ppxscal/embedding_network huggingface dataset:
Embedded Neural Network for Swarm Learning of Physical Robots
Authors: Pitoyo Hartono, Sachiko Kakita
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

In this study we ran real time learning of multiple physical autonomous robots situated in a real dynamic environment. Each robot has an onboard micro controller where a simple neural network is embedded. The neural network was built with the consideration of the power and calculation resources limitation which is a general characteristic of simple robots. In the experiments, several autonomous robots were placed in one environment, where each of them was given a specific task which was expressed as the evaluation function for the robot's neural network. The learning processes of the robots were started simultaneously from their randomized initial conditions. The presence of several robots consequently formed a dynamic environment, in which an action of one robot affected the learning process of others. We demonstrated the efficiency of the embedded learning mechanism with respect to different environmental factors.
Reading Beside the Lines: Indentation as a Proxy for Complexity Metric
Authors: Abram Hindle, Michael W. Godfrey, Richard C. Holt
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

Maintainers face the daunting task of wading through a collection of both new and old revisions, trying to ferret out revisions which warrant personal inspection. One can rank revisions by size/lines of code (LOC), but often, due to the distribution of the size of changes, revisions will be of similar size. If we can't rank revisions by LOC perhaps we can rank by Halstead's and McCabe's complexity metrics? However, these metrics are problematic when applied to code fragments (revisions) written in multiple languages: special parsers are required which may not support the language or dialect used; analysis tools may not understand code fragments. We propose using the statistical moments of indentation as a lightweight, language independent, revision/diff friendly metric which actually proxies classical complexity metrics. We have extensively evaluated our approach against the entire CVS histories of the 278 of the most popular and most active SourceForge projects. We found that our results are linearly correlated and rank-correlated with traditional measures of complexity, suggesting that measuring indentation is a cheap and accurate proxy for code complexity of revisions. Thus ranking revisions by the standard deviation and summation of indentation will be very similar to ranking revisions by complexity.
A Recommender System Architecture for Instructional Engineering
Authors: Manuel E. Prieto, Víctor H. Menéndez, Alejandra A. Segura, Christian L. Vidal
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

In recent years, Recommender System's models and techniques, have been applied in e-Learning and main efforts are been centered in learners, their guide and their success when using Learning Management Systems and other Web-based and virtual artifacts. Several techniques were adapted or even developed for this purposes. Our current project is concerned to the need to develop a Recommender System Architecture that may assist teachers in their e-Learning design practices. Instructional Design Methods, Learning Theories, Efficient Searching Methods and Tools and Meta-data Managing, are examples of the necessary knowledge and abilities. In this document we are centered in presenting the overall system architecture and describing their main parts. We are also reporting actual results. Due to it´s wide conception, this project involves Knowledge Engineering, Software Engineering, Machine Learning, Semantic Web Searching, and Data Mining models and tools.
Plenary lecture V: formalisation and verification in a type-theoretic framework
Authors: Zhaohui Luo
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Dependent type theory provides a powerful logical calculus for computer-assisted formal reasoning. The associated technology of theorem proving has produced very useful tools, the so-called "proof assistants", for formal proof development both in verification of programs and in formalisation of mathematics. After giving an overview of the research field, I shall present a new type-theoretic framework LTT and explain its use in formalisation and verification. The particular features of the LTT framework include: LTT is a foundational calculus for formal reasoning with different logical foundations, establishing the basis for wider applications of the type theory based theorem proving technology. LTT employs a notion of "typed set", combining type-theoretical reasoning with set-theoretical reasoning in an effective way and supporting efficient proof development in formalisation and verification. As a promising framework, LTT has been used in several case studies, including the formalisation of Weyl's predicative mathematics and the analysis of security protocols.
A Numerical Solutions Based on the Quasi-wavelet Analysis
Authors: Z. H. Huang, L. Xia, X. P. He
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Taking the approximate equations for long waves in shallow water as example, the quasi-wavelet discrete scheme is proposed for obtaining numerical solution of the (1+1) dimension nonlinear partial differential equation. In the method, the quasi-wavelet discrete scheme is adopted to discretize the spatial derivative discrete and the ordinary differential equation about time is obtained. Then the fourth order Rung-Katta method is employed to discretize the temporal derivative. Finally the quasi-wavelet solution is compared with the analytical solution, and the computations are validated.
Analysis of Japanese folktales for the purpose of story generation
Authors: Takaaki Kato, Koji Miyazaki, Ryohei Nakatsu
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

