use of Convolutional Neural Networks (CNNs), a type of Deep Learning, to automate the detection of SMTs in fullsize X-ray images of cargo containers. Novel approaches for dataset augmentation allowed to train CNNs from-scratch despite the scarcity of data available. We report fewer than 6% false alarms when detecting 90% SMTs synthetically concealed in streamof-commerce images, which corresponds to an improvement of over an order of magnitude over conventional approaches such as Bag-of-Words (BoWs). The proposed scheme offers potentially super-human performance for a fraction of the time it would take for a security officers to carry out visual inspection (processing time is approximately 3.5s per container image).

The current lifestyles, increasing population, and limited resources result in energy research being at the forefront of worldwide grand challenges, increasing the demand for sustainable and more efficient energy devices. In this context, additive manufacturing brings the possibility of making electrodes and electrical energy storage devices in any desired three-dimensional (3D) shape and dimensions, while preserving the multifunctional properties of the active materials in terms of surface area and conductivity. This paves the way to optimized and more efficient designs for energy devices. Here, we describe how three-dimensional (3D) printing will allow the fabrication of bespoke devices, with complex geometries, tailored to fit specific requirements and applications, by designing water-based thermoresponsive inks to 3D-print different materials in one step, for example, printing the active material precursor (reduced chemically modified graphene (rCMG)) and the current collector (copper) for supercapacitors or anodes for lithium-ion batteries. The formulation of thermoresponsive inks using Pluronic F127 provides an aqueous-based, robust, flexible, and easily upscalable approach. The devices are designed to provide low resistance interface, enhanced electrical properties, mechanical performance, packing of rCMG, and low active material density while facilitating the postprocessing of the multicomponent 3D-printed structures. The electrode materials are selected to match postprocessing conditions. The reduction of the active material (rCMG) and sintering of the current collector (Cu) take place simultaneously. The electrochemical performance of the rCMG-based self-standing binder-free electrode and the two materials coupled rCMG/Cu printed electrode prove the potential of multimaterial printing in energy applications.

A technology for microelectromechanical systems (MEMS) and microstructure fabrication is introduced where the bulk metallic glass (BMG) is formed at a temperature where the BMG exist as a viscous liquid under an applied pressure into a mold. This thermoplastic forming is carried out under comparable forming pressure and temperatures that are used for plastics. The range of possible sizes in all three dimensions of this technology allows the replication of high strength features ranging from about 30 nm to centimeters with aspect ratios of 20 to 1, which are homogeneous and isotropic and free of stresses and porosity. Our processing method includes a hot-cutting technique that enables a clean planar separation of the parts from the BMG reservoir. It also allows to net-shape three-dimensional parts on the micron scale. The technology can be implemented into conventional MEMS fabrication processes. The properties of BMG as well as the thermoplastic formability enable new applications and performance improvements of existing MEMS devices and nanostructures


Question: Real-time X-ray imaging of defect and molten pool dynamics during laser additive manufacturing process.

This comprehensive review examines the evolution and current state of additive manufacturing (AM) for metals over the past two decades. Initially, AM was confined to 3D printing for rapid prototyping, but it has since advanced to sophisticated rapid manufacturing techniques capable of creating parts directly, eliminating the need for traditional tooling. The process involves constructing components layer by layer based on 3D model data, which has the potential to transform various manufacturing sectors. AM offers significant advantages such as reduced component lead times, minimized material waste, decreased energy consumption, and a lower carbon footprint. Moreover, it enables the creation of innovative product designs that are unachievable through conventional manufacturing methods. This review delves into the current landscape of AM technologies for direct metal fabrication, providing a detailed definition of AM, an overview of commercially available and emerging technologies, a discussion on the possibilities they present, and a critical assessment of the current state of the art. Additionally, it offers insights into future research directions that could further enhance the capabilities of AM for metal fabrication.

Convolutional autoencoders have emerged as popular methods for unsupervised defect segmentation on image data. Most commonly, this task is performed by thresholding a per-pixel reconstruction error based on an `-distance. This procedure, however, leads to large residuals whenever the reconstruction includes slight localization inaccuracies around edges. It also fails to reveal defective regions that have been visually altered when intensity values stay roughly consistent. We show that these problems prevent these approaches from being applied to complex real-world scenarios and that they cannot be easily avoided by employing more elaborate architectures such as variational or feature matching autoencoders. We propose to use a perceptual loss function based on structural similarity that examines inter-dependencies between local image regions, taking into account luminance, contrast, and structural information, instead of simply comparing single pixel values. It achieves significant performance gains on a challenging real-world dataset of nanofibrous materials and a novel dataset of two woven fabrics over state-of-the-art approaches for unsupervised defect segmentation that use per-pixel reconstruction

http://dx.doi.org/10.1016/j.displa.2016.07.002 0141-9382/ 2016 Elsevier B.V. All rights reserved. q This paper was recommended for publication by Richard H.Y. So. ⇑ Corresponding author at: University of California, Irvine, 2201 Social & Behavioral Sciences Gateway Building, Irvine, CA 92697-5100, USA. E-mail addresses: mdenniso@uci.edu (M.S. Dennison), awisti@uci.edu (A.Z. Wisti), mdzmura@uci.edu (M. D’Zmura). Mark S. Dennison ⇑, A. Zachary Wisti, Michael D’Zmura

This paper introduces Dynamic 3D Printing, a fast and reconstructable shape formation system. Dynamic 3D Printing can assemble an arbitrary three-dimensional shape from a large number of small physical elements. Also, it can disassemble the shape back to elements and reconstruct a new shape. Dynamic 3D Printing combines the capabilities of 3D printers and shape displays: Like conventional 3D printing, it can generate arbitrary and graspable three-dimensional shapes, while allowing shapes to be rapidly formed and reformed as in a shape display. To demonstrate the idea, we describe the design and implementation of Dynablock, a working prototype of a dynamic 3D printer. Dynablock can form a three-dimensional shape in seconds by assembling 3,000 9 mm blocks, leveraging a 24 x 16 pin-based shape display as a parallel assembler. Dynamic 3D printing is a step toward achieving our long-term vision in which 3D printing becomes an interactive medium, rather than the means for fabrication that it is today. In this paper, we explore possibilities for this vision by illustrating application scenarios that are difficult to achieve with conventional 3D printing or shape display systems.

