Miracle-dz/UniFAR-FTUs huggingface dataset:
BANKACILIK SEKTÖRÜNDE FARKLI OLMA ÜSTÜNLÜĞÜNÜN VE MÜŞTERİ SADAKATİNİN YARATTIĞI DEĞER:ISPARTA İLİNDE BİR UYGULAMA

Yogunlasan rekabet ve ekonominin liberalizasyonu sonucu bankalar, musterileri icin farkli hizmetler sunma ve deger yaratma arayisi icine girmislerdir. Bu nedenle bankalarin farkli olma ustunlugu yaratmanin yani sira musteri tatmini ve sadakati yaratmak icin rakiplerinden farkli stratejiler gelistirmeleri ve onlarin sundugu degerlerden daha ustun degerler sunmalari kacinilmazdir. Bu calisma, bankalarin farkli olma ustunlugu icin gelistirdikleri stratejiler ile musterilerinin aldiklari hizmetlerden duyduklari tatminin/sadakatin yarattigi degeri tanimlamak amaciyla hazirlanmistir. Calismada, Porter’in rekabetci avantaj yaratmanin iki onemli kaynagindan biri olan farklilik yaratma stratejisi incelenmis ve banka musterilerinin tatmin ve sadakat duzeyini etkileyen faktorler icin Servqual olcum tekniginin hizmet olcum faktorleri kullanilmistir. Calismanin sonucunda SERVQUAL olcum faktorlerinden guvenilirlik ve heveslilik faktorlerinden elde edilen tatmin duzeyi arttikca bankalara olan sadakatin arttigi ve rakiplerinden farkli stratejiler uygulayan bankalarin pazarda farkli olma ustunlugu elde ettikleri dolayisiyla rekabetci avantaj kazandiklari sonucuna ulasilmistir
Formulating the Brogden Classification Framework as a Discrete Choice Model

Abstract : The Brogden optimal classification framework measures potential classification benefits of predictors by assigning applicants to the jobs that will maximize predicted performance subject to job quota constraints. Current implementations of Brogden? s framework do not include classification policy constraints (e.g., cut scores and gender restriction), applicant preferences, or the impact of other classification tools available to the Army (e.g., monetary incentives to channel applicants to particular job training). To accommodate elements of real world classification systems and thereby better inform operational problems, this research reformulated Brogden? s classification framework using discrete choice modeling. We specified a mixed multinomial logit model for classification that is mathematically equivalent to a multivariate normal based implementation of Brogden? s framework. We also proposed an empirical or sample based method for classification analysis based on the multinomial logit (MNL) model that can accommodate personnel classification policy constraints, such as cut scores and gender restriction, and is robust to the functional form and distribution of the criterion estimates. Illustrative example applications of the MNL classification model showed the expected effects of policy constraints, with practical implications for the analysis results.
Data-Driven Controller Design: The H2 Approach

Data-Based Controller Designpresents a comprehensive analysis of data-based control design. It brings together the different data-based design methods that have been presented in the literature since the late 1990s. To the best knowledge of the author, these data-based design methods have never been collected in a single text, analyzed in depth or compared to each other, and this severely limits their widespread application. In this book these methods will be presented under a common theoretical framework, which fits also a large family of adaptive control methods: the MRAC (Model Reference Adaptive Control) methods. This common theoretical framework has been developed and presented very recently. The book is primarily intended for PhD students and researchers - senior or junior - in control systems. It should serve as teaching material for data-based and adaptive control courses at the graduate level, as well as for reference material for PhD theses. It should also be useful for advanced engineers willing to apply data-based design. As a matter of fact, the concepts in this book are being used, under the authors supervision, for developing new software products in a automation company. The book will present simulation examples along the text. Practical applications of the concepts and methodologies will be presented in a specific chapter.
Uncovering vein patterns from color skin images for personal identification in forensic investigation

