ppxscal/embedding_network huggingface dataset:
Towards Formal Verification of ToolBus Scripts
Authors: Wan Fokkink, Paul Klint, Bert Lisser, Yaroslav S. Usenko
Venue: Proceedings of the 12th international conference on Algebraic Methodology and Software Technology (2008)

ToolBus allows one to connect tools via a software bus. Programming is done using the scripting language Tscript, which is based on the process algebra ACP. Tscript was originally designed to enable formal verification, but this option has so far not been explored in any detail. We present a method for analyzing a Tscript by translating it to the process algebraic language mCRL2, and then applying model checking to verify behavioral properties.
Left Ventricle Tracking Using Overlap Priors
Authors: Ismail Ayed, Yingli Lu, Shuo Li, Ian Ross
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

This study investigates overlap priors for tracking the Left Ventricle (LV) endo- and epicardium boundaries in cardiac Magnetic Resonance (MR) sequences. It consists of evolving two curves following the Euler-Lagrange minimization of two functionals each containing an original overlap prior constraint. The latter measures the conformity of the overlap between the nonparametric (kernel-based) intensity distributions within the three target regions---LV cavity, myocardium and background---to a prior learned from a given segmentation of the first frame. The Bhattacharyya coefficient is used as an overlap measure. Different from existing intensity-driven constraints, the overlap priors do not assume implicitly that the overlap between the distributions within different regions has to be minimal. Although neither shape priors nor curve coupling were used, quantitative evaluation showed that the results correlate well with independent manual segmentations and the method compares favorably with other recent methods. The overlap priors lead to a LV tracking which is more versatile than existing methods because the solution is not bounded to the shape/intensity characteristics of a training set. We also demonstrate experimentally that the used overlap measures are approximately constant over a cardiac sequence.
An Improved Evolutionary Algorithm for Dynamic Vehicle Routing Problem with Time Windows
Authors: Jiang-Qing Wang, Xiao-Nian Tong, Zi-Mao Li
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

The dynamic vehicle routing problem is one of the most challenging combinatorial optimization tasks. The interest in this problem is motivated by its practical relevance as well as by its considerable difficulty. We present an approach to search for best routes in dynamic network. We propose a dynamic route evaluation model for modeling the responses of vehicles to changing traffic information, a modified Dijkstra's double bucket algorithm for finding the real-time shortest paths, and an improved evolutionary algorithm for searching the best vehicle routes in dynamic network. The proposed approach has been evaluated by simulation experiment using DVRPSIM. It has been found that the proposed approach quite efficient in finding real-time best vehicle routes where the customer nodes and network information changes dynamically.
Fuzzy Bilateral Matchmaking in e-Marketplaces
Authors: Azzurra Ragone, Umberto Straccia, Fernando Bobillo, Tommaso Noia, Eugenio Sciascio
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

We present a novel Fuzzy Description Logic (DL) based approach to automate matchmaking in e-marketplaces. We model traders' preferences with the aid of Fuzzy DLs and, given a request, use utility values computed w.r.t. Pareto agreements to rank a set of offers. In particular, we introduce an expressive Fuzzy DL, extended with concrete domains in order to handle numerical, as well as non numerical features, and to deal with vagueness in buyer/seller preferences. Hence, agents can express preferences as e.g. I am searching for a passenger car costing about 22000¿ yet if the car has a GPS system and more than two-year warranty I can spend up to 25000¿. Noteworthy our matchmaking approach, among all the possible matches, chooses the mutually beneficial ones.
Assessing the Influence of Stereotypes on the Comprehension of UML Sequence Diagrams: A Controlled Experiment
Authors: Marcela Genero, José A. Cruz-Lemus, Danilo Caivano, Silvia Abrahão, Emilio Insfran, José A. Carsí
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

The main goal of this paper is to provide empirical evidence, through a controlled experiment, of the influence of stereotypes when modelers, developers, and maintainers have to comprehend UML sequence diagrams. The comprehension of UML sequence diagrams with and without stereotypes was analyzed from three different perspectives: semantic comprehension, retention and transfer. The experiment was carried out with 77 fourth year undergraduate students of Computer Science from the University of Bari in Italy. The results obtained show a slight tendency in favor of the use of stereotypes in facilitating the comprehension of UML sequence diagrams, although it is not statistically significant. Further replications are needed to obtain more conclusive results.
Finding Minimum Containing Cylinder of Space Finite Points with Genetic Algorithm
Authors: Hongfa Wang, Ming Zhou
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The geometric concepts of outer containing cylinder for space finite points have frequently been introduced into the evaluation of molding error of cylinder surface in the operation of mechanical manufacturing and mold processing. Since space finite points obviously consists of numerous outer containing cylinders, a mathematical model is built to find the minimum outer containing cylinder in this paper, which converts the task to a problem of function optimization which is solved by a genetic algorithm. Experimental results show that the proposed algorithm has advantages of high convergence speed, efficiency and accuracy.
A New Fuzzy Risk Assessment Approach
Authors: Huey-Ming Lee, Lily Lin
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

