ppxscal/embedding_network huggingface dataset:
Using LEGO Mindstorms as an Instructional Aid in Technical and Vocational Secondary Education: Experiences from an Empirical Case Study
Authors: Maria Moundridou, Alexander Kalinoglou
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

This paper reports on an empirical study concerning the use of LEGO Mindstorms Robotics kit as an instructional tool in technical and vocational secondary education. In particular, a robot car was developed and programmed in order to be utilized in teaching classes in the field of Mechanical Engineering. The paper describes the rationale for that construction and the robot car itself and proposes a lesson plan exploiting this technology. The pilot study that was conducted aimed at measuring the effectiveness of this approach in terms of learning outcomes as well as students' satisfaction, enjoyment and perceived usefulness. The results of the study are encouraging towards the adoption of robotics in technical education although raising some issues that need to be further explored.
An Efficient Buffer Management Scheme for Implementing a B-Tree on NAND Flash Memory
Authors: Hyun-Seob Lee, Sangwon Park, Ha-Joo Song, Dong-Ho Lee
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

Recently, NAND flash memory has been used for a storage device in various mobile computing devices such as MP3 players, mobile phones and laptops because of its shock-resistant, low-power consumption, and none-volatile properties, However, due to the very distinct characteristics of flash memory, disk based systems and applications may result in severe performance degradation when directly adopting them on flash memory storage systems. Especially, when a B-tree is constructed, intensive overwrite operations may be caused by record inserting, deleting, and its reorganizing, This could result in severe performance degradation on NAND flash memory because of its distinct characteristics. In this paper, we propose an efficient buffer management scheme, called IBSF, which eliminates redundant index units in the index buffer and then delays the time that the index buffer is filled up. Consequently, IBSF significantly reduces the number of write operations to a flash memory when constructing a B-tree. We also show that IBSF yields a better performance on a flash memory by comparing it to the related technique called BFTL through various experiments.
Rational Passing Decision Based on Region for the Robotic Soccer
Authors: Xu Yuan, Tan Yingzi
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

For an agent to behave appropriately in an uncertain environment, efficient representation of knowledge and reliable reasoning mechanisms are at the core of design. This paper proposes a novel region based passing scheme for the robotic soccer. The scheme captures qualitative knowledge of soccer in a natural and efficient way. We implemented the rational passing decision based on region(RPDR) in our RoboCup simulation 3D team. Experiments show that our method outperforms the base line method, i.e. position searching approach.
DIXI --- A Generic Text-to-Speech System for European Portuguese
Authors: Sérgio Paulo, Luís C. Oliveira, Carlos Mendes, Luís Figueira, Renato Cassaca, Céu Viana, Helena Moniz
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

This paper describes a new generic text-to-speech synthesis system, developed in the scope of the Tecnovoz Project. Although it was primarily targeted at speech synthesis in European Portuguese, its modular architecture and flexible components allows its use for different languages. We also provide a survey on the development of the language resources needed by the TTS.
Pareto-Optimal Offensive Player Positioning in Simulated Soccer
Authors: Vadim Kyrylov, Serguei Razykov
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

The ability by the simulated soccer player to make rational decisions about moving without ball is a critical factor of success. Here we limit our scope to the offensive situation, i.e. when the ball is controlled by own team, and propose a systematic method for determining the optimal player position. Existing methods for accomplishing this task do not systematically balance risks and rewards, as they are not Pareto optimal by design. This may result in overlooking good opportunities. One more shortcoming of these methods is over simplifications in predicting the situation on the field, which may lead to performance loss. We propose two new ideas to address these issues. Experiments demonstrate that this results in a substantial increase in the team performance.
The Impact of Details in the Class Diagram on Software Size Estimation
Authors: Aleš Živkovič, Marjan Heričko, Boštjan Brumen, Simon Beloglavec, Ivan Rozman
Venue: Informatica (2005)

Software size is an important attribute in software project planning. Several methods for software size estimation are available; most of them are based on function points. Albrecht introduced function points as a technologically independent method with its own software abstraction layer. However, it is difficult to apply original abstraction elements to current technologies. Therefore researchers introduced additional rules and mappings for object-based solutions. In this paper several mapping strategies are discussed and compared. Based on the similarities in compared mappings, a common mapping strategy is then defined. This mapping is then tested on the reference application portfolio containing five applications. The aim of the test scenario is to evaluate the impact of the diverse detail levels in the class diagrams on software size measurement. Although the question of how to perform quality size measurements in object-oriented projects remains unanswered, the paper gives valuable information on the topic, supported by mathematics.
A Simple WordNet-Ontology Based Email Retrieval System for Digital Forensics
Authors: Phan Thien Son, Lan Du, Huidong Jin, Olivier Vel, Nianjun Liu, Terry Caelli
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