ii In the second approach, we use principles of optics and skin biophysics for uncovering vein patterns. It inverses the process of skin color formation in an image and derives the corresponding biophysical parameters, where veins can be observed. Based on this approach we develop four optical models for simulating skin color formation. They are all based on the radiative transfer equation which quantitatively describes transport of light in the human skin. The first and second optical models use the Kubelka-Munk (K-M) model to approximate the solution of the radiative transfer equation, whose exact analytical solution has not yet been obtained for complex and multiple scattering media such as human skin. In these two models, we assume that the optical properties of human skin is determined by three layers – the stratum corneum, the epidermis, and the dermis, and veins are located in the dermis. To overcome the limits of the first model, the second optical model uses a color optimization scheme and the automatic intensity adjustment scheme. The third and fourth optical models use Reichman’s solution to the radiative transfer equation. In the fourth optical model, we add the fourth layer, the hypodermis consisting of adipose and blood vessels to the skin structure. Because none of the models can provide exact and complete vein patterns, we propose a method to fuse the vein patterns obtained from different models. Experimental evaluations show that the fusion results are much better than any of the single models and also the RGB-NIR mapping approach. Its matching result is even better than matching NIR images. Furthermore, we develop two specific approaches to remove blocking artifacts in JPEGcompressed skin images. The first one is a maximum-a-posteriori (MAP)-based approach which formulates skin image deblocking as an estimation problem, and embeds statistical information of skin images into a MAP model to perform the estimation. The second one is a knowledge-based approach which extracts prior knowledge of skin images from a training set, and uses it to infer original blocks in compressed evidence images. Two inference schemes, a block synthesis algorithm and an indexing mechanism are also proposed for this approach. Both approaches guarantee that the resultant and compressed images have the same quantized DCT coefficients. Experimental results demonstrate that the approaches perform better than other methods. In this research, we break the limit of traditional vein recognition and show its potential for forensic analysis. According to our best knowledge, no one did similar research before.
Neural units with higher-order synaptic operations with applications to edge detection and control systems

The biological sense organ contains infinite potential. The artificial neural structures have emulated the potential of the central nervous system; however, most of the researchers have been using the linear combination of synaptic operation. In this thesis, this neural structure is referred to as the neural unit with linear synaptic operation (LSO). The objective of the research reported in this thesis is to develop novel neural units with higher-order synaptic operations (HOSO), and to explore their potential applications. The neural units with quadratic synaptic operation (QSO) and cubic synaptic operation (CSO) are developed and reported in this thesis. A comparative analysis is done on the neural units with LSO, QSO, and CSO. It is to be noted that the neural units with lower order synaptic operations are the subsets of the neural units with higher-order synaptic operations. It is found that for much more complex problems the neural units with higherorder synaptic operations are much more efficient than the neural units with lower order synaptic operations. Motivated by the intensity of the biological neural systems, the dynamic nature of the neural structure is proposed and implemented using the neural unit with CSO. The dynamic structure makes the system response relatively insensitive to external disturbances and internal variations in system parameters. With the success of these dynamic structures researchers are inclined to replace the recurrent (feedback) neural networks (NNs) in their present systems with the neural units with CSO.
Lectures on Data Security, Modern Cryptology in Theory and Practice, Summer School, Aarhus, Denmark, July 1998

Practice-Oriented Provable-Security. - to Secure Computation. - Commitment Schemes and Zero-Knowledge Protocols. - Emerging Standards for Public-Key Cryptography. - Contemporary Block Ciphers. - Primality Tests and Use of Primes in Public Key Systems. - Signing Contracts and Paying Electronically. - The State of Cryptographic Hash Functions. - The Search for the Holy Grail in Quantum Cryptography. - Unconditional Security in Cryptography.
Analyzing Baseball Data with R

