الصفحة 7
الصفحة 7
Digital Human Modeling : Trends in Human Algorithms
The emerging information technologies have given rise to new human patterns in terms of both physiological and psychological interactions. Human Algorithms aim to model human forms, interactions, and dynamics in this new context.
DevOps Tools for Java Developers : Best Practices from Source Code to Production Containers
Explore software lifecycle best practices Use DevSecOps methodologies to facilitate software development and delivery Understand the business value of DevSecOps best practices Manage and secure software dependencies Develop and deploy applications using containers and cloud native technologies Manage and administrate source control repositories and development processes Use automation to set up and administer build pipelines Identify common deployment patterns and antipatterns Maintain and monitor software after deployment
Detection of intrusions and malware, and vulnerability assessment ; 3rd International Conference, DIMVA 2006, Berlin, Germany, July 13-14, 2006, Proceedings
This book constitutes the refereed proceedings of the Third International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2006, held in Berlin, Germany in July 2006.The 11 revised full papers presented were carefully reviewed and selected from 41 submissions.
Design Patterns in Modern C++20 : Reusable Approaches for Object-Oriented Software Design
As well as covering traditional design patterns, this book fleshes out new design patterns and approaches that will be useful to modern C++ developers. Author Dmitri Nesteruk presents concepts as a fun investigation of how problems can be solved in different ways, along the way using varying degrees of technical sophistication and explaining different sorts of trade-offs. You will: Use creational patterns such as builder, factories, prototype and singleton / Implement structural patterns such as adapter, bridge, decorator, facade and more / Work with the behavioral patterns such as chain of responsibility, command, iterator, mediator and more / Apply functional design patterns such as the Maybe Monad
Design and implementation of an array of patch antenna
Wireless technology is one of the main areas of research in global communication systems today and the study of communication systems is incomplete without an understanding of the process and manufacture of antennas. This was the main reason for choosing this project to focus on this area. This paper presents the design and implementation of an antenna array consisting of 4 patch antenna elements that work on 2.4GHz frequency,the substrate FR4, It was analyzed using HFSS (High Frequency Simulator Structure). In order to achieve a gain of 7 db, and a reflection coefficient of s11 of -10db Then the board was printed And he made measurements in the laboratory on the spectrum analyzer and the kit for the antennas As a result of the measurements, we obtained the antenna gain, the antenna radiation pattern, and the s11
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics : Techniques and Applications
Examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever.
Deep learning methods for converting speech to text = تقنيات التعلم العميق في تحويل الصوت إلى نص
Aims to design and develop a system capable of extracting audio content from films and audio recordings and converting it into text using deep learning techniques. This is done by analyzing audio patterns, extracting sounds and words from the video, and then converting them into written text. Deep learning, a branch of artificial intelligence, is used to accomplish this task. The study also includes comparing different deep learning techniques to determine their effectiveness in this context.
Database systems for advanced applications ; Vol. 3453 ; 10th international conference, DASFAA 2005, Beijing, China, April 17-20, 2005, Proceedings
Data Stream Mining and Resource Adaptive Computation.- Purpose Based Access Control for Privacy Protection in Database Systems.- Complex Networks and Network Data Mining.- Bioinformatics.- Indexing DNA Sequences Using q-Grams.- PADS: Protein Structure Alignment Using Directional Shape Signatures.- LinkageTracker: A Discriminative Pattern Tracking Approach to Linkage Disequilibrium Mapping.- Watermarking and Encryption.- Query Optimization in Encrypted Database Systems.- Watermarking Spatial Trajectory Database.- Effective Approaches for Watermarking XML Data.- XML Query Processing.- A Unifying Framework for Merging and Evaluating XML Information.- Efficient Evaluation of Partial Match Queries for XML Documents Using Information Retrieval Techniques.- PathStack: A Holistic Path Join Algorithm for Path Query with Not-Predicates on XML Data.- XML Coding and Metadata Management.- An Improved Prefix Labeling Scheme: A Binary String Approach for Dynamic Ordered XML.- Efficiently Coding and Indexing XML Document.- XQuery-Based TV-Anytime Metadata Management.- Data Mining.- Effective Database Transformation and Efficient Support Computation for Mining Sequential Patterns.
Data Warehousing and Knowledge Discovery ; Vol.4081 ; 8th International Conference, DaWaK 2006, Krakow, Poland, September 4-8, 2006, Proceedings
DaWaK aimed at providing the right and logical balance between data warehousing and knowledge discovery. In data warehousing the papers cover different research problems, such as advanced techniques in OLAP visuali- tion and multidimensional modelling, innovation of ETL processes and integration problems, materialized view optimization, very large data warehouse processing, data warehouses and data mining applications integration, data warehousing for real-life applications, e. g. , medical applications and spatial applications. In data mining and knowledge discovery, papers are focused on a variety of topics from data streams analysis and mining, ontology-based mining techniques, mining frequent item sets, clustering, association and classification, patterns and so on.
Data Streams : Models and Algorithms
It primarily discusses issues related to the mining aspects of data streams rather than the database management aspect of streams. This volume covers mining aspects of data streams in a comprehensive style. Each contributed chapter, from a variety of well known researchers in the data mining field, contains a survey on the topic, the key ideas in the field from that particular topic, and future research directions.
Data science and analytics ; 5th International conference on recent developments in science, engineering and technology, REDSET 2019, Gurugram, India, November 15–16, 2019, Revised Selected Papers, Part I
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.
Data mining with computational intelligence
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Data Mining for Biomedical Applications ; PAKDD 2006 Workshop, BioDM 2006, Singapore, April 9, 2006, Proceedings
This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with 1 keynote talks were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on protein-protein interactions, database and search, bio data clustering, and in-silico diagnosis.
Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques
This book will give the reader a perspective into the core theory and practice of data mining and knowledge discovery (DM&KD). Its chapters combine many theoretical foundations for various DM&KD methods, and they present a rich array of examples—many of which are drawn from real-life applications. Most of the theoretical developments discussed are accompanied by an extensive empirical analysis, which should give the reader both a deep theoretical and practical insight into the subjects covered.
Data Mining : Theory, Methodology, Techniques, and Applications
This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums.
Data Complexity in Pattern Recognition
Data Complexity in Pattern Recognition is unique in its comprehensive coverage and multidisciplinary approach from various methodological and practical perspectives. Researchers and practitioners alike will find this book an insightful reference to learn about the current status of available techniques as well as application areas.
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
Coordination models and languages ; Vol.4038 ; 8th International Conference, COORDINATION 2006, Bologna, Italy, June 14-16, 2006, Proceedings
This book constitutes the refereed proceedings of the 8th International Conference on Coordination Models and Languages, COORDINATION 2006, held in Bologna, Italy, June 2006. The 17 revised full papers presented were carefully reviewed and selected from 50 submissions. Among the topics addressed are component connectors, negotiation in service-oriented computing, process algebraic specification, workflow patterns, reactive XML, ubiquitous coordination, type systems, ad-hoc network coordination, choreography, communication coordination, and distributed embedded systems.
Constraint-Based Mining and Inductive Databases ; European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers
The interconnected ideas of inductive databases and constraint-based mining are appealing and have the potential to radically change the theory and practice of data mining and knowledge discovery.
