Miracle-dz/UniFAR-FTUs huggingface dataset:
TCS: a shell for content-based text categorization

The kind of application that the text categorization shell, TCS, can produce is characterized. Many of its applications have great commercial value. The design goals for TCS are discussed, and other approaches to text categorization in the light of these goals are examined. The TCS and how it meets its design goals are described, and examples of applications built with TCS are given. A text-categorization application developed with TCS consists of the TCS run-time system and a rule base. The rule base defines what categories the application can assign to texts and contains rules that make the categorization decisions for particular texts. The data-driven nature of TCS allows it is to satisfy fully the requirements of ease of application development, portability to other applications and maintainability. <<ETX>>
Processing Load and Biopotentials: An Evaluation of a Consumer Electroencephalogram (EEG)

The general public is extremely interested in mental training and the use of brain imaging to study the mind. One device that combines the two and is currently on the market for consumers is a single channel EEG band produced by NeuroSky which claims to measure concentration. However, the claim that they have developed a single channel measure of concentration and meditation have not been tested. EEG power is related to cognitive memory and performance, which both contribute to concentration. In addition to EEG waves, pupil size is a reliable physiological index of processing load and concentration. The first purpose of this study is to replicate the finding of pupil diameter size and concentration. The second purpose is to see if the results of the replication correlate with the proprietary concentration reading from the NeuroSky single channel EEG as a first step towards understanding what, if anything, consumer EEG equipment measures. In this study we found that pupil diameter can measure concentration and that a single channel consumer EEG device is also sensitive to concentration.
Model-Based Automatic Building Extraction From LIDAR and Aerial Imagery

The automatic recognition and reconstruction of buildings from sensory input data is an important research topic with widespread applications in city modeling, urban planning, environmental studies, and telecommunication. This study presents integration methods to increase the level of automation in building recognition and reconstruction. Aerial imagery has been used as a major source in mapping fields and, in recent years, LIDAR data became popular as another type of mapping resource. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. LIDAR data provide direct information about heights of object surfaces but have limitations with respect to boundary localization. Efficient methods to generate building boundary hypotheses and localize object features are described. Such methods use complementary characteristics of two sensors. Graph data structures are used for interpreting surface discontinuities. Buildings are recognized by analyzing contour graphs and modeled with surface patches from LIDAR data. Building model hypotheses are generated as a combination of wing models and are verified by assessing the consistency between corresponding data sets. Experiments using aerial imagery and LIDAR data are presented. Three findings are noted: First, building boundaries are successfully recognized using the proposed contour analysis method. Second, the wing model and hypothesized contours increase the level of automation in building ii hypothesis generation/verification. Third, the integration of aerial images and LIDAR data enhances the accuracy of reconstructed buildings in the horizontal and vertical directions.
A Robust Causal Discovery Algorithm against Faithfulness Violation

Methods of statistical causal discovery that use conditional independence (CI) tests are attractive due to their time efficiency and applications to latent variable systems. However, they often suffer from worse inference results induced by statistical errors in CI tests than other approaches. We considered part of these errors to be due to statistically weak violations of a usually used assumption, called the causal faithfulness condition. We propose a causal discovery algorithm that can reduce the numbers of unnecessarily performed CI tests in this study and so provide accurate and fast inference without loss of theoretical correctness. We also introduce unreliable directions, which can reduce orientation errors caused by the locality of CI tests in the algorithm. Further, simulations are provided to demonstrate the performance of the proposed algorithm for discrete probability systems and continuous linear structural equation models.
Visual Summary for Understanding Topic Transition in BBS Thread

本論文では，電子掲示板（BBS）のスレッドにおける話題とその遷移を，投稿を読むことなしに把握することを可能にする，情報可視化技術を用いたインタラクティブな情報提示手法「視覚的要約」を提案する．近年，Webからは多種多様な情報が入手可能であるが，その中でもBBSやブログ，SNS（Social Networking Service）などのCGM（Consumer Generated Media）により供給される個人の感想や意見などの情報は，Webに特有のものであり，企業のマーケティングや，個人の観光や購買における意思決定などに有効な情報源として重要視されている．BBSスレッド中で言及される話題の時間的変化，話題の言及のされ方の時間的変化といった話題遷移も有益な情報であるが，各スレッドに含まれる多数の投稿を人手で読むことは困難であり，スレッドの進行に伴う話題遷移を可視化し，把握を支援することが重要と考える．本論文で提案する視覚的要約は，共起キーワードの時間的変化に着目し，アニメーションにより提示することで話題遷移を可視化する．また，着目する話題や投稿時期をユーザが対話的に指定し，探索的にスレッドを分析するインタラクティブ性も備える．提案手法をプロトタイプシステムとして実装し，被験者実験を行った結果より，提案する視覚的要約が話題遷移パターンの判別や話題の推定に有効である事を示す．また，被験者行動を分析し，投稿を読む場合と同様の手がかりを用いて分析を行っていること，および被験者によらず一定の合理的な分析手順が存在することを示す．
Applications of Articial Intelligence and Machine Learning in Othello

