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Asil Kan
“ARIANA GRANDE!” Türkiye Cumhuriyeti’nin kuruluş gayesinin esası, yakın bir gelecekte tüm milletleri “İnsanlık Rotası’nda” birleştirecek yapıyı kurabilmekti. Çünkü, Anadolu insanı, bu “yüksek bilince” ulaşabilecek genetik ve kozmik aktarımlarla donatılmıştır. Anadolu’nun, zor dönemlerde Seçilmiş Lider, yani Yaradan tarafından seçilmiş ve insiye edilmiş lider çıkarabilme potansiyelinin yüksek oluşu, tesadüfi olayların değil genetiğe ve bilince işlemiş “kültürel kodların” neticesiyle olmuştur. Asil Kan olarak seçilmiş, vazifeli olan kişiler icazete ihtiyaç duymadan kararlar alırlar. Ayrıca onlar, “devlet yönetme” irade...
Ottoman-Southeast Asian Relations (2 vols.)
Ottoman-Southeast Asian Relations: Sources from the Ottoman Archives, is a product of meticulous study of İsmail Hakkı Kadı, A.C.S. Peacock and other contributors on historical documents from the Ottoman archives. The work contains documents in Ottoman-Turkish, Malay, Arabic, French, English, Tausug, Burmese and Thai languages, each introduced by an expert in the language and history of the related country. The work contains documents hitherto unknown to historians as well as others that have been unearthed before but remained confined to the use of limited scholars who had access to the Ottoman archives. The resources published in this study show that the Ottoman Empire was an active actor within the context of Southeast Asian experience with Western colonialism. The fact that the extensive literature on this experience made limited use of Ottoman source materials indicates the crucial importance of this publication for future innovative research in the field. Contributors are: Giancarlo Casale, Annabel Teh Gallop, Rıfat Günalan, Patricia Herbert, Jana Igunma, Midori Kawashima, Abraham Sakili and Michael Talbot
Encyclopedia of the Ottoman Empire
Presents a comprehensive A-to-Z reference to the empire that once encompassed large parts of the modern-day Middle East, North Africa, and southeastern Europe.
Enhancing Synergies in a Collaborative Environment
This volume contains a selection of the best papers presented at the 8th International Conference on Industrial Engineering and Industrial Management, XX International Conference on Industrial Engineering and Operations Management, and International IIE Conference 2014, hosted by ADINGOR, ABEPRO and the IIE, whose mission is to promote links between researchers and practitioners from different branches, to enhance an interdisciplinary perspective of industrial engineering and management. The conference topics covered: operations research, modelling and simulation, computer and information systems, operations research, scheduling and sequencing, logistics, production and information systems, ...
Graph Representation Learning
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical sy...
Introduction to Autonomous Mobile Robots, second edition
The second edition of a comprehensive introduction to all aspects of mobile robotics, from algorithms to mechanisms. Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material f...
Federated Learning
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated lear...
LAW, POLITICS & SOCIETY: The Unravelling of Malaysia and Indonesia Potentiality
Penerbit: Airlangga University Press ISBN: 9786024737740 This book is the fourth compilation as a regular joint publishing effort since 2017 between Sultan Zainal Abidin University (UniSZA), Terengganu, Malaysia, and Airlangga University (UNAIR), Surabaya, Indonesia. Filled by lecturers and students, this book is expected to strengthen the relationship between the two universities and further strengthen the Malaysia-Indonesia relationship.
Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.
