ppxscal/embedding_network huggingface dataset:
Analyzing Hypervolume Indicator Based Algorithms
Authors: Dimo Brockhoff, Tobias Friedrich, Frank Neumann
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

Indicator-based methods to tackle multiobjective problems have become popular recently, mainly because they allow to incorporate user preferences into the search explicitly. Multiobjective Evolutionary Algorithms (MOEAs) using the hypervolume indicator in particular showed better performance than classical MOEAs in experimental comparisons. In this paper, the use of indicator-based MOEAs is investigated for the first time from a theoretical point of view. We carry out running time analyses for an evolutionary algorithm with a (μ + 1)-selection scheme based on the hypervolume indicator as it is used in most of the recently proposed MOEAs. Our analyses point out two important aspects of the search process. First, we examine how such algorithms can approach the Pareto front. Later on, we point out how they can achieve a good approximation for an exponentially large Pareto front.
Accuracy of Velocity Perception Generated by Tactile Apparent Motion
Authors: Kentaro Kotani, Yuki Imae, Takafumi Asao, Ken Horii
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The objective of this study is to empirically compare the accuracy of velocity perception generated by visual apparent motion with that generated by tactile apparent motion. From the results, the subjects were able to perceive velocity information through tactile stimulus presentation more accurately than through visual stimulus presentation. When tactile stimuli were presented, the effect of apparent motion enhanced the accuracy of velocity perception; however, this was not the case when the stimulus sets were visually presented.
Erlang testing and tools survey
Authors: Tamás Nagy, Anikó Nagyné Víg
Venue: Proceedings of the 7th ACM SIGPLAN workshop on ERLANG (2008)

As the commercial usage of Erlang increases, so does the need for mature development and testing tools. This paper aims to evaluate the available tools with their shortcomings, strengths and commercial usability compared to common practices in other languages. To identify the needs of Erlang developers in this area we published an online survey advertising it in various media. The results of this survey and additional research in this field is presented. Through the comparison of tools and the requirements of the developers the paper identifies paths for future development.
Implicit extension of taylor series method for initial value problems
Authors: Gyözö Molmárka
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

The Taylor series method is one of the earliest analytic-numeric algorithms for approximate solution of initial value problems for ordinary differential equations. The main idea of the rehabilitation of these algorithms is based on the approximate calculation of higher derivatives using well-known technique for the partial differential equations. The approximate solution is given as a piecewise polynomial function defined on the subintervals of the whole interval. This property offers different facility for adaptive error control. This paper describes several explicit Taylor series with implicit extension algorithms and examines its consistency and stability properties. The implicit extension based on a collocation term added to the explicit truncated Taylor series. This idea is different from the general collocation method construction, which conduces to the implicit R-K algorithms [12]. It demonstrates some numerical test results for stiff systems herewith we attempt to prove the efficiency of these new-old algorithms.
Discovery and analysis of genomic patterns: applications to transcription factor binding and genome rearrangement
Authors: Jaroslaw Meller, Anil G. Jegga
Venue:  (2008)

One of the most challenging open problems of the post-genomic era for computer scientists, bioinformaticians and molecular biologists is to identify and characterize all the elements involved in the gene regulation, at both the transcriptional and post-transcriptional level. The rapid availability of multiple genomes also necessitates a need for efficient computational solutions to aid in comparative syntenic analysis&mdash;the analysis of relative gene-order conservation between species&mdash;which can provide key insights into evolutionary chromosomal dynamics, rearrangement rates between species, and speciation analysis. Thus, in this dissertation, we address these issues and develop computational approaches to identify genomic patterns at both micro and macro levels. To address the problem of gene regulation, we developed algorithms for identifying transcription factor binding sites (short repeated patterns or sequence motifs) in genomes. We have developed a level-based search algorithm which is able to identify regulatory motifs in a wide variety of datasets and demonstrate that our method works more efficiently than the current best methods. Further, we have also developed statistical models for identification of known motifs. Finally, we refine the motif discovery process through methods that discriminate and characterize the co-factors of a transcription factor. At macro level, we developed efficient methods (Cinteny) for fast identification of syntenic blocks with various levels of coarse graining and determine evolutionary relationships between genomes in terms of the number of rearrangements (the reversal distance). Cinteny web server integrates syntenic region browsing with evolutionary distance assessment, offers flexibility to adjust all parameters and recompute the results on-the-fly, and ability to work with user provided data.
On Applying Dimension Reduction for Multi-labeled Problems
Authors: Moonhwi Lee, Cheong Hee Park
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Traditional classification problem assumes that a data sample belongs to one class among the predefined classes. On the other hand, in a multi-labeled problem such as text categorization, data samples can belong to multiple classes and the task is to output a set of class labels associated with new unseen data sample. As common in text categorization problem, learning a classifier in a high dimensional space can be difficult, known as the curse of dimensionality. It has been shown that performing dimension reduction as a preprocessing step can improve classification performances greatly. Especially, Linear discriminant analysis (LDA) is one of the most popular dimension reduction methods, which is optimized for classification tasks. However, in applying LDA for a multi-labeled problem some ambiguities and difficulties can arise. In this paper, we study on applying LDA for a multi-labeled problem and analyze how an objective function of LDA can be interpreted in multi-labeled setting. We also propose a LDA algorithm which is effective in a multi-labeled problem. Experimental results demonstrate that by considering multi-labeled structures LDA can achieve computational efficiency and also improve classification performances greatly.
Team project patterns for college students
Authors: Darren Hayes, Jonathan Hill, Anne Mannette-Wright, Henry Wong
Venue: Proceedings of the 2006 conference on Pattern languages of programs (2006)