In this paper, we present computational rule inferences to tackle the rate of aggregative risk in fuzzy circumstances. Because the proposed assessment method directly uses the fuzzy numbers rather than the linguistic values to evaluate, it can be executed faster than before. The proposed fuzzy assessment method is easier, closer to evaluator real thinking and more useful than the ones they have presented before.
Topological Complexity of the Relative Closure of&#x00a0;a&#x00a0;Semi-Pfaffian&#x00a0;Couple
Authors: Thierry Zell
Venue: Discrete Computational Geometry (2008)

Gabrielov introduced the notion of relative closure of a Pfaffian couple as an alternative construction of the o-minimal structure generated by Khovanskii&#x2019;s Pfaffian functions. In this paper, we use the notion of format (or complexity) of a Pfaffian couple to derive explicit upper bounds for the homology of its relative closure. We consider both the singular and the Borel&#x2013;Moore homology theories.
Parameterized Complexity and Logic
Authors: Jörg Flum
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We introduce and discuss some basic concepts of parameterized complexity theory via model-checking problems.
Characterization of copper grain growth limitations inside narrow wires depending of overburden thickness
Authors: O. Dubreuil, M. Cordeau, Th. Mourier, P. Chausse, M. Mellier, D. Bellet, J. Torres
Venue: Microelectronic Engineering (2008)

With the downscaling of feature dimensions, copper interconnects exhibit properties differing from bulk or film material. Resistivity increases and limits electrical performances, and reliability of interconnects becomes a more important challenge for each new technological node. In this study, we present an approach of copper grain growth control inside narrow wires by adding a step between the copper electro-chemical deposition (ECD) and the chemical-mechanical polishing (CMP). This step corresponds to a partial CMP step (pre-CMP) and is applied after ECD and before anneal in order to modify the copper overburden thickness. Depending on the targeted thickness, copper grain growth occurs during anneal with different efficiencies. Crystallization and grain growth behaviour inside wires is investigated with focused ions beam (FIB). We present here our methodology for sample preparation and characterization. Results are focused on electrical variations and on morphological aspects of copper crystallization and grain growth inside lines observed with various overburden thicknesses.
Word of Mouth: Rumor Dissemination in Social Networks
Authors: Jan Kostka, Yvonne Anne Oswald, Roger Wattenhofer
Venue: Proceedings of the 15th international colloquium on Structural Information and Communication Complexity (2008)

In this paper we examine the diffusion of competing rumors in social networks. Two players select a disjoint subset of nodes as initiators of the rumor propagation, seeking to maximize the number of persuaded nodes. We use concepts of game theory and location theory and model the selection of starting nodes for the rumors as a strategic game. We show that computing the optimal strategy for both the first and the second player is NP-complete, even in a most restricted model. Moreover we prove that determining an approximate solution for the first player is NP-complete as well. We analyze several heuristics and show that--counter-intuitively--being the first to decide is not always an advantage, namely there exist networks where the second player can convince more nodes than the first, regardless of the first player's decision.
Coping with Uncertainty
Authors: M. Satyanarayanan
Venue: IEEE Pervasive Computing (2003)

This issue of IEEE Pervasive Computing focuses on building systems that deal with uncertainty. "Bayesian Filtering for Location Estimation" discusses how to reduce uncertainty in location estimates through statistical techniques. "Coping with Uncertainty in a Location-Based Game" discusses the impact of uncertainty in location sensing on user experience. It describes this impact in the context of a game and presents the authors' attempts to overcome the effects of this uncertainty. "Managing Context Information in Mobile Devices" describes a context management framework and API that simplifies the programming complexity of developing systems that handle uncertainty. Finally, "Using Trust for Secure Collaboration in Uncertain Environments" addresses the problem of uncertainty in the context of security. This uncertainty leads to risk, and the authors describe techniques to handle this risk.
Real-Time Neighborhood Based Disparity Estimation Incorporating Temporal Evidence
Authors: Bogumil Bartczak, Daniel Jung, Reinhard Koch
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

