الصفحة 1
الصفحة 1
Nonlinear kalman filtering for force-controlled robot tasks
This monograph focuses on how to achieve more robot autonomy by means of reliable processing skills. "Nonlinear Kalman Filtering for Force-Controlled Robot Tasks " discusses the latest developments in the areas of contact modeling, nonlinear parameter estimation and task plan optimization for improved estimation accuracy.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
IOT control and surveillance system
An automated system is a combination of both software and hardware which is designed and programmed to work automatically without the need of any human operator to provide inputs and instructions for each operation. The Internet of Things (IoT) is a network of connected things. These ‘things’ (devices) communicate with each other using machine to machine communication (M2M). Information is traversed between devices so that processes can be automated, without the need for human intervention. By reducing the number of people involved in a business process, several advantages arise, including improved accuracy and up-time. We will build an IoT automated system to control access of humans and vehicles to a warehouse based on biometrics and image recognition techniques.
Internet of things, artificial intelligence and blockchain technology
Explores the concepts and techniques of IoT, AI, and blockchain. Also discussed is the possibility of applying blockchain for providing security in various domains. The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems. Explains how blockchain can significantly increase data privacy and security while boosting accuracy and integrity in IoT generated data and AI processed information; Gives insight into blockchain’s numerous potential applications, starting with recent technologies that give users control over sharing and privacy; Shows readers how to employ blockchain in IoT and AI, helping them to understand what they can and cannot do with blockchain.
Intelligent engineering systems and computational cybernetics
A further important component of machine intelligence is a kind of “structural uniformity” giving room and possibility to model arbitrary particular details a priori not specified and unknown.This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This “learning ability” is a key element of machine intelligence.The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing.
Intelleger = انتليجر
The project management system is a web application designed to assist software managers in efficiently managing their projects, including websites, mobile apps, and other software initiatives. Utilizing artificial intelligence, the application streamlines project creation and management processes, offering significant benefits in terms of organization and accuracy. Managers can create projects by inputting essential details such as the name, scope, deadline, and tasks. The system generates AI-based functional and non-functional requirements tailored to the project scope using gpt2 model on Pure dataset. Managers can then review and edit these requirements as needed before finalizing the project. The application facilitates comprehensive task management by allowing managers to assign tasks to developers, edit task details, and ensure task deadlines align with project deadlines. Developers can log their start and end times automatically when they begin and complete tasks, providing accurate time tracking and performance analysis.also they can use code generation model to generate their task’s code using codebert model on concode and codesearchnet dataset Real-time notifications keep both managers and developers informed of task assignments, completions, and other critical updates.
Implementation and application of functional languages ; 18th International Symposium, IFL 2006, Budapest, Hungary, September 4-6, 2006, Revised Selected Papers
This volume constitutes the post-proceedings of the 18th International Workshop on Implementation and Applications of Functional Languages. Each one was submitted to two rounds of reviews to ensure accuracy, thoroughness, and readability. The papers address all current theoretical and methodological issues in functional and function-based languages.
Identification of nonlinear systems using neural networks and polynomial models : A block-oriented approach
The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models".
High accuracy detection of mobile malware using machine learning
As increasingly sophisticated and evasive malware attacks continue to emerge, more effective detection solutions to tackle the problem are being sought through the application of advanced machine learning techniques. This reprint presents several advances in the field including: a new method of generating adversarial samples through byte sequence feature extraction using deep learning; a state-of-the-art comparative evaluation of deep learning approaches for mobile botnet detection; a novel visualization-based approach that utilizes images for Android botnet detection; a study on the detection of drive-by exploits in images using deep learning; etc. Furthermore, this reprint presents state-of-the-art reviews about machine learning-based detection techniques that will increase researchers' knowledge in the field and enable them to identify future research and development directions.
Handbook of Fractional Calculus for Engineering and Science
Provides reliable methods for solving fractional-order models in science and engineering. Contains efficient numerical methods and algorithms for engineering-related equations. Contains comparison of various methods for accuracy and validity. Demonstrates the applicability of fractional calculus in science and engineering. Examines qualitative as well as quantitative properties of solutions of various types of science- and engineering-related equations.
Geometric Properties for Incomplete Data
Computer vision and image analysis require interdisciplinary collaboration between mathematics and engineering. This book addresses the area of high-accuracy measurements of length, curvature, motion parameters and other geometrical quantities from acquired image data. It is a common problem that these measurements are incomplete or noisy, such that considerable efforts are necessary to regularise the data, to fill in missing information, and to judge the accuracy and reliability of these results. This monograph brings together contributions from researchers in computer vision, engineering and mathematics who are working in this area.
