Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic 3D model creation with velocity-based surface deformations

The virtual worlds of Computer Graphics are populated by geometric objects, called models. Researchers have addressed the problem of synthesizing models automatically. Traditional modeling approaches often require a user to guide the synthesis process and to look after the geometry being synthesized, but user attention is expensive, and reducing user interaction is therefore desirable. I present a scheme for the automatic creation of geometry by deforming surfaces. My scheme includes a novel surface representation; it is an explicit representation consisting of points and edges, but it is not a traditional polygonal mesh. The novel surface representation is paired with a resampling policy to control the surface density and its evolution during deformation. The surface deforms with velocities assigned to its points through a set of deformation operators. Deformation operators avoid the manual computation and assignment of velocities, the operators allow a user to interactively assign velocities with minimal effort. Additionally, Petri nets are used to automatically deform a surface by mimicking a user assigning deformation operators. Furthermore, I present an algorithm to translate from the novel surface representations to a polygonal mesh. I demonstrate the utility of my model generation scheme with a gallery of models created automatically. The scheme’s surface representation and resampling policy enables a surface to deform without requiring a user to control the deformation; self-intersections and hole creation are automatically prevented. The generated models show that my scheme is well suited to create organic-like models, whose surfaces have smooth transitions between surface features, but can also produce other kinds of models. My scheme allows a user to automatically generate varied instances of richly detailed models with minimal user interaction.
Implementacja algorytmów użytkownika w środowisku Business Intelligence SQL Server 2008

To sum up this article, it can be argued that the assumptions made in the introduction has been fully completed. According to these assumptions has been implemented Least squares approximation algorithm in the Business Intelligence Sql Server 2008 enivironment. The project is divided into two independent parts: algorithm, which is represented by the library dll and the viewer, which is also a dll library. Thus prepared, you can register in the library system, using the built-in mechanisms for Windows and then when you start SQL Server Business Intelligence Development Studio, you can analyze the data. Of course, the algorithm is very simple and there is no use in professional data mining, however, the foundation work has not been focusing on the algorithm as such, only on presentation of how to implement any complex algorithm. Because of the choice so simple algorithm, were not necessarily used all the possibilities for Analysis Services, such as full implementation of prediction, or Drill-through. Also, the viewer does not belong to a specially complicated, but the author believes that anyone who reads this article will stand up to implement their solutions. Implementacja algorytmów użytkownika w środowisku Business Intelligence . 321
Computer Sound Design : Synthesis techniques and programming

Foreword by Jean-Claude Risset Preface Computer sound synthesis fundamentals Loose modelling approaches: from modulation and waveshaping to Walsh and wavetable Spectrum modelling approaches: from additive to analysis-resynthesis and formant Source modelling approaches: from subtractive and waveguides to physical and modal Time-based approaches: from granular and pulsar to PSOLA and statistical Practical case studies and sound design secrets: from humanoid singing to Klingon phasers Artificial intelligence, supercomputing and evolutionary computation: towards the cutting edge Introduction to the software on the accompanying CD-ROM Appendix 1: Mathematical specifications Appendix 2: Formant values Appendix 3: Artist's Inductive Machine Learning Algorithm References CD-ROM instructions
A statistical comparison between an unsupervised neural network and a partially connected neural network in the detection of breast cancer

This paper deals with the comparison of the two neural network methods of learning: supervised (partially connected neural network) and unsupervised (self organizing featuremaps (SOFM), in order to assess their performances on a labeled breast cancer database. A statistical comparison has been made to reveal the di®erences between the two methods regarding diagnosis accuracy and computational time.
Hadoop Distributed File System-Experiment and Analysis for Optimum Performance

The size of the data used in today’s enterprises has been growing at exponential rates from last few years. Simultaneously, the need to process and analyze the large volumes of data has also increased . Hadoop is a popular open-source implementation of MapReduce for the analysis of large datasets. To manage and storage resources across the cluster, Hadoop uses a distributed user-level filesystem. This filesystem, HDFS is written in Java and designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications . This paper initially deals with the review of HDFS in details. Later on, the paper reports the experimental work of Hadoop with the big data and suggests the various factors on which Hadoop cluster shows an optimal performance. Paper concludes with providing the different real field challenges of Hadoop in recent days.
Steady state load models for power system analysis