A novel three-dimensional (3D) printing technique was utilized in the preparation of drug implants that can be designed to have complex drug release profiles. The method we describe is based on a lactic acid polymer matrix with a predefined microstructure that is amenable to rapid prototyping and fabrication. We describe how the process parameters, especially selection of the binder, were optimized. Implants containing levofloxacin (LVFX) with predefined microstructures using an optimized binder solution of ethanol and acetone (20:80, v/v) were prepared by a 3D printing process that achieved a bi-modal profile displaying both pulsatile and steady state LVFX release from a single implant. The pulse release appeared from day 5 to 25, followed by a steady state phase of 25 days. The next pulse release phase then began at the 50th day and ended at the 80th day. To evaluate the drug implants structurally and analytically, the microscopic morphologies and the in vitro release profiles of the implants fabricated by both the 3D printing technique and the conventional lost mold technique were assessed using environmental scanning electron microscopy (ESEM) and UV absorbance spectrophotometry. The results demonstrate that the 3D printing technology can be used to fabricate drug implants with sophisticated micro- and macro-architecture in a single device that may be rapidly prototyped and fabricated. We conclude that drug implants with predefined microstructure fabricated by 3D printing techniques can have clear advantages compared to implants fabricated by conventional compressing methods.


Question: An image-guided nanopositioning strategy for SEM analysis.

This article presents a novel method for real-time visual tracking of rigid bodies within a scanning electron microscope (SEM), a significant advancement in the field of nanomanipulation. As robotics technology advances, there is a growing demand for computer-assisted or fully automated methods to handle objects at the micro and nanoscale. Despite the availability of actuators capable of achieving subnanometer displacement resolutions, the development of feedback technologies has lagged behind. This deficiency often restricts the full potential of these high-precision actuators in automated tasks due to the absence of suitable feedback mechanisms. To address this issue, the paper suggests a rigid-model-based approach for tracking the end effector within an SEM, which is crucial for enhancing the precision of automated manipulations and measurements at the nanoscale. By employing these models, the system can capitalize on specific knowledge about the domain to improve performance in the complex environment of SEM-based tracking.

This paper presents an 6-axis optical force sensor which can be used in fMRI. Recently, fMRIs are widely used for studying human brain function. Simultaneous measurement of brain activity and peripheral information, such as grip force, enables more precise investigations in studies of motor function. However, conventional force sensors cannot be used in fMRI environment, since metal elements generate noise which severely contaminate the signals of fMRI. An optical 2-axis force sensor has been developed using photo sensors and optical fibers by Tada et. al.[1], that resolved these problems. The developed force sensor removed all magnetic components from the sensing part. It detected minute displacements by measure amount of light and light traveled through the optical fibers. However, there still remain several problems on this optical force sensor. Firstly, the accuracy is not high compared to the conventional force sensors. Secondly, the robustness is not enough against the contact force to the optical fibers. In this paper, the problems concerning to the accuracy and the sensor output stability has been improved by novel methods of fixing fibers and arithmetic circuit. Furthermore, an optical 6-axis force sensor is developed based on these improvements, and usefulness of our sensor for brain function analysis is confirmed in fMRI experimentations.

We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes.

Graphene is the two-dimensional building block for carbon allotropes of every other dimensionality. We show that its electronic structure is captured in its Raman spectrum that clearly evolves with the number of layers. The D peak second order changes in shape, width, and position for an increasing number of layers, reflecting the change in the electron bands via a double resonant Raman process. The G peak slightly down-shifts. This allows unambiguous, high-throughput, nondestructive identification of graphene layers, which is critically lacking in this emerging research area.

A novel direct-drive planar parallel manipulator for high-speed and high-precision semiconductor packaging systems is presented. High precision kinematics design, significant reduction on moving mass and driving power of the actuators over traditional XY motion stages are the benefits of the proposed manipulator. The mathematical model of the manipulator is obtained using the Newton-Euler method and a practical model-based control design approach is employed to design the PID computed-torque controller. Experimental results demonstrate that the proposed planar parallel manipulator has significant improvements on motion performance in terms of positioning accuracy, settling time and stability when compared with traditional XY stages. This shows that the proposed planar parallel manipulator can provide a superior alternative for replacing traditional XY motion stages in high precision low-payload applications

J. Appl. Phys. 111, 07E328 (2012) A single-solenoid pulsed-magnet system for single-crystal scattering studies Rev. Sci. Instrum. 83, 035101 (2012) Solution to the problem of E-cored coil above a layered half-space using the method of truncated region eigenfunction expansion J. Appl. Phys. 111, 07E717 (2012) Array of 12 coils to measure the position, alignment, and sensitivity of magnetic sensors over temperature J. Appl. Phys. 111, 07E501 (2012) Skin effect suppression for Cu/CoZrNb multilayered inductor J. Appl. Phys. 111, 07A501 (2012)

This article presents the development of an autonomous motion planning algorithm for a soft planar grasping manipulator capable of grasp-and-place operations by encapsulation with uncertainty in the position and shape of the object. The end effector of the soft manipulator is fabricated in one piece without weakening seams using lost-wax casting instead of the commonly used multilayer lamination process. The soft manipulation system can grasp randomly positioned objects within its reachable envelope and move them to a desired location without human intervention. The autonomous planning system leverages the compliance and continuum bending of the soft grasping manipulator to achieve repeatable grasps in the presence of uncertainty. A suite of experiments is presented that demonstrates the system's capabilities.

In this study, a novel approach for the detection of parcel loading positions on a pallet is presented. This approach was realized as a substantial change in comparison with traditional system design of contour detection in de-palletizing processes. Complex 3D-vision systems, costly laser scanners or throughput decreasing local sensor solutions integrated in grippers are substituted by a lowcost photonic mixing device (PMD) camera. By combining PMD technology and a predetermined model of loading situations, stored during assembling the pallet, this approach can compensate for the drawbacks of each respective system. An essential part of the approach are computer-graphics methods specific to the given problem to both detect the deviation between the nominal and the actual loading position and if necessary an automated correction of the packaging scheme. From an economic point of view, this approach can decrease the costs of mandatory contour checking in automated de-palletizing processes.

