Miracle-dz/UniFAR-FTUs huggingface dataset:
An animated Auslan Tuition System

The Auslan Tuition System uses a computer generated signer to provide a flexible, visual Australian Sign Language (Auslan) educational tool. Signs are generated and animated by our generic Human Modelling System that is implemented in cross-platform object-oriented C++. The Human Modelling System consists of three modules: the core Human Modelling Module for model construction, manipulation and forward kinematics; the Model Rendering Module for displaying model configuration visually using OpenGL; and the Model Interpolation Module, for providing flexible partial-keyframe interpolation and animation control. These modules form the basis of the Auslan Tuition System, and allow the display of categorised sign phrases, interactive fingerspelling and contextual sign dialogue examples. The user has complete viewing control of sign display and animation, running on modest hardware.
Electronically tunable floating CMOS resistor independent of the MOS parameters and temperature

A novel, electronically tunable floating resistor, which can be realized by CMOS technology is presented in this work. The resistance value is independent of the MOS threshold voltage V/sub T/, the mobility /spl mu//sub 0/ and the parameter C/sub 0x/. The above characteristics allow the implementation of an accurate resistance value, independent of temperature. Yet, a theoretical analysis concerning second order effects is presented which leads to useful conclusions concerning circuit design and operation. The theoretical predictions are verified by PSPICE simulation results.
On a high-performance vlsi solution to database problems

Abstract : This thesis explores the design and use of custom-made VLSI hardware in the area of database problems. Our effort differs from most previous ones in that we search for structures and algorithms, directly implementable on silicon, for the solution of computation-intensive database problems. The types of target database systems include the general database management systems and the design database systems. The thesis deals mainly with database systems of the relational model. One common view concerning special-purpose hardware usage is that it performs a specific task. The proposed device is not a hardware solution to a specific problem, but provides a number of useful data structures and basic operations. It can be used to improve the performance of any sequential algorithm which makes extensive use of such data structures and basic operations. The design is based on a few basic cells, interconnected together in the form of a complete binary tree. The proposed device can handle all the basic relational operations: select, join, project, union, and intersection. With a special-purpose device of limited size attached to a host, the overall performance may ultimately be dictated by the I/O between the two sites. The ideal special-purpose device design is one that achieves a balance between computation and I/O. We propose a model to study the I/O complexity for sorting n numbers with any special-purpose hardware device of size s, and show a lower bound result of omega (n log n/log s). We present an optimal design achieving this bound. An important finding is that for practical ranges on the quantity of data to be sorted, systolic sorting devices of small sizes can beat fast sequential sorting algorithms.
Addictive Drugs and Synaptic Plasticity

The term addiction, derived from a Latin word meaning ‘‘bound to’’ or ‘‘enslaved by,’’ was initially not linked to substance use. However, over the past several hundred years, addiction became associated with excessive alcohol and then drug use, such that by the late 1980s it was largely synonymous with compulsive drug use (O’Brien et al., 2006). The core features of addiction are manifest in the continued performance of the behavior despite adverse consequences, compulsive engagement or diminished control over the behavior, and an appetitive urge or craving state prior to the behavioral engagement representing core elements (Holden, 2010).
Non-monotonic Lyapunov functions for stability of nonlinear and switched systems : theory and computation

Lyapunov’s direct method, which is based on the existence of a scalar function of the state that decreases monotonically along trajectories, still serves as the primary tool for establishing stability of nonlinear systems. Since the main challenge in stability analysis based on Lyapunov theory is always to find a suitable Lyapunov function, weakening the requirements of the Lyapunov function is of great interest. In this thesis, we relax the monotonicity requirement of Lyapunov’s theorem to enlarge the class of functions that can provide certificates of stability. Both the discrete time case and the continuous time case are covered. Throughout the thesis, special attention is given to techniques from convex optimization that allow for computationally tractable ways of searching for Lyapunov functions. Our theoretical contributions are therefore amenable to convex programming formulations. In the discrete time case, we propose two new sufficient conditions for global asymptotic stability that allow the Lyapunov functions to increase locally, but guarantee an average decrease every few steps. Our first condition is nonconvex, but allows an intuitive interpretation. The second condition, which includes the first one as a special case, is convex and can be cast as a semidefinite program. We show that when non-monotonic Lyapunov functions exist, one can construct a more complicated function that decreases monotonically. We demonstrate the strength of our methodology over standard Lyapunov theory through examples from three different classes of dynamical systems. First, we consider polynomial dynamics where we utilize techniques from sum-of-squares programming. Second, analysis of piecewise affine systems is performed. Here, connections to the method of piecewise quadratic Lyapunov functions are made. Finally, we examine systems with arbitrary switching
Superior decoupled control of active and reactive power for three-phase voltage source converters

