Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00111
Fahim UDDIN
This manuscript aims to introduce the concept of orthogonal fuzzy b-metric-like spaces and discuss some fixed point results. A non-trivial example is imparted to illustrate the feasibility of the proposed methods. Finally, to validate the superiority of the obtained results, we provide an application to fractional differential equations. Cite this article as: Uddin F, Ishtiaq U, Aydi H, Javed K, Arshad M. On orthogonal fuzzy b-metric-like spaces and their fixed point application. Sigma J Eng Nat Sci 2023;41(5):916−925.
{"title":"On orthogonal fuzzy b-metric-like spaces and their fixed point application","authors":"Fahim UDDIN","doi":"10.14744/sigma.2023.00111","DOIUrl":"https://doi.org/10.14744/sigma.2023.00111","url":null,"abstract":"This manuscript aims to introduce the concept of orthogonal fuzzy b-metric-like spaces and discuss some fixed point results. A non-trivial example is imparted to illustrate the feasibility of the proposed methods. Finally, to validate the superiority of the obtained results, we provide an application to fractional differential equations. Cite this article as: Uddin F, Ishtiaq U, Aydi H, Javed K, Arshad M. On orthogonal fuzzy b-metric-like spaces and their fixed point application. Sigma J Eng Nat Sci 2023;41(5):916−925.","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135156203","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00108
Ebru GÜNDOĞAN AŞIK
High-leverage points, known as good and bad leverage points, are also known as points away from center of x space. Bad leverage points are marginal values that show the incompatibility with misclassified observations and other observation values at x space. In the identification of bad leverage points, the problems of masking and swamping constitute a problem for the logistic regression model just as in the linear regression model. In this research, in addition to existing deviance components (DEVC), robust deviance components (RobDEVC) that are used to identify bad leverage points, different robust methods recommended to be used at the management of deviance components were examined. Also, for these methods, robust cut-off value combinations were examined as well. With the conducted simulation, robust methods recommended to be used in the deviance component method have shown better performance to identify bad leverage points by showing different cut-off values
{"title":"Robust methods for detecting bad leverage point in logistic regression","authors":"Ebru GÜNDOĞAN AŞIK","doi":"10.14744/sigma.2023.00108","DOIUrl":"https://doi.org/10.14744/sigma.2023.00108","url":null,"abstract":"High-leverage points, known as good and bad leverage points, are also known as points away from center of x space. Bad leverage points are marginal values that show the incompatibility with misclassified observations and other observation values at x space. In the identification of bad leverage points, the problems of masking and swamping constitute a problem for the logistic regression model just as in the linear regression model. In this research, in addition to existing deviance components (DEVC), robust deviance components (RobDEVC) that are used to identify bad leverage points, different robust methods recommended to be used at the management of deviance components were examined. Also, for these methods, robust cut-off value combinations were examined as well. With the conducted simulation, robust methods recommended to be used in the deviance component method have shown better performance to identify bad leverage points by showing different cut-off values","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135156691","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00110
Erman ALBAYRAK
{"title":"TRIZ approach to the relevant problem for the transport of assay tubes: A case study on family health centers in Amasya","authors":"Erman ALBAYRAK","doi":"10.14744/sigma.2023.00110","DOIUrl":"https://doi.org/10.14744/sigma.2023.00110","url":null,"abstract":"","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135158013","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.001201
Yerlan BEKESHEV
Bacteria capable of decomposing hydrocarbon rocket power kerosene T-1 were isolated and studied. In the course of the studies, 30 isolates of microbial cultures were isolated from soils contaminated with hydrocarbon rocket fuel, of which 9 isolates were selected that actively assimilate kerosene T-1 as the only headwater of carbon. The strains that showed the best results in these screening analyses on four nutrient media with a concentration of T-1 kerosene 1% (10 g/kg) grow well 9 isolates of culture microorganisms: (cid:0) 4, 8, 14, 23, 5, 18, 20, 25 and yeast (cid:0) 12/5. Isolates on a medium with a concentration of T-1 kerosene 2% (20 g/kg) and 5% (50 g/kg) showed good growth in bacterial cultures (cid:0) 5, 18, 20, 25, and yeast (cid:0) 12/5. The selected microorganisms were identified by physiological and biochemical characteristics: (cid:0) 5 – Arthrobacter sp., (cid:0)18 – Acinetobacter calcoaceticum, (cid:0)20 – Bacillus sp., (cid:0)25-Micrococcus roseus, (cid:0) 12/5-Candida sp. Cultivation conditions for isolated microorganisms were created. It has been established that the optimal development temperature for the culture of Arthrobacter sp. 5 is 25-30°C, Acinetobacter calcoaceticum. 18 is 30-35 °(cid:0) , Micrococcus roseus. 25 is 25-37 °(cid:0). The optimal duration of cultivation of Candida sp. 12/5 is 1 day, for the rest of the studied cultures - 2 days.