In this paper, we present the design, construction, and control of a six-degree-of-freedom (DOF), 12 mm diameter, parallel continuum manipulator with a 2-DOF, cable-driven grasper. This work is a proof-of-concept first step towards miniaturization of this type of manipulator design to provide increased dexterity and stability in confined-space surgical applications, particularly for endoscopic procedures. Our robotic system consists of six superelastic NiTi (Nitinol) tubes in a standard Stewart-Gough configuration and an end effector with 180 degree motion of its two jaws. Two Kevlar cables pass through the centers of the tube legs to actuate the end effector. A computationally efficient inverse kinematics model provides low-level control inputs to ten independent linear actuators, which drive the Stewart-Gough platform and end-effector actuation cables. We demonstrate the performance and feasibility of this design by conducting open-loop range-of-motion tests for our system.

Segmentation of the object of interest is a difficult step in the analysis of digital images. Fully automatic methods sometimes fail, producing incorrect results and requiring the intervention of a human operator. This is often true in medical applications, where image segmentation is particularly difficult due to restrictions imposed by image acquisition, pathology and biological variation. In this paper we present an early review of the largely unknown territory of human-computer interaction in image segmentation. The purpose is to identify patterns in the use of interaction and to develop qualitative criteria to evaluate interactive segmentation methods. We discuss existing interactive methods with respect to the following aspects: the type of information provided by the user, how this information affects the computational part, and the purpose of interaction in the segmentation process. The discussion is based on the potential impact of each strategy on the accuracy, repeatability and interaction efficiency. Among others, these are important aspects to characterise and understand the implications of interaction to the results generated by an interactive segmentation method. This survey is focused on medical imaging, however similar patterns are expected to hold for other applications as well.

http://dx.doi.org/10.1016/j.displa.2016.07.002 0141-9382/ 2016 Elsevier B.V. All rights reserved. q This paper was recommended for publication by Richard H.Y. So. ⇑ Corresponding author at: University of California, Irvine, 2201 Social & Behavioral Sciences Gateway Building, Irvine, CA 92697-5100, USA. E-mail addresses: mdenniso@uci.edu (M.S. Dennison), awisti@uci.edu (A.Z. Wisti), mdzmura@uci.edu (M. D’Zmura). Mark S. Dennison ⇑, A. Zachary Wisti, Michael D’Zmura


Question: An image-guided nanopositioning system for SEM applications.

This paper presents an analytical investigation into the phase correlation of downsampled images, leading to the development of a novel subpixel registration technique. We have demonstrated that when images are downsampled, the signal power in the phase correlation does not concentrate solely in a single peak, but rather forms a cluster of coherent peaks, primarily situated adjacent to one another. These peaks are directly related to the polyphase transform of a filtered unit impulse, with the peak cluster centered at the registration point. Our analytical findings offer a precise, closed-form solution for subpixel translation estimation, which we have thoroughly validated through error analysis. The technique has been successfully applied to a variety of images across different spectral bands, yielding highly accurate subpixel translation estimations.

**Question**: A new method for the identification of functional elements in gene regulatory networks

**Documents**: Gene regulatory network inference using multiobjective evolutionary algorithms
The inference of gene regulatory networks (GRNs) from time series microarray data is a crucial task in systems biology. In this paper, we propose a new method for GRN inference using multiobjective evolutionary algorithms (MOEAs). The method is based on the integration of a multiobjective optimization algorithm with a Bayesian network model. The Bayesian network model is used to represent the structure of the GRN, while the MOEA is used to search for the optimal structure of the network. The multiobjective optimization algorithm is used to simultaneously optimize two conflicting objectives: the fit of the network to the data and the complexity of the network. The method is tested on both synthetic and real-world data sets, and the results are compared with those obtained using other methods. The results show that the proposed method is able to infer GRNs with high accuracy and low complexity.

**Similar Documents**: This paper introduces an innovative approach for the inference of gene regulatory networks (GRNs) from time series microarray data, employing multiobjective evolutionary algorithms (MOEAs) in a novel context. The proposed method integrates a Bayesian network model with a multiobjective optimization algorithm to effectively infer the structure of GRNs. The Bayesian network model serves as the framework for representing the GRN structure, while the MOEA is tasked with searching for the most optimal network structure. The multiobjective optimization algorithm is pivotal in balancing two opposing goals: maximizing the network's fit to the data and minimizing network complexity. The method's efficacy is demonstrated through rigorous testing on both synthetic and real-world datasets, with comparisons to alternative approaches revealing its capability to accurately infer GRNs with minimal complexity.

ARTICLE INFO In this system an electro-mechanical robot is designed and controlled using hand gesture in real time. The system is designed on microcontroller platform using Keil and MPLAB tools. Hand gesture recognition is done on the principle of resistance change sensed through flex sensor. These sensors are integrated in a hand gloves from which input to the system is given. The designed system is divided into two sections as transmitter and receiver. The transmitter section will be in hand gloves from which the data is sensed and processed through PIC16F7487 and send serially to the receiver section. RF technology is used to transmit the data at the receiver section at the frequency of 2.4 GHz. ARM 7 (LPC2148) processor is used to receive the data. Here from the received data, the character is predicted and matched with the closet character from which the character is identified and displayed on LCD. The various case studies is prepared for the designed system and tested in real time. The proposed system can be used for the various applications such as in unmanned machines, industries, handicapped personnel etc. Keywords— a Sensor gloves, flex sensors, PIC controller, ARM processor etc Article History Received:20 th September 2015 Received in revised form :

For the first time, nano-meter-scaled 1T-1R non-volatile memory (NVM) architecture comprising of RRAM cells built on vertical GAA nano-pillar transistors, either junction-less or junction-based, is systematically investigated. Transistors are fabricated using fully CMOS compatible technology and RRAM cells are stacked onto the tip of the nano-pillars (with a diameter down to ~37nm) to achieve a compact 4F2 footprint. In addition, through this platform, different RRAM stacks comprising CMOS friendly materials are studied, and it is found that TiN/Ni/HfO2/n+-Si RRAM cells show excellent switching properties in either bipolar or unipolar mode, including (1) ultra-low switching current/power: SET ~20nA/85nW and RESET ~200pA/700pW, (2) multi-level switchability, (3) good endurance, >105, (4) satisfactory retention, 10 years at 85oC; and (5) fast switching speed ~50ns. Moreover, this vertical (gate-all-around) GAA nano-pillar based 1T-1R architecture provides a more direct and flexible test vehicle to verify the scalability and functionality of RRAM candidates with a dimension close to actual application.

