ppxscal/embedding_network huggingface dataset:
An Automatic Software Test-Data Generation Scheme Based on Data Flow Criteria and Genetic Algorithms
Authors: Andreas S. Andreou, Kypros A. Economides, Anastasis A. Sofokleous
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Software test-data generation research primarily focuses on using control flow graphs for producing an optimum set of test cases. This paper proposes the integration of a data flow graph module with an existing testing framework and the utilisation of a specially designed genetic algorithm for automatically generating test cases based on data flow coverage criteria. The enhanced framework aims to explore promising aspects of software testing that have not yet received adequate research attention, by exploiting the data information of a program and provide a different testing coverage approach compared to existing control flow-oriented ones. The performance of the proposed approach is assessed and validated on a number of sample programs of different levels of size and complexity. The associated experimental results indicate successful performance in terms of testing coverage, which is significantly better when compared to those of existing dynamic data flow-oriented test data generation methods.
Feature Abstraction of Time-Sequence Curve and Its Similarity Calculation
Authors: Guohe Li, Xi Jiang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Guohe Li Xi Jiang Department of Computer Science and Technology, China University of Petroleum(Beijing) Guohe_li@sina.com ricksmiles@sina.com Abstract Time-sequence data are visually shown in curves. A great deal of information can be derived from them, which lays the foundation for the recognition of curves. Along the x-axis direction and by means of averagely dividing 0 o ~180o into small intervals, standard codes are adopted to represent the general tendency of the curve. Based on standard codes, corresponding revisal codes are adopted to represent the deviation from them. The combination of the two-level codes describes the curve shape exactly. A similarity function is defined to compute the similarity between two curves, which in most cases are not of the same length. The method described above is proved effective in the recognition of sediment microfacies by well-logging curves from the Luliang Area of Xinjiang Kelamayi Oil Field.
An Industrial Perspective on Solid Modeling
Authors: W. Myers
Venue: IEEE Computer Graphics and Applications (1982)

A few solid modeling packages have reached the market, and early users like themmore are on the way. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
An Incremental Programming Environment
Authors: R. Medina-Mora
Venue: IEEE Transactions on Software Engineering (1981)

This paper describes an incremental programming environment (IPE) based on compilation technology, but providing facilities traditionally found only in interpretive systems. IPE provides a comfortable environment for a single programmer working on a single program.
Security analysis of a new multi-party payment protocol with intermediary service.
Authors: Mildrey Carbonell, Jose Maria Sierra, Joaquin Torres, Antonio Izquierdo
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Most of the electronic payment proposals found in the scientific literature are focused on a traditional two-domain business model: customer and merchant. However, an enhanced payment model with an intermediary entity could be considered, with the goal of providing additional advantages for the parties in the e-commerce scenario. In this article, we will show the utility of intermediary inside the payment process describing a service of centralization of the payment system (different to a gateway, TTP or connection broker) in a multi-party payment scenario. We illustrate how this service improves Internet selling applications security, which currently need an effort for facing the weaknesses of the different payments models.
Multiplicative updates for non-negative projections
Authors: Zhirong Yang, Jorma Laaksonen
Venue: Neurocomputing (2007)

We present here how to construct multiplicative update rules for non-negative projections based on Oja's iterative learning rule. Our method integrates the multiplicative normalization factor into the original additive update rule as an additional term which generally has a roughly opposite direction. As a consequence, the modified additive learning rule can easily be converted to its multiplicative version, which maintains the non-negativity after each iteration. The derivation of our approach provides a sound interpretation of learning non-negative projection matrices based on iterative multiplicative updates-a kind of Hebbian learning with normalization. A convergence analysis is scratched by interpretating the multiplicative updates as a special case of natural gradient learning. We also demonstrate two application examples of the proposed technique, a non-negative variant of the linear Hebbian networks and a non-negative Fisher discriminant analysis, including its kernel extension. The resulting example algorithms demonstrate interesting properties for data analysis tasks in experiments performed on facial images.
Value functions and error bounds of trust region methods
Authors: Wenling Zhao, Changyu Wang
Venue: Journal of Applied Mathematics and Computing (2007)

This paper studies some properties of the value functions and gives some sufficient and necessary conditions about the presented global error and local error. And it leads to one kind of relationship between iterative points and optimal solution or K-T point.
Visualisation of "High p, Small n" data
Authors: Y. E. Pittelkow, S. R. Wilson
Venue: Computational Statistics (2007)

