EDV-gestützte Personaleinsatzplanung. Methoden und Verfahren:1. Auflage. Philipp Funke
EDV-gestützte Personaleinsatzplanung. Methoden und Verfahren:1. Auflage Philipp Funke
This study invested the face recognition system as a method of authentication for recognition of students in Mengo Senior secondary school. The objectives of the study where to study the inherent weaknesses of other technologies that are already existing, to determine the requirements for the Face Recognition Systems as a method of authentication for Mengo Senior School, to design the Face Recognition System for the purpose of authentication and to implement a working prototype of the Face Recognition System as a method of authentication for Mengo Senior School. The methods used in data collection were structured questionnaires and interviews.The author used C# programming language to develop the algorithms of the system. Visual Studio was also used to design interfaces and open CV libraries. Thus, the system was developed, tested and proved to be successful. In organizations, Back up systems should always be used.
These proceedings consist of 19 papers, which have been peer-reviewed by international program committee and selected for the 5th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2017), which was held on June 30-July 1, 2017 in Berlin, Germany. The respective chapters discuss both theoretical and practical issues in connection with computational methods and optimization methods for knowledge engineering. The broad range of application areas discussed includes network computing, simulation, intelligent and adaptive e-learning, information retrieval, sentiment analysis, autonomous underwater vehicles, social media analysis, natural language processing, biomimetics in organizations, and cash management. In addition to pure content, the book offers many inspiring ideas and suggests new research directions, making it a valuable resource for graduate students, Ph.D. students, and researchers in Computer Science and Applied Mathematics alike.
This book presents modern techniques for the analysis of Markov chain Monte Carlo (MCMC) methods. A central focus is the study of the number of iteration of MCMC and the relation to some indices, such as the number of observation, or the number of dimension of the parameter space. The approach in this book is based on the theory of convergence of probability measures for two kinds of randomness: observation randomness and simulation randomness. This method provides in particular the optimal bounds for the random walk Metropolis algorithm and useful asymptotic information on the data augmentation algorithm. Applications are given to the Bayesian mixture model, the cumulative probit model, and to some other categorical models. This approach yields new subjects, such as the degeneracy problem and optimal rate problem of MCMC. Containing asymptotic results of MCMC under a Bayesian statistical point of view, this volume will be useful to practical and theoretical researchers and to graduate students in the field of statistical computing.
The development of modern high-tech branches of medicine, including orthopaedics, traumatology and dentistry, places high demands on the quality of materials. The study of the processes occurring in the design of biocompatible material and the manufacture of medical products from it, as well as the ability to manage them, contribute to the production of a material with specified properties. So, the task of the optimal biocompatible material selection for medical usage is a complex task that we solved using Artificial Intelligence tools. In the book, authors describe an improved approach to the development of supervised learning methods for high-precision biocompatible materials selection. The general idea of these methods is a compatible use of the Kolmogorov-Gabor polynomial and machine learning algorithms. This polynomial allows increasing the dimension of the input dataset, which in turn increases the likelihood of correct materials classification. Machine learning algorithms are used as fast tools for finding the coefficients of this polynomial. Experimental studies have shown high classification accuracy using the proposed approach.
This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods. Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data. Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner. The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.
This new and completely updated edition is a comprehensive, easy-to-read, ´´how-to´´ guide on user research methods. You´ll learn about many distinct user research methods and also pre- and post-method considerations such as recruiting, facilitating activities or moderating, negotiating with product developments teams/customers, and getting your results incorporated into the product. For each method, you´ll understand how to prepare for and conduct the activity, as well as analyze and present the data - all in a practical and hands-on way. Each method presented provides different information about the users and their requirements (e.g., functional requirements, information architecture). The techniques can be used together to form a complete picture of the users´ needs or they can be used separately throughout the product development lifecycle to address specific product questions. These techniques have helped product teams understand the value of user experience research by providing insight into how users behave and what they need to be successful. You will find brand new case studies from leaders in industry and academia that demonstrate each method in action. This book has something to offer whether you are new to user experience or a seasoned UX professional. After reading this book, you´ll be able to choose the right user research method for your research question and conduct a user research study. Then, you will be able to apply your findings to your own products. Completely new and revised edition includes 30+% new content! Discover the foundation you need to prepare for any user research activity and ensure that the results are incorporated into your products Includes all new case studies for each method from leaders in industry and academia
Are you attracted by the promises of agile methods but put off by the fanaticism of many agile texts? Would you like to know which agile techniques work, which ones do not matter much, and which ones will harm your projects? Then you need Agile! : the first exhaustive, objective review of agile principles, techniques and tools. Agile methods are one of the most important developments in software over the past decades, but also a surprising mix of the best and the worst. Until now every project and developer had to sort out the good ideas from the bad by themselves. This book spares you the pain. It offers both a thorough descriptive presentation of agile techniques and a perceptive analysis of their benefits and limitations. Agile! serves first as a primer on agile development : one chapter each introduces agile principles, roles, managerial practices, technical practices and artifacts. A separate chapter analyzes the four major agile methods: Extreme Programming, Lean Software, Scrum and Crystal. The accompanying critical analysis explains what you should retain and discard from agile ideas. It is based on Meyer´s thorough understanding of software engineering, and his extensive personal experience of programming and project management. He highlights the limitations of agile methods as well as their truly brilliant contributions - even those to which their own authors do not do full justice. Three important chapters precede the core discussion of agile ideas: an overview, serving as a concentrate of the entire book; a dissection of the intellectual devices used by agile authors; and a review of classical software engineering techniques, such as requirements analysis and lifecycle models, which agile methods criticize. The final chapters describe the precautions that a company should take during a transition to agile development and present an overall assessment of agile ideas. This is the first book to discuss agile methods, beyond the brouhaha, in the general context of modern software engineering. It is a key resource for projects that want to combine the best of established results and agile innovations.