ppxscal/embedding_network huggingface dataset:
A review on wireless home network technologies
Authors: K. Vaxevanakis, Th. Zahariadis, N. Vogiatzis
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2003)

Connecting residences to broadband access networks offers an unprecedented opportunity to extend the networking customer base beyond the satiated corporate environment. Yet despite this promising prospect, the market is evolving very tenuously: on one hand, there are numerous industrial consortia and standardization bodies that continue their work on independent and often non-interoperable specifications for residential networks; on the other hand, while there are multiple home PCs and multimedia network-enabled appliances, the majority of the houses can not support sophisticated interconnection, while most consumers are unwilling or cannot afford a large scale home rewiring. Among many competing technologies, wireless networks can resolve the rewiring issue capturing a major percentage of the Home Network market. In this paper, we review the available technologies in the home network area, and provide a comparison of the wireless broadband in-home technologies
Digital image processing techniques for automatic textile quality control
Authors: M. Bennamoun, A. Bodnarova
Venue: Systems Analysis Modelling Simulation (2003)

This article dealth with a complex problem of textile quality control by the means of computer vision using advanced digital signal and image processing tools. An investigation into a computer vision solution to quality inspection of textiles suggested a texture analysis approach. Since each texture analysis method presents a different potential for analysis of textured textile images, a large number of standard approaches from this category was examined. By considering their advantages and potential for successful flaw detection performance in homogeneous and jacquard textiles, six standard texture analysis techniques were identified for further investigation. A comprehensive examination and evaluation of these chosen techniques resulted. Normalised cross-correlation and SCLC approaches were identified as suitable candidates for real-time flaw detection in textiles with homogeneous structure.Inspection of jacquard textiles, however, presents a problem of greater complexity, the solution to which has not as yet been documented in the literature. To address this problem, a need for the application of a comprehensive cojoint spatial-spatial frequency approach was identified. A Gabor filter approach was chosen as a suitable representative of this class of techniques. This research then successfully applied optimised 2-D Gabor filters to the textile flaw detection problem and provided a further support of their suitability for this task.A novel optimised 2-D Gabor algorithm presented in this study is an automatic solution which is adaptable to detect a large variety of textile flaw types, both structural and tonal.
BINTEST - Binary Search-based Test Case Generation
Authors: Sami Beydeda, Volker Gruhn
Venue: Proceedings of the 27th Annual International Conference on Computer Software and Applications (2003)

One of the important tasks during software testing is thegeneration of test cases. Various approaches have beenproposed to automate this task. The approaches available,however, often have problems limiting their use. A problemof dynamic test case generation approaches, for instance,is that a large number of iterations can be necessary to obtaintest cases. This article proposes a novel algorithm forpath-oriented test case generation based on binary searchand describes a possible implementation.
Using game days to teach a multiagent system class
Authors: Leen-Kiat Soh
Venue: ACM SIGCSE Bulletin (2004)

Multiagent systems is an attractive problem solving approach that is becoming ever more feasible and popular in today's world. It combines artificial intelligence (AI) and distributed problem solving to allow designers (programmers and engineers alike) to solve problems otherwise deemed awkward in traditional approaches that are less flexible and centralized. In the Fall semester of 2002, I introduced a new game-based technique to my Multiagent Systems class. The class was aimed for seniors (with special permission) and graduate students in Computer Science, covering some breadth and depth of issues in multiagent systems. One of the requirements was participation in four Game Days. On each Game Day, student teams competed against each other in games related to issues such as auction, task allocation, coalition formation, and negotiation. This article documents my designs of and lessons learned from these Game Days. The Game Days were very successful. Through role-playing, the students were motivated and learned about multiagent systems.
Integrated Rate Control and Entropy Coding for JPEG 2000
Authors: Wei Yu
Venue: Proceedings of the Conference on Data Compression (2004)

In this paper, we present an Integrated Rate control and Entropy Coding (IREC) schemefor JPEG 2000. Based on an efficient heap-based rate allocation algorithm, the characteristicsof image content, the subband coefficinet and bitplane weighting models, and the user-specifiedoptimization criteria, the proposed IREC scheme can selectively perform entropy coding onlyon those parts of image data that are likely to be included in the final bitstream. Since entropycoding is the most time and power consuming part, the IREC scheme can then reduce theoverall computation and power consumption of JPEG 2000 encoding procedure. Both theoreticalanalysis and empirical results validate the advantages of the IREC scheme. For example, whenencoding the lenna color image with a targeted compression ratio of 128:1, compared withthe separate rate control and entropy coding schemes, about 93% savings in computation andpower consumption can be achieved on the entropy coding procedure.
A computer-assisted instruction approach to supplement the classroom instruction addressing mathematics of finance
Authors: Bradley S. Thomas
Venue:  (2002)

