ppxscal/embedding_network huggingface dataset:
PHP and MySQL, 1st Pap/Dvdr edition
Authors: Marc Wandschneider
Venue:  (2008)

For every developer who wants to build production-quality applications using PHP and MySQL.In this one-of-a-kind video package, top Web developer and Prentice Hall author Marc Wandschneider shows you exactly how to build reliable, secure, industrial-strength Web applications with PHP and MySQL. Youll master both PHP and MySQL through 18 comprehensive video lessons, and youll have your first PHP/MySQL application running in less than an hour. Wandschneider shows how to set up PHP on Windows and Mac OS X and then builds your skills by walking you through actual application development projects. Just click, watch, and learn efficient ways to implement user account creation, form validation, cookie and session management, file upload/download, and much more. Everythings taught visually, using sample applications ranging from a simple calculator to a full-fledged photo sharing site, and all the sample code is on the DVD. Programming challenges at the end of each lesson teach you how to take your skills to the next level. Youll master essential PHP and MySQL best practices at your own pace and learn how to deliver production-quality PHP/MySQL solutions faster and more effectively.LiveLessons: Video Instruction from Technology ExpertsLooking for a better way to master todays rapidly changing technologies? Want expert help, but dont have the time or energy to read a book? Cant find classroom training worth the money? Discover LiveLessons: self-paced, personal video instruction from the worlds leading experts.LiveLessons are video courses, on DVD with a book supplement, that are organized into bite-sized, self-contained sessionsyoull learn key skills in as little as fifteen minutes! Each lesson begins with well-defined learning objectives so you know exactly what you will learn in the lesson. Follow along as your instructor shows exactly how to get great results in your real-world environment.
A new class of invertible FIR filters for spectral shaping
Authors: Issa M. S. Panahi, Kripasagar Venkat
Venue: Signal Processing (2009)

Spectral shaping filters find a rich set of applications in the statistical signal processing problems such as signal modeling, spectral estimation, system identification, and channel equalization. In this paper, we present a new class of LTI causal FIR filters for converting a set of autocorrelation samples representing the input to a prescribed set of output autocorrelation samples. The input autocorrelation samples may represent a MA, AR, or ARMA process, with or without additive white noise, whose stable model is minimum or non-minimum phase. In contrast to the existing methods, derivation of a FIR filter of this class is direct requiring no intermediate step and no direct application of orthogonality principle or minimization of a cost function. The FIR filter is minimum-phase and its output autocorrelation lags, except the lag zero, match the set of prescribed values precisely. We characterize the filters solution space and present a novel time-domain algorithm for finding a unique invertible FIR filter of minimum-order in the solution space. We refer to the solution filter as an ''optimal invertible FIR (OIFIR)'' filter, in general, and as a ''semi-whitening filter (SWF)'', in particular, when the prescribed output autocorrelation lags, except the lag zero, are all equal to zero. It is shown that the whitening filter obtained by Yule-Walker equations (or by the orthogonality principle) belongs to the solution space of SWF only if the set of input autocorrelation samples accurately represents an AR process of finite order. Examples show performance of the proposed class of filters in spectral shaping applications including the AR modeling of a stationary process.
Characteristics of GdGaO grown by MBE
Authors: M. Holland, P. Longo, G. W. Paterson, W. Reid, A. R. Long, C. R. Stanley, A. J. Craven, I. Thayne, R. Gregory
Venue: Microelectronic Engineering (2009)

Ga"2O"3/GdGaO dielectric stacks have been grown on GaAs for MOSFETs. This paper highlights variations in the characteristics of GdGaO as the Gd flux, Ga"2O flux and substrate temperature are changed. The growth rate, composition, crystallinity are discussed and the sheet resistance of final MOSFET structures are presented. The Gd compositional variation with depth is examined using Rutherford back scattering (RBS) and electron energy loss spectroscopy (EELS).
Mining sequential patterns by PrefixSpan algorithm with approximation
Authors: Ankhbayar Yukhuu, Sansarbold Garamragchaa, Hwang Young Sup
Venue: Proceedings of the 8th conference on Applied computer scince (2008)

