Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1926

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17th International Conference on Mechatronics Technology, October 15-18, 2013, Jeju Island, Korea
(Elsevier, 2015) Hwang, Sung Ho; Kim, Joon-wan; Dorantes-Gonzalez, Dante Jorge
In recent years, Mechatronics has gained a lot of interest as more applications have been introduced to industry and society. The need for new mechatronic technologies in the form of advanced production systems, mechatronic devices, control systems, robotics, biomedical applications, MEMS, and measurement systems, among others, is very much required in improving productivity and competitiveness in many industries. Thus, this conference was organized to address the state-of-the-art technology for the benefit of researchers and users, and this time the conference made a special focus on the topic: Sustainable Mechatronics Technology.
18 - Acoustic and Mechanical Properties of Biofibers and Their Composites
(Elsevier, 2022) Koç, Büşra; Genç, Garip; Körük, Hasan
In this study, the acoustic and mechanical properties of many biofibers and their composites are presented. First, the sound absorption coefficients and transmission losses of commonly used natural fibers and their composites are presented, by clearly reporting the thickness of the samples, for three different frequency ranges (<500 Hz: low, 500–2000 Hz: medium, and >2000 Hz: high). In addition, the sound absorption coefficients (for low- and medium-frequency ranges) and noise reduction coefficients of some 40-cm-thick samples are overlaid in order to directly compare their performances. Second, the physical properties, such as the density, diameter, and length of biofibers, and mechanical properties, such as the damping (or loss factor) and Young’s modulus of biofibers and their composites, are presented in detail. For comparison purposes, the acoustic and mechanical properties of some conventional materials, such as carbon and glass fibers, are included in the tables and figures. Finally, the effects of some parameters, such as pretreatment, fiber diameter, fiber/matrix ratio, moisture content, manufacturing and machining parameters/techniques, and measurement conditions/methods, on the acoustic and mechanical properties of natural materials are presented. Furthermore, current applications and potential usage areas of natural fibers are briefly discussed.
19 - Identification of the Elastic and Damping Properties of Jute and Luffa Fiber-Reinforced Biocomposites
(Elsevier, 2022) Genç, Garip; Saygılı, Yusuf; Körük, Hasan; Şanlıtürk, Yusuf Kenan
Although there are many studies in the literature on the static mechanical properties of biomaterials such as tensile strength, the dynamic mechanical properties of biomaterials such as modal loss factors have not been investigated in detail. In this study, the Young’s moduli and damping (or loss factors) of some jute and luffa fiber-reinforced biocomposites are investigated. The effects of fiber/resin ratio and thickness on the mechanical properties of the jute and luffa composites are identified via an experimental approach. For this purpose, acoustic and structural frequency response functions of some homogeneous and hybrid jute and luffa composite plates with different fiber/resin ratios and thicknesses are measured. By analyzing the measured frequency response functions using the circle-fit method, the modal frequencies and loss factors of the homogeneous and hybrid composite plates are determined. By assuming that the homogeneous plates are isotropic, the same plates are modeled using the finite element method, and by comparing the experimental and theoretical natural frequencies, the elastic properties of the homogeneous plates are determined. In addition, the same homogeneous plates are modeled by considering an anisotropic material model, and the associated material properties are determined. By using the identified material properties, the finite element models of the hybrid composite plates are developed, and by comparing their experimental and theoretical natural frequencies, the identified elastic material properties are evaluated and validated.
2D Modeling Temperature Development of Mass Concrete Structures at Early Age
(fib. The International Federation for Structural Concrete, 2018) Yıkıcı, T.A.; Chen, R.H.L.
In this paper, a 2D finite volume analysis methodology was used to predict temperature development within three different bridge pier caps. MATLAB® was employed to generate a program that solves the governing heat transfer equation where development of thermo-physical concrete properties was defined as a function of degree of hydration. The rate of heat generation was obtained experimentally via adiabatic calorimetry and the activation energy was determined following the ASTM C 1074 procedure to implement equivalent age concept. 2D finite volume analysis results were presented in comparison with the recorded concrete temperatures from the field. Accordingly, temperature time histories at the center and the side surface of the bridge pier caps were predicted reasonably well using the concrete mixture information and the measured concrete hydration properties. © Springer International Publishing AG 2018.
