Page 3
Page 3
Artificial Intelligence and COVID Effect on Accounting
This book considers the effects of COVID-19 on accounting, particularly with regard to the role of artificial intelligence in accounting in the post-pandemic business environment. The contributions in the book consider a variety of sectors that have been affected by the pandemic, such as the stock market, forensic accounting, Bitcoin, as well as the economic and educational responses to the pandemic and the aftermath felt by both developing and developed countries.
Architecting dependable systems IV
As software systems become ubiquitous, the issues of dependability become more and more crucial. Given that solutions to these issues must be considered from the very beginning of the design process, it is reasonable that dependability is addressed at the architectural level. It also contains sections on architectural description languages, architectural components and patterns, architecting distributed systems, and architectural assurances for dependability.
Architecting dependable systems III
As software systems become ubiquitous, the issues of dependability become more and more crucial. Given that solutions to these issues must be considered from the very beginning of the design process, it is reasonable that dependability is addressed at the architectural level. This book comes as a result of an effort to bring together the research communities of software architectures and dependability. The papers are organised in topical sections on architectures for dependable services, monitoring and reconfiguration in software architectures, dependability support for software architectures, architectural evaluation, and architectural abstractions for dependability
Applications of artificial intelligence in business, education and healthcare
Highlights the opportunities and challenges of artificial intelligence in business, education, and healthcare from institutional, environmental, social perspectives Includes empirical and theoretical research Presents applications of Artificial Intelligence in Business, Education and Healthcare
Analyse asymptotique et couche limite = Asymptotic analysis and boundary layer
The aim of the book is to give teachers and students (from Bac + 4) in applied mathematics and fluid mechanics a teaching and learning tool illustrated by fifty problems accompanied by their detailed correction. This book presents a new method of asymptotic analysis for "boundary layer" problems. This is called MASC "Method of Complementary Successive Approximations". The first half of the book is devoted, in addition to the presentation of the MASC, to organize the knowledge necessary for the asymptotic analysis and to give the keys allowing the understanding of what is a problem called "boundary layer" and the methods allowing. to build an approximation. The second part is devoted to the application of MASC in fluid mechanics and to the comparison with the more traditional methods resulting from the famous MDAR, "Method of Connected Asymptotic Developments".
Advances in Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry ; International Conference, MDA 2006/2007, Leipzig, Germany, July 18, 2007, Selected Papers
The automatic analysis of images and signals in medicine, biotechnology, and chemistry is a challenging and demanding field. Signal-producing procedures by microscopes, spectrometers, and other sensors have found their way into wide fields of medicine, biotechnology, economy, and environmental analysis. With this arises the problem of the automatic mass analysis of signal information. Signal-interpreting systems which generate automatically the desired target statements from the signals are therefore of compelling necessity. The continuation of mass analyses on the basis of classical procedures leads to investments of proportions that are not feasible. New procedures and system architectures are therefore required. The goals of this: Provide a forum for identifying important contributions and opportunities for research on mass data analysis on microscopic images Promote the systematic study of how to apply automatic image analysis and interpretation procedures to that field Show case applications of mass data analysis in biology, medicine, and chemistry Topics of interest include (but are not limited to): Techniques and developments of signal and image producing procedures Object matching and object tracking in microscopic and video microscopic images 1D, 2D, and 3D shape analysis and description
Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry ; 3rd International Conference, MDA 2008 Leipzig, Germany, July 14, 2008 Proceedings
Presents the broad and growing scientific evidence linking mass data analysis with challenging problems in medicine, biotechnology and chemistry.
Advanced Fuzzy Logic Technologies in Industrial Applications
Addresses the problem by introducing a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The tuning process is a major focus in this volume because it is the most difficult stage in fuzzy control application. Using new methods such as µ-law technique, histogram equalization and the Bezier-based method, all detailed here, the tuning process can be significantly simplified and control performance improved. The other great strength of this book lies in the range and contemporaneity of its applications and examples which include: laser tracking and control; robot calibration; image processing and pattern recognition; medical engineering; audio systems; autonomous underwater vehicles and data mining.
A Study about Prevalence of Thalassemia Complications in Syrian Patients
Inherited haemoglobin disorders, including thalassemia and sickle-cell disease, are the most common monogenic diseases worldwide. Several clinical forms of α-thalassemia and β-thalassemia, including the co-inheritance of β-thalassemia with haemoglobin E resulting in haemoglobin E/β-thalassemia, have been described. The disease hallmarks include imbalance in the α/β-globin chain ratio, ineffective erythropoiesis, chronic hemolytic anemia, compensatory hemopoietin expansion, hypercoagulability, and increased intestinal iron absorption. The complications of iron overload, arising from transfusions that represent the basis of disease management in most patients with severe thalassemia. The mature Hb molecule is a tetramer composed of 2 a-globin and 2 b-globin polypeptides, which assemble, along with a heme prosthetic group, to form the complete molecule.
A healthcare professionals training system
The Objective Structured Clinical Examination (OSCE) is a type of examination often used in health sciences. It is designed to test clinical skill performance and competence in a range of skills. It is a practical, real-world approach to learning and assessment. Comprises a circuit of short (5-10 minutes) stations, in which each candidate is examined on a one-to-one basis with one or two impartial examiner(s) and patients who are either real or simulated (actors or electronic patient simulators). Each station has a different examiner; in comparison, the traditional method of clinical examination is when a candidate is assigned to an examiner for the entire examination.
3D Segmentation for medical images (OsteoVision) = التقطيع ثلاثي الأبعاد للصور الطبية
With the increasing integration of AI across various sectors, artificial intelligence (AI) is already playing a significant role in the healthcare industry, and its use is expected to grow further. AI systems used in image processing and computer vision algorithms have shown a significant ability to perform many operations such as segmentation, classification, and detection. This project presents the application of computer vision algorithms in the field of medical imaging for diagnostic, therapeutic, and interventional purposes. This thesis explores the use of several computer vision algorithms to address different pathologies, specifically brain tumors (glioma) (see Appendix A) and knee osteoarthritis (OA), as well as tracking the progression of knee osteoarthritis using the Kellgren and Lawrence (KL) grading system, a common method for classifying the severity of OA into five grades. To achieve the desired impact, the project employs various techniques, including 3D segmentation for brain tumors, 2D segmentation for knee joints, and multinomial classification for determining the severity of knee OA injuries. The primary aims of the project are to enhance diagnostic accuracy, assist in creating treatment plans, provide an assistive tool for healthcare providers to make more informed decisions, leverage AI's capabilities to detect abnormalities that might escape the human eye, and streamline workflow. To facilitate these goals, the project incorporates a user-friendly UI, a website, and a Flutter-based mobile application, enabling healthcare providers to efficiently integrate these tools into their practice and improve patient care.