This paper presents a system for dense area based disparity estimation from binocular rectified image sequences with the integration of temporal evidence. The system is using dense 2D optical flow fields and timely displaced disparity estimates to reason about the observed 3D scene flow. This scene flow is then exploited to strengthen timely consistent observations in the disparity estimation. Moreover a novel neighborhood assumption is presented, which allows to seamlessly implement the presented algorithm on the GPU. It is shown that by means of the presented approach the sensitivity to noise and ambiguities observed with plain real-time disparity estimations can be improved, even in fully dynamic scenarios with simultaneous movement of objects and cameras.
A New Approach to Interactive Visual Search with RBF Networks Based on Preference Modelling
Authors: Paweł Rotter, Andrzej M. Skulimowski
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

In this paper we propose a new method for image retrieval with relevance feedback based on eliciting preferences from the decision-maker acquiring visual information from an image database. The proposed extension of the common approach to image retrieval with relevance feedback allows it to be applied to objects with non-homogenous colour and texture. This has been accomplished by the algorithms, which model user queries by an RBF neural network. As an example of application of this approach, we have used a content-based search in an atlas of species. An experimental comparison with the commonly used content-based image retrieval approach is presented.
Applying stochastic resonance to magnify µ and β wave suppression
Authors: Chou-Ching K. Lin, Ming-Shaung Ju, Cheng-Wei Hsu, Yung-Nien Sun
Venue: Computers in Biology and Medicine (2008)

The goal was to test whether band-limited sensory noises with adequate amplitudes, by the principle of stochastic resonance, could enhance @m and @b wave suppressions. Scalp EEG was recorded while the subject performed thumb movements in the presence of vibratory noises applied to thenar belly or thumb tip. Seven subjects without clear @m or @b wave suppression in the absence of the mechanical stimuli were recruited. The results showed that when the stimuli were applied to the thenar belly, both @m and @b wave suppressions were enhanced in a bell-shaped trend (the characteristics of stochastic resonance) in four subjects.
Adaptive Natural Gradient Algorithm for Blind Convolutive Source Separation
Authors: Jian Feng, Huaguang Zhang, Tieyan Zhang, Heng Yue
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

An adaptive natural gradient algorithm for blind source separation based on convolutional mixture model is proposed. The proposed method makes use of cost function as optimum criterion in separation process. The update formula of separation matrix is deduced. The learning steps for blind source separation algorithm are given, and high capability of the proposed algorithm has been demonstrated. The simulations results have shown the validity, practicability and the better performance of the proposed method. This technique is suitable for many applications in real life systems.
Verification of Expressiveness of Procedural Parameters for Generating Emotional Motions
Authors: Yueh-Hung Lin, Chia-Yang Liu, Hung-Wei Lee, Shwu-Lih Huang, Tsai-Yen Li
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

Body movements are crucial for emotion expression of a virtual agent. However, the perception of expressiveness of an animation has always been a subjective matter. Research in psychology has asked professional actors to perform emotional motions to study how body gestures deliver emotions [2]. In this work, we aim to design an animation system that can generate human body motions in a more systematic manner and then study the expressiveness of the generated animation as a preceding step for the study of the relation between motion and emotion.
On the Reachability Analysis of Acyclic Networks of Pushdown Systems
Authors: Mohamed Faouzi Atig, Ahmed Bouajjani, Tayssir Touili
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

We address the reachability problem in acyclic networks of pushdown systems. We consider communication based either on shared memory or on message passing through unbounded lossy channels. We prove mainly that the reachability problem between recognizable sets of configurations (i.e., definable by a finite union of products of finite-state automata) is decidable for such networks, and that for lossy channel pushdown networks, the channel language is effectively recognizable. This fact holds although the set of reachable configurations (including stack contents) for a network of depth (at least) 2 is not rational in general (i.e., not definable by a multi-tape finite automaton). Moreover, we prove that for a network of depth 1, the reachability set is rational and effectively constructible (under an additional condition on the topology for lossy channel networks).
Supporting Collaborative Learning With An Intelligent Web-Based System
Authors: Judith Israel, Robert Aiken
Venue: International Journal of Artificial Intelligence in Education (2007)

