Sanal Gerçeklik teknolojisi son yıllarda hayatın her alanında kullanılmaya başlanan yeni bir teknoloji olarak karşımıza çıkmaktadır. Yeni bir teknolojinin getirdiği belirsiz alanlar ve potansiyelinin henüz tam olarak bilinmeyişi bu alandaki araştırmaların artmasına zemin hazırlamıştır. Sanal Gerçeklikte Bulanık Mantık Yaklaşımının kullanılması da bu araştırma alanlarından biri olmuştur. Bulanık mantığın belirsizlik içeren kontrol ve karar verme süreçlerindeki başarısı, sanal gerçeklik teknolojisine entegrasyonunda etkili olmuştur. Sanal ortam, araç ve eğitim ortamlarının tasarlanma süreçlerindeki kontrol ve karar verme süreçleri bu yöntemin kullanılması için çok elverişlidir. Çalışmada son yirmi yıllık süreçte bulanık mantık yaklaşımına dayanan sanal gerçeklik alanındaki çalışmalar incelenerek, ilgili yazın taraması hakkında değerlendirmelerde bulunulmuştur.
{"title":"Sanal Gerçeklik Uygulamalarında Bulanık Mantık Yaklaşımı: Sistematik Derleme","authors":"Azize Sudan Aran, Ergün Eraslan","doi":"10.56554/jtom.1373850","DOIUrl":"https://doi.org/10.56554/jtom.1373850","url":null,"abstract":"Sanal Gerçeklik teknolojisi son yıllarda hayatın her alanında kullanılmaya başlanan yeni bir teknoloji olarak karşımıza çıkmaktadır. Yeni bir teknolojinin getirdiği belirsiz alanlar ve potansiyelinin henüz tam olarak bilinmeyişi bu alandaki araştırmaların artmasına zemin hazırlamıştır. Sanal Gerçeklikte Bulanık Mantık Yaklaşımının kullanılması da bu araştırma alanlarından biri olmuştur. Bulanık mantığın belirsizlik içeren kontrol ve karar verme süreçlerindeki başarısı, sanal gerçeklik teknolojisine entegrasyonunda etkili olmuştur. Sanal ortam, araç ve eğitim ortamlarının tasarlanma süreçlerindeki kontrol ve karar verme süreçleri bu yöntemin kullanılması için çok elverişlidir. Çalışmada son yirmi yıllık süreçte bulanık mantık yaklaşımına dayanan sanal gerçeklik alanındaki çalışmalar incelenerek, ilgili yazın taraması hakkında değerlendirmelerde bulunulmuştur.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825724","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}
Giderek hayatımızda daha büyük yer edinen dijital eğlence, müşteri deneyimi ve davranışlarının yakından izlenmesi gereken bir alan haline gelmiştir. Taşınabilirliği sayesinde insanların herhangi bir mekânda ve zamanda eğlenmesine olanak sağlayan mobil oyunlar, çocuklar kadar yetişkinlere de hitap ederek daha kazançlı hale gelmiş; böylelikle mobil oyun pazarı, küresel ölçekte son yıllarda daha fazla yatırım çekmeye başlamıştır. Teknolojik gelişmeler sayesinde mobil oyunlarda gözlenen hızlı büyüme eğilimi, COVID-19 pandemisi nedeniyle ivme kazanmıştır. Böyle dönüşüm şoklarının büyüme potansiyeli yüksek bir sektörü nasıl etkilediğini incelemek önemlidir. Pandeminin oyun pazarına olan etkisini, oyuncu davranışlarını inceleyerek ortaya koymayı amaçlayan bu çalışmada, belli bir oyun türüne ait Türkçe kullanıcı yorumları toplanmış, kullanıcıların pandemi öncesindeki ve sonrasındaki duyguları uyum analizi ve konu modellemesi sayesinde karşılaştırılmıştır. Her iki yöntem de pandemi sonrasında öne çıkan sorunların ve konu başlıklarının pandemi öncesine kıyasla farklılaştığını ortaya koymaktadır. Tek bir türden kısıtlı sayıda oyun göz önünde bulundurularak uygulanan metodolojik çerçeve, farklı dillerde yazılmış yorumlara sahip başka oyunlara ve mobil uygulamalara da kolaylıkla uyarlanabilir.