This three-week study examined the effects on student achievement and attitude using computer software as an alternative approach to homework exercises. The study involved three intact Mathematics Explorations classes and one intact Finite Mathematics class at Heartland Community College. All four classes addressed mathematics of finance during the study. The researcher hypothesized that using the software would produce a difference in achievement and attitude between the students accessing the software for homework exercises (treatment group) and the students taking the traditional approach of referencing the textbook for homework (comparison group). Two instructors volunteered to assist with the study. Each instructor taught two classes; the researcher did not instruct the classes during the study. An even distribution of students in the treatment and comparison groups existed for each class; some students chose not to participate. Achievement, measured by administering an exam at the end of the study, evaluated the student's ability to apply the appropriate mathematical model to a scenario. This was a paper and pencil exam requiring minimal computation. The researcher then compared the means of the exam scores between the treatment and comparison groups. The students' performance before the study was considered as a covariate to achievement and influenced the design of the sampling technique. A survey conducted at the end of the study measured the difference in attitudes between the treatment and comparison groups. The treatment and comparison group surveys used five questions to compare the attitudes between the two groups; the treatment group survey used six additional questions to monitor the student's anxieties, inconveniences, etc. while using the software. The researcher concluded that there was no evidence for a difference in achievement and attitude between students accessing the Mathematics of Finance Software for their homework assignment and students referencing the textbook for their homework assignment.
A decision support system for the electrical power districting problem
Authors: Paul K. Bergey, Cliff T. Ragsdale, Mangesh Hoskote
Venue: Decision Support Systems (2003)

Many national electricity industries around the globe are being restructured from regulated monopolies to deregulated marketplaces with competitive business units. The business units responsible for transmission and distribution must be given physical property rights to certain parts of the power grid in order to provide reliable service and make effective business decisions. However, partitioning a physical power grid into economically viable districts (distribution companies) involves many considerations. We refer to this complex problem as the electrical power districting problem (EPDP). This research identifies the fundamental characteristics required to appropriately model and solve an EPDP. The proposed solution methodology is implemented as a decision support system (DSS) featuring a visualization tool that allows decision makers (DMs) to explore what we refer to as a "soft efficient frontier." This DSS was found to effectively support DMs at The World Bank in solving an EPDP in the context of a case study for the Republic of Ghana.
Asap for developing adaptive software within dynamic heterogeneous environments
Authors: Matt W. Mutka
Venue:  (2003)

As the improvement of hardware technology and increased deployment of wireless infrastructures, computer systems are increasingly heterogeneous and dynamic. Heterogeneity and dynamic raise several challenges for software developers and users. Such challenges are software portability, software or computing environments configuration, unexpected environments, and platforms with limited resources. A feasible approach for these challenges is to develop adaptive software that may be aware of environments and adapt itself. We propose and implement the adaptive software architecture project (ASAP), which includes the software framework (FRAME), Component/Constraint Markup Language (CSML), and on-line adaptation, for the challenges under dynamic heterogeneous environments. Software may have a list of constraints for the environment. During execution, software may use the list to determine whether the environmental changes, and then the software responds accordingly. ASAP may support applications in different domains, including ad hoc systems that are temporarily organized. FRAME provides the APIs for adding adaptation to software. The adaptation and functionality of software are separately specified and implemented under FRAME, and hence, lessen development complexity. To further alleviate the complexity of developing adaptive software under FRAME, a high-level adaptive software specification language, CSML, may be used to specify the architecture of the software system and the constraints. The code for adaptation will be automatically generated by CSML. Then, developers only need to inherit the generated code to implement the functionality. To avoid an unnecessary performance impact, ASAP uses two different on-line adaptation schemes, Brew and component reassembly, to let software respond to different scales of environmental changes. For small environmental changes, people may use Brew to repair the affected software without terminating the software. Otherwise, the execution of the software will be temporarily suspended to invoke the component reassembly, and then resumed with appropriate implementations of the components. Also, two approaches, partial reassembly and caching, are proposed to further reduce the performance impact of reassembly. Three different applications are used to evaluate various features of ASAP. The GO game demonstrate the basic features of ASAP, including distributed component assembly. The Java MPEG Player has time constraints, which may not be satisfied under certain conditions and may be repaired by Brew. The last application demonstrates how ASAP may be used to realize behavior-based approach for the adaptive robotic control systems. Different performance results are also presented and discussed.
Detailed Comparison of Dependability Analyses Performed at RT and Gate Levels
Authors: A. Ammari, R. Leveugle, M. Sonza-Reorda, M. Violante
Venue: Proceedings of the 18th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (2003)