The last full review of load models used for power system studies occurred in the 1980s. Since then, new types of loads have been introduced and system load mix has changed considerably. The examples of newly introduced loads include drive-controlled motors, low energy consumption light sources and other modern power electronic loads. Their numbers have been steadily increasing in recent years, a trend which is expected to escalate. Accordingly, the majority of load models used in traditional power system studies are becoming outdated, as they are unable to accurately represent power demand characteristics of existing and future loads. Therefore, in order to accurately predict both active and non-active power demand characteristics of aggregated modern power system loads in different load sectors (e.g. residential, commercial or industrial), existing load models should be updated and new models developed. This thesis aims to fill this gap by developing individual, generic and aggregated steady state models of the most common loads in use today, as well as of those expected to show significant growth in the future. The component-based approach is adopted for load modelling, where individual load models are obtained in detailed simulations of physical devices. Whenever possible, the developed individual load models are validated by measurements. These detailed individual load models are then simplified and expressed as equivalent circuit and analytical models, which allowed the establishment of generic load models that can be easily aggregated. It should be noted that since all non-active power characteristics are correctly represented, the developed aggregated load models allow for a full harmonic analysis, which is not the case with the standard steady state load models. Therefore, the proposed load models form an extensive library of comprehensive load models that are suitable for use in multiple areas of power system research. Based on the results of research related to typical domestic/residential sector load mix, the newly developed load models are aggregated and then applied to a typical UK/Scotland distribution network. Considerable differences are seen between network characteristics of newly proposed and previously developed models. The voltage distortion of a typical distribution system bus is investigated, and it is shown that distortion of the system voltage is likely to increase significantly in the future. The results of the presented research also suggest that neglecting the harmonic characteristics from the set of general load attributes may introduce errors in standard load flow studies.
Dynamic neural networks with the use of divide and conquer

An algorithm called divide and conquer neural networks that creates a feedforward neural network during training based upon the training examples is described. In addition to learning the weights for connections, it learns an architecture that enables it to learn the examples. Training is done on the inputs to one cell at a time with learned weights being frozen. Error is never propagated backwards through a hidden cell. Examples of the algorithm's performance on the exclusive-OR and the Iris plant data, which contain two nonlinearly separable classes, are given. The results show that this algorithm can effectively learn a viable architecture in which training examples may be encoded and generalized for later use in classification. <<ETX>>
Variable structure control theory and application: a survey

The recent development of the variable structure control (VSC) is discussed in this paper. It can be summarized as follows: main theoretical problems of the variable structure control (VSC) are investigated deeply and comprehensively; some new synthesis methods of VSC are presented and are extended to many kinds of systems, thus the distance between theory and practice is much shortened; variable structure control integrates with other control strategies (for example, classical control, adaptive control and fuzzy control, etc.). The key problems for the study of VSC are the robustness and the reduction of chattering. With the development of VSC theoretical research, many real application results are reported recently.
Toward harnessing a Java high-level language virtual machine for supporting software testing

H igh-level language virtual machines (HLL VMs) have been playing a key role as a mechanism for implementing programming languages. Languages that run on these execution environments have many advantages over languages that are compiled to native code. These advantages have led HLL VMs to gain broad acceptance in both academy and industry. However, much of the research in this area has been devoted to boosting the performance of these execution environments. Few efforts have attempted to introduce features that automate or facilitate some software engineering activities, including software testing. This research argues that HLL VMs provide a reasonable basis for building an integrated software testing environment. To this end, two software testing features that build on the characteristics of a Java virtual machine (JVM) were devised. The purpose of the first feature is to automate weak mutation. Augmented with mutation support, the chosen JVM achieved speedups of as much as 95% in comparison to a strong mutation tool. To support the testing of concurrent programs, the second feature is concerned with enabling the deterministic re-execution of Java programs and exploration of new scheduling sequences.
Randomized coordinate descent methods for big data optimization