We are developing an interactive folktale system in which users can enjoy both the generation of Japanese folktales as well as interaction with the system. In order to generate any kind of Japanese folktale, the system must give each character appearing in the folktales the ability to achieve a sufficient number of motions. To determine the number of motions that need to be prepared for the system, we carried out an analysis of the verbs that appear in Japanese folktales. Based on the analysis of 50 representative Japanese folktales, we found that the total number of verbs used is more than 2,000. By deleting the overlap of verbs in different folktales, while giving consideration to their meanings in actual usage, the number decreased to about 900. In addition, by restricting the verbs to those that can be expressed by computer graphics, the total number of verbs further decreased to about 100. Then we carried out experiments on generating various scenes of Japanese folktales by using several motion sets, each of which is a subset of the 100 motions corresponding to the reduced verbs. Finally, we evaluated the least number of animations needed to generate animations of sufficient quality.
Spindle-Deviation Minimization Method for Classification in NDE System
Authors: Z. D. Jiang, F. Tong, B. L. Luk, K. P. Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Various feature extraction methods are developed in non-destructive evaluation (NDE). Among many linear methods been proposed, the Fisher linear discriminant is a very useful technique. But as the mean square error (MSE) increased, a classifier based on Fisher criterion will reduce the efficiency. In this paper, we expand the criterion and develop a spindle-deviation minimization (SDM) method to solve the classification problem. A comparison on global solution based on Fisher criterion with our method will be given, and it shows our method has good performance. Also, the results on our impact acoustic NDE system will verify the method efficient further.
Negative Productivity and What to Do about It
Authors: Robert L. Glass
Venue: IEEE Software (2008)

Three anecdotes show how one member of a work team can decrease the whole team's productivity.
An Algorithm for Acquiring Reliable Path in Abnormal Traffic Condition
Authors: Do-Hyeon Lee, Doo-Young Kim, Jae-Il Jung, Young-Soo An
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

Most Reliable Paths algorithm make it enable to select the most stable path on network by considering not only link cost but also link capacity, link operation probability and the size of message to be sent. But this algorithm uses a fixed value as link operation probability so that it can be applicable in the normal network state, not in the network state that traffic abnormally increase. To solve this problem, this thesis applies the packet drop probability of RED (Random Early Detection) method to the operation probability of the most reliable path algorithm so that the most reliable path can be guaranteed. For this purpose, we propose an All-Pairs Most Reliable Paths acquiring algorithm having time complexity based on the All-Pairs Shortest Paths algorithm proposed by Floyd-Warshall.
Chattering-Free LS-SVM Sliding Mode Control
Authors: Jianning Li, Yibo Zhang, Haipeng Pan
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Least squares support vector machine (LS-SVM) classifiers are a class of kernel methods whose solution follows a set of linear equations. In this work we present a least squares support vector machine sliding mode control (LS-SVM-SMC) strategy for uncertain discrete system with input saturation. The output of LS-SVM is used for replacing sign function of the reaching law in traditional sliding mode control (SMC). An equivalent matrix is constructed for input saturation condition in the scheme. Combined LS-SVM-SMC with linear Matrix Inequalities (LMIs), a chattering free control algorithm is applied in the uncertain discrete systems with input saturation. The feasibility and effectiveness of the LS-SVM-SMC scheme are demonstrated via numerical examples. As a result, compared with conventional SMC, the LS-SVM-SMC is able to achieve the desire transient response with input saturation. And there is no chattering in steady state while unmatched parameter uncertainty exists.
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
Authors: Linas Baltrunas, Francesco Ricci
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a set of items are pairwise compared and averaged (correlation). In this paper we make user-to-user similarity adaptive, i.e., we dynamically change the computation depending on the profiles of the compared users and the target item whose rating prediction is sought. We propose to base the similarity between two users only on the subset of co-rated items which best describes the taste of the users with respect to the target item. These are the items which have the highest correlation with the target item. We have evaluated the proposed method using a range of error measures and showed that the proposed locally adaptive neighbor selection, via item selection, can significantly improve the recommendation accuracy compared to standard CF.
Voters' Perceptions of Voting Technology
Authors: Menno De Jong, Joris Van Hoof, Jordy Gosselt
Venue: Social Science Computer Review (2008)