The Baseball Datasets Introduction The Lahman Database: Season-by-Season Data Retrosheet Game-by-Game Data Retrosheet Play-by-Play Data Pitch-by-Pitch Data Introduction to R Introduction Installing R and RStudio Vectors Objects and Containers in R Collection of R Commands Reading and Writing Data in R Data Frames Packages Splitting, Applying, and Combining Data Traditional Graphics Introduction Factor Variable Saving Graphs Dot Plots Numeric Variable: Stripchart and Histogram Two Numeric Variables A Numeric Variable and a Factor Variable Comparing Ruth, Aaron, Bonds, and A-Rod The 1998 Home Run Race The Relation between Runs and Wins Introduction The Teams Table in Lahman's Database Linear Regression The Pythagorean Formula for Winning Percentage The Exponent in the Pythagorean Formula Good and Bad Predictions by the Pythagorean Formula How Many Runs for a Win? Value of Plays Using Run Expectancy The Runs Expectancy Matrix Runs Scored in the Remainder of the Inning Creating the Matrix Measuring Success of a Batting Play Albert Pujols Opportunity and Success for All Hitters Position in the Batting Lineup Run Values of Different Base Hits Value of Base Stealing Advanced Graphics Introduction The lattice Package The ggplot2 Package Balls and Strikes Effects Introduction Hitter's Counts and Pitcher's Counts Behaviors by Count Career Trajectories Introduction Mickey Mantle's Batting Trajectory Comparing Trajectories General Patterns of Peak Ages Trajectories and Fielding Position Simulation Introduction Simulating a Half Inning Simulating a Baseball Season Exploring Streaky Performances Introduction The Great Streak Streaks in Individual At-Bats Local Patterns of Weighted On-Base Average Learning about Park Effects by Database Management Tools Introduction Installing MySQL and Creating a Database Connecting R to MySQL Filling a MySQL Game Log Database from R Querying Data from R Baseball Data as MySQL Dumps Calculating Basic Park Factors Exploring Fielding Metrics with Contributed R Packages Introduction A Motivating Example: Comparing Fielding Metrics Comparing Two Shortstops Appendix A: Retrosheet Files Reference Appendix B: Accessing and Using MLBAM Gameday and PITCHf/x Data Bibliography Index Further Reading and Exercises appear at the end of each chapter.
iClone 4.31 3D Animation Beginner's Guide

This book is a part of the Beginner's guide series, wherein you will quickly start doing tasks with precise instructions. Then the tasks will be followed by explanation and then a challenging task or a multiple choice question about the topic just covered. Do you have a story to tell or an idea to illustrate? This book is aimed at film makers, video producers/compositors, vxf artists or 3D artists/designers like you who have no previous experience with iClone. If you have that drive inside you to entertain people via the internet on sites like YouTube or Vimeo, create a superb presentation video, showcase a product or create a movie, or get a fast start on the iClone program, this Beginner's guide was written with you in mind.
Compression and View Interpolation for Multiview Imagery

This thesis deals with the tremendous amounts of data produced by camera arrays used in emerging technologies like 3D-TV and free-viewpoint TV. Being highly redundant, the imagery is eligible for efficient compression. A commonly used data format is N-texture/N-depth where each camera image is accompanied by pixelwise scene depth values. For this format, we present a novel codec. Tree-structured depth images are proposed to encode the depth information. Their advantage is efficient self-sustained compression without side information. To process the texture, we extend the class of Motion-Compensated Orthogonal Transforms by a wavelet decomposition along the view axis using depth image based rendering (DIBR). To cope with prevalent visibility issues of DIBR, orthogonal shape-adaptive transforms have been developed. The combination of the proposals yields a rate-distortion optimal codec. This system exploits the specific properties of depth images as opposed to previous approaches which rather attach a depth coder to a texture coder. The performance is evaluated by encoding multiview testsets and measuring the MSE after decoding. In the process, a MEX-file implementation of the Embedded Block Coding with Optimized Truncation algorithm has been created. We believe its speed boost can prove valuable for other’s projects in the field.
Stochastic geometry and wireless networks

