Data Mining at IgMin Research | Engineering Group

Pneumonia is described as an acute infection of lung tissue produced by one or more bacteria, and Coronavirus Disease (COVID-19) is a deadly virus that affects the lungs of the human body. The symptoms of COVID-19 disease are closely related to pneumonia. In this work, we identify the patients of pneumonia and coronavirus from chest X-ray images. We used a convolutional neural network for spatial feature learning from X-ray images. We experimented with pneumonia and coronavirus X-ray images in the Kaggle dataset. Pneumonia and corona patients a...re classified using a feed-forward neural network and hybrid models (CNN+SVM, CNN+RF, and CNN+Xgboost). The experimental findings on the Pneumonia dataset demonstrate that CNN detects Pneumonia patients with 99.47% recall. The overall experiments on COVID-19 x-ray images show that CNN detected the COVID-19 and pneumonia with 95.45% accuracy.Read more

Energy Valley Optimizer (EVO) is one of the recent metaheuristic algorithms. It draws inspiration from advanced principles in physics related to particle stability and decay modes. This paper presents a new Energy Valley Optimizer (EVO) and levy flights that are hybrid to improve the EVO in solving optimization problems. Levy flight is one of the most important randomization techniques. Fifteen mathematical test functions (five unimodal functions, four multimodal functions, and six composite functions) are solved with the proposed algorithm. We... also compare our results with previous results of metaheuristic algorithms. The statistical results show that the results of the Levy Energy Valley Optimizer (LEVO) outperform other algorithms in almost all mathematical test functions.Read more

The rapid development of wearable technology provides new opportunities for action data processing and classification techniques. Wearable sensors can monitor the physiological and motion signals of the human body in real-time, providing rich data sources for health monitoring, sports analysis, and human-computer interaction. This paper provides a comprehensive review of motion data processing and classification techniques based on wearable sensors, mainly including feature extraction techniques, classification techniques, and future developmen...t and challenges. First, this paper introduces the research background of wearable sensors, emphasizing their important applications in health monitoring, sports analysis, and human-computer interaction. Then, it elaborates on the work content of action data processing and classification techniques, including feature extraction, model construction, and activity recognition. In feature extraction techniques, this paper focuses on the content of shallow feature extraction and deep feature extraction; in classification techniques, it mainly studies traditional machine learning models and deep learning models. Finally, this paper points out the current challenges and prospects for future research directions. Through in-depth discussions of feature extraction techniques and classification techniques for sensor time series data in wearable technology, this paper helps promote the application and development of wearable technology in health monitoring, sports analysis, and human-computer interaction.Index Terms: Activity recognition, Wearable sensor, Feature extraction, ClassificationRead more

The currently existing Russian and other legislation, as well as special literature, do not contain a methodology for the formation of the business reputation of the organization’s personnel and as a result, there is no unambiguous perception of the business, professional qualities of personnel as an object of evaluation of the organization in the market system. Therefore, it is impossible to single out the share of the results of intellectual advantage in the goods and services produced. This confirms the requirements formulated in para...graph 4 of Accounting Regulation 14/2007 «Accounting for intangible assets», which states that the intellectual and business qualities of the organization’s personnel, their qualifications, and their ability to work are not included in the intangible assets (since they are inseparable from their carriers and cannot be used without them). Meanwhile, the interests of the leading economically developed countries of the world lie in the field of accelerated growth of knowledge acquisition and application of professional skills. This trend of development of economically developed countries forms the basis of competitiveness and efficiency of their work. It should be noted that in the world economy, there is insufficient theoretical elaboration and a special practical significance and relevance of the issue of assessing the business reputation of the personnel of an economic entity. The article presents a comprehensive methodology for evaluating the performance of industrial and production personnel (the standard-production methodology), which contributes to the formation of accounting and information support for the analysis of the activities of both structural divisions, responsibility centers, business segments and commercial organizations as a whole. The author’s standard-production methodology makes it possible to determine the business reputation of industrial and production personnel, which contradicts the official economic paradigm.Read more