Methods allowing a designer to perform early dependability analyses aim either at classifying the faults according to their main potential effect, or at analyzing more in depth the error propagation paths in the circuit. In the two cases, these methods can be applied at several description levels, starting from the behavioral level down to the gate level with back-annotation data. This paper compares results obtained at RT and gate levels. The advantages of combining an error propagation path analysis and a classification are also discussed.
Leveraging Visio for Adoption-Centric Reverse Engineering Tools
Authors: Qin Zhu, Yu Chen, Piotr Kaminski, Anke Weber, Holger Kienle, Hausi A. Müller
Venue: Proceedings of the 10th Working Conference on Reverse Engineering (2003)

There are many reasons why reverse engineering researchtools often fail to be evaluated or adopted in industry.Their rough user interfaces and poor interoperabilityare just two frequently mentioned issues. The aim of theACSE (Adoption-Centric Software Engineering) project,conducted at the University of Victoria, is to investigatehow some of these impediments can be overcome by buildingsoftware engineering tools on top of Commercial Off-The-Shelf (COTS) products.This paper outlines how to leverage Microsoft Visio fora software visualization and metrics tool. Software developersfamiliar with Visio only have to learn the reverseengineering specific functions introduced by our tools andcan take advantage of their existing, domain-independentVisio knowledge. Thus, compared to a stand-alone application,this Visio-based tool leverages the cognitive supportpreviously acquired by developers using Visio.
Local complexity of Boolean functions
Authors: A. V. Chashkin
Venue: Discrete Applied Mathematics (2004)

Classes of locally complex and locally simple functions are introduced. The classes are proved to be invariant with respect to polynomially equivalent complexity measures. A relationship is considered between proving that a function belongs to a class of locally complex functions and proving lower bounds for Boolean circuits, switching circuits, formulas, and π-circuits (formulas over the basis {&,V,-}).
Acquisition of large-scale surface light fields
Authors: Wei-Chao Chen, Lars Nyland, Anselmo Lastra, Henry Fuchs
Venue: ACM SIGGRAPH 2003 Sketches Applications (2003)

This sketch reports the development of an acquisition methodology to acquire high-resolution surface light fields of an office-size environment.
An inventory system of ameliorating items for price dependent demand rate
Authors: Biswajit Mondal, Asoke Kumar Bhunia, Manoranjan Maiti
Venue: Computers and Industrial Engineering (2003)

This study is concerned with the development of inventory model for ameliorating items. These items include the fast growing animals like duck, pigs, broiler, etc. in poultry farm, high breed fishes in bhery (pond), etc. When these items stay at farm or bhery or in the sales counter or distribution centre, the stock increases due to growth and decreases also due to death. As a result, both amelioration and deterioration effect are seen simultaneously for this type of inventory system. In this paper, we have developed an instantaneous replenishment inventory model of these ameliorating items for prescribed time period. The rate of amelioration follows the Weibull distribution and the demand rate is assumed to be a function of selling price of an item. Shortages are not allowed. The salvage values of deteriorated units due to death of such items and the cost for feeding the life stocks are taken into account. The model is numerically illustrated with the demand rate dependent linearly on the selling price of the item. Finally, the effect of amelioration as well as the deterioration on an inventory policy has been studied. The sensitivity of the average profit with respect to the amelioration parameters has also been presented with the help of Analysis of Variance method.
Semiparametric estimation based on parametric modeling of the cause-specific hazard ratios in competing risks
Authors: A. Suzukawa, N. Taneichi
Venue: Journal of Multivariate Analysis (2003)

This paper is intended as an investigation of estimating cause-specific cumulative hazard and cumulative incidence functions in a competing risks model. The proportional model in which ratios of the cause-specific hazards to the overall hazard are assumed to be constant (independent of time) is a well-known semiparametric model. We are here concerned with relaxation of the proportionality assumption. The set C of all causes are decomposed into two disjoint subsets of causes as C - C1 ∪ C2. The relative risk of cause A in the sub-causes C1 can be represented as a function defined by ratic of the cause-specific hazard of cause A to the sum of cause-specific hazards in the sub-causes C1. We call this function the risk pattern function of cause A in C1, and consider a semiparametric model in which risk pattern functions in C1 are not constant (independent of time) but those functional forms, except for finite-dimensional parameters, are known. Based on this model, semiparametric estimators are obtained, and estimated variances of them are derived by delta methods. We investigate asymptotic properties of the semiparametric estimators and compare them with the nonparametric estimators. The semiparametric procedure is illustrated with the radiation-exposed mice data set, which represents lifetimes and causes of death of mice exposed to radiation in two different environments.
Automatic Reassembly of Document Fragments via Context Based Statistical Models
Authors: Kulesh Shanmugasundaram, Nasir Memon
Venue: Proceedings of the 19th Annual Computer Security Applications Conference (2003)