Preface. Preface to Volume II. Contents of Volume II. Part IV Medium Access Control 1 Spatial Aloha: the Bipole Model 2 Receiver Selection in Spatial 3 Carrier Sense Multiple 4 Code Division Multiple Access in Cellular Networks Bibliographical Notes on Part IV. Part V Multihop Routing in Mobile ad Hoc Networks: 5 Optimal Routing 6 Greedy Routing 7 Time-Space Routing Bibliographical Notes on Part V. Part VI Appendix:Wireless Protocols and Architectures: 8 RadioWave Propagation 9 Signal Detection 10 Wireless Network Architectures and Protocols Bibliographical Notes on Part VI Bibliography Table of Notation Index.
Neuron Implementation using System Generator

Artificial Neural Networks have a wide application in terms of research areas but they have never lived up to the promise they seemed to be in the beginning of the 80s. One of the reasons for this is a lack of hardware for their implementation in a straightforward and simple way. This paper proposes a step in this direction: a quasi automated solution to build a neuron and it also includes a study about Read Only Memory implementation of the hyperbolic tangent as activation function. The results obtained are very promising and future work will lead to the implementation of a full Artificial Neural. Copyright CONTROLO2010.
Cutting and packing in production and distribution : a typology and bibliography

Within such disciplines as Management Science, Informationand Computer Sciences, Engineering, Mathematics andOperations Research, problems of cutting and packing (C&P)ofconcrete or abstract objects appear under variousspecifications although they have essentially the samelogical structure. This book tries to give a description andcategorization of C&P-problems as a whole, making themcomparable in such a way as to clearly mark theirsimilarities and differences with respect to the underlyingplanning problems. The purpose is to create a basis ofknowledge which presents suggestions for selection,development and utilization of appropriate solutionapproaches. For this purpose the book- creates a consistent terminology for C&P problems,- developes anappropriate characterization scheme of 34 properties, and- typifies more than 300 real C&P-problems published in the German and English literature. Moreover, the book contains a collection of nearly 700German and English references on C&P-problems.
Toolkit for Tactical Visualizations that Represent Uncertainty Dynamically

Abstract : Decisions are usually made under uncertainty, so displaying uncertainty information is very important to decision-making. In the past, uncertainty information associated with tactical symbols was ignored. Recent research explored uncertainty display techniques and investigated the capabilities of the human perceptual system. However, most previous studies focused on static display, and limited techniques. In this report, we investigated dynamic display of uncertainty information of tactical symbols. A comparison study was carried out for three display methods: rectangular bar, color saturation, and blurred image. This report reviews uncertainty display methods, describes the design and development of the software toolkit, and discusses the experimental procedure and results. A new method for dynamic display of uncertainty, an automatic feature based morphing, was also developed and included in the report.
Formal Verification of UML-RT Capsules using Model Checking

Formal verification methods have successfully been used to ensure correctness of both hardware and software systems. In contrast to testing methods, that can demonstrate the presence of faults in a system, formal methods can prove their absence. A department of the telecommunications company Ericsson AB in Gothenburg, Sweden, uses the UML-RT language to model software used in WCDMA radio base stations. These concurrent and reactive systems can be modeled in the Eclipse-based RSARTE environment. Previous work underlines a need of narrowing the gap between software development tools used in industry and formal verification tools. This thesis examines the feasibility of using model checking to verify properties of UMLRT capsules. We present a prototype tool for generating verification models in the Promela language for the model checker Spin. The tool is implemented as a model-to-text transformation using the JET tool and is integrated into RSARTE. The result of the work establishes that it, for a subset of constructs in UML-RT, is possible to automate generation of verification models that can be used to demonstrate properties of the original UML-RT capsules. We demonstrate this with example models created in RSARTE.
Pengaruh Informasi Real-Time pada Kecepatan Keputusan Stratejik dan Konsensus di Lingkungan High Velocity

