ppxscal/embedding_network huggingface dataset:
Testing of SoCs with Hierarchical Cores: Common Fallacies, Test Access Optimization, and Test Scheduling
Authors: Sandeep Goel, Erik Jan Marinissen, Anuja Sehgal, Krishnendu Chakrabarty
Venue: IEEE Transactions on Computers (2009)

Many system-on-chip (SOC) integrated circuits today contain hierarchical (parent) cores that have multiple levels of design hierarchy involving "child cores". Hierarchy imposes a number of constraints on the manner in which tests must be applied to parent cores and their child cores. However, most prior work on wrapper design, test access mechanism (TAM) optimization, and test scheduling are hierarchy-oblivious, i.e., these techniques treat all cores in an SOC at the same level of hierarchy. We first show that wrappers, TAMs and test schedules designed for non-hierarchical SOCs are not valid for SOCs with hierarchical cores. We next present two approaches for the efficient testing of SOC with hierarchical cores. In the first approach, an existing wrapper design is modified such that that all constraints imposed by the hierarchy are satisfied and full flexibility is provided for TAM optimization and test scheduling. The second approach is based on a hierarchy-aware wrapper architecture for parent cores that operates in two disjoint modes for the testing of parent and child cores. We show how an existing test-architecture design algorithm can be adapted for use with these two methods. Results for the ITC'02 SOC Test Benchmarks show that the first approach offers lower test application times while the second approach requires less area overhead.
SRAM dynamic stability: theory, variability and analysis
Authors: Wei Dong, Peng Li, Garng M. Huang
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

Technology scaling in sub-100nm regime has significantly shrunk the SRAM stability margins in data retention, read and write operations. Conventional static noise margins (SNMs) are unable to capture nonlinear cell dynamics and become inappropriate for state-of-the-art SRAMs with shrinking access time and/or advanced dynamic read-write-assist circuits. Using the insights gained from rigorous nonlinear system theory, we define the much needed SRAM dynamic noise margins (DNMs). The newly defined DNMs not only capture key SRAM nonlinear dynamical characteristics but also provide valuable design insights. Furthermore, we show how system theory can be exploited to develop CAD algorithms that can analyze SRAM dynamic stability characteristics three orders of magnitude faster than a brute-force approach while maintaining SPICE-level accuracy. We also demonstrate a parametric dynamic stability analysis approach suitable for low-probability cell failures, leading to three orders of magnitude runtime speedup for yield analysis under high-sigma parameter variations.
Mathematical model of IRIS replication mechanism for the simulation of tactical networks
Authors: Joe Mohorko, Matja Fras
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

The Multilateral Interoperability Programme (MIP) was established to promote more successful and better harmonized operational functions for international peace-keeping forces. The C2IEDM/JC3IEDM (Command and Control Information Exchange Data Model) ensures the interconnection of Command and Control Information Systems (C2ISs) throughout all levels, from the corps down to the lower ranks. The usability of C2ISs highly correlates with the capacities of data information carriers, and the need is growing for greater capacity and reliability of transmission media and cryptographic message security. Simulation of tactical networks is an important task in planning military missions. Such methodologies assure a higher probability of success during critical tactical operations. This article focuses on a new radio network modeling method for the C2IS, which is verified by the OPNET simulation environment. This modeling method can be used in tactical radio network planning and optimization processes.
Graph-based tools for microscopic cellular image segmentation
Authors: Vinh-Thong Ta, Olivier Lézoray, Abderrahim Elmoataz, Sophie Schüpp
Venue: Pattern Recognition (2009)

We propose a framework of graph-based tools for the segmentation of microscopic cellular images. This framework is based on an object oriented analysis of imaging problems in pathology. Our graph tools rely on a general formulation of discrete functional regularization on weighted graphs of arbitrary topology. It leads to a set of useful tools which can be combined together to address various image segmentation problems in pathology. To provide fast image segmentation algorithms, we also propose an image simplification based on graphs as a pre processing step. The abilities of this set of image processing discrete tools are illustrated through automatic and interactive segmentation schemes for color cytological and histological images segmentation problems.
Statistical Multisource-Multitarget Information Fusion
Authors: Ronald P. S. Mahler
Venue:  (2007)