Development of methods for visualisation of high-dimensional data where the number of observations, n, is small compared to the number of variables, p, is of increasing importance. One major application is the burgeoning field of microarray (gene expression) experiments. Because of their high cost, the number of chips (n) is O(10 ¿ 102) while the number (p) of genes (including expressed sequence tags) on each chip is O(103 ¿ 104). Based on synthetic data simulated in accord with current biological interpretation of microarray data, we have adapted the biplot that simultaneously plots the genes and the chips to display relevant experimental information. Other ordination techniques are also useful for visually exploring microarray data. The biological information that can be revealed by applying these exploratory, visual techniques is illustrated using data from gene expression experiments. When ordination methods, or dimension reduction methods such as PCA and its many variants, are used, in association with gene selection methods, it is well known that "selection bias" can result. We show an application of bootstrap methodology to ordination methods that can be used to account for this bias. Such methods are invaluable when visualization methods are used for pattern recognition, such as when identifying previously unknown sub-classes of tumours in molecular classification.
A First Step towards an Epistemology of the Subjective Uncertainty: Its Premises and Modeling
Authors: Fabio Campos, Andre Neves, Rodrigo Souza
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

The uncertainty may be divides it into two major groups, "objective uncertainty" and "subjective uncertainty". The objective uncertainty has already been extensively explored in works on classic probability, but this is not the case with subjective uncertainty, a field of knowledge where there is not even a well established epistemology. In this work we show a first step towards an epistemology of the subjective uncertainty, its premises, and also a way to model them. If a system fails to model all the premises it will not be able to generically model the subjective uncertainty. This is what happens, for example, with the rules of combination until now used within the Dempster-Shafer Theory, one of the formal models that deals with subjective uncertainty. The Dempster-Shafer Theory provides a method for com- bining evidence from different sources without prior know- ledge of their distributions, however, it has some pitfalls caused by an incomplete modeling of the premises. In this paper we present a method that models the three subjective uncertainty premises (the explicit lack of knowledge, the conflict among the evidence, and the non- uniqueness of the assignment of belief and relative divi- sion of the belief among the hypotheses chosen), extend- ing the Dempster-Shafer Theory, correcting its counter- intuitive behavior, and allowing its use in a broad range of situations.
Error-Aware Design
Authors: Fadi Kurdahi, Ahmed Eltawil, Amin K. Djahromi, Mohammad Makhzan, Stanley Cheng
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

The universal underlying assumption made today is that Systems on chip must maintain 100% correctness regardless of the application. This work advocates the concept that some applications - by construction - are inherently error tolerant and therefore do not require this strict bound of 100 % correctness. In such cases, it is possible to exploit this tolerance by aggressively reducing the supply voltage, thereby reducing power consumption significantly. This approach is demonstrated on several case studies in imaging, video and wireless communication fields.
High-Level Computer Architecture
Authors: Yaohan Chu
Venue: Computer (1981)

Associated with each programming language is a computer architecture that executes programs in that language. If the language is a low-level instruction set, the associated computer architecture is a low-level von Neumann architecture; if the language is high-level, the associated architecture is high-level. The internal structure of a high-level architecture reflects the constructs of the high-level language. The articles in this special issue deal with high-level computer architecture. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Undercomplete Blind Subspace Deconvolution
Authors: Zoltán Szabó, Barnabás Póczos, András Lőrincz
Venue: The Journal of Machine Learning Research (2007)

We introduce the blind subspace deconvolution (BSSD) problem, which is the extension of both the blind source deconvolution (BSD) and the independent subspace analysis (ISA) tasks. We examine the case of the undercomplete BSSD (uBSSD). Applying temporal concatenation we reduce this problem to ISA. The associated `high dimensional' ISA problem can be handled by a recent technique called joint f-decorrelation (JFD). Similar decorrelation methods have been used previously for kernel independent component analysis (kernel-ICA). More precisely, the kernel canonical correlation (KCCA) technique is a member of this family, and, as is shown in this paper, the kernel generalized variance (KGV) method can also be seen as a decorrelation method in the feature space. These kernel based algorithms will be adapted to the ISA task. In the numerical examples, we (i) examine how efficiently the emerging higher dimensional ISA tasks can be tackled, and (ii) explore the working and advantages of the derived kernel-ISA methods.
SET Emulation Under a Quantized Delay Model
Authors: Mario Garcia Valderas, Raul Fernandez Cardenal, Celia Lopez Ongil, Marta Portela Garcia, Luis Entrena
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