This paper presents an active-reactive power control strategy for voltage source converters (VSCs) based on derivation of the direct and quadrature components of the VSC output current. The proposed method utilizes a multivariable proportional-integral controller and provides almost completely decoupled control capability of the active and reactive power with almost full disturbance rejection due to step changes in the power exchanged between the VSC and the grid. It also imposes fast transient response and zero steady-state error as compared to the conventional power control approaches. The applicability of the proposed power control strategy for providing the robust stability of the system against the uncertainties of the load parameters is also investigated. The superiority of the proposed control strategy over conventional approaches in the new condition of supplying the load is demonstrated. The theoretical aspects of the proposed multivariable-based power control strategy and the conventional approaches are reviewed and simulation results are presented in two separate sections. MATLAB/Simulink 2009a is used to simulate different scenarios of the simulation.
Automated discovery of causal relationships in managerial problem domains

The research investigated the extent to which the computer itself can propose hypotheses of causal relationships among variables in a business problem domain. The goals of the research were: (1) to develop a methodology for automating three theories for positing hypotheses of causality among data elements in organizational databases, (2) to determine the extent to which these automated discovery methods could be used for development of a knowledge base in a managerial problem domain, and (3) to evaluate the performances of the three automated discovery methods compared with that of human decision makers. This research aimed to improve the managerial problem formulation process and construction of cognitive maps--activities which are inherently biased and restricted by perceptions of decision makers, and by volatility and uncertainty in managerial environments. The results indicated that the three automated discovery methods outperformed experienced decision makers in finding causal relationships in a simulated managerial problem domain.
Notice of Retraction Fusion Algorithms of Membership Based on Data-Mining

Existing fusion algorithms of membership are questionable because they can't distinguish the useful or useless part in indexes membership. As a result, redundant data, which are useless to objective classification, are involved in calculation of object membership. In order to eliminate the interference of redundant data in fusion algorithms of membership, through excavating the information of the object classification that hides in index membership to eliminate the redundant data using data excavation method based on entropy; and extract effective value; Then transform effective value to comparable value; At last define object membership by comparable sum. Based on this, a fusion algorithm of information based on membership can be realized, and illustrate the algorithm application by a case.
Representação temática de imagens: perspectivas metodológicas.

Exposicao dos resultados do estudo teorico sobre metodologias de representacao tematica da informacao imagetica a partir da experimentacao desenvolvida por meio de analises qualitativas aplicadas a obra de Salvador Dali. Assume carater de pesquisa documental por fundamentar argumentos embasados na bibliografia da area de Ciencia da Informacao e evidenciar metodologias anteriormente propostas.
Object Databases: An ODMG Approach

From the Publisher: This book/CD-ROM resource offers software developers hands-on experience with an object database. Through interactive tutorials and worked-out examples, users will master the concepts of object databases in a real-world setting and learn how to help their companies become ODMG compliant. The CD-ROM, which runs on all PCs, contains the software needed to run the examples. 75 illus.
Application of neural sequential associator to long-term stock price prediction

A neural sequential associator using feedback multilayer neural networks in duplicate is proposed to analyze the inherent structure in the sequence and to predict the future sequence based on this structure. It is shown that the present method gives a better performance than that of neural networks without feedback when applied to the prediction of long-term stock prices. <<ETX>>
Navigating the virtual library: a 3D browsing interface for information retrieval

An interface is described for graphically navigating a large collection of documents, as in a library. Its design is based on the metaphor of traversing a landscape. Documents are depicted as buildings, clustered to form 'towns'. A network of 'roads' connects these towns according to the classification hierarchy of the document set. A three-dimensional scene rendering technique allows the user to view this landscape from different perspectives, and at different levels of detail. At one level, the appearance of the buildings provides information like document size and age, at a glance. At higher levels, we provide the user with a visualisation of the structure and extent of the document set that is impossible with a traditional 'shelf' presentation. At all levels, a sense of physical context is maintained, encouraging and supporting browsing. <<ETX>>
Practical Handbook of Genetic Algorithms: New Frontiers

