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Citation - WoS: 5
Citation - Scopus: 5
Personalization in Marketing: How Do People Perceive Personalization Practices in the Business World
(California State Univ, 2023) Aksoy, Nilsah Cavdar; Kabadayi, Ebru Tumer; Yilmaz, Cengiz; Alan, Alev Kocak
With emerging digital technologies, personalization has become a key activity for marketing strategy to gain competitive success in customer relationships. The aim of this study is to develop and empirically assess a general measurement model of perceived personalization. Multiple data gathering processes and rigorous empirical testing procedures are employed to assess and validate the proposed measurement model. The perceived personalization scale developed in the study rests on the focus of what is personalized and includes three main categories: (1) individuallevel, (2) social-level, and (3) situation-based personalization. A multidimensional measure of personalization is developed based on these categories and is validated via several tests, including a test of nomological validity exploring the effects of perceived personalization on critical customer responses such as positive emotions, negative emotions, perceived sincerity, satisfaction, and behavioral intentions. These findings shed light on and open new avenues of development for this growing practice for both researchers and practitioners in marketing.
Citation - Scopus: 1
Man-Hour Prediction for Complex Industrial Products
(Institute of Electrical and Electronics Engineers Inc., 2023) Unal, Ahmet Emin; Boyar, Halit; Kuleli Pak, Burcu Kuleli; Cem Yildiz, Mehmet; Erten, Ali Erman; Güngör, Vehbi Çağrı
Accurately predicting the cost is crucial for the success of complex industrial projects. There can be several sources contributing to the cost. Traditional methods for cost estimation may not provide the required accuracy and speed to ensure the success of the project. Recently, machine learning techniques have shown promising results in improving cost estimation in various industrial products. This study investigates the performance of gradient-boosting machine learning models and feature engineering techniques on a private dataset of metal sheet project man-hour costs. A comparison of distinct models is conducted, key aspects influencing cost are identified, and the implications of incorporating domain-specific knowledge, including its advantages and disadvantages, are assessed based on performance outcomes. Experimental results demonstrate that LightGBM and XGBoost outperform other models, and feature selection and synthetic data generation techniques improve the performance. Overall, this study highlights the potential of machine learning in metal sheet sampling projects and emphasizes the importance of feature engineering and domain expertise for better model performance. © 2024 Elsevier B.V., All rights reserved.
Preface of Mini Symposia of 82-Statistical Methods and Applications in Engineering
(American Institute of Physics Inc., 2018) Greenacre, Zerrin Aşan; Atay, Mehmet Tarık; Gazeloǧlu, Cengiz
Preface of Mini Symposia of 82-Statistical Methods and Applications in Engineering
Citation - WoS: 8
Citation - Scopus: 8
Low Velocity Oblique Impact Behavior of Adhesively Bonded Single Lap Joints
(Taylor & Francis Ltd, 2019) Atahan, M. Gokhan; Apalak, M. Kemal; Atahan, M. Gokhan; Apalak, M. Kemal
This article addresses the low velocity oblique impact behavior of adhesively bonded single lap joints, and the effects of adherend strength and plastic ductility, impact energy, overlap length and oblique impact angle on the damage initiation and propagation in the adhesive layer. The experimental contact force-time, contact force-central displacement variations, axial separation lengths through the adhesive layer and permanent central deflections of overlap region, adhesive fracture surfaces were evaluated in detail. In the explicit finite element analyses, the adhesive layer was divided into three zones: upper and lower adhesive interfaces and the adhesive layer between these interfaces. The adhesive interfaces were modeled with cohesive zone approach to predict the failure initiation and propagation along both upper and lower adhesive-adherend interfaces, whereas the elastic-plastic material model was implemented for the middle adhesive region between the upper and lower adhesive interfaces. The proposed finite element model predicted reasonably the damage initiation and propagation through the adhesive layer, and the contact force-time/central displacement variations. Especially, the test and analysis results were compared with those of the adhesively bonded single lap joints under a normal transverse impact load. Increasing oblique impact angle resulted in lower peak contact forces, shorter contact durations and earlier damage initiation and propagation through the adhesive layer. The peak contact forces increased, the contact duration decreased with increasing impact energy. The strength and plastic deformation capability of adherend materials also affected the damage initiation and propagation through the adhesive layer as well as the after-impact joint geometry.
