This paper deals with the ideal convergence theorem of martingales of ideal Bochner integrablefunctions.First, a characterization of the properties of ideal convergent martingales is obtained.In this papermartingales of ideal Bochner integrable functions with values in a Banach space are treated.
{"title":"ON THE IDEAL CONVERGENCE OF MARTINGALES","authors":"Anita Caushi","doi":"10.59287/icsis.635","DOIUrl":"https://doi.org/10.59287/icsis.635","url":null,"abstract":"This paper deals with the ideal convergence theorem of martingales of ideal Bochner integrablefunctions.First, a characterization of the properties of ideal convergent martingales is obtained.In this papermartingales of ideal Bochner integrable functions with values in a Banach space are treated.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130566564","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}
Pınar Avcı, Sevgi Sümerli Sarigül, Ramazan Aldemir
Green energy production is crucial to protecting the environment and meeting future energydemand. Therefore, the study aims to investigate the relationship between oil price indices and green energystock prices. In this study, the data of Nasdaq OMX Wind and Nasdaq OMX Solar indices and crude oilindex (Oil) for the period of January 2015-March 2023 are collected and investigated using Fourier analysismethod. Therefore, in this study, the correlation between Oil and other (Solar and Wind) data values isexamined. Fourier power spectrum analysis method is used and according to the results of this powerspectrum analysis; The fact that there is a correlation between the Oil data values and both the Solar andWind data values is demonstrated by the average, maximum and standard deviation values obtained as aresult of the Fourier power spectrum and power spectrum. In conclusion, the findings of this study alsoprovide important recommendations for investors, managers and policy makers.
{"title":"Modeling the Variation between Green Energy Stock Prices and Oil Prices Using Fourier Analysis","authors":"Pınar Avcı, Sevgi Sümerli Sarigül, Ramazan Aldemir","doi":"10.59287/icsis.615","DOIUrl":"https://doi.org/10.59287/icsis.615","url":null,"abstract":"Green energy production is crucial to protecting the environment and meeting future energydemand. Therefore, the study aims to investigate the relationship between oil price indices and green energystock prices. In this study, the data of Nasdaq OMX Wind and Nasdaq OMX Solar indices and crude oilindex (Oil) for the period of January 2015-March 2023 are collected and investigated using Fourier analysismethod. Therefore, in this study, the correlation between Oil and other (Solar and Wind) data values isexamined. Fourier power spectrum analysis method is used and according to the results of this powerspectrum analysis; The fact that there is a correlation between the Oil data values and both the Solar andWind data values is demonstrated by the average, maximum and standard deviation values obtained as aresult of the Fourier power spectrum and power spectrum. In conclusion, the findings of this study alsoprovide important recommendations for investors, managers and policy makers.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129940129","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}
Cheating in e-exams is a real problem that threatens academic integrity and underminesconfidence in the feasibility of remote assessments. Many previous research papers and studies discussedthe issue of cheating in e-exams to prevent or reduce it through the use of the available technologies suchas the use of a web camera to monitor the examinee, some researchers proposed using specific software torestrict the examinee from accessing resources that are not permitted during the exam. This work aims todesign a Semi-automatic, AI-based e-proctoring system that mitigates cheating in e-exams. This researchproposed an innovative method to detect the possibility of cheating in the e-exams. This method relies onthe use of IoT and the Muse2 devices to detect the examinee's physiological state and determine whether itis “Normal” or “Abnormal” through the examinee`s EEG signal, where the abnormal state indicates apossibility of cheating. Convolutional Neural Network (CNN) was used to distinguish the examinee's state.The collected data from 15 students at the fourth stage of the Computer Engineering Department/ Universityof Mosul ranging between 23 and 26 years old showed that there is an obvious difference between the“calm” or “Normal” state and “stress” or “Abnormal” state in the EEG signal of the volunteer. The accuracyof the system was obtained for many testing datasets. The dataset was divided into two main datasets; the30 and 60 seconds duration time. The best accuracy obtained for the 30sec duration time was 97.37%, and97.14% for the 60sec duration time. The researchers concluded that the EEG signal contains a lot ofimportant information that can be utilized to detect the physiological state of the examinee and that theMuse2 device can be reliable to record the EEG signal.
