ppxscal/embedding_network huggingface dataset:
How Does a Measurement Programme Evolve in Software Organizations?
Authors: Lasse Harjumaa, Jouni Markkula, Markku Oivo
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

Establishing a software measurement programme within an organization is not a straightforward task. Previous literature surveys have focused on software process improvement in general and software measurement has been analysed in case studies. This literature survey collects the data from separate cases and presents the critical success factors that are specific to software measurement programmes. We present a categorization of the success factors based on organizational roles that are involved in measurement. Furthermore, the most essential elements of success in different phases of the life cycle of the measurement programme are analysed. It seems that the role of upper management is crucial when starting measurement and the individual developers' impact increases in the later phases. Utilization of the measurement data and improvement of the measurement and development processes requires active management support again.
Quality-Evaluation Models and Measurements
Authors: Jeff Tian
Venue: IEEE Software (2004)

Quality can determine a software product's success or failure in today's competitive market. Among the many characteristics of quality, some aspects deal directly with the functional correctness or the conformance to specifications, while others deal with usability, portability, and so on. Correctness is typically the most important aspect of quality. Even for market segments in which new features and usability take priority, such as software for personal use in the mass market, correctness is still a fundamental part of the users' expectations. This article classifies several quality-evaluation models.
Application of Potts-Model Perceptron for Binary Patterns Identification
Authors: Vladimir Kryzhanovsky, Boris Kryzhanovsky, Anatoly Fonarev
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

We suggest an effective algorithm based on q ¿state Potts model providing an exponential growth of network storage capacity M ~N 2S + 1, where N is the dimension of the binary patterns and S is the free parameter of task. The algorithm allows us to identify a large number of highly distorted similar patterns. The negative influence of correlations of the patterns is suppressed by choosing a sufficiently large value of the parameter S. We show the efficiency of the algorithm by the example of a perceptron identifier, but it also can be used to increase the storage capacity of full connected systems of associative memory. Restrictions on S are discussed.
Electronic business communities model using agent technology
Authors: Azlinah Mohamed, Nor Zuraina Kamarul Ariffin, Noor Habibah Arshad, Yap May Lin, Fauzah Mohd Mokhtar
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

In the early 1990s, as the Internet became more commercialized, users flocked to participate in the World Wide Web (WWW). Electronic business (e-business) rapidly expanded primarily owing to the development of new networks, protocols, software, and specifications. Conducting e-business means extensive use of information technology (IT) in general and the Internet in particular. Furthermore, the globalization of the economy is driving e-business to become service-centric, offering services that can be flexibly and dynamically composed of rapidly deployable electronic services (e-services). In a dynamic E-business environment, interoperation and coordination across distributed services are very important. These needs have given rise to a new set of requirements of negotiation-based, autonomous, and intelligent computing. This paper will focus on analysing the concept of agent-oriented software implemented in e-business. Findings on interoperability problems in e-business will be discussed and an information brokering agent, known as E-Business Agent Communities (EBAC), that has the ability to migrate through network is proposed. It is hoped that EBAC will provide virtual enterprises with the ability to share resources and business processes for production, marketing, and other services.
Twostep-by-twostep PIRK-type PC methods with continuous output formulas
Authors: Nguyen Huu Cong, Le Ngoc Xuan
Venue: Journal of Computational and Applied Mathematics (2008)

This paper deals with parallel predictor-corrector (PC) iteration methods based on collocation Runge-Kutta (RK) corrector methods with continuous output formulas for solving nonstiff initial-value problems (IVPs) for systems of first-order differential equations. At nth step, the continuous output formulas are used not only for predicting the stage values in the PC iteration methods but also for calculating the step values at (n+2)th step. In this case, the integration processes can be proceeded twostep-by-twostep. The resulting twostep-by-twostep (TBT) parallel-iterated RK-type (PIRK-type) methods with continuous output formulas (twostep-by-twostep PIRKC methods or TBTPIRKC methods) give us a faster integration process. Fixed stepsize applications of these TBTPIRKC methods to a few widely-used test problems reveal that the new PC methods are much more efficient when compared with the well-known parallel-iterated RK methods (PIRK methods), parallel-iterated RK-type PC methods with continuous output formulas (PIRKC methods) and sequential explicit RK codes DOPRI5 and DOP853 available from the literature.
Sparse Coding Neural Gas for Analysis of Nuclear Magnetic Resonance Spectroscopy
Authors: Frank-Michael Schleif, Matthias Ongyerth, Thomas Villmann
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Nuclear Magnetic Resonance Spectroscopyis a technique for the analysis of complex biochemical materials. Thereby the identiﬁcation of known sub-patterns is important. These measurements require an accurate preprocessing and analysis to meet clinical standards. Here we present a method for an appropriate sparse encoding of NMRspectral data combined with a fuzzy classiﬁcation system allowing the identiﬁcation of sub-patterns including mixtures thereof. The method is evaluated in contrast to an alternative approach using simulated metabolic spectra.
Secured Smart Card Using Palm Vein Biometric On-Card-Process
Authors: Rajendran Jeyaprakash, Jin Lee, Subir Biswas, Jae Mook Kim
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