Because of the high impact of high-tech digital crime upon our society, it is necessary to develop effective Information Retrieval (IR) tools to support digital forensic investigations. In this paper, we propose an IR system for digital forensics that targets emails. Our system incorporates WordNet (i.e. a domain independent ontology for the vocabulary) into an Extended Boolean Model (EBM) by applying query expansion techniques. Structured Boolean queries in Backus-Naur Form (BNF) are utilized to assist investigators in effectively expressing their information requirements. We compare the performance of our system on several email datasets with a traditional Boolean IR system built upon the Lucene keyword-only model. Experimental results show that our system yields a promising improvement in retrieval performance without the requirement of very accurate query keywords to retrieve the most relevant emails.
Intellectual Property Protection for Embedded Sensor Nodes
Authors: Michael Gora, Eric Simpson, Patrick Schaumont
Venue: Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation (2008)

Embedded Sensor Networks are deeply immersed in their environment, and are difficult to protect from abuse or theft. Yet the software contained within these remote sensors often represents years of development, and requires adequate protection. We present a software based solution for the Texas Instruments C5509A DSP processor which uses object-code encryption and public-key key exchange with a server. The scheme is tightly integrated into the tool flow of the DSP processor and compatible with existing embedded processor design flows. We present performance and overhead metrics of the encryption algorithms and the security protocols. We also describe the limitations of the solution that originate from its software-only, backwards-compatible nature.
Token Coherence: A New Framework for Shared-Memory Multiprocessors
Authors: Milo M. K. Martin, Mark D. Hill, David A. Wood
Venue: IEEE Micro (2003)

Commercial workload and technology trends are pushing existing shared-memory multiprocessor coherence protocols in divergent directions. Token Coherence provides a framework for new coherence protocols that can reconcile these opposing trends.
Refinements of Aczél, Popoviciu and Bellman's inequalities
Authors: J. L. Díaz-Barrero, M. Grau-Sánchez, P. G. Popescu
Venue: Computers Mathematics with Applications (2008)

In this paper, splitting finite sums, refinements of the inequalities of Aczel, Popoviciu and Bellman are obtained.
Feature Ranking Derived from Data Mining Process
Authors: Aleš Pilný, Pavel Kordík, Miroslav Šnorek
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Most common feature ranking methods are based on the statistical approach. This paper compare several statistical methods with new method for feature ranking derived from data mining process. This method ranks features depending on percentage of child units that survived the selection process. A child unit is a processing element transforming the parent input features to the output. After training, units are interconnected in the feedforward hybrid neural network called GAME. The selection process is realized by means of niching genetic algorithm, where units connected to least significant features starve and fade from population. Parameters of new FR algorithm are investigated and comparison among different methods is presented on well known real world and artificial data sets.
Recognition of Patterns Without Feature Extraction by GRNN
Authors: Övünç Polat, Tülay Yıldırım
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Automatic pattern recognition is a very important task in many applications such as image segmentation, object detection, etc. This work aims to find a new approach to automatically recognize patterns such as 3D objects and handwritten digits based on a database using General Regression Neural Networks (GRNN). The designed system can be used for both 3D object recognition from 2D poses of the object and handwritten digit recognition applications. The system does not require any preprocessing and feature extraction stage before the recognition. Simulation results show that pattern recognition by GRNN improves the recognition rate considerably in comparison to other neural network structures and has shown better recognition rates and much faster training times than that of Radial Basis Function and Multilayer Perceptron networks for the same applications.
Research Article: The cross-species prediction of bacterial promoters using a support vector machine
Authors: Michael Towsey, Peter Timms, James Hogan, Sarah A. Mathews
Venue: Computational Biology and Chemistry (2008)

