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"abstract": "It has recently been shown that if we twist an arbitrary subset of edges of a mesh on an orientable surface, the resulting extended graph rotation system (EGRS) can be used to induce a cyclic weaving on the surface. In extended graph rotation systems, an edge is viewed as a paper strip that can be twisted. The sides of the paper strips provide ``two strands'' to construct weaving structures. Either these strands are ``parallel'' to the mesh edge for an ``untwisted edge'', or they both cross over the edge and over each other for a ``twisted edge''. If an arbitrary subset of edges of a mesh on an orientable surface is twisted in the same helical sense, then the EGRS induces a cyclic plain-weaving on the surface, which consists of cycles that cross other cycles (or themselves) by alternatingly going over and under. In this paper, we show that it is always possible to create a single-cycle plain-weaving starting from a mesh on an arbitrary surface, by selecting an appropriate subset of edges to be twisted. We also demonstrate how, starting from a mesh, to construct a large number of single-cycle plain-woven objects. Interestingly, the single-cycle solutions with a minimal number of edge twists correspond to plain-woven objects that are visually similar to Celtic knots. For converting plain-weaving cycles to 3D thread structures, we extend the original projection method, which previously worked only when all mesh edges are twisted. With the extension described here, our projection method can also be used to handle untwisted edges. We have developed a system that converts any manifold mesh into single-cycle plain-woven objects, by interactively controlling the proportion of edges that are twisted. The system also allows us to change the shapes of the threads with a set of parameters, interactively in real-time. We demonstrate here that by using this system, we can create a wide variety of single-cycle plain-woven objects.",
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"abstract": "Although the application of sketch-based chart annotation is not pervasive in management, the use of sketchmarks can provide numerous benefits to managerial discussions. The collaborative use of chart annotations can support management teams in their decision making based on quantitative charts by visually eliciting and capturing interpretation processes, clarifying basic assumptions, stimulating different perspectives, and extrapolating trends into the future. Sketch-based annotations combine the simplicity and immediacy of drawing with the clarity and richness of charting. In this paper, we provide the rationale for this under-researched visual management and communication practice, illustrate it through examples, and - as our main contribution - provide a first overview classification of the different sketchmarks that management groups can use in their discussion of quantitative charts (for such contexts as strategy or project reviews). In the end of the paper we briefly describe our future research in this area and highlight implications for management.",
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"title": "2014 IEEE International Conference on Healthcare Informatics (ICHI)",
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"title": "Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making",
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"abstract": "Background: Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective: The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method: After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results: We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion: Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application: Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.",
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{
"abstractType": "Regular",
"content": "Background: Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective: The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method: After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results: We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion: Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application: Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.",
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"normalizedAbstract": "Background: Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective: The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method: After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results: We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion: Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application: Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.",
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"Antibiotics",
"Cognition",
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"Clinical Decision Support",
"Heuristics",
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"Decision Task In Medicine",
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"fullName": "Roosan Islam",
