Medical document classification is one of the important topics of text mining. Globalisation techniques play a major role in text classification. It is also known that globalisation techniques play an important role in text classification. Our aim in the study is to conduct a detailed analysis on two data sets with English and Turkish content by using medical text summaries of Turkish articles. These datasets consist of Turkish and English text summaries of the same articles. To observe how successful local feature selection methods in the field of text classification affect the classification performance on these two equivalent data sets by applying different globalisation techniques. The feature selection methods used are CHI2, MI, OR, WLLR. Globalisation techniques are SUM, AVG, MAX. Classifiers are MNB, DT, and SVM.
{"title":"Comparative Analysis of Globalisation Techniques for Medical Document Classification","authors":"B. Parlak, S. Aydemi̇r","doi":"10.55195/jscai.1216800","DOIUrl":"https://doi.org/10.55195/jscai.1216800","url":null,"abstract":"Medical document classification is one of the important topics of text mining. Globalisation techniques play a major role in text classification. It is also known that globalisation techniques play an important role in text classification. Our aim in the study is to conduct a detailed analysis on two data sets with English and Turkish content by using medical text summaries of Turkish articles. These datasets consist of Turkish and English text summaries of the same articles. To observe how successful local feature selection methods in the field of text classification affect the classification performance on these two equivalent data sets by applying different globalisation techniques. The feature selection methods used are CHI2, MI, OR, WLLR. Globalisation techniques are SUM, AVG, MAX. Classifiers are MNB, DT, and SVM.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"1 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89722698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the material. In material science, structure of the material is analyzed to understand that a material can provide certain standards, such as toughness and durability. Therefore, it is a great importance to make this measurement carefully and accurately. The segmentation approach, which is frequently used in image processing, aims to isolate objects in an image from the background. In this sense, the separation of particles from the background can be considered as a problem of the image processing. In image processing applications, there are different approaches used in segmentation such as histogram-based, clustering-based, region amplification, separation and merging. In this review, a comparative analysis was made by examining recent studies on particle size measurement.
{"title":"A Review on Measurement of Particle Sizes by Image Processing Techniques","authors":"Vahit Tongur, A. B. Batibay, Murat Karakoyun","doi":"10.55195/jscai.1218662","DOIUrl":"https://doi.org/10.55195/jscai.1218662","url":null,"abstract":"This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the material. In material science, structure of the material is analyzed to understand that a material can provide certain standards, such as toughness and durability. Therefore, it is a great importance to make this measurement carefully and accurately. The segmentation approach, which is frequently used in image processing, aims to isolate objects in an image from the background. In this sense, the separation of particles from the background can be considered as a problem of the image processing. In image processing applications, there are different approaches used in segmentation such as histogram-based, clustering-based, region amplification, separation and merging. In this review, a comparative analysis was made by examining recent studies on particle size measurement.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"9 10-11 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90373998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1007/978-3-031-23480-4
{"title":"Artificial Intelligence and Soft Computing: 21st International Conference, ICAISC 2022, Zakopane, Poland, June 19–23, 2022, Proceedings, Part II","authors":"","doi":"10.1007/978-3-031-23480-4","DOIUrl":"https://doi.org/10.1007/978-3-031-23480-4","url":null,"abstract":"","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"66 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89274927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1007/978-3-031-23492-7
{"title":"Artificial Intelligence and Soft Computing: 21st International Conference, ICAISC 2022, Zakopane, Poland, June 19–23, 2022, Proceedings, Part I","authors":"","doi":"10.1007/978-3-031-23492-7","DOIUrl":"https://doi.org/10.1007/978-3-031-23492-7","url":null,"abstract":"","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"98 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83588956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sedat Golgiyaz, Mahmut Daskin, C. Onat, M. F. Talu
In this study, NOx emission has been estimated by processing the flame image of visible wavelength and its experimental verification has been presented. The experimental study has been performed by using a domestic coal boiler with a capacity of 85000 Kcal / h. The real NOx value has been measured from a flue gas analyzer device. The flame image has been taken by CCD camera from the observation hole on the side of the burner. The data set which is related to instantaneous combustion performance and flame images was recorded simultaneously on the same computer with time stamps once a second. The color flame image has been transformed into a gray scale. Features have been obtained from the gray scale flame image. The features are obtained by using the cumulative projection vectors of row and column matrices. ANN regression model has been used as the learning model. The relationship between flame image and NOx emission has been obtained with the accuracy of R = 0.9522. Highly accurate measurement results show that the proposed system can be used in advanced closed loop combustion control systems.