{"title":"Cheating Detection in E-exams System Using EEG Signals","authors":"H. Mohammed, Qutaiba Ibrahim Ali","doi":"10.59287/icsis.601","DOIUrl":"https://doi.org/10.59287/icsis.601","url":null,"abstract":"Cheating in e-exams is a real problem that threatens academic integrity and underminesconfidence in the feasibility of remote assessments. Many previous research papers and studies discussedthe issue of cheating in e-exams to prevent or reduce it through the use of the available technologies suchas the use of a web camera to monitor the examinee, some researchers proposed using specific software torestrict the examinee from accessing resources that are not permitted during the exam. This work aims todesign a Semi-automatic, AI-based e-proctoring system that mitigates cheating in e-exams. This researchproposed an innovative method to detect the possibility of cheating in the e-exams. This method relies onthe use of IoT and the Muse2 devices to detect the examinee's physiological state and determine whether itis “Normal” or “Abnormal” through the examinee`s EEG signal, where the abnormal state indicates apossibility of cheating. Convolutional Neural Network (CNN) was used to distinguish the examinee's state.The collected data from 15 students at the fourth stage of the Computer Engineering Department/ Universityof Mosul ranging between 23 and 26 years old showed that there is an obvious difference between the“calm” or “Normal” state and “stress” or “Abnormal” state in the EEG signal of the volunteer. The accuracyof the system was obtained for many testing datasets. The dataset was divided into two main datasets; the30 and 60 seconds duration time. The best accuracy obtained for the 30sec duration time was 97.37%, and97.14% for the 60sec duration time. The researchers concluded that the EEG signal contains a lot ofimportant information that can be utilized to detect the physiological state of the examinee and that theMuse2 device can be reliable to record the EEG signal.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"430 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116002328","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}
Kanarya Adaları, kuzeybatı Afrika kıta sahanlığının dışında yer alan yedi adet volkanik adadanoluşan bir zincir oluşturur. La Palma Adası, Kanarya Adaları'nın en kuzeybatısında yer alan, beşinci enbüyük ve ikinci en yüksek adasıdır. La Palma Adası tarihte birçok denizaltı ve deniz üstü volkanikpatlamaya sahne olmuştur. Son olarak 1971 de meydana gelen Teneguía patlamasından yıllar sonragünümüzde 19 Eylül 2021’de yanardağ yeniden patlamıştır. Adada gerçekleşen bu patlama kayıtlara göretam 85 gün sürmüş ve 13 Aralık 2021 de ise patlamanın durduğu duyurulmuştur. Diferansiyel yapayaçıklıklı radar interferometri tekniği ile deprem, tasman, heyelan, obruk oluşumu, volkanik patlama gibidoğal ve doğal olmayan nedenlerle meydana gelen yüzey deformasyonları tespit edilebilmektedir. Buçalışmada, La Palma Adasın’da meydana gelen volkanik patlamanın neden olduğu yüzey deformasyonu,Avrupa Uzay Ajansı’nın (ESA) yapay açıklıklı radar uyduları olan Sentinel 1A ve Sentinel 1B uydu verilerive yine ESA’nın ücretsiz açık kaynaklı bir yazılımı olan SNAP kullanılarak belirlenmiştir. Yapılandeğerlendirmeler sonucunda, adanın güneybatı bölümünde uydu bakış doğrultusunda meydana gelenmaksimum kabarma miktarı yaklaşık olarak 31 cm ve adanın güneydoğu kesiminde uydu bakışdoğrultusunda meydana gelen maksimum kabarma miktarı da yaklaşık olarak 11 cm olarak elde edilmiştir.
