A. Darabi, A. Shariati, R. Ghanaee, Ali Gholipour Soleimani
{"title":"Economic assessment of a hybrid turboexpander-fuel cell gas energy extraction plant","authors":"A. Darabi, A. Shariati, R. Ghanaee, Ali Gholipour Soleimani","doi":"10.3906/ELK-1303-7","DOIUrl":"https://doi.org/10.3906/ELK-1303-7","url":null,"abstract":"In this paper, a hybrid turboexpander-fuel cell (TE-FC) is investigated for extraction of electrical energy from high pressure gas in which the fuel cells are used for preheating the gas. Combination of expanders and fuel cells will reduce the fuel consumption and greenhouse gas emission. This study reveals that there are some circumstances in which the use of fuel cells in conjunction with a turboexpander is not recommended from an economic point of view. This paper seeks the region in which utilization of fuel cells along with a turboexpander presents maximum economic profit. Using the strategy provided in this paper one can decide whether to invest in the hybrid fuel cells-turboexpander or individually planned turboexpander with a conventional gas fired preheating system. Almost all effective parameters are taken into account and this can be considered a superiority of the present paper.","PeriodicalId":189800,"journal":{"name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","volume":"40 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128828881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A comprehensive comparison of features and embedding methods for face recognition","authors":"H. Yavuz, Hakan Cevikalp, R. Edizkan","doi":"10.3906/elk-1301-65","DOIUrl":"https://doi.org/10.3906/elk-1301-65","url":null,"abstract":"Face recognition is an essential issue in modern-day applications since it can be used in many areas for several purposes. Many methods have been proposed for face recognition. It is a difficult task since variations in lighting, instantaneous mimic varieties, posing angles, and scaling differences can drastically change the appearance of the face. To suppress these complications, effective feature extraction and proper alignment of face images gain as much importance as the recognition method choice. In this paper, we provide an extensive comparison of the state-of-theart face recognition methods with the most well-known techniques used in feature representation. In order to test the performances of these various methods, we created a new face database, named the ESOGU face database, which includes frontal images of 100 people taken under different lighting and posing conditions. In addition to our new database, we also present experiments on the well-known AR face database to obtain more general and reliable results. Moreover, we investigate the automatic face detection and automatic normalization of the face images in the databases. Based on this, we discuss the use of such automatic methods for face recognition applications.","PeriodicalId":189800,"journal":{"name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","volume":"138 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120881526","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}