{"title":"An Artificial Intelligence Regression Model for Prediction of NOx Emission from Flame Image","authors":"Sedat Golgiyaz, Mahmut Daskin, C. Onat, M. F. Talu","doi":"10.55195/jscai.1213863","DOIUrl":"https://doi.org/10.55195/jscai.1213863","url":null,"abstract":"In this study, NOx emission has been estimated by processing the flame image of visible wavelength and its experimental verification has been presented. The experimental study has been performed by using a domestic coal boiler with a capacity of 85000 Kcal / h. The real NOx value has been measured from a flue gas analyzer device. The flame image has been taken by CCD camera from the observation hole on the side of the burner. The data set which is related to instantaneous combustion performance and flame images was recorded simultaneously on the same computer with time stamps once a second. The color flame image has been transformed into a gray scale. Features have been obtained from the gray scale flame image. The features are obtained by using the cumulative projection vectors of row and column matrices. ANN regression model has been used as the learning model. The relationship between flame image and NOx emission has been obtained with the accuracy of R = 0.9522. Highly accurate measurement results show that the proposed system can be used in advanced closed loop combustion control systems.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"189 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78045931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The boron element forms more than 600 compounds with different element roots and shows very different properties. Boron compounds with these different properties have deserved to be the most important strategic feature in the world as they meet the demands above the targeted standards in industries such as energy, structure, chemistry, weapons and space. Today, the industries of developed countries have begun to take advantage of these energy sources due to the reduction of fossil energy resources, the inability of the industry to store enough electricity for an entire facility, and the limitations imposed on environmental policies. Developing countries continue to use fossil resources, but health and environmental costs are increasing. Whether they are developed countries or developing countries, they have attached importance to the research of energy systems that are capable of replacing fossil energy systems, which are environmentally friendly, sustainable, and have high performance. Boron has an important role in the energy field for the isolation, high energy value retention, fuel and ion batteries, solar panels and high-temperature transistors. In this study, the desired properties of boron compounds in energy studies were investigated by considering the positive effects of boron on the energy market.
{"title":"Boron's Critical Importance in Future Energy Technologies","authors":"Fatih Arlı","doi":"10.55195/jscai.1216892","DOIUrl":"https://doi.org/10.55195/jscai.1216892","url":null,"abstract":"The boron element forms more than 600 compounds with different element roots and shows very different properties. Boron compounds with these different properties have deserved to be the most important strategic feature in the world as they meet the demands above the targeted standards in industries such as energy, structure, chemistry, weapons and space. Today, the industries of developed countries have begun to take advantage of these energy sources due to the reduction of fossil energy resources, the inability of the industry to store enough electricity for an entire facility, and the limitations imposed on environmental policies. Developing countries continue to use fossil resources, but health and environmental costs are increasing. Whether they are developed countries or developing countries, they have attached importance to the research of energy systems that are capable of replacing fossil energy systems, which are environmentally friendly, sustainable, and have high performance. Boron has an important role in the energy field for the isolation, high energy value retention, fuel and ion batteries, solar panels and high-temperature transistors. In this study, the desired properties of boron compounds in energy studies were investigated by considering the positive effects of boron on the energy market.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"2 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2022-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88946163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we examine the concept of Delta-statistical boundedness of order Beta in sequences of fuzzy numbers and give some inclusion relations between Delta- statistical boundedness of order Beta and Delta-statistical convergence of order Beta
本文研究了模糊数序列中阶-统计有界性的概念，给出了阶-统计有界性与阶-统计收敛性之间的包含关系
{"title":"Generalized gama Statistical Boundedness of Order Beta in Sequences of Fuzzy Numbers","authors":"Mithat Kasap, H. Altinok","doi":"10.55195/jscai.1218844","DOIUrl":"https://doi.org/10.55195/jscai.1218844","url":null,"abstract":"In this paper, we examine the concept of Delta-statistical boundedness of order Beta in sequences of fuzzy numbers and give some inclusion relations between Delta- statistical boundedness of order Beta and Delta-statistical convergence of order Beta","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"1 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89434650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is an active field of study in studies where the iris center is referenced, such as iris center detection, gaze tracking, driver fatigue detection. In this study, an approach for real-time detection of iris centers based on convolutional neural networks is presented. The GI4E dataset was used as the dataset for the proposed approach. Experimental results estimated the test data of the proposed convolutional neural network model with an accuracy of 97.2% based on the 0.025 error corresponding to the closest position to the iris center according to the maximum normalized error criteria. The study was also tested in real time with a webcam built into the computer. While the test accuracy is satisfactory, real-time speed performance needs to be improved.