{"title":"COVID-19 Pandemisinin Türkiye Mobil Oyun Pazarına Etkisi: Bir Metin Madenciliği Uygulaması","authors":"Cigdem Kadaifci, Cafer Erhan Bozdağ, Erkan Işıklı","doi":"10.56554/jtom.1284249","DOIUrl":"https://doi.org/10.56554/jtom.1284249","url":null,"abstract":"Giderek hayatımızda daha büyük yer edinen dijital eğlence, müşteri deneyimi ve davranışlarının yakından izlenmesi gereken bir alan haline gelmiştir. Taşınabilirliği sayesinde insanların herhangi bir mekânda ve zamanda eğlenmesine olanak sağlayan mobil oyunlar, çocuklar kadar yetişkinlere de hitap ederek daha kazançlı hale gelmiş; böylelikle mobil oyun pazarı, küresel ölçekte son yıllarda daha fazla yatırım çekmeye başlamıştır. Teknolojik gelişmeler sayesinde mobil oyunlarda gözlenen hızlı büyüme eğilimi, COVID-19 pandemisi nedeniyle ivme kazanmıştır. Böyle dönüşüm şoklarının büyüme potansiyeli yüksek bir sektörü nasıl etkilediğini incelemek önemlidir. Pandeminin oyun pazarına olan etkisini, oyuncu davranışlarını inceleyerek ortaya koymayı amaçlayan bu çalışmada, belli bir oyun türüne ait Türkçe kullanıcı yorumları toplanmış, kullanıcıların pandemi öncesindeki ve sonrasındaki duyguları uyum analizi ve konu modellemesi sayesinde karşılaştırılmıştır. Her iki yöntem de pandemi sonrasında öne çıkan sorunların ve konu başlıklarının pandemi öncesine kıyasla farklılaştığını ortaya koymaktadır. Tek bir türden kısıtlı sayıda oyun göz önünde bulundurularak uygulanan metodolojik çerçeve, farklı dillerde yazılmış yorumlara sahip başka oyunlara ve mobil uygulamalara da kolaylıkla uyarlanabilir.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827689","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}
This study investigates the three factors that contribute to designing efficient buildings, namely technical solutions, facade systems, and occupant requirements, through the use of a real-world dataset consisting of 49 efficient buildings from various locations across the globe. Each factor comprises distinct elements that are essential in achieving building efficiency. Statistical methods, including correlation and Kruskal-Wallis methods, as well as advanced statistical methods such as the reversible jump Markov chain Monte Carlo method, were employed to estimate parameters that represent the conditional dependence between the elements of each factor. The undirected graphs were generated for each factor based on the conditional depence between the elements of the factor which is shown by a link. Through the analysis of these graphs, designers can enhance their comprehension of the correlation between the various elements of each factor, which can ultimately result in improved building efficiency. This, in turn, may lead to a decrease in air pollution and energy consumption while enhancing human comfort.