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"content": "There are two major difficulties in the indefinite multi-objective decision making process: As the information about attributes is indefinite, how to express the indefinite information; as the information has multi-channels, how to fuse the information into synthetic information. The multiple-valued intuitive fuzzy sets is one new mathematical model, this model can process well fuzzy information gained from multi-sources. In this article, firstly conduct the research to the multiple-valued intuitive fuzzy set's information fusion and construct some methods to fuse the information included in the degree of membership or non-degree of membership of multiple-valued intuitive fuzzy set , then use the isomorphism mind to research indefinite isomerism multi-objective decision making and construct one new algorithm for interval value and indefinite language isomerism multi-objective decision making based on isomorphism information fusion.",
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"abstract": "Viscoelastic materials, such as gels, gelatin, and mucus, are increasingly present in movies and games. One common method to simulate this kind of fluid is the Smoothed Particle Hydrodynamics (SPH) using a velocity correction which limits the fluid deformation providing visually consistent results. However, it is very time-consuming. This paper presents the acceleration of viscoelastic SPH using graphics processing unit using CUDA being able to simulate a large number of particles, up to 1 million. The method was implemented as an extension of the DualSPHysics open source project and the performance was compared to an OpenMP implementation, being able to achieve an average of 7.76 speedup.",
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"abstract": "DNA@Home is a volunteer computing project that aims to use Gibbs Sampling for the identification and location of DNA control signals on full genome-scale datasets. A fault tolerant and asynchronous implementation of Gibbs sampling using the Berkeley Open Infrastructure for Network Computing (BOINC) was used to identify the location of binding sites of the SNAI1 (Snail) and SNAI2 (Slug) transcription factors across the human genome. Genes regulated by Slug but not Snail, and genes regulated by Snail but not Slug provided two datasets with known motifs. These datasets contained up to 994 DNA sequences which to our knowledge is largest scale use of Gibbs sampling for discovery of binding sites. 1000 parallel sampling walks were used to search for the presence of 1, 2 or 3 possible motifs using small, medium, and full size sets of these sequences. These runs were performed over a period of two months using over 1500 volunteered computing hosts and generated over 2.2 Terabytes of sampling data. High performance computing resources were used for post processing. This paper presents intra and inter walk analyses used to determine walk convergence. The results were validated against current biological knowledge of the Snail and Slug promoter regions and present avenues for further biological study.",
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"abstract": "Recent advances in DNA sequencing technology have enabled Next Generation Sequencing (NGS) instruments to accelerate generating billions of DNA reads in a few days. However, the management of enormous NGS data and the concurrent analysis of these vast amount of data requires a great deal of computing power and memory as well as huge disk storage. Current popular job scheduling systems provide efficient ways for managing and scheduling vast amount of analysis based on the available computing resources but don't consider the maximum amount of Input/Output (I/O). Thus, when executing large number of genome analysis on a large scale cluster system, the maximum bandwidth of storage I/O is insufficient to utilize all computing resources so the analysis jobs are frequently suspended. Here we developed a disk I/O aware job submission scheduler to maximize disk I/O usage but not hampering previously running jobs due to the heavy disk I/O of a new job. And we constructed a cancer genome analysis pipeline by using our I/O aware scheduler and HPC resources in National Institute of Supercomputing and Networking (NISN) to overcome the obstacles of concurrent analysis for vast amount of NGS data. Based on our I/O aware job submission scheduler, we performed major genome analyses on over 50 case-control pairs of chromophobe renal cell carcinoma patients whole genome samples sequenced by The Cancer Genome Atlas (TCGA) and successfully completed all analysis jobs while maintaining no jobs to be suspended by I/O bottleneck.",
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"content": "Recent advances in DNA sequencing technology have enabled Next Generation Sequencing (NGS) instruments to accelerate generating billions of DNA reads in a few days. However, the management of enormous NGS data and the concurrent analysis of these vast amount of data requires a great deal of computing power and memory as well as huge disk storage. Current popular job scheduling systems provide efficient ways for managing and scheduling vast amount of analysis based on the available computing resources but don't consider the maximum amount of Input/Output (I/O). Thus, when executing large number of genome analysis on a large scale cluster system, the maximum bandwidth of storage I/O is insufficient to utilize all computing resources so the analysis jobs are frequently suspended. Here we developed a disk I/O aware job submission scheduler to maximize disk I/O usage but not hampering previously running jobs due to the heavy disk I/O of a new job. And we constructed a cancer genome analysis pipeline by using our I/O aware scheduler and HPC resources in National Institute of Supercomputing and Networking (NISN) to overcome the obstacles of concurrent analysis for vast amount of NGS data. Based on our I/O aware job submission scheduler, we performed major genome analyses on over 50 case-control pairs of chromophobe renal cell carcinoma patients whole genome samples sequenced by The Cancer Genome Atlas (TCGA) and successfully completed all analysis jobs while maintaining no jobs to be suspended by I/O bottleneck.",