Robust, accurate pose estimation and mapping at real-time in six dimensions is a primary need of mobile robots, in particular flying Micro Aerial Vehicles (MAVs), which still perform their impressive maneuvers mostly in controlled environments. This work presents a visual-inertial sensor unit aimed at effortless deployment on robots in order to equip them with robust real-time Simultaneous Localization and Mapping (SLAM) capabilities, and to facilitate research on this important topic at a low entry barrier. Up to four cameras are interfaced through a modern ARM-FPGA system, along with an Inertial Measurement Unit (IMU) providing high-quality rate gyro and accelerometer measurements, calibrated and hardware-synchronized with the images. This facilitates a tight fusion of visual and inertial cues that leads to a level of robustness and accuracy which is difficult to achieve with purely visual SLAM systems. In addition to raw data, the sensor head provides FPGA-pre-processed data such as visual keypoints, reducing the computational complexity of SLAM algorithms significantly and enabling employment on resource-constrained platforms. Sensor selection, hardware and firmware design, as well as intrinsic and extrinsic calibration are addressed in this work. Results from a tightly coupled reference visual-inertial motion estimation framework demonstrate the capabilities of the presented system.

This paper deals with the implementation of mobile measuring station in greenhouse environment navigated using potential field method. The function of a greenhouse is to create the optimal growing conditions for the full life of the plants. Using autonomous measuring systems helps to monitor all the necessary parameters for creating the optimal environment in the greenhouse. The robot equipped with sensors is capable of driving to the end and back along crop rows inside the greenhouse. It introduces a wireless sensor network that was used for the purpose of measuring and controlling the greenhouse application. Continuous advancements in wireless technology and miniaturization have made the deployment of sensor networks to monitor various aspects of the environment increasingly flexible.

Anyone who has gazed through the eyepiece of an astronomical telescope knows that, with the exception of the Moon and the planets, extra-solar astronomical objects are disappointing to observe visually. This is mainly due to their low surface brightness, but also depends on the visibility, sky brightness and telescope aperture. We propose a system which projects images of astronomical objects (with focus on nebulae and galaxies), animations and additional information directly into the eyepiece view of an astronomical telescope. As the telescope orientation is queried continuously, the projected image is adapted in real-time to the currently visible field of view. For projection, a custom-built video projection module with high contrast and low maximum luminance value was developed. With this technology visitors to public observatories have the option to experience the richness of faint astronomical objects while directly looking at them through a telescope.

The present study investigated the ability to inter actively locate points in a three dimensional computer environment using a six degree of freedom input device. Four different visu al feedback modes were tested: fixed viewpoint monoscopic persp ective, fixed viewpoint stereoscopic perspective, head-tracked mo noscopic perspective and head-tracked stereoscopic perspecti ve. Targets were located at plus and minus 10cm along the X, Y or Z axes, from a fixed starting location. Data about the time to complete the task and positioning accuracy (error) are gathered for each trial. In addition, subjective feedback regarding the apparat us, visual mode and task difficulty was solicited from subject s. The results indicate that stereoscopic performance is superior to monoscopic performance and that asymmetries exist both across and within axes. Head tracking had no appreciable effect upon performance. Subjective feedback regarding performance is usuall y consistent with objective measures, but some inconsistencies a re present.

Tracking, or camera pose determination, is the main technical challenge in creating augmented realities. Constraining the degree to which the environment may be altered to support tracking heightens the challenge. This paper describes several years of work at the USC Computer Graphics and Immersive Technologies (CGIT) laboratory to develop self-contained, minimally intrusive tracking systems for use in both indoor and outdoor settings. These hybrid-technology tracking systems combine vision and inertial sensing with research in fiducial design, feature detection, motion estimation, recursive filters, and pragmatic engineering to satisfy realistic application requirements.

^ IEEE ConsumEr ElECtronICs magazInE 19 By early 2016, Pabellon achieved another major milestone: a first touchfree control panel using solely the body’s electrolytes to control a matrix of magnetic pixels. Unlike conventional passive near-field communication technology that relies on receiver loop antennas for detection and identification, the magnetic pixel needs only our body salts to work. Each pixel represents a discrete sensing element. When arrayed or matrixed, the collection of pixels can be used to position index fingers approaching but not touching the surface. Pabellon’s powertransfer emitter turns into a touch-free pad. Unlike motion and other opticalsensing methods, the position of objects like fingers can be resolved by small changes in the magnetic near field. The ability to finely control the vast amount of things we contact on a daily basis may not require contact alone. The magnetic pixel has a very exciting future in the look-but-don’t-touch world that Pabellon envisions.

Takeo Kanade, Robert T. Collins, and Alan J. Lipton Carnegie Mellon University, Pittsburgh, PA e-mail: fkanade,rcollins,ajlg@cs.cmu.edu homepage: http://www.cs.cmu.edu/ vsam P. Anandan, Peter Burt, and Lambert Wixson David Sarno Research Center, Princeton, NJ e-mail: fpanandan,pburt,lwixsong@sarno .com Abstract Carnegie Mellon University (CMU) and the David Sarno Research Center (Sarno ) have begun a joint, integrated feasibility demonstration in the area of Video Surveillance and Monitoring (VSAM). The objective is to develop a cooperative, multi-sensor video surveillance system that provides continuous coverage over large battle eld areas. Image Understanding (IU) technologies will be developed to: 1) coordinate multiple sensors to seamlessly track moving targets over an extended area, 2) actively control sensor and platform parameters to track multiple moving targets, 3) integrate multisensor output with collateral data to maintain an evolving, scene-level representation of all targets and platforms, and 4) monitor the scene for unusual \trigger" events and activities. These technologies will be integrated into an experimental testbed to support evaluation, data collection, and demonstration of other VSAM technologies developed within the DARPA IU community.

This work demonstrates a 3-axis Lorentz force magnetometer for electronic compass purposes. The magnetometer measures magnetic flux in 3 axes using a single structure. With 1 mW power consumption, the sensor achieves sub-30 nT/√Hz resolution in each of the 3 axes. Compared to the 3-axis Hall sensors currently used in smartphones, the 3-axis magnetometer shown here has the advantages of 10× lower noise floor and the ability to be co-fabricated with MEMS inertial sensors.


Question: An image-guided nanopositioning method for SEM analysis.