This comprehensive resource provides you with an in-depth understanding of finite-set statistics (FISST) - a recently developed method which unifies much of information fusion under a single probabilistic, in fact Bayesian, paradigm. The book helps you master FISST concepts, techniques, and algorithms, so you can use FISST to address real-world challenges in the field. You learn how to model, fuse, and process highly disparate information sources, and detect and track non-cooperative individual/platform groups and conventional non-cooperative targets. You find a rigorous Bayesian unification for many aspects of expert systems theory. Moreover, the book presents systematic integral and differential calculus for multisource-multitarget problems, providing a methodology for devising rigorous new techniques. This accessible and detailed book is supported with over 3,000 equations, 90 clear examples, 70 explanatory figures, and 60 exercises with solutions.
MAkE: Multiobjective algorithm for k-way equipartitioning of a point set
Authors: Sriparna Saha, Susmita Sur-Kolay, Parthasarathi Dasgupta, Sanghamitra Bandyopadhyay
Venue: Applied Soft Computing (2009)

The classical problem of partitioning a given set of points, has applications in several areas such as facility location, scattered network, and in hierarchical design of VLSI circuits. While equipartitioning is traditionally associated with the single objective of minimum cutcost, the above application areas appear to demand more. In this paper, we introduce the problem of multiobjective k-way equipartitioning of a point set. Brief discussions on the above applications are followed by their generic formulation as a multiobjective k-way equipartitioning problem of a given point set. The non-commensurate multiobjective criteria addressed include (i) minimizing overall areas of the partitions, (ii) maximizing area of the individual partitions, (iii) minimizing the total compactness of the partitions, and (iv) minimizing the total geometric diversity of the obtained partitions. Since this optimization problem is computationally expensive in time and space, a technique based on genetic algorithm is proposed in order to obtain high quality results. Crossover and mutation operators specific to the k-way equipartitioning problem, have been designed and a new greedy operator named compaction is proposed to accelerate convergence. To illustrate the utility of the proposed formulation and the algorithm, a problem in VLSI layout design is considered. Results on synthetic data sets as well as those extracted from layouts of benchmark circuits demonstrate the effectiveness of the proposed multiobjective approach.
Performance Analysis of Gradient Adaptive Lattice Joint Processing Algorithm
Authors: Haibing Qi
Venue: Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics (2009)

Tracking speed and stability of adaptive gradient filtering algorithms represented by least mean square (LMS) are restricted for non-stationary circumstance. A joint processor which consist of the gradient lattice filter and transversal LMS linear combiner was designed, the performance of processor were investigated when the input signals were interfered by white noise, Volvo noise and pink noise respectively. The noise canceling computer simulation testified that the joint processor could get stabilization only after 20 iterative operations, and provide stronger ability to boost SNR of weak signal compared with transversal LMS filter. All the performance indices including tracking ability and convergence stability are superior to the transversal LMS algorithm in the same circumstance, and it needs less hardware resource.
Clean the graph before you draw it!
Authors: Serge Gaspers, Margaret-Ellen Messinger, Richard J. Nowakowski, Paweł Prałat
Venue: Information Processing Letters (2009)

We prove a relationship between the Cleaning problem and the Balanced Vertex-Ordering problem, namely that the minimum total imbalance of a graph equals twice the brush number of a graph. This equality has consequences for both problems. On one hand, it allows us to prove the NP-completeness of the Cleaning problem, which was conjectured by Messinger et al. [M.-E. Messinger, R.J. Nowakowski, P. Pralat, Cleaning a network with brushes, Theoret. Comput. Sci. 399 (2008) 191-205]. On the other hand, it also enables us to design a faster algorithm for the Balanced Vertex-Ordering problem [J. Kara, K. Kratochvil, D. Wood, On the complexity of the balanced vertex ordering problem, Discrete Math. Theor. Comput. Sci. 9 (1) (2007) 193-202].
Visualizing the Impact of 4on-Functional Requirements on Variants: A Case Study
Authors: Clotilde Rohleder
Venue: Proceedings of the 2008 Requirements Engineering Visualization (2008)

Developers must seriously address non-functional requirements (Quality of Service) in the production of software families that include variants for different customers. Most prior research in this area deals with design and implementation aspects such as mechanisms that help implement the variability in software architecture. Few researchers have addressed how to represent variability in non-functional requirements. Many representation models lack clarity in representing variants and explaining how non- functional requirements impact on them. e adopted the map model that represents variants clearly and we developed a way to visualize impact of non-functional requirements on variants. We propose in this paper a goal-driven approach of variability representation that captures the variability at both functional and non- functional requirements level
Taxonomy of exertion games
Authors: Florian 'Floyd' Mueller, Martin R. Gibbs, Frank Vetere
Venue: Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat (2008)