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"abstract": "Pairwise Whole Genome Alignment (WGA) is a crucial first step to understanding evolution at the DNA sequence-level. Pairwise WGA of thousands of currently available species genomes could help make biological discoveries, however, computing them for even a fraction of the millions of possible pairs is prohibitive - WGA of a single pair of vertebrate genomes (human-mouse) takes 11 hours on a 96-core Amazon Web Services (AWS) instance (c5.24xlarge). This paper presents SegAlign - a scalable, GPU-accelerated system for computing pairwise WGA. SegAlign is based on the standard seed-filter-extend heuristic, in which the filtering stage dominates the runtime (e.g. 98% for human-mouse WGA), and is accelerated using GPU(s). Using three vertebrate genome pairs, we show that SegAlign provides a speedup of up to 14× on an 8-GPU, 64-core AWS instance (p3.16xlarge) for WGA and nearly 2.3× reduction in dollar cost. SegAlign also allows parallelization over multiple GPU nodes and scales efficiently.",
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"abstract": "As a powerful unsupervised learning method, Generative Adversarial Network (GAN) plays an important role in many domains such as video prediction and autonomous driving. It is one of the ten breakthrough technologies in 2018 reported in MIT Technology Review. However, training a GAN imposes three more challenges: (1) intensive communication caused by complex train phases of GAN, (2) much more ineffectual computations caused by special convolutions, and (3) more frequent off-chip memory accesses for exchanging inter-mediate data between the generator and the discriminator. In this paper, we propose LerGAN, a PIM-based GAN accelerator to address the challenges of training GAN. We first propose a zero-free data reshaping scheme for ReRAM-based PIM, which removes the zero-related computations. We then propose a 3D-connected PIM, which can reconfigure connections inside PIM dynamically according to dataflows of propagation and updating. Our proposed techniques reduce data movement to a great extent, avoiding I/O to become a bottleneck of training GANs. Finally, we propose LerGAN based on these two techniques, providing different levels of accelerating GAN for programmers. Experiments shows that LerGAN achieves 47.2×, 21.42× and 7.46× speedup over FPGA-based GAN accelerator, GPU platform, and ReRAM-based neural network accelerator respectively. Moreover, LerGAN achieves 9.75×, 7.68× energy saving on average over GPU platform, ReRAM-based neural network accelerator respectively, and has 1.04× energy consuming over FPGA-based GAN accelerator.",
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"abstract": "In this work, we introduce a novel method for video temporal irregularity detection using the discriminative framework of 3D convolutional generative adversarial networks (3D-GANs). Temporal irregularities indicate unusual video segments. Detecting such irregularities is essential to video analysis applications like video anomaly detection and video summarization. To detect temporal irregularities in videos we need to address two problems: 1) temporal irregularities are difficult to define, different situations have different irregularities, and 2) irregularities are scarce in videos. Therefore, we formulate video temporal irregularity detection as fake data detection via the discriminative framework of a designed 3D-GAN. This new formulation only employs regular videos during the training phase and detects irregularities according to the deviation estimated by the discriminator of 3D-GAN. We take regular videos as real data and construct a 3D-GAN to learn the distribution of regular videos during the training phase. Since testing data contain irregular videos or fake data, whose distribution is different from regular videos or real data, the trained discriminator of our networks is able to detect temporal regularities and irregularities. Experiments show that 3D-GANs outperforms 2D-GANs in temporal irregularity detection, and demonstrate the effectiveness and competitive performance of our approach on anomaly detection datasets.",
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"abstract": "Face synthesis has achieved advanced development by using generative adversarial networks (GANs). Existing methods typically formulate GAN as a two-player game, where a discriminator distinguishes face images from the real and synthesized domains, while a generator reduces its discriminativeness by synthesizing a face of photorealistic quality. Their competition converges when the discriminator is unable to differentiate these two domains. Unlike two-player GANs, this work generates identity-preserving faces by proposing FaceID-GAN, which treats a classifier of face identity as the third player, competing with the generator by distinguishing the identities of the real and synthesized faces (see Fig.1). A stationary point is reached when the generator produces faces that have high quality as well as preserve identity. Instead of simply modeling the identity classifier as an additional discriminator, FaceID-GAN is formulated by satisfying information symmetry, which ensures that the real and synthesized images are projected into the same feature space. In other words, the identity classifier is used to extract identity features from both input (real) and output (synthesized) face images of the generator, substantially alleviating training difficulty of GAN. Extensive experiments show that FaceID-GAN is able to generate faces of arbitrary viewpoint while preserve identity, outperforming recent advanced approaches.",