Due to degeneracy of the observed binding sites, the in silico prediction of bacterial @s^7^0-like promoters remains a challenging problem. A large number of @s^7^0-like promoters has been biologically identified in only two species, Escherichia coli and Bacillus subtilis. In this paper we investigate the issues that arise when searching for promoters in other species using an ensemble of SVM classifiers trained on E. coli promoters. DNA sequences are represented using a tagged mismatch string kernel. The major benefit of our approach is that it does not require a prior definition of the typical -35 and -10 hexamers. This gives the SVM classifiers the freedom to discover other features relevant to the prediction of promoters. We use our approach to predict @s^A promoters in B. subtilis and @s^6^6 promoters in Chlamydia trachomatis. We extended the analysis to identify specific regulatory features of gene sets in C. trachomatis having different expression profiles. We found a strong -35 hexamer and TGN/-10 associated with a set of early expressed genes. Our analysis highlights the advantage of using TSS-PREDICT as a starting point for predicting promoters in species where few are known.
Automatic Selection of Cutting Tools Geometry Using an Evolutionary Approach
Authors: Orlando Duran, Nibaldo Rodriguez, Luiz Airton Consalter
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

This paper presents the application of an evolutionary algorithm for the definition of the optimal cutting tool geometry in machining operations. In essence, the proposed approach points to the use of a genetic algorithm for selecting adequate cutting tool angles. This optimization approach was developed considering a Macro Optimization Model reported in the literature. To determine the most appropriate configuration of the genetic algorithm and its parameters a set of tests were carried out. The different algorithm settings were tested against data obtained from experimental test carried out and provided by the authors of the optimization model. A variety of simulations were carried out to validate the performance of the system and to show the usefulness of the applied approach. The definition of proposed approach also has presented the following main conclusion: through the utilization of the evolutionary approach, the selection of the appropriate cutting tool geometry is possible in real world environments.
Models and algorithmic approaches for cooperative multi-robot systems: thesis abstract
Authors: Noa Agmon
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: doctoral mentoring program (2008)

The subject of multi-robot systems has been thoroughly investigated in the past decade (e.g., [9, 12, 11, 7]). Current research in multi-robot systems can be divided, roughly, according to two aspects: theoretical robotics (e.g. [12]) and practical robotics (e.g. [10]). Theoretical robotics research, in many cases, make unrealistic assumptions on the robots' capabilities. For example, robots are sometime assumed to have unlimited visibility [8], or limited radius of visibility but omnidirectional [6]. In practice, it is usually not the case --- robots have a limited angle of visibility along with limited radius of visibility. On the other hand, practical robotics research is driven, in many cases, by the will to solve problems, thus tend to be proven only for a specific robotic system.
Fingerprint Matching Using Dual Hilbert Scans
Authors: Li Tian, Liang Chen, Sei-ichiro Kamata
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

A new fingerprint matching algorithm using dual Hilbert scans is presented in this study. We treat the fingerprint matching as point pattern matching problem and Hilbert scans are used in two aspects of the matching problem: one is applied to the similarity measure and the other is used in search space reduction. The similarity measure named Hilbert Scanning Distance (HSD) can be computed fast by converting the 2-D coordinates of 2-D images into 1-D space information using Hilbert scan. On the other hand, the 3-D search space can be converted to a 1-D search space sequence. The proposed method has been tested on FVC2002 database. The experimental results show that our method can implement fingerprint matching robustly and efficiently. The performance evaluation EER (Equal-Error Rate) generally used is very low by our algorithm.
Uniform Algebraic Reducibilities between Parameterized Numeric Graph Invariants
Authors: J. A. Makowsky
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

We report about our ongoing study of inter-reducibilities of parameterized numeric graph invariants and graph polynomials. The purpose of this work is to systematize recent emerging work on graph polynomials and various partition functions with respect to their combinatorial expressiveness and computational complexity.
Vague Rough Set Techniques for Uncertainty Processing in Relational Database Model
Authors: Karan Singh, Samajh Singh Thakur, Mangi Lal
Venue: Informatica (2008)

The study of databases began with the design of efficient storage and data sharing techniques for large amount of data. This paper concerns the processing of imprecision and indiscernibility in relational databases using vague rough technique leading to vague rough relational database model. We utilize the notion of indiscernibility and possibility from rough set theory coupled with the idea of membership and non-membership values from vague set theory to represent uncertain information in a manner that maintains the degree of uncertainty of information for each tuple of the original database and also those resulting from queries. Comparisons of theoretical properties of operators within this model with those in the standard relational database model are discussed. A simple entity-relationship type diagram for database design, a database definition language and an SQL-like query language for vague rough relational database model are described.
Hybrid Fuzzy Colour Processing and Learning
Authors: Daniel P. Playne, Vrushank D. Mehta, Napoleon H. Reyes, Andre L. Barczak
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

