ppxscal/embedding_network huggingface dataset:
Designing a combinatorial java unit testing tool
Authors: Kamal Zuhairi Zamli, Nor Ashidi Mat Isa, Mohammed Fadel Jamil Klaib, Siti Norbaya Azizan
Venue: Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology (2007)

Software testing relates to the process of executing a program or system with the intent of finding errors. Covering as much as 40 to 50 percent of the development costs and resources, software testing is an integral part of the software development lifecycle. Despite its importance, current software testing practice lacks automation and is still primarily based on highly manual processes from the generation of test cases (i.e. from the specifications documents) up to the actual execution of the test. Although the emergence of helpful automated testing tools in the market is blooming, their adoptions are lacking as they do not adequately provide the right level of abstraction and automation required by test engineers. JTst is a Java based automated unit testing tool that addresses some of the aforementioned issues. The main novel features of JTst are the fact that it permits combinatorial test case generations as well as automated and concurrent execution of test cases for Java classes, enabling higher product quality at lower testing costs.
Image Analysis of Brain Physiology
Authors: Arthur Toga, Tamara Arnicar
Venue: IEEE Computer Graphics and Applications (1985)

To understand the mechanisms responsible for behavior, neuroscientists need a holistic, 3D view of the brain.
Efficient decoupling capacitance budgeting considering operation and process variations
Authors: Yiyu Shi, Jinjun Xiong, Chunchen Liu, Lei He
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

This paper solves the variation-aware on-chip decoupling capacitance (decap) budgeting problem. Unlike previous work assuming the worst-case current load, we develop a novel stochastic current model, which efficiently and accurately captures operation variation such as temporal correlation between clock cycles and logic-induced correlation between ports. The models also considers current variation due to process variation with spatial correlation. We then propose an iterative alternative programming algorithm to solve the decap budgeting problem under the stochastic current model. Experiments using industrial examples show that compared with the baseline model which assumes maximum currents at all ports and under the same decap area constraint, the model considering temporal correlation reduces the noise by up to 5x, and the model considering both temporal and logic-induced correlations reduces the noise by up to 17x. Compared with the model using deterministic process parameters, considering process variation (Leff variation in this paper) reduces the mean noise by up to 4x and the 3&sigma; noise by up to 13x. While the existing stochastic optimization has been used mainly for process variation purpose, this paper to the best of our knowledge is the first in-depth study on stochastic optimization taking into account both operation and process variations for power network design. We convincingly show that considering operation variation is highly beneficial for power integrity optimization and this should be researched for optimizing signal and thermal integrity as well.
Runtime monitoring of web service conversations
Authors: Yuan Gan, Marsha Chechik, Shiva Nejati, Jon Bennett, Bill O'Farrell, Julie Waterhouse
Venue: Proceedings of the 2007 conference of the center for advanced studies on Collaborative research (2007)

For a system of distributed processes, correctness can be ensured by (statically) checking whether their composition satisfies properties of interest. In contrast, Web services are being designed so that each partner discovers properties of others dynamically, through a published interface. Since the overall system may not be available statically and since each business process is supposed to be relatively simple, we propose to use runtime monitoring of conversations between partners as a means of checking behavioural correctness of the entire web service system. Specifically, we identify a subset of UML 2.0 Sequence Diagrams as a property specification language and show that it is sufficiently expressive for capturing safety and liveness properties. By transforming these diagrams to automata, we enable conformance checking of finite execution traces against the specification. We describe an implementation of our approach as part of an industrial system and report on preliminary experience.
On-Line Handwritten Text Line Detection Using Dynamic Programming
Authors: M. Liwicki, E. Indermuhle, H. Bunke
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

In this paper we propose a novel approach to the detec- tion of on-line handwritten text lines based on dynamic pro- gramming. We try to find the paths with the minimum cost between two consecutive text lines. Most steps of the pro- posed algorithm are based on off-line information. Hence the method can also be applied to off-line documents af- ter a few minor changes. In our experiments we show that this dynamic programming based approach is better than a common on-line segmentation procedure.
Exploiting Fisher Kernels in Decoding Severely Noisy Document Images
Authors: J. Chen, Y. Wang
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