Single Event Transient (SET) fault analysis is usually performed trough digital simulation at the gate level. However, this method cannot be used for large fault injection campaigns, since gate level simulation is quite slow. In this paper, we propose an approach to build an FPGA based SET emulator, which implements a quantized delay model of the circuit under evaluation. Experimental results demonstrate that the quantized delay model produces accurate results and can be easily captured in a FPGA. The proposed approach can be automated to increase SET fault analysis performance by three orders of magnitude with respect to simulation.
Terrain Classification Using Clustering Algorithms
Authors: Dong-Min Woo, Dong-Chul Park, Young-Soo Song, Quoc-Dat Nguyen, Quang-Dung Nguyen Tran
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Texture analysis has been efficiently utilized in the area of terrain classification. The widely used co-occurrence features have been reported most effective for this application. Since the number of co-occurrence features is very high, a terrain classifier based on co-occurrence features should deal with high dimensionality problem. This paper deals with how to solve high dimensionality problems by employing a conventional linear discriminant classifier and clustering algorithms based on ANN (Artificial Neural Network). A implemented linear discriminant classifier is based on dimensionality reduction by using FST (Foley- Sammon transform), and its result is compared with ANN clustering algorithm FCM (Fuzzy C-mean). Experimental results show that the overall classification accuracy using clustering algorithm is good, especially for some particular classes.
The Software Life Cycle A Management and Technological Challenge in the Department of Defense
Authors: B. C. De Roze
Venue: IEEE Transactions on Software Engineering (1978)

The importance of software in defense systems continues to intensify as new systems emerge in response to increasing threats and declining force levels. The need to manage this software as a critical component of defense systems over their life cycle is becoming widely recognized. A general awareness of this need as an institutional problem requiring special attention within the Office of the Secretary of Defense has been growing as software problems have reached top level defense management visibility with increasing regularity. Software costs are continuing to multiply in step with advancing weapons systems sophistication, and opportunities for cost avoidance now are leveraged against large dollar investments. These conditions characterize the computer industry at large, but very little overall focus has been visible to improve the software development process. Consequently, the Department of Defense (DoD) has undertaken a two part effort to accelerate both near-term and long-term improvements in software development for weapons system applications. These efforts, the establishment of software life cycle management policy and practices, and the vigorous development and application of new software technology are discussed in considerable depth.
An Adaptive Inter-Mobility Supports Scheme for NetLMM
Authors: Jong-Hyouk Lee, Joong-Hee Lee, Tai-Myoung Chung
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

In this paper, we propose an adaptive intermobility supports scheme for Network-based Localized Mobility Management (NetLMM). The NetLMM approach uses Proxy Mobile IPv6 (PMIPv6) technique and employs a PMIP client to manage a mobile node (MN) within a local mobility domain (LMD). The distinguishing mark is that an MN does not need to have a mobility stack for mobility supports within the NetLMM approach. However, the NetLMM approach has not provided an inter-mobility, where the MN hands off between the LMDs. Thus, in this paper, we propose the adaptive inter-mobility supports scheme where an MN hands off between the LMDs even though the MN does not have the mobility stack. In the proposed scheme, the old LMA recognizes that the MN has been moved into a specific LMA and then the old LMA forwards the packets destined to the MN to the specific LMA. Thus, the proposed scheme provides a seamless handoff service and inter-mobility supports.
The Agents Are All Busy Doing Stuff!
Authors: Peter McBurney, Michael Luck
Venue: IEEE Intelligent Systems (2007)

In answer to the question, "Where have all the agents gone?" this column asserts that agent technologies are pervasive, not missing.
Temporal Interaction Contracts for Components in a Distributed System
Authors: Omakr J. Tilak, Rajeev R. Raje
Venue: Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference (2007)

Software realization of distributed computing systems is typically achieved through the component-based software development approach. Thus, software executing on such distributed systems consists of many autonomous components which interact with each other to coordinate their activities. The need for such coordination along with requirements such as heterogeneity, scalability, security, and availability, considerably increases the complexity of code in distributed systems. Simplifying distributed component-based software development requires abstractions at various levels that enable separate design and specification of component interactions and the components themselves. This paper depicts a method to specify component interactions involving temporal invocation constraints. Based on the knowledge of component interactions, two types of replaceability criteria are defined and empirically evaluated.
Inference of Genetic Regulatory Networks with Recurrent Neural Network Models Using Particle Swarm Optimization
Authors: Rui Xu, Donald Wunsch II, Ronald Frank
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2007)