Acoustic and Mechanical Properties of Luffa Fiber-Reinforced Biocomposites
(Elsevier, 2019) Genç, Garip; Körük, Hasan
This chapter presents an overview of acoustic and mechanical behaviors of luffa fiber reinforced biocomposites. A growing number of studies are examining the composites of biodegradable fibers such as flax, hemp, kenaf and luffa due to the adverse effects of chemical materials on nature. The low cost and superior acoustic and acceptable mechanical properties of biocomposites make them very attractive for practical applications such as sound and vibration isolation. However, the acoustic and mechanical characteristics of biocomposites and their dynamic behaviors should be fully determined before considering them for practical applications. In this chapter, acoustic properties, such as sound absorption and transmission loss, and mechanical properties, such as damping and elasticity of luffa fiber reinforced composites, are presented. The variations in acoustic and mechanical properties due to different samples and manufacturing process are explored.
An Adaptive Admittance Controller for Collaborative Drilling With a Robot Based on Subtask Classification Via Deep Learning
(Elsevier, 2022) Başdoğan, Çağatay; Niaz, P. Pouya; Aydın, Yusuf; Güler, Berk; Madani, Alireza
In this paper, we propose a supervised learning approach based on an Artificial Neural Network (ANN) model for real-time classification of subtasks in a physical human–robot interaction (pHRI) task involving contact with a stiff environment. In this regard, we consider three subtasks for a given pHRI task: Idle, Driving, and Contact. Based on this classification, the parameters of an admittance controller that regulates the interaction between human and robot are adjusted adaptively in real time to make the robot more transparent to the operator (i.e. less resistant) during the Driving phase and more stable during the Contact phase. The Idle phase is primarily used to detect the initiation of task. Experimental results have shown that the ANN model can learn to detect the subtasks under different admittance controller conditions with an accuracy of 98% for 12 participants. Finally, we show that the admittance adaptation based on the proposed subtask classifier leads to 20% lower human effort (i.e. higher transparency) in the Driving phase and 25% lower oscillation amplitude (i.e. higher stability) during drilling in the Contact phase compared to an admittance controller with fixed parameters.
Adaptive Boosting of Dnn Ensembles for Brain-Computer Interface Spellers
(IEEE, 2021) Çatak, Yiğit; Aksoy, Can; Özkan, Hüseyin; Güney, Osman Berke; Koç, Emirhan; Arslan, Şuayb Şefik
Steady-state visual evoked potentials (SSVEP) are commonly used in brain computer interface (BCI) applications such as spelling systems, due to their advantages over other paradigms. In this study, we develop a method for SSVEP-based BCI speller systems, using a known deep neural network (DNN), which includes transfer and ensemble learning techniques. We test performance of our method on publicly available benchmark and BETA datasets with leave-one-subject-out procedure. Our method consists of two stages. In the first stage, a global DNN is trained using data from all subjects except one subject that is excluded for testing. In the second stage, the global model is fine-tuned to each subject whose data are used in the training. Combining the responses of trained DNNs with different weights for each test subject, rather than an equal weight, provide better performance as brain signals may differ significantly between individuals. To this end, weights of DNNs are learnt with SAMME algorithm with using data belonging to the test subject. Our method significantly outperforms canonical correlation analysis (CCA) and filter bank canonical correlation analysis (FBCCA) methods.
Adaptive Human Force Scaling Via Admittance Control for Physical Human-Robot Interaction
(IEEE, 2021) Başdoğan, Çağatay; Aydın, Yusuf; Hamad, Yahya M.