We want to find sequential patterns in a long continues noisy DNA sequence. Sequential pattern mining, which discovers frequent subsequences as patterns in a sequence database, is an important data mining problem with broad applications, including the analysis of customer purchase patterns or Web access patterns and analysis of DNA sequences, and so on. We investigated sequential pattern mining algorithms for long continues DNA sequences. Most previously proposed mining algorithms follow the exact matching with a sequential pattern definition. They are not able to work in noisy environments and inaccurate data in practice. We investigated approximate matching method to deal with those cases. In this paper, we develop and apply Pattern-Growth PrefixSpan algorithm to find most repeated patterns, for example, motifs in DNA sequence. Our algorithm gains its efficiency by using pattern growth and approximation methodologies. The algorithm is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call approximated pattern. We developed algorithms to quickly find out all relative frequents by a pattern growth method and to determine approximated patterns from those frequents. Our experimental studies demonstrate that our algorithm is efficient in mining repeated approximate sequential patterns that would have been missed by existing methods.
Improvement and optimization of an embedded system for short-time weather forecasting
Authors: Hristo Kilifarev, Ivan Simeonov, Raycho Ilarionov
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

In this paper is presented the improvement of the hardware and the optimization of the algorithm of a system for short-time weather forecasting, developed by the authors. With a purpose of reading of more parameters there are proposed some solutions, related with giving of more accurate forecasts. The features of the system are extended and by means of Wireless communication and access to Internet for connection with other similar systems and/or Internet servers for meteorological information. The algorithm of work of the system is optimized as for base methods for prediction are accepted the Trends and Persistent methods, and the read of the surface effects are reduced to the influence of the wind, the humidity and the clouds cover. This leads to reducing of the requirements for processing resources of the used microcontroller and the volume of the processed statistical data. Under account are taken some modern methods for atmosphere sounding, and by them to increase the accuracy and to extend the range of the given forecasts.
Discussion of Offspring Generation Method for Interactive Genetic Algorithms with Consideration of Multimodal Preference
Authors: Fuyuko Ito, Tomoyuki Hiroyasu, Mitsunori Miki, Hisatake Yokouchi
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

The interactive genetic algorithm(iGA) is a method to obtain and predict a user's preference based on subjective evaluation of users, and it has been applied to many unimodal problems, such as designing clothes or fitting of hearing aids. On the other hand, we are interested in applying iGA to user's preferences, which can be described as a multimodal problem with equivalent fitness values at the peaks. For example, when iGA is applied to product recommendation on shopping sites, users have several types of preference trends at the same time in product selection. Hence, reflecting all the trends in product presentation leads to increased sales and consumer satisfaction. In this paper, we propose a new offspring generation method that enables efficient search even with multimodal user preferences by introducing clustering of selected individuals and generating offspring from each cluster. Furthermore, we perform a subjective experiment using an experimental iGA system for product recommendation to verify the efficiency of the proposed method. The results confirms that the proposed method enables offspring generation with consideration of multimodal preferences, and there is no negative influence on the performance of preference prediction by iGA.
Automatic Singing Voice Recognition Employing Neural Networks and Rough Sets
Authors: Paweł Żwan, Piotr Szczuko, Bożena Kostek, Andrzej Czyżewski
Venue: Transactions on Rough Sets IX (2008)

The aim of the research study presented in this paper is the automatic recognition of a singing voice. For this purpose, a database containing sample recordings of trained and untrained singers was constructed. Based on these recordings, certain voice parameters were extracted. Two recognition categories were defined --- one reflecting the skills of a singer (quality), and the other reflecting the type of the singing voice (type). The paper also presents the parameters designed especially for the analysis of a singing voice and gives their physical interpretation. Decision systems based on artificial neutral networks and rough sets are used for automatic voice quality/ type classification. Results obtained from both decision systems are then compared and conclusions are derived.
A policy management framework for content-based publish/subscribe middleware
Authors: Alex Wun, Hans-Arno Jacobsen
Venue: Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware (2007)

Content-based Publish/Subscribe (CPS) is a powerful paradigm providing loosely-coupled, event-driven messaging services. Although the general CPS model is well-known, many features remain implementation specific because of different application requirements. Many of these requirements can be captured in policies that separate service semantics from system mechanisms, but no such policy framework currently exists in the CPS context. In this paper, we propose a novel policy model and framework for CPS systems that benefits from the scalability and expressiveness of existing CPS matching algorithms. In particular, we provide a reference implementation and several evaluation scenarios that demonstrate how our approach easily and dynamically enables features such as notification semantics, meta-events, security zoning, and CPS firewalls.
Virtual surrounding face geocasting in wireless ad hoc and sensor networks
Authors: Jie Lian, Yunhao Liu, Kshirasagar Naik, Lei Chen
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

