Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Techniques in Exposure Assessment: A Handbook for Dealing with Variability and Uncertainty in Models and Inputs

Introduction. A Basic Framework for Probabilistic Analysis. Approaches to Model Uncertainty. Characterizing Variability and Uncertainty in Model Inputs. Data and Distributions. Special Topics Related to Distribution Development. Probabilistic Modeling Techniques. Identifying Key Contributors to Variability and Uncertainty in Model Outputs. An Illustrative Case Study of the Application of Probabilistic Exposure Assessment. Glossary. Index.
Wordcraft: Applied Qualitative Data Analysis (Qda): : Tools for Public and Voluntary Social Services

Introduction PART I: THEORY AND PRACTICE Introduction to Part I Ch 1. Welcome to the "Terminological Jungle" With Figures Ch 2. Subjectivity, Objectivity, and Ethics in Qualitative Data Analysis (QDA) With Figures Ch 3. Qualitative Data Analysis: By Computer or by Hand? With Figures Ch 4. A Written Model of QDA, With Figures Ch 5. Applying the QDA Model: Coding, Memoing, Concept Mapping, and Theme Development, With Figures Ch 6. Case Illustrations: Intensive Interviewing Ch 7. Case Illustrations: Participant Observation Ch 8. Case Illustrations: Focus Groups Ch 9. Case Illustrations: Mixed Strategies of Data Collection Glossary Appendix: Selected Samples of Professional Codes of Ethics About the Author
Peer recommendation based on comments write on social networks

Social networks and virtual communities has become a popular communication tool among Internet users. Millions of users share publications about different aspects: educational, personal, cultural, etc. Therefore these social sites are rich sources of information about who can help us solve any problems. In this paper, we focus on using the written comments to recommend a person who can answer a request. An automatic analysis of information using text mining techniques was proposed to select the most suitable users. Experimental evaluations show that the proposed techniques are efficient and perform better than a standard search.
Fault-tolerant wide-area control of power systems

In this thesis, the stability and performance of closed-loop systems following the loss of sensors or feedback signals (sensor faults) are studied. The objective is to guarantee stability in the face of sensor faults while optimising performance under nominal (no sensor fault) condition. One of the main contributions of this work is to deal effectively with the combinatorial binary nature of the problem when the number of sensors is large. Several fault-tolerant controller and observer architectures that are suitable for different applications are proposed and their effectiveness demonstrated. The problems are formulated in terms of the existence of feasible solutions to linear matrix inequalities. The formulations presented in this work are described in a general form and can be applied to a large class of systems. In particular, the use of fault-tolerant architectures for damping interarea oscillations in power systems using wide-area signals has been demonstrated. As an extension of the proposed formulations, regional pole placement to enhance the damping of inter-area modes has been incorporated. The objective is to achieve specified damping ratios for the inter-area modes and maximise the closed-loop performance under nominal condition while guaranteeing stability for all possible combinations of sensors faults. The performances of the proposed fault-tolerant architectures are validated through extensive nonlinear simulations using a simplified equivalent model of the Nordic power system. Dedicated to my beloved wife Judith and my dear family. Dad, you were the best role model I could have, God bless you.
An analysis of hierarchical clustering and neural network clustering for suggestion supervisors and examiners

Document clustering has been investigated for use in a number of different areas of information retrieval. This study applies hierarchical based document clustering and neural network based document clustering to suggest supervisors and examiners for thesis. The results of both techniques were compared to the expert survey. The collection of 206 theses was used and employed the pre-processed using stopword removal and stemming. Inter document similarity were measured using Euclidean distance before clustering techniques were applied. The results show that Wardâ€™s algorithm is better for suggestion supervisor and examiner compared to Kohonen network.
Deep convolutional neural networks for ATR from SAR imagery

Deep architectures for classification and representation learning have recently attracted significant attention within academia and industry, with many impressive results across a diverse collection of problem sets. In this work we consider the specific application of Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR) data from the MSTAR public release data set. The classification performance achieved using a Deep Convolutional Neural Network (CNN) on this data set was found to be competitive with existing methods considered to be state-of-the-art. Unlike most existing algorithms, this approach can learn discriminative feature sets directly from training data instead of requiring pre-specification or pre-selection by a human designer. We show how this property can be exploited to efficiently adapt an existing classifier to recognise a previously unseen target and discuss potential practical applications.
From the road network database to a graph for localization purposes

The problems of finding best facility locations require complete and accurate road network with the corresponding population data in a specific area. However the data obtained in road network databases usually do not fit in this usage. In this paper we propose our procedure of converting the road network database to a road graph which could be used in localization problems. The road network data come from the National road data base in Sweden. The graph derived is cleaned, and reduced to a suitable level for localization problems. The population points are also processed in ordered to match with that graph. The reduction of the graph is done maintaining most of the accuracy for distance measures in the network.
Comparison Study of Test Case Allocation Schemes in Software Partition Testing