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"abstract": "Recent advances in Generative Adversarial Networks (GANs) have shown increasing success in generating photorealistic images. But they also raise challenges to visual forensics and model attribution. We present the first study of learning GAN fingerprints towards image attribution and using them to classify an image as real or GAN-generated. For GAN-generated images, we further identify their sources. Our experiments show that (1) GANs carry distinct model fingerprints and leave stable fingerprints in their generated images, which support image attribution; (2) even minor differences in GAN training can result in different fingerprints, which enables fine-grained model authentication; (3) fingerprints persist across different image frequencies and patches and are not biased by GAN artifacts; (4) fingerprint finetuning is effective in immunizing against five types of adversarial image perturbations; and (5) comparisons also show our learned fingerprints consistently outperform several baselines in a variety of setups.",
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"abstract": "Data visualization becomes a crucial component in data analytics, especially data exploration, understanding, and analysis. Effective data visualization impacts decision-making and aids in discovering and understanding relationships. It leads to benefits in data-intensive software development tasks e.g., feature engineering in machine learning-based software projects. However, it is unknown how visualizations are used in competitive programming. The idea of this paper is to report early results on what visualizations are prevalent in competitive programming. Grandmasters are the highest level reached in competitions (novice, expert, master, and grandmaster). Analyzing the visualizations of 7 high-rank competitors (i.e., Grandmaster) in Kaggle, we identify and present a catalog of visualizations used to both tell a story from the data, as well as explain the process and pipelines involved to explain their coding solutions. Our taxonomy includes nine types from over 821 visualizations in 68 instances of Jupyter notebooks. Furthermore, most visualizations are for data analysis for distribution (DA Distribution), and frequency (DA Frequency) are most used. We envision that this catalog can be useful to better understand different situations in which to employ these visualizations.",
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"content": "Data visualization becomes a crucial component in data analytics, especially data exploration, understanding, and analysis. Effective data visualization impacts decision-making and aids in discovering and understanding relationships. It leads to benefits in data-intensive software development tasks e.g., feature engineering in machine learning-based software projects. However, it is unknown how visualizations are used in competitive programming. The idea of this paper is to report early results on what visualizations are prevalent in competitive programming. Grandmasters are the highest level reached in competitions (novice, expert, master, and grandmaster). Analyzing the visualizations of 7 high-rank competitors (i.e., Grandmaster) in Kaggle, we identify and present a catalog of visualizations used to both tell a story from the data, as well as explain the process and pipelines involved to explain their coding solutions. Our taxonomy includes nine types from over 821 visualizations in 68 instances of Jupyter notebooks. Furthermore, most visualizations are for data analysis for distribution (DA Distribution), and frequency (DA Frequency) are most used. We envision that this catalog can be useful to better understand different situations in which to employ these visualizations.",
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"abstract": "This paper presents a new approach allowing one or more projectors to display an undistorted image on a surface of unknown geometry. To achieve this, a single camera is used to capture the viewer?s perspective of the projection surface. No explicit camera and projector calibration is required since only their relative geometries are computed using structured light patterns. There is no specific constraint on the position or the orientation of the projectors and the camera with respect to the projection surface, except that the area visible to the camera must be covered by the projectors. The procedure defines a function establishing the correspondence of each pixel of a projector image to a pixel of the camera image. After the mapping of each projector has been carried out, one can display an image corrected in real-time for the point of view of an observer, which takes into account his position, the surface distortion, and the projector position and orientation. This method automatically takes into account any distortion in the projector lenses. Typical applications of this method include projection in small rooms, shadow elimination and wide screen projection using multiple projectors. Intensity blending can be combined to our method to ensure minimal visual artifacts. The implementation has shown convincing results for many configurations.",