{"title":"Isolation of kerosene-degrading bacteria from soil samples and determination of optimal growth conditions","authors":"Yerlan BEKESHEV","doi":"10.14744/sigma.2023.001201","DOIUrl":"https://doi.org/10.14744/sigma.2023.001201","url":null,"abstract":"Bacteria capable of decomposing hydrocarbon rocket power kerosene T-1 were isolated and studied. In the course of the studies, 30 isolates of microbial cultures were isolated from soils contaminated with hydrocarbon rocket fuel, of which 9 isolates were selected that actively assimilate kerosene T-1 as the only headwater of carbon. The strains that showed the best results in these screening analyses on four nutrient media with a concentration of T-1 kerosene 1% (10 g/kg) grow well 9 isolates of culture microorganisms: (cid:0) 4, 8, 14, 23, 5, 18, 20, 25 and yeast (cid:0) 12/5. Isolates on a medium with a concentration of T-1 kerosene 2% (20 g/kg) and 5% (50 g/kg) showed good growth in bacterial cultures (cid:0) 5, 18, 20, 25, and yeast (cid:0) 12/5. The selected microorganisms were identified by physiological and biochemical characteristics: (cid:0) 5 – Arthrobacter sp., (cid:0)18 – Acinetobacter calcoaceticum, (cid:0)20 – Bacillus sp., (cid:0)25-Micrococcus roseus, (cid:0) 12/5-Candida sp. Cultivation conditions for isolated microorganisms were created. It has been established that the optimal development temperature for the culture of Arthrobacter sp. 5 is 25-30°C, Acinetobacter calcoaceticum. 18 is 30-35 °(cid:0) , Micrococcus roseus. 25 is 25-37 °(cid:0). The optimal duration of cultivation of Candida sp. 12/5 is 1 day, for the rest of the studied cultures - 2 days.","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610013","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00114
Süleyman ŞENGÜL
In this study, Wong-Zakai approximation method has been used to obtain approximate solutions for two compartmental models of smoking dynamics. Stratonovich stochastic differential equation systems are obtained for these two stochastic models for the application of Wong-Zakai method. Wong-Zakai method is used together with the predictor-corrector deterministic approximation method where Adams-Bashforth method is used as the predictor pair and Adams-Moulton method is used as the corrector pair. Stochastic Runge-Kutta IV, Euler-Maruyama and stochastic Runge-Kutta strong order 1.0 schemes are also used to investigate the models and the results are compared to the results from Wong-Zakai approximation. The comparison shows that Wong-Zakai method is a reliable tool for the analysis of stochastic models and can be considered as an alternative investigation method for modeling studies. Solution graphs, error graphs and numerical results have been given as evidence to show that Wong-Zakai method can also be a reliable method for analyzing various models. An alternate technique for parallelizing the algorithm has also been given to decrease CPU times for Wong-Zakai method. This technique is suggested to overcome the extra calculation load that comes with Wong-Zakai method.