A new set of computationally-augmented games have emerged recently that require the user to move their body. These exertion games are believed to contribute to social, mental and in particular, physical benefits, marking a change in how we perceive computer gaming. However, although these games are a commercial success, research is lacking a theoretical understanding how to analyse existing and guide future designs. We present initial investigations towards a taxonomy of such exertion games with a focus on social aspects, based on work on traditional play and sports. Our contribution lays the foundation for the creation of a theoretical framework on exertion games, expanding our understanding of this exciting new area.
Architectures for supersystems of the '80s
Authors: Svetlana P. Kartashev, Steven I. Kartashev
Venue: Proceedings of the May 19-22, 1980, national computer conference (1980)

Several areas of science and technology offer a number of problems which solutions require an enormous computational power. For instance, partial differential equations in computational aerodynamics, real-time radar signal processing, control of fast and complex nuclear or chemical reactions, accurate weather prediction, etc., necessitate throughputs which are several orders of magnitude higher than those of existing complex parallel systems.
Mobile eLearning Platform for Interactive Patient Education
Authors: Joseph Finkelstein, Jeffrey Wood
Venue: Proceedings of the 2009 International Conference on Mobile, Hybrid, and On-line Learning (2009)

We developed an interactive patient learning system for use on mobile phones to inform an asthma patient about this chronic condition and enforce knowledge retention by questioning the user. The system uses a mobile phone's internet connection to retrieve information from a database and download recorded audio files corresponding to asthma information screens. The mobile application was successfully developed, implemented, and tested on the Motorola i730 mobile phone with Nextel as a service provider. The application can be utilized as a universal mobile eLearning platform for interactive patient education.
Efficient layered density-based clustering of categorical data
Authors: Bill Andreopoulos, Aijun An, Xiaogang Wang, Dirk Labudde
Venue: Journal of Biomedical Informatics (2009)

A challenge involved in applying density-based clustering to categorical biomedical data is that the ''cube'' of attribute values has no ordering defined, making the search for dense subspaces slow. We propose the HIERDENC algorithm for hierarchical density-based clustering of categorical data, and a complementary index for searching for dense subspaces efficiently. The HIERDENC index is updated when new objects are introduced, such that clustering does not need to be repeated on all objects. The updating and cluster retrieval are efficient. Comparisons with several other clustering algorithms showed that on large datasets HIERDENC achieved better runtime scalability on the number of objects, as well as cluster quality. By fast collapsing the bicliques in large networks we achieved an edge reduction of as much as 86.5%. HIERDENC is suitable for large and quickly growing datasets, since it is independent of object ordering, does not require re-clustering when new data emerges, and requires no user-specified input parameters.
Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support
Authors: Paul A. Harris, Robert Taylor, Robert Thielke, Jonathon Payne, Nathaniel Gonzalez, Jose G. Conde
Venue: Journal of Biomedical Informatics (2009)

Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
A meta user interface to control multimodal interaction in smart environments
Authors: Dirk Roscher, Marco Blumendorf, Sahin Albayrak
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2009)

Smart environments bring together multiple users, (interaction) resources and services. This creates complex and unpredictable interactive computing environments that are hard to understand. Users thus have difficulties to build up their mental model of such interactive systems. To address this issue users need possibilities to evaluate the state of these systems and to adapt them according to their needs. In this work we present our implementation of the functionalities to evaluate and control multimodal interaction in smart environments, which is accessible for users through a meta user interface.
Mental simulation for creating realistic behavior in physical security systems simulation
Authors: Volkan Ustun, Jeffrey S. Smith
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Mental simulation is proposed by cognitive psychologists as a candidate to model the human reasoning process. In this paper, we propose a methodology that models mental simulation to create realistic human behavior in simulated environments. This methodology is used to generate realistic intruder and guard behavior in physical security systems simulation. The behaviors include moving to a target while avoiding detection/capture for intruders and following and apprehending intruders for guards.
Leaf Powers and Their Properties: Using the Trees
Authors: Michael R. Fellows, Daniel Meister, Frances A. Rosamond, R. Sritharan, Jan Arne Telle
Venue: Proceedings of the 19th International Symposium on Algorithms and Computation (2008)

