ppxscal/embedding_network huggingface dataset:
Empirical studies of a decentralized regression test selection framework for web services
Authors: Michael E. Ruth, Shengru Tu
Venue: Proceedings of the 2008 workshop on Testing, analysis, and verification of web services and applications (2008)

As Web services grow in popularity and use, it is becoming more important for organizations to verify their evolving services to ensure that they are providing a desired level of confidence and one of the most common ways to perform this verification is regression testing. Safe regression test selection techniques are often employed in conjunction with regression testing to reduce the associated costs of testing without reducing the level of confidence provided. In a previous work, a framework which automates the safe regression test selection and regression testing processes was developed in a decentralized, end-to-end manner. This paper reports an empirical study of the framework designed to compare the cost of performing the proposed approach and running the selected tests with the cost of running all tests without performing a selection step. The results indicate that the framework can be effective in reducing the costs of performing regression test selection.
Unsupervised pattern classification by means of cellular neural networks
Authors: G. Costantini, D. Casali, M. Carota
Venue: Proceedings of the 9th International Conference on Circuits (2005)

A novel algorithm for unsupervised classification of datasets made up of integer valued patterns by means of Cellular Neural Network (CNN) is proposed. The adopted CNN is n-dimensional and is based on a space-variant template - neighborhood order 1 - to cluster n-dimensional datasets. The choice of a CNN architecture allows a straightforward hardware implementation, particularly suited for bi-dimensional patterns.
Copper planar microcoils applied to magnetic actuation
Authors: Marion Woytasik, Johan Moulin, Emile Martincic, Anne-Lise Coutrot, Elisabeth Dufour-Gergam
Venue: Microsystem Technologies (2008)

Recent advances in microtechnology allow realization of planar microcoils. These components are integrated in MEMS as magnetic sensor or actuator. In the latter case, it is necessary to maximize the effective magnetic field which is proportional to the current passing through the copper track and depends on the distance to the generation microcoil. The aim of this work was to determine the optimal microcoil design configuration for magnetic field generation. The results were applied to magnetic actuation, taking into account technological constraints. In particular, we have considered different realistic configurations that involve a magnetically actuated device coupled to a microcoil. Calculations by a semi-analytical method using Matlab software were validated by experimental measurements. The copper planar microcoils are fabricated by UV micromoulding on different substrates: flexible polymer (Kapton&#x00ae;) and silicate on silicon. They are constituted by a spiral-like continuous track. Their total surface is about 1&#x00a0;mm2.
An optimization-based approach for data classification
Authors: St. Busygin, O. A. Prokopyev, P. M. Pardalos
Venue: Optimization Methods Software (2007)

In this paper we discuss an optimization-based approach to handling data classification problems. The main idea of the proposed method is to reformulate the classification problem as a mathematical programming problem, whose solution implies relevant feature selection and forms the classes of data. Encouraging computational results on two DNA microarray data mining problems are reported.
Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies), 1 edition
Authors: Matthieu Cord, Pdraig Cunningham, Matthieu Cord, Pdraig Cunningham
Venue:  (2008)

Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music. This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
Decision support for team staffing: An automated relational recommendation approach
Authors: Jochen Malinowski, Tim Weitzel, Tobias Keim
Venue: Decision Support Systems (2008)

Selecting individuals for teams is only rarely supported by IS. Existing systems only consider whether a person has the required technical skills and abilities for a job. Another important aspect is neglected - the match between the person and the team members in terms of interpersonal compatibility. We present a decision support system based on a relational recommendation approach for providing an automated pre-selection of candidates that fit best with future team members. The relational recommender contributes to theory by proposing an IS-supported relational approach to team staffing and to practice by offering time and cost savings for HR professionals.
A Framework for Assessing RFID System Security and Privacy Risks
Authors: Pawel Rotter
Venue: IEEE Pervasive Computing (2008)

Radio Frequency Identification is a technology that uses radio waves to automatically identify physical objects. Researchers have been rapidly developing RFID systems over the last few years, and such systems have proven benefits in many application domains. However, RFID systems also raise serious privacy and security concerns. This article offers a brief review of the main threats to RFID systems and proposes a methodology for qualitatively evaluating the risk level for various application domains. The evaluation is based on three criteria: the system's deployment range, the type of link between the RFID tag and identity-related data, and the domain's security demands. The author also presents a taxonomy of some existing RFID applications and discusses each in relation to the evaluation criteria.
Arithmetic Operation in Membrane System
Authors: Ping Guo, Jing Chen
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Membrane system is a computing model which imitates natural process at cellular level. In this system all objects can evolve in a maximal parallelism and distributed manner. Recent results show that this model is a promising framework for solving NP complete problems in polynomial time. The paper proves the possibility to perform operations with integer numbers in a membrane system, and gives an effective method to implement arithmetic operations, which seems to have a lower complexity than when implementing them in usual computer architecture.
Low-cost modifications of Rao-Blackwellized particle filters for improved speech denoising
Authors: Frédéric Mustière, Martin Bouchard, Miodrag Bolić
Venue: Signal Processing (2008)