Team Project Patterns for College Students is a pattern language intended for use by faculty instructing college students. The language is not designed for the college or university environment where courses are taught online but rather can be applied universally to third level education. There are two goals with implementing these patterns: (i) Team Building and (ii) Enhance Shared Learning. In writing these patterns, we were using examples of semester-long projects.
Any-World Access to OWL from Prolog
Authors: Tobias Matzner, Pascal Hitzler
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

The W3C standard OWL provides a decidable language for representing ontologies. While its use is rapidly spreading, efforts are being made by researchers worldwide to augment OWL with additional expressive features or by interlacing it with other forms of knowledge representation, in order to make it applicable for even further purposes. In this paper, we integrate OWL with one of the most successful and most widely used forms of knowledge representation, namely Prolog, and present a hybrid approach which layers Prolog on top of OWL in such a way that the open-world semantics of OWL becomes directly accessible within the Prolog system.
DeMIMA: A Multilayered Approach for Design Pattern Identification
Authors: Yann-Gaël Guéhéneuc, Giuliano Antoniol
Venue: IEEE Transactions on Software Engineering (2008)

Design patterns are important in object-oriented programming because they offer design motifs, elegant solutions to recurrent design problems, which improve the quality of software systems. Design motifs facilitate system maintenance by helping to understand design and implementation. However, after implementation, design motifs are spread throughout the source code and are thus not directly available to maintainers. We present DeMIMA, an approach to identify semi-automatically micro-architectures that are similar to design motifs in source code and to ensure the traceability of these micro-architectures between implementation and design. DeMIMA consists of three layers: two layers to recover an abstract model of the source code, including binary class relationships, and a third layer to identify design patterns in the abstract model. We apply DeMIMA to five open-source systems and, on average, we observe 34% precision for the considered 12 design motifs. Through the use of explanation-based constraint programming, DeMIMA ensures 100% recall on the five systems. We also apply DeMIMA on 33 industrial components.
Charles University at CLEF 2007 Ad-Hoc Track
Authors: Pavel Češka, Pavel Pecina
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)

In this paper we describe retrieval experiments performed at Charles University in Prague for participation in the CLEF 2007 Ad-Hoc track. We focused on the Czech monolingual task and used the LEMUR toolkit as the retrieval system. Our results demonstrate that for Czech as a highly inflectional language, lemmatization significantly improves retrieval results and manually created queries are only slightly better than queries automatically generated from topic specifications.
On Iterative Algorithms with an Information Geometry Background
Authors: Imre Csiszár
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

Several extremum problems in Statistics and Artificial Intelligence, e.g., likelihood maximization, are often solved by iterative algorithms such as iterative scaling or the EM algorithm, admitting an intuitive "geometric" interpretatation as iterated projections in the sense of Kullback information divergence. Such iterative algorithms, including those using Bregman rather than Kullback divergences, will be surveyed. It will be hinted to that the celebrated belief propagation (or sum-product) algorithm may also admit a similar interpretation.
Development of software using fuzzy logic to predict erosive wear in slurry pipeline system
Authors: Rajat Gupta, Bikramjit Chowdhury, Ambarish Kapil Barpujari, Jnandeep Borbarua
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