{"title":"Wong-Zakai approximation for stochastic models of smoking","authors":"Süleyman ŞENGÜL","doi":"10.14744/sigma.2023.00114","DOIUrl":"https://doi.org/10.14744/sigma.2023.00114","url":null,"abstract":"In this study, Wong-Zakai approximation method has been used to obtain approximate solutions for two compartmental models of smoking dynamics. Stratonovich stochastic differential equation systems are obtained for these two stochastic models for the application of Wong-Zakai method. Wong-Zakai method is used together with the predictor-corrector deterministic approximation method where Adams-Bashforth method is used as the predictor pair and Adams-Moulton method is used as the corrector pair. Stochastic Runge-Kutta IV, Euler-Maruyama and stochastic Runge-Kutta strong order 1.0 schemes are also used to investigate the models and the results are compared to the results from Wong-Zakai approximation. The comparison shows that Wong-Zakai method is a reliable tool for the analysis of stochastic models and can be considered as an alternative investigation method for modeling studies. Solution graphs, error graphs and numerical results have been given as evidence to show that Wong-Zakai method can also be a reliable method for analyzing various models. An alternate technique for parallelizing the algorithm has also been given to decrease CPU times for Wong-Zakai method. This technique is suggested to overcome the extra calculation load that comes with Wong-Zakai method.","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135260972","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00102
Fuat KARTAL
This study aims to predict machinability and high performance optimum surface roughness ( R a ) by developing multiple regression models and artificial neural network (ANN) model for abrasive waterjet cutting (AWJC) of Aluminum 7068 alloy. Important basic processing parameters such as pump pressure (3500-4000 Bar), nozzle distance (2-5 mm), abrasive flow rate (200-350 g/min), abrasive grain size (100-110, mesh), and nozzle traverse speed (240-300 mm/min) were selected in the study. To examine the effects of these parameters on R a , 32 experiments were conducted using the L32 orthogonal array, and data was collected. Additionally, the most important factors and interactions affecting R a were determined using multiple regression analysis and analysis of variance (ANOVA). The ANN model was designed to have multiple hidden layers using MATLAB. The model was trained and evaluated using experimental data, and its performance was measured using mean squared error (MSE) and mean absolute error (MAE). The model was optimized using hyper parameter tuning and cross-validation techniques. As a result, it was determined that the best R2 value of 95.65% from the multiple regression models created to estimate the surface roughness could be obtained from the linear regression model. While selecting the optimum process parameters for AWJC, it was determined that nozzle rotation speed, abrasive grain size and flow rate had the greatest effect by 35.5%, 25.4% and 21.9%, respectively. The optimized ANN model showed high accuracy in predicting R a for different input parameter combinations. This study provides a reliable and efficient tool for predicting R a in AWJC, which can contribute to improving process planning and control.
{"title":"Artificial neural network and multiple regression analysis for predicting abrasive water jet cutting of al 7068 aerospace alloy","authors":"Fuat KARTAL","doi":"10.14744/sigma.2023.00102","DOIUrl":"https://doi.org/10.14744/sigma.2023.00102","url":null,"abstract":"This study aims to predict machinability and high performance optimum surface roughness ( R a ) by developing multiple regression models and artificial neural network (ANN) model for abrasive waterjet cutting (AWJC) of Aluminum 7068 alloy. Important basic processing parameters such as pump pressure (3500-4000 Bar), nozzle distance (2-5 mm), abrasive flow rate (200-350 g/min), abrasive grain size (100-110, mesh), and nozzle traverse speed (240-300 mm/min) were selected in the study. To examine the effects of these parameters on R a , 32 experiments were conducted using the L32 orthogonal array, and data was collected. Additionally, the most important factors and interactions affecting R a were determined using multiple regression analysis and analysis of variance (ANOVA). The ANN model was designed to have multiple hidden layers using MATLAB. The model was trained and evaluated using experimental data, and its performance was measured using mean squared error (MSE) and mean absolute error (MAE). The model was optimized using hyper parameter tuning and cross-validation techniques. As a result, it was determined that the best R2 value of 95.65% from the multiple regression models created to estimate the surface roughness could be obtained from the linear regression model. While selecting the optimum process parameters for AWJC, it was determined that nozzle rotation speed, abrasive grain size and flow rate had the greatest effect by 35.5%, 25.4% and 21.9%, respectively. The optimized ANN model showed high accuracy in predicting R a for different input parameter combinations. This study provides a reliable and efficient tool for predicting R a in AWJC, which can contribute to improving process planning and control.","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136368240","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00122
Hakan CENGIZLER
The production of low-cost open-pore ceramic materials from fly ash (FA) and marble waste (MW) was investigated.The effect of MW (5-40 wt.%) onthe open porosity was determined. To reduce the sintering temperature and improve the properties of porous materials, the mixtures were activated with an alkali solution. Samples pressed from FA and FA+MW mixtures were sintered at low temperature (900 °C), but sufficient strength could not be obtained. However, when these mixtureswere subjected to alkali activation, pressed and sintered at 900 °C, sufficient strength and porosity values were reached. The open porosity of the MW neat specimen was 12.70%, but it increased up to 39.91% at 40 wt.% MW, which was the highest ratio used in the literature. The main phase structure was nepheline at 0-20 wt.% MW, but gehlenite became the dominant phase at 40 wt. % MW. The compressive and flexural strength values of 40 wt.% MW added specimen was determined to be 12 and 5.35 MPa, respectively.The open-pore ceramic of high MW ratio, produced by this new alternative route, has the potential for use in water purification membranes for macro filtration purposes.