The biometric on-card-process solution used on the smart card has a potential for high security with greatly minimized fraud risks in financial sector. In this paper we discuss the palm vein biometric system and its compatibility in financial sector, software design for on-card-processing solution based on java virtual machine. The solution is stimulated and the result obtained and that was tested on PC login application. The security level of this solution is highly reliable since the FRR and FAR is very low compared to other biometric systems.
Modeling of Nonlinear Block-Oriented Systems Using Orthonormal Basis and Radial Basis Functions
Authors: Rafal Stanislawski, Wojciech P. Hunek, Krzysztof J. Latawiec
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

This paper presents a methodology for modeling of Wiener, Hammerstein and feedback-nonlinear systems via orthonormal basis and radial basis functions. The approach is computationally effective, in particular in terms of elimination of the disastrous bilinearity effect. Simulation study for the magnetic levitation process confirms the attractiveness of the method.
A Local-Information-Based Blind Image Restoration Algorithm Using a MLP
Authors: Hui Wang, Nian Cai, Ming Li, Jie Yang
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Based on a multilayer perceptron (MLP), a blind image restoration method is presented. The algorithm considers both local region information and edge information of an image. To reduce the dimension of the network's input, a sliding window approach is employed to extract the features of the blurred image, which makes use of local region information. For the purpose of accelerating training and improving the restoration performance, the edge part and the smooth part in an image are separated and then used as training sets, respectively. A mapping model between the blurred image and the clear one is established through training the MLP with LM algorithm and then it is utilized to restore the blurred image. The simulation results demonstrate the proposed method feasible for image restoration.
Do Students Trust Their Open Learner Models?
Authors: Norasnita Ahmad, Susan Bull
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

Open learner models (OLM) enable users to access their learner model to view information about their understanding. Opening the learner model to the learner may increase their perceptions of how a system evaluates their knowledge and updates the model. This raises questions of trust relating to whether the learner believes the evaluations are correct, and whether they trust the system as a whole. We investigate learner trust in various OLM features: the complexity of the model presentation; the level of learner control over the model contents; and the facility to release one's own model for peer viewing.
Processing pronouns without antecedents: Evidence from event-related brain potentials
Authors: Ruth Filik, Anthony J. Sanford, Hartmut Leuthold
Venue: Journal of Cognitive Neuroscience (2008)

Pronouns that do not have explicit antecedents typically cause processing problems. We investigate a specific example in which this may not be the case, as in “At the interview, they asked really difficult questions,” where the plural pronoun they has no explicit antecedent, yet is intuitively easy to process. Some unspecified but constrained set of individuals (the interview panel or the company) can be inferred as the referent, but it is not crucial to determine specifically which entities are being referred to. We propose that this contrasts with the processing of singular pronouns (he or she), for which it is necessary to determine a specific referent. We used event-related brain potentials to investigate how readers process the pronoun (they vs. he/she) in these cases. Sentences were placed in a context that either did or did not contain an explicit antecedent for the pronoun. There were two key findings. Firstly, when there was no explicit antecedent, a larger fronto-central positivity was observed 750 msec after pronoun onset for he/she than they, possibly reflecting the additional difficulty involved in establishing a referent for he/she than for they when no explicit referent is available. Secondly, there was a larger N400-like deflection evoked by he/she than they, regardless of whether there was an explicit antecedent for the pronoun. We suggest that this is due to the singular pronouns bringing about a greater integration effort than the plural pronoun. This observation adds to a growing body of research revealing fundamental differences in the way these pronouns are handled by the language processor.
Application of Wavelet Packet Neural Network on Relay Protection Testing of Power System
Authors: Xin-Wei Du, Yuan Li, Di-Chen Liu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The paper presents a wavelet packet neural network (WPNN) approach for solving the waveform distortion problem of protective relaying testing instrument. With its excellent time-frequency localization property and approximation ability, WPNN is used to establish an identification model of the non-linear amplifier of the protective relaying testing instrument. The fault data to be put into the instrument is compensated by an adjusting function getting from the identification model, which makes the whole instrumentation system show linear performance so that the distortion of the output waveform is constrained greatly. Simulation results indicate the feasibility and validity of the proposed approach, and a prototype has been put into practical operation.
Representation Levels Within Knowledge Representation
Authors: Heather D. Pfeiffer, Joseph J. Pfeiffer,  Jr.
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