The partition testing method is a commonly followed practice towards the selection of test cases. For partition testing, the program’s input domain is divided into subsets, called subdomains, and one or more representatives from each subdomain are selected to test the program. The goal of such partitioning is to make the division of the program’s input domain in such a way that when the tester selects test cases based on the subsets, the resulting test set is a good representation of the entire domain. The main aim of the paper is to analyse the fault-detecting ability of the partition testing method. Using effectiveness metrics for testing and partitioning schemes this paper makes a comparison of various test case allocation schemes in partition testing.
Virtualizing Open Access Networks

Existing network virtualization methods in Open-Flow networks are lacking in many respects, especially whenapplied in multi-tenant scenarios such as open access networks. Inthis paper we investigate how OpenFlow can be used to simplifythe use and management of a shared network infrastructure inopen access networks. We then present initial ideas on how toimprove virtualization in OpenFlow networks by applying novelmethods to virtualize the forwarding plane itself.
The RISC-V Instruction Set Manual. Volume 1: User-Level ISA, Version 2.0

Abstract : RISC-V (pronounced risk-five) is a new instruction set architecture (ISA) that was originally designed to support computer architecture research and education, but which we now hope will become a standard open architecture for industry implementations. The RISC-V manual is structured in two volumes. This volume covers the user-level ISA design, including optional ISA extensions. The second volume provides examples of supervisor-level ISA design.
Perceptual Computing: Aiding People in Making Subjective Judgments

Explains for the first time how "computing with words" can aid in making subjective judgments Lotfi Zadeh, the father of fuzzy logic, coined the phrase "computing with words" (CWW) to describe a methodology in which the objects of computation are words and propositions drawn from a natural language. Perceptual Computing explains how to implement CWW to aid in the important area of making subjective judgments, using a methodology that leads to an interactive devicea "Perceptual Computer"that propagates random and linguistic uncertainties into the subjective judgment in a way that can be modeled and observed by the judgment maker. This book focuses on the three components of a Perceptual Computerencoder, CWW engines, and decoderand then provides detailed applications for each. It uses interval type-2 fuzzy sets (IT2 FSs) and fuzzy logic as the mathematical vehicle for perceptual computing, because such fuzzy sets can model first-order linguistic uncertainties whereas the usual kind of fuzzy sets cannot. Drawing upon the work on subjective judgments that Jerry Mendel and his students completed over the past decade, Perceptual Computing shows readers how to: Map word-data with its inherent uncertainties into an IT2 FS that captures these uncertainties Use uncertainty measures to quantify linguistic uncertainties Compare IT2 FSs by using similarity and rank Compute the subsethood of one IT2 FS in another such set Aggregate disparate data, ranging from numbers to uniformly weighted intervals to nonuniformly weighted intervals to words Aggregate multiple-fired IF-THEN rules so that the integrity of word IT2 FS models is preserved Free MATLAB-based software is also available online so readers can apply the methodology of perceptual computing immediately, and even try to improve upon it. Perceptual Computing is an important go-to for researchers and students in the fields of artificial intelligence and fuzzy logic, as well as for operations researchers, decision makers, psychologists, computer scientists, and computational intelligence experts.
The Canadian Language Benchmarks Placement Test (review)

Longman. Munnich, E. , Flynn, S. , & Martohardjono, G. (1994). Elicited imitation and grammaticality judgment tasks: What they measure and how they relate to each other. In E. Tarone, S. Gass & A. Cohen (Eds.). Research methodology in second language acquisition (pp. 227–245). Mahwah, NJ: Erlbaum. Naiman, N. (1974). The use of elicited imitation in second language acquisition research. Working Papers on Bilingualism, 2, 1–37. Perkins, K. , Brutten, S.R. , & Angelis, P.J. (1986). Derivational complexity and item difficulty in a sentence repetition task. Language Learning, 36, 125–141. Scott, M.L. (1994). Auditory memory and perception in younger and older adult second language learners. Studies in Second Language Acquisition, 16, 263–281. Slobin, D.I. , & Welsh, C.A. (1973). Elicited imitation as a research tool in developmental psycholinguistics. In C. Ferguson & D. Slobin (Eds.). Studies of child language development (pp. 485–497). New York: Holt, Rinehart & Winston. Smith, C. (1973). An experimental approach to children. In C. Ferguson & D. Slobin (Eds.). Studies of child language development (pp. 497–521). New York: Holt, Rinehart & Winston. Spitze, K. , & Fischer, S. (1981). Short-term memory as a test of language proficiency. ESL Talk, 12, 32–41. Van Boxtel, S. , Bongaerts, T. , & Coppen, P.A. (2005). Native-like attainment of dummy subjects in Dutch and the role of the L1. International Review of Applied Linguistics in Language Teaching, 43, 355–380. Vinther, T. (2002). Elicited imitation: A brief overview. International Journal of Applied Linguistics, 12, 54–73.
Essentials of Mastering English: A Concise Grammar