This project explores Articial Intelligence techniques in the board game Othello. Several Othello-playing programs were implemented and compared. The performance of minimax search algorithms, including alpha-beta, NegaScout and MTD(f), and of other search improvements such as transposition tables, was analyzed. In addition, the use of machine learning to enable AI players to improve play automatically through training was investigated.
Comparative Analysis of Trace Tools for Real-Time Linux

Real-Time variants of the Linux kernel are in a constant process of development due to the inclusion of new features. In this context, trace tools are necessary to test and validate new implementations. Due to the existence of many parallel Linux projects, there are also several trace tools proposed by different authors. Researchers face many times the difficult task of choosing which trace tool to use in order to validate his/her specific new implementation. This paper analyses three trace tools commonly used for the validation of new real-time Linux implementations: Feather-Trace, Ftrace and LTTng. Motivated by the absence of a set of metrics to evaluate and compare these tools, we also define in this paper a proper set of metrics. We use this new set of metrics to make a comparative analysis among the tools and to present use cases where each tool is the best choice.
Training and Research in Phonetics for Spanish as a Second Language with Technological Support

Foreign language acquisition must inevitably start with phonetics, an aspect of language whose importance is matched only by its neglect. Different research has shown how the systematic teaching of pronunciation is beneficial not only because it aids the comprehension of messages and their expression, but also because it diminishes the anxiety students feel when communicating orally. Furthermore, pronunciation is the first indication of social identity, with all that means for one's integration in or exclusion from a speech community. But nevertheless, phonetics practice takes a back seat in foreign language teaching programmes, in teacher training, in teaching material and, above all, in research work, and this is particularly true in the case of teaching Spanish as a second language. In order to redress this situation, researchers from nine universities have put together an oral corpus and developed a series of resources, tools and applications which can all be accessed at a website for cooperative and interactive work called Fono.ele. The corpus is the first to gather together a significant and representative number of oral recordings of learners of Spanish. It also breaks new ground in embarking on a general study of the pronunciation of Spanish/L2 in relation to social, cultural and educational factors. In addition, it makes available data regarding oral production and auditory perception. As for its applications, they enable those who may be interested (researchers and/or teachers) to handle and manage the speech extracts from the oral corpus, to carry out searches in the phonological errors data base, to obtain quantitative and statistical data, to interconnect text, sound and data, and to devise training exercises. All the foregoing can be done using our materials (that is, in collaboration with the AACFELE Project) or the user's own materials (for the preparation of new projects). Our article describes these resources, explains their features and functions, and indicates the options they offer different kinds of users.
Geo-Nested Analysis: Mixed-Methods Research with Spatially Dependent Data

Mixed-methods designs, especially those where cases selected for small-N analysis (SNA) are nested within a large-N analysis (LNA), have become increasingly popular. Yet, since the LNA in this approach assumes that units are independently distributed, such designs are unable to account for spatial dependence, and dependence becomes a threat to inference, rather than an issue for empirical or theoretical investigation. This is unfortunate, since research in political science has recently drawn attention to diffusion and interconnectedness more broadly. In this paper we develop a framework for mixed-methods research with spatially dependent data—a framework we label “geo-nested analysis”—where insights gleaned at each step of the research process set the agenda for the next phase and where case selection for SNA is based on diagnostics of a spatial-econometric analysis. We illustrate our framework using data from a seminal study of homicides in the United States.
LINEAR PROGRAMMING PROBLEMS BY DECOMPOSITION AND PARALLEL PROCEDURES

Dantzig's decomposition principle for linear programming problem is re-examined and implemented in a parallel and sparse computational environments. Issues in computational speed, and memory requirements for "block" linear programming problems are emphasized. The resulting sub-problems can be solved by either the revised Simplex or the Interior Point methods. Linear programming problems have been solved by single and multiple processors to validate the procedures, and evaluate the performance of the developed parallel MPI/FORTRAN computer code.
The Research on Real-Time Collision Detection of Large-Scale Complex Dynamic Scene

The rapid real-time collision detection is one of technical difficulties in large-scale simulation of complex dynamic scenes. Complex large-scale real-time scenario, demands of users on the efficiency and the accuracy of collision detection is higher and higher, which has made it become the subject of people to study. Based on the domestic and foreign existing collision detection algorithm, improved the process of collision detection framework, designed and implemented parallel collision detection with method of SIMD technology and multithreading programming, and made combination of these used in the collision detection of complex and dynamic scenes. Experimental results show that the algorithm design made the object in large and complex space of the 3D scene could be achieved real-time simulation. And the method solved the graphic images of moving objects and undetected penetration phenomena, shorten the detection time and response time of the collision for deformation object, increased the realism and immersion.
Enhanced server fault-tolerance techniques for improved user experience

