الصفحة 8
الصفحة 8
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Dependable computing ; 2nd Latin-American symposium, LADC 2005, Salvador, Brazil, October 25-28, 2005 : proceedings

Contains the proceedings of the 'Second Latin-American Symposium' on Dependable Computing, LADC 2005. This book comprises 16 papers presented together with 3 invited talks. The papers are organized in topical sections on evaluation, certification, modelling, embedded systems, time, and distributed systems algorithms.

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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%.

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Deepfake

The technology used to create such digital content has quickly become accessible to the masses, such as “DEEPFAKE.” Deep fakes refer to manipulated videos, or other digital representations produced by sophisticated artificial intelligence, that yields to synthesize a sequence of face images and voices of characters corresponding to their identities, such as voice tone, facial expression, with a good lip synchronization. Therefore, this study is about developing real-time video generation software, which generates a target video from a single input image. Several methods and algorithms have been applied to detect, analyze personalize facial expression, voice and natural head poses to present a life-like image instead of a low quality one.

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Data science on the Google cloud platform : Implementing end-to-end real-time data pipelines : From ingest to machine learning

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. You'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines

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Data science and data analytics : Opportunities and challenges

Gives the concept of data science, tools, and algorithms that exist for many useful applications / Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems / Identifies many areas and uses of data science in the smart era / Applies data science to agriculture, healthcare, graph mining, education, security, etc.

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Data Driven Methods for Civil Structural Health Monitoring and Resilience : Latest Developments and Applications

Provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications

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Crime detection camera

This paper presents a comprehensive crime detection system that uses a combination of hardware and software to monitor homes and communities in real time. The system consists of a Raspberry Pi 4B, a Raspberry Pi Camera V2, a flame sensor, an MQ-6 gas sensor, and a microphone, which are all connected to a database management system powered by MySQL. The data collected from these devices is analyzed by machine learning algorithms to detect crimes, such as theft or robbery, as well as fires and gas leaks. The system also includes a mobile app, ‘Safe Home’ which provides live video monitoring and real-time notifications to users, and an employee dashboard to monitor all statistics and manage all implemented systems.

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Cooperative tool

Online collaboration is fast becoming a permanent feature of the modern workplace. Companies and organizations are attracted by the cost-effective technology allowing employees to work together anywhere, at any time using any internet-enabled device. Online collaboration gives team members the tools they need to work with others from any location, including from home and while travelling. This drastically reduces “downtime” and allows people to be productive when it best suits them therefore we propose a website that provides content (videoconference, real-time Chat, whiteboard).

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Control and Scheduling Codesign : Flexible Resource Management in Real-Time Control Systems

Recent evolutionary advances in information and communication technologies give rise to a new environment for Real Time Control Systems. This book is a monograph that covers our recent and original results in this direction.

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Contrast-Enhanced Ultrasound in Clinical Practice : Liver, Prostate, Pancreas, Kidney and Lymph Nodes

Concomitant with the improvement of contrast agents, different contrast-specific imaging modalities have been developed which, used in combination with USCA and a low mechanical index, allow continuous real-time grey-scale imaging. These recent technical improvements have opened new possibilities in the use of USCA in a variety of indications. Written by internationally renowned experts, the contributions gathered in this book give an overview of current and possible future new applications of USCA in routine and clinical practice.

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Condition Monitoring and Control for Intelligent Manufacturing

Manufacturing systems and processes are becoming increasingly complex, making more rational decision-making in process control a necessity. The book presents a wide and comprehensive review of the key areas of research in machine condition monitoring and control, before focusing on an in-depth treatment of each important technique, from multi-domain signal processing for defect diagnosis to web-based information delivery for real-time control.

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CONCUR 2005 - Concurrency Theory

This volume contains the papers presented at CONCUR 2005, the 16th - ternational Conference on Concurrency Theory. The purpose of the CONCUR series of conferences is to bring together researchers,developers, and students in order to advance the theory of concurrency and to promote its applications. The Program Committee selected 38 papers for presentation. Because of the format of the conference and the high number of submissions, many good papers could not be included. Although submissions werereadand evaluated, the papers that appear in this volume may di?er in form and contents from the corresponding submissions.

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Computer safety, reliability, and security ; Vol. 3688

This book constitutes the refereed proceedings of the 24th International Conference on Computer Safety, Reliability, and Security, SAFECOMP 2005, held in Fredrikstad, Norway, in September 2005. The 30 revised full papers were carefully reviewed and selected for inclusion in the book. The papers address all aspects of dependability and survivability of critical computerized systems in various branches and infrastructures.

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Computational Cognitive Modeling and Linguistic Theory

This book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science.

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Combinatorial Image Analysis ; Vol.4040 : 11th International Workshop, IWCIA 2006, Berlin, Germany, June 19-21, 2006, Proceedings

Constitutes the refereed proceedings of the 11th International Workshop on Combinatorial Image Analysis, IWCIA 2006, held in Berlin, June 2006. The book presents 34 revised full papers together with two invited papers, covering topics including combinatorial image analysis; grammars and models for analysis and recognition of scenes and images; combinatorial topology and geometry for images; digital geometry of curves and surfaces; algebraic approaches to image processing, and more.

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Manufacturing Systems Control Design : A Matrix-based Approach

The matrix-based approach presented here is a solution to the real-time application of control in discrete event systems and flexible manufacturing systems (FMS), and offers a sound practical basis for the design of controllers for manufacturing systems.

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Manufacturing Execution Systems - MES

The production plants of today develop into modern service centers. Economic efficiency of modern added value is not a property of products alone but of the process. Decisive potential in business now is a question of process capability, rather than production capability. Process capability in business requires real-time systems for optimization. Business-IT needs to be developed from telecommunications and ERP to real time services, which are not offered by the prevailing ERP systems. Today, only modern Manufacturing Execution Systems (MES) offer real-time applications. They generate current as well as historic mappings of production facilities and thus they can be used as basis for optimizations. It is important to map the supply chain in real time. Increasing complexity in production requires an integrated view of the production and service facilities: detailed scheduling, status collection, quality, performance analysis, tracing of material and so on have to be recorded and displayed in an integrated way.

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Managing Agile Business Technology : The Business and Technology Relationship Model in Practice

Describes in detail how the BTRM, combined with a focus on value creation and value delivery, will enable continuous change, in the context of current, emerging and future technologies. It illustrates the potential for real-time insight and control not previously considered and provides a wide range of information to plan an implementation, understand where AI can be applied, and its importance in the world of self-managing systems.

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Management of Converged Multimedia Networks and Services ; 11th IFIP/IEEE International Conference on Management of Multimedia and Mobile Networks and Services, MMNS 2008, Samos Island, Greece, September 22-26, 2008. Proceedings

This volume presents the proceedings of the 11th IFIP/IEEE International Conference on Management of Multimedia and Mobile Networks and Services (MMNS 2008), which was held on Samos, Greece during September 22–26 as part of the 4th International Week on Management of Networks and Services (Manweek 2008). As in the previous three years, the Manweek umbrella - lowed an international audience of researchers and scientists from industry and academia – who are researching and developing management systems – to share views and ideas and present their state-of-the-art results. The other events co-located with Manweek 2008 were the 19th IFIP/IEEE International Workshop on Distributed Systems.

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Machine learning in healthcare : Fundamentals and recent applications

Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.

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