The goal of this article is to design an admittance controller for a robot to adaptively change its contribution to a collaborative manipulation task executed with a human partner to improve the task performance. This has been achieved by adaptive scaling of human force based on her/his movement intention while paying attention to the requirements of different task phases. In our approach, movement intentions of human are estimated from measured human force and velocity of manipulated object, and converted to a quantitative value using a fuzzy logic scheme. This value is then utilized as a variable gain in an admittance controller to adaptively adjust the contribution of robot to the task without changing the admittance time constant. We demonstrate the benefits of the proposed approach by a pHRI experiment utilizing Fitts’ reaching movement task. The results of the experiment show that there is a) an optimum admittance time constant maximizing the human force amplification and b) a desirable admittance gain profile which leads to a more effective co-manipulation in terms of overall task performance.
Adding Rapid-Acting Insulin or Glp-1 Receptor Agonist To Basal Insulin: Outcomes in a Community Setting
(2015) Dalal, Mehul R; DiGenio, Andres; Xie, Lin; Başer, Onur
To evaluate real-world outcomes in patients with type 2 diabetes mellitus (T2DM)receiving basal insulin, who initiate add-on therapy with a rapid-acting insulin (RAI) or aglucagon-like peptide 1 (GLP-1) receptor agonist.Data were extracted retrospectively from a U.S. health claims database. Adults withT2DM on basal insulin who added an RAI (basal+RAI) or GLP-1 receptor agonist (basal+GLP-1) were included. Propensity score matching (1 up to 3 ratio) was used to control for differencesin baseline demographics, clinical characteristics, and health resource utilization. Endpointsincluded prevalence of hypoglycemia, pancreatic events, all-cause and diabetes-relatedresource utilization, and costs at 1 year follow-up. Overall, 6,718 matched patients were included: 5,013 basal+RAI and 1,705basal+GLP1. Patients in both groups experienced a similar proportion of any hypoglycemicevent (P = .4079). Hypoglycemic events leading to hospitalization were higher in the basal+RAIcohort (2.7% vs. 1.8%; P = .0444). The basal+GLP-1 cohort experienced fewer all-cause(13.55% vs. 18.61%; P<.0001) and diabetes-related hospitalizations (11.79% vs. 15.68%;P<.0001). The basal+GLP-1 cohort had lower total all-cause health care costs ($18,413 vs.$20,821; P = .0002), but similar diabetes-related costs ($9,134 vs. $8,985; P<.0001) comparedwith the basal+RAI cohort. Add-on therapy with a GLP-1 receptor agonist in T2DM patients receiving basalinsulin was associated with fewer hospitalizations and lower total all-cause costs compared withadd-on therapy using a RAI, and could be considered an alternative to a RAI in certain patientswith T2DM, who do not achieve effective glycemic control with basal insulin.
Affection for Nouvel Architecture: on Contemporary (islamic) Architecture and Affect
(Intellect Ltd., 2022) Yücel, Şebnem
[No abstract available]
All You Fear Is Love: the Roles of Rejection by Intimate Others
(Wiley, 2023) Aracı-İyiaydın, Ayşegül; Toplu-Demirtaş, Ezgi; Rohner, Ronald P. P.; Akçabozan-Kayabol, Nazlı Büşra
Interpersonal acceptance-rejection theory (IPARTheory) asserts that recollections of parental rejection in childhood tend to result in psychological maladjustment and intimacy problems in later romantic relationships. Informed by IPARTheory, we investigated the association between maternal & paternal rejection, and fear of intimacy by the mediating role of psychological maladjustment in a Turkish sample with 462 mostly young adults. We further explored the moderator role of gender in Model 1 and the moderating roles of both gender and intimate partner rejection in Model 2. Model 1 revealed that adults who had experienced maternal and paternal rejection in childhood tended to be psychologically maladjusted. Consequently, they also tended to have a fear of intimacy, regardless of gender. Model 2 revealed that women who recall having been rejected in childhood by their mothers tended to be psychologically maladjusted and to have a significant fear of intimacy when they also experienced moderate or more than moderate intimate-partner rejection. However, both women and men who experienced paternal rejection in childhood tended to be psychologically maladjusted and to experience a greater fear of intimacy when they perceived any degree of intimate partner rejection. Implications of the results for theory, research, and practice are discussed.
