Plazma glukoz konsantrasyonu, serum insülin direnci ve diastolik kan basıncı göstergeleri ile makine öğrenme yöntemleri kullanılarak diyabet hastalığının erken tanısı

Aim: It is a known fact that diabetes mellitus is increasing frequently and triggering many different diseases. Therefore, early diagnosis of the disease is important. This study was trying to predict the early diagnosis of the disease, according to machine learning methods by measuring plasma glucose concentration, serum insulin resistance, and diastolic blood pressure. Material and Methods: In the study, the public dataset from a website consists of 768 samples and nine variables. Three different machine learning strategies were used in the early diagnosis of diabetes mellitus (Support Vector Machine, Multilayer Perceptron, and Stochastic Gradient Boosting). 3 repeats and 10 fold cross-validation method was used to optimize the hyperparameters. The model’s performance parameters were evaluated based on accuracy, specificity, sensitivity, confusion matrix, positive predictive value (precision), negative predictive value, and AUC (area under the ROC curve). Results: According to the experimental results (the criteria of accuracy (0.79), sensitivity (0.57), specificity (0.91), positive predictive value (0.79), negative predictive value (0.80), and AUC (0.74)) the Support Vector Machine was more successful than other methods. Conclusion: Plasma glucose concentration, serum insulin resistance, and diastolic blood pressure markers are important indicators in the early diagnosis of diabetes mellitus. In this study, it was seen that these markers make a significant contribution to the early diagnosis of diabetes mellitus. However, it has been observed that these indicators alone will not be sufficient in the early diagnosis of the disease, especially since age, body mass index and pregnancy contribute significantly.Amaç: Diyabetin sıklıkla arttığı ve bir çok farklı hastalığı tetiklediği bilinen bir gerçektir. Bu nedenle hastalığın erken teşhisi önemlidir. Bu çalışmada plazma glukoz konsantrasyonu, serum insülin direnci ve diyastolik kan basıncı göstergelerinden, makine öğrenmesi yöntemlerine göre hastalığın erken teşhisi öngörülmeye çalışılmıştır. Materyal ve Metot: Çalışmada, bir web sitesinden alınan halka açık veri seti 768 örnek ve dokuz değişkenden oluşmaktadır. Diyabetin erken teşhisinde üç farklı makine öğrenme stratejisi kullanıldı (Destek Vektör Makineleri, Çok Katmanlı Algılayıcılar ve Stokastik Gradyan Artırma). Hiper parametre optimizasyonu için 3 tekrarlı 10 kat tekrarlı çapraz doğrulama yöntemi kullanıldı. Modellerin performansı doğruluk, seçicilik, duyarlılık, karışıklık matrisi, pozitif tahmin değeri (kesinlik), negatif tahmin değeri ve AUC (ROC eğrisi altında kalan alan) temel alınarak değerlendirilmiştir. Bulgular: Deneysel sonuçlara göre (doğruluk (0.79), duyarlılık (0.57), özgüllük (0.91), pozitif tahmin değeri (0.79), negatif tahmin değeri (0.80) ve AUC (0.74) kriterleri), Destek Vektör Makineleri diğer yöntemlere göre daha başarılı çıkmıştır. Sonuç: Diyabet hastalığının erken tanısında plazma glukoz konsantrasyonu, serum insülin direnci ve diastolik kan basinci belirteçleri önemli göstergelerdir. Bu çalışmada da bu belirteçlerin diyabetin erken tanısında önemli katkı sağladığı görülmüştür. Ancak tek başlarına bu göstergelerin hastalığın erken tanısında yeterli olmayacağı özellikle yaş, beden kitle indeksi ve gebeliğin de önemli derecede katkı sağladığı görülmüştür