User applications, such as email, calendar, maps, are migrating from local desktop machines to data centers due to the many advantages offered by such a computing paradigm. Furthermore, this trend is creating a marked increase in the deployment of servers at data centers. To ride the price/performance curves for CPU, memory and other HW, inexpensive commodity machines—although having low availability numbers—are the most cost effective choices for a data center. However, increased server failures cause service outages and degrade user experience which in turn results in lost revenue for businesses. Also, emerging web applications put additional demands on server fault-tolerance. For example, if a user is browsing a map service like Google, Yahoo or MSN maps, a server failure leading to an outage of more than a few seconds is detectable by a user and hence degrades user experience. In this thesis, I propose three novel techniques aimed at improving server fault-tolerance: (1) ST-TCP, which is an extension of TCP to tolerate server failures. This is done by using an active-backup which replicates the state of a primary and seamlessly takes over a TCP connection on primary server failure; (2) CRAFT, where the TCP splicing mechanism is enhanced to make it both fault-tolerant and more scalable; this then forms the basis of a scalable and fault-tolerant web server architecture that specifically addresses server fault-tolerance issues for highly interactive or real time applications; and, (3) Call-preserving failover, which is an efficient and scalable fault-tolerance mechanism for migrating IP telephony calls to an alternate call controller.
Resource Allocation for Cellular/WLAN Integrated Networks

The next-generation wireless communications have been envisioned to be supported by heterogeneous networks using various wireless access technologies. The popular cellular networks and wireless local area networks (WLANs) present perfectly complementary characteristics in terms of service capacity, mobility support, and quality-of-service (QoS) provisioning. The cellular/WLAN interworking is thus an effective way to promote the evolution of wireless networks. As an essential aspect of the interworking, resource allocation is vital for efficient utilization of the overall resources. Specially, multi-service provisioning can be enhanced with cellular/WLAN interworking by taking advantage of the complementary network strength and an overlay structure. Call assignment/reassignment strategies and admission control policies are effective resource allocation mechanisms for the cellular/WLAN integrated network. Initially, the incoming calls are distributed to the overlay cell or WLAN according to call assignment strategies, which are enhanced with admission control policies in the target network. Further, call reassignment can be enabled to dynamically transfer the traffic load between the overlay cell and WLAN via vertical handoff. By these means, the multi-service traffic load can be properly shared between the interworked systems. In this thesis, we investigate the load sharing problem for this heterogeneous wireless overlay network. Three load sharing schemes with different call assignment/reassignment strategies and admission control policies are proposed and analyzed. Effective analytical models are developed to evaluate the QoS performance and determine the call admission and assignment parameters. First, an admission control scheme with servicedifferentiated call assignment is studied to gain insights on the effects of load sharing on interworking effectiveness. Then, the admission scheme is extended by using randomized call assignment to enable distributed implementation. Also, we analyze the
La traducción automática y sus implicaciones en la representación del conocimiento

A theoretical approach about the different tendencies of the Machine Translation. The more significant aspects of components and processes involve in the different phases of the Machine Translation are proposed, special emphasis in the linguistic analysis. We will describe the different cognitive views that are present in Knowledge-Based Machine Translation and the development of techniques for natural language processing. We will show the incursions of this interdisciplinary knowledge area in the expert systems and the theory from the connectionism.
Tangent point oriented curve negotiation

Drivers are known to frequently fixate on the tangent point during curve negotiation. The question is how they use the tangent point to obtain the input signal(s) necessary to steer their car through a curve. In this paper, an answer is provided in terms of a steering control model that uses the distance to the tangent point and the car's heading relative to the tangent point vector. These two quantities are intermittently registered and used to update the steering angle. Experimental data obtained in our fixed based driving simulator shows good agreement with the model. They show similar behavior in terms of anticipation (steer into curve before the road starts to bend) as well as cutting through the inner side of the curve to keep the maximum curvature of the car's trajectory as low as possible. Besides providing insight into human steering behavior and a framework in which many hypothesis about curve negotiation can be tested, one of the applications for this model lies in the area of automatic steering control.
Measurement of elementary movement vectors in human visual system