Alternative Data Sources and Psychometric Scales Supported Credit Scoring Models
(IEEE, 2023) Şahin, Türkay; Filiz, Gözde; Çakar, Tuna; Özvural, Özden Gebizlioğlu; Nicat, Şahin
This study aims to evaluate individuals with limited access to banking services and enhance credit scoring models with alternative data sources. A psychometric-based credit scoring model was developed and tested. Despite limited data, significant potential findings were obtained. However, clarification of the distinction between credit payment intention and ability and validation of the results with more data are necessary.
Analysis of a New Business Model To Fundraise Non-Governmental Organizations Using Fuzzy Cognitive Maps
(IOS Press, 2020) Aytore, Can; Sergi, Duygu; Ucal Sari, Irema
Fundraising is one of the most critical issues for non-governmental organizations (NGOs) to carry out their projects. In this paper, a search engine project which aims to find additional financial sources and increase donations for NGOs is proposed. The proposed search engine project is analyzed using fuzzy cognitive maps (FCMs) to define and manage factor influences on the success of the project. FCMs are useful tools to define long term effects of important factors for a system. First casual relations of the factors are determined and then using sigmoid function for learning algorithm, the equilibrium state for the system is obtained. It is found that the factors generating monetary values are the most important ones for the project to be successful in long term.
An Analysis of Elementary School Children's Fractional Knowledge Depicted With Circle, Rectangle, and Number Line Representations
(Springer, 2015) Tunç-Pekkan, Zelha
It is now well known that fractions are difficult concepts to learn as well as to teach. Teachers usually use circular pies, rectangular shapes and number lines on the paper as teaching tools for fraction instruction. This article contributes to the field by investigating how the widely used three external graphical representations (i.e., circle, rectangle, number line) relate to students' fractional knowledge and vice versa. For understanding this situation, a test using three representations with the same fractional knowledge framed within Fractional Scheme Theory was developed. Six-hundred and fifty-six 4th and 5th grade US students took the test. A statistical analysis of six fractional Problem Types, each with three external graphical representations (a total of 18 problems) was conducted. The findings indicate that students showed similar performance in circle and rectangle items that required using part-whole fractional reasoning, but students' performance was significantly lower on the items with number line graphical representation across the Problem Types. In addition, regardless of the representation, their performance was lower on items requiring more advanced fractional thinking compared to part-whole reasoning. Possible reasons are discussed and suggestions for teaching fractions with graphical representations are presented. Copyright of Educational Studies in Mathematics is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.
Analysis of Intelligent Software Implementations in Air Cargo Using Fermatean Fuzzy Codas Method
(Springer, 2022) Sergi, Duygu; Sarı, İrem Ucal; Kuchta, Dorota
The chapter focuses on the problem of analyzing and selecting intelligent software in Air Cargo in the concept of Aviation 4.0. First, the notions, problems and challenges linked to air cargo are discussed. Recent developments, ongoing innovative projects and unfilled gaps in the area of intelligent air cargo software are presented. Next, the proposed method to analyze a select software to be used by air cargo companies is described. It is a modified version of one of the recent multi-criteria decision-making methods, called CODAS. Its original, crisp version and its existing fuzzy extensions are first presented. Next, an original extension of the method, using Fermatean fuzzy sets, is proposed. In the application section a logistics company is considered, which is facing the problem of selecting software supporting the air cargo process. The criteria are selected by experts holding various positions in the company, and three alternatives of air cargo software provider are determined. Then, the proposed method is applied to solve the intelligent software selection problem. Finally, conclusion and future research perspectives are given.