This research describes an Intelligent Collaborative Support System (ICSS) that supports a collaborative effort by analyzing and modifying the collaborative process dynamically while employing a web-based interface. Based upon principles rooted in Computer-Supported Cooperative Work (CSCW), Intelligent Tutoring Systems (ITS) and Cooperative Learning (CL), this system extends the Group Leader paradigm to assist students working together in collaborative groups. Discussion skills are supported by examination of sentence openers chosen from a menu, keywords found in free-text sentence closers, student and group models, and historical database files. Groups are categorized and guided toward the optimal category of a high-performing cooperative group with positive interdependence. The use of the dialogue designated as creative conflict is mediated by an agent to assist in formulating a constructive discussion, serving as an instructional tool. Conflicts in the categorization of discussion skills exhibited in the sentence openers versus the sentence closers are resolved. Implemented in Java, the Group Leader module interacts with intelligent agents as it guides students working in groups remotely in the cross-platform environment provided by the Java Virtual Machine.
Mobile Robot Global Path Planning Based on Improved Augment Ant Colony Algorithm
Authors: Meijuan Gao, Jin Xu, Jingwen Tian
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

To overcome the defects of precocity and the time for initial population building is too long in traditional augment ant colony algorithm for mobile robot global path planning, an improved augment ant colony algorithm is presented in this paper. The operations of crossover and mutation of genetic algorithm (GA) are used in augment ant colony optimization, and the heuristic probability function is added to the process of the initial population building. The process flow of improved ant colony algorithm is given and the simulation experiment is done under the VC++ 6.0 environment. Experimental results show that the algorithm has much higher capacity of global optimization than traditional augment ant colony algorithm.
Dynamic Error of Heat Measurement in Transient
Authors: Fang Lide, Li Jinhai, Cao Suosheng, Zhu Yan, Kong Xiangjie
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

According to EN1434 (European Standard) and OIML R-75(International Organization of Legal Metrology), there are two methods in heat measurement, and they are all steady-state methods of test, using them in transient, obvious error will be produced, so some accurately measuring functions should be seeking. In a previous published paper of the author, a transient function relationship of heat quantity and time is deduced, and the validity of this function is proved through experimentation, also it is simplified reasonably, so it can be used in variable flow rate heating system. In this study, a comparison with steady-state method and dynamic method is presented, the errors exist in the steady state method are analyzed. A conclusion is improved that the steady-state methods used in variable flow heating system will result in appreciable errors, the errors only exist in transient, when system reach steady state, the errors disappear, moreover, the transient time is long in heating system, it is at least 30 minutes, so it is necessary to take some measures to correct them, however, study showed that the error can be ignored when the flow rate step change is less than 5kg/h.
Joining the results of heterogeneous search engines
Authors: Daniele Braga, Alessandro Campi, Stefano Ceri, Alessandro Raffio
Venue: Information Systems (2008)

In recent years, while search engines have become more and more powerful, several specialized search engines have been developed for different domains (e.g. library services, services dedicated to specific business sectors, geographic services, and so on). While such services beat generic search engines in their specific domain, they do not enable cross-references; therefore, they are of little use when queries require input from two or more of such services (e.g., ''find papers in VLDB 2000 authored by a member of a specified department'' or ''books sold online written by prolific database authors'' or ''vegetarian restaurants in the surroundings of San Francisco''). In this paper, we study how to join heterogeneous search engines and get a unique answer that satisfies conjunctive queries, where each query can be routed to a specialized engine. The paper includes both the theoretical framework for stating such problem and the description of pragmatic solutions based on web service technology. We present several algorithms for the efficient computation of join results under several cost model assumptions.
Influence of Resampling and Weighting on Diversity and Accuracy of Classifier Ensembles
Authors: R. M. Valdovinos, J. S. Sánchez, E. Gasca
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Diversity in the decisions of a classifier ensemble appears as one of the main issues to take into account for its construction and operation. However, the potential relationship between diversity and accuracy, with respect to the resampling method and/or the classifier fusion technique has not been clearly proved. The present paper analyzes the influence of different resampling methods and dynamic weighting schemes on diversity and how this can affect to the accuracy of the classifier ensemble. This is specifically studied in the framework of the Nearest Neighbor classification algorithm.
Enhancing predictive models using principal component analysis and search based metric selection: a comparative study
Authors: Rodrigo Vivanco, Dean Jin
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Predictive models are used for the detection of potentially problematic component that decrease product quality. Source code metrics can be used as input features in predictive models; however, there exist numerous structural measures that capture different aspects of size, coupling, cohesion, inheritance and complexity. An important question to answer is which metrics should be used with a predictor. A comparative analysis of metric selection strategies (principal component analysis, a genetic algorithm and the CK metrics set) has been carried out. Initial results indicate that search-based metric selection gives the best predictive performance in identifying Java classes with high cognitive complexity that degrades product maintenance.