The universe is governed by science. But science tells us that we can’t solve the equations, directly in the abstract. — Stephen Hawking (1942) This thesis consists of 5 chapters. We develop new serial (Chapter 2), parallel (Chapter 3), distributed (Chapter 4) and primal-dual (Chapter 5) stochastic (randomized) coordinate descent methods, analyze their complexity and conduct numerical experiments on synthetic and real data of huge sizes (GBs/TBs of data, millions/billions of variables). In Chapter 2 we develop a randomized coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth separable convex function and prove that it obtains an -accurate solution with probability at least 1 − ρ in at most O((n/ ) log(1/ρ)) iterations, where n is the number of blocks. This extends recent results of Nesterov [43], which cover the smooth case, to composite minimization, while at the same time improving the complexity by the factor of 4 and removing from the logarithmic term. More importantly, in contrast with the aforementioned work in which the author achieves the results by applying the method to a regularized version of the objective function with an unknown scaling factor, we show that this is not necessary, thus achieving first true iteration complexity bounds. For strongly convex functions the method converges linearly. In the smooth case we also allow for arbitrary probability vectors and non-Euclidean norms. Our analysis is also much simpler. In Chapter 3 we show that the randomized coordinate descent method developed in Chapter 2 can be accelerated by parallelization. The speedup, as compared to the serial method, and referring to the number of iterations needed to approximately solve the problem with high probability, is equal to the product of the number of processors and a natural and easily viii
Using Personal Response Systems to Address the Net-Generation of University Students

Abstract: Personal Response Systems are a technology similar to use to a television remote control or a mobile telephone for sending SMS messages. They enable almost instant communication between student and instructor in lecture situations. This paper examines the claims made by Personal Response Systems and considers whether they may be especially appropriate to the preferences and expectations of Net-Generation students. The Net-Generation (also known as N-Gens) is made up of students born between 1981 and 2001. They now make up the bulk of finance students in universities across our region. But have we really adapted our lecturing styles to meet their needs? This paper explores how N-Gen students’ learning behaviours and expectations are different from the generations preceding them and reflects on one possible way of adapting our teaching styles to better meet their learning needs.
SDL-based network performance simulation

Specification and description language (SDL) is an object-oriented formal language defined as a standard by ITU-T. Though SDL is mainly used in describing communication protocols, it is an efficient way to simulate the network performance with SDL tools according to our experience. This paper presents our methodology of SDL-based network performance simulation in such aspects as the simulation platform, the simulation modes and the integrated simulation environment. Note that Telelogic Tau 4.3 SDL suite is used here as the simulation environment though our methodology isn't limited to the software. Finally the SDL-based open shortest path first (OSPF) performance simulation in the wireless private network is illustrated as an example of our methodology, which indicates that SDL is indeed an efficient language in the area of the network performance simulation.
Practical soft typing

Soft typing is an approach to type checking for dynamically typed languages. Like a static type checker, a soft type checker infers syntactic types for identifiers and expressions. But rather than reject programs containing untypable fragments, a soft type checker inserts explicit run-time checks to ensure safe execution. Soft typing was first introduced in an idealized form by Cartwright and Fagan. This thesis investigates the issues involved in designing a practical soft type system. A soft type system for a purely functional, call-by-value language is developed by extending the Hindley-Milner polymorphic type system with recursive types and limited forms of union types. The extension adapts Remy's encoding of record types with subtyping to union types. The encoding yields more compact types and permits more efficient type inference than Cartwright and Fagan's early technique. Correctness proofs are developed by employing a new syntactic approach to type soundness. As the type inference algorithm yields complex internal types that are difficult for programmers to understand, a more familiar language of presentation types is developed along with translations between internal and presentation types. To address realistic programming languages like Scheme, the soft type system is extended to incorporate assignment, continuations, pattern matching, data definition, records, modules, explicit type annotations, and macros. Imperative features like assignment and continuations are typed by a new, simple method of combining imperative features with Hindley-Milner polymorphism. The thesis shows soft typing to be practical by illustrating a prototype soft type system for Scheme. Type information determined by the prototype is sufficiently precise to provide useful diagnostic aid to programmers and to effectively minimize run-time checking. The type checker typically eliminates 90% of the run-time checks that are necessary for safe execution with dynamic typing. This reduction in run-time checking leads to significant speedup for some bench marks. Through several examples, the thesis shows how prototypes, developed using a purely semantic understanding of types as sets of values, can be transformed into robust maintainable, and efficient programs by rewriting them to accommodate better syntactic type assignment.
Rancang Bangun Aplikasi Mobile Learning Pada Sistem Operasi Android

