Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of DNA microarray data using self-organizing map and kernel based clustering

We describe a method of combining a self-organizing map (SOM) and a kernel based clustering for analyzing and categorizing the gene expression data obtained from DNA microarray. The SOM is an unsupervised neural network learning algorithm and forms a mapping a high-dimensional data to a two-dimensional space. However, it is difficult to find clustering boundaries from results of the SOM. On the other hand, the kernel based clustering can partition the data nonlinearly. In order to understand the results of SOM easily, we apply the kernel based clustering to finding the clustering boundaries and show that the proposed method is effective for categorizing the gene expression data.
Video Conferencing - User Interface with a Remote Control for TV-sets

By using Axis pan/tilt/zoom cameras it is possible to create a simple, high quality video conference system, without the need for a separate computer to control the system. This can be achieved by connecting the camera to a standard television set and utilize open standards like the HDMI feature Con- sumer Electronics Control (CEC). With CEC it should be possible to control the system using a standard TV remote control, thus moving a major part of the user interaction to an external device. Though this approach has its ben- efits by removing the need for Axis to provide a separate remote control, it also sets higher requirements on the user interface. Especially with regards to the usability since TV remote controls differ in many ways depending on the manufacturer. A user interface with a TV remote control solution has been prototyped and implemented demonstrating a peer-to-peer video conference system. This was done through the use of on-screen displays, an iterative design process with multiple usability tests and an evaluation of similar video conference products as a basis. The test results shows that a prototype with high usability was cre- ated which the users felt confident using.
Electrical Neuroimaging: Overview of analytical approaches

The general model The aim of this chapter is to introduce a structured overview of the different possibilities available to display and analyze brain electric scalp potentials. First, a general formal model of time-varying distributed EEG potentials is introduced. Based on this model, the most common analysis strategies used in EEG research are introduced and discussed as specific cases of this general model. Both the general model and particular methods are also expressed in mathematical terms. It is however not necessary to understand these terms to understand the chapter. The general model that we propose here is based on the statement made in Chapter 3, stating that the electric field produced by active neurons in the brain propagates in brain tissue without delay in time. Contrary to other imaging methods that are based on hemodynamic or metabolic processes, the EEG scalp potentials are thus “real-time,” not delayed and not a-priori frequency-filtered measurements. If only a single dipolar source in the brain were active, the temporal dynamics of the activity of that source would be exactly reproduced by the temporal dynamics observed in the scalp potentials produced by that source. This is illustrated in Figure 5.1, where the expected EEG signal of a single source with spindle-like dynamics in time has been computed. The dynamics of the scalp potentials exactly reproduce the dynamics of the source. The amplitude of the measured potentials depends on the relation between the location and orientation of the active source, its strength and the electrode position.
Development of a Compact, 
Configurable, Real-Time Range 
Imaging System

This thesis documents the development of a time-of-flight (ToF) camera suitable for autonomous mobile robotics applications. By measuring the round trip time of emitted light to and from objects in the scene, the system is capable of simultaneous full-field range imaging. This is achieved by projecting amplitude modulated continuous wave (AMCW) light onto the scene, and recording the reflection using an image sensor array with a high-speed shutter amplitude modulated at the same frequency (of the order of tens of MHz). The effect is to encode the phase delay of the reflected light as a change in pixel intensity, which is then interpreted as distance. A full field range imaging system has been constructed based on the PMD Technologies PMD19k image sensor, where the high-speed shuttering mechanism is builtin to the integrated circuit. This produces a system that is considerably more compact and power efficient than previous iterations that employed an image intensifier to provide sensor modulation. The new system has comparable performance to commercially available systems in terms of distance measurement precision and accuracy, but is much more flexible with regards to its operating parameters. All of the operating parameters, including the image integration time, sensor modulation phase offset and modulation frequency can be changed in realtime either manually or automatically through software. This highly configurable system serves as an excellent platform for research into novel range imaging techniques. One promising technique is the utilisation of measurements using multiple modulation frequencies in order to maximise precision over an extended operating range. Each measurement gives an independent estimate of the distance with limited range depending on the modulation frequency. These are combined to give a measurement with extended maximum range using a novel algorithm based on the New Chinese Remainder Theorem. A theoretical model for the measurement precision and accuracy of the new algorithm is presented and verified with experimental results. All distance image processing is performed on a per-pixel basis in real-time using a Field Programmable Gate Array (FPGA). An efficient hardware implementation of the phase determination algorithm for calculating distance is investigated. The limiting resource for such an implementation is random access memory (RAM), and a detailed analysis of the trade-off between this resource and measurement precision is also presented.
ConstraintAgentSpeak: an extension of the Agent Specification Language - AgentSpeak(L)