This paper explores a technique for the computation of optical flow, a critical component in understanding motion in image sequences. The primary challenge lies in the fact that optical flow cannot be determined locally due to the single measurement available at each point in the image, which contrasts with the two components of flow velocity. To address this issue, a method is proposed that presumes a smooth variation in the apparent velocity of the brightness pattern across most of the image area. The algorithm detailed in this study is iterative and has been tested on various synthetic image sequences, demonstrating its effectiveness in computing optical flow accurately. A key feature of this approach is its robustness, enabling it to function well even with image sequences that are coarsely quantized in both space and time. Moreover, the algorithm exhibits resilience against quantization of brightness levels and additive noise, further enhancing its reliability. The paper also includes scenarios where the smoothness assumption is breached at singular points or along lines within the image, illustrating the algorithm's limitations and areas for potential improvement.

The system design of an integrated microwave imaging radar for the diagnostic screening of breasts cancer is presented. A custom integrated circuit implemented in a 65-nm CMOS technology and a pair of patch antennas realized on a planar laminate are proposed as the basic module of the imaging antenna array. The radar operates on the broad frequency range from 2 to 16 GHz with a dynamic range of 107 dB. Imaging experiments carried out on a realistic breast phantom show that the system is capable of detecting tumor targets with a resolution of 3 mm.

Continuous electrowetting (CEW) is demonstrated to be an effective actuation mechanism for reconfigurable radio frequency (RF) devices that use non-toxic liquid-metal tuning elements. Previous research has shown CEW is an efficient means of electrically inducing motion in a liquid-metal slug, but precise control of the slug's position within fluidic channels has not been demonstrated. Here, the precise positioning of liquid-metal slugs is achieved using CEW actuation in conjunction with channels designed to minimize the liquid-metal surface energy at discrete locations. This approach leverages the high surface tension of liquid metal to control its resting position with submillimeter accuracy. The CEW actuation and fluidic channel design were optimized to create reconfigurable RF devices. In addition, solutions for the reliable actuation of a gallium-based, non-toxic liquid-metal alloy (Galinstan) are presented that mitigate the tendency of the alloy to form a surface oxide layer capable of wetting to the channel walls, inhibiting motion. A reconfigurable slot antenna utilizing these techniques to achieve a 15.2% tunable frequency bandwidth is demonstrated.

The amazing climbing ability of geckos has attracted the interest of philosophers and scientists alike for centuries. However, only in the past few years has progress been made in understanding the mechanism behind this ability, which relies on submicrometre keratin hairs covering the soles of geckos. Each hair produces a miniscule force approximately 10(-7) N (due to van der Waals and/or capillary interactions) but millions of hairs acting together create a formidable adhesion of approximately 10 N x cm(-2): sufficient to keep geckos firmly on their feet, even when upside down on a glass ceiling. It is very tempting to create a new type of adhesive by mimicking the gecko mechanism. Here we report on a prototype of such 'gecko tape' made by microfabrication of dense arrays of flexible plastic pillars, the geometry of which is optimized to ensure their collective adhesion. Our approach shows a way to manufacture self-cleaning, re-attachable dry adhesives, although problems related to their durability and mass production are yet to be resolved.

This paper presents motion analyses and experiments of an in-pipe robot with screw drive mechanism while it moves inside curved pipes. This robot is driven by only one motor and composed of two units. One unit works as a rotator and the another one works as a stator. Screw drive mechanism is a better way to travel inside pipelines of small diameter for inspection, because the area for moving of the robot is narrow and the number of actuators can be reduced (minimum is just one). Therefore, the robot can be smaller and lighter. Furthermore, the control becomes easier. Although many kinds of in-pipe robots with screw drive mechanism have been reported to date, the most important problem of such drive mechanism is the difficulty of traveling in pipes other than straight ones. Examples of such pipes are curved pipes like elbow and bent, branch pipes like a T-shape and the pipe where diameter changes. A concrete analysis has not been done yet. In this paper, we concentrate on a helical driving motion of the robot inside the curved pipe and finally perform experiments to determine the characteristics of it.

Radiation-induced single event upsets (SEUs) pose a major challenge for the design of memories and logic circuits in high-performance microprocessors in technologies beyond 90nm. Historically, we have considered power-performance-area trade offs. There is a need to include the soft error rate (SER) as another design parameter. In this paper, we present radiation particle interactions with silicon, charge collection effects, soft errors, and their effect on VLSI circuits. We also discuss the impact of SEUs on system reliability. We describe an accelerated measurement of SERs using a high-intensity neutron beam, the characterization of SERs in sequential logic cells, and technology scaling trends. Finally, some directions for future research are given.

Image-based 6-DoF pose estimation of arbitrarily shaped 3D objects based on their shape is a rarely studied problem. Most existing image-based methods for pose estimation either exploit textural information in form of local features or, if shape-based, rely on the extraction of straight line segments or other primitives. Straight-forward extensions of 2D approaches are potentially more general, but in practice assume a limited range of possible view angles. The general problem is that a 3D object can potentially produce completely different 2D projections depending on its relative pose to the observing camera. One way to reduce the solution space is to exploit temporal information, i.e. perform tracking. Again, existing model-based tracking approaches rely on relatively simple object geometries. In this paper, we propose a particle filter based tracking approach that can deal with arbitrary shapes and arbitrary or even no texture, i.e. it offers a general solution to the rigid object tracking problem. As our approach can deal with occlusions, it is in particular of interest in the context of goal-directed imitation learning involving the observation of object manipulations. Results of simulation experiments as well as real-world experiments with different object types prove the practical applicability of our approach.

This paper describes performance evaluation of a wearable augmented reality system for natural outdoor environments. Applied Research Associates (ARA), as prime integrator on the DARPA ULTRA-Vis (Urban Leader Tactical, Response, Awareness, and Visualization) program, is developing a soldier-worn system to provide intuitive ‘heads-up’ visualization of tactically-relevant geo-registered icons. Our system combines a novel pose estimation capability, a helmet-mounted see-through display, and a wearable processing unit to accurately overlay geo-registered iconography (e.g., navigation waypoints, sensor points of interest, blue forces, aircraft) on the soldier’s view of reality. We achieve accurate pose estimation through fusion of inertial, magnetic, GPS, terrain data, and computer-vision inputs. We leverage a helmet-mounted camera and custom computer vision algorithms to provide terrain-based measurements of absolute orientation (i.e., orientation of the helmet with respect to the earth). These orientation measurements, which leverage mountainous terrain horizon geometry and mission planning landmarks, enable our system to operate robustly in the presence of external and body-worn magnetic disturbances. Current field testing activities across a variety of mountainous environments indicate that we can achieve high icon geo-registration accuracy (<10mrad) using these vision-based methods.