Abstrak Teknologi diharapkan menjadi solusi kebutuhan masa depan. Pada saat ini hampir setiap orang memiliki telepon seluler. Teknologi telepon seluler selalu berkembang dari masa ke masa hingga sekarang dimana telepon seluler dapat terkoneksi dengan internet dan mengambil data dari server melalui sistem cloud computing. Salah satu pemanfaatan dari sistem ini adalah untuk pendidikan. Dengan demikian pendidikan dapat diusahakan dapat dinikmati semua orang dimanapun dan kapanpun. Telepon seluler yang terkoneksi dengan internet dapat berperan sebagai pendamping peserta didik untuk belajar, yang sering disebut dengan istilah mobile learning. Namun di sisi lain perangkat mobile learning memiliki keterbatasan sumber daya dan keragaman platform sehingga diperlukan rancangan yang mampu menjamin kompatibilitas. Dari percobaan-percobaan yang telah dilakukan dalam beberapa smartphone android dengan spesifikasi yang berbeda-beda, maka dapat disimpulkan bahwa aplikasi yang dibangun dapat berjalan dengan baik. Keywords: telepon seluler, cloud computing, internet, mobile learning Â Abstract Technology is expected to be a future solution needs. At present, almost every people has a cellular phone. Mobile phone technology is always evolving from time to time until now where cellular phones can be connected to the Internet and retrieve data from the server over the cloud computing system. One of the utilization of this system is for education. Using this technology education can be done by people everywhere and everytime. Cellular phone that connected to the internet can be as a assistant to the learners to learn, which is called as mobile learning. However mobile learning devices is limited by resources and diversity of the platform. With the result, design to ensure compatibility is required. By experiments have been conducted in several android smartphone with different specifications, it can be concluded that mobile learning application run properly. Keywords: cellular phone, cloud computing, internet, mobile learning
The Failure of 'The Failure of Poisson Modeling' for Internet Bandwidth Measurements

There is a classic paper, which claims that many parameters of network traffic are best modeled by stochastic distributions with infinite variance. We believe that although this paper is correct, it has commonly been overinterpreted. It is true that some distributions have infinite variance, but not all. There are important cases where distributions of traffic parameters have finite variance. As an example, we show that the end-to-end available bandwidth must have finite variance, outline a method for measuring it, and present some experimental data.
Knowledge-based systems development : a methodology for management

As more organizations start to consider the benefits of knowledge-based applications, they also experience the growth pains of learning how to manage knowledge-based systems projects. This article provides a context for understanding the difficulties unique to a knowledge-based systems development project and describes one methodology that offers solutions to many of the management problems confronting those responsible for knowledge-based systems development and implementation efforts.
Issues In A User Access Management System

Current efforts in end-user computing are focused in part on the need to provide more facile access to information, rather than individual systems and data. User Access Management System (UAMS) technology gives an underlying framework for this access. A UAMS is a network component that interfaces between the end-user and one or more applications residing on local or remote hosts. The UAMS provides services and capabilities such as network address resolution, user interface management system (UIMS), device independence, and automated information access. In this paper, we provide our definition of a UAMS, and describe a variety of issues germane to the on-going exploration of this technology.
An FPGA Implementation Of Alamouti's Transmit Diversity Technique

This paper presents the FPGA implementation of a multiple antenna wireless communications system based on Alamouti’s transmit diversity scheme [1]. Alamouti’s transmit diversity scheme is a space-time block code with support for two transmit antennas and an arbitrary number of receive antennas. Our implementation demonstrates this space-time code in a system with two transmit and just one antenna at the receiver. In addition to implementing the encoding and decoding algorithms described in [1], we have designed and implemented additional subsystems necessary to establish an end-to-end link over real wireless channels. These systems, described in detail below, address the challenges of timing synchronization, carrier offset recovery and channel estimation. When combined with an implementation of Alamouti’s code, these designs form a complete multiple antenna wireless communications system.
Applying region growing algorithm to hyperspectral image for oil segmentation

Region growing is one of the popular segmentation algorithms for 2-D image, which comes up a continuous interested region. How to extent this method to hyperspectral image processing effectively is a problem needs to be discussed deeply. Here in this paper, three ways of using region growing in hyperspectral scenario are explored to separate oil from sea water. Furthermore, in order to release the influence of sunlight, a modification to growing rule is prompted, considering the property of local region. At last, a normalized ATGP is used to obtain more potential target. The experiment results show that combining unmixing techniques with region growing is better than other methods.
Iris: An Integrated Circuit Layout Automatic Generator

In integrated circuit design, layout generation is tedious, time-consuming and error-prone. Motivated by seeking an alternative to manual layout design, I implmented a C A D tool, Iris, dedicating to layout generation automation. By using Iris, the designer describes the circuit netlist and relative placement of each transistor and signal in the high level language Java. Iris works out the details of every design stage and produces the final layout. Experimental results show that Iris generates layouts which are comparable to manual layouts with much less effort by the designer.