Geocasting in wireless sensor and ad hoc networks means delivering a message from a source node to all the nodes in a given geographical region. The objectives of a geocasting protocol are two-fold: guaranteed message delivery and low transmission cost. Most of the existing protocols do not guarantee message de-livery, and those that do, incur high transmission costs. In this study, we propose the concept of Virtual Surrounding Face (VSF), and design a VSF-based geocasting protocol (VSFG). We also design a SKIP method and a local dominating set (DS) based restricted flooding technique to further reduce the cost of VSFG. Through mathematical analysis and comprehensive sim-ulations, we show that VSFG, together with SKIP and local DS based restricted flooding, guarantees message delivery and has a much lower transmission cost than the previous approaches. The reduction of cost can be up to 65% compared with the most effi-cient existing approach.
Analysis of system bus transaction vulnerability in systemC TLM design platform
Authors: Yung-Yuan Chen, Chung-Hsien Hsu, Kuen-Long Leu
Venue: Proceedings of the 3rd WSEAS international conference on Computer engineering and applications (2009)

As system-on-chip (SoC) becomes prevalent in the intelligent system applications, the reliability issue of SoC is getting more attention in the design industry while the SoC fabrication enters the very deep submicron technology. The system bus, such as AMBA AHB, provides an integrated platform for IP-based SoC. Apparently, the robustness of system bus plays an important role in the SoC reliability. In this study, we propose a useful bus system vulnerability model and present a thorough analysis of system bus vulnerability in SystemC transaction-level modeling (TLM) design level by injecting faults into the bus signals, which can assist us in predicting the robustness of the system bus, in locating the weaknesses of the bus system, and in understanding the effect of bus faults on system behavior during the SoC design phase. The impact of benchmarks on system bus vulnerability is also addressed. The contribution of this work is to promote the dependability verification to TLM abstraction level that can significantly enhance the simulation performance, and provide the comprehensive results to validate the system bus dependability in early design phase for safety-critical applications.
Applying self-aggregation to load balancing: experimental results
Authors: Elisabetta Di Nitto, Daniel J. Dubois, Raffaela Mirandola, Fabrice Saffre, Richard Tateson
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

One of the today issues in software engineering is to find new effective ways to deal intelligently with the increasing complexity of distributed computing systems. In this context a crucial role is played by the balancing of the work load among all nodes in the system. So far load balancing approaches have been designed for networks with fixed or dynamic topologies. These approaches work well in the case each node knows its similes and is able to contact them to delegate tasks. However, they do not address the needs of more dynamic systems where nodes are able to process different types of jobs and have limited knowledge about their neighbors and the whole system. To address these issue, we are experimenting with the usage of autonomic self-aggregation techniques that rewire such highly dynamic systems in groups of homogeneous nodes that are then able to balance the load among each others. We present our approach and show through simulation that it provides significant advantages under the circumstances described before.
A randomized approximation algorithm for computing bucket orders
Authors: Antti Ukkonen, Kai Puolamäki, Aristides Gionis, Heikki Mannila
Venue: Information Processing Letters (2009)

We show that a simple randomized algorithm has an expected constant factor approximation guarantee for fitting bucket orders to a set of pairwise preferences.
CURSO DE PROGRAMACION PHP
Authors: Minera, Francisco
Venue:  (2008)

This book is a full PHP learning course. Aimed for those who want to migrate to this language, as well as for those who want to learn programming, even if they do not have previous knowledge on the subject.
Efficient Output-Sensitive Construction of Reeb Graphs
Authors: Harish Doraiswamy, Vijay Natarajan
Venue: Proceedings of the 19th International Symposium on Algorithms and Computation (2008)

The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. This paper describes a near-optimal two-step algorithm that constructs the Reeb graph of a Morse function defined over manifolds in any dimension. The algorithm first identifies the critical points of the input manifold, and then connects these critical points in the second step to obtain the Reeb graph. A simplification mechanism based on topological persistence aids in the removal of noise and unimportant features. A radial layout scheme results in a feature-directed drawing of the Reeb graph. Experimental results demonstrate the efficiency of the Reeb graph construction in practice and its applications.
Computer technologies for 3D video delivery for home entertainment
Authors: Atanas Gotchev
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

The paper overviews the state-of-the-art in the area of 3D video content creation, coding, transmission, and display. Computer technologies for 3D video capture, format conversion and compression, as well as network technologies for 3D video delivery are briefly described. Standardization activities in the area are reviewed as well. As of 3D displays, special attention is driven to the most mature technology in that field --- the so-called auto-stereoscopic displays delivering 3D visual sensations to single or multiple users without any special glasses. Conclusions about the open questions before the 3D technology reaches the users homes are drawn.
In CMC we trust: the role of similarity
Authors: Lauren E. Scissors, Alastair J. Gill, Kathleen Geraghty, Darren Gergle
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

