الصفحة 4
الصفحة 4
Developing Ambient Intelligence ; Proceedings of the First International Conference on Ambient Intelligence Developments (AmID'06)
As Ambient Intelligence (AmI) ecosystems are rapidly becoming a reality, they raise new research challenges. Unlike predefined static architectures as we know them today, AmI ecosystems are bound to contain a large number of heterogeneous computing, communication infrastructures and devices that will be dynamically assembled. Architectures will be sensitive, adaptive, context-aware and responsive to users‚ needs and habits.Researchers need to both enable their user-friendly application in a growing number of areas while ensuring that these applications remain reliable and secure. Held in Sophia Antipolis (France) from September the 20th to September the 22nd 2006, the first edition of the AmI.d conference tackled the latest research challenges within AmI ecosystems, presented AmI applications as well as security solutions.
Deterministic and statistical methods in Machine Learning ; 1st International Workshop, Sheffield, UK, September 7-10, 2004. Revised Lectures
This book consitutes the refereed proceedings of the First International Workshop on Machine Learning held in Sheffield, UK, in September 2004. The 19 revised full papers presented were carefully reviewed and selected for inclusion in the book. They address all current issues in the rapidly maturing field of machine learning that aims to provide practical methods for data discovery, categorisation and modelling. The particular focus of the workshop was advanced research methods in machine learning and statistical signal processing.
Deepfake detection = اكتشاف التزييف العميق
In the rapidly evolving era of artificial intelligence, addressing the escalating threats of deepfake technology becomes a necessity because of the increasing sophistication of AI algorithms in generating deceptive content, and since it threatens the integrity of information across diverse data. The main objective is to build a sophisticated AI-driven system to detect different types of deepfake in text, audio, and images. In English text deepfake detection, multiple pre-trained tokenizers have been used, but XLNET and BERT stand out with identifying objects outside the dataset with an accuracy of 0.9809 and both have been generalized & trained using LSTM. In Arabic text deepfake detection, Arabert has been trained using LSTM which led with an accuracy of 99.53% by generalizing the model. Both English and Arabic datasets have been generated to enhance the accuracy and effectiveness of the models. Audio deepfake detection has been generalized too, using Random Forest with an accuracy of 98.259%.
Deepfake detection
Recently, various techniques of manipulating the video content have become available to everyone – online, one can find free applications e.g., for face swapping in videos. Such universal accessibility carries a notable risk of flooding online content with false information, affecting not only the greats of this world, but also the whole societies, also the rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. It is therefore necessary to develop a verification tool that will help assess the authenticity of the videos posted on the internet. This project describes the approach of using artificial intelligence solutions to detect doctored videos.
Deep Learning-Based Face Analytics
Provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field.
Deep learning pipeline : Building a deep learning model with TensorFlow
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.
Decrypted Secrets : Methods and Maxims of Cryptology
Cryptology, for millennia a "secret science", is rapidly gaining in practical importance for the protection of communication channels, databases, and software. Beside its role in computerized information systems (public key systems), more and more applications within computer systems and networks are appearing, which also extend to access rights and source file protection. The first part of this book treats secret codes and their uses - cryptography. The second part deals with the process of covertly decrypting a secret code - cryptanaly-sis - where in particular advice on assessing methods is given. The book presupposes only elementary mathematical knowledge.
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 science, AI, and machine learning in drug development
The confluence of big data, AI, and machine learning has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R&D, emerging applications of big data, AI and machine learning in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations
Data Quality : Concepts, Methodologies and Techniques
Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art.
Data parallel C++programming accelerated systems using C++ and SYCL
Full of practical advice, detailed explanations, and code examples to illustrate key topics. SYCL enables access to parallel resources in modern accelerated heterogeneous systems. Now, a single C++ application can use any combination of devices–including GPUs, CPUs, FPGAs, and ASICs–that are suitable to the problems at hand. This book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL. Later chapters cover advanced topics, including error handling, hardware-specific programming, communication and synchronization, and memory model considerations.