Despite their unmistakable advantages, the use of voting machines in elections is a topic of vivid debates. This article focuses on the experiences of voters using three types of voting equipment: (a) a paper ballot, (b) a voting machine, and (c) a voting machine with paper audit trail. An independent-groups experiment was conducted in which voters had to cast a vote for a donation to a charity organization and afterwards filled out a questionnaire about their voting experiences. The paper ballot was considered to be the most anonymous way of voting, especially by female voters. The voting machine (with or without paper trail), on the other hand, was considered to be more user-friendly than the paper ballot and gave the voters more confidence that their votes would actually be processed correctly. No differences were found between the voting machine with and without paper audit trail.
Routing and Security in Mobile Ad Hoc Networks
Authors: Nikola Milanovic, Miroslaw Malek, Anthony Davidson, Veljko Milutinovic
Venue: Computer (2004)

Mobile ad hoc networks remove the dependence on a fixed network infrastructure by treatingevery available mobile node as an intermediate switch, thereby extending the range of mobile nodes well beyond that of their base transceivers. The authors present four manet routing algorithms along with a hybrid approach, discuss their advantages and disadvantages, and describe security problems inherent in such networks.
Face Detection Based on Template Matching and 2DPCA Algorithm
Authors: Jizeng Wang, Hongmei Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Human face recognition technology is a popular research topic in the biometrics identification area. Face detection is the most important pre-processing module of a face recognition system, and it plays an important role in applications such as video surveillance, human computer interface. The purpose of the face detection is to search and orient faces in images in complex background. In this paper, we propose a hierarchical face detection method by using the template matching algorithm and 2DPCA algorithm. The method includes two different classifiers. The first one is called rough classifier, which filtrates the most of the non-face. The second one is a core classifier, which uses 2DPCA algorithm to detect the face based on the result from the first classifier. The results of the experiment indicates that we implement hierarchical detection to face images not only improves the accurate rate of the face detection, but also shortens detection time greatly.
Petri Nets Are Dioids
Authors: Paolo Baldan, Fabio Gadducci
Venue: Proceedings of the 12th international conference on Algebraic Methodology and Software Technology (2008)

In a seminal paper Montanari and Meseguer showed that an algebraic interpretation of Petri nets in terms of commutative monoids can be used to provide an elegant characterisation of the deterministic computations of a net, accounting for their sequential and parallel composition. Here we show that, along the same lines, by adding an (idempotent) operation and thus taking dioids (commutative semirings) rather than monoids, one can faithfully characterise the non-deterministic computations of a Petri net.
A measurement study of inter-vehicular communication using steerable beam directional antenna
Authors: Anand Prabhu Subramanian, Vishnu Navda, Pralhad Deshpande, Samir R. Das
Venue: Proceedings of the fifth ACM international workshop on VehiculAr Inter-NETworking (2008)

We provide a measurement study of a single vehicle-to-vehicle (V2V) link using 802.11b as the link layer technology. Our goal is to investigate practical usage of steerable beam directional antennas to improve V2V communications. We conduct extensive experiments using commercially available phased-array antennas mounted on cars in two different environments -- suburban roads and highways, with various drive patterns. It is observed that directional beamforming improves the link SNR significantly, that translates to significant range improvements. However, to achieve this performance gain both antenna beams must be steered appropriately in the right direction. We observe that often the best beams indeed point directly to each other (called `LOS beams'), in spite of various sources of reflections that could be present in the environment. We develop and evaluate a simple beam steering approach that uses LOS beams for communication. We present experimental data, demonstrating the performance gains (in terms of SNR and PHY-layer data rates) achieved by this approach. While we have studied a single V2V link, this method can be extended to a multihop V2V network.
A Unified String Kernel for Biology Sequence
Authors: Dehui Yuan, Shengyun Yang, Guoming Lai
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

In this paper, we introduce a unified String Kernel. Based on this unified string kernel, we construct improved sparse kernel and composite kernel. Using the same target families and the same test and training set splits as in the protein classification experiments from Weston, we do experiments with these new kernels. The results show that our kernels are superior to previously developed string kernel.
Syntactic Metatheory of Higher-Order Subtyping
Authors: Andreas Abel, Dulma Rodriguez
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