The linear array of two-state elements presented in a sequence of 100-ms frames was used as a stimulus. The state of every element depends from the state of its left or right neighbour-element from the preceding frame«repeat­ ing the latter'a state with the probability P (State Repetition Probability). The shift dlrectior identification functions were obtained as a function of number of elements in the array (E) and frames (F). The results confirm general findings obtained with circular random cinematograms and show the applicability of the Dipole Contribution Model ( Allik & Dzhafarov, 1984). According to this model the observer's decisions are based on the counts of the shortest dipoles (pair of neighbour-elements from the successive frames) of the different types. It was found that three from five observers could not maintain the same dipoles counting probability when the number of elements (two observers) Or frames (one observer) became less or equal 4. Some speculations about reasons of this oddity are presented.
Academic Goal Orientations and Junior Secondary School Students' Performance in Home Economics

The aim of the study was to investigate the relationship between sel ected Academic Goal Orientation (mastery-avoidance and performance-avoidance) and Junior Secondary School Students’ Performance in Home Economics in Uyo Educational Zone of Akwa Ibom State. Two null hypotheses were tested at 0.05 level of significance. The study adopted a survey research design. The population for the study comprised of 3000 Junior Secondary school students in Uyo educational zone. Stratified random sampling technique was used to select 250 students as sample for the study. Two instruments were used for data collection; a structured questionnaire tagged Academic Goal Orientation Questionnaire (AGOQ) and Home Economics Performan ce Test (HEPT). Data obtained was analysed using Pearson Product Moment Correlation analysis. The study revealed that there is a significant relationship between mastery-avoidance and performance
Algorithm of Critical Path Based on Dynamic Programming

Directed acyclic graph (abbreviated as DAG) is an effective way to describe a project, such as planning process, construction work, production process and program flow etc., while critical path is used to estimate the shortest time to complete the whole project. AOE network refers to a directed graph in which vertex stands for events, directed edge for activities, weights on the edge of the cost are the said activities. In this paper the algorithm of solving the critical paths based on the philosophy of dynamic programming is presented, and the analysis and research on the algorithm is also furnished.
New Perspectives on English Sound Patterns

Principles of Evolutionary Phonology are applied to a selection of sound changes and stable sound patterns in varieties of English. These are divided into two types: natural phonetically motivated internal changes and all others, which are classified as unnatural. While natural phonetically motivated sound change may be inhibited by external forces, certain phonotactic patterns show notable stability in English and are only eliminated under particular types of contact with languages lacking the same patterns. Within the evolutionary model, this stability is expected since natural sound changes involving wholesale elimination of these patterns are not known.
Scalable and Efficient Tree based Memory Mapping in VirtualRouters

Many well liked algorithms for fast packet forwarding and filtering rely on the tree facts and figures structure. Examples are the triebased IP lookup and package classification algorithms. With the latest interest in mesh virtualization, the ability to run multiple virtual router examples on a common personal router stage is absolutely vital. A significant climbing issue is the number of virtual router examples that can run on the platform. One limiting factor is the allowance of high-speed recollection and caches available for storing the packet forwarding and filtering data organizations. A perfect goal is to accomplish good climbing while sustaining total isolation amidst the virtual routers. Although total isolation requires sustaining distinct facts and figures structures in high speed memory for each virtual router. In this paper, we study the case where some sharing of the forwarding and filtering facts and figures organizations is permissible and evolve algorithms for blending tries used for IP lookup and packet classification expressly, we evolve a means called trie braiding that allows us to blend tries from the facts and figures organizations of different virtual routers into just one compact trie. Two optimal braiding algorithms and a faster heuristic algorithm are offered, and the effectiveness is demonstrated utilizing the real-world facts and figures sets.
Performance modeling of the IrDA protocol for infrared wireless communications

This article presents a performance analysis of the IrDA protocol used for short-range IR data communication using an analytical mathematical model. The IrDA protocol specifies a protocol stack for reliable short-range infrared wireless data communication between devices with the data link layer (IrLAP) being an HDLC derivative. The mathematical model is based on unidirectional data transfer and uses the concept of the virtual transmission time, which provides the average end-to-end transmission time of a packet, incorporating the time for retransmissions if packet errors occur or other enforced delays. Analytical results are produced for throughput against packet size, BER and minimum turnaround time. They indicate certain limitations of the protocol for efficient throughput at high data speeds, and indicate that the maximum frame size and window size should be increased and the minimum turnaround time minimized for improved results.
Measuring Per-Frame Energy Consumption of Real-Time Graphics Applications

Energy and power efficiency are becoming important topics within the graphics community. In this paper, we present a simple, straightforward method for measuring per-frame energy consumption of real-time graphics workloads. The method is non-invasive, meaning that source code is not needed, which makes it possible to measure on a much wider range of applications. We also discuss certain behaviors of the measured platforms that can affect energy measurements, e.g., what happens when calling glFinish(), which ensures that all issued graphics commands are finished executing. Measurements are done both on a smartphone and on CPUs with integrated graphics processors.