Decoding noisy document images is commonly needed in applications such as enterprise content management. Available OCR solutions are still not satisfactory especially on noisy images, and re-trainable systems require difficult and tedious training example preparation. Motivated by this challenging real application, we propose a novel so- lution that organically combines generative template mod- els with discriminative classifiers via RBF Fisher kernel de- rived from a generative model. We show that the new ap- proach is highly accurate in decoding noisy document im- ages, making the system more generalizable to variations in font and degradation, and hence significantly reduces the burden in training example preparation. We also show that as it weights the pixel features by their relevancies, RBF Fisher kernel is more robust, and leads to smaller, faster models by dimensionality reduction.
Vector coding algorithms for multidimensional discrete Fourier transform
Authors: Zhaodou Chen, Lijing Zhang
Venue: Journal of Computational and Applied Mathematics (2008)

A new fast algorithm is presented for the multidimensional discrete Fourier transform (DFT). This algorithm is derived using an interesting technique called ''vector coding'' (VC), and we call it the vector-coding fast Fourier transform (VC-FFT) algorithm. Since the VC-FFT is an extension of the Cooley-Tukey algorithm from 1-D to multidimensional form, the structure of the program is as simple as the Cooley-Tukey fast Fourier transform (FFT). The new algorithm significantly reduces the number of multiplications and recursive stages. The VC-FFT therefore comprehensively reduces the complexity of the algorithm as compared with other current multidimensional DFT algorithms.
Middle -- long Electric Power Load Forecasting Based on Co-integration and Support Vector Machine
Authors: Dongxiao Niu, Jinchao Li, Jinying Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Middle -- long forecasting of Electric Power is crucial to the electric investment, which is the guarantee of the healthy development of electric industry. There are so many factors which influence the middle-long electric power load. So in this paper the co-integration technology is used to analyze the influencing factors' inter characters, then a co-integration relating formula is found which is used to forecasting the middle-long electric power load, at last the support vector machine is used to correct the forecast error of the co-integrating method in order to improve the forecasting accuracy. The combined of the upper two methods can find out the long term equilibrium relationship and short term fluctuating relationship among the electric power load and other influencing factors, so the forecasting result become more sensible and scientific. A case showed that the proposed method is feasible and effective for middle-long electric power load forecasting.
Microprocessor Bus Structures and Standards
Authors: Paul Borrill
Venue: IEEE Micro (1981)

Bus structures must be transparent to the programmer of multiprocessor systems. Such transparency can be attained with the adoption of a standard data representation for future bus designs.
Towards understanding user perceptions of authentication technologies
Authors: Laurie A. Jones, Annie I. Antón, Julia B. Earp
Venue: Proceedings of the 2007 ACM workshop on Privacy in electronic society (2007)

Digital identities are increasingly being used to facilitate the execution of transactions in various domains. When developing and analyzing digital identity technologies, it is important to consider the perceptions and responses of end users. Users are typically concerned about privacy and security, but do not necessarily understand how these issues are impacted by the use of digital identities. In this paper, we discuss preliminary results of a survey regarding authentication technologies used to generate digital identities. Most respondents were unfamiliar with a majority of the technologies in question (e.g. hand geometry scans), and expressed uncertainty about their use. Perceptions were more positive for the use of authentication technologies in the financial domain, and more negative for their use in the retail domain. The results may inform the design of future systems.
Energy-Efficient Scheduling for Real-Time Systems on Dynamic Voltage Scaling (DVS) Platforms
Authors: Jian-Jia Chen, Chin-Fu Kuo
Venue: Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2007)

Energy-efficient designs have played import roles for hardware and software implementations for a decade. With the advanced technology of VLSI circuit designs, energy-efficiency can be achieved by adopting the dynamic voltage scaling (DVS) technique. In this paper, we survey the studies for energy-efficient scheduling in real-time systems on DVS platforms to cover both theoretical and practical issues.
Rules Extraction of Interval Type-2 Fuzzy Logic System Based on Fuzzy c-Means Clustering
Authors: Wei-bin Zhang, Huai-zhong Hu, Wen-jiang Liu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

An improved clustering algorithm is proposed in this paper, which originates from Fuzzy c-Means Clustering(FCM). FCM is one of the algorithms used commonly to extract fuzzy rules from type-1 fuzzy logic system. However, its application is merely limited to dots set. This deficiency is improved in the new algorithm, Interval Fuzzy c-Means Clustering(IFCM), which is adequate to deal with interval sets. The enhanced algorithm is based on a new definition of distance between interval data. This article will also focus on extracting fuzzy rule from interval type-2 fuzzy systems. The type-2 fuzzy system is suitable to handle the situations with complicated uncertainties. However, how to extract fuzzy rules from type-2 fuzzy logic systems remains an important issue. This paper will attempt to exhibit an unique method to extract rule from interval type-2 fuzzy systems with IFCM. Simulation results are included at the end of this article that indicates the validity of IFCM.
Priority sampling for estimation of arbitrary subset sums
Authors: Nick Duffield, Carsten Lund, Mikkel Thorup
Venue: Journal of the ACM (JACM) (2007)