{"title":"Exploring the Relationship Between Technical and Comfort Factors in Designing Efficient Buildings: A Statistical Analysis of a Real-World Dataset","authors":"Nastaran Deljavan, Hajar Franoudkia","doi":"10.56554/jtom.1332101","DOIUrl":"https://doi.org/10.56554/jtom.1332101","url":null,"abstract":"This study investigates the three factors that contribute to designing efficient buildings, namely technical solutions, facade systems, and occupant requirements, through the use of a real-world dataset consisting of 49 efficient buildings from various locations across the globe. Each factor comprises distinct elements that are essential in achieving building efficiency. Statistical methods, including correlation and Kruskal-Wallis methods, as well as advanced statistical methods such as the reversible jump Markov chain Monte Carlo method, were employed to estimate parameters that represent the conditional dependence between the elements of each factor. The undirected graphs were generated for each factor based on the conditional depence between the elements of the factor which is shown by a link. Through the analysis of these graphs, designers can enhance their comprehension of the correlation between the various elements of each factor, which can ultimately result in improved building efficiency. This, in turn, may lead to a decrease in air pollution and energy consumption while enhancing human comfort.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824617","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}
Emre Yazıcı, Ufukcan Ebiri, Berat Alperen Kızılay, Onur Oruç, Hacı Mehmet Alakaş
Günümüzde teknolojik ürünlerin kullanımı hayatımızın hemen hemen her alanında vardır. Bu ürünlerin üretiminde çeşitli amaçlar için kullanılan mekanik ve elektronik cihazlar bulunmaktadır. Bu cihazlardan biriside elektronik devre elemanlarının lehimlenmesinde kullanılan havya setleridir. İşletmeler için ciddi mali yükleri olan ve hassas kullanım isteyen havya setlerinin seçimi önemli bir karar problemi niteliğindedir. Bu çalışmada bir elektronik işletmesi için alınması planlanan havya setlerinin seçimi incelenmektedir. Havya setlerinin seçiminde etkili olan kriterler belirlenerek kriterlerin ağırlıkları Analitik Hiyerarşi Prosesi (AHP) yöntemi ile hesaplanmıştır. Alternatiflerin sıralanması için karşılaştırmalı bir yaklaşım benimsenerek üç farklı sıralama algoritması ile alternatiflerin sıralaması elde edilmiştir. Sıralamaların belirlenmesi için TOPSIS, COPRAS ve PROMETHEE yöntemleri kullanılmıştır. Çalışmanın sonucunda çok kriterli karar verme (ÇKKV) yöntemleri ile işletmenin amaçlarına en uygun havya seti seçimi yapılmıştır.
{"title":"Havya setlerin seçimi için karşılaştırmalı çok kriterli karar verme yaklaşımı","authors":"Emre Yazıcı, Ufukcan Ebiri, Berat Alperen Kızılay, Onur Oruç, Hacı Mehmet Alakaş","doi":"10.56554/jtom.1260377","DOIUrl":"https://doi.org/10.56554/jtom.1260377","url":null,"abstract":"Günümüzde teknolojik ürünlerin kullanımı hayatımızın hemen hemen her alanında vardır. Bu ürünlerin üretiminde çeşitli amaçlar için kullanılan mekanik ve elektronik cihazlar bulunmaktadır. Bu cihazlardan biriside elektronik devre elemanlarının lehimlenmesinde kullanılan havya setleridir. İşletmeler için ciddi mali yükleri olan ve hassas kullanım isteyen havya setlerinin seçimi önemli bir karar problemi niteliğindedir. Bu çalışmada bir elektronik işletmesi için alınması planlanan havya setlerinin seçimi incelenmektedir. Havya setlerinin seçiminde etkili olan kriterler belirlenerek kriterlerin ağırlıkları Analitik Hiyerarşi Prosesi (AHP) yöntemi ile hesaplanmıştır. Alternatiflerin sıralanması için karşılaştırmalı bir yaklaşım benimsenerek üç farklı sıralama algoritması ile alternatiflerin sıralaması elde edilmiştir. Sıralamaların belirlenmesi için TOPSIS, COPRAS ve PROMETHEE yöntemleri kullanılmıştır. Çalışmanın sonucunda çok kriterli karar verme (ÇKKV) yöntemleri ile işletmenin amaçlarına en uygun havya seti seçimi yapılmıştır.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" December","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823951","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 utilization of 2-level factorial design has been extensive in the literature to observe the relationship between parameters and responses. Among the subjects open for exploration, the process of nanofiber creation stands out as an intriguing avenue to explore the correlations that emerge between variables and outcomes. The primary objective of the study is to establish the relationships between the parameters of electrospinning of polyamide 6 (PA6) solutions to obtain desired nanofiber diameters by response surface method (RSM) and two level full factorial design. The investigation hones in on four critical parameters related to the electrospinning of PA6 solutions. These parameters encompass factors like solution concentration, applied voltage, distance between the spinneret and the collector, and the flow rate of the solution. Employing a two-level factorial design, these parameters are methodically manipulated at two distinct levels each to systematically unravel their individual and collective impacts on nanofiber diameter outcomes. To understand the relationship between electrospinning process and these factors, these kind of experimental studies gives us much accurate results.