Rao-Blackwellized particle filtering (RBPF) has established itself as an appealing alternative to classical Kalman filter-based speech enhancement schemes. Its advantages include a high noise reduction between utterances, and flexibility in the definition of model parameters. There is, however, still room for improvement in reducing the level of residual noise within the estimated speech. In this paper, low-cost ways to improve the quality of enhanced speech are proposed, starting from an existing RBPF algorithm. In the first method, the RBPF is slightly modified to produce improved but delayed estimates. The next two methods are centered on the inclusion of low-order FIR filters during or after the estimation process. Finally, a simple way to combine different speech estimates is shown. The main interest is that even rough estimates obtained with lightweight algorithms can be used to improve the resulting quality. The idea is centered on a single Kalman filter running on mixing proportions. Various simulation results are shown and rated using their overall SNR, their segmental SNR, and their PESQ (wideband extension) score. Advantages and drawbacks of each method are highlighted. Overall, the changes proposed are found to be beneficial across most or all of the measures used.
On the performance of the ICP algorithm
Authors: Esther Ezra, Micha Sharir, Alon Efrat
Venue: Computational Geometry: Theory and Applications (2008)

We present upper and lower bounds for the number of iterations performed by the Iterative Closest Point (ICP) algorithm. This algorithm has been proposed by Besl and McKay as a successful heuristic for matching of point sets in d-space under translation, but so far it seems not to have been rigorously analyzed. We consider two standard measures of resemblance that the algorithm attempts to optimize: The RMS (root mean squared distance) and the (one-sided) Hausdorff distance. We show that in both cases the number of iterations performed by the algorithm is polynomial in the number of input points. In particular, this bound is quadratic in the one-dimensional problem, under the RMS measure, for which we present a lower bound construction of @W(nlogn) iterations, where n is the overall size of the input. Under the Hausdorff measure, this bound is only O(n) for input point sets whose spread is polynomial in n, and this is tight in the worst case. We also present several structural geometric properties of the algorithm under both measures. For the RMS measure, we show that at each iteration of the algorithm the cost function monotonically and strictly decreases along the vector @Dt of the relative translation. As a result, we conclude that the polygonal path @p, obtained by concatenating all the relative translations that are computed during the execution of the algorithm, does not intersect itself. In particular, in the one-dimensional problem all the relative translations of the ICP algorithm are in the same (left or right) direction. For the Hausdorff measure, some of these properties continue to hold (such as monotonicity in one dimension), whereas others do not.
Read-once polynomial identity testing
Authors: Amir Shpilka, Ilya Volkovich
Venue: Proceedings of the 40th annual ACM symposium on Theory of computing (2008)

In this paper we study the problems of polynomial identity testing (PIT) and reconstruction of read-once formulas. The following are some deterministic algorithms that we obtain. An nO(k2) algorithm for checking whether given k ROFs sum to zero or not. An nO(d+k2) time algorithm for checking whether a black box holding the sum of k depth d ROFs computes the zero polynomial. In other words, we provide a hitting set of size nO(d+k2) for the sum of k depth d ROFs. This implies an nO(d) deterministic algorithm for the reconstruction of depth d ROFs. A hitting set of size exp(~O(√n+k2)) for the sum of k ROFs (without depth restrictions). This implies a sub-exponential time deterministic algorithm for black-box identity testing and reconstructing of ROFs. To the best of our knowledge our results give the first polynomial time (non black-box) and sub-exponential time (black-box) identity testing algorithms for the sum of (a constant number of) ROFs. In addition, we introduce and study the read-once testing problem (ROT for short): Given an arithmetic circuit computing a polynomial P(x), decide whether there is a ROF computing P(x). If there is such a formula then output it. Otherwise output "No". We show that most previous algorithms for polynomial identity testing can be strengthen to yield algorithms for the ROT problem. In particular we give ROT algorithms for: Depth-2 circuits (circuits computing sparse polynomials), Depth-3 circuits with bounded top fan-in (both in the black-box and non black-box settings, where the running time depends on the model), non-commutative formulas and sum of k ROFs. The running time of the ROT algorithm is essentially the same running time as the corresponding PIT algorithm for the class. The main tool in most of our results is a new connection between polynomial identity testing and reconstruction of read-once formulas. Namely, we show that in any model that is closed under partial derivatives (that is, a partial derivative of a polynomial computed by a circuit in the model, can also be computed by a circuit in the model) and that has an efficient deterministic polynomial identity testing algorithm, we can also answer the read-once testing problem.
A Genetic Algorithm for Finding Minimal Multi-homogeneous Bézout Number
Authors: Dongshu Yan, Jintao Zhang, Bo Yu, Changtong Luo, Shaoliang Zhang
Venue: Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (2008)