Kecepatan keputusan stratejik dan konsensus telah diidentifikasi sebagai faktor yang mempengaruhi kinerja perusahaan [5, 38]. Sesuai dengan perspektif parallel information processing model [15], penelitian kualitatif [20] menunjukkan bahwa informasi real-time membantu eksekutif di industri high velocity mengambil keputusan stratejik dengan cepat. Penelitian ini dilakukan untuk mengkonfirmasi temuan-temuan tersebut, dalam konteks yang baru di Indonesia, serta untuk memahami apakah kecepatan keputusan dan konsensus dapat dicapai secara bersamaan. Studi ini melibatkan 156 responden yang merupakan manajemen puncak di industri telekomunikasi, media, dan IT di Indonesia. Hasil kuantitatif empirik menunjukkan bahwa informasi real-time meningkatkan kecepatan keputusan, konsensus, dan dukungan pada keputusan. Lebih penting lagi, penelitian ini menunjukkan bahwa kecepatan keputusan dan konsensus dapat dicapai secara bersamaan, dan keduanya akan meningkatkan dukungan para anggota tim manajemen puncak (TMP) terhadap keputusan stratejik yang diambil. Strategic decision speed and consensus have been previosly identified as determinants of firm performance [5, 38]. In line with the parallel information processing model [15], [20] showed that real-time information helps executives in high velocity industry make fast strategic decisions. This research was conducted to confirm those findings, within a new context in Indonesia, and whether decision speed and consensus can be achieved simultaneously. It involved 156 respondents who belong to the top management within the telecommunication, IT, and media sectors in Indonesia. The quantitative empirical evidence shows that real-time information has positive effects on strategic decision speed, consensus, and support for the decision. More importantly, this study demonstrates that decision speed and consensus can be achieved simultaneously and both will improve support for the strategic decision by members of the top management team (TMT).
Dal testo alla conoscenza e ritorno : estrazione terminologica e annotazione semantica di basi documentali di dominio

The paper focuses on the automatic extraction of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system (T2K, Text-2-Knowledge) that includes a battery of tools for Natural Language Processing, statistical text analysis and machine learning. Evaluated results show the considerable potential of systems like T2K, exploiting an incremental interleaving of NLP and machine learning techniques for accurate large-scale semi-automatic extraction and structuring of domain-specific knowledge.
Virtual Reality Technology

While e-collaboration technologies have been around for more than 30 years, the advent of the Internet and the World Wide Web has revolutionized the way in which these technologies are implemented and used (Kock, 2005, 2005b), arguably in a way that many technology trailblazers see as somewhat disappointing. Initially, in the 1960s and 1970s, these technologies supported primarily geographically distributed interaction among a relatively small number of individuals housed in research centers and universities. The sophistication of e-collaboration technologies steadily increased in the 1980s, particularly in terms of task-specific features (Bannon, 1993; Grudin, 1994). This period saw the development of new e-collaboration technology paradigms (Briggs et al., 2003; Markus, 2005) such as those underlying group decision support systems (e.g., Meetingworks) and e-collaboration development suites (e.g., Lotus Notes). Since the Internet-based infrastructure to support distributed interaction was not fully in place in the 1980s or even in the early 1990s, powerful and sophisticated e-collaboration technologies in this period became largely restricted to supporting collaborative work and communication among collocated or quasi-col-located groups of individuals (e.g., individuals working in the same campus and interacting through an extended local area network). Later, especially since the mid-1990s, and in an apparent technologically backward move, much less powerful and sophisticated Internet-and Web-based e-collaboration technologies appeared in the market, primarily because of the relatively low bandwidth available. This is the period in which we are living now, where the promise of instant and high-quality movie watching, conference participation, and other bandwidth-intensive activities over BOOK REVIEW Virtual Reality Technology (2nd ed.)
Probability: A Very Short Introduction

1. Fundamentals 2. The workings of probability 3. Historical sketch 4. Chance experiments 5. Making sense of probabilities 6. Games people play 7. Applications in science and operations research 8. Other applications 9. Curiosities and dilemmas Appendix - Answers to questions posed