From a high-volume stream of weighted items, we want to create a generic sample of a certain limited size that we can later use to estimate the total weight of arbitrary subsets. Applied to Internet traffic analysis, the items could be records summarizing the flows of packets streaming by a router. Subsets could be flow records from different time intervals of a worm attack whose signature is later determined. The samples taken in the past thus allow us to trace the history of the attack even though the worm was unknown at the time of sampling. Estimation from the samples must be accurate even with heavy-tailed distributions where most of the weight is concentrated on a few heavy items. We want the sample to be weight sensitive, giving priority to heavy items. At the same time, we want sampling without replacement in order to avoid selecting heavy items multiple times. To fulfill these requirements we introduce priority sampling, which is the first weight-sensitive sampling scheme without replacement that works in a streaming context and is suitable for estimating subset sums. Testing priority sampling on Internet traffic analysis, we found it to perform an order of magnitude better than previous schemes. Priority sampling is simple to define and implement: we consider a steam of items i &equals; 0,&hellip;,n &minus; 1 with weights wi. For each item i, we generate a random number &alpha;i &isin; (0,1] and create a priority qi &equals; wi/&alpha;i. The sample S consists of the k highest priority items. Let &tau; be the (k &plus; 1)th highest priority. Each sampled item i in S gets a weight estimate &wcirc;i &equals; max{wi, &tau;}, while nonsampled items get weight estimate &wcirc;i &equals; 0. Magically, it turns out that the weight estimates are unbiased, that is, E[&wcirc;i] &equals; wi, and by linearity of expectation, we get unbiased estimators over any subset sum simply by adding the sampled weight estimates from the subset. Also, we can estimate the variance of the estimates, and find, surprisingly, that the covariance between estimates &wcirc;i and &wcirc;j of different weights is zero. Finally, we conjecture an extremely strong near-optimality; namely that for any weight sequence, there exists no specialized scheme for sampling k items with unbiased weight estimators that gets smaller variance sum than priority sampling with k &plus; 1 items. Szegedy settled this conjecture at STOC'06.
Toward High Confidence Software
Authors: J. P. Cavano
Venue: IEEE Transactions on Software Engineering (1985)

Moving toward high confidence software that can meet ever increasing demands for critical DOD applications will require planning, specifying, selecting, and managing the necessary development and testing activities that will ensure the success of the software project. In order to trust the decisions being made, there must be evidence (i.e., an information base of data and facts) that techniques and tools being chosen for application on critical projects will perform as expected. Today, these expectations are mostly intuitive; there is little hard evidence available to guide acquisition managers and software developers in making necessary decisions.
A Sharable Built-in Self-repair for Semiconductor Memories with 2-D Redundancy Scheme
Authors: Swapnil Bahl
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

Newer technologies like 90 nm and 65 nm bring with them new challenges: longer time to process maturity, higher defect densities and poorer yields. The quality of test and repair determines the design's final yield and profitability. With increasing amount of memory on the chip, the need for an efficient and fast converging perfect algorithm for memory repair is increasing becoming important. In this paper, a perfect algorithm is presented for standalone repairable memories as well as for situations where redundancy is shared between different memories. The proposed BISR is composed of Built-in self-test (BIST) and built-in redundancy analysis (BIRA) module. The BISR module has a low overhead - about 5.05 % of memories area for a typical automotive chip. The proper redundancy scheme and the proposed BIRA algorithm ensure a high repair rate for the SOC and shorter test times as well as optimized area and maximum performance.
Re-usable knowledge: Development of an object oriented industrial KBS and a collaborative domain ontology
Authors: Paul Crowther, Gerd Berner, Raymond Williams
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2003)

Since the early eighties, there has been a gradual shift in the focus of development of knowledge based systems away from the rapid prototyping techniques that had previously prevailed, toward more structured methodologies, including model based reasoning and modeling of knowledge domains. The default standard for the development of these systems has become the CommonKADS methodology. This paper will assess the feasibility of applying the CommonKADS methodology to the knowledge base of an existing legacy system, the subsequent re-useability of knowledge and domain schema that results from the process and the development of collaborative domain ontologies. Currently the CommonKADS methodology embraces reuse by providing standard inferencing primitives and a set of generic task models. The resulting model set is assessed to determine its suitability to form the basis of an ontology for electroplating in the manufacturing industry.
Adaptive searching in succinctly encoded binary relations and tree-structured documents
Authors: Jérémy Barbay, Alexander Golynski, J. Ian Munro, S. Srinivasa Rao
Venue: Theoretical Computer Science (2007)

