In this study, poly(acrylic acid) (PAA)/bentonite (BNT) composites were synthesized through chemical crosslinking by a chemical polymerization using ammonium persulfate as initiator and N,N’-methylenebisacrylamide as crosslinker. Poly(3,4-ethylenedioxythiophene) (PEDOT) was synthesized by oxidative polymerization and then PEDOT/PAA/BNT composites were prepared by mixing PEDOT at 5%, 10% and 20% by mass into PAA/BNT composite. These hydrogel composites were characterized by FTIR, XRD and SEM. It was observed that water absorbency increased with the increase of PEDOT ratio of hydrogel composites.
{"title":"PREPARATION AND SWELLING PROPERTIES OF POLY(3,4 –ETHYLENEDIOXYTHIOPHENE)/POLY(ACRYLIC ACID)/BENTONITE COMPOSITE HYDROGELS","authors":"K. Hüner","doi":"10.30931/jetas.1001134","DOIUrl":"https://doi.org/10.30931/jetas.1001134","url":null,"abstract":"In this study, poly(acrylic acid) (PAA)/bentonite (BNT) composites were synthesized through chemical crosslinking by a chemical polymerization using ammonium persulfate as initiator and N,N’-methylenebisacrylamide as crosslinker. Poly(3,4-ethylenedioxythiophene) (PEDOT) was synthesized by oxidative polymerization and then PEDOT/PAA/BNT composites were prepared by mixing PEDOT at 5%, 10% and 20% by mass into PAA/BNT composite. These hydrogel composites were characterized by FTIR, XRD and SEM. It was observed that water absorbency increased with the increase of PEDOT ratio of hydrogel composites.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86992122","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}
In recent years, different types of cancer cases are common. In addition to being the most common cancer among women today, breast cancer has surpassed lung cancer as the most common cancer type in the world since 2021. The fact that early diagnosis greatly reduces the risk of death in breast cancer necessitated the use of computer-aided systems in these processes. These systems are extremely important in terms of being an assistant to the expert opinion. In this study, we reduced our dataset to 171 data using Principal Component Analysis (PCA) to accelerate disease diagnosis on the Wisconsin Breast Cancer dataset and 2 different classification processes were performed using 5 different machine learning. The success rate of each algorithm was compared and it was revealed that Logistic Regression was the most successful method with an accuracy rate of 98.8% after PCA
{"title":"ANALYSIS OF DIFFERENT MACHINE LEARNING TECHNIQUES WITH PCA IN THE DIAGNOSIS OF BREAST CANCER","authors":"Hüseyin Yilmaz, F. Kuncan","doi":"10.30931/jetas.1166768","DOIUrl":"https://doi.org/10.30931/jetas.1166768","url":null,"abstract":"In recent years, different types of cancer cases are common. In addition to being the most common cancer among women today, breast cancer has surpassed lung cancer as the most common cancer type in the world since 2021. The fact that early diagnosis greatly reduces the risk of death in breast cancer necessitated the use of computer-aided systems in these processes. These systems are extremely important in terms of being an assistant to the expert opinion. In this study, we reduced our dataset to 171 data using Principal Component Analysis (PCA) to accelerate disease diagnosis on the Wisconsin Breast Cancer dataset and 2 different classification processes were performed using 5 different machine learning. The success rate of each algorithm was compared and it was revealed that Logistic Regression was the most successful method with an accuracy rate of 98.8% after PCA","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"94 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79595773","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}
In this work, it has been applied two methods for solving the (2+1)-dimensional soliton equation, namely, the ansatz method and the F-expansion method. These methods are utilized to provide new accurate periodic and soliton solutions to this problem that are more generic. An appropriate transformation can be used to convert this nonlinear system into another nonlinear ordinary differential equation. In mathematical physics, it is demonstrated that the ansatz method and the F-expansion method give a strong mathematical tool for solving a large number of systems of nonlinear partial differential equations.