Fundamentals of manufacturing engineering using digital visualization
Offers a guide to core principles and practices of manufacturing engineering. It covers the design of, together with technological and measurement issues for, technical systems. Locating charts and setup schemes describing different machining processes are included. Concepts of product quality, with a focus on accuracy indicators, machining accuracy, roughness, and the impact of surface quality on exploitation properties are also explained. Furthermore, key machining methods, including turning, milling, hole machining, grinding, and gear machining, are analyzed in depth, covering their principles, applications, and techniques. The book is enriched by QR codes, linking to a mobile application presenting additional information about the content, for an interactive and extended learning experience. It also uses illustrations visualized with digital tools to promote a better understanding of the concepts.
FitBuddy : An artificial intelligence powered personal trainer
FitBuddy App is a sports application that employs artificial intelligence in its job as a personal trainer that enables users to exercise anywhere with convenience, tremendous benefit, and high accuracy. The user can exercise with or without weights, in addition to cycling and running. The user must first provide the application with the personal data it has asked for in order to create an appropriate sports program for the user. After that, the user may explore the sports program's weeks and day's sections.
Enhanced Living Environments : Algorithms, Architectures, Platforms, and Systems
Ambient Assisted Living (AAL) is an area of research based on Information and Communication Technologies (ICT), medical research, and sociological research. AAL is based on the notion that technology and science can provide improvements in the quality of life for people in their homes, and that it can reduce the financial burden on the budgets of the healthcare providers. The concept of Enhanced Living Environments (ELE) refers to the AAL area that is more related with ICT. Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science in this area and the development of new and innovative solutions. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area.
Elevating video content creation with ai assistance = ارتقاء إنشاء محتوى الفيديو بمساعدة الذكاء الاصطناعي
We developed an AI Assistant equipped with features such as description crafting, title generation, keyword extraction, image captioning, clickbait detection, and sentiment analysis.To achieve these functionalities, we proposed a model for generating video descriptions using ResNet50 as a feature extractor and a LSTM network with an attention mechanism as a sequence generator, achieving a BLEU-1 score of 0.907 and a ROUGE-L score of 0.645. For keyword extraction, we utilized Sentence Transformer to identify strategically relevant keywords from the generated descriptions. For title generation, we fine-tuned the BART model, achieving a ROUGE-L score of 0.45. For clickbait detection, we used SVC classifier with linear kernel and TF-IDF vectorization for feature extraction, resulting in 96% accuracy. Our sentiment analysis model using a CNN-LSTM architecture achieved 80% accuracy in analyzing comments on videos. For image captioning, we employed a feature extractor with a CNN layer followed by an LSTM model, achieving a BLEU-1 score of 0.53. Our platform empowers creators by simplifying complex tasks and offering deeper audience engagement insights, making it a powerful tool in the evolving digital content creation.
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%.
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.
Computer Vision Metrics : Survey, Taxonomy, and Analysis
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more.
Computational Science -- ICCS 2005 ; Vol. 3516 ; 5th International Conference, Atlanta, GA, USA, May 22-25, 2005, Proceedings, Part III
This book constitutes the refereed proceedings of the Fifth International Conference on Computational Science (ICCS 2005) held in Atlanta, Georgia, USA, 2005, Computational science is rapidly maturing as a mainstream discipline. It is central to an ever-expanding variety of ?elds in which computational methods and tools enable new discoveries with greater accuracy and speed. The primary objectives of this conference were to discuss problems and solutions in allareas,toidentifynewissues,toshapefuturedirectionsofresearch,andtohelp users apply various advanced computational techniques. The event highlighted recent developments in algorithms, computational kernels, next generation c- puting systems, tools, advanced numerical methods, data-driven systems, and emerging application ?elds, such as complex systems, ?nance, bioinformatics, computational aspects of wireless and mobile networks, graphics, and hybrid computation.
Computational Science -- ICCS 2005 ; Vol. 3515 ; 5th International Conference, Atlanta, GA, USA, May 22-25, 2005, Proceedings, Part I
This book constitutes the refereed proceedings of the Fifth International Conference on Computational Science (ICCS 2005) held in Atlanta, Georgia, USA, 2005, Computational science is rapidly maturing as a mainstream discipline. It is central to an ever-expanding variety of ?elds in which computational methods and tools enable new discoveries with greater accuracy and speed. The primary objectives of this conference were to discuss problems and solutions in allareas,toidentifynewissues,toshapefuturedirectionsofresearch,andtohelp users apply various advanced computational techniques. The event highlighted recent developments in algorithms, computational kernels, next generation c- puting systems, tools, advanced numerical methods, data-driven systems, and emerging application ?elds, such as complex systems, ?nance, bioinformatics, computational aspects of wireless and mobile networks, graphics, and hybrid computation.
