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Doing Cross-Cultural Research : Ethical and Methodological Perspectives
Conducting cross-cultural research is rife with methodological, ethical and moral challenges. Researchers are challenged with many issues in carrying out their research with people in cross-cultural arenas. In this book, I attempt to bring together salient issues for the conduct of culturally appropriate research. The task of undertaking cross-cultural research can present researchers with unique opportunities, and yet dilemmas. The book will provide some thought-provoking points so that our research may proceed relatively well and yet ethical in our approach. The subject of the book is on the ethical, methodological, political understanding and practical procedures in undertaking cross-cultural research.
Do-All Computing in Distributed Systems : Cooperation in the Presence of Adversity
Do-All Computing in Distributed Systems: Cooperation in the Presence of Adversity is the first book that presents an in depth study of cooperation problems, abstracted in terms of the Do-All problem, where a collection of processors cooperatively perform a collection of independent tasks in the presence of adversity.
Dissemination of information in communication networks : Broadcasting, gossiping, leader election, and fault-tolerance
Preface Due to the development of hardware technologies (such as VLSI) in the early 1980s, the interest in parallel and distributive computing has been rapidly growingandinthelate1980sthestudyofparallelalgorithmsandarchitectures became one of the main topics in computer science. To bring the topic to educatorsandstudents,severalbooksonparallelcomputingwerewritten. The involvedtextbook“IntroductiontoParallelAlgorithmsandArchitectures”by F. Thomson Leighton in 1992 was one of the milestones in the development of parallel architectures and parallel algorithms. But in the last decade or so the main interest in parallel and distributive computing moved from the design of parallel algorithms and expensive parallel computers to the new distributive reality – the world of interconnected computers that cooperate (often asynchronously) in order to solve di?erent tasks.
Digitization of the management accounting function : A case study analysis on manufacturing companies
Analyzes the impact of digitization on management accounting in five manufacturing companies. It is one of the first in-depth empirical studies on the intersection of management accounting and digitization. The study suggests that there are two archetypes of digitization of the management accounting function. The first archetype emphasizes top-down-driven changes that aim to enhance efficiency, such as conducting tasks with a higher degree of automation in a leaner structure with fewer resources. The second archetype is strongly driven and initiated by employees in the management accounting function (bottom-up). The focus is on improving the use of data by applying innovative analytics methods, integrating additional sources of data, and benefiting from new technologies like artificial intelligence. The results of the study also indicate that digitization of the management accounting function is mostly in line with the overall company strategy.
Digital Image Processing
The book offers an integral view of image processing from image acquisition to the extraction of the data of interest. The discussion of the general concepts is supplemented with examples from applications on PC-based image processing systems and ready-to-use implementations of important algorithms. Each chapter now includes exercises that help you to test your understanding, train your skills, and introduce you to real-world image processing tasks. An important part of the exercises is a wealth of interactive computer exercises, which cover all topics of this textbook.
Diabetes genetic finder & predictor = أداة البحث والتنبؤ الجيني لمرض السكري
The diabetes genetic finder & predictor app is a comprehensive, user-friendly solution that revolutionizes diabetes care. This powerful app integrates a wide array of features designed to empower diabetes patients and enhance their overall well-being. A standout feature of the app is its ability to predict the risk of hereditary diabetes diseases, offering users early detection and intervention opportunities. It also predicts general diabetes risk, diabetic foot complications, and retinopathy. Users can monitor their blood sugar levels, heart rate, and oxygenation either manually or through smart watch integration. Additionally, users can enter their diabetes type and HbA1c levels.The app's medication management feature simplifies the complex task of tracking and organizing medications, providing timely reminders to ensure adherence to treatment plans. Users can scan QR codes on products to check their sugar content and suitability, schedule their medications, generate reports for specific periods, and access a comprehensive list of frequently asked questions about diabetes..
Developing BIM talent : A guide to the BIM body of knowledge with Metrics, KSAs, and learning outcomes
A systematic Building Information Modeling (BIM) framework features cutting-edge use cases and competencies for students and professionals pursuing BIM careers. Offers: A solid foundation and guidelines for educators and practitioners for starting or enhancing a BIM curriculum or training program Templates, expert interviews, and case studies that provide in-depth knowledge and lessons learned that can facilitate process changes and strategic action plans Strategies for standardizing emerging BIM job tasks, descriptions, and methods for benchmarking performance
Designing virtual reality systems : The structured approach
Virtual Reality (VR) is a field of study that aims to create a system that provides a synthetic experience for its users. Developing and maintaining a VR system is a very difficult task, requiring in-depth knowledge in many different disciplines, such as sensing and tracking technologies, stereoscopic displays, multimodal interaction and processing, computer graphics and geometric modeling, dynamics and physical simulation, performance tuning, etc. The difficulty lies in the complexity of having to simultaneously consider many system goals, some of which are conflicting.