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"abstract": "In this paper we present a novel technique to calibrate multiple casually aligned projectors on a fiducial-free cylindrical curved surface using a single camera. We impose two priors to the cylindrical display: (a) cylinder is a vertically extruded surface; and (b) the aspect ratio of the rectangle formed by the four corners of the screen is known. Using these priors, we can estimate the display's 3D surface geometry and camera extrinsic parameters using a single image without any explicit display to camera correspondences. Using the estimated camera and display properties, we design a novel deterministic algorithm to recover the intrinsic and extrinsic parameters of each projector using a single projected pattern seen by the camera which is then used to register the images on the display from any arbitrary viewpoint making it appropriate for virtual reality systems. Finally, our method can be extended easily to handle sharp corners - making it suitable for the common CAVE like VR setup. To the best of our knowledge, this is the first method that can achieve accurate geometric auto-calibration of multiple projectors on a cylindrical display without performing an extensive stereo reconstruction.",
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"abstract": "This paper presents a vision-based geometric alignment system for aligning the projectors in an arbitrarily large display wall. Existing algorithms typically rely on a single camera view and degrade in accuracy¹ as the display resolution exceeds the camera resolution by several orders of magnitude. Naïve approaches to integrating multiple zoomed camera views fail since small errors in aligning adjacent views propagate quickly over the display surface to create glaring discontinuities. Our algorithm builds and refines a camera homography² tree to automatically register any number of uncalibrated camera images; the resulting system is both faster and significantly more accurate than competing approaches, reliably achieving alignment errors of 0.55 pixels on a 24-projector display in under 9 minutes. Detailed experiments compare our system to two recent display wall alignment algorithms, both on our 18 Megapixel display wall and in simulation. These results indicate that our approach achieves sub-pixel accuracy even on dis-plays with hundreds of projectors.",
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"content": "We proposed the way that can repeatedly evaluate the localization methods for moving sounds in the same condition regardless of a kind of methods and a number of microphones. And, we developed two-channel-based sound source localization integrated with a cross-power spectrum phase (CSP) analysis and EM algorithm. This one can localize several moving sounds and reduce localization error. Many sound source localization methods have already been developed. However, they could not be evaluated for moving sound in the same condition because it is hard to build database for moving sounds with accurate track information whenever making experiments. Also, to localize several moving sounds, conventional methods need a lot of microphone and/or prior information such as impulse response data. In this paper, we evaluated our sound localization method using 3D moving sound creation tool and confirmed that our method with two microphones can well localize the voices of a moving talker without impulse response data.",
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"abstract": "Interactive Evolutionary Computation is well known as an effective method to create media contents suited to user's preference and objectives to use. As one of the methods, we have already presented a method that creates sign sounds with Interactive Differential Evolution (IDE). In the user's evaluation process, the user selects better one from two presented media contents. In this study, to fundamentally investigate the efficacy of the IDE method, three listening experiments were performed, experiment 1 as comparing experiment, experiment 2 as re-evaluation for subjects themselves, and experiment 3 as re-evaluation for other subjects. Target of the creation with the IDE method was warning sign sounds. Ten males participated as subjects in the experiments. In the result of the experiment 2, gradual increase of the subjective fitness value was observed. In the result of the experiment 3, increase of the subjective fitness value was not observed. These results suggested that the IDE method has a possibility to create sign sounds suited to user's preference.",
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"abstract": "Even high-quality lenses suffer from optical aberrations, especially when used at full aperture. Furthermore, there are significant lens-to-lens deviations due to manufacturing tolerances, often rendering current software solutions like DxO, Lightroom, and PTLens insufficient as they don't adapt and only include generic lens blur models. We propose a method that enables the self-calibration of lenses from a natural image, or a set of such images. To this end we develop a machine learning framework that is able to exploit several recorded images and distills the available information into an accurate model of the considered lens.",
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"title": "Collimation Properties of Microstrip Patch Fed Dielectric Lens Antenna for Broadband Mobile Communication",