From the Publisher: The mathematics employed by genetic algorithms (GAs)are among themost exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organisms so those "organisms" can pass beneficial and survival-enhancing traits to new generations. GAs are useful in the selection of parameters to optimize a system's performance. A second potential use lies in testing and fitting quantitative models. Unlike any other book available, this interesting new text/reference takes you from the construction of a simple GA to advanced implementations. As you come to understand GAs and their processes, you will begin to understand the power of the genetic-based problem-solving paradigms that lie behind them. The Practical Handbook of Genetic Algorithms presents for the first time new areas of research and implementation. Problems that for many have been considered intractable are shown to be solvable using the techniques described in this work. Specific solution descriptions to real-world problems are provided, or use these as examples to develop solutions to unique problems. Volume II picks up where the first book leaves off and presents the topic from more of an applications point of view. The focus of the book is to show the reader how to develop their own genetic algorithm coding schemes and how and when to employ the GA to solve problems.
Modelo de servidor web com quatro módulos de atendimento de requisições (SWMAR)

This work presents the implementation and validation of a web server model that divides the web server functions into four modules and each one of these is responsible for an execution step, in which a request goes through during processing. These modules are: request serving (module 1); file transferring to the main memory (module 2); dynamic request processing (module 3); and client file sending (module 4). These four modules are linked and the W4Gen generates the initial loads. These loads run in the order as follows: modules 1, 2 and 4. The module 3 is used only when the request is dynamic. When a request is served by a module, an execution time is defined (i.e. the time used by the request in the module), which is based on real world web servers benchmark’s. The results obtained in the work aims to be integrated to other projects conduced in the Distributed System and Concurrent Programming group (LaSDPC) in order to reach results close to real world web servers.
Predicting deterministic execution times of real-time programs

The most distinctive characteristic of a real-time system is that it requires temporal correctness. Therefore, analyzing the timing behavior of a real-time system is essential. In this dissertation, we address this problem by predicting the deterministic execution times of the programs comprising a system. Our approach is to predict a time interval, covering all execution cases, with an analytic method at the source program level. The basic prediction method is based on a formal timing schema for a source-level construct. A simple and efficient timing tool for C programs is implemented in a practical setting. Comparison with measurements shows that predictions are safe and usually tight. However, the tool produces loose predictions for some complex programs because of infeasible paths. For tighter predictions, we analyze the dynamic behavior of a program using information provided by a user. We introduce a formal path model where both a program and user execution information are represented by a set of program paths described by an extended regular expression. Infeasible paths are eliminated by intersecting the two path sets. With a well-defined practical high-level interface language, the path model can be used in an easy and efficient way. We also introduce a method to verify given user information with known program verification techniques. Extended with path analysis, a timing tool yields safe and accurate predictions for a wide range of programs. It also supports incremental refinement where overall prediction cost is scalable with respect to desired precision. As a start for deterministic timing analysis of input/output operations, we introduce a method to predict the execution time of an I/O statement. The main problems in I/O analysis are predicting waiting time for a device or data and analyzing interference caused by asynchronous execution, in a variety of implementation policies. Our approach is to develop a general framework and to apply it to a specific case in a systematic way. We provide a schema refinement rule for each implementation policy that transforms a timing schema to be more specific and thus more predictable in a target system. We also introduce formulas that compute the effect of interference in a target system. We developed methods to predict deterministic program execution times, and validated them by experiments. Predictions are safe, accurate and feasible with reasonable cost. Future work includes experimenting with large programs, analyzing concurrent programs, and reasoning about the timing properties of a system with predictions.
A Review on Face Recognition Approaches

— Face recognition is a type of biometric software application that works on “Verification” and “Identification”, which is very strong in authentication field because of its accuracy, reliability, and capability of keeping information’s safe and well maintained. Face recognition applications recognizes a person based on face. The system will capture the image of a person and store it and then will try to recognize the person based on some unique features of human face that are previously present in the dataset. This paper explains review of Face Recognition Work Flow, Existing systems and results that are given by authors are shown. Face Recognition techniques such as Principle Component Analysis and Neural Networks are explained.
Fast image restoration in large digital photos

In this paper, a new technique for acceleration of iterative image restoration algorithms is presented. Unlike other fast algorithms which tend to accelerate the rate of convergence of iterative procedures, the proposed method achieves the speed improvement by extending the equivalent restoration filter of a small local block to the whole image directly. Considerable reduction in restoration time can be achieved with little image distortion. The speedup achieved increases rapidly with the drop of the ratio of the block size to the whole image size. An expression for estimating the acceleration factor is derived and confirmed experimentally. The proposed method has a special application in restoration of very large digital images with the prevalence of digital cameras.
A survey on web user personalization techniques