This paper examines how different forms of linguistic similarity in a text-chat environment relate to the establishment of interpersonal trust. Sixty-two pairs played an iterative social dilemma investment game and periodically communicated via Instant Messenger (IM). Novel automated and manual analysis techniques identify linguistic similarity at content, structural and stylistic levels. Results reveal that certain types of content (some positive emotion words, task-related words), structural (verb tense, phrasal entrainment), and stylistic (emoticons) similarity characterize high trusting pairs while other types of similarity (e.g., negative emotion words) characterize low trusting pairs. Contrary to previous literature, this suggests that not all similarity is good similarity.
Diagnosis modelling of urethral obstructions using fuzzy expert system
Authors: Kürşat Zühtüoǧullari, Ismail Saritaş, Nihat Arikan
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

The aim of this study is to help the doctors for diagnosis process of urinary system illnesses that causes obstruction in the urethra and the bladder. There are several reasons that cause obstructions in the urinary system. The common causes of these obstructions are prostate cancers, verimontanum hypertrophies, detrusor instabilities, urinary incontinence, the bladder cancer and malfunctions. This study is to help the specialist doctors about the evaluation process of the uroflowmetric measurements that are made to determine the intensity of the urinary obstructions. The average flowrate (ml) and the residual urine volume measured in the bladder are accepted as the input variables of the fuzzy logic system. The output variable is the urinary obstruction rate of the urethra. When the obstruction reaches the dangerous levels, it means that the severity of the obstruction in the urethra is high and this obstruction can easily give harm to the kidneys and at the advanced stages of the illness it can cause real failure. Matlab 7 Fuzzy Logic Toolbox is used for the simulation of the fuzzy logic urinary obstruction diagnosis system.
Wavelet Time Series ARMA Prediction on Cutting Vibration in Diamond Turning
Authors: Liwei Li, Qiwen Ran, Shen Dong
Venue: Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics (2009)

It is a critical step to control the cutting vibration during diamond turning in order to obtain super smooth surface. Both the wavelet transformation method and the autoregressive moving average (ARMA) model are combined utilized to predict and fit the cutting vibration signals in diamon turning. Firstly, by means of the wavelet transform, the cutting vibration series have been decomposed at multi-levels so as to get their scale decomposition series and wavelet decomposition series. Further, the scale decomposition series have been forecasted by intercepting segments from sine wave at each level. And the wavelet decomposition series have been predicted based on the ARMA model at each level. Finally, the forcasted scale decomposition series and wavelet decomposi-tion series have been reconstructed and fitted into the predicting vibration series. In addtition, the cutting vibration series have been extracted from the scanned AFM digital images of diamond turning surface, where the valley signals exhibit the serial vibrating information of each cutting edge profile along cutting direction.
Development and testing of a prototype reflex measurement system employing artificial neural networks
Authors: A. C. Busch, C. Scheffer, A. H. Basson
Venue: Computer Methods and Programs in Biomedicine (2009)

This paper presents the development, testing and performance evaluation of a patellar tendon reflex measurement system to provide a quantitative reflex evaluation for use by medical practitioners and in a telemedicine or E-medicine environment. A prototype was developed that makes use of XSens MTx orientation sensors, force-sensitive resistors and an electromyogram to measure the reflex response. Suitable parameters from the sensors were identified for analysis, and clinical testing was performed on 20 subjects to collect data to evaluate the system's performance. Subjective reflex evaluations were conducted by three medical doctors according to a standard reflex grading scale using video recordings of the tests. Multi-layer feed-forward (MLFF) artificial neural networks (ANNs) were used to analyze the collected data with the aim of pattern identification and reflex grading prediction. It was found that the MLFF network delivered the corresponding reflex grading with an accuracy of 85%, which was of the same order as the rate of differences between the subjective reflex evaluations performed by the doctors (80%). The use of ANNs to analyze a reflex measurement offers a repeatable and concise representation of the reflex that is familiar to doctors and can be developed for use in a general clinical setting or for telemedicine purposes.
First Order Stålmarck
Authors: Magnus Björk
Venue: Journal of Automated Reasoning (2009)

We present a proof method with a novel way of introducing universal lemmas. The method is a first order extension of Stålmarck's method, containing a branch-and-merge rule known as the dilemma rule. The dilemma rule creates two branches in a tableau-like way, but later recombines the two branches, keeping the common consequences. While the propositional version uses normal set intersection in the merges, the first order version searches for pairwise unifiable formulae in the two branches. Within branches, the system uses a special kind of variables that may not be substituted. At branch merges, these variables are replaced by universal variables, and in this way universal lemmas can be introduced. Relevant splitting formulae are found through failed unifications of variables in branches. This article presents the calculus and proof procedure, and shows soundness and completeness. Benchmarks of an implementation are also presented.