Ceramide Is a Key Factor That Regulates the Crosstalk Between TGF-Β and Sonic Hedgehog Signaling at the Basal Cilia to Control Cell Migration and Tumor Metastasis
(Federation Amer Soc Exp Biol, 2016) Gencer, Salih; Oleinik, Natalia; Dany, Mohammed; Ogretmen, Besim
Citation - WoS: 6
Citation - Scopus: 7
Synergistic Effect of Organic Acid on the Dissolution of Mixed Nickel-Cobalt Hydroxide Precipitate in Sulphuric Acid Solution
(Edp Sciences S A, 2019) Kursunoglu, Sait; Kursunoglu, Sait
The synergistic effect of an organic acid on the dissolution of nickel and cobalt from a mixed nickel-cobalt hydroxide precipitate (MHP) in sulphuric acid solution was studied. The effects of sulphuric acid concentration, the type of organic acid, leaching time, leaching temperature and stirring speed on the dissolution of the metals were experimentally investigated. It was observed that there is no beneficial effect of leaching temperature and stirring speed on the dissolution of the metals from the used MHP product which contains 37.7% Ni, 2.1% Co and 5.6% Mn. It was found that citric acid was more effective than oxalic acid for the dissolution of nickel and manganese, whereas oxalic acid was more effective than citric acid for the dissolution of cobalt. The addition of oxalic acid into the leaching system, however, affected the dissolution of nickel negatively because nickel precipitate as nickel oxalate. Therefore, the use of citric acid as synergist for sulphuric acid leaching of MHP product is more promising. After 60 min of leaching, 90.9% Ni, 84.2% Co and 98.1% Mn were dissolved under the following conditions: 0.75 M sulphuric acid, 2 g citric acid, 1/10 solid-to-liquid ratio, 400 rpm stirring speed and 30 degrees C temperature. The experimental results demonstrate that the addition of citric acid as a synergist for sulphuric acid leaching of a MHP product provides beneficial effect for the dissolution of nickel, cobalt and manganese.
Enhancing the Freeze Thaw Resistance of Pozzolanic Lime Mortars by Optimising the Dewatering Process
(Springer, 2024) Su-Cadirci, Tugce Busra; Ince, Ceren; Calabria-Holley, Juliana; Ball, Richard James
Freeze-thaw weathering is commonly attributed to the premature degradation of lime mortars. This study is unique as it explores how the effect of incorporating pozzolanic brick dust, combined with the dewatering mechanism, can influence the resistance to freeze-thaw cycling. The combination of brick dust and hydrated lime constitutes a pozzolanic lime mortar with hydraulic character. Importantly, the addition of brick dust was shown to play a crucial role by modifying the pore structure of the mortar matrix, which affected the water transport kinetics, and durability. This rigorous investigation evaluates the freeze and thaw resistance of hardened young (7-day) and old (180-day) mortars in both dewatered and non-dewatered conditions. Quantitative analysis of the microstructure highlights the role of brick dust and dewatering in densifying the matrix, refining the pore structure, and enhancing the freeze and thaw resistance. The benefits of dewatered brick dust mortars were demonstrated as young-age dewatered mortars showed similar resistance to freeze and thaw compared to the older-age non-dewatered mortars. This was attributed to the reduction of the water/binder ratio due to dewatering. It has been successfully demonstrated that freshly mixed mortars can be enhanced on-site through the addition of brick dust and coupling with a substrate that promotes dewatering. Using this approach to produce mortars with greater freeze thaw resistance will improve longevity and reduce failure rates. Impact will be realised in mortars for both new build and conservation applications.