{"title":"ANALYTICAL SOLUTIONS OF THE NONLINEAR (2 + 1)-DIMENSIONAL SOLITON EQUATION BY USING SOME METHODS","authors":"Ayten Özkan","doi":"10.30931/jetas.1108028","DOIUrl":"https://doi.org/10.30931/jetas.1108028","url":null,"abstract":"In this work, it has been applied two methods for solving the (2+1)-dimensional soliton equation, namely, the ansatz method and the F-expansion method. These methods are utilized to provide new accurate periodic and soliton solutions to this problem that are more generic. An appropriate transformation can be used to convert this nonlinear system into another nonlinear ordinary differential equation. In mathematical physics, it is demonstrated that the ansatz method and the F-expansion method give a strong mathematical tool for solving a large number of systems of nonlinear partial differential equations.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"113 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74513211","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}
In this study, a new algorithm is introduced for the numerical solution of equal width (EW) equation. This algorithm is created by using the collocation finite element method based on decic B-spline functions for the space discretization of the EW equation and the Crank-Nicolson method for the time discretization of his equation. The obtained results are compared with the previous ones to see the efficiency and accuracy of the proposed method.
{"title":"A NEW ALGORITHM BASED ON THE DECIC (TENTH DEGREE) B-SPLINE FUNCTIONS FOR NUMERICAL SOLUTION OF THE EQUAL WIDTH EQUATION","authors":"Melis Zorsahin Gorgulu","doi":"10.30931/jetas.1072151","DOIUrl":"https://doi.org/10.30931/jetas.1072151","url":null,"abstract":"In this study, a new algorithm is introduced for the numerical solution of equal width (EW) equation. This algorithm is created by using the collocation finite element method based on decic B-spline functions for the space discretization of the EW equation and the Crank-Nicolson method for the time discretization of his equation. The obtained results are compared with the previous ones to see the efficiency and accuracy of the proposed method.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81449675","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}
In this paper, we introduce a new iterative algorithm to approximate fixed points of generalized multivalued nonexpansive mappings. We established some weak and strong convergence theorems in a uniformly convex real Banach space.
{"title":"A new iterative scheme for approximating fixed points of generalized multivalued nonexpansive mappings","authors":"Makbule Kaplan","doi":"10.30931/jetas.1003445","DOIUrl":"https://doi.org/10.30931/jetas.1003445","url":null,"abstract":"In this paper, we introduce a new iterative algorithm to approximate fixed points of generalized multivalued nonexpansive mappings. We established some weak and strong convergence theorems in a uniformly convex real Banach space.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"163 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86631334","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}
Detection of volatile organic compound (VOC) vapors, which are known to have carcinogenic effects, is extremely important and necessary in many areas. In this work, the sensing properties of a cobalt phthalocyanine (CoPc) thin film at six different VOC vapors (methanol, ethanol, butanol, isopropyl alcohol, acetone, and ammonia) concentrations from 50 to 450 ppm are investigated and it is observed that the interaction between the VOC vapors and CoPc surface is not selective. It is shown that using machine learning algorithms the present sensor, which is poorly selective, can be transformed into a more efficient one with better detection ability. As a feature, 10 seconds of raw responses taken from steady state region are used without any additional processing technique. Among classification algorithms, k-nearest neighbor (KNN) reaches the highest accuracy of 97.1%. The selected feature is also compared with classical steady state response feature. Classification results indicate that the feature based on 10 seconds of raw responses taken from steady state region is much better than that based on classical steady state response feature.
