Sharing information with AI (versus a human) impairs brand trust: The role of audience size inferences and sense of exploitation

This research examines whether and why disclosing information to AI as opposed to humans influences an important brand-related outcome—consumers’ trust in brands. Results from two pilot studies and nine controlled experiments (n = 2,887) show that consumers trust brands less when they disclose information to AI as opposed to humans. The effect is driven by consumers’ inference that AI shares information with a larger audience, which increases consumers’ sense of exploitation. This, in turn, decreases their trust in brands. In line with our theorizing, the effect is stronger among consumers who are relatively more concerned about the privacy of their data. Furthermore, the negative consequences for brands can be mitigated when (1) customers are informed that the confidentiality of their information is protected, (2) AI is anthropomorphized, and (3) the disclosed information is relatively less relevant

Cell load based user association for TETRA trunk systems

10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Bursa; Turkey; 29 November 2017 through 2 December 2017Increasing traffic in communication systems need efficient new cell selection algorithms to control the distribution of users. For better and seamless transmission, load balancing become critical factors for cell selection algorithms. Un-desired consequents in these situations may cause disasters specifically for the emergency cases in public safety services. In this paper, a cell selection algorithm is proposed for Terrestrial Trunked Radio (TETRA) based Professional Mobile Radio (PMR) systems. The proposed algorithm is designed to provide a fairer distribution of users among cells while keeping the number of received power measurement less. The performances of the proposed algorithm are obtained in urban and rural environment.Republic Ministry of Science, Industry and Technology under SAN-TEZ 0686.STZ.2014 Programme

New localities of scardinius elmaliensis bogutskaya, 1997 (Teleostei: Cyprinidae) and its phylogenetic relationship based on mt DNA cytb region sequences

This study was conducted to report five new localities out of its type locality for Scardinius elmaliensis in the Western Mediterranean Basin of Turkey by providing their morphological characteristics, and their phylogenetic relationship based on mtDNA Cytb region. The results revealed significant differences of all studied populations in terms of the morphometric characters despite their low genetic differences, but their meristic characters were not different. All six studied populations of S. elmaliensis including that of type locality formed a monophyletic group with S. erythrophthalmus as sister group. The molecular result confirmed distinction of S. elmaliensis from S. erythrophthalmus based on Cytb genetic distance of 1.6-1.8%. The occurrence of S. elmaliensis out of type locality was firstly reported in this study. Such knowledge is important for future conservation strategies and habitat management of this species

Bilişsel tanı modellerinde üst düzey düşünme becerilerinin ölçülmesinde ikili ve çoklu q matris yapılandırmasının karşılaştırılması