Representation of knowledge is used to store and retrieve informational data in a machine. Since meaning cannot be directly stored in the computer; this work proposes a series of levels of representation. The meaning of the data is transformed to a format that the machine can use to store and retrieve knowledge. These levels are designed to transform the knowledge from an abstract definition to a machine representation without loosing any meaning.
An enhancement of TCP Veno with forward acknowledgement
Authors: Ke Zhang, Cheng Peng Fu
Venue: Computer Communications (2008)

One sender-side TCP enhancement, called TCP Veno, was recently proposed to mainly eliminate TCP performance suffering in the wireless environments. Although TCP Veno shows remarkable performance improvement over legacy TCP, namely TCP Reno, Veno has not been utilized at its full potential. In this paper, we study the enhancement of TCP Veno with FACK (forward acknowledgement), called TCP Veno-F. The network simulation results show that, (1) TCP Veno-F improves TCP performance by better utilization of link bandwidth; (2) TCP Veno-F co-exists with legacy TCP harmoniously in the wired networks; (3) TCP Veno-F deals with a large range of network scenarios such as heterogeneous network, RED queue management.
Cost Models and Efficient Algorithms on Existentially Uncertain Spatial Data
Authors: Elias Frentzos, Nikos Pelekis, Yannis Theodoridis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

The domain of existentially uncertain spatial data refers to objects that are modelled using an existential probability accompanying spatial data values. An interesting and challenging query type over existentially uncertain data is the search of the Nearest Neighbor (NN), since the probability of a potential dataset object to be the NN of the query object depends on the locations and probabilities of other points in the same dataset. In this paper, following a statistical approach, we estimate the average number of the NNsrequired to answer probabilistic thresholding NN(PTNN) queries as function of the threshold t, allowing us to utilize existing approaches and propose a cost model for such queries. Based on the same statistical approach, we propose an efficient algorithm for PTNN queries over arbitrarily structured existentially uncertain spatial data. Our experimental study demonstrates the accuracy and efficiency of the proposed techniques.
Generic Reactive Animation: Realistic Modeling of Complex Natural Systems
Authors: David Harel, Yaki Setty
Venue: Proceedings of the 1st international workshop on Formal Methods in Systems Biology (2008)

Natural systems, such as organs and organisms, are large-scale complex systems with numerous elements and interactions. Modeling such systems can lead to better understanding thereof and may help in efforts to save on resources and development time. In recent years, our group has been involved in modeling and understanding biological systems, which are perhaps the prime example of highly complex and reactive large-scale systems. To handle their complexity, we developed a technique called reactive animation (RA), which smoothly connects a reactive system engine to an animation tool, and which has been described in earlier publications. In the present paper we show how the basic idea of RA can be made generic, by providing a simple general way to link up any number of reactive system engines -- even ones that are quite different in nature -- to an animation tool. This results in natural-looking, fully interactive 3D animations, driven by complex reactive systems running in the background. We illustrate this with two examples that link several tools: Rhapsody for state-based specification, the Play-Engine for scenario-based specification, MATLAB for mathematical analysis and the 3DGameStudio for animation. Our examples are both from biology (pancreatic development) and from everyday activities (e.g., gym training).
A method for measuring threats and errors in surgery
Authors: K. R. Catchpole, A. E. B. Giddings, G. de Hirst, T. Dale, G. J. Peek, M. R. Leval
Venue: Cognition, Technology and Work (2008)

We examined the measurement of non-technical skills for surgical teams using a framework derived from aviation. Twenty four paediatric cardiac surgical and 20 orthopaedic operations were studied by a single observer. Predefined intraoperative failures were recorded, from which it was possible to derive measures of technical errors, threats, and non-technical errors (NTEs). A second non-technical scoring (NTS) method was used which required the observer to give a score from 1 to 4 on the four dimensions of the scale for three stages of each operation. There was a significant positive relationship between NTEs and operative duration in orthopaedic surgery (p&#x00a0;<&#x00a0;0.01). In paediatric cardiac surgery, the ranked NTS measures correlated positively with the number of threats (p&#x00a0;<&#x00a0;0.005) and with operative duration (p&#x00a0;<&#x00a0;0.005). Non-technical skills measures (ranked NTS and NTEs) were also significantly positively correlated (p&#x00a0;<&#x00a0;0.01). This suggests that it is possible to evaluate non-technical skills in operating theatre teams, but further work is needed to improve the reliability and accuracy of the measurement methods.
Computational, statistical and graph-theoretical methods for disease mapping and cluster detection
Authors: Kenneth Mandl, Bonnie Berger
Venue:  (2007)