{"title":"Classification of VOC Vapors Using Machine Learning Algorithms","authors":"S. Aksoy, Muttalip Özavsar, A. Altındal","doi":"10.30931/jetas.1030981","DOIUrl":"https://doi.org/10.30931/jetas.1030981","url":null,"abstract":"Detection of volatile organic compound (VOC) vapors, which are known to have carcinogenic effects, is extremely important and necessary in many areas. In this work, the sensing properties of a cobalt phthalocyanine (CoPc) thin film at six different VOC vapors (methanol, ethanol, butanol, isopropyl alcohol, acetone, and ammonia) concentrations from 50 to 450 ppm are investigated and it is observed that the interaction between the VOC vapors and CoPc surface is not selective. It is shown that using machine learning algorithms the present sensor, which is poorly selective, can be transformed into a more efficient one with better detection ability. As a feature, 10 seconds of raw responses taken from steady state region are used without any additional processing technique. Among classification algorithms, k-nearest neighbor (KNN) reaches the highest accuracy of 97.1%. The selected feature is also compared with classical steady state response feature. Classification results indicate that the feature based on 10 seconds of raw responses taken from steady state region is much better than that based on classical steady state response feature.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74290077","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}
The real-life optimization problems are too complex to be solved by developing a mathematical formula. Heuristic methods are the methods defined to decide the best of a variety of solution actions to solve a problem. Furthermore, it is preferred that heuristic methods are short in solution time and can be applied to different problems. Heuristic methods were developed while trying to find the best solution. The created algorithm, which was based on herd intelligence, was used to solve optimization problems based on the behaviors of bees moving in nature in the process of finding nutrients. By the studies, transformer failures allow us to know without any measurements and tests. The software was developed in C++ programming language by using the created artificial algorithms. The transformer analyses programs have been created by using Microsoft SQL Server 2017 database.
现实生活中的优化问题太复杂了，不能用数学公式来解决。启发式方法是指在解决问题的各种解决方案行动中确定最佳解决方案的方法。此外，启发式方法求解时间短，可以应用于不同的问题，这是可取的。在试图找到最佳解决方案时，开发了启发式方法。该算法以蜂群智能为基础，根据蜜蜂在自然界中寻找营养物质的行为来解决优化问题。通过研究，我们无需任何测量和测试就可以知道变压器的故障。利用所建立的人工算法，用c++编程语言进行软件开发。使用Microsoft SQL Server 2017数据库创建了变压器分析程序。
{"title":"Definition of Faults and Efficiency in Power Transformers Using the Algorithm and Computer Program Created by the Heuristic Optimization Methods Developed","authors":"M. Zile","doi":"10.30931/jetas.1118283","DOIUrl":"https://doi.org/10.30931/jetas.1118283","url":null,"abstract":"The real-life optimization problems are too complex to be solved by developing a mathematical formula. Heuristic methods are the methods defined to decide the best of a variety of solution actions to solve a problem. Furthermore, it is preferred that heuristic methods are short in solution time and can be applied to different problems. Heuristic methods were developed while trying to find the best solution. The created algorithm, which was based on herd intelligence, was used to solve optimization problems based on the behaviors of bees moving in nature in the process of finding nutrients. By the studies, transformer failures allow us to know without any measurements and tests. The software was developed in C++ programming language by using the created artificial algorithms. The transformer analyses programs have been created by using Microsoft SQL Server 2017 database.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82288395","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}
{"title":"INFLUENCE OF DIFFERENT CONCENTRATIONS OF MURASHIGE AND SKOOG MEDIUM ON MULTIPLE SHOOT REGENERATION OF Staurogyne repens (Nees) Kuntze","authors":"Muhammet Dogan","doi":"10.30931/jetas.1055833","DOIUrl":"https://doi.org/10.30931/jetas.1055833","url":null,"abstract":"","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84734890","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}
{"title":"OPTIMAL CHOICE AND ALLOCATION OF SHUNT FACTS DEVICES USING DIFFERENTIAL SEARCH ALGORITHM","authors":"Kadir Abaci","doi":"10.30931/jetas.1024878","DOIUrl":"https://doi.org/10.30931/jetas.1024878","url":null,"abstract":"","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84309118","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}
{"title":"Operational Efficiency and Energy Saving Analysis of Urban Transportation:The Case of Akcaray","authors":"Z. Aydin","doi":"10.30931/jetas.977795","DOIUrl":"https://doi.org/10.30931/jetas.977795","url":null,"abstract":"","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76370276","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}
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