{"title":"Optimization of nanofiber diameter in the electrospinning of polyamide 6 by two-level factorial design","authors":"Deniz Efendioğlu, Şerife Akkoyun","doi":"10.56554/jtom.1363324","DOIUrl":"https://doi.org/10.56554/jtom.1363324","url":null,"abstract":"The utilization of 2-level factorial design has been extensive in the literature to observe the relationship between parameters and responses. Among the subjects open for exploration, the process of nanofiber creation stands out as an intriguing avenue to explore the correlations that emerge between variables and outcomes. The primary objective of the study is to establish the relationships between the parameters of electrospinning of polyamide 6 (PA6) solutions to obtain desired nanofiber diameters by response surface method (RSM) and two level full factorial design. The investigation hones in on four critical parameters related to the electrospinning of PA6 solutions. These parameters encompass factors like solution concentration, applied voltage, distance between the spinneret and the collector, and the flow rate of the solution. Employing a two-level factorial design, these parameters are methodically manipulated at two distinct levels each to systematically unravel their individual and collective impacts on nanofiber diameter outcomes. To understand the relationship between electrospinning process and these factors, these kind of experimental studies gives us much accurate results.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825257","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}
This research presents a comprehensive investigation into the accurate estimation of shear strength in rectangular reinforced concrete columns through advanced machine learning (ML) models. The study addresses the intricate challenge posed by shear strength complexity, which is crucial for evaluating column stability and ensuring structural integrity. Building upon a substantial dataset comprising 545 experimental observations sourced from diverse literature, this research establishes a robust foundation for predictive modeling. Four distinct ML regression models, Random Forest, Decision Tree, XGBoost, and LightGBM, are meticulously evaluated for their performance. The evaluation employs established metrics, including R2, RMSE, MAE, and MAPE to quantify their predictive capabilities. The outcomes highlight the models' robustness in capturing nuanced variations in shear strength, with impressive R2 values ranging from 93.6% to 93.9%, showcasing their exceptional ability to elucidate intricate shear behaviors. Furthermore, comparative analysis indicates the slightly superior performance of the Random Forest over the Decision Tree, highlighting the efficacy of ensemble methods in this context. Extending the exploration to include XGBoost and LightGBM, the study showcases their potential as accurate shear strength predictors. The performance of the models is validated through scatter plots and error distribution plots, confirming accurate shear strength predictions across various scenarios. This research contributes significantly to the advancement of structural engineering methodologies by highlighting the potential of ML to improve the accuracy of shear strength estimation. The findings not only underscore the exceptional performance of ML models but also provide valuable insights into their comparative effectiveness, paving the way for enhanced structural assessments in columns.