{"title":"La Palma Adasında Meydana Gelen Volkanik Patlamanın Diferansiyel Yapay Açıklıklı Radar İnterferometrisi İle İncelenmesi","authors":"Hilal Yılmaz, Hüseyin Kemaldere","doi":"10.59287/icsis.607","DOIUrl":"https://doi.org/10.59287/icsis.607","url":null,"abstract":"Kanarya Adaları, kuzeybatı Afrika kıta sahanlığının dışında yer alan yedi adet volkanik adadanoluşan bir zincir oluşturur. La Palma Adası, Kanarya Adaları'nın en kuzeybatısında yer alan, beşinci enbüyük ve ikinci en yüksek adasıdır. La Palma Adası tarihte birçok denizaltı ve deniz üstü volkanikpatlamaya sahne olmuştur. Son olarak 1971 de meydana gelen Teneguía patlamasından yıllar sonragünümüzde 19 Eylül 2021’de yanardağ yeniden patlamıştır. Adada gerçekleşen bu patlama kayıtlara göretam 85 gün sürmüş ve 13 Aralık 2021 de ise patlamanın durduğu duyurulmuştur. Diferansiyel yapayaçıklıklı radar interferometri tekniği ile deprem, tasman, heyelan, obruk oluşumu, volkanik patlama gibidoğal ve doğal olmayan nedenlerle meydana gelen yüzey deformasyonları tespit edilebilmektedir. Buçalışmada, La Palma Adasın’da meydana gelen volkanik patlamanın neden olduğu yüzey deformasyonu,Avrupa Uzay Ajansı’nın (ESA) yapay açıklıklı radar uyduları olan Sentinel 1A ve Sentinel 1B uydu verilerive yine ESA’nın ücretsiz açık kaynaklı bir yazılımı olan SNAP kullanılarak belirlenmiştir. Yapılandeğerlendirmeler sonucunda, adanın güneybatı bölümünde uydu bakış doğrultusunda meydana gelenmaksimum kabarma miktarı yaklaşık olarak 31 cm ve adanın güneydoğu kesiminde uydu bakışdoğrultusunda meydana gelen maksimum kabarma miktarı da yaklaşık olarak 11 cm olarak elde edilmiştir.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128212927","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 the research, the electrooxidation method of the electrochemical treatment methods in thebatch system was explored a variety of experimental conditions for the treatment of wastewater from thepaper sector. 4 anodes and 4 cathodes sieve type plates with dimensions of 7 cm x 10 cm were positionedat 0,5 cm intervals in the 2000 mL volume jacketed glass reactor used for the treatment of wastewater fromthe paper industry, and 1200 mL wastewater was used in the testing. 4 coated Ti/IrO2/RuO2 electrodes ofthe sieve type were used as the anode material and 4 uncoated Ti electrodes of the sieve type were utilizedas the cathode material in the electrooxidation of effluent from the paper industry. In the experiments, theremoval rate of the COD (Chemical Oxygen Demand) pollutant parameter; The effects of supportingelectrolyte types and concentrations such as KCl, NaCl, NaNO3, and Na2SO4, and parameters such as initialpH value and current density of wastewater without supporting electrolyte were investigated. According tothe results obtained; In the experiments conducted at the natural pH value of wastewater, 18.55 mA/cm2was the most effective current density, 0.50 M NaCl was the most effective supporting electrolyte type andconcentration. The COD removal rate at the best conditions (37.11 mA/cm2current density) was 90.62%.In optimum conditions; 73.20% COD removal efficiency has been achieved.
在研究中，对电化学处理方法中的电氧化法在批处理系统中进行了多种实验条件的探索，用于造纸行业废水的处理。在造纸工业废水处理用的2000 mL容积夹套玻璃反应器中，以0.5 cm的间隔放置4个尺寸为7 cm × 10 cm的阳极和4个阴极筛板，试验用废水为1200 mL。采用4个筛型包覆Ti/IrO2/RuO2电极作为阳极材料，4个未包覆Ti电极作为阴极材料，对造纸废水进行了电氧化处理。在实验中，COD(化学需氧量)污染物的去除率参数;考察了支持电解质类型、浓度(KCl、NaCl、NaNO3和Na2SO4)以及初始ph值和电流密度等参数对无支持电解质废水的影响。根据所得结果;在废水自然pH值下进行的实验中，18.55 mA/cm2是最有效的电流密度，0.50 M NaCl是最有效的支撑电解质类型和浓度。在最佳电流密度(37.11 mA/cm2)下，COD去除率为90.62%。在最佳条件下;COD去除率达到73.20%。
{"title":"Evaluation of the Efficiency of Ti/IrO2/RuO2 Anode in COD Removal from Paper Industry Wastewaters by Electrooxidation Method","authors":"B. A. Fil, Cansu Elgün","doi":"10.59287/icsis.596","DOIUrl":"https://doi.org/10.59287/icsis.596","url":null,"abstract":"In the research, the electrooxidation method of the electrochemical treatment methods in thebatch system was explored a variety of experimental conditions for the treatment of wastewater from thepaper sector. 4 anodes and 4 cathodes sieve type plates with dimensions of 7 cm x 10 cm were positionedat 0,5 cm intervals in the 2000 mL volume jacketed glass reactor used for the treatment of wastewater fromthe paper industry, and 1200 mL wastewater was used in the testing. 4 coated Ti/IrO2/RuO2 electrodes ofthe sieve type were used as the anode material and 4 uncoated Ti electrodes of the sieve type were utilizedas the cathode material in the electrooxidation of effluent from the paper industry. In the experiments, theremoval rate of the COD (Chemical Oxygen Demand) pollutant parameter; The effects of supportingelectrolyte types and concentrations such as KCl, NaCl, NaNO3, and Na2SO4, and parameters such as initialpH value and current density of wastewater without supporting electrolyte were investigated. According tothe results obtained; In the experiments conducted at the natural pH value of wastewater, 18.55 mA/cm2was the most effective current density, 0.50 M NaCl was the most effective supporting electrolyte type andconcentration. The COD removal rate at the best conditions (37.11 mA/cm2current density) was 90.62%.In optimum conditions; 73.20% COD removal efficiency has been achieved.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130505231","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 COVID-19 was declared as an international health emergency concern by World HealthOrganization (WHO) in 2020. It caused about 7 million deaths and has taken interest in various disciplines.On the other hand, modeling infectious diseases can provide critical planning to control the outbreak andpublic health research. In this work, we consider three classical epidemic models, namely, the SI(Susceptible, Infectious) model, SIS (Susceptible, Infectious, Susceptible) model and SIR (Susceptible,Infectious, Recovered) model to simulate the spread of COVID-19 in Türkiye. We compare theirperformances by applying recent data of COVID-19 outbreak. We present numerical experiments toindicate which models can reproduce the epidemic dynamics qualitatively and quantitatively forforecasting.