We present a robust fuzzy colour processing system with automatic rule extraction and colour descriptors calibration for accurate colour object recognition and tracking in real-time. The system is anchored on the fusion of fuzzy colour contrast rules that operate on the red, green and blue channels independently and adaptively to compensate for the effects of glare, shadow, and illumination variations in an indoor environment. The system also utilises a pie-slice colour classification technique in a modified rg-chromaticity space. Now, colour operations can be defined linguistically to allow a vision system to discriminate between similarly coloured objects more effectively. The validity and generality of the proposed fuzzy colour processing system is analysed by examining the complete mapping of the fuzzy colour contrast rules for each target colour object under different illumination intensities with the presence of similarly coloured objects. The colour calibration algorithm is able to extract colour descriptors in a matter of seconds as compared to manual calibration usually taking hours to complete. Using the robot soccer environment as a test bed, the algorithm is able to calibrate colours with excellent accuracy.
Cost-Bounded Binary Decision Diagrams for 0-1 Programming
Authors: Tarik Hadžić, J. N. Hooker
Venue: Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2007)

In recent work binary decision diagrams (BDDs) were introduced as a technique for postoptimality analysis for integer programming. In this paper we show that much smaller BDDs can be used for the same analysis by employing cost bounding techniques in their construction.
Sharp inequalities of Ostrowski type for convex functions defined on linear spaces and application
Authors: Eder Kikianty, S. S. Dragomir, P. Cerone
Venue: Computers Mathematics with Applications (2008)

An Ostrowski type inequality for convex functions defined on linear spaces is generalised. Some inequalities which improve the Hermite-Hadamard type inequality for convex functions defined on linear spaces are derived using the obtained result. The results in normed linear spaces are used to obtain some inequalities which are related to the given norm and associated semi-inner products, and to prove the sharpness of the constants in those inequalities.
Seeding strategies and recombination operators for solving the DNA fragment assembly problem
Authors: Gabriela Minetti, Enrique Alba, Gabriel Luque
Venue: Information Processing Letters (2008)

The fragment assembly problem consists in building the DNA sequence from several hundreds (or even, thousands) of fragments obtained by biologists in the laboratory. This is an important task in any genome project since the rest of the phases depend on the accuracy of the results of this stage. Therefore, accurate and efficient methods for handling this problem are needed. Genetic Algorithms (GAs) have been proposed to solve this problem in the past but a detailed analysis of their components is needed if we aim to create a GA capable of working in industrial applications. In this paper, we take a first step in this direction, and focus on two components of the GA: the initialization of the population and the recombination operator. We propose several alternatives for each one and analyze the behavior of the different variants. Results indicate that using a heuristically generated initial population and the Edge Recombination (ER) operator is the best approach for constructing accurate and efficient GAs to solve this problem.
Algebraic Graph Algorithms
Authors: Piotr Sankowski
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

The aim of this paper is to survey the results on dynamic algebraic algorithms, with main interest in matrix functions such as, determinant, inverse, rank and characteristic polynomial. First of all we summary the papers that in dynamic setup these problems can be solved faster than evaluating everything from scratch. The static complexity of these problem equals the matrix multiplication complexity, whereas the presented solutions work in subquadratic or quadratic (characteristic polynomial) time in the worst case. The dynamic matrix computations can be used to solve the following graphs problems in dynamic setup: computing transitive closure, computing shortest paths lengths, computing maximum matching size and computing vertex connectivity. For all of these problem the dynamic approach lead to the first known subquadratic algorithms. Astonishingly, the dynamic matrix algorithms can be used to obtain efficient static algorithms for the perfect matching problem as well. Using the O(n 2) algorithms for the dynamic matrix inverse, one can obtain a very simple randomized algorithm for computing perfect matchings in O(n 3) time. When the fast matrix multiplication is used, the complexity of this algorithm can be improved to O(n ¿ ) time, where ¿ is the exponent of the best known matrix multiplication algorithm. Since ¿< 2.38, this algorithm breaks through the O(n 2.5) barrier for the matching problem. The interplay between algebraic algorithms and graphs problems can be explored even further in order to obtain O(Wn ¿ ) time algorithms for single source shortest paths problem and weighted bipartite matching problem.
Mobile Next-Generation Networks
Authors: Josef F. Huber
Venue: IEEE MultiMedia (2004)

Mobile next-generation networks (NGNs)are a necessary element in reaching the goal of truly ubiquitous computing.The Universal Mobile Telecommunication System, the third-generation mobile service concept, is a technology step to mobile NGNs. This article delves into the evolution of UMTS as it strives to provide multimedia applications globally.