INTRODUCTION In literature, there are many definitions for higher-order thinking skills and the debates are ongoing. Still, there are some common points that define higher-order thinking skills like changing and transforming the existing knowledge, making original contributions, planning, and designing systems for various researchers. In the measurement of higher-order thinking skills, CDM classifications may be very helpful and inspiring. In this thesis, a dichotomous Q matrix and a polytomous Q matrix were modeled and the participants were classified with the appropriate models, DINA and pG-DINA. In this thesis, the main aim is to decide which CDM model can classify the participants in a more useful way and a better fit. For this study, the post-test data of the TUBITAK project "A Recommended Model to Increase Success Level of Turkey in Mathematics in International Wide-Scale Exams. Effectiveness of Cognitive Diagnosis Based Tracking Model" which numbered 115K531 was used. METHODOLOGY The research sample consists of 3705 students selected by random sampling method. The data set consists of the answers of the participants to a 30-question long mathematics test. DINA and pG-DINA models classified participants in three defined higher-order thinking skills in Q matrices. Polytomous Q matrix consists of four levels of each skill which are 0-1-2-3. The fit percentage CDM classifications for measured skills, the fit between posterior probabilities and true probabilities, relative fit indices, guess and slip parameters of the models and mean correct answers with z points of each latent class were analyzed to assess DINA and pG-DINA model in terms of usefulness. FINDINGS It has been observed that the fit of classification for each skill is approximately around %80 between DINA and pG-DINA models. True probabilities and posterior probabilities for each latent class are in a fit except for DINA class "000" and "001". DINA class tended to classify more for "001" than true probabilities and "000" less than true probabilities. Relative fit indices show consistently to each other that the pG-DINA model is a more useful model than the DINA model for measuring higher-order thinking skills. Guess and slip parameters between models are significantly different for most of the items according to z analysis made with z values of 1,64; 2,33 and 3,61 that shows significance levels of .05; .01 and .001. Mean of both parameters are lower in the pG-DINA model. In the perspective of classical test theory, total correct response means, and z value means are consistently rises as the number and levels of attributes increases. There are some uncertainties about some of the pG-DINA class hierarchical order, for those examples, it is quite hard to make a solid interpretation of classical test theory points. CONCLUSIONS In conclusion, for the DINA and the pG-DINA models, the probabilities of classifying attribute existence and attribute absence are similar. The DINA model showed some misfit to classify participants who has only the attribute "analytical reasoning" aka. latent class "001" and participants with no attribute aka. latent class "000" while the pG-DINA model showed not such a big misfit between true probabilities and posterior probabilities. Relative fit indices clearly and consistently point out that the pG-DINA is a more useful model to classify higher-order thinking skills. The parameters were significantly different for most of the items unexpectedly and pG-DINA models had lower values of guess and slip parameters. For both models, the latent classes were consistently have rising correct response and z score means as the number and level of attributes increases. To sum it all, the pG-DINA model showed more fit in analyzes and has already a potential of more informative classifications. It can be concluded that pG-DINA is a better model to use classification participants for their higher-order thinking skills.Bu tezde, "Uluslararası Geniş Ölçekli Sınavlarda Türkiye'nin Matematik Başarısını Arttırabilmek İçin Bir Model Önerisi: Bilişsel Tanıya Dayalı İzleme Modelinin Etkililiği." 115K531 numaralı TÜBİTAK projesi kapsamında elde edilen son test verileri kullanılmıştır. Araştırma için seçkisiz olarak seçilmiş 3705 öğrenciden oluşan örneklem kullanılmıştır. Kullanılan veri seti 115K531 numaralı TÜBİTAK projesi kapsamında ve bu tezde kullanılan 30 adet matematik sorusuna cevap veren öğrencileri içermektedir. Araştırma kapsamında üst düzey düşünme becerilerine yönelik sınıflandırmalar DINA ve pG-DINA modeller ile yapılmış ve Q matrisin hangi tür yapılandırma ile üst düzey düşünme becerilerini ölçmeye daha uygun olduğu saptanmaya çalışılmıştır. Çoklu Q matris düzenlemesi düzeyler 0-1-2-3 olmak üzere dört düzeyli olarak oluşturulmuştur. Araştırma kapsamında DINA ve pG-DINA modellerin becerileri ne düzeyde uyumlu sınıflayabildiğine yönelik bulgular, bütün becerilerin yaklaşık %80 oranında uyumlu sınıflandığını işaret etmektedir. Modellerin gerçek olasılıklar ve sonsal olasılıklar noktasında kendi içlerindeki uyumu incelendiğinde pG-DINA model DINA modeldeki bazı uyumsuzlukları göstermemektedir. Göreli uyum indeksleri daha küçük değerler alarak pG-DINA modelin daha uyumlu ve kullanışlı olduğuna işaret etmektedir. DINA ve pG-DINA modellerin parametreleri karşılaştırıldığında pG-DINA modelin parametre ortalama değerlerinin DINA modele göre düşük olduğu ve birçok parametre değerinin modeller arasında farklılık gösterdiği bulunmuştur. Klasik test teorisi bağlamında toplam puanlar ve z puanları incelendiğin hem DINA model hem de pG-DINA model örtük sınıfları özellik sayı ve düzeyi artışında tutarlı bir yükseliş göstermektedir. Bütün bu bilgiler ışığında pG-DINA modelin daha uyumlu olması ve daha detaylı bir tasnifleme ve tanımlama imkânı tanıması modeli özellikle pratikteki problemleri çözüldükten sonra kullanılabilir kılmaktadı

Experimental Investigation of the Microclimate Effects on Floating Solar Power Plant Energy Efficiency

Solar PVs are mostly built on uncultivated land. However, the increase in land values due to the increasing world population, the lack of suitable areas for potential PV plants, especially in the land-scarce countries, and the increasing energy need led researchers to seek new solutions. At this point, floating solar power plants emerge as a good alternative with their advantages such as not occupying land area and reducing water evaporation by covering the water surface. In this study, a floating photovoltaic power plant with 120 kWp installation power was installed on Buyukcekmece Lake, and the effect of the microclimate data on the produced energy of the system was investigated. Since the energy produced by PV panels is highly dependent on climate effects and there may be many climatic variations depending on the geographical conditions, experimental measurements have been made annually in this study and the results have been analyzed in order to contribute to the researches in this field. From the obtained results, it is seen that the most important factor that positively affects the energy produced is solar irradiance, while specific humidity, wave loads, and module temperature have a negative effect