Intelligent agent technology has been recognized as one of the prominent research area. It is viewed as a very promising area in terms of its innovativeness and its potential impacts on the development of information technology. The demand for more flexible and intelligent computing solution in today’s computing environment has strongly supported the above statement and opened up more opportunities for the application of agent-based technology. The design of complex agent-based systems requires the use of expressive high-level specification languages which eventually translate into efficient implementations. This thesis suggests that constraint-based agent specification is one of the approaches that meet these requirements. To support this assertion, this thesis presents an augmentation of the BDI agent programming language AgentSpeak(L) [Rao, 1996] with constraints and describes an implementation of an interpreter for the proposed agent specification language. The proposed language, called ConstraintAgentSpeak, improves over AgentSpeak(L) in a manner parallel to the gains achieved by integrating constraints in a logic programming framework to obtain constraint logic programming [Jaffar, 1986], in terms of both expressivity and efficiency. A preliminary observation on BDI agent architecture and constrain-based reasoning is given in chapter 2. Other chapters of this thesis present the following discussions on ConstraintAgentSpeak. 1. a detail description of ConstraintAgentSpeak in terms of its syntax and operational
Optimal design of broadband ATM switches for VLSI implementations

A new design approach, optimal design approach of ATM switches, is proposed. This approach starts with given performance requirements and calculates the switch design parameters while minimizing VLSI implementation cost. The design problems are formulated as non-linear discrete optimization problems at both the architecture level and the circuit level. At the architecture level we consider an input/output buffered switch architecture. At the circuit level we consider a high bit rate inverter chain which is based on a new GaAs logic family. <<ETX>>
Reactive Learning Environment for Computer Assisted Electronics Instruction.

Abstract : This report describes the development of several new computer based strategies for teaching troubleshooting principles to electronics technicians. The computer programs to implement these strategies were developed in part from software produced in previous contracts. The report documents an experiment in which those materials were presented to student technicians to determine their attitudes toward the techniques, and to determine whether the resulting training resulted in improvement of their technical skills. Results in both cases were positive with students responding very favorably to the materials and with their performance improving quantitatively and qualitatively after the instruction. The computer based techniques used are explained and examples of student interaction with the materials are included in the report. Copies of the tutorial materials used in conjunction with the on-line computer presentations are presented in an appendix. (Author)
Human Face Segmentation and Identification

This thesis considers segmentation and identiication of human faces from grey scale images with clutter. The segmentation developed utilizes the elliptical structure of the human head. It uses the information present in the edge map of the image and through some preprocessing separates the head from the background clutter. An ellipse is then tted to mark the boundary between the head region and the background. The identiication procedure nds feature points in the segmented face through a Gabor wavelet decomposition and performs graph matching. The segmentation and identiication algorithms were tested on a database of 48 images of 16 persons with encouraging results. Dedication To my grandmother Masooda Begum and my parents Iftikhar A. Sirohey and Zarina Sirohey ii Acknowledgements I would like to take this opportunity to thank all the people who have been instrumental the accomplishment of this task. First of all Professor Rama Chellappa, with his superb guidance and support during the course of this thesis. Dr. Q. Zheng for his time and eeort and the lively discussions that we had concerning the topic. and David for putting up with me for the last year. Our discussions together brought new insight for me regarding the research. And of course this work would not have been possible if not for the undying love, support and encouragement of my parents, Iftikhar A. Sirohey and Zarina Sirohey. To them any gratitude I may express will not be enough.
Evolutionary computation for topological optimization of 3-connected computer networks

In the 3-connected computer network design problem, a set of links is to be assigned to some computer sites (nodes) such that every source-destination pair of nodes can successfully communicate with each other via at least one of three diverse paths. The objective is to minimize the total link connection costs while maintaining the 3-connectivity constraint. We develop two heuristics, a greedy heuristic and a genetic algorithm (GA) based heuristic to approximately solve the design problem. An experimental evaluation shows that the GA consistently outperforms the greedy algorithm for the problem instances considered.
A survey of MRI-based brain tumor segmentation methods

Brain tumor segmentation aims to separate the different tumor tissues such as active cells, necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF). MRI-based brain tumor segmentation studies are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast of Magnetic Resonance Imaging (MRI) images. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting brain tumor are becoming more and more mature and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for MRI-based brain tumor segmentation methods. Firstly, a brief introduction to brain tumors and imaging modalities of brain tumors is given. Then, the preprocessing operations and the state of the art methods of MRI-based brain tumor segmentation are introduced. Moreover, the evaluation and validation of the results of MRI-based brain tumor segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for MRI-based brain tumor segmentation methods.
Eliminating chattering phenomenon in sliding mode control of robot manipulators in the joint space using fuzzy logic

