Browsing by Publication Index "WoS"

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1441. Quantification of the Flow Noise in Household Refrigerators
(JVE INTERNATIONAL LTD., 2014) Körük, Hasan; Arısoy, Ahmet; Bilgin, Necati
The flow noise in household refrigerators is quantified in this study. First, the sound pressure measurements in a quiet room using typical household refrigerators are conducted and the noise characteristics of the refrigerators are presented. Then, the flow noise in household refrigerators is quantified using the results of the overall analysis and Fourier transform of the measured sound pressure data. After that, the flow noise in household refrigerators is quantified using the sound pressure measurements conducted using a specially designed test rig. The frequency characteristics of the flow noise in household refrigerators are also explored and the contribution of the flow noise is identified.
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.
2D Modeling Temperature Development of Mass Concrete Structures at Early Age
(fib. The International Federation for Structural Concrete, 2017) Yikici T.A.; Chen R.H.L.; Chen, Roger H. L.; Yikici, Tahsin Alper
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.
A 32-Society Investigation of the Influence of Perceived Economic Inequality on Social Class Stereotyping
(Wiley, 2022) Ashokkumar, Ashwini; Billet, Matthew; Becker, Maja; Peters, Kim; Jetten, Joland; Barry, Oumar; Tanjitpiyanond, Porntida; Peker, Müjde; Yeung, Victoria Wai-Lan
There is a growing body of work suggesting that social class stereotypes are amplified when people perceive higher levels of economic inequality—that is, the wealthy are perceived as more competent and assertive and the poor as more incompetent and unassertive. The present study tested this prediction in 32 societies and also examines the role of wealth-based categorization in explaining this relationship. We found that people who perceived higher economic inequality were indeed more likely to consider wealth as a meaningful basis for categorization. Unexpectedly, however, higher levels of perceived inequality were associated with perceiving the wealthy as less competent and assertive and the poor as more competent and assertive. Unpacking this further, exploratory analyses showed that the observed tendency to stereotype the wealthy negatively only emerged in societies with lower social mobility and democracy and higher corruption. This points to the importance of understanding how socio-structural features that co-occur with economic inequality may shape perceptions of the wealthy and the poor. © 2022 The Authors. European Journal of Social Psychology published by John Wiley & Sons Ltd.
A Bayesian Allocation Model Based Approach To Mixed Membership Stochastic Blockmodels
(Taylor and Francis Ltd., 2022) Kırbız, Serap; Hızlı, Çağlar
Although detecting communities in networks has attracted considerable recent attention, estimating the number of communities is still an open problem. In this paper, we propose a model, which replicates the generative process of the mixed-membership stochastic block model (MMSB) within the generic allocation framework of Bayesian allocation model (BAM) and BAM-MMSB. In contrast to traditional blockmodels, BAM-MMSB considers the observations as Poisson counts generated by a base Poisson process and marks according to the generative process of MMSB. Moreover, the optimal number of communities for BAM-MMSB is estimated by computing the variational approximations of the marginal likelihood for each model order. Experiments on synthetic and real data sets show that the proposed approach promises a generalized model selection solution that can choose not only the model size but also the most appropriate decomposition.
A Benchmark Dataset for Turkish Data-To Generation
(Elsevier, 2023) Demir, Şeniz; Öktem, Seza
In the last decades, data-to-text (D2T) systems that directly learn from data have gained a lot of attention in natural language generation. These systems need data with high quality and large volume, but unfortunately some natural languages suffer from the lack of readily available generation datasets. This article describes our efforts to create a new Turkish dataset (Tr-D2T) that consists of meaning representation and reference sentence pairs without fine-grained word alignments. We utilize Turkish web resources and existing datasets in other languages for producing meaning representations and collect reference sentences by crowdsourcing native speakers. We particularly focus on the generation of single-sentence biographies and dining venue descriptions. In order to motivate future Turkish D2T studies, we present detailed benchmarking results of different sequence-to-sequence neural models trained on this dataset. To the best of our knowledge, this work is the first of its kind that provides preliminary findings and lessons learned from the creation of a new Turkish D2T dataset. Moreover, our work is the first extensive study that presents generation performances of transformer and recurrent neural network models from meaning representations in this morphologically-rich language.
A Capacitated Lot Sizing Problem With Stochastic Setup Times and Overtime
(Elsevier Science bv, 2019) Jabali, Ola; Gendreau, Michel; Jans, Raf; Taş, Duygu
In this paper, we study a Capacitated Lot Sizing Problem with Stochastic Setup Times and Overtime (CLSPSSTO). We describe a mathematical model that considers both regular costs (including production, setup and inventory holding costs) and expected overtime costs (related to the excess usage of capacity). The CLSP-SSTO is formulated as a two-stage stochastic programming problem. A procedure is proposed to exactly compute the expected overtime for a given setup and production plan when the setup times follow a Gamma distribution. A sample average approximation procedure is applied to obtain upper bounds and a statistical lower bound. This is then used to benchmark the performance of two additional heuristics. A first heuristic is based on changing the capacity in the deterministic counterpart, while the second heuristic artificially modifies the setup time. We conduct our computational experiments on well-known problem instances and provide comprehensive analyses to evaluate the performance of each heuristic. (C) 2018 Elsevier B.V. All rights reserved.