The phenomenon of wear is a major challenge in transportation through slurry pipeline system. A predictive software tool has been devised using Fuzzy Logic for predicting the erosive wear rate in slurry pipeline system. It is based on published experimental results conducted in a pot tester for two materials namely brass and mild steel. The software is coded using Java Programming Language. It has been established that the predictive tool devised works with fair approximation in relation to the experimental results. So it is proposed that this predictive tool can be used in industries as a tool for carrying out predictive maintenance operations in the slurry pipeline system.
A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer
Authors: Paul R. Smart, Alistair Russell, Dave Braines, Yannis Kalfoglou, Jie Bao, Nigel R. Shadbolt
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Query formulation is a key aspect of information retrieval, contributing to both the efficiency and usability of many semantic applications. A number of query languages, such as SPARQL, have been developed for the Semantic Web; however, there are, as yet, few tools to support end users with respect to the creation and editing of semantic queries. In this paper we introduce NITELIGHT, a Web-based graphical tool for semantic query construction that is based on the W3C SPARQL specification. NITELIGHT combines a number of features to support end-users with respect to the creation of SPARQL queries. These include a columnar ontology browser, an interactive graphical design surface, a SPARQL-compliant visual query language, a SPARQL syntax viewer and an integrated semantic query results browser. The functionality of each of these components is described in the current paper. In addition, we discuss the potential contribution of the NITELIGHT tool to rule creation/editing and semantic integration capabilities.
From 3D Discrete Surface Skeletons to Curve Skeletons
Authors: Carlo Arcelli, Gabriella Sanniti Di Baja, Luca Serino
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

An algorithm to compute the curve skeleton of a 3D object starting from its surface skeleton is presented. The voxels of the surface skeleton are suitably classified to compute the geodesic distance transform of the surface skeleton and to identify anchor points. Voxels are examined in increasing distance order and are removed, provided that they are not anchor points and are not necessary to preserve topology. The resulting curve skeleton is topologically equivalent to the surface skeleton and reflects its geometry.
WebAngels Filter: A Violent Web Filtering Engine Using Textual and Structural Content-Based Analysis
Authors: Radhouane Guermazi, Mohamed Hammami, Abdelmajid Ben Hamadou
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

The development of the Web has been paralleled by the proliferation of harmful Web pages content. Using Violent Web page as a case study, we review some existing solutions, then we propose a violent Web content detection and filtering system called "WebAngels filter" which uses textual and structural analysis. "WebAngels filter" has the advantage of combining several data mining algorithms for Web site classification. We present a comparative study of different data mining techniques to block violent contentWeb pages. Also, we discuss how the combination learning based methods can improve filtering performances. Our results show that it can detect and filter violent content effectively.
Distributed trust management in autonomic networks
Authors: John S. Baras
Venue:  (2007)

The management of autonomic networks has gained more and more attentions because of their wide applications and control difficulties. Autonomic networks are decentralized and self-organized. Without global knowledge on the states of autonomic networks, it is difficult to predict behaviors of such networks and thus to conduct proper network management and control. This dissertation is the starting point of my effort to theoretically understand the complex characteristics of autonomic networks. In particular, I focus on a specific application: distributed trust management. We view trust among users as a set of relations established on the basis of trust credentials and required by specified policies. Two important components of a distributed trust management system are studied in this work: trust credential distribution and trust evaluation. In autonomic networks, trust credentials are distributed throughout the network. Given the mobility and dynamics of the networks, it is important to properly distribute trust credentials such that users are able to efficiently obtain required credentials and update existing credentials. I present a trust credential distribution scheme based on network coding. After obtaining credentials in need, policies are required for users to evaluate trustworthiness of targets in a distributed way. In this dissertation, I model distributed trust evaluation as an estimation problem and trust evaluation policies based on local interactions are studied. I investigate the convergence of both deterministic and stochastic voting rules and prove their effectiveness with the present of misbehaving users. Autonomic networks rely on collaboration among users. The conflict between the benefit from collaboration and the required cost for collaboration naturally leads to game-theoretic studies. I study collaboration based on cooperative games with communication constraints and give the conditions under which users are willing to collaborate. The results in this dissertation show that a well-designed trust management system is helpful to enforce collaboration. Besides collaboration, I show that trust can be used to the utility optimization problems as well. The effect of trust values is that in the routing and scheduling problems the trustworthiness of the node will be automatically considered and used. For example, packets will not be routed frequently to suspicious nodes.
Webstrategy Formulation: Benefiting from Web 2.0 Concepts to Deliver Business Values
Authors: Senoaji Wijaya, Marco R. Spruit, Wim J. Scheper
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