{"title":"Real-time Iris Center Detection Based on Convolutional Neural Networks","authors":"Kenan Donuk, D. Hanbay","doi":"10.55195/jscai.1216384","DOIUrl":"https://doi.org/10.55195/jscai.1216384","url":null,"abstract":"It is an active field of study in studies where the iris center is referenced, such as iris center detection, gaze tracking, driver fatigue detection. In this study, an approach for real-time detection of iris centers based on convolutional neural networks is presented. The GI4E dataset was used as the dataset for the proposed approach. Experimental results estimated the test data of the proposed convolutional neural network model with an accuracy of 97.2% based on the 0.025 error corresponding to the closest position to the iris center according to the maximum normalized error criteria. The study was also tested in real time with a webcam built into the computer. While the test accuracy is satisfactory, real-time speed performance needs to be improved.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"8 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82568588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
People mostly communicate through speech or facial expressions. People's feelings and thoughts are reflected in their faces and speech. This phenomenon is an important tool for people to empathize when communicating with each other. Today, human emotions can be recognized automatically with the help of artificial intelligence systems. Automatic recognition of emotions can increase productivity in all areas including virtual reality, psychology, behavior modeling, in short, human-computer interaction. In this study, we propose a method based on improving the accuracy of emotion recognition using speech data. In this method, new features are determined using convolutional neural networks from MFCC coefficient matrices of speech records in Crema-D dataset. By applying particle swarm optimization to the features obtained, the accuracy was increased by selecting the features that are important for speech emotion classification. In addition, 64 attributes used for each record were reduced to 33 attributes. In the test results, 62.86% accuracy was obtained with CNN, 63.93% accuracy with SVM and 66.01% accuracy with CNN+BPSO+SVM.
{"title":"CREMA-D: Improving Accuracy with BPSO-Based Feature Selection for Emotion Recognition Using Speech","authors":"Kenan Donuk","doi":"10.55195/jscai.1214312","DOIUrl":"https://doi.org/10.55195/jscai.1214312","url":null,"abstract":"People mostly communicate through speech or facial expressions. People's feelings and thoughts are reflected in their faces and speech. This phenomenon is an important tool for people to empathize when communicating with each other. Today, human emotions can be recognized automatically with the help of artificial intelligence systems. Automatic recognition of emotions can increase productivity in all areas including virtual reality, psychology, behavior modeling, in short, human-computer interaction. In this study, we propose a method based on improving the accuracy of emotion recognition using speech data. In this method, new features are determined using convolutional neural networks from MFCC coefficient matrices of speech records in Crema-D dataset. By applying particle swarm optimization to the features obtained, the accuracy was increased by selecting the features that are important for speech emotion classification. In addition, 64 attributes used for each record were reduced to 33 attributes. In the test results, 62.86% accuracy was obtained with CNN, 63.93% accuracy with SVM and 66.01% accuracy with CNN+BPSO+SVM.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"56 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81602071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Solving optimization is still a big challenge in the area of optimization algorithms. Many proposed algorithms in the literature don’t consider the relations between the variables of the nature of the problem. However, a recently published algorithm, called “Bayesian Multiploid Genetic Algorithm” exploits the relations between the variables and then solves the given problem. It also uses more than one genotype unlike the simple Genetic Algorithm (GA) and it acts like an implicit memory in order to remember the old but good solutions. In this work, the well-known Multidimensional Knapsack Problem (MKP) is solved. And the results show that exploiting relations between the variables gets a huge advantage in solving the given problem.
{"title":"Solving Multidimensional Knapsack Problem with Bayesian Multiploid Genetic Algorithm","authors":"Emrullah Gazioglu","doi":"10.55195/jscai.1216193","DOIUrl":"https://doi.org/10.55195/jscai.1216193","url":null,"abstract":"Solving optimization is still a big challenge in the area of optimization algorithms. Many proposed algorithms in the literature don’t consider the relations between the variables of the nature of the problem. However, a recently published algorithm, called “Bayesian Multiploid Genetic Algorithm” exploits the relations between the variables and then solves the given problem. It also uses more than one genotype unlike the simple Genetic Algorithm (GA) and it acts like an implicit memory in order to remember the old but good solutions. In this work, the well-known Multidimensional Knapsack Problem (MKP) is solved. And the results show that exploiting relations between the variables gets a huge advantage in solving the given problem.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"360 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77502554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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