{"title":"A Comparative Study for COVID-19 Forecasting Models","authors":"A. Sendur, Zafer Cakir","doi":"10.59287/icsis.600","DOIUrl":"https://doi.org/10.59287/icsis.600","url":null,"abstract":"The COVID-19 was declared as an international health emergency concern by World HealthOrganization (WHO) in 2020. It caused about 7 million deaths and has taken interest in various disciplines.On the other hand, modeling infectious diseases can provide critical planning to control the outbreak andpublic health research. In this work, we consider three classical epidemic models, namely, the SI(Susceptible, Infectious) model, SIS (Susceptible, Infectious, Susceptible) model and SIR (Susceptible,Infectious, Recovered) model to simulate the spread of COVID-19 in Türkiye. We compare theirperformances by applying recent data of COVID-19 outbreak. We present numerical experiments toindicate which models can reproduce the epidemic dynamics qualitatively and quantitatively forforecasting.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123327596","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}
Bu çalışmada son yıllarda yüksek antioksidan içeriği ve insan beslenmesindeki önemi ile dikkatçeken aronya bitkisinin in vitro ve in vivo ortamlarda tuz stresine karşı gösterdiği tepkiler araştırılmıştır.Bu kapsamda bitkilerin in vitro ve in vivo ortamlarda farklı tuz seviyelerinde morfolojik, fizyolojik vebiyokimyasal tepkileri incelenmiştir. Tuz konsantrasyonları in vitro ortamında 1/3 seyreltik MS, 7/10seyreltik MS, MS (kontrol), MS +1g L-1 NaCl, MS +3 g L-1 NaCl, MS +6 g L-1 NaCl, MS +8 g L-1 NaCl,MS +9 g L-1 NaCl; in vivo ortamda ise 2:1 oranında torf: perlit karışımı içeren 2 litrelik saksılara dikilmişolan aronya fidanlarına sulama suyuyla birlikte haftada 25mM NaCl şeklinde uygulanmıştır. Yapraklardatuz stresine bağlı olarak zararlanmanın başladığı andan itibaren topraktaki tuz seviyeleri belirlenerekdeneme sonlandırılmıştır. Araştırma sonuçlarına göre in vitro şartlarda 1/3 seyreltik MS, 7/10 seyreltik MS,MS (kontrol) ortamlarında explantlarda zarar meydana gelmemiş, MS +1g L-1 NaCl ve MS +3g L-1 NaCldozlarında sürgün ucu ve yapraklarda kahverengileşme, MS +6 g L-1 NaCl, MS +8 g L-1 NaCl, MS +9 g L1 NaCl ortamlarında ise ölüm meydana gelmiştir. in vivo şartlarda tuz uygulamasında bitkilerde sürgün ucuve yapraklarda kahverengileşme meydana gelmiştir. Tuz uygulamaları sonucu dozun artışına paralel olarakbitki boyu, bitki kuru ağırlığı, kök uzunluğu, klorofil içeriği, protein içeriği azalmış, yaprak nispi su içeriğive prolin içeriğinde ise değişiklik meydana gelmemiştir.