Essentials of Mastering English: A Concise Grammar is both an ideal companion for undergraduate students wishing to acquire a high level of grammatical proficiency and a readily accessible reference work for teachers of English at all levels. It provides an introduction to basic grammatical terms and to elementary syntactic description, enabling students to analyse sentences and utterances down to word level with a specification of both the form and the function of all constituents.
Feather, Scent, and Shaker: Supporting Simple Intimacy

In this paper, we describe three experiments in designing for minimal, expressive communication. These are very simple networked devices that are aimed at supporting implicit, personal, and expressive communication, as opposed to the explicit, goal-oriented, and informative communication characterising most CSCW systems. We suggest that these prototypes open an interesting space for collaborative systems, and describe some of the issues and opportunities they raise.
QUEUEING THEORY APPROACHES

RESULTS ARE PRESENTED OF SOME OF THE STUDIES OF PROBABILITY MODELS OF TRAFFIC DELAY. SOME FUNDAMENTAL CHARACTERISTICS ARE DESCRIBED OF VARIABLE PROCESSES AS WELL AS THE IMPORTANT ASSUMPTIONS GOVERNING THE ARRIVAL OF STREAMS OF TRAFFIC AT A GIVEN POINT AND THE VARIABILITY OF GAP ACCEPTANCE OF DRIVERS AND PEDESTRIANS ATTEMPTING TO CROSS A TRAFFIC STREAM. A BRIEF SUMMARY IS PRESENTED OF SOME ELEMENTS OF QUEUEING OR WAITING-LINE THEORY FROM THE BRANCH OF MATHEMATICS DEALING WITH CONGESTED SYSTEMS. SUMMARIES ARE PRESENTED OF THE MOST SIGNIFICANT PUBLISHED WORKS RELATIVE TO DELAYS AT SIGNALIZED AND STOP-SIGN CONTROLLED INTERSECTIONS, PASSING ON A TWO-LANE ROADWAY, AND A NUMBER OF SPECIAL TOPICS SUCH AS MULTIPLE QUEUES, PARKING AND ONE-LANE BOTTLENECKS.
Advances in Image Understanding: A Festschrift for Azriel Rosenfeld

From the Publisher: This volume of original papers has been assembled to honor Azriel Rosenfeld, a dominant figure in the field of computer vision and image processing for over 30 years. Over this period he has made many fundamental and pioneering contributions to nearly every area in this field. Azriel Rosenfeld wrote the first textbook in the field in 1969 and was the founding editor of its first journal in 1972. The contributions in this book illustrate the changes that have occurred in dealing with crucial research problems and the methodologies employed to solve them. The 22 papers specifically written for this text are by only a handful of researchers who have known and worked with Azriel over the years. These papers address five major themes: image segmentation, feature extraction, 3D shape estimation from 2D images, object recognition, and applications technologies.
Search and retrieval in massive data collections

THE main goal of this research is to produce a novel and efficient searching application by means of best match and proximity searching with particular application to very large numeric and textual data stores. In today’s world a huge amount of information is produced. Almost every part of our society is touched by systems that collect, store and analyse data. As an example I mention the case of scientific instrumentation: new sensors capture massive amounts of information (e.g. new telescopes acquiring data from different regions of the spectrum). Description of biological and chemical interactions also produce complex and large amounts of data. It is in this context that a big challenge for current analysis algorithms is presented. Many of the traditional methods for data analysis do not scale well in massive data sets nor in very high dimensional spaces. In this work I introduce a novel (ultrametric) distance called Baire based on the longest common prefix and show how it can be used to produce clusters through grouping data in ’bins’ taking linear or O(n) computational time. Furthermore, it follows that this distance can be strictly fitted to a hierarchy tree. This is a property that proves very useful for classifying, storing, accessing and retrieving information. I go further to apply this methodology on data from different scientific areas such as astronomy and chemistry to create groups or clusters. Additionally I apply this method to document sets for clustering and retrieval. In particular, I look into the new area of enterprise search to propose a new method to support scalable search and clustering.
ESTIMATING ANNUAL WATERWAY TONNAGE FROM LOCK DATA: METHODOLOGY