Information on the World Wide Web (WWW) is growing every second by second. This vast growth causes huge amount of information on the web. Out of which, seekers seek their required information. Researchers are continuously focusing toward the satisfaction of user's requirement in Information retrieval. This is an emerging and interesting area where the data mining techniques is being applied. Web mining is the application of data mining, which includes web content mining, web usage mining and web structure mining. Personalization is one of the applications of web usage mining and which is helpful to provide the user required information in an efficient manner. In this paper, we will discuss on various techniques used in web user personalization and conclude the paper with our findings on current web scenario and what is expected on future work.
Calculating the position of the observer in 3D using 2D images for the interactive presentation of virtual objects

The article presents the initial approach to the implementation of the video tracking system. We are going to use such system for the implementation of interactive virtual presentation of objects. We assumed, that tracking is done with video cameras only, and the location of the user in 3d space is estimated using methods of computer vision. The position of the user within the scene changes, and is observed by a set of cameras. The aim is to determine the place where that user is located, and then generate stereoscopic images for this viewpoint. A review of the literature on methods of user-tracking was done, and a simple experiment on reconstruction of a point in 3D space based on a set of images was described.
Recognizing Three-Dimensional Objects without the Use of Models

Abstract : We present an approach to the problem of recognizing three- dimensional objects from line-drawings. In this approach there are no models. The system needs only to be given a single picture of an object; it can be then recognize the object in arbitrary orientations. Keywords: Recognition, Vision, Three dimensional, Line Drawings.
Neural training and generalisation of sequences using continuous temporal structure

An approach for sequential neural behavior called continuous backpropagation is evolved from standard backpropagation where a state is replaced by a state transition sequence as the goal weight condition. The approach may be used to train mappings of analog input/output (I/O) signals or discrete I/O sequences with underlying continuity. An arbitrarily increasing number of values in the I/O sequences may be trained without having to increase the number of hidden units. The training and generalization techniques are illustrated by a sequential four-spiral version of Wieland's two-spirals problem. The results show a substantial improvement over standard state-based backpropagation. <<ETX>>
Temperature analysis of reference evapotranspiration models

Evapotranspiration has a significant role in agricultural and forest meteorology research, the hydrological cycle, irrigation scheduling and water resources management. Several models are available to estimate evapotranspiration, including mass transfer‐based, radiation‐based, temperature‐based and pan evaporation‐based models. This study aims to assess temperature‐based models versus the Food and Agriculture Organization of the United Nations (FAO) Penman–Monteith model to detect the best one using linear regression under different weather conditions. For this purpose, weather data were gathered from 181 synoptic stations in 31 provinces of Iran. Evapotranspiration was estimated using 11 temperature‐based models and was compared with the FAO Penman–Monteith model. The results showed that the modified Hargreaves–Samani 1 estimates the evapotranspiration better than other models in most provinces of Iran. However, the R2 values were <0.9930 for 20 provinces of Iran. The best precise method was the modified Hargreaves–Samani 4 for Alborz province (AL). Finally, a list of the best performances of each model was presented to use in other regions according to mean, maximum and minimum temperature elevation, minimum and mean relative humidity, sunshine, precipitation and wind speed. The best weather conditions for use in temperature‐based equations (based on the performance of all methods) are 12–18 °C, 18.0–22.5 °C, 5–13 °C, 40–55%, 2.00–3.25 m s−1 and 230–260 h month−1 for mean, maximum and minimum temperatures, relative humidity, wind speed and sunshine respectively. Results are also useful for selecting the best model when researchers must apply temperature‐based models on the basis of available data.
Statistical Tools for Analyzing Water Quality Data

Water quality data are often collected at different sites over time to improve water quality management. Water quality data usually exhibit the following characteristics: non-normal distribution, presence of outliers, missing values, values below detection limits (censored), and serial dependence. It is essential to apply appropriate statistical methodology when analyzing water quality data to draw valid conclusions and hence provide useful advice in water management. In this chapter, we will provide and demonstrate various statistical tools for analyzing such water quality data, and will also introduce how to use a statistical software R to analyze water quality data by various statistical methods. A dataset collected from the Susquehanna River Basin will be used to demonstrate various statistical methods provided in this chapter. The dataset can be downloaded from website http://www.srbc. net/programs/CBP/nutrientprogram.htm.