Analysis of Amino Acid and Phenolic Content in Honey by UPLC-ESI-MS/MS

Honey is the very valuable natural animal product. It offers more than hundred nutritional substances to its consumers, human being and animals. Though major constituent of honey is sugar and water, honey also possesses amino acids, phenolic compounds, vitamins, minerals and enzymes. Amino acids are one of the important components of food. They provide the required building blocks and protein synthesis. Moreover, phenolic compounds in honey constitute the important quality parameter and account for its colour, sensory properties and antioxidant activity. Analysis of phenolic compound and amino acid is very important. They are generally used to identify the origin of honey. Amino acids in honey come from animals and vegetables. In the literature, there are several techniques concerning amino acid and phenolic compound identifications. In this chapter, usage of ultra-performance liquid chromatography with electrospray ionization coupled to tandem mass spectrometry (UPLC-ESI-MS/MS) techniques and methods for the determination of amino acids and phenolic compounds of honey is explained

An insight into R&D in emerging countries and prominent concepts within the literature

Multinational companies (MNCs) show an apparent tendency toward research and development (R&D) for the last three decades. Many kinds of research have recently focused on R&D in emerging countries (ECs) to reveal the differences from R&D in developed countries. This paper presents a literature review consisting of 23 articles from 2004-2019 on R&D in emerging markets. By conducting content analysis, it has been analyzed their prominent concepts and results. According to the research focus, the articles examined have been classified into five main groups – internationalization of R&D, R&D activities, R&D investments, technology-based R&D, R&D offshoring – along with articles that cannot be grouped. The main purpose of this study is to determine the current tendency of R&D in emerging markets. Thus, it provides to understand in which position R&D has in emerging markets, and under which circumstances it is successful. Furthermore, practitioners can benefit from the results of the presented study. The systematic evaluation of the findings contributes to the formation of a general view for future research

R&D in emerging markets: Literature review and future directions

Research and development (R&D) in emerging markets has become very popular in terms of multinational companies (MNCs). So, many researches on R&D in the field of International Business have attracted attention recently. This paper presents a literature review consisting of 22 articles from 2014-2019 on R&D in emerging markets. By conducting content analysis, it has been analyzed their prominent terms and results. Accordingly, this review has divided selected articles into three main groups - R&D internationalization, activities and investment -by extracting articles that cannot grouped. All headlines successively have contended results regarding advantages of internationalization, long-term investment choices, and diversification of R&D activities. To put it another way, this paper provides to understand in which position R&D has in emerging markets countries, and under which circumstances it is successful. The systematic evaluation of the findings contributes to the formation of a general view for future research

An investigation of ensemble learning methods in classification problems and an application on non-small-cell lung cancer data

This study aims to classify NSCLC death status and consists of patient records of 24 variables created by the open-source dataset of the cancer data site. Besides, basic classifiers such as SMO (Sequential Minimal Optimization), K-NN (K-Nearest Neighbor), random forest, and XGBoost (Extreme Gradient Boosting), which are machine learning methods, and their performances, and voting, bagging, boosting, and stacking methods from ensemble learning methods were used. Performance evaluation of models was compared in terms of accuracy, specificity, sensitivity, precision, and Roc curve. The basic classifier performances of random forest, SMO, K-NN, and XGBoost classifiers, their performances in the bagging ensemble learning method, and their performances in the boosting ensemble learning method are evaluated. In addition, Model 1 (random forest + SMO), Model 2 (XGBoost + K-NN), Model 3 (random forest + K-NN), Model 4 (XGBoost+SMO), Model 5 (SMO+K-NN + random forest), Model 6 (SMO+K-NN+XGBoost) and Model 7 (SMO+K-NN + random forest + XGBoost) the performances of in different metrics were expressed. The boosting ensemble learning method, which provides the maximum classification performance with XGBoost, achieved a 0.982 accuracy value, 0.971 sensitivity value, 0.989 precision value, 0.989 specificity value, and 0.998 ROC curve. It is recommended to use ensemble learning methods for classification problems in patients with a high prevalence of cancer to achieve successful results

Türkiye’de kentleşme süreci ve illerin gsyh verileri ile göç oranları arasındaki ilişkinin kümeleme analiziyle incelenmesi