{"title":"Aronya (Aronia melanocarpa) Fidanlarının in Vitro ve in Vivo Şartlarda Tuz Stresine Toleranslarının Belirlenmesi","authors":"Mahmood Shaker Mahmood, Lütfi Pırlak","doi":"10.59287/icsis.583","DOIUrl":"https://doi.org/10.59287/icsis.583","url":null,"abstract":"Bu çalışmada son yıllarda yüksek antioksidan içeriği ve insan beslenmesindeki önemi ile dikkatçeken aronya bitkisinin in vitro ve in vivo ortamlarda tuz stresine karşı gösterdiği tepkiler araştırılmıştır.Bu kapsamda bitkilerin in vitro ve in vivo ortamlarda farklı tuz seviyelerinde morfolojik, fizyolojik vebiyokimyasal tepkileri incelenmiştir. Tuz konsantrasyonları in vitro ortamında 1/3 seyreltik MS, 7/10seyreltik MS, MS (kontrol), MS +1g L-1 NaCl, MS +3 g L-1 NaCl, MS +6 g L-1 NaCl, MS +8 g L-1 NaCl,MS +9 g L-1 NaCl; in vivo ortamda ise 2:1 oranında torf: perlit karışımı içeren 2 litrelik saksılara dikilmişolan aronya fidanlarına sulama suyuyla birlikte haftada 25mM NaCl şeklinde uygulanmıştır. Yapraklardatuz stresine bağlı olarak zararlanmanın başladığı andan itibaren topraktaki tuz seviyeleri belirlenerekdeneme sonlandırılmıştır. Araştırma sonuçlarına göre in vitro şartlarda 1/3 seyreltik MS, 7/10 seyreltik MS,MS (kontrol) ortamlarında explantlarda zarar meydana gelmemiş, MS +1g L-1 NaCl ve MS +3g L-1 NaCldozlarında sürgün ucu ve yapraklarda kahverengileşme, MS +6 g L-1 NaCl, MS +8 g L-1 NaCl, MS +9 g L1 NaCl ortamlarında ise ölüm meydana gelmiştir. in vivo şartlarda tuz uygulamasında bitkilerde sürgün ucuve yapraklarda kahverengileşme meydana gelmiştir. Tuz uygulamaları sonucu dozun artışına paralel olarakbitki boyu, bitki kuru ağırlığı, kök uzunluğu, klorofil içeriği, protein içeriği azalmış, yaprak nispi su içeriğive prolin içeriğinde ise değişiklik meydana gelmemiştir.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125308238","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}
Cargo sampling, which indicates the condition of the cargo on the ship, is one of the importantchemical tanker shipboard operations where human performance is prominent. Any negligence during thecargo sampling process can result in loss of human life, environmental disasters and financial losses.Therefore, evaluating human performance in the cargo sampling process on chemical tanker ships is vitalto avoid these. This paper aims to evaluate the contribution of human errors to the cargo sampling process.Hence, the Success Probability Index Method (SLIM) is conducted, incorporating Evidential Reasoning(ER) approach. While SLIM systematically predicts human error probabilities (HEP) consideringperformance shaping factors (PSFs), ER deals with the uncertain and subjective judgments of experts inthe step of rating and weighting PSFs. Based on the presented ER-SLIM model, HEP can be estimated byaggregating the belief degree of the experts and human performance for the cargo sampling process can beevaluated. The outputs of the paper provide a practical contribution to chemical tanker ship owners, healthsafety environment and quality (HSEQ) managers, maritime safety professionals and, chemical tankerofficers in order to minimize the probability of human error in the cargo sampling process, as well as thetheoretical background.