Homotopy continuation is a most efficient numerical method for finding all isolated solutions of system of polynomial equations, and finding minimal multi-homogeneous Bezout number is a basic problem of homotopy continuation. This paper presents a problem-specific genetic algorithm for finding minimal multi-homogeneous Bezout number. The algorithm is easy to implement and easy to be parallelized for large scale problems. It can find the minimal multi-homogeneous Bezout number in probability 1. Numerical results indicate that the proposed algorithm is reliable and efficient. The algorithm offers a competitive alternative for minimal multi-homogeneous Bezout number problem. Meanwhile, it extends the application fields of genetic algorithms.
A virtual painting knife
Authors: Naoto Okaichi, Henry Johan, Takashi Imagire, Tomoyuki Nishita
Venue: The Visual Computer: International Journal of Computer Graphics (2008)

Recently, in the area of non-photorealistic rendering, there has been a significant effort in digital painting research to simulate traditional painting styles and painting pigments. In particular, the simulation of painting tools is very important because this enables an intuitive painting experience for a user and generates rich painting effects. Many painting systems have been proposed using brushes, but less for other painting tools. As a result, there is still a limitation in the variety of painting effects that can be generated. In this paper, we propose a method to simulate painting using a painting knife, which is an important tool in oil painting. We model a painting knife and model the pigments such that the system is suitable for realizing the impasto style. We also present a technique for simulating the interaction between a painting knife and pigments on a canvas in real-time.
Proceedings of the first international workshop on Leadership and management in software architecture
Venue: International Conference on Software Engineering (2008)

It is our great pleasure to welcome you to the 1st International Workshop on Leadership and Management in Software Architecture -- LMSA08. This year's workshop is the first one that we can recall that was devoted exclusively to leadership and management skills of the software architect. The mission of our workshop is to provide vital information to the community at large in two areas -- how can software engineering education and internal training in industry be improved to get the architects of tomorrow ready for the management challenges that they will face. Our workshop is off to an inauspicious start, with only 5 presenters. However, we expect a lively workshop and we feel that the attendees and the presenters have some very important things to say; information that can make a real impact on the software engineering profession. The attendees and chairs cumulatively have extensive experience in the field. Co-chair Len Bass, for example, has written two books on software architecture. Co-chair Brian Berenbach, from 1975 to 1993 was a senior solution architect designing and installing industrial and power plant control systems, first for American Cyanamid Company and then for ABB Corporation. Several of the presenters and attendees have also worked in industry as engineering managers or solution architects. As project size increases, the chief solution architect becomes less of a technologist and more of a manager. On very large projects, he becomes the technical management linchpin that can drive a project to successful completion or utter failure. Without awareness of the challenges he or she faces, prior apprenticeships and good people skills, a senior architect may be unprepared for the challenges of managing diverse teams, complex system construction, with aggressive schedules and rapidly changing technologies. We expect to address these issues in our workshop, and, hopefully, make a real contribution in terms of checklists and guides. Moreover, the architect and the development team do not exist in a vacuum within an organization. Organizations must provide support for the career development of an architect, they must understand the importance of software architecture in the development life cycle beginning with project feasibility and including project budget and scheduling. Our presented papers touch on some of these issues -- the architect skill set and the training of the architect. The papers by Berenbach, Creighton and Singer, Islam and Dong and Ali Babar deal with the skills of the software architect. The paper by Sangwan and Ros touches on the organizational implications associated with global development. We expect the workshop to deal not only with the individual skills of the architect and how they develop them but the educational and organizational infrastructure to nurture and support them.
Recent land-cover/use change associated with land degradation in the Lake Baringo catchment, Kenya, East Africa: evidence from Landsat TM and ETM+
Authors: L. M. Kiage, K. -B. Liu, N. D. Walker, N. Lam, O. K. Huh
Venue: International Journal of Remote Sensing (2007)