Migration is a concept as old as human history. Large-scale migrations have occurred in every period of human history. There are many economic, social, political and legal reasons behind migration movements. It is known that economic reasons are the most determining factors in the occurrence of migration. Generally, the direction of migration is from rural to urban, underdeveloped regions to developed regions, east to west in Turkey. Population is largely concentrated in cities. Cities with a high level of economic development are the cities with the most populous population. While many socio-economic indicators can be used to reveal the level of economic development, an evaluation can also be made based on the GDP data of the provinces, which is considered as a combination of these indicators. In the study, a statistical significance relationship is sought between migration data and GDP data of the provinces. The analysis method used is the cluster analysis. According to the results, the basic hypothesis of the study is confirmed at a rate of 79%. That means, the provinces with high GDP levels receive immigration, while the provinces with low GDP emigrate.Göç, insanlık tarihi kadar eski bir kavramdır. İnsanlık tarihinin her döneminde büyük ölçekli göçler meydana gelmiştir. Göç hareketlerinin temelinde çok sayıda ekonomik, sosyal, kültürel, siyasi ve hukuki neden yer almaktadır. Göçün ortaya çıkmasında en belirleyici etkenin ekonomik nedenler olduğu bilinmektedir. Türkiye’de göçün yönü genellikle kırdan kente, az gelişmiş yörelerden gelişmiş yörelere, doğudan batıya doğru olmuştur. Nüfus, büyük ölçüde kentlerde toplanmıştır. Ekonomik gelişmişlik düzeyi yüksek olan kentler, nüfusu en kalabalık olan kentlerdir. Ekonomik gelişmişlik düzeyini ortaya koymak üzere çok sayıda sosyo- ekonomik göstergeden yararlanılabileceği gibi, bu göstergelerin bir bileşkesi olarak kabul ettiğimiz illerin Gayrisafi Yurtiçi Hâsıla (GSYH) verilerini temel alarak bir değerlendirme de yapılabilir. Bu çalışmada, illerin göç verileri ile illerin GSYH verileri arasında istatistiksel bir anlamlılık ilişkisi aranmaktadır. Kullanılan analiz yöntemi kümeleme analizidir. Sonuçlara göre çalışmamızın temel hipotezi %79 oranında doğrulanmaktadır. Yani GSYİH düzeyi yüksek olan iller göç alırken, GSYİH düzeyi düşük olan iller göç vermektedir

A low cost shading analyzer and site evaluator design to determine solar power system installation area

Shading analyzer systems are necessary for selecting the most suitable installation site to sustain enough solar power. Afterwards, changes in solar data throughout the year must be evaluated along with the identification of obstructions surrounding the installation site in order to analyze shading effects on productivity of the solar power system. In this study, the shading analysis tools are introduced briefly, and a new and different device is developed and explained to analyze shading effect of the environmental obstruction on the site on which the solar power system will be established. Thus, exposure duration of the PV panels to the sunlight can be measured effectively. The device is explained with an application on the installation area selected as a pilot site, Denizli, in Turkey. © 2015 Selami Kesler et al

Beytüllahim’e hicret

Neil Postman, televizyonun “Cesur Yeni Dünyamız”da bizi nasıl esir aldığını ve medyanın manevî yaşamımızı nasıl dönüştürdüğünü şu başlıkla ifadelendirmişti: Beytüllahim’den Kurtulmak! İbadetin, maneviyatın ve kutsalın mekândan ve zamandan soyutlanarak, sanallaşmasını ve dünyevîleşmesini anlatmak için bu cümleyi kuruyordu Postman. Bugün, Filistin ve Kudüs meselesi bizi derinden sarsarken konuya bir de bu açıdan bakmakta yarar olduğunu düşünüyorum. Sizi Beytüllahim’e yani Kudüs’e giden yola kendi ellerimizle taş koyup koymadığımızı düşünmeye davet ediyorum

Hydrogen Fuel Cell Powered Electric Vehicles And An Application Of Improvement For The Desorption Efficiency Of A Metal Hydride Storage