本研究通过先进的机器学习（ML）模型，对准确估算矩形钢筋混凝土柱的抗剪强度进行了全面调查。该研究解决了剪切强度复杂性带来的复杂挑战，这对于评估柱稳定性和确保结构完整性至关重要。本研究以大量数据集为基础，其中包括从各种文献中获取的 545 个实验观测数据，为预测建模奠定了坚实的基础。对随机森林、决策树、XGBoost 和 LightGBM 四种不同的 ML 回归模型进行了细致的性能评估。评估采用了既定指标，包括 R2、RMSE、MAE 和 MAPE，以量化它们的预测能力。结果凸显了这些模型在捕捉剪切强度细微变化方面的稳健性，R2 值从 93.6% 到 93.9% 不等，令人印象深刻，展示了它们阐明复杂剪切行为的卓越能力。此外，比较分析表明，随机森林的性能略优于决策树，突出了集合方法在此方面的功效。研究将探索范围扩大到 XGBoost 和 LightGBM，展示了它们作为精确剪切强度预测器的潜力。通过散点图和误差分布图验证了模型的性能，确认了在各种情况下剪切强度预测的准确性。这项研究通过强调 ML 在提高剪切强度估算准确性方面的潜力，为结构工程方法的进步做出了重大贡献。研究结果不仅强调了 ML 模型的卓越性能，还为它们的比较效果提供了宝贵的见解，为加强柱结构评估铺平了道路。
{"title":"Assessing Column Stability: A Comparative Study of Machine Learning Regression Models for Shear Strength Prediction","authors":"Aybike Özyüksel Çiftçioğlu","doi":"10.56554/jtom.1401261","DOIUrl":"https://doi.org/10.56554/jtom.1401261","url":null,"abstract":"This research presents a comprehensive investigation into the accurate estimation of shear strength in rectangular reinforced concrete columns through advanced machine learning (ML) models. The study addresses the intricate challenge posed by shear strength complexity, which is crucial for evaluating column stability and ensuring structural integrity. Building upon a substantial dataset comprising 545 experimental observations sourced from diverse literature, this research establishes a robust foundation for predictive modeling. Four distinct ML regression models, Random Forest, Decision Tree, XGBoost, and LightGBM, are meticulously evaluated for their performance. The evaluation employs established metrics, including R2, RMSE, MAE, and MAPE to quantify their predictive capabilities. The outcomes highlight the models' robustness in capturing nuanced variations in shear strength, with impressive R2 values ranging from 93.6% to 93.9%, showcasing their exceptional ability to elucidate intricate shear behaviors. Furthermore, comparative analysis indicates the slightly superior performance of the Random Forest over the Decision Tree, highlighting the efficacy of ensemble methods in this context. Extending the exploration to include XGBoost and LightGBM, the study showcases their potential as accurate shear strength predictors. The performance of the models is validated through scatter plots and error distribution plots, confirming accurate shear strength predictions across various scenarios. This research contributes significantly to the advancement of structural engineering methodologies by highlighting the potential of ML to improve the accuracy of shear strength estimation. The findings not only underscore the exceptional performance of ML models but also provide valuable insights into their comparative effectiveness, paving the way for enhanced structural assessments in columns.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826016","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}
Medine Demir, Pınar Usta, Sırma Zeynep Alparslan Gök
Akran grup durumları ve buna bağlı kurulan oyunlar çeşitli ekonomik ve yöneylem araştırması problemlerinde karşımıza çıkmaktadır. Örneğin ihalelerde koalisyonel davranış çalışıldığı zaman ortaya çıkan kooperatif oyunların bir kısıtlanmış sınıfı akran grup oyunları ile ifade edilmektedir. Akran grup durumlarında, organizasyonların sosyal yapılandırması, tüm temsilci grupların potansiyel olasılıklarını etkilemektedir. Katı bir hiyerarşide verilen her bir temsilci bir ya da daha çok temsilcinin yardımıyla doğrudan veya dolaylı olarak lider ile ilişkilidir. Bir temsilciye ait olan ekonomik olasılık hiyerarşi içerisindeki konumu ile kısıtlanmaktadır. Akran grubundaki temsilci için önemli olan grup lideri temsilcinin kendisi ve lideri arasında verilen hiyerarşide var olan tüm orta düzeydeki temsilcilerin oluşturduğu grup olarak karşımıza çıkmaktadır. Temsilcilerin böyle bir grubu akran grup olarak adlandırılmaktadır. Bu çalışmada akran grup durumları ve ona bağlı kurulan akran grup oyunları ele alınmıştır. Çalışmanın amacı akran grup oyunlarının gerçek yaşamımızda ihale durumları, sıralama durumları ve havaalanı durumları gibi farklı ekonomik durumlarda kullanılabilir olduğunu göstermektir. Ayrıca bu çalışmada akran grup oyunları ile ilişkili ekonomik ve yöneylem araştırması durumlarına değinilecektir.