{"title":"The effect of marble waste in the production of low-temperature porous material from Alkali-activated fly ash","authors":"Hakan CENGIZLER","doi":"10.14744/sigma.2023.00122","DOIUrl":"https://doi.org/10.14744/sigma.2023.00122","url":null,"abstract":"The production of low-cost open-pore ceramic materials from fly ash (FA) and marble waste (MW) was investigated.The effect of MW (5-40 wt.%) onthe open porosity was determined. To reduce the sintering temperature and improve the properties of porous materials, the mixtures were activated with an alkali solution. Samples pressed from FA and FA+MW mixtures were sintered at low temperature (900 °C), but sufficient strength could not be obtained. However, when these mixtureswere subjected to alkali activation, pressed and sintered at 900 °C, sufficient strength and porosity values were reached. The open porosity of the MW neat specimen was 12.70%, but it increased up to 39.91% at 40 wt.% MW, which was the highest ratio used in the literature. The main phase structure was nepheline at 0-20 wt.% MW, but gehlenite became the dominant phase at 40 wt. % MW. The compressive and flexural strength values of 40 wt.% MW added specimen was determined to be 12 and 5.35 MPa, respectively.The open-pore ceramic of high MW ratio, produced by this new alternative route, has the potential for use in water purification membranes for macro filtration purposes.","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135660099","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}
Pub Date : 2023-01-01DOI: 10.14744/sigma.2023.00112
Asma MAHMOOD
The aim of this paper is to obtain optimum fuzzy soft constants through multi-criteria decision-making approaches. TOPSIS and VIKOR are utilized for this purpose and results are compared with those obtained through Bonferroni mean. The hesitant fuzzy soft set is taken as initial data in decision-making methods. Hesitant fuzzy Bonferroni means and distance measures for TOPSIS and VIKOR are calculated in the structure of hesitant fuzzy set and hesitant fuzzy soft set. OFSCs are chosen from the constants which rank the alternatives in the decision-making process. By using the system of linear differential equations based on OFSCs, the future approach of people with respect to their decisions is analyzed and is observed through phase portrait and a line graph of that system of differential equations. To explain the proposed idea, explanative examples for two techniques are also given. These examples illustrate that if two persons select the two different alternatives, they do not favor each other after that decision. Cite this article as: Mahmood A, Abbas M, Murtaza G. Observation of experts, attitudes through multi-criteria decision-making. Sigma J Eng Nat Sci 2023;41(5):926−937.
{"title":"Observation of experts, attitudes through multi-criteria decision-making","authors":"Asma MAHMOOD","doi":"10.14744/sigma.2023.00112","DOIUrl":"https://doi.org/10.14744/sigma.2023.00112","url":null,"abstract":"The aim of this paper is to obtain optimum fuzzy soft constants through multi-criteria decision-making approaches. TOPSIS and VIKOR are utilized for this purpose and results are compared with those obtained through Bonferroni mean. The hesitant fuzzy soft set is taken as initial data in decision-making methods. Hesitant fuzzy Bonferroni means and distance measures for TOPSIS and VIKOR are calculated in the structure of hesitant fuzzy set and hesitant fuzzy soft set. OFSCs are chosen from the constants which rank the alternatives in the decision-making process. By using the system of linear differential equations based on OFSCs, the future approach of people with respect to their decisions is analyzed and is observed through phase portrait and a line graph of that system of differential equations. To explain the proposed idea, explanative examples for two techniques are also given. These examples illustrate that if two persons select the two different alternatives, they do not favor each other after that decision. Cite this article as: Mahmood A, Abbas M, Murtaza G. Observation of experts, attitudes through multi-criteria decision-making. Sigma J Eng Nat Sci 2023;41(5):926−937.","PeriodicalId":45000,"journal":{"name":"Sigma Journal of Engineering and Natural Sciences-Sigma Muhendislik ve Fen Bilimleri Dergisi","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135156205","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：