Many parts of East Africa are experiencing dramatic changes in land-cover/use at a variety of spatial and temporal scales, due to both climatic variability and human activities. Information about such changes is often required for planning, management, and conservation of natural resources. Several methods for land cover/change detection using Landsat TM/ETM+ imagery were employed for Lake Baringo catchment in Kenya, East Africa. The Lake Baringo catchment presents a good example of environments experiencing remarkable land cover change due to multiple causes. Both the NDVI differencing and post-classification comparison effectively depicted the hotspots of land degradation and land cover/use change in the Lake Baringo catchment. Change-detection analysis showed that the forest cover was the most affected, in some sections recording reductions of over 40% in a 14-year period. Deforestation and subsequent land degradation have increased the sediment yield in the lake resulting in reduction in lake surface area by over 10% and increased turbidity confirmed by the statistically significant increase (t = -84.699, p
iSpreadRank: Ranking sentences for extraction-based summarization using feature weight propagation in the sentence similarity network
Authors: Jen-Yuan Yeh, Hao-Ren Ke, Wei-Pang Yang
Venue: Expert Systems with Applications: An International Journal (2008)

Sentence extraction is a widely adopted text summarization technique where the most important sentences are extracted from document(s) and presented as a summary. The first step towards sentence extraction is to rank sentences in order of importance as in the summary. This paper proposes a novel graph-based ranking method, iSpreadRank, to perform this task. iSpreadRank models a set of topic-related documents into a sentence similarity network. Based on such a network model, iSpreadRank exploits the spreading activation theory to formulate a general concept from social network analysis: the importance of a node in a network (i.e., a sentence in this paper) is determined not only by the number of nodes to which it connects, but also by the importance of its connected nodes. The algorithm recursively re-weights the importance of sentences by spreading their sentence-specific feature scores throughout the network to adjust the importance of other sentences. Consequently, a ranking of sentences indicating the relative importance of sentences is reasoned. This paper also develops an approach to produce a generic extractive summary according to the inferred sentence ranking. The proposed summarization method is evaluated using the DUC 2004 data set, and found to perform well. Experimental results show that the proposed method obtains a ROUGE-1 score of 0.38068, which represents a slight difference of 0.00156, when compared with the best participant in the DUC 2004 evaluation.
On the complexity of deriving schema mappings from database instances
Authors: Pierre Senellart, Georg Gottlob
Venue: Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2008)

We introduce a theoretical framework for discovering relationships between two database instances over distinct and unknown schemata. This framework is grounded in the context of data exchange. We formalize the problem of understanding the relationship between two instances as that of obtaining a schema mapping so that a minimum repair of this mapping provides a perfect description of the target instance given the source instance. We show that this definition yields "intuitive" results when applied on database instances derived from each other by basic operations. We study the complexity of decision problems related to this optimality notion in the context of different logical languages and show that, even in very restricted cases, the problem is of high complexity.
Automatic CoDec generation to reduce test engineering cost
Authors: Ariel Sabiguero, Anthony Baire, C&#x00e9;sar Viho
Venue: International Journal on Software Tools for Technology Transfer (STTT) (2008)

TTCN-3 is an abstract language for specification of Abstract Test Suites. Coding of TTCN-3 values into physically transmittable messages and decoding of bitstrings into their TTCN-3 representation has been removed from the language itself and relayed to external and specialized components, called CoDec. CoDec development, either implicitly or explicitly, is a must in any TTCN-3 testing activity. Field experience showed that there is a high cost associated with CoDec development and maintenance. To achieve adequate software engineering practices, a set of types, tools and definitions were developed. This paper unveils gray areas in TTCN-3 architecture and presents a methodological approach to minimize the complexity of CoDec development. Even though the initial field of application is IPv6 testing, the main tool introduced&#x2014;the CoDec Generator&#x2014;is a valuable tool in any testing application domain. It is designed to lower the CoDec maintenance costs in all test case lifecycle stages, from development to maintenance.
K&ouml;nig's edge coloring theorem without augmenting paths
Authors: Romeo Rizzi
Venue: Journal of Graph Theory (1998)

We give a simple, self-contained proof of the following basic fact [1, 2] in matching theory. &copy; 1998 John Wiley & Sons, Inc. J. Graph Theory 29: 87, 1998