Vector processing operations use essential spectral and spatial information to remove noise and localize microarray spots. The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool.

ÐThis paper describes a robust hierarchical algorithm for fully-automatic registration of a pair of images of the curved human retina photographed by a fundus microscope. Accurate registration is essential for mosaic synthesis, change detection, and design of computer-aided instrumentation. Central to the new algorithm is a 12-parameter interimage transformation derived by modeling the retina as a rigid quadratic surface with unknown parameters, imaged by an uncalibrated weak perspective camera. The parameters of this model are estimated by matching vascular landmarks extracted by an algorithm that recursively traces the blood vessel structure. The parameter estimation technique, which could be generalized to other applications, is a hierarchy of models and methods: an initial match set is pruned based on a zeroth order transformation estimated as the peak of a similarity-weighted histogram; a first order, affine transformation is estimated using the reduced match set and least-median of squares; and the final, second order, 12-parameter transformation is estimated using an M-estimator initialized from the first order estimate. This hierarchy makes the algorithm robust to unmatchable image features and mismatches between features caused by large interframe motions. Before final convergence of the M-estimator, feature positions are refined and the correspondence set is enhanced using normalized sum-of-squared differences matching of regions deformed by the emerging transformation. Experiments involving 3,000 image pairs (I; HPR Â I; HPR pixels) from 16 different healthy eyes were performed. Starting with as low as 20 percent overlap between images, the algorithm improves its success rate exponentially and has a negligible failure rate above 67 percent overlap. The experiments also quantify the reduction in errors as the model complexities increase. Final registration errors less than a pixel are routinely achieved. The speed, accuracy, and ability to handle small overlaps compare favorably with retinal image registration techniques published in the literature.


Question: An image-guided nanopositioning method for scanning electron microscopy.

This paper presents an innovative technique for enhancing image resolution through precise image registration. The method is effective when the exact relative displacements within image sequences are determined accurately, and there is a basic understanding of the imaging process involved. The technique mirrors the back-projection method used in tomography, offering a novel application of this principle. Demonstrative examples are provided, showcasing the improvement in image resolution for both grayscale and color images. These enhancements are achieved by calculating the unknown displacements directly from the image sequence, illustrating the technique's capability to refine image quality significantly.

Continuous electrowetting (CEW) is demonstrated to be an effective actuation mechanism for reconfigurable radio frequency (RF) devices that use non-toxic liquid-metal tuning elements. Previous research has shown CEW is an efficient means of electrically inducing motion in a liquid-metal slug, but precise control of the slug's position within fluidic channels has not been demonstrated. Here, the precise positioning of liquid-metal slugs is achieved using CEW actuation in conjunction with channels designed to minimize the liquid-metal surface energy at discrete locations. This approach leverages the high surface tension of liquid metal to control its resting position with submillimeter accuracy. The CEW actuation and fluidic channel design were optimized to create reconfigurable RF devices. In addition, solutions for the reliable actuation of a gallium-based, non-toxic liquid-metal alloy (Galinstan) are presented that mitigate the tendency of the alloy to form a surface oxide layer capable of wetting to the channel walls, inhibiting motion. A reconfigurable slot antenna utilizing these techniques to achieve a 15.2% tunable frequency bandwidth is demonstrated.

In this paper, we present a low-cost and rapid self-alignment process for temporary bonding of MEMS chip onto carrier wafer for size-free MEMS-IC integration. For the first time, a hydrophobic self-assembled monolayer (SAM), FDTS (CF<inf>3</inf>(CF<inf>2</inf>)<inf>7</inf>(CH<inf>2</inf>)<inf>2</inf>SiCl<inf>3</inf>), was successfully patterned by lift-off process on an oxidized silicon carrier wafer. Small volume of H<inf>2</inf>O (∼µl/cm2) was then dropped and spread on the non-coated hydrophilic SiO<inf>2</inf> surface for temporary bonding of MEMS chip. Our results demonstrated that the hydrophobic FDTS pattern on carrier wafer enables rapid and precise self-alignment of MEMS chip onto SiO<inf>2</inf> binding-site by capillary force. After transfer the MEMS chips to target wafer, FDTS can be removed by O<inf>2</inf> plasma treatment or UV irradiation.

Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for onchip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain one major problem associated with sample preparation on a conventional DMFB. For conventional DMFBs, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. To overcome the drawback, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (MEDA), for sample preparation. We propose the first sample preparation method that exploits the MEDA-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated MEDA biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.

In this study, a novel approach for the detection of parcel loading positions on a pallet is presented. This approach was realized as a substantial change in comparison with traditional system design of contour detection in de-palletizing processes. Complex 3D-vision systems, costly laser scanners or throughput decreasing local sensor solutions integrated in grippers are substituted by a lowcost photonic mixing device (PMD) camera. By combining PMD technology and a predetermined model of loading situations, stored during assembling the pallet, this approach can compensate for the drawbacks of each respective system. An essential part of the approach are computer-graphics methods specific to the given problem to both detect the deviation between the nominal and the actual loading position and if necessary an automated correction of the packaging scheme. From an economic point of view, this approach can decrease the costs of mandatory contour checking in automated de-palletizing processes.

Underwater high resolution 3D mapping implies a very accurate sensor pose estimation to fuse the sensor readings over time into one consistent model. In the case of optical mapping systems, the needed accuracy can easily lie outside of the specification of Doppler Velocity Logs normally used for pose estimation by remotely operated and autonomous underwater vehicles. This is especially the case for difficult terrains or for low altitude situations. Therefore, to improve performance in such situations, a self-referenced laser system is proposed performing micro navigation to significantly improve the resolution of optical underwater 3D seabed mapping.

