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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Neural Networks - ISNN 2025: 19th International Symposium on Neural Networks, Zhangye, China, August 22-24, 2025, Proceedings
by Long Jin, Lidan Wang
English | 2026 | ISBN: 9819512328 | 603 Pages | True PDF | 72 MB

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Networks, Intelligence and Computing
English | 2024 | ISBN: 1032553871 | 845 Pages | EPUB | 92 MB
The year 2023 marks the 100th birth anniversary of E.F. Codd (19 August 1923 - 18 April 2003), a computer scientist, who while working for IBM invented the relational model for database management, the theoretical basis for relational databases and relational database management systems. He made other valu□able contributions to computer science but the relational model, a very influential general theory of data management, remains his most mentioned, analyzed, and celebrated achievement. School of Computer Application, under the aegis of Lovely Professional University, pays homage to this great scientist of all times by hosting "CODD100 - International Conference on Networks, Intelligence and Computing (ICONIC-2023)".

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Mechanical Engineering and Material Sciences
English | 2026 | ISBN: 1041209673 | 398 Pages | PDF EPUB (True) | 92 MB
The International Conference on Advances in Mechanical Engineering and Material Sciences (ICAMEMS-2025) was organized by the Department of Mechanical Engineering, Department of Physics and Department of Chemistry, Vidyavardhaka College of Engineering, Mysuru from 10th to 11th March 2025 at Department of Mechanical Engineering, Vidyavardhaka College of Engineering, Mysuru. ICAMEMS 2025 served as a multidisciplinary platform for researchers, academicians, industry experts, and students to present and discuss the latest innovations, challenges, and opportunities in the fields of mechanical engineering and material sciences. The conference aimed to promote collaboration and knowledge exchange by covering a wide range of topics including thermal and fluid engineering, manufacturing technologies, industrial design, quality engineering, advanced materials, engineering chemistry, and applied physics.

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Machine Learning
English | 2018 | ISBN: 1773610678 | 408 Pages | PDF (True) | 24 MB
Recently, a new field of computer science was derived, including methods and techniques of problem solving that cannot be easily described by traditional algorithms. This field, called ""cognitive computing"" or ""real-world computing"", has a varied set of working methodologies, such as: fuzzy logic, approximate reasoning, genetic algorithms, chaos theory, and the Artificial Neural Networks (ANN). The objective of the present work is to introduce the problematic of the latter: definitions, principles and typology, as well as concrete applications in the field of information retrieval.

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Healthcare using Machine Learning: Volume 1
English | 2026 | ISBN: 1032853484 | 265 Pages | PDF EPUB (True) | 32 MB
The rapid technological advancements in the healthcare industry over recent decades have been transformative. These innovations have not only enhanced our understanding of the morphology and physiology of various organs but have also significantly improved the early diagnosis and treatment of numerous diseases across different medical specialties. This progress has been largely driven by advancements in artificial intelligence (AI) and computer vision (CV). AI and CV enable the real-time collection, processing, interpretation, and analysis of vast amounts of static and dynamic medical data, revolutionizing disease characterization and patient selection. Early detection is crucial in treating life-threatening illnesses such as COVID-19, pneumonia, and cancer. Computer-based medical imaging techniques, including CT scans and X-rays, play a vital role in diagnosing these conditions. Similarly, biological signals like electroencephalography (EEG) and electrocardiography (ECG) help anticipate brain anomalies and heart diseases. Machine learning further enhances the accuracy of disease prediction, assisting clinicians in making precise diagnoses. By facilitating faster disease recognition, these technologies also enable wider access to healthcare, including remote and underserved areas. This book aims to develop machine learning algorithms that analyze diverse medical data and predict diseases based on their characteristics, ultimately advancing healthcare diagnostics and treatment strategies.