Data parallel C++ : Mastering DPC++ for programming of heterogeneous systems using C++ and SYCL
This book teaches data-parallel programming using C++ and the SYCL standard from the Khronos Group and walks through everything needed to use SYCL for programming heterogeneous systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL and Data Parallel C++ (DPC++), the open source compiler used in this book.
Data mining and machine learning applications
Elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data.
Data Algorithms with Spark
Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns
Cryptographic hardware and embedded systems - CHES 2007 ; 9th International Workshop, Vienna, Austria, September 10-13, 2007, Proceedings
The papers collected in this volume represent cutting-edge world wide research in the rapidly evolving fields of crypto-hardware, fault-based and side-channel cryptanalysis, and embedded cryptography, at the crossing of academic and - dustrial research. The wide diversity of subjects appearing in these proceedings covers virtually all related areas and shows our e?orts to extend the scope of CHES more than usual.
Creating Mobile Games : Using Java™ ME Platform to Put the Fun into Your Mobile Device and Cell Phone
Creating Mobile Games: shows you how to create a basic game and make it a professional one (by adding a pro look-and-feel by writing your own menus or using the open source J2ME Polish, and enabling marketing/billing from your own web site). Demonstrates Wireless Messaging and other optional APIs (using SMS, PIM, File Connection, Bluetooth, and so forth in a multiplayer game).
Creating Flash Widgets with Flash CS4 and ActionScript 3.0
Creating Flash Widgets with Flash CS4 and ActionScript 3.0 is an introduction to developing widgets for the Internet using the features of Flash CS4 and ActionScript 3.0. Many social-networking sites, blogs, and personal home pages have adopted the use of widgets and Flash developers can create and distribute their own widgets for others to use. A step-by-step example demonstrates how to design and develop your own Flash widgets and integrate them with XML. In addition, publishing, promoting, and capitalizing on your Flash widgets is discussed.
Core Java ; Vol. I : Fundamentals ; 12th ed.
The definitive guide to writing robust, maintainable code. Whatever version of Java you are using—up to and including Java 17—this book will help you achieve a deep and practical understanding of the language and APIs. With hundreds of realistic examples, Cay S. Horstmann reveals the most powerful and effective ways to get the job done.
Content based social platform optimization “Fashion Platform"
The purpose of this project is to design a platform that concentrates on Fashion in addition to assisting users with gathering an informative feedback, as well as linking local stores to those users. This platform will be delivered as a mobile application that is available to any user who is interested in expressing and sharing his/her prevailing taste in fashion simply by posting photos, interacting with other people’s posts and leaving comments for them. The app will also provide some features in an attempt to push the users to be more enthusiastic and to be more encouraged about trying and continuously using this app. Moreover, this platform will incorporate a Shop section, which will be the actual local stores that are connected to it, so the user can buy an item that he/she is fond of.
Constraint solving and language processing
Contains selected and thoroughly revised papers plus contributions from invited speakers presented at the First International Workshop on C- straint Solving and Language Processing, held in Roskilde, Denmark, September 1–3, 2004. Constraint Programming and Constraint Solving, in particular Constraint Logic Programming, appear to be a very promising platform, perhaps the most promising present platform, for bringing forward the state of the art in natural language processing, this due to the naturalness in speci?cation and the direct relation to e?cient implementation. Language, in the present context, may - fer to written and spoken language, formal and semiformal language, and even general input data to multimodal and pervasive systems, which can be handled in very much the same ways using constraint programming. The notion of constraints, with slightly differing meanings, apply in the characterization of linguistic and cognitive phenomena, in formalized linguistic m- els as well as in implementation-oriented frameworks. Programming techniques for constraint solving have been, and still are, in a period with rapid devel- ment of new eficient methods and paradigms from which language processing can prompt. A common metaphor for human language processing is one big c- straint solving process in which the differently specified linguistic and cognitive phases take place in parallel and with mutual cooperation, which ?ts quite well with current constraint programming paradigms.