Epidemiology, the study of disease risk factors in populations, emerged between the 16th and 19th centuries in response to terrifying epidemics of infectious diseases such as yellow fever, cholera and bubonic plague. Traditional epidemiological studies have led to modifications in hygiene, diet, and many other practices that have profoundly altered the dynamic between humans and diseases.In this thesis, we develop mathematical techniques to address modern challenges, including emerging diseases such as SARS and West Nile virus, the threat of bioterrorism, and stringent legislation protecting patient privacy. Within spatial epidemiology, one problem is to map the risk of disease across space (i.e., disease mapping), and another is to analyze the data for clustering. We propose a general technique, cartograms created from exact patient location data, that can address both of these problems. We also develop a graph-theoretical method to detect spatial clusters of any shape based on Euclidean minimum spanning trees. For mapping applications, we present an optimal strategy for mapping patient locations that preserves both privacy and spatial patterns within the data. For real-time disease surveillance, in which the goal is early detection of outbreaks based on time-series data, we introduce a generalized additive model that maintains constant specificity on various time scales. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Trees in Concept Lattices
Authors: Radim Belohlavek, Bernard Baets, Jan Outrata, Vilem Vychodil
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

The paper presents theorems characterizing concept lattices which happen to be trees after removing the bottom element. Concept lattices are the clustering/classification systems provided as an output of formal concept analysis. In general, a concept lattice may contain overlapping clusters and need not be a tree. On the other hand, tree-like classification schemes are appealing and are produced by several classification methods as the output. This paper attempts to help establish a bridge between concept lattices and tree-based classification methods. We present results presenting conditions for input data which are sufficient and necessary for the output concept lattice to form a tree after one removes its bottom element. In addition, we present illustrative examples and several remarks on related efforts and future research topics.
An extension of the light meshes method for three-dimensional scenes with semitransparent surfaces
Authors: V. A. Debelov, G. G. Smirnova, L. F. Vasilyeva
Venue: Programming and Computing Software (2008)

The light meshes method (a modification of the Whitted backwards recursive ray tracing) was justified and studied for scenes consisting of opaque surfaces. Its main difference from the basic method is that the rendered image may include soft shadows (i.e., point sources are simulated by area sources). This study makes a further step in the development of this method: it is extended for rendering scenes containing semitransparent surfaces. A few computational schemes are considered and, for each of them, the difference between the image calculated by the standard scheme and obtained by the application of the light meshes method is shown.
A Lexical Approach for Spanish Question Answering
Authors: Alberto Téllez, Antonio Juárez, Gustavo Hernández, Claudia Denicia, Esaú Villatoro, Manuel Montes, Luis Villaseñor
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper discusses our system's results at the Spanish Question Answering task of CLEF 2007. Our system is centered in a full data-driven approach that combines information retrieval and machine learning techniques. It mainly relies on the use of lexical information and avoids any complex language processing procedure. Evaluation results indicate that this approach is very effective for answering definition questions from Wikipedia. In contrast, they also reveal that it is very difficult to respond factoid questions from this resource solely based on the use of lexical overlaps and redundancy.
Parallel distributed fuzzy PID control of hydro turbine generator
Authors: Michail Petrov, Albena Taneva, Teofana Puleva, Emil Garipov
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

In this paper the design methodology of parallel distributed fuzzy PID control is presented. The idea is to design a control law for each rule of the fuzzy controller and blend them together. The proposed parallel distributed fuzzy control algorithm is developed as a natural similarity to the conventional PID controller. This paper describes the structure and the design aspects of a fuzzy PID controller based on Takagi-Sugeno fuzzy technique with fuzzy-neural implementation. The antecedent part of the applied fuzzy rules contains a linear function, similar to the discrete equation of the corresponding conventional controller. The final controller is realized as a parallel distributed combination of the local controllers represented into the fuzzy rules. The simulations demonstrate satisfactory results of these performances and implementations applied to a nonlinear plant - hydro turbine generator.