To provide more timely data, the Corps of Engineers has developed advance reports on estimates of commodity tonnage on American waterways since 1989. They are based on correlations between lockage data and operator-reported data over a decade. Experimentation and development of better methods provide more accurate estimates a year before the final published reports. Better methods include regression equations and common sense. Graphical analysis was used. Scattergrams pinpoint outliers due to poor data collection. Line graphs of tonnages by commodity of river locks show which give the maximum waterway tonnage. Time-series graphs of actual tonnage and promising regression estimates show the best estimator and unreported data. Analysis of the past flow of commodities shows which locks are more logical predictors. Graphs can show patterns in past tonnage relationships to justify estimation. Unreliable data must be identified and dropped from the analysis. The temptation to be mechanistic in the methodology must be avoided, and common sense must be used to overcome spuriousness and multicollinearity errors. These precautions can overcome the pitfalls of automatic computer-generated methods. Methods that improved accuracy included graphical analysis, adjusted regression equations, commonsense methods, and adjusted R-square. Analysis of errors improves methods. Advance data for 1990 showed improvement. Validity measures were developed that prove the model valid. Reliability can be predicted, and factors that increase reliability are known.
Solaris Performance and Tools: DTrace and MDB Techniques for Solaris 10 and OpenSolaris

It sounds good when knowing the solaris performance and tools dtrace and mdb techniques for solaris 10 and opensolaris in this website. This is one of the books that many people looking for. In the past, many people ask about this book as their favourite book to read and collect. And now, we present hat you need quickly. It seems to be so happy to offer you this famous book. It will not become a unity of the way for you to get amazing benefits at all. But, it will serve something that will let you get the best time and moment to spend for reading the book.
Polygonal models from range scanned trees

3D Models of botanical trees are very important in video games, simulation, virtual reality, digital city modeling and other fields of computer graphics. However, since the early days of computer graphics, the modeling of trees has been challenging, because of the huge dynamical range between its smallest and largest structures and their geometrical complexity. Trees are also ubiquitous which makes it even hard to model them in a realistic way, Current techniques are limited in that they model a tree either in a rule-based way or in an approximated way. These methods emphasize appearance while sacrificing its real structure. Recent development in range scanners are making 3D aquisition feasible for large and complex objects. This report presents the semi-automatic technique developed for modeling laser-scanned trees. First, the user draws a few strokes on the depth image plane generated from the dataset. Branches are then extracted through the 2D Curve detection algorithm originally developed. Afterwards, those short branches are connected together to generate the skeleton of the tree by forming a Minimum Spanning Tree (MST). Finally, the geometry of the tree skeleton is produced using allometric rules for branch thickness and branching angles.
A Taxonomy of Spectral Unmixing Algorithms and Performance Comparisons

Abstract : In this report, algorithms for spectral umnixing are organized into taxonomies and their performance is then compared. Our motivation is to collectively organize and relate algorithms in order to assess the current state-of-the-art in the field and to facilitate objective comparisons between methods. The hyperspectral sensing community is populated by investigators with disparate scientific backgrounds and efforts in spectral umnixing developed within disparate communities have inevitably led to duplication. This report is intended to remove ambiguity and redundancy by using a standard vocabulary, and clearly summarize what has and has not been done. As will be evident, the framework for the taxonomies derives its organization from the fundamental, philosophical assumptions imposed on the problem, rather than the common calculations they perform, or the similar outputs they might yield. The taxonomies are supplemented by a comparison of umnixing performance using techniques that typifY the approaches of wide classes of algorithms.
A RESEARCH TAXONOMY FOR E-COMMERCESYSTEM USABILITY

E-commerce systems (ECS) are Web-based systems that perform various stages of an e-commerce transaction. ECS typically include sub-systems such as electronic catalogs, shopping-cart systems, payment systems, ordertracking systems, merchandise return systems, customer service systems, and other e-commerce functions. Similar to conventional information systems, system usability is an important issue for ECS. For developers, usability guidelines or principles are essential for improving user interfaces, system designs, and functionality of the system. However, most existing usability studies were conducted on different computing platforms. The results may not be applicable to ECS unconditionally. This paper is a research in progress that examines the usability issues of ECS. It first reviews and classifies existing studies related to system usability in the past few decades. The applicability of findings from existing studies is examined and discussed. Finally, a research taxonomy for measuring and improving the usability of ECS is proposed.
A framework for characterizing usability requirements elicitation and analysis methodologies (UREAM)

Dedicated methodologies for the elicitation and analysis of usability requirements have been proposed in literature, usually developed by usability experts. The usability of these approaches by non-expert software engineers is not obvious. In this paper, the objective is to support developers and managers in a software development project in deciding on which methodology to select, taking into account local strengths and weaknesses. We define a framework based on a set of criteria that allow for the comparison of methodologies.
The Visual Dictionary of Photography

"The Visual Dictionary of Photography" is a guide to the many and varied terms used within photography, from Abstract to the Zone System, Acutance to Zoom Lens. The dictionary provides clear definitions of key terms and concepts, backed up by hundreds of illustrative examples. Covering practical terms, it deals with the terminology of both digital and traditional photography. This book is an invaluable resource for anyone interested in photography, lens-based media and related visual arts. It serves not only to explain terms and words but also act as a source of inspiration, encouraging exploration through understanding.