Reassembly of fragmented objects from a collection ofrandomly mixed fragments is a common problem in classicalforensics. In this paper we address the digital forensicequivalent, i.e., reassembly of document fragments, usingstatistical modelling tools applied in data compression. Wepropose a general process model for automatically analyzinga collection fragments to reconstruct the original documentby placing the fragments in proper order. Probabilitiesare assigned to the likelihood that two given fragments areadjacent in the original using context modelling techniquesin data compression. The problem of finding the optimalordering is shown to be equivalent to finding a maximumweight Hamiltonian path in a complete graph. Heuristicsare designed and explored and implementation results providedwhich demonstrate the validity of the proposed technique.
Bootstrapping a data mining intrusion detection system
Authors: Daniel Barbará, Yi Li, Julia Couto, Jia-Ling Lin, Sushil Jajodia
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

The application of data mining techniques in intrusion detection has received a lot of attention lately. Most of the approaches require of a training phase based on the availability of labelled data, where the labels indicate whether the points correspond to normal events or attacks. Unfortunately, this labelled data is not readily available in practice. In this paper we present a novel method based in intersecting segments of unlabelled data and using the intersection as the base data for unsupervised learning (clustering). The clustering algorithm, along with a method to find outliers with respect to the base clusters form the basis for separation of unlabelled data into groups of points that are normal (attack-free) and points that correspond to attacks. We show that the technique is very sucessful in separating points of the data sets of the DARPA, Lincoln Labs evaluation of 1999.
Efficient multi-way text categorization via generalized discriminant analysis
Authors: Tao Li, Shenghuo Zhu, Mitsunori Ogihara
Venue: Proceedings of the twelfth international conference on Information and knowledge management (2003)

Text categorization is an important research area and has been receiving much attention due to the growth of the on-line information and of Internet. Automated text categorization is generally cast as a multi-class classification problem. Much of previous work focused on binary document classification problems. Support vector machines (SVMs) excel in binary classification, but the elegant theory behind large-margin hyperplane cannot be easily extended to multi-class text classification. In addition, the training time and scaling are also important concerns. On the other hand, other techniques naturally extensible to handle multi-class classification are generally not as accurate as SVM. This paper presents a simple and efficient solution to multi-class text categorization. Classification problems are first formulated as optimization via discriminant analysis. Text categorization is then cast as the problem of finding coordinate transformations that reflects the inherent similarity from the data. While most of the previous approaches decompose a multi-class classification problem into multiple independent binary classification tasks, the proposed approach enables direct multi-class classification. By using Generalized Singular Value Decomposition (GSVD), a coordinate transformation that reflects the inherent class structure indicated by the generalized singular values is identified. Extensive experiments demonstrate the efficiency and effectiveness of the proposed approach.
An Ocularist's Approach to Human Iris Synthesis
Authors: Aaron Lefohn, Brian Budge, Peter Shirley, Richard Caruso, Erik Reinhard
Venue: IEEE Computer Graphics and Applications (2003)

Human irises gain their appearance from a layered and highly complex structure that is difficult to model and render with conventional techniques. This article presents an approach that uses domain knowledge from the field of ocular prosthetics. In that field, ocularists create an artificial iris by painting many simple semitransparent layers. This methodology is translated into a simple and effective toolkit, which can be used to create and render realistic looking irises.
Motion Recognition Using Nonparametric Image Motion Models Estimated from Temporal and Multiscale Cooccurrence Statistics
Authors: R. Fablet, P. Bouthemy
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

Abstract--A new approach for motion characterization in image sequences is presented. It relies on the probabilistic modeling of temporal and scale cooccurrence distributions of local motion-related measurements directly computed over image sequences. Temporal multiscale Gibbs models allow us to handle both spatial and temporal aspects of image motion content within a unified statistical framework. Since this modeling mainly involves the scalar product between cooccurrence values and Gibbs potentials, we can formulate and address several fundamental issues: model estimation according to the ML criterion (hence, model training and learning) and motion classification. We have conducted motion recognition experiments over a large set of real image sequences comprising various motion types such as temporal texture samples, human motion examples, and rigid motion situations.