The Revolarization of Industrial Heritage: AGU Sumer Campus in Kayseri, Turkey
(Scuola Pitagora Editrice, 2016) Asiliskender, Burak; Baturayoglu Yoney, Nilufer
The Sumerbank Textile Factory in Kayseri (1932-1935) was one of the earliest and largest industrial complexes designed and constructed following the foundation of the Turkish Republic. This was a striking ensemble of buildings with rationalist and functionalist vocabulary, which also functioned as an urban center of social and cultural modernization, providing work and cultural/recreational activities based on a secular and westernized way of life in contrast with the existing traditional society. The factory went through a number of technological changes during its production history, and was finally closed and abandoned in 1999. The site, located along the northern development corridor of the city, and its buildings soon became derelict and were vandalized. Various projects for its regeneration as a green area were not implemented. National designation followed for the site in 2003 and for the buildings in 2007. However no conservation or adaptive re-use plans were made until the allocation of the complex to Abdullah Gul University in 2012. Today the complex is being transformed into an urban university campus. The master plan dated 2014 aims to redefine the urban and socio-cultural function of the complex. The open campus concept will welcome the citizens to an architecturally preserved and restored site with a selection of new activities focusing on culture and education at different levels where the spirit and memory of place will be sustained.
Citation - WoS: 5
Citation - Scopus: 5
Formation of a Very High-Density Amorphous Phase of Carbon and Its Crystallization into a Simple Cubic Structure at High Pressure
(Elsevier B.V., 2021) Durandurdu, M.
We report a direct computational evidence of a two-step transformation sequence for tetrahedral amorphous carbon (ta-C) with increasing pressure. First, ta-C gradually transforms into a very high-density amorphous phase (VHDA) phase. Second, the VDHA phase converts into a simple cubic (SC) crystal. The structural defects formed during the high-pressure treatment play important roles for the formation and stabilization of the SC structure, rather than favorable the SC4 crystal. These phase transformations are reversible. © 2021 Elsevier B.V., All rights reserved.
Overlooked Strategies in Exploitation of Microorganisms in the Field of Building Materials
(SPRINGER-VERLAG SINGAPORE PTE LTD, 152 BEACH ROAD, #21-01/04 GATEWAY EAST, SINGAPORE, 189721, SINGAPORE, 2019) Ersan, Yusuf Cagatay
Resource efficiency reports released in the last decade point out construction industry as one of the key sectors that needs improvement in terms of ecological sensitivity. Being aware of this unfavorable reputation of construction industry, researchers embarked on replacing the ongoing conventional methods with more sustainable and environmentally friendly ones. One of the approaches for the latter is incorporating microorganisms into construction industry. Popularly investigated strategies can be listed as biocementation, biomasonry, biorepair, and bioconsolidation. Most of these processes are the outcome of a single approach, namely microbial-induced calcium carbonate precipitation (MICP) which was mostly investigated by means of axenic cultures and through one single microbial process, ureolysis. The state of the art about the latter is close to saturation. Moreover, approaching from the ecological wisdom perspective it can be said that some promising microbial strategies to achieve green building materials were overlooked and drawing attention to these strategies became necessary. This review study reveals the overlooked promising microbial strategies in the field of construction biotechnology. The context mainly discusses the potential of five overlooked microbial strategies: (i) heterotrophic and autotrophic MICP pathways, (ii) microbial strategies for surface treatment, (iii) microbial-induced corrosion inhibition, (iv) microbial sequestration of greenhouse gases, and (v) microbial- produced polymers, for their application in the field of construction materials. Further suggestions aim to integrate the microbial resource management approach and non-axenic cultures into the relevant fields of research for the development of environmentally friendly building materials.
Citation - WoS: 5
Node-Level Error Control Strategies for Prolonging the Lifetime of Wireless Sensor Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2021) Tekin, Nazli; Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri
In Wireless Sensor Networks (WSNs), energy-efficiency and reliability are two critical requirements for attaining a long-term stable communication performance. Using error control (EC) methods is a promising technique to improve the reliability of WSNs. EC methods are typically utilized at the network-level, where all sensor nodes use the same EC method. However, improper selection of EC methods on some nodes in the network-level strategy can reduce the energy-efficiency, thus the lifetime of WSNs. In this study, a node-level EC strategy is proposed via mixed-integer programming (MIP) formulations. The MIP model determines the optimum EC method (i.e., automatic repeat request (ARQ), forward error correction (FEC), or hybrid ARQ (HARQ)) for each sensor node to maximize the network lifetime while guaranteeing a pre-determined reliability requirement. Five meta-heuristic approaches are developed to overcome the computational complexity of the MIP model. The performances of the MIP model and meta-heuristic approaches are evaluated for a wide range of parameters such as the number of nodes, network area, packet size, minimum desired reliability criterion, transmission power, and data rate. The results show that the node-level EC strategy provides at least 4.4% prolonged lifetimes and 4.0% better energy-efficiency than the network-level EC strategies. Furthermore, one of the developed meta-heuristic approaches (i.e., extended golden section search) provides lifetimes within a 3.9% neighborhood of the optimal solutions, reducing the solution time of the MIP model by 89.6%.