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"abstract": "This paper demonstrates collimation property of dielectric lens over a multiband set of small size patch antennas. The lenses provide collimation, wide angle steering and act as rugged radome providing an effective protection for the array. Lens antennas are better suited to an ocean environment and mobile communication applications. The primary radiator which is microstrip patch is designed at S band to provide the desired radiation source. The dielectric lens is designed as a secondary radiator to produce the desired collimation, with low insertion loss. The fabricated lens was tested with and without primary radiators, in an anechoic chamber. The experimental results obtained are in close agreement with the simulation results obtained from IE3D and are highly encouraging.",
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"title": "Effects of viewing conditions and rotation methods in a collaborative tabletop AR environment",
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"abstract": "In this paper, we investigate the effects of viewing conditions and rotation methods on different types of collaborative tasks in a tabletop AR environment in which two users are co-located. The viewing condition means how the manipulation of a tabletop world by one user is shown in the other users' view and the rotation method means what type of input devices is used to rotate the tabletop world for alternative orientations. Our experiment considered two different viewing conditions-consistent view and inconsistent view and two different rotation methods-direct turn and indirect turn. In the experiment, a 3D display environment called ¿Stereoscopic Collaboration in Augmented and Projective Environments (SCAPE)¿ was utilized as a test environment, and two tasks were considered: Lego-like block building task and text label selection task. The former was designed for synchronous and referring-strong type, and the latter was designed for asynchronous and orientation-strong type. As dependent variables, various objective and subjective measurements including task completion time, quality of task result, turn angle, and questionnaire were measured. According to the results, the viewing conditions had significant effects on several objective and subjective measurements. On task completion time, their effect for the synchronous task was opposite to that for the asynchronous task. On the other hand, the rotation methods had significant effects only on turn angle.",
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"abstractType": "Regular",
"content": "In this paper, we investigate the effects of viewing conditions and rotation methods on different types of collaborative tasks in a tabletop AR environment in which two users are co-located. The viewing condition means how the manipulation of a tabletop world by one user is shown in the other users' view and the rotation method means what type of input devices is used to rotate the tabletop world for alternative orientations. Our experiment considered two different viewing conditions-consistent view and inconsistent view and two different rotation methods-direct turn and indirect turn. In the experiment, a 3D display environment called ¿Stereoscopic Collaboration in Augmented and Projective Environments (SCAPE)¿ was utilized as a test environment, and two tasks were considered: Lego-like block building task and text label selection task. The former was designed for synchronous and referring-strong type, and the latter was designed for asynchronous and orientation-strong type. As dependent variables, various objective and subjective measurements including task completion time, quality of task result, turn angle, and questionnaire were measured. According to the results, the viewing conditions had significant effects on several objective and subjective measurements. On task completion time, their effect for the synchronous task was opposite to that for the asynchronous task. On the other hand, the rotation methods had significant effects only on turn angle.",
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"abstract": "We propose a novel method for generating test patterns that can be encoded efficiently using reseeding of LFSRbased schemes for hybrid BIST. Our focus is to reduce the number of deterministic tests while keeping their overall number of specified bits small and, thus, reduce the storage requirements for the LFSR seeds. The proposed solution is based on test function manipulation and generates a compact test set in which individual tests have a high number of unspecified bits. The method uses Binary Decision Diagrams (BDDs) and a modified version of the min-cost max-matching problem on graphs. The obtained experimental results clearly demonstrate the impact of the proposed ATPG algorithm in reducing the on-chip seed storage, when combined with the considered BIST schemes.",
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"content": "We propose a novel method for generating test patterns that can be encoded efficiently using reseeding of LFSRbased schemes for hybrid BIST. Our focus is to reduce the number of deterministic tests while keeping their overall number of specified bits small and, thus, reduce the storage requirements for the LFSR seeds. The proposed solution is based on test function manipulation and generates a compact test set in which individual tests have a high number of unspecified bits. The method uses Binary Decision Diagrams (BDDs) and a modified version of the min-cost max-matching problem on graphs. The obtained experimental results clearly demonstrate the impact of the proposed ATPG algorithm in reducing the on-chip seed storage, when combined with the considered BIST schemes.",
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