Autonomous microhelicopters will soon play a major role in tasks like search and rescue, environment monitoring, security surveillance, and inspection. If they are further realized in small scale, they can also be used in narrow outdoor and indoor environments and represent only a limited risk for people. However, for such operations, navigating based only on global positioning system (GPS) information is not sufficient. Fully autonomous operation in cities or other dense environments requires microhelicopters to fly at low altitudes, where GPS signals are often shadowed, or indoors and to actively explore unknown environments while avoiding collisions and creating maps. This involves a number of challenges on all levels of helicopter design, perception, actuation, control, and navigation, which still have to be solved. The Swarm of Micro Flying Robots (SFLY) project was a European Union-funded project with the goal of creating a swarm of vision-controlled microaerial vehicles (MAVs) capable of autonomous navigation, three-dimensional (3-D) mapping, and optimal surveillance coverage in GPS-denied environments. The SFLY MAVs do not rely on remote control, radio beacons, or motion-capture systems but can fly all by themselves using only a single onboard camera and an inertial measurement unit (IMU). This article describes the technical challenges that have been faced and the results achieved from hardware design and embedded programming to vision-based navigation and mapping, with an overview of how all the modules work and how they have been integrated into the final system. Code, data sets, and videos are publicly available to the robotics community. Experimental results demonstrating three MAVs navigating autonomously in an unknown GPS-denied environment and performing 3-D mapping and optimal surveillance coverage are presented.

We describe a novel system for rapid prototyping of laserbased optical and holographic layouts. Users of this optical prototyping tool – called the Illuminating Light system – move physical representations of various optical elements about a workspace, while the system tracks these components and projects back onto the workspace surface the simulated propagation of laser light through the evolving layout. This application is built atop the Luminous Room infrastructure, an aggregate of interlinked, computer-controlled projector-camera units called I/O Bulbs. Philosophically, the work embodies the emerging ideas of the Luminous Room and builds on the notions of ‘graspable media’. We briefly introduce the I/O Bulb and Luminous Room concepts and discuss their current implementations. After an overview of the optical domain that the Illuminating Light system is designed to address, we present the overall system design and implementation, including that of an intermediary toolkit called voodoo which provides a general facility for object identification and tracking.

A surface potential measuring system was developed by utilizing Pockels sensor for measuring the potential distribution on the stress grading (SG) system of form wound motor coils. A Bi4Ge3O12 (BGO) Pockels crystal is put close to a measuring object and the capacitively-induced voltage on the end surface of the BGO crystal is measured by using Pockels effect of the crystal itself. The spatial resolution of the measuring system is 5 mm, and the frequency response reaches up to GHz-range. With this system, the surface potential distributions on a model bar coil were measured. According to the measuring results, it is shown that the newly developed potential measuring system here is very useful for evaluating the reliability of the SG system of motors.

Thomas Glotzbach, TU Ilmenau; Fraunhofer Center for Applied Systems Technology, Ilmenau/Germany, thomas.glotzbach@tu-ilmenau.de Andrea Picini, INNOVA S.p.A., Rome/Italy, a.picini@innova-eu.net Antonio Zangrilli, INNOVA S.p.A., Rome/Italy, a.zangrilli@innova-eu.net Mike Eichhorn, TU Ilmenau/Germany, mike.eichhorn@tu-ilmenau.de Peter Otto, TU Ilmenau/Germany, peter.otto@tu-ilmenau.de Matthias Schneider, TU Ilmenau/Germany, schneider.matthias@tu-ilmenau.de

Image-based 6-DoF pose estimation of arbitrarily shaped 3D objects based on their shape is a rarely studied problem. Most existing image-based methods for pose estimation either exploit textural information in form of local features or, if shape-based, rely on the extraction of straight line segments or other primitives. Straight-forward extensions of 2D approaches are potentially more general, but in practice assume a limited range of possible view angles. The general problem is that a 3D object can potentially produce completely different 2D projections depending on its relative pose to the observing camera. One way to reduce the solution space is to exploit temporal information, i.e. perform tracking. Again, existing model-based tracking approaches rely on relatively simple object geometries. In this paper, we propose a particle filter based tracking approach that can deal with arbitrary shapes and arbitrary or even no texture, i.e. it offers a general solution to the rigid object tracking problem. As our approach can deal with occlusions, it is in particular of interest in the context of goal-directed imitation learning involving the observation of object manipulations. Results of simulation experiments as well as real-world experiments with different object types prove the practical applicability of our approach.


Question: An image-guided nanopositioning system for SEM applications.

This paper provides an overview of the latest advancements in affine covariant region detectors and conducts a comprehensive performance analysis under various imaging scenarios using a standardized set of test images. The study encompasses six distinct detector types: those relying on affine normalization centered around Harris (Mikolajczyk and Schmid, 2002; Schaffalitzky and Zisserman, 2002) and Hessian points (Mikolajczyk and Schmid, 2002), the 'maximally stable extremal regions' detector proposed by Matas et al. (2002), an edge-based region detector (Tuytelaars and Van Gool, 1999), a detector based on intensity extrema (Tuytelaars and Van Gool, 2000), and the 'salient regions' detector introduced by Kadir, Zisserman, and Brady (2004). The evaluation focuses on the detectors' resilience to changes in viewpoint, scale, illumination conditions, defocus, and image compression. The primary aim is not only to compare these detectors but also to establish a standardized test set of images and a performance evaluation software framework, enabling future detectors to be assessed within the same context, facilitating consistent and comparable results across different algorithms.

Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain/machine interfaces. This article describes a material strategy for a type of bio-interfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal models illustrate one mode of use for this class of technology. These concepts provide new capabilities for implantable and surgical devices.

Sparse sampling schemes can broadly be classified into two main categories: static sampling where the sampling pattern is predetermined, and dynamic sampling where each new measurement location is selected based on information obtained from previous measurements. Dynamic sampling methods are particularly appropriate for pointwise imaging methods, in which pixels are measured sequentially in arbitrary order. Examples of pointwise imaging schemes include certain implementations of atomic force microscopy, electron back scatter diffraction, and synchrotron X-ray imaging. In these pointwise imaging applications, dynamic sparse sampling methods have the potential to dramatically reduce the number of measurements required to achieve a desired level of fidelity. However, the existing dynamic sampling methods tend to be computationally expensive and are, therefore, too slow for many practical applications. In this paper, we present a framework for dynamic sampling based on machine learning techniques, which we call a supervised learning approach for dynamic sampling (SLADS). In each step of SLADS, the objective is to find the pixel that maximizes the expected reduction in distortion (ERD) given previous measurements. SLADS is fast because we use a simple regression function to compute the ERD, and it is accurate because the regression function is trained using datasets that are representative of the specific application. In addition, we introduce an approximate method to terminate dynamic sampling at a desired level of distortion. We then extend our algorithm to incorporate multiple measurements at each step, which we call groupwise SLADS. Finally, we present results on computationally generated synthetic data and experimentally collected data to demonstrate a dramatic improvement over state-of-the-art static sampling methods

