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Unlock Your Potential with "Basic Computer Engineering" Designed for Computer and IT students, this textbook is meticulously organized to provide a seamless understanding of computer fundamentals and advanced concepts. Covering essential topics in alignment with the RGPV syllabus, this book offers a comprehensive journey from basic components to modern digital applications. Equip yourself with the knowledge you need to excel in your studies and future career. Perfect for mastering the subject and acing your exams, "Basic Computer Engineering" is your key to success!
A groundbreaking investigation into why so many Islamic radicals are engineers The violent actions of a few extremists can alter the course of history, yet there persists a yawning gap between the potential impact of these individuals and what we understand about them. In Engineers of Jihad, Diego Gambetta and Steffen Hertog uncover two unexpected facts, which they imaginatively leverage to narrow that gap: they find that a disproportionate share of Islamist radicals come from an engineering background, and that Islamist and right-wing extremism have more in common than either does with left-wing extremism, in which engineers are absent while social scientists and humanities students are prominent. Searching for an explanation, they tackle four general questions about extremism: Under which socioeconomic conditions do people join extremist groups? Does the profile of extremists reflect how they self-select into extremism or how groups recruit them? Does ideology matter in sorting who joins which group? Lastly, is there a mindset susceptible to certain types of extremism? Using rigorous methods and several new datasets, they explain the link between educational discipline and type of radicalism by looking at two key factors: the social mobility (or lack thereof) for engineers in the Muslim world, and a particular mindset seeking order and hierarchy that is found more frequently among engineers. Engineers' presence in some extremist groups and not others, the authors argue, is a proxy for individual traits that may account for the much larger question of selective recruitment to radical activism. Opening up markedly new perspectives on the motivations of political violence, Engineers of Jihad yields unexpected answers about the nature and emergence of extremism.
More software engineers are likely to work in a globally distributed environment, which brings benefits that include quick and better software development, less manpower retention, scalability, and less software development cost and sharing of knowledge from the global pool of employees. However, these work environments also introduce a physical separation between team members and project leaders, which can create problems in communication and ultimately lead to the failure of the project. Human Factors in Global Software Engineering is a collection of innovative research focusing on the challenges, issues, and importance of human factors in global software engineering organizations in order to help these organizations better manage their manpower and provide an appropriate culture and technology in order to make their software development projects successful. While highlighting topics including agile software, knowledge management, and human-computer interaction, this book is ideally designed for project managers, administrators, business professionals, researchers, practitioners, students, and academicians.
In this book written for a dangerous age, the founder of The Investigative Project on Terrorism offers a thorough and factual overview of the Islamist terrorist threat to America.
This collection of papers, articles, and monographs details the ethical landscape as it exists for the distinct areas of Internet and network security, including moral justification of hacker attacks, the ethics behind the freedom of information which contributes to hacking, and the role of the law in policing cyberspace.
The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and efficacy of programming such algorithms. Applications of Machine Learning and Deep Learning on Biological Data is an examination of applying ML and DL to such areas as proteomics, genomics, microarrays, text mining, and systems biology. The key objective is to cover ML applications to biological science problems, focusing on problems related to bioinformatics. The book looks at cutting-edge research topics and methodologies in ML applied to the rapidly advancing discipline of bioinformatics. ML and DL applied to biological and neuroimaging data can open new frontiers for biomedical engineering, such as refining the understanding of complex diseases, including cancer and neurodegenerative and psychiatric disorders. Advances in this field could eventually lead to the development of precision medicine and automated diagnostic tools capable of tailoring medical treatments to individual lifestyles, variability, and the environment. Highlights include: Artificial Intelligence in treating and diagnosing schizophrenia An analysis of ML’s and DL’s financial effect on healthcare An XGBoost-based classification method for breast cancer classification Using ML to predict squamous diseases ML and DL applications in genomics and proteomics Applying ML and DL to biological data
They are Americans, and they are mujahideen. Hundreds of men from every imaginable background have walked away from the traditional American dream to volunteer for battle in the name of Islam. Some have taken part in foreign wars that aligned with U.S. interests, while others have carried out violence against Westerners abroad, fought against the U.S. military, and even plotted terrorist attacks on American soil. This story plays out over decades and continents: from the Americans who took part in the siege of Mecca in 1979 through conflicts in Lebanon, Afghanistan, and Bosnia, and continuing today in Afghanistan and Somalia. Investigative journalist J. M. Berger profiles numerous fighters, including some who joined al Qaeda and others who chose a different path. In these pages he portrays, among others, Abdullah Rashid, who fought the Soviets in Afghanistan; Mohammed Loay Bayazid, who was present at the founding of al Qaeda; Ismail Royer, who fought in Bosnia and Kashmir, then returned to run training camps in the United States; Adam Gadahn, a Jewish Californian who is now al Qaeda's chief spokesman; and Anwar Awlaki, the Yemeni-American imam with links to 9/11 who is now considered one of the biggest threats to America's security.
Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry. This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system. This book is written for Researchers, Students, Professionals, Executives, and the general public.
This book constitutes the refereed proceedings of the 6th International Conference on Soft Computing in Data Science, SCDS 2021, which was held virtually in November 2021. The 31 revised full papers presented were carefully reviewed and selected from 79 submissions. The papers are organized in topical sections on ​​AI techniques and applications; data analytics and technologies; data mining and image processing; machine & statistical learning.
This book comprises a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2021), held at Technical University of Sofia, Sofia, Bulgaria, during 08–10 July 2021. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more.