In industrial robotic manipulator, due to the presence of quite nonlinear dynamic and structural and nonstructural uncertainties, a precise model is not easily obtained. As a result, designing a controller with a suitable function based on system model is a challenging issue. Sliding mode control is a robust control with numerous applications which can overcome the aforementioned uncertainties. However, this control method has several defects such as chattering in input control in implementing stage. In this article, Fuzzy sliding mode control based on TSK method for controlling manipulator position tracking is suggested. This control method not only has advantages of sliding mode but also it has no chattering control effect in implementation process. To exhibit the function of sliding mode control, a case study is implemented on a robot manipulator with two revolute joints. The mathematical proofs and the simulation results reveal the desirable efficiency of Fuzzy sliding mode control.
Advances in Natural Language Processing: Third International Conference, PorTAL 2002, Faro, Portugal, June 23-26, 2002. Proceedings

Invited Speakers. - WordsEye: A Text-to-Scene Conversion System. - Automatic Anaphora Resolution: Limits, Impediments, and Ways Forward. - Pragmatics, Discourse, Semantics, Syntax, and the Lexicon. - Feature-Based WSD: Why We Are at a Dead-End. - Improving Feature Selection for Maximum Entropy-Based Word Sense Disambiguation. - Heuristics-Based Replenishment of Collocation Databases. - On the Analysis of Locative Phrases with Graphs and Lexicon-Grammar: The Classifier/Proper Noun Pairing. - The Role of Pause Occurrence and Pause Duration in the Signaling of Narrative Structure. - A Grammar-Based System to Solve Temporal Expressions in Spanish Texts. - Semantic Information in Anaphora Resolution. - A Type of Transitive Inalienable Possession Construction in Korean. - The Treatment of Numbers in Polish by Graphs. - From Syntax to Semantics: Taking Advantages of 5P. - Processing Discontinuity. - Resolution of Demonstrative Anaphoric References in Portuguese Written Texts. - Interpreting and Generating Spoken and Written Language. - Large Vocabulary Continuous Speech Recognition Using Weighted Finite-State Transducers. - Building Language Models for Continuous Speech Recognition Systems. - Language-Oriented Information Retrieval, Question Answering, Summarization, and Information Extraction. - Relevant Information Extraction Driven with Rhetorical Schemas to Summarize Scientific Papers. - Language-Oriented Machine Learning. - Mapping an Automated Survey Coding Task into a Probabilistic Text Categorization Framework. - Combining Multiclass Maximum Entropy Text Classifiers with Neural Network Voting. - Multi-lingual Processing, Machine Translation, and Translation Aids. - Compound Temporal Adverbs in Portuguese and in Spanish. - Description of a Multilingual Database of Proper Names. - Natural Language Interfaces and Dialogue Systems. - A Project of Speech Input and Output in an E-commerce Application. - Ambiguity Reports for Flexible Dialog Management. - A Natural Language Dialogue Manager for Accessing Databases. - Helping the Composition of Help Contents. - Meteo: A Telephone-Based Portuguese Conversation System in Weather Domain. - Tools and Resources. - Concluding Remarks on Multi-band and Multi-stream Research for Noise-Robust ASR. - Groundwork for the Development of the Brazilian Portuguese Wordnet. - Linguistic Processing of Biomedical Texts. - DISPARA, a System for Distributing Parallel Corpora on the Web. - Using Morphological, Syntactical, and Statistical Information for Automatic Term Acquisition. - Complex Lexical Units and Automata. - Constructing Empirical Formulas for Testing Word Similarity by the Inductive Method of Model Self-Organization. - Multilingual Corpora Annotation for Processing Definite Descriptions. - Relational Data Model in Document Hierarchical Indexing. - Evaluation of Systems. - DMSumm: Review and Assessment.
Formal models and semantics

"Of all the books I have covered in the Forum to date, this set is the most unique and possibly the most useful to the SIGACT community, in support both of teaching and research. The books can be used by anyone wanting simply to gain an understanding of one of these areas, or by someone desiring to be in research in a topic, or by instructors wishing to find timely information on a subject they are teaching outside their major areas of expertise. " -- Rocky Ross, "SIGACT News" "This is a reference which has a place in every computer science library. " -- Raymond Lauzzana, "Languages of Design" The Handbook of Theoretical Computer Science provides professionals and students with a comprehensive overview of the main results and developments in this rapidly evolving field. Volume A covers models of computation, complexity theory, data structures, and efficient computation in many recognized subdisciplines of theoretical computer science. Volume B takes up the theory of automata and rewriting systems, the foundations of modern programming languages, and logics for program specification and verification, and presents several studies on the theoretic modeling of advanced information processing. The two volumes contain thirty-seven chapters, with extensive chapter references and individual tables of contents for each chapter. There are 5,387 entry subject indexes that include notational symbols, and a list of contributors and affiliations in each volume.
Beyond OER: Shifting Focus to Open Educational Practices