In this paper, we have developed a method to tele-control a robot arm to imitate human writing skills using electromyography (EMG) signals. The control method is implemented on the Baxter® robot with a brush attached on the endpoint of its arm to imitate human writing skills, and a MYO sensor is used to measure the surface electromyographic (sEMG) signals generated by contractions of human muscles involved in writing tasks. A haptic device Sensable® Omni is used to control the motion of the Baxter® robot arm, and V-Rep® is employed to simulate the movement of the arm and to calculate the inverse kinematic of Baxter® robot arm. All the communications for Baxter® robot, V-Rep simulator, Omni device and MYO are integrated in MATLAB®/Simulink®. The main test is to make the Baxter® arm following the movement of a human subject when writing with Omni stylus, and the EMG signals are processed using low pass filter and moving average technique to extract the smoothed envelope which is utilised to control the variation of position instead of variation of force along the vertical Z axis, so when the operator writes with force variations, the Baxter® can draw lines with variable thickness. This imitation system is successfully tested to make the Baxter® arm to follow the writing movement of the operator's hand and would have potential applications in more complicated human robot teleoperation tasks such as tele-rehabilitation and tele-surgery.

ARTICLE INFO In this system an electro-mechanical robot is designed and controlled using hand gesture in real time. The system is designed on microcontroller platform using Keil and MPLAB tools. Hand gesture recognition is done on the principle of resistance change sensed through flex sensor. These sensors are integrated in a hand gloves from which input to the system is given. The designed system is divided into two sections as transmitter and receiver. The transmitter section will be in hand gloves from which the data is sensed and processed through PIC16F7487 and send serially to the receiver section. RF technology is used to transmit the data at the receiver section at the frequency of 2.4 GHz. ARM 7 (LPC2148) processor is used to receive the data. Here from the received data, the character is predicted and matched with the closet character from which the character is identified and displayed on LCD. The various case studies is prepared for the designed system and tested in real time. The proposed system can be used for the various applications such as in unmanned machines, industries, handicapped personnel etc. Keywords— a Sensor gloves, flex sensors, PIC controller, ARM processor etc Article History Received:20 th September 2015 Received in revised form :

This paper investigated various indoor positioning techniques and presented a comprehensive study about their advantages and disadvantages. Infrared, Ultrasonic and RF technologies are used in different indoor positioning systems. RFID positioning systems based on RSSI technology are the most recent developments. Positioning accuracy was greatly improved by using integrated RFID technologies.

We present an open-source marker-based localization system intended as a low-cost easy-to-deploy solution for aerial and swarm robotics. The main advantage of the presented method is its high computational efficiency, which allows its deployment on small robots with limited computational resources. Even on low-end computers, the core component of the system can detect and estimate 3D positions of hundreds of black and white markers at the maximum frame-rate of standard cameras. The method is robust to changing lighting conditions and achieves accuracy in the order of millimeters to centimeters. Due to its reliability, simplicity of use and availability as an open-source ROS module (http://purl.org/robotics/whycon), the system is now used in a number of aerial robotics projects where fast and precise relative localization is required.

Recent years have seen advances in many enabling augmented reality technologies. Furthermore, much research has been carried out on how augmented reality can be used to enhance existing applications. This paper describes our experiences with an AR-museum guide that combines some of the latest technologies. Amongst other technologies, markerless tracking, hybrid tracking, and an ultra-mobile-PC were used. Like existing audio guides, the AR-guide can be used by any museum visitor, during a six-month exhibition on Islamic art. We provide a detailed description of the museumpsilas motivation for using AR, of our experiences in developing the system, and the initial results of user surveys. Taking this information into account, we can derive possible system improvements.

This paper deals with a relatively new area of radio-frequency (RF) technology based on microelectromechanical systems (MEMS). RF MEMS provides a class of new devices and components which display superior high-frequency performance relative to conventional (usually semiconductor) devices, and which enable new system capabilities. In addition, MEMS devices are designed and fabricated by techniques similar to those of very large-scale integration, and can be manufactured by traditional batch-processing methods. In this paper, the only device addressed is the electrostatic microswitch—perhaps the paradigm RF-MEMS device. Through its superior performance characteristics, the microswitch is being developed in a number of existing circuits and systems, including radio front-ends, capacitor banks, and time-delay networks. The superior performance combined with ultra-low-power dissipation and large-scale integration should enable new system functionality as well. Two possibilities addressed here are quasi-optical beam steering and electrically reconfigurable antennas.

We describe monocrystalline graphitic films, which are a few atoms thick but are nonetheless stable under ambient conditions, metallic, and of remarkably high quality. The films are found to be a two-dimensional semimetal with a tiny overlap between valence and conductance bands, and they exhibit a strong ambipolar electric field effect such that electrons and holes in concentrations up to 10(13) per square centimeter and with room-temperature mobilities of approximately 10,000 square centimeters per volt-second can be induced by applying gate voltage.

This second edition of Dr. Grove's book (the original was published in 2008) could arguably be considered a new work. At just under 1,000 pages (including the 11 appendices on the DVD), the second edition is 80% longer than the original. Frankly, the word "book" hardly seems adequate, considering the wide range of topics covered. "Mini-encyclopedia" seems more appropriate. The hardcover portion of the book comprises 18 chapters, and the DVD includes the aforementioned appendices plus 20 fully worked examples, 125 problems or exercises (with answers), and MATLAB routines for the simulation of many of the algorithms discussed in the main text. Here is a brief overview of the contents: ▸ Chapters 1–3: an overview of the diversity of positioning techniques and navigation systems; fundamentals of coordinate frames, kinematics and earth models; introduction to Kaiman filtering ▸ Chapters 4–6: inertial sensors, inertial navigation, and lower-cost dead reckoning systems ▸ Chapters 7–12: principles of radio positioning, short-, medium-, and long-range radio navigation, as well as extensive coverage of global navigation satellite systems (GNSS) ▸ Chapter 13: environmental feature matching. ▸ Chapters 14–16: various integration topics, including inertial navigation system (INS)/GNSS integration, alignment, zero-velocity updates, and multisensor integration ▸ Chapter 17: fault detection. ▸ Chapter 18: applications and trends. In summary, this book is an excellent reference (with numerous nuggets of wisdom) that should be readily handy on the shelf of every practicing navigation engineer. In the hands of an experienced instructor, the book will also serve students as a great textbook. However, the lack of examples integrated in the main text makes it difficult for the book to serve as a self-study guide for those that are new to the field.