What Does the Bibliometrics of an Interdisciplinary Field Tell Us?: The Case of Cognitive Science
(Seoul Natl Univ, inst Cognitive Science, 2023) Arik, Beril T.; Arik, Engin
This study investigated the bibliometric characteristics of an interdisciplinary field, Cognitive Science, which consists of contributions from diverse fields such as psychology, computer science, philosophy, linguistics, and anthropology, among others. The results showed that there were 4,711 publications in Web of Science between 1900 and 2017, with an exponential increase in the number of publications in recent years. About two-thirds of publications were classified as social science, of which 41% were in the field of psychology. Seventy percent of the publications were journal articles, half of the publications were written by researchers in the USA, and 95% of the publications were in English. Corpus analyses of abstracts and keywords showed that frequently used words included cognitive, science, research, theory, model, cognition, information, learning, and psychology. These analyses also showed that research in this field centered on the common themes of cognition, information, psychology, language, learning, representation, artificial intelligence, and mind before 2010 and focused on more restricted themes such as embodied and extended cognition, morality and religion, quantum, and music after 2010.
Hydroponic Agriculture with Machine Learning and Deep Learning Methods
(Gazi Mühendislik, 2023) Bulut,Nurten; Hacıbeyoğlu, Mehmet
In the face of the rapidly increasing population of our world today, researchers have turned to studies that use existing resources more effectively and efficiently in addition to searching for new resources in order to meet the rapidly decreasing needs such as raw materials and nutrients. The use of hydroponic agriculture, which is one of the alternative methods that can be used to meet the need for nutrients, which is one of the greatest needs of humanity, has become more popular day by day. The use of nutrient solution water instead of soil, the fact that it is not affected by weather conditions, that it can be applied indoors and that it can be vertically oriented are the characteristics that make hydroponic agriculture different from other agricultural methods. In addition, the lack of soil in this agricultural method brings with it the need for more observation and supervision. The aim of this study is to show that the observation and surveillance needs necessary to increase yield in hydroponic agriculture can be achieved using machine learning and deep learning methods. For this purpose, it has been observed that the efficiency of hydroponic agriculture has been increased in experimental studies conducted using five machine learning and deep learning methods. The deep learning method has achieved better results with 99.7% success compared to other methods.
Ensemble Churn Prediction for Internet Service Provider with Machine Learning Techniques
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2020) Goy, Gokhan; Kolukisa, Burak; Bahcevan, Cenk; Gungor, Vehbi Cagri
With the developing technology in every fields, a competitive marketing environment has been arised In this competitive environment analyzing customer behavior has become vital In particular, the ability to easily change any service provider has become vet) , critical for the company to continue its existence At the same time, the amount of financial resources spent on retaining instituters much less than to obtain new clients. In this context, the traditional methods of examining vast amount of data obtained today for establishing decision support systems have lost their validities In this study. we used a dataset which is provided by TurkNet serving as an internet service provider in Turkey. Various preprocessing steps has performed on this dataset and then classification algorithms ran. Afterwards results have obtained and compared. The results of these experiments analyzed in terms of the area under the curve value In this context the aunt successful classifier algorithm has been determined as the Random Trees algorithm with a value of 0.936.
Citation - Scopus: 2
Street Vendor Detection: Helping Municipalities Make Decisions With Actionable Insights
(IEEE, 2021) Agba, Hatice Nur; Tahir, Abdullah
Street vendors are quite common in countries across the world. By the prevalence of mobile surveillance systems, increasing demand for automatic detection of street vendors for further decisions and planning by the city administrators emerged. In this paper, an object detector is developed using a MobileNet SSD object detection algorithm to detect vendors on the street. For this study images were used, however, in the future this technique could be used for real time video footage from street cameras. Since this is the first study tackling this issue, a data set was created from scratch. The accuracy achieved by the algorithm is promising considering the size of the data set and the minimal computational power available. The goal of this research is to pave the way for more work to be done in this area and help municipalities improve their decision making process regarding street vendor activities in countries like Mexico, Pakistan, China, Turkey, etc.