With the accelerating growth of internet users, a rise of globalization, distributed work environments, knowledge-based economies, and collaborative business models, it becomes clear that there is currently a high and growing number of organizations that demand a proper webstrategy. The emergence of web 2.0 technologies has led many internet companies, such as Google, Amazon, Wikipedia, and Facebook, to successfully adjust their webstrategy by adopting web 2.0 concepts to sustain their competitive advantage and reach their objectives. This has raised an interest for more traditional organizations to benefit from web 2.0 concepts in order to enhance their competitive advantage. This article discusses the effective webstrategy formulation based on the web 2.0 concepts in [21] and the differing requirements, characteristics, and objectives in different types of organizations. This research categorizes organizations into Customer Intimacy, Operational Excellence, and Product Leadership, according to the Value Disciplines model in [26].
A Multicriteria Fuzzy System Using Residuated Implication Operators and Fuzzy Arithmetic
Authors: Sandra Sandri, Christophe Sibertin-Blanc, Vicenç Torra
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

We present a multicriteria fuzzy system using gradual rules and fuzzy arithmetic. We first present a multicriteria problem and its solution for the case of precise information. Then we extend the model to treat pieces of information that may involve imprecision/vagueness. We show that the use of residuated implication operators, employed by gradual rules, coupled with similarity relations offer a better treatment of the problem than a Mamdani-like approach.
Integration of Stereoscopic and Perspective Cues for Slant Estimation in Natural and Artificial Systems
Authors: Eris Chinellato, Angel P. Pobil
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

Within the framework of a model of vision-based robotic grasping inspired on neuroscience data, we deal with the problem of object orientation estimation by analyzing human psychophysical data in order to reproduce them in an artificial setup. A set of ANN is implemented which, on the one hand, allows to replicate some neuroscientific findings and, on the other hand, constitutes a tool for slant estimation that can improve the reliability of artificial vision systems, namely those dedicated to analyze visual data inherent to the interaction robot-environment, such as in grasping actions. The implementation confirms the hypothesis that integration of monocular and binocular data for the extraction of action-related object properties can provide an artificial system with improved pose estimation capabilities.
Nginx: the high-performance web server and reverse proxy
Authors: Will Reese
Venue: Linux Journal (2008)

A leaner, meaner Apache.
Evaluation of plasma damage in ultra-low-k materials with cap film using "extracted k-value" method
Authors: Hyoh Takahashi, Yoshio Takimoto, Makoto Masuda, Yoshito Ando
Venue: Microelectronic Engineering (2008)

An ''extracted k-value'' method has been developed for evaluating postdevice-process damage in ultra-low-k materials inside a multi-layer structure. It is found that an in-depth analysis with using X-ray reflectivity (XRR) is very effective for recognizing the nature of the damage. With these methods, it is investigated that the damage generated in porous methylsilsesquioxane (MSQ) during cap-film deposition and the effect of subsequent process for the improvement.
Dynamic Scheduling Protocol for Highly-Reliable, Real-Time Information Aggregation for Telematics Intersection Safety System(TISS)
Authors: Wang Won Han, Hongjae Park, Young Man Kim
Venue: Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing (2007)

Despite the fact that intersection collisions account for almost 30% of all crashes, intersection collision avoidance systems received less attention than the forward collision avoidance systems[1,2]. It is because the intersection collision problem is more complicated than rear-end crash and the limitations of the radar technology, the most widely used object sensing method in vehicle collision avoidance systems.Recently, in [3,4], an intersection collision warning systems is reported and inter-vehicle data communication is done by direct broadcast based on 802.11[5] or DOLPHIN[6]. It is assumed that DGPS provides data to all the vehicles and all the 4-wheeled vehicles have the access to the navigation system. At a certain distance from the intersection, the vehicles begin to broadcast their locations, directions of travel and speeds. However, this approach has a shortcoming that broadcast is inherently unreliable without ACK messages from all the receiving peers, that is very difficult to be achieved in real-time environment.In this paper, we evaluate a contention-free dynamic scheduling protocol, called Telematics Scheduling Protocol(TSP), for WSN-based intersection safety system in terms of the real-time reliable information aggregation characteristics. In particular, we use ns-2[7] simulator to demonstrate the real-time data aggregation performance of TSP. The performance result of TSP shows very high throughput and short delivery time suitable for the real-time reliable Telematics Intersection Safety System(TISS).