An Analysis of the Causes of Water Crisis in the Euphrates-Tigris River Basin
(Springer, 2014) Kibaroğlu, Ayşegül; Maden, Tuğba Evrim
The Euphrates-Tigris river basin now faces severe water crisis that have been fueled by national development projects in a mainly water-scarce region. Increasing demand-induced scarcity is further complicated by a history of international tensions between the three riparian nations of Turkey, Syria and Iraq and has occurred in a changing climate. Water is a critical security issue for these nations. This essay analyses the causes of the water crises by reviewing the historical hydropolitical international relations of the region.
An Analysis of Turkey’s Water Diplomacy and Its Evolving Position Vis-À International Water Law
(Taylor & Francis, 2014) Kibaroğlu, Ayşegül
This article analyzes Turkey’s transboundary water policy by examining its institutional framework and basic principles. It explores the reasons why Turkey voted against the UN Watercourses Convention. Turkey’s harmonization with the water law of the European Union is also scrutinized with an aim to assess its implications for transboundary water policy making. Turkish water diplomacy faces new challenges, such as the devastating impacts of prolonged droughts as well as ongoing instability and conflicts in Syria and Iraq. Hence, it is imperative for Turkey to systematically reconcile its water policy objectives in accordance with the global norms that are adopted in this field
Analytical Approaches in Customer Relationship Management
(IEEE, 2023) Akata, Mustafa Aşkım; Ergin, Kaan; Kaya, Büşra; Kızılay, Ayşe; Çakar, Tuna; Şahin, Zeynep
This study examines the impact of analytical customer relationship management (aCRM) strategies, specifically the segmentation approach using RFM analysis and artificial learning methods, on customer satisfaction, revenue performance, and loyalty in businesses. The research adopts an approach that integrates data from both online and offline channels onto a single platform, providing a holistic view of customer behaviors. Combining the segmentation obtained through RFM analysis and artificial learning methods with timely campaigns has enhanced shopping opportunities for customers and increased customer satisfaction and loyalty. The use of aCRM as a strategic marketing and sales tool has enabled businesses to manage customer relationships more effectively. This paper contributes to the literature in this field by presenting in detail the advantages offered by aCRM, its application methods, and the results obtained.
Analyzing Consumer Behavior: the Impact of Retro Music in Advertisements on a Chocolate Brand and Consumer Engagement
(IEEE, 2023) Girişken, Yener; Soyaltın, Tuğçe Ezgi; Filiz, Gözde; Çakar, Tuna; Türkyılmaz, Ceyda Aysuna
This study presents research utilizing binary classification models to analyze consumer behaviors such as chocolate consumption and retro music ad viewing. Retro music, with its potential to evoke nostalgic feelings in consumers, is used in advertisements, which can have a significant impact on brand perception and consumer engagement. Firstly, a model focusing on chocolate consumption was developed and tested. The model yields significant outcomes. Secondly, a model based on retro music ad viewing status was developed and tested. Significant potential findings were obtained. This study emphasizes the applicability of effective classification models that can be used to understand and predict consumer behaviors, yielding significant outcomes.
Analyzing Customer Churn: a Comparative Study of Machine Learning Models on Pay-Tv Subscribers in Turkey
(IEEE, 2023) Obalı, Emir; Çalışkan, Sibel Kırmızıgül; Karani Yılmaz, Veysel; Kara, Erkan; Meşe, Yasemin Kürtcü; Çakar, Tuna; Yıldız, Ayşenur; Hataş, Tuğce Aydın
Understanding the reasons for customer churn provides added value in terms of retaining existing customers, as customer attrition leads to revenue loss for companies and incurs marketing costs for acquiring new customers. In this study, the 6-month historical data of a Pay-TV company operating in Turkey was used, and due to the imbalanced nature of the dataset on a label basis, the oversampling method was applied. During the model development phase, various artificial learning algorithms (Random Forest, Logistic Regression, KNearest Neighbors, Decision Tree, AdaBoost, XGBoost, Extra Tree Classifier) were utilized, and their performances were compared. Based on the evaluation of success criteria for each model, it was observed that the tree-based Random Forest, Extra Tree Classifier and XGBoost achieved the highest performance for this dataset.

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