{"title":"Akran Grup Durumları ve Oyun Teorisi ile Modellenmesi Üzerine","authors":"Medine Demir, Pınar Usta, Sırma Zeynep Alparslan Gök","doi":"10.56554/jtom.1292921","DOIUrl":"https://doi.org/10.56554/jtom.1292921","url":null,"abstract":"Akran grup durumları ve buna bağlı kurulan oyunlar çeşitli ekonomik ve yöneylem araştırması problemlerinde karşımıza çıkmaktadır. Örneğin ihalelerde koalisyonel davranış çalışıldığı zaman ortaya çıkan kooperatif oyunların bir kısıtlanmış sınıfı akran grup oyunları ile ifade edilmektedir. Akran grup durumlarında, organizasyonların sosyal yapılandırması, tüm temsilci grupların potansiyel olasılıklarını etkilemektedir. Katı bir hiyerarşide verilen her bir temsilci bir ya da daha çok temsilcinin yardımıyla doğrudan veya dolaylı olarak lider ile ilişkilidir. Bir temsilciye ait olan ekonomik olasılık hiyerarşi içerisindeki konumu ile kısıtlanmaktadır. Akran grubundaki temsilci için önemli olan grup lideri temsilcinin kendisi ve lideri arasında verilen hiyerarşide var olan tüm orta düzeydeki temsilcilerin oluşturduğu grup olarak karşımıza çıkmaktadır. Temsilcilerin böyle bir grubu akran grup olarak adlandırılmaktadır. Bu çalışmada akran grup durumları ve ona bağlı kurulan akran grup oyunları ele alınmıştır. Çalışmanın amacı akran grup oyunlarının gerçek yaşamımızda ihale durumları, sıralama durumları ve havaalanı durumları gibi farklı ekonomik durumlarda kullanılabilir olduğunu göstermektir. Ayrıca bu çalışmada akran grup oyunları ile ilişkili ekonomik ve yöneylem araştırması durumlarına değinilecektir.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826407","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}
Abstract − The Occupational health and safety is a discipline that prevents work accidents and occupational diseases with a proactive method. For employee health, countries have legal responsibilities within the scope of international conventions, and employers have national responsibilities. It is obligatory for employers to carry out risk assessments, provide occupational safety trainings, carry out inspections, employ occupational safety specialists and workplace physicians, and record all work regard work safety. In countries, inspections are carried out with labor inspectors and private companies provide occupational safety services. However, it is difficult for the authorities to monitor occupational safety in large industrial facilities such as petrochemicals and refineries, where the flow of workers, materials and work equipment is too much and very fast. As workplace capacity, number of employees and material flow increase, the type and number of work accidents and occupational diseases also increase. Artificial intelligence technologies facilitate these follow-ups. The purpose of this article is to investigate the proactive prevention of the factors that cause work accidents and occupational diseases with supervised machine learning algorithms in different sectors. A literature search was conducted on sciencedirect, scopus, googlescholar databases. It has been examined what kind of algorithms are used in which sectors. According to the studies in the literature and applications in different sectors, the data collected with sensors and stored with cloud computing are fed to the relevant supervised machine learning algorithms that have been trained and tested before, and the factors that cause work accidents and occupational diseases are determined in advance. In addition to sound, image, health, location and environment data, physical parameters such as distance, level and pressure are monitored instantly with sensors. Managers are warned when a dangerous situation or behavior is detected in and threshold values are exceeded. In addition to employee and vehicle location tracking, predictive maintenance is provided by monitoring the performance of work and production vehicles. With the decrease in occupational accidents and diseases, occupational safety performance increases and costs decrease.
