This book constitutes the proceedings of the 15th International Conference on Quantitative Evaluation Systems, QEST 2018, held in Beijing, China, in September 2018. The 24 full papers presented were carefully reviewed and selected from 51 submissions. The papers cover topics in the field of quantitative evaluation and verification of computer systems and networks through stochastic models and measurements emphasizing two frontier topics in research: quantitative information flow for security and industrial formal methods.
This book constitutes the proceedings of the 17th International Conference on Quantitative Evaluation Systems, QEST 2020, held in Vienna, Austria, in August/September 2020. The 12 full papers presented together with 7 short papers were carefully reviewed and selected from 42 submissions. The papers cover topics such as classic measures involving performance and reliability, quantification of properties that are classically qualitative, such as safety, correctness, and security as well as analytic studies, diversity in the model formalisms and methodologies employed, and development of new formalisms and methodologies.
This book constitutes the proceedings of the 14th International Conference on Quantitative Evaluation Systems, QEST 2017, held in Berlin, Germany, in September 2017.The 20 full papers and 4 tool papers presented were carefully reviewed and selected From 58 submissions. The papers are organized in topical sections entitled: probabilistic modeling; smart energy systems over the cloud; Petri nets and performance modeling; parametric verification; machine learning and formal methods; tools.
This book constitutes the proceedings of the 12th International Conference on Quantitative Evaluation of Systems, QEST 2015, held in Madrid, Spain, in September 2015. The 19 papers presented were carefully reviewed and selected from 42 submissions. They are organized in topical sections named: modelling and applications; tools; petri nets, process algebra and fault trees; applications; and queuing systems and hybrid systems. The book also contains one full-paper invited talk.
This book constitutes the proceedings of the 13th International Conference on Quantitative Evaluation Systems, QEST 2016, held in Quebec City, Canada, in August 2016. The 21 full papers and 3 tool demonstration papers presented were carefully reviewed and selected from 46 submissions. They are organized in topical sections entitled: Markov processes; tools; sampling, inference, and optimization methods; Markov decision processes and Markovian analysis; networks.
This book constitutes the proceedings of the 8th International Conference on Modelling Techniques and Tools for Computer Performance Evaluation (Performance Tools '95) and of the 8th GI/ITG Conference on Measuring, Modelling and Evaluating Computing and Communication Systems, MMB '95, held jointly in Heidelberg, Germany in September 1995. The volume presents 26 full refereed papers selected from a total of 86 submissions, together with two invited contributions. The scope of the papers includes measurement- and model-based approaches for quantitative systems assessment, reports on theoretical and methodological progress, and novel and improved assessment techniques and their tool implementations and applications.
Clustering is an important technique for discovering relatively dense sub-regions or sub-spaces of a multi-dimension data distribution. Clus tering has been used in information retrieval for many different purposes, such as query expansion, document grouping, document indexing, and visualization of search results. In this book, we address issues of cluster ing algorithms, evaluation methodologies, applications, and architectures for information retrieval. The first two chapters discuss clustering algorithms. The chapter from Baeza-Yates et al. describes a clustering method for a general metric space which is a common model of data relevant to information retrieval. The chapter by Guha, Rastogi, and Shim presents a survey as well as detailed discussion of two clustering algorithms: CURE and ROCK for numeric data and categorical data respectively. Evaluation methodologies are addressed in the next two chapters. Ertoz et al. demonstrate the use of text retrieval benchmarks, such as TRECS, to evaluate clustering algorithms. He et al. provide objective measures of clustering quality in their chapter. Applications of clustering methods to information retrieval is ad dressed in the next four chapters. Chu et al. and Noel et al. explore feature selection using word stems, phrases, and link associations for document clustering and indexing. Wen et al. and Sung et al. discuss applications of clustering to user queries and data cleansing. Finally, we consider the problem of designing architectures for infor mation retrieval. Crichton, Hughes, and Kelly elaborate on the devel opment of a scientific data system architecture for information retrieval.
The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author’s years of research and teaching experiences. It is difficult to evaluate an organization’s performance when multiple performance metrics are present. The difficulties are further enhanced when the relationships among the performance metrics are complex and involve unknown tradeoffs. This book introduces Data Envelopment Analysis (DEA) as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective. Conventional and new DEA approaches are presented and discussed using Excel spreadsheets — one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets. DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA’s ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores. This book also provides an easy-to-use DEA software — DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject to the capacity of Excel Solver. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational performance issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.
Over thirty years of input from instructors and students have gone into this popular research methods text, resulting in a refined ninth edition that is easier to read, understand, and apply than ever before. Using unintimidating language and real-world examples, it introduces students to the key concepts of evidence-based practice that they will use throughout their professional careers. It emphasizes both quantitative and qualitative approaches to research, data collection methods, and data analysis, providing students with the tools they need to become evidence-based practitioners.