Designing human interface in speech technology
Designing Human Interface in Speech Technology bridges a gap between the needs of the technical engineer and cognitive researchers working in the multidisciplinary area of speech technology applications. The approach is systematic and the focus is on the utility of developing and designing speech related products. Included is coverage of topics such as neuroscience on the multimodal cortex, cognitive theories on multi-task performance, stress and workload, as well as human information process theory and ecological interface design theory for evaluating speech-related human-system interfaces.
Design for Environmental Sustainability
Design for Environmental Sustainability is a technical and operative contribution to the United Nations "Decade on Education for Sustainable Development" (2005-2014), aiding the development of a new generation of designers, responsible and able in the task of designing environmentally sustainable products.
Design and analysis of randomized algorithms : Introduction to design paradigms
Randomness is a powerful phenomenon that can be harnessed to solve various problems in all areas of computer science. Randomized algorithms are often more efficient, simpler and, surprisingly, also more reliable than their deterministic counterparts. Computing tasks exist that require billions of years of computer work when solved using the fastest known deterministic algorithms, but they can be solved using randomized algorithms in a few minutes with negligible error probabilities. Introducing the fascinating world of randomness, this book systematically teaches the main algorithm design paradigms – foiling an adversary, abundance of witnesses, fingerprinting, amplification, and random sampling, etc. – while also providing a deep insight into the nature of success in randomization. Taking sufficient time to present motivations and to develop the reader's intuition, while being rigorous throughout, this text is a very effective and efficient introduction to this exciting field.
Design and Analysis of Learning Classifier Systems : A Probabilistic Approach
This book provides a comprehensive introduction to the design and analysis of Learning Classifier Systems (LCS) from the perspective of machine learning. LCS are a family of methods for handling unsupervised learning, supervised learning and sequential decision tasks by decomposing larger problem spaces into easy-to-handle subproblems.
Dental materials : Properties and manipulation
Focusing on the dental materials most commonly used, Dental Materials: Properties and Manipulation, 10th Edition covers the tasks that dental assistants and dental hygienists typically perform. It shows the most current materials, how to mix and apply them in a clinical setting, and how to educate patients about them. Now in full color, this edition adds more photographs of materials actually being mixed, used, and applied, and includes detailed coverage of ceramics, metals, and implant and impression materials. Written by well-known experts on restorative dentistry and materials
Deep learning methods for converting speech to text = تقنيات التعلم العميق في تحويل الصوت إلى نص
Aims to design and develop a system capable of extracting audio content from films and audio recordings and converting it into text using deep learning techniques. This is done by analyzing audio patterns, extracting sounds and words from the video, and then converting them into written text. Deep learning, a branch of artificial intelligence, is used to accomplish this task. The study also includes comparing different deep learning techniques to determine their effectiveness in this context.
Deep learning and computer vision in remote sensing-I
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
Declarative agent languages and technologies II ; 2nd international workshop, DALT 2004, New York, NY, USA, July 19, 2004, revised selected papers
Nearly 40 research groups worldwide were motivated to contribute to this event by submitting their most recent research achievements, covering a wide variety of the topics listed in the call for papers. More than 30 top researchers agreed to join the Program Committee, which then collectively faced the hard task of selecting the one-day event program. The fact that research in multi-agent systems is no longer only a novel and promising research horizon at dawn is, in our opinion, the main reason behind DALT’s (still short) success story. On the one hand, agent theories and app- cations are mature enough to model complex domains and scenarios, and to successfully address a wide range of multifaceted problems, thus creating the urge to make the best use of this expressive and versatile paradigm, and also pro?t from all the important results achieved so far. On the other hand, bui- ing multi-agent systems still calls for models and technologies that could ensure system predictability, accommodate ?exibility, heterogeneity and openness, and enable system veri?cation.
Dataset Studio
Data is the new oil, which means that AI engineers can face difficulties in locating suitable datasets. Dataset Studio is a comprehensive platform designed to support AI engineers in the creation and optimization of datasets. This project offers a diverse range of services that encompass data collection, data augmentation, and data classification. As a result, this software empowers engineers by automatically generating structured data through the utilization of advanced tools and AI techniques. By automating the laborious tasks of manual data collection and extraction, Dataset Studio effectively streamlines the workflow for AI engineers, enabling them to save valuable time and focus on the more intricate aspects of dataset development and refinement.
Data mining with computational intelligence
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Data Manipulation with R
Since its inception, R has become one of the preeminent programs for statistical computing and data analysis. The ready availability of the program, along with a wide variety of packages and the supportive R community make R an excellent choice for almost any kind of computing task related to statistics. However, many users, especially those with experience in other languages, do not take advantage of the full power of R. Because of the nature of R, solutions that make sense in other languages may not be very efficient in R. This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data.
Data and Text Processing for Health and Life Sciences
This book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application.