{"title":"Prevention of Occupational Accidents and Occupational Diseases with Supervised Machine Learning Algorithms: Different Sector Applications","authors":"Adnan Karabulut, Mehmet Baran, Ergün Eraslan","doi":"10.56554/jtom.1245965","DOIUrl":"https://doi.org/10.56554/jtom.1245965","url":null,"abstract":"Abstract − The Occupational health and safety is a discipline that prevents work accidents and occupational diseases with a proactive method. For employee health, countries have legal responsibilities within the scope of international conventions, and employers have national responsibilities. It is obligatory for employers to carry out risk assessments, provide occupational safety trainings, carry out inspections, employ occupational safety specialists and workplace physicians, and record all work regard work safety. In countries, inspections are carried out with labor inspectors and private companies provide occupational safety services. However, it is difficult for the authorities to monitor occupational safety in large industrial facilities such as petrochemicals and refineries, where the flow of workers, materials and work equipment is too much and very fast. As workplace capacity, number of employees and material flow increase, the type and number of work accidents and occupational diseases also increase. Artificial intelligence technologies facilitate these follow-ups. The purpose of this article is to investigate the proactive prevention of the factors that cause work accidents and occupational diseases with supervised machine learning algorithms in different sectors. A literature search was conducted on sciencedirect, scopus, googlescholar databases. It has been examined what kind of algorithms are used in which sectors. According to the studies in the literature and applications in different sectors, the data collected with sensors and stored with cloud computing are fed to the relevant supervised machine learning algorithms that have been trained and tested before, and the factors that cause work accidents and occupational diseases are determined in advance. In addition to sound, image, health, location and environment data, physical parameters such as distance, level and pressure are monitored instantly with sensors. Managers are warned when a dangerous situation or behavior is detected in and threshold values are exceeded. In addition to employee and vehicle location tracking, predictive maintenance is provided by monitoring the performance of work and production vehicles. With the decrease in occupational accidents and diseases, occupational safety performance increases and costs decrease.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827083","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}
Sustainable aviation fuels (SAF) present a feasible solution to decarbonize modern aviation. Unlike traditional jet fuels, SAFs are produced in a variety of ways, thereby choosing one of these processes as a complicated Multi-Criteria Decision challenge that involves conflicting priorities. This study evaluates SAF production processes using a multicriteria methodology, PROMETHEE-2. With SAF technology in its nascent stage and limited data, several stakeholders in the aviation sector were enlisted to assist in the collection of data and preferences. The suggested framework’s strength lies in its adaptability to suit the subjective opinions of diverse stakeholders, selection of ranking system, and robustness of outcomes. This research engaged stakeholders in a participative manner to rank 11 (A1 to A11) SAF production paths based on 24 parameters categorized into social, environmental, economic, and technological evaluation criteria. Industry professionals were given a form to rate SAF production methods according to a performance criterion. Data is validated using fuzzy TOPSIS and fuzzy VIKOR and PROMETHEE-II to reduce professionals’ judgmental personal prejudice. Results indicate the optimal feedstock for SAF production is the direct transition process of CO2 to SAF (A11) in the gasification or Fischer-T synthesis group.