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Healthcare Using Machine Learning: Volume 2
English | 2026 | ISBN: 104114542X | 308 Pages | PDF EPUB (True) | 43 MB
The technological advancements made in recent decades have not only helped us better comprehend the morphology and physiology of the organs of the human body, but they have also advanced the diagnosis and, therefore, the treatment of a number of diseases in a variety of medical specialties from very early stages. Artificial Intelligence (AI) and Computer Vision (CV) enable us to collect, process, interpret, and analyze a limitless quantity of static and dynamic medical data in real time, which improve the way each disease is characterized and the patients are chosen. Many potentially fatal illnesses, such as COVID-19, pneumonia, and cancer, can be cured if diagnosed in initial stages very early on. Computer-based medical imaging techniques, such as CT scan and X-rays are useful in detecting all of these illnesses. On the other hand, various brain anomalies and heart diseases can also be anticipated using biological signals, like electroencephalography (EEG), electrocardiogram (ECG) etc. The application of machine learning makes the predictions more accurate and help the clinician to detect appropriate one. This helps in faster recognition of disease as well as with the intervention of the technology, makes it feasible to spread to the remote places. The goal of the book is to create machine learning algorithms that aids in the analysis of diverse medical data and the prediction of diseases based on the characteristics of the data.

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Grid Computing
English | 2023 | ISBN: 1682519449 | 306 Pages | PDF (True) | 12 MB
Grid computing has been the subject of many large national and international IT projects. However, not all goals of these projects have been achieved. In particular, the number of users lags behind the initial forecasts laid out by proponents of grid technologies. Grid computing is the technology for sharing distributed resources at a large-scale, which is accomplished in a transparent and location-independent way. It allows users to effortlessly take advantage of the vast computational resources available on the grid by simply plugging applications into it. Grid-enabled applications are specific software applications that can utilize grid infrastructure. The availability of powerful computers and high-speed computer networks such as the Internet is changing the way computing is done. These new technologies have led to all kinds of computing such as parallel computing, distributed computing, cloud computing, utility computing, cluster computing, mobile computing, and grid computing. The term "grid computing" was first used in the early 1990s as a metaphor for making computer power as easy to access as an electric power grid. It was first established in the early 1990s by Carl Kesselman, Ian Foster and Steve Tuecke, who are widely regarded as the "fathers of the grid." Grid computing was inspired by the electrical power grid. It involves computation in a distributed manner. Grid technologies leverage the computational power of the available computers by managing them in the grid infrastructure. Grid or distributed computing is a special type of parallel computing that relies on complete computers connected to a computer network.

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Functional Analysis and Operator Theory: AMS-EMS-SMF Special Session on Advances in Functional Analysis and Operator Theory, July 18-22, 2022, Université de Grenoble-Alpes, Grenoble, France
by Marat V. Markin, Igor V. Nikolaev
English | 2024 | ISBN: 1470473054 | 250 Pages | True PDF | 2 MB

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Economics and Econometrics: Volume 1: Twelfth World Congress
English | 2025 | ISBN: 1009531328 | 471 Pages | PDF | 5 MB
Every five years, the World Congress of the Econometric Society brings together scholars from around the world. Leading scholars present state-of-the-art overviews of their areas of research, offering newcomers access to key research in economics. Advances in Economics and Econometrics: Twelfth World Congress consist of papers and commentaries presented at the Twelfth World Congress of the Econometric Society. This two-volume set includes surveys and interpretations of key developments in economics and econometrics, and discussion of future directions for a variety of topics, covering both theory and application. The first volume addresses such topics as contract theory, industrial organization, health and human capital, as well as racial justice, while the second volume includes theoretical and applied papers on climate change, time series econometrics, and causal inference. These papers are invaluable for experienced economists seeking to broaden their knowledge or young economists new to the field.

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  Author: creativelivenew1   |   04 January 2026   |   Comments icon: 0

Free Download Advances in Deep Generative Models for Healthcare and Medical Applications
English | 2026 | ISBN: 1032988959 | 283 Pages | PDF EPUB (True) | 26 MB
This book provides a platform for research on deep generative models, with an emphasis on its healthcare applications. The book addresses the unanswered questions that stop these approaches from making a huge difference in real-world clinical practice. The goal of this book is to bring together a wide range of methodologies which are using generative models in health care-related contexts. The book leverages the recent methodological advancements in deep generative models to address critical health-care challenges across all data-types, paving the way for their practical integration into the healthcare system and elevate their impact on the future of healthcare.

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