{"title":"Human error probability prediction for cargo sampling process on chemical tanker ship under extended SLIM Evidential Reasoning approach","authors":"Sukru Ilke Sezer, E. Akyuz, O. Arslan","doi":"10.59287/icsis.604","DOIUrl":"https://doi.org/10.59287/icsis.604","url":null,"abstract":"Cargo sampling, which indicates the condition of the cargo on the ship, is one of the importantchemical tanker shipboard operations where human performance is prominent. Any negligence during thecargo sampling process can result in loss of human life, environmental disasters and financial losses.Therefore, evaluating human performance in the cargo sampling process on chemical tanker ships is vitalto avoid these. This paper aims to evaluate the contribution of human errors to the cargo sampling process.Hence, the Success Probability Index Method (SLIM) is conducted, incorporating Evidential Reasoning(ER) approach. While SLIM systematically predicts human error probabilities (HEP) consideringperformance shaping factors (PSFs), ER deals with the uncertain and subjective judgments of experts inthe step of rating and weighting PSFs. Based on the presented ER-SLIM model, HEP can be estimated byaggregating the belief degree of the experts and human performance for the cargo sampling process can beevaluated. The outputs of the paper provide a practical contribution to chemical tanker ship owners, healthsafety environment and quality (HSEQ) managers, maritime safety professionals and, chemical tankerofficers in order to minimize the probability of human error in the cargo sampling process, as well as thetheoretical background.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127394687","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}
Traditional classification methods have difficulty in meeting the changing needs according tothe ever-increasing data piles. With the development of processors with high performance as memory andprocessing capabilities, deep learning-based methods have been widely used. A large amount of data isneeded to train a deep learning-based model, which is a computational science field. CIFAR-10, whichcontains images of 10 different objects in the world, is a benchmark dataset used effectively in imageidentification and classification. The proposed deep learning-based models should be tested in a computerenvironment in order to be used in real life. The proposed model performs the testing process with imagesthat it has never encountered during the training phase. In this article, a deep learning model is proposedthat performs classification on the CIFAR-10 dataset, which contains images of objects in the world. Aneffective classification method has been developed by removing the overfitting effect, if any, on theproposed model. Proposed model, classification process was carried out both with and without dataaugmentation. The data set used was expanded with random crop, scale transformation, vertical andhorizontal flipping data augmentation techniques. In the experimental studies, there was a big differencebetween the performance of the process using the data augmentation technique and the process without anyaugmentation. Using different augmentation techniques together or individually did not improve modelperformance. Proposed model achieved success rates of 91.93%, 93.63% and 90.49%, respectively,including train accuracy, precision, recall. According to the results obtained, it can be said that the studyhas achieved results that can compete with the literature.
{"title":"Measuring the Effect of Data Augmentation in a CNN-Based Deep Neural Network Model","authors":"Halit Çetiner, Sedat Metlek","doi":"10.59287/icsis.589","DOIUrl":"https://doi.org/10.59287/icsis.589","url":null,"abstract":"Traditional classification methods have difficulty in meeting the changing needs according tothe ever-increasing data piles. With the development of processors with high performance as memory andprocessing capabilities, deep learning-based methods have been widely used. A large amount of data isneeded to train a deep learning-based model, which is a computational science field. CIFAR-10, whichcontains images of 10 different objects in the world, is a benchmark dataset used effectively in imageidentification and classification. The proposed deep learning-based models should be tested in a computerenvironment in order to be used in real life. The proposed model performs the testing process with imagesthat it has never encountered during the training phase. In this article, a deep learning model is proposedthat performs classification on the CIFAR-10 dataset, which contains images of objects in the world. Aneffective classification method has been developed by removing the overfitting effect, if any, on theproposed model. Proposed model, classification process was carried out both with and without dataaugmentation. The data set used was expanded with random crop, scale transformation, vertical andhorizontal flipping data augmentation techniques. In the experimental studies, there was a big differencebetween the performance of the process using the data augmentation technique and the process without anyaugmentation. Using different augmentation techniques together or individually did not improve modelperformance. Proposed model achieved success rates of 91.93%, 93.63% and 90.49%, respectively,including train accuracy, precision, recall. According to the results obtained, it can be said that the studyhas achieved results that can compete with the literature.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125877982","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 paper presents a risk assessment approach for the case of possible explosions in a series oftanks. Explosion occurs in a tank and spreads to the adjacent or neighboring tanks with certain probabilities.An excel simulation procedure is applied to a case problem with a series of three tanks and the level of risksinvolved is determined with possible monetary loss values. The simulation is a useful tool for riskassessment of such cases and can be applied to other related problem areas in industry.
{"title":"Simulation Analysis for Risk Assessment of Explosions in a Series of Fuel Tanks","authors":"M. Savsar","doi":"10.59287/icsis.611","DOIUrl":"https://doi.org/10.59287/icsis.611","url":null,"abstract":"This paper presents a risk assessment approach for the case of possible explosions in a series oftanks. Explosion occurs in a tank and spreads to the adjacent or neighboring tanks with certain probabilities.An excel simulation procedure is applied to a case problem with a series of three tanks and the level of risksinvolved is determined with possible monetary loss values. The simulation is a useful tool for riskassessment of such cases and can be applied to other related problem areas in industry.","PeriodicalId":178836,"journal":{"name":"International Conference on Scientific and Innovative Studies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130151770","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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