Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska最新文献_第5页

ADVERTISING BIDDING OPTIMIZATION BY TARGETING BASED ON SELF-LEARNING DATABASE 基于自学习数据库的目标定位优化广告竞价

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5376

Roman Kvуetnyy, Yu. Bunyak, Olga Sofina, Oleksandr Kaduk, O. Mamyrbayev, Vladyslav Baklaiev, B. Yeraliyeva

引用次数: 0

AC POWER REGULATION TECHNIQUES FOR RENEWABLE ENERGY SOURCES 可再生能源交流电源调节技术

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5301

Mariusz Ostrowski

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BROWSERSPOT – A MULTIFUNCTIONAL TOOL FOR TESTING THE FRONT-END OF WEBSITES AND WEB APPLICATIONS browserspot - 用于测试网站和网络应用程序前端的多功能工具

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5374

Szymon Binek, Jakub Góral

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IMPROVEMENT OF THE ALGORITHM FOR SETTING THE CHARACTERISTICS OF INTERPOLATION MONOTONE CURVE 改进设置插值单调曲线特性的算法

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5392

Y. Kholodniak, Y. Havrylenko, S. Halko, V. Hnatushenko, O. Suprun, T. Volina, O. Miroshnyk, Taras Shchur

{"title":"IMPROVEMENT OF THE ALGORITHM FOR SETTING THE CHARACTERISTICS OF INTERPOLATION MONOTONE CURVE","authors":"Y. Kholodniak, Y. Havrylenko, S. Halko, V. Hnatushenko, O. Suprun, T. Volina, O. Miroshnyk, Taras Shchur","doi":"10.35784/iapgos.5392","DOIUrl":"https://doi.org/10.35784/iapgos.5392","url":null,"abstract":"Interpolation of a point series is a necessary step in solving such problems as building graphs de-scribing phenomena or processes, as well as modelling based on a set of reference points of the line frames defining the surface. To obtain an adequate model, the following conditions are imposed upon the interpolating curve: a minimum number of singular points (kinking points, inflection points or points of extreme curvature) and a regular curvature change along the curve. The aim of the work is to develop the algorithm for assigning characteristics (position of normals and curvature value) to the interpolating curve at reference points, at which the curve complies with the specified conditions. The characteristics of the curve are assigned within the area of their possible location. The possibilities of the proposed algorithm are investigated by interpolating the point series assigned to the branches of the parabola. In solving the test example, deviations of the normals and curvature radii from the corresponding characteristics of the original curve have been determined. The values obtained confirm the correctness of the solutions proposed in the paper.","PeriodicalId":504633,"journal":{"name":"Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139169567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

USAGE OF ARTIFICIAL NEURAL NETWORKS IN THE DIAGNOSIS OF KNEE JOINT DISORDERS 人工神经网络在膝关节疾病诊断中的应用

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5380

Konrad Witkowski, Mikołaj Wieczorek

引用次数: 0

AI EMPOWERED DIAGNOSIS OF PEMPHIGUS: A MACHINE LEARNING APPROACH FOR AUTOMATED SKIN LESION DETECTION 天疱疮的人工智能诊断：自动皮肤病变检测的机器学习方法

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5366

Mamun Ahmed, Salma Binta Islam, Aftab Uddin Alif, Mirajul Islam, Sabrina Motin Saima

{"title":"AI EMPOWERED DIAGNOSIS OF PEMPHIGUS: A MACHINE LEARNING APPROACH FOR AUTOMATED SKIN LESION DETECTION","authors":"Mamun Ahmed, Salma Binta Islam, Aftab Uddin Alif, Mirajul Islam, Sabrina Motin Saima","doi":"10.35784/iapgos.5366","DOIUrl":"https://doi.org/10.35784/iapgos.5366","url":null,"abstract":"Pemphigus is a skin disease that can cause a serious damage to human skin. Pemphigus can result in other issues including painful patches and infected blisters, which can result in sepsis, weight loss, and starvation, all of which can be life-threatening, tooth decay and gum disease. Early prediction of Pemphigus may save us from fatal disease. Machine learning has the potential to offer a highly efficient approach for decision-making and precise forecasting. The healthcare sector is experiencing remarkable advancements through the utilization of machine learning techniques. Therefore, to identify Pemphigus using images, we suggested machine learning-based techniques. This proposed system uses a large dataset collected from various web sources to detect Pemphigus. Augmentation has been applied on our dataset using techniques such as zoom, flip, brightness, distortion, magnitude, height, width to enhance the breadth and variety of the dataset and improve model’s performance. Five popular machine learning algorithms has been employed to train and evaluate model, these are K-Nearest Neighbor (referred to as KNN), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), and Convolutional Neural Network (CNN). Our outcome indicate that the CNN based model outperformed the other algorithms by achieving accuracy of 93% whereas LR, KNN, RF and DT achieved accuracies of 78%, 70%, 85% and 75% respectively.","PeriodicalId":504633,"journal":{"name":"Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139169066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

COMPREHENSIVE MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR PARKINSON'S DISEASE CLASSIFICATION AND SEVERITY ASSESSMENT 用于帕金森病分类和严重程度评估的综合机器学习和深度学习方法

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska Pub Date : 2023-12-20 DOI: 10.35784/iapgos.5309

Oumaima Majdoubi, A. Benba, A. Hammouch

{"title":"COMPREHENSIVE MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR PARKINSON'S DISEASE CLASSIFICATION AND SEVERITY ASSESSMENT","authors":"Oumaima Majdoubi, A. Benba, A. Hammouch","doi":"10.35784/iapgos.5309","DOIUrl":"https://doi.org/10.35784/iapgos.5309","url":null,"abstract":"In this study, we aimed to adopt a comprehensive approach to categorize and assess the severity of Parkinson's disease by leveraging techniques from both machine learning and deep learning. We thoroughly evaluated the effectiveness of various models, including XGBoost, Random Forest, Multi-Layer Perceptron (MLP), and Recurrent Neural Network (RNN), utilizing classification metrics. We generated detailed reports to facilitate a comprehensive comparative analysis of these models. Notably, XGBoost demonstrated the highest precision at 97.4%. Additionally, we took a step further by developing a Gated Recurrent Unit (GRU) model with the purpose of combining predictions from alternative models. We assessed its ability to predict the severity of the ailment. To quantify the precision levels of the models in disease classification, we calculated severity percentages. Furthermore, we created a Receiver Operating Characteristic (ROC) curve for the GRU model, simplifying the evaluation of its capability to distinguish among various severity levels. This comprehensive approach contributes to a more accurate and detailed understanding of Parkinson's disease severity assessment.","PeriodicalId":504633,"journal":{"name":"Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139170245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0