A graph G on n vertices is a k-leaf power ($G \in {\cal G}_{k}$) if it is isomorphic to a graph that can be "generated" from a tree T that has n leaves, by taking the leaves to represent vertices of G, and making two vertices adjacent if and only if they are at distance at most k in T. We address two questions in this paper:(1) As k increases, do we always have ${\cal G}_{k} \subseteq {\cal G}_{k+1}$ ? Answering an open question of Andreas Brandstädt and Van Bang Le [2,3,1], we show that the answer, perhaps surprisingly, is "no."(2) How should one design algorithms to determine, for k-leaf powers, if they have some property?One way this can be done is to use the fact that k-leaf powers have bounded cliquewidth. This fact, plus the FPT cliquewidth approximation algorithm of Oum and Seymour [14], combined with the results of Courcelle, Makowsky and Rotics [7], allows us to conclude that properties expressible in a general logic formalism, can be decided in FPT time for k-leaf powers, parameterizing by k. This is wildly inefficient. We explore a different approach, under the assumption that a generating tree is given with the graph. We show that one can use the tree directly to decide the property, by means of a finite-state tree automaton. (A more general theorem has been independently obtained by Blumensath and Courcelle [5].)We place our results in a general context of "tree-definable" graph classes, of which k-leaf powers are one particular example.
Stray Example Sheltering by Loss Regularized SVM and kNN Preprocessor
Authors: Chan-Yun Yang, Che-Chang Hsu, Jr-Syu Yang
Venue: Neural Processing Letters (2009)

This paper presents a new model developed by merging a non-parametric k-nearest-neighbor (kNN) preprocessor into an underlying support vector machine (SVM) to provide shelters for meaningful training examples, especially for stray examples scattered around their counterpart examples with different class labels. Motivated by the method of adding heavier penalty to the stray example to attain a stricter loss function for optimization, the model acts to shelter stray examples. The model consists of a filtering kNN emphasizer stage and a classical classification stage. First, the filtering kNN emphasizer stage was employed to collect information from the training examples and to produce arbitrary weights for stray examples. Then, an underlying SVM with parameterized real-valued class labels was employed to carry those weights, representing various emphasized levels of the examples, in the classification. The emphasized weights given as heavier penalties changed the regularization in the quadratic programming of the SVM, and brought the resultant decision function into a higher training accuracy. The novel idea of real-valued class labels for conveying the emphasized weights provides an effective way to pursue the solution of the classification inspired by the additional information. The adoption of the kNN preprocessor as a filtering stage is effective since it is independent of SVM in the classification stage. Due to its property of estimating density locally, the kNN method has the advantage of distinguishing stray examples from regular examples by merely considering their circumstances in the input space. In this paper, detailed experimental results and a simulated application are given to address the corresponding properties. The results show that the model is promising in terms of its original expectations.
Motion Detection Based on Background Modeling and Performance Analysis for Outdoor Surveillance
Authors: Tianci Huang, Jingbang Qiu, Takahiro Sakayori, Satoshi Goto, Takeshi Ikenaga
Venue: Proceedings of the 2009 International Conference on Computer Modeling and Simulation (2009)

Real-time segmentation of moving objects in video sequences is a fundamental step for surveillance systems. One of successful methods for complex background is to use a multi-color background model per pixel. However, Common problem for this approach is that it suffers from illumination changing environment, in addition, it is incapable of removing shadows of moving objects. This paper proposed an effective scheme to improve the adaptive background model for each pixel by introducing a background training parameter into every Gaussian model, and region-based scheme is applied to judgment by utilizing both spatial and temporal information. Experimental results will be presented to validate proposed algorithm keep robustness in the situation of illumination changes, shadow can be removed in foreground mask, results shows False Alarm Rate can be reduced from 34.9% to 35.8% while the overlap varies within normal range from 0.4 to 0.6 compared with conventional Gaussian mixture model.
Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems, 3rd ed. edition
Authors: Thomas Brunl
Venue:  (2008)

This book presents a unique combination of mobile robots and embedded systems, from introductory to intermediate level. It is structured in three parts, dealing with embedded systems (hardware and software design, actuators, sensors, PID control, multitasking), mobile robot design (driving, balancing, walking, and flying robots), and mobile robot applications (mapping, robot soccer, genetic algorithms, neural networks, behavior-based systems, and simulation). The book is written as a text for courses in computer science, computer engineering, IT, electronic engineering, and mechatronics, as well as a guide for robot hobbyists and researchers.
Simulation as a tool for life cycle cost analysis
Authors: Khaled Shahata, Tarek Zayed
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Life cycle cost is an essential approach to decide on alternative rehabilitation strategies for infrastructure systems. Monte Carlo simulation approach is used to develop a stochastic life cycle cost (SLCC) model and methodology in order to compare different rehabilitation scenarios/alternatives for infrastructures, such as water mains. The presented research in this paper identifies several rehabilitation methods for water mains, which are classified into three main categories: repair, renovation, and replacement. The developed model helps academics and practitioners (e.g. municipal engineers) to predict the suitable new installation and/or rehabilitation programs as well as their corresponding costs, thereby, to avoid any unpleasant surprises.