可持续航空燃料（SAF）是现代航空业去碳化的可行解决方案。与传统喷气燃料不同，可持续航空燃料的生产方式多种多样，因此选择其中一种生产工艺是一项复杂的多标准决策挑战，涉及相互冲突的优先事项。本研究采用多标准方法 PROMETHEE-2 对 SAF 生产工艺进行了评估。由于 SAF 技术尚处于起步阶段，数据有限，因此在收集数据和偏好的过程中邀请了航空部门的几位利益相关者提供协助。建议框架的优势在于其适应性，可满足不同利益相关者的主观意见、选择排序系统以及结果的稳健性。这项研究让利益相关者以参与的方式，根据社会、环境、经济和技术评估标准等 24 个参数，对 11 条（A1 至 A11）SAF 生产路径进行排序。行业专业人士获得了一份表格，根据绩效标准对 SAF 生产方法进行评分。使用模糊 TOPSIS、模糊 VIKOR 和 PROMETHEE-II 对数据进行验证，以减少专业人士的个人偏见判断。结果表明，生产 SAF 的最佳原料是气化或 Fischer-T 合成组中从 CO2 到 SAF 的直接转化过程（A11）。
{"title":"Assessment of Sustainable Aviation Fuel Production Methods: A Promethee II Approach","authors":"Ibrahim Temam Ibrahim, A. Kuşakcı, Amna Abdullah","doi":"10.56554/jtom.1406562","DOIUrl":"https://doi.org/10.56554/jtom.1406562","url":null,"abstract":"Sustainable aviation fuels (SAF) present a feasible solution to decarbonize modern aviation. Unlike traditional jet fuels, SAFs are produced in a variety of ways, thereby choosing one of these processes as a complicated Multi-Criteria Decision challenge that involves conflicting priorities. This study evaluates SAF production processes using a multicriteria methodology, PROMETHEE-2. With SAF technology in its nascent stage and limited data, several stakeholders in the aviation sector were enlisted to assist in the collection of data and preferences. The suggested framework’s strength lies in its adaptability to suit the subjective opinions of diverse stakeholders, selection of ranking system, and robustness of outcomes. This research engaged stakeholders in a participative manner to rank 11 (A1 to A11) SAF production paths based on 24 parameters categorized into social, environmental, economic, and technological evaluation criteria. Industry professionals were given a form to rate SAF production methods according to a performance criterion. Data is validated using fuzzy TOPSIS and fuzzy VIKOR and PROMETHEE-II to reduce professionals’ judgmental personal prejudice. Results indicate the optimal feedstock for SAF production is the direct transition process of CO2 to SAF (A11) in the gasification or Fischer-T synthesis group.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 97","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824501","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}
It is essential to identify the critical success factors due to their direct effects on the establishment of safety programs. These factors should also be prioritized to facilitate the establishment of process safety management (PSM) system in process industries. The fuzzy analytic hierarchy process (FAHP) was employed in this study to weight the critical success factors in implementing and executing safety programs for establishing a process safety management system. For this purpose, a few prominent process safety management models were reviewed, and the critical success factors of safety programs establishment were extracted. After that, a questionnaire was developed and distributed among the experts. The fuzzy analytic hierarchy process was then adopted to calculate the weights of factors for prioritization. This study aimed to determine the most effective factors in implementing and improving process safety management systems in process industries. Other factors will be effected in establishing process safety management in subsequent priorities, one after another.
{"title":"Implement a Process Safety Management System Based on the Identification of the most Critical Factors in the Establishment of Safety Programs, Using Fuzzy Analytic Hierarchy Process","authors":"Mazdak Khodadadi-karimvand, Zahra Sojoudi, Hamidreza Zakeri","doi":"10.56554/jtom.1281386","DOIUrl":"https://doi.org/10.56554/jtom.1281386","url":null,"abstract":"It is essential to identify the critical success factors due to their direct effects on the establishment of safety programs. These factors should also be prioritized to facilitate the establishment of process safety management (PSM) system in process industries. The fuzzy analytic hierarchy process (FAHP) was employed in this study to weight the critical success factors in implementing and executing safety programs for establishing a process safety management system. For this purpose, a few prominent process safety management models were reviewed, and the critical success factors of safety programs establishment were extracted. After that, a questionnaire was developed and distributed among the experts. The fuzzy analytic hierarchy process was then adopted to calculate the weights of factors for prioritization. This study aimed to determine the most effective factors in implementing and improving process safety management systems in process industries. Other factors will be effected in establishing process safety management in subsequent priorities, one after another.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826518","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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