This study presents the findings of a quantitative study on the use of Open Educational Resources (OER) and Open Educational Practices (OEP) in Higher Education and Adult Learning Institutions. The study is based on the results of an online survey targeted at four educational roles: educational policy makers; institutional policy makers/managers; educational professionals; and learners. The report encompasses five chapters and four annexes. Chapter I presents the survey and Chapter II discloses the main research questions and models. Chapter III characterises the universe of respondents. Chapter IV advances with a detailed survey analysis including an overview of key statistical data. Finally, Chapter V provides an exploratory in-depth analysis of some key issues: representations, attitudes and uses of OEP. The table of contents and the complete list of diagrams and tables can be found at the end of the report.
Uma abordagem conexionista para anotação de papéis semânticos

Semantic Role Labeling (SRL) is a subfield of Natural Language Processing (NLP) which began to be explored for English in 2002. Its goal is to detect structures of predicate and arguments in written sentences, which correspond to descriptions of events (usually made by verbs); its participants, such as agents and patients; and circumstances, such as time, place, etc. Many NLP applications, as machine translation and information retrieval, have achieved performance gains by applying SRL as a pre-processing step. For Portuguese, advances in SRL research are still in very early stages. Given that the majority of works found in the literature of this area employ supervised machine learning, a limiting factor has been the absence of labeled data in Portuguese, a problem that only recently was partially solved with the creation of PropBank-Br. This resource follows the annotation model used in PropBank, the main labeled data set employed in the SRL task for English. Even then, PropBank-Br contains less than one tenth of the data instances present in the original PropBank. Another point to be observed is that the most common approach to SRL is based on the extraction of a great amount of information from the input sentences to be used by automatic classifiers. Such approach is extremely dependent on other NLP tools, a particularly undesirable feature in the case of Portuguese, which does not have many freely available resources. On the other hand, another succesful approach found in the literature forgoes the use of explicit linguistic knowledge and associates words to numeric sequences, whose values are adjusted during the training of an artificial neural network. These sequences are then employed by the network in order to perform SRL, and can also be useful for other NLP tasks. This work followed the second method described above. Modifications on this method were implemented and allowed for a performance gain in comparison with its original version when tested on PropBank-Br. The final version of the developed system is ready for use and will be able to help NLP research in Portuguese.
Hidden Markov models, maximum mutual information estimation, and the speech recognition problem

Hidden Markov Models (HMMs) are one of the most powerful speech recognition tools available today. Even so, the inadequacies of HMMs as a "correct" modeling framework for speech are well known. In that context, we argue that the maximum mutual information estimation (MMIE) formulation for training is more appropriate vis-a-vis maximum likelihood estimation (MLE) for reducing the error rate. We also show how MMIE paves the way for new training possibilities. We introduce Corrective MMIE training, a very efficient new training algorithm which uses a modified version of a discrete reestimation formula recently proposed by Gopalakrishnan et al. We propose reestimation formulas for the case of diagonal Gaussian densities, experimentally demonstrate their convergence properties, and integrate them into our training algorithm. In a connected digit recognition task, MMIE consistently improves the recognition performance of our recognizer.
Um Algoritmo Evolutivo para Aprendizado On-line em Jogos Eletrônicos

Abstract. The goal of this work is to verify if it is possible to apply Evolutionary Algorithms to on-lin e learning in computer games. Some authors agree that evolutionary algorithms do not work properly in tha t case. With the objective of contesting this affirma tion, this work was performed. To accomplish the goal of this work, a computer game was developed, in which the learning algorithm must create intelligent and adaptive strategies to control the non-player chara cters using an evolutionary algorithm. Therefore, the aim of the evolutionary algorithm is to adapt the strategy used by the computer according to the player's actions during the game. A review on Evolutionary Computation and the techniques used to produce intelligent behaviors for the computer controlled characters in modern game is presented, exposing th e advantages, the problems and some applications of each technique. The proposed game is also explained , together with the implemented algorithms, the experiments and the obtained results. Finally, it i s presented a comparison between the implemented algorithm and the Dynamic Script technique. Thus, t his work offers contributions to the fields of Evolutio nary Computation and Artificial Intelligence applied to games.