We present a new proof of decidability of higher-order subtyping in the presence of bounded quantification. The algorithm is formulated as a judgement which operates on beta-eta-normal forms. Transitivity and closure under application are proven directly and syntactically, without the need for a model construction or reasoning on longest beta-reduction sequences. The main technical tool is hereditary substitution, i.e., substitution of one normal form into another, resolving all freshly generated redexes on the fly. Hereditary substitutions are used to keep types in normal-form during execution of the subtyping algorithm. Termination of hereditary substitutions can be proven in an elementary way, by a lexicographic induction on the kind of the substituted variable and the size of the expression substituted into--this is what enables a purely syntactic metatheory.
Plenary lecture two: decision support systems, human centric/centered computing, and computing with words: a synergistic combination?
Authors: Janusz Kacprzyk
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

We start with a brief account of complex decision making problems, and advocate the use of modern approaches to real world decision making emphasizing the concept of a decision making process that involves more factors and aspects like: the use of explicit and tacit knowledge, intuition, individual habitual domains, non-trivial rationality, different paradigms, etc. We stress the need for computer based decision support systems that should exhibit some "intelligence" which is meant in an individual and collective perspective, and give an overview of main types of decision support systems. We present some new so-called computing paradigms that try to attain a synergy, and bridge the gap between the human user and computer systems that is mainly caused by the fact that natural language is the only fully natural means of communication and articulation for a human being but it is "strange" to the computer. We advocate the so-called: human centric computing, human centered computing, human computing, etc. that can help bridge this gap. Then, we present Zadeh's paradigm of computing with words (and perceptions) as a tool that may help bring computing closer to the human being by an explicit use of (quasi)natural language in many phases of computing, problem solving, etc. We indicate relations between the computing with words and human centric computing paradigms, and indicate - first - that the former can be viewed as an attempt at providing proper tools to implement the latter, and that both can play a crucial role in intelligent decision support systems. We show some implementations of using linguistic data summaries in a business context and show that they can be viewed as extremely human consistent data mining tools, notably for novice users.
How to Split Recursive Automata
Authors: Isabelle Tellier
Venue: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications (2008)

In this paper, we interpret in terms of operations applying on extended finite state automata some algorithms that have been specified on categorial grammars to learn subclasses of context-free languages. The algorithms considered implement specialization strategies. This new perspective also helps to understand how it is possible to control the combinatorial explosion that specialization techniques have to face, thanks to a typing approach.
A web-based braille translation for digital music scores
Authors: Toshiyuki Gotoh, Reiko Minamikawa-Tachino, Naoyoshi Tamura
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

This paper proposes computer environment called BrailleMUSE that is a free Braille music translation server on the Internet. In experiments with expert Braille translators, translation errors occurred only at extremely slight frequency. Also, the BrailleMUSE has a mirror page to a music site showing about 4,000 digital scores. It was confirmed that the system provided Braille scores by working together with the music site. It is suggested that the system is suitable for practical use.
Considering Defense in Depth for Software Applications
Authors: Martin R. Stytz
Venue: IEEE Security and Privacy (2004)

Despite efforts to develop processes and technologies that enhance software application security, to date no one has found a silver bullet and there don't appear to be any on the horizon. Thus, perhaps researchers and developers should apply the defense-in-depth strategy to see if it provides better application security than a single line of defense. In this department, the author explores its implications for application protection technology and research.
Teaching Robust Programming
Authors: Matt Bishop, Deb Frincke
Venue: IEEE Security and Privacy (2004)

Badly written programs are a common reason for security failures. Programs crash, or fail to perform as intended, when users provide invalid inputs, either deliberately or accidentally. One response by the educational community has been to teach robust programming, which aims to prevent abnormal termination or unexpected actions and requires code to handle bad (invalid or absurd) inputs in a way that is consistent with the developer's intent. For example, if an internal error occurs, the program might terminate gracefully rather than simply failing, providing enough information for the programmer to debug the program and avoiding giving the user additional access or information.
Towards a Catalogue of Patterns for Defining Metrics over i* Models
Authors: Xavier Franch, Gemma Grau
Venue: Proceedings of the 20th international conference on Advanced Information Systems Engineering (2008)

Metrics applied at the early stages of the Information Systems development process are useful for assessing further decisions. Agent-oriented models provide descriptions of processes as a network of relationships among actors and their analysis allows discerning whether a model fulfils some required properties, or comparing models according to some criteria. In this paper, we adopt metrics to drive this analysis and we propose the use of patterns to design these metrics, with emphasis in their definition over i* models. Patterns are organized in the form of a catalogue structured along several dimensions, and expressed using a template. The patterns and the metrics are written using OCL expressions defined over a UML conceptual data model for i*. As a result, we promote reusability improving the metrics definition process in terms of accuracy and efficiency of the process.