The methods most heavily used by search engines to answer conjunctive queries on binary relations (such as one associating keywords with web-pages) are based on computing the intersection of postings lists stored as sorted arrays and using variants of binary search. We show that a succinct representation of the binary relation permits much better results, while using less space than traditional methods. We apply our results not only to conjunctive queries on binary relations, but also to queries on semi-structured documents such as XML documents or file-system indexes, using a variant of an adaptive algorithm used to solve conjunctive queries on binary relations.
Using mutation analysis to evaluate test generation strategies in a synchronous context
Authors: L. du Bousquet, M. Delaunay
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

LUTESS is a test data generator dedicated to synchronous software validation. The tool produces test with respect to an environment description. To check if this description is really as expected, we use mutation analysis. The key point of the approach is to select a subset of mutants which characterizes some kind of "interesting situations" that are supposed to be often produced thanks to environment description. Intuitively, if pre-selected mutants are killed "very often" during tests, environment description is as expected (with respect to these "interesting situations").
Deductive Fault Simulation of Internal Faults of Inverter-Free Circuits and Programmable Logic Arrays
Authors: F. Ozguner
Venue: IEEE Transactions on Computers (1986)

A method for the deductive fault simulation of faults in inverter-free circuits is presented. It is shown that in an inverter-free circuit, fault lists on lines with complementary logic values are disjoint, and fault list calculations can be done by performing fewer set operations compared to conventional gate level deductive simulation. Applications of the method to programmable logic arrays (PLA's) and deductive fault simulation of PLA faults are discussed.
Scalable Semantic Search with Hybrid Concept Index over Structure Peer-to-Peer Network
Authors: Wenhui Ma, Gang Wang, Jing Liu
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

The primary challenge in developing a peer-topeer( P2P) file sharing system is implementing an efficient keyword search mechanism. Current keyword search approaches for structured P2P networks are built on the distributed inverted index by keywords. However, when executing multiple-attribute queries, they suffer from the problem of unscalable bandwidth consumption. Moreover, these approaches only support literally word match, not taking into account the meaning of word. In this paper, we propose an efficient keyword search mechanism over structure P2P network. Peers use a shared ontology to describe the content of a document and the subject of a query. A distributed hybrid concept index is constructed, which efficiently supports the query routing and matching, and avoids the intersection of inverted list among peers, which is cause of unscallabe network bandwidth consumption. Based on the semantic similarity between the subjects of queries and the contents of documents, peers can get results matching their queries semantically, instead of literally word match. Simulation experiments show that keyword search with the approach proposed in this paper is much less on bandwidth costs and much higher on retrieval perform than that based on standard inverted index by keywords.
Special Feature: Fillin: A Reusable Tool for Form-Oriented Software
Authors: S. P. Wartik
Venue: IEEE Software (1986)

The reusable tool was designed to improve man-machine interaction. Its tool-oriented environment also enforces standards better than any list of rules can.
Dealing with software viruses: A biological paradigm
Authors: Erol Gelenbe
Venue: Information Security Tech. Report (2007)

We introduce a probability model for populations of cells and viruses that interact in the presence of an anti-viral agent. Cells can be infected by viruses, and their longevity and ability to avoid infection are modified if they survive successive attacks by viruses. Viruses that survive the effect of the anti-viral agent may find that their ability to survive a future encounter with molecules of the anti-viral agent is modified, as is their ability to infect a healthy cell. Additionally, we assume that the anti-viral agents can be a cocktail with different proportions of agents that target different strains of the virus. In this paper, we give the state equations for the model and derive its analytical solution in steady state. The solution then provides insight into the appropriate mix or ''cocktail'' of anti-viral agents that can be designed to deal with the virus' ability to mutate. In particular, the analysis shows that the concentration of anti-viral agent by itself does not suffice to ultimately control the infection, and that it is important to dose a mix of anti-viral agents so as to target each strain of virus in a specific manner, taking into account the ability of each virus strain to survive in the presence of the anti-viral agents. Models of this kind may eventually lead to the computer aided design of therapeutic protocols or drug design.