Citation - WoS: 6
Citation - Scopus: 6
Experimental Measurements of Some Thermophysical Properties of Solid CdSb Intermetallic in the Sn-Cd Ternary Alloy
(Springer, 2016) Ozturk, Esra; Aksoz, Sezen; Altintas, Yemliha; Keslioglu, Kazum; Marasli, Necmettin
The equilibrated grain boundary groove shapes of solid CdSb in equilibrium with Sn-Cd-Sb eutectic liquid were observed from a quenched sample by using a radial heat flow apparatus. The Gibbs-Thomson coefficient, solid-liquid interfacial energy and grain boundary energy of the solid CdSb intermetallic were determined from the observed grain boundary groove shapes. The thermal conductivity of the eutectic solid and the thermal conductivity ratio of eutectic liquid to the eutectic solid in the Sn-35.8 at.%Cd-6.71 at.%Sb eutectic alloy at its eutectic melting temperature were also measured with a radial heat flow apparatus and a Bridgman-type growth apparatus, respectively.
Evaluation of Hybrid Classification Approaches: Case Studies on Credit Datasets
(Springer Verlag service@springer.de, 2018) Cetiner, Erkan; Güngör, Vehbi Çağrı; Kocak, Taskin
Hybrid classification approaches on credit domain are widely used to obtain valuable information about customer behaviours. Single classification algorithms such as neural networks, support vector machines and regression analysis have been used since years on related area. In this paper, we propose hybrid classification approaches, which try to combine several classifiers and ensemble learners to boost accuracy on classification results. We worked with two credit datasets, German dataset which is a public dataset and a Turkish Corporate Bank dataset. The goal of using such diverse datasets is to search for generalization ability of proposed model. Results show that feature selection plays a vital role on classification accuracy, hybrid approaches which shaped with ensemble learners outperform single classification techniques and hybrid approaches which consists SVM has better accuracy performance than other hybrid approaches. © 2018 Elsevier B.V., All rights reserved.
Citation - WoS: 54
Citation - Scopus: 58
Understanding the Effects of Artificial Intelligence on Energy Transition: The Moderating Role of Paris Agreement
(Elsevier, 2024) Chishti, Muhammad Zubair; Xia, Xiqiang; Dogan, Eyup
This study contributes to the existing literature by investigating and confirming a range of diverse outcomes related to the interplay of factors shaping the global energy transition (ET). Employing advanced methodologies, including the extension of the QVAR technique to short-term (SR), medium-term (MR), and long-term (LR) connectedness analysis, as well as the application of the CQ method to explore relationships within varying market conditions and timeframes, the study examines the interconnectedness of critical variables: artificial intelligence (AI), the Belt and Road Initiative (BRI), the Paris Agreement (PA), green technologies (GT), geopolitical risk (GPR), and ET. The findings highlight several crucial insights. Firstly, all selected variables demonstrate substantial interconnectedness across different time horizons, except for MR, which exhibits comparatively weaker connectedness than SR and LR. Secondly, independent series reveal diverse impacts on ET across various market conditions and periods. For example, in SR, most series produce mixed effects on ET, with BRI having primarily adverse consequences and GPR predominantly yielding positive impacts. In MR, the influence of AI, PA, and GT on ET varies, while BRI enhances ET, and GPR essentially hampers it. Notably, in LR, AI, BRI, PA, and GT significantly promote ET, while GPR disrupts its progress. Additionally, the study underscores the dynamic and time-varying nature of the relationships between AI, BRI, PA, GT, GPR, and ET across different market conditions, thus holding essential implications for shaping global policies to foster sustainable energy transitions.
Grasp based metaheuristic approach for dynamic flexible job shop scheduling problem.
(2020) Alper Hamza Dayı; Fatma Selen MADENOĞLU; Adil Baykasoğlu
Grasp
TGF-Β Receptor I/II Signaling at Primary Cilia Membrane Is Regulated by Ceramide to Modulate Cell Migration
(Elsevier Sci Ltd, 2016) Gencer, S.; Ogretmen, B.

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