V knige predlagaetsya jetalonnaya model´ IT-servisov vuza i rassmatrivaetsya vopros pokrytiya jetoj modeli besplatnymi resheniyami. Kniga prednaznachena dlya lic, otvetstvennyh za informatizaciju v vysshih uchebnyh zavedeniyah. Ona pomozhet opredelit´ nezakrytye IT-potrebnosti, ocenit´ nalichie besplatnyh reshenij i vybrat´ podhodyashhuju platformu dlya avtomatizacii konkretnyh processov. Krome togo, rezul´taty privedennogo issledovaniya budut polezny predstavitelyam kompanij-integratorov v sfere obrazovaniya. Oni obespechat bolee polnoe ponimanie potrebnostej zakazchika i pozvolyat sformirovat´ tehniko-kommercheskoe predlozhenie po avtomatizacii imenno teh zadach, kotorye ne mogut byt´ resheny s pomoshh´ju besplatnyh programmnyh produktov.
In Classification, Model Selection is one of the critical issues as different models from different categories are available. To select the best model for any given data set is a challenging task. Meta Learning automates this task by acquiring knowledge from the past experience and stores this knowledge into database called Meta Knowledge Base. When new data set comes, stored knowledge can be used for proving ranking of the candidate algorithms. But one of the problems with Meta Learning is generation of Meta Examples as large number of candidate algorithms and data sets are available. To reduce the generation of Meta Examples into Meta Knowledge Base, Active Meta Learning can be used that reduces generation of Meta Examples and at the same time maintaining the performance of candidate algorithms. In this book, Ranking is provided using Active Meta Learning approach by considering Data set Characteristics.
Limited to a strict interpretation of its definition, open source consists of a set of rules which apply to a piece of software and which specify how the software and derivatives of it may be used. However, it is widely seen as much more than a simple licensing agreement, it is a ´´philoshophy´´, a ´´production model´´, a ´´way of organizing projects´´, or even ´´a new innovation model´´. But how are open source projects organized and how is work coordinated and distributed between its developers? This work contributes by examining actual source code changes, comparing 29 projects. Which developers collaborate in the same files and wich work exclusively in their own domain? Looking for patterns across projects, this work attempts to identify coordination styles in open source projects.
Market threats, opportunities, changes in regulations and various quality improvement programs are the main drivers of change in an organization. These changes are very often depicted in business processes and business rules. Propagation of these changes to the underlying Information and Communication Technology (ICT) infrastructure becomes difficult due to lack of available documentation and rigid application design. Considering the frequency of changes in business processes in today´s competitive world, the resulting maintenance of supporting information system becomes difficult. This book proposes an approach ´´Business Process to Software Design (BP2SD)´´ that can help in the automatic propagation of changes in the process model to the software design. Business processes of an organization are modeled in suitable modeling languages and constructs of these process models are then linked to the corresponding software design elements. Whenever a change is introduced to these process models, it is automatically propagated to the linked software design element(s). Finally, a case study is presented in order to demonstrate the applicability of the proposed approach.
Learn Intel 64 assembly language and architecture, become proficient in C, and understand how the programs are compiled and executed down to machine instructions, enabling you to write robust, high-performance code. Low-Level Programming explains Intel 64 architecture as the result of von Neumann architecture evolution. The book teaches the latest version of the C language (C11) and assembly language from scratch. It covers the entire path from source code to program execution, including generation of ELF object files, and static and dynamic linking. Code examples and exercises are included along with the best code practices. Optimization capabilities and limits of modern compilers are examined, enabling you to balance between program readability and performance. The use of various performance-gain techniques is demonstrated, such as SSE instructions and pre-fetching. Relevant Computer Science topics such as models of computation and formal grammars are addressed, and their practical value explained. What You´ll Learn Low-Level Programming teaches programmers to: Freely write in assembly language Understand the programming model of Intel 64 Write maintainable and robust code in C11 Follow the compilation process and decipher assembly listings Debug errors in compiled assembly code Use appropriate models of computation to greatly reduce program complexity Write performance-critical code Comprehend the impact of a weak memory model in multi-threaded applications Who This Book Is For Intermediate to advanced programmers and programming students
This work focuses on the area of authentication and machine binding using either smart card or trusted platform module (TPM) technology, or a combination thereof. It is the major objective to demonstrate the value of each of these technologies based upon selected business scenarios. Underlying trust models and architectural requirements are discussed, and theoretical background of these technologies is provided to accommodate readers with the relevant terms to follow the subsequent discussion. The major part of this thesis consists of the research, comparison and analysis of existing publications and other sources-scientific, commercial, qualified journalistic or other-to gather a foundation of information on the subject topic. The problem cases or scenarios for applicability of smart card or TPM technology are based upon that research as well as the professional experience of the author and are not selected at random. This thesis shall provide interested readers with a decision base for the selection of protection mechanisms based upon either smart cards or TPM, or both.
Environmental visualisation is an emerging topic in the field of information visualisation. It is fast gaining importance because natural environments are constantly being subjected to complex interactions between the physical world and human impacts. Natural environments are valued because of their pristine wilderness appearances, and human interventions normally seek to be in sympathy with the aesthetics of natural environments wherever possible. Visualisation can be used to show the visual impact of changes on a landscape. Visualisation can be used to structure information in ways which highlight interests of users, rather than simply providing raw data. In seeking to manage natural environments, it is desirable to model and understand these complex interactions in order to compare the outcomes when different management scenarios are applied. To achieve this, environmental visualisations are valuable.
Geneticheskij algoritm byl predlozhen v 1975 godu Dzhonom Hollandom. Dannyj metod optimizacii yavlyaetsya jevristicheskim i predstavlyaet soboj prostejshuju model´ jevoljucii v prirode. Algoritm Hollanda ne garantiruet obnaruzheniya global´nogo resheniya za priemlemoe vremya. Krome togo, net garantii optimal´nosti najdennogo resheniya. Odnako jeto ne pomeshalo emu poluchit´ priznanie. Neosporimoe dostoinstvo geneticheskogo algoritma zakljuchaetsya v ego universal´nosti. On mozhet primenyat´sya dlya resheniya zadach, dlya kotoryh ne razrabotano special´nyh metodov. Ves´ma sushhestvenen tot fakt, chto teoriya geneticheskogo algoritma prosta, ne trebuet osobyh znanij, dostupna ljubomu obyvatelju. Nastrojka zhe parametrov geneticheskogo algoritma yavlyaetsya neprostoj zadachej. Cel´ju raboty yavlyaetsya issledovanie znachimosti dannyh parametrov. Kakie parametry yavlyajutsya naibolee sushhestvennymi? Sushhestvuet li svyaz´ mezhdu parametrami? Kakie rekomendacii mozhno dat´ po nastrojke geneticheskogo algoritma?
This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users´ perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this re search area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences.
The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.