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2011İçinde bulunulan yüzyılda insanlarının en temel ihtiyaçlarından biri olan “ulaşım” yaygın olarak fosil yakıtlı araçlar tarafından karşılanmaktadır. Fosil yakıtların kıtlığı ve üretilmelerinden tüketilmelerine kadar olan çevrimde doğaya olan zararlı etkileri; alternatif, temiz enerji kaynaklarıyla (Ör: Güneş, Hidrojen) çalışan araçların gerekliliğini ortaya çıkarmaktadır. Bu çalışmada hidrojen yakıt hücreli elektrikli bir aracın, hidrojen saklama ortamının salıverme verimini arttırmak amaçlanmıştır. Aracın, polimer elektrolit membran tipli yakıt hücresi, hidrojen deposu olarak metal hidrid tüp grubu tarafından beslenmektedir. Araçta kullanılan metal hidrid saklama ortamlarının salıverme verimini arttırmak amacıyla kapalı devre ısı transfer sistemi kurulmuştur. Yapılan deneyler sonucunda kurulan sistemin, salınan hidrojen miktarını kayda değer oranda arttırdığı görülmüştür. Yakıt hücresi, çıkışında 800W güç üretecek şekilde yüklenmiş; ilk olarak ısı transfer sistemiyle, daha sonra ısı transfer sistemi olmadan, aynı şartlarda doldurulmuş metal hidrid tüpe bağlanmıştır. Isı transfer sistemi ile çalışan metal hidrid tüp 61 dakika boyunca; ısı transfer sistemi olmadan çalışan tüp ise sadece 18 dakika yakıt hücresini ortalama 800 W güç üretecek şekilde besleyebilmiştir.Fossil fuels are used by vehicles in transportation, which is one of the main needs of people. The share of transportation in fossil fuel usage is very high and daily oil consumption has been increasing. Shortage of fossil fuels and harmful effects’ have become main problem of today’s world. These causes force people to find new clean energy sources for vehicles to decrease pollutant gas emissions such as solar energy and hydrogen energy. In this study, it is aimed that improving the desorption efficiency of a hydrogen fuel cell vehicle’s hydrogen storage. The vehicle’s fuel cell type is PEM, which is sourced by a group of metal hydride hydrogen storage. To improve the desorption efficiency of the metal hydride storage; a closed-circuit heat transfer system was designed. The experiments showed that proposed system significantly increased the desorbed hydrogen amount from the metal hydride storage. The metal hydride storage was tested with and without proposed system while the PEM fuel cell was supplying 800 W output power. The storage could supply hydrogen for 61 minutes with proposed system, on the other hand; it could supply only 18 minutes without proposed system.Yüksek LisansM.Sc

Short-term effect of angiotensin converting enzyme inhibitor on choroidal vascularity

Purpose: To determine the effect of angiotensin-converting enzyme (ACE) inhibitors on choroidal vascularity using the binarization method in a group of treatment-naïve hypertensive patients. Methods: There were 48 treatment-naive hypertensive patients who were diagnosed according to the "2013 European Society of Hypertension/European Society of Cardiology" guideline and started angiotensin-converting enzyme inhibitor perindopril (Coversyl) in the study. As a control group, 48 healthy volunteers were randomly selected among people who attended the outpatient clinic for routine ophthalmological examination. Enhanced-depth imaging optical coherence tomography (EDI-OCT) images were captured at baseline and at 1 month after treatment. Binarization of the EDI-OCT images was performed by Image-J software. The choroidal thickness (CT), total choroidal area, luminal area, stromal area, and choroidal vascularity index (CVI) were measured. Results: There was a statistically significant increase in CT at all locations (subfoveal, nasal, and temporal) at 1 month after treatment compared with baseline (for all, p˂0.001). Choroidal structural parameters and the mean CVI were statistically significantly increased at 1 month after treatment (for all, p˂0.001). When compared, there was no statistically significant difference for the vascular parameters between the control group and the patient group at 1 month (for all, p>0.05). Conlusion: A statistically significant improvement was demonstrated in the choroidal vascular parameters except for the stromal area after treating with an ACE inhibitor in a group of hypertensive patients. © 2021 Elsevier B.V