Genetic regulatory network inference is critically important for revealing fundamental cellular processes, investigating gene functions, and understanding their relations. The availability of time series gene expression data makes it possible to investigate the gene activities of whole genomes, rather than those of only a pair of genes or among several genes. However, current computational methods do not sufficiently consider the temporal behavior of this type of data and lack the capability to capture the complex nonlinear system dynamics. We propose a recurrent neural network (RNN) and particle swarm optimization (PSO) approach to infer genetic regulatory networks from time series gene expression data. Under this framework, gene interaction is explained through a connection weight matrix. Based on the fact that the measured time points are limited and the assumption that the genetic networks are usually sparsely connected, we present a PSO-based search algorithm to unveil potential genetic network constructions that fit well with the time series data and explore possible gene interactions. Furthermore, PSO is used to train the RNN and determine the network parameters. Our approach has been applied to both synthetic and real data sets. The results demonstrate that the RNN/PSO can provide meaningful insights in understanding the nonlinear dynamics of the gene expression time series and revealing potential regulatory interactions between genes.
Topological Properties in Covering-Based Rough Sets
Authors: William Zhu, Fei-Yue Wang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

In covering setting, there are five types of rough set mod- els in literature, but only one type of them has been studied from the point of topological view. In this paper, we ad- dress the topological properties in the other four types of covering-based rough sets; especially we present the condi- tions under which lower approximation operations become interior operators and the conditions under which the upper approximation operations become closure operators.
Boolean representation based data-adaptive correlation analysis over time series streams
Authors: Tiancheng Zhang, Dejun Yue, Yu Gu, Ge Yu
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Correlation analysis is a basic problem in the field of data stream mining. Typical approaches add sliding window to data streams to get the recent results, but the window length defined by users is always fixed which is not suitable for the changing stream environment. We propose a Boolean representation based data-adaptive method for correlation analysis among a large number of time series streams. The periodical trends of each stream series to are monitored to choose the most suitable window size and group the series with the same trends together. Instead of adopting complex pair-wise calculation, we can also quickly get the correlation pairs of series at the optimal window sizes. All the processing is realized by simple Boolean operations. Both the theory analysis and the experimental evaluations show that our method has good computation efficiency with high accuracy.
High performance combinatorial algorithm design on the Cell Broadband Engine processor
Authors: David A. Bader, Virat Agarwal, Kamesh Madduri, Seunghwa Kang
Venue: Parallel Computing (2007)

The Sony-Toshiba-IBM Cell Broadband Engine (Cell/B.E.) is a heterogeneous multicore architecture that consists of a traditional microprocessor (PPE) with eight SIMD co-processing units (SPEs) integrated on-chip. While the Cell/B.E. processor is architected for multimedia applications with regular processing requirements, we are interested in its performance on problems with non-uniform memory access patterns. In this article, we present two case studies to illustrate the design and implementation of parallel combinatorial algorithms on Cell/B.E.: we discuss list ranking, a fundamental kernel for graph problems, and zlib, a data compression and decompression library. List ranking is a particularly challenging problem to parallelize on current cache-based and distributed memory architectures due to its low computational intensity and irregular memory access patterns. To tolerate memory latency on the Cell/B.E. processor, we decompose work into several independent tasks and coordinate computation using the novel idea of Software-Managed threads (SM-Threads). We apply this generic SPE work-partitioning technique to efficiently implement list ranking, and demonstrate substantial speedup in comparison to traditional cache-based microprocessors. For instance, on a 3.2GHz IBM QS20 Cell/B.E. blade, for a random linked list of 1 million nodes, we achieve an overall speedup of 8.34 over a PPE-only implementation. Our second case study, zlib, is a data compression/decompression library that is extensively used in both scientific as well as general purpose computing. The core kernels in the zlib library are the LZ77 longest subsequence matching algorithm and Huffman data encoding. We design efficient parallel algorithms for these combinatorial kernels, and exploit concurrency at multiple levels on the Cell/B.E. processor. We also present a Cell/B.E. optimized implementation of gzip, a popular file-compression application based on the zlib library. For our Cell/B.E. implementation of gzip, we achieve an average speedup of 2.9 in compression over current workstations.