A Comparative Analysis of the Health Care Utilization and Costs of Patients Diagnosed With and Without Liver Cancer in the Us Medicare Population
(2017) Ogbomo, A.; Lin, Y.; Keshishian, A; Xie, L; Yuce, H; Başer, Onur
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A Comparative Study of Branch-And Algorithms for Vehicle Routing With Time Windows and Waiting Time Costs
(Wiley, 2026) Michelini, Stefano; Kucukaydin, Hande; Arda, Yasemin
Branch-and-price is one of the most commonly used methodologies for solving routing problems. In recent years, several studies have investigated advanced labeling algorithms to solve the related pricing problem, which is usually a variant of the elementary shortest path problem with resource constraints. Such algorithms include efficient techniques such as decremental state space relaxation, ng-route relaxation, and several hybridizations of these two relaxation methods. In this study, we compare the performance of these labeling algorithms in a branch-and-price framework when applied to the vehicle routing problem with time windows and a variant of this problem in which waiting times have a linear cost. For the latter problem, we also propose an appropriate label structure with associated resource extension functions and dominance rules. We perform these comparisons by using a rigorous methodology, which consists of parameterizing several features of these algorithms, obtaining a good parameter configuration for each algorithm, and analyzing the performance of these configurations on benchmark instances. In order to obtain good configurations, we make use of irace, which is a tool for automated parameter tuning, while statistical tests are used for performance comparisons. Our results show that a class of hybrid algorithms with certain features based on ng-route relaxation outperforms all the others.
A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making
(MDPI, 2023) Abacıoğlu, Seda; Ayan, Büşra; Basilio, Marcio Pereira
In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.
A Configurational Analysis of the Impact of Entrepreneurial Orientation and Global Mindset on Export Performance of Smes
(SAGE Publications Inc., 2025) Matemane, R.; Mintah, R.; Şahin, F.; Karadağ, H.
Although contemporary literature provides several important insights into the role of attributes of SMEs, there is much less evidence on what configuration of entrepreneurial orientation and global mindset makes this process successful, that is, contributing to the export performance of SMEs. This study uses a fuzzy set qualitative comparative analysis on a sample of 97 SMEs in Ghana to explore the potential complementary role between the entrepreneurial orientation dimensions and global mindset for superior export performance. The results indicate two different yet equifinal configurations of these factors that lead to a high level of export performance of SMEs. One of the configurations shows that proactive and innovative SMEs with managers high on global mindset achieve superior export performance regardless of their willingness to take risks. Another configuration indicates that regardless of the global mindset of managers, SMEs can achieve higher export performance by being proactive, innovative, and willing to take high risks. Several implications for theory and practice are discussed based on the findings. © The Author(s) 2024.
A Data-Assisted Reliability Model for Carrier-Assisted Cold Data Storage Systems
(Elsevier, 2020) Arslan, Şuayb Şefik; Göker, Turguy; Peng, James
Cold data storage systems are used to allow long term digital preservation for institutions’ archive. The common functionality among cold and warm/hot data storage is that the data is stored on some physical medium for read-back at a later time. However in cold storage, write and read operations are not necessarily done in the same exact geographical location. Hence, a third party assistance is typically utilized to bring together the medium and the drive. On the other hand, the reliability modeling of such a decomposed system poses few challenges that do not necessarily exist in other warm/hot storage alternatives such as fault detection and absence of the carrier, all totaling up to the data unavailability issues. In this paper, we propose a generalized non-homogenous Markov model that encompasses the aging of the carriers in order to address the requirements of today's cold data storage systems in which the data is encoded and spread across multiple nodes for the long-term data retention. We have derived useful lower/upper bounds on the overall system availability. Furthermore, the collected field data is used to estimate parameters of a Weibull distribution to accurately predict the lifetime of the carriers in an example scale-out setting.
A Decade of Discriminative Language Modeling for Automatic Speech Recognition
(Springer-Verlag Berlin, 2015) Arısoy, Ebru; Saraçlar, Murat; Dikici, Erinc
This paper summarizes the research on discriminative language modeling focusing on its application to automatic speech recognition (ASR). A discriminative language model (DLM) is typically a linear or log-linear model consisting of a weight vector associated with a feature vector representation of a sentence. This flexible representation can include linguistically and statistically motivated features that incorporate morphological and syntactic information. At test time, DLMs are used to rerank the output of an ASR system, represented as an N-best list or lattice. During training, both negative and positive examples are used with the aim of directly optimizing the error rate. Various machine learning methods, including the structured perceptron, large margin methods and maximum regularized conditional log-likelihood, have been used for estimating the parameters of DLMs. Typically positive examples for DLM training come from the manual transcriptions of acoustic data while the negative examples are obtained by processing the same acoustic data with an ASR system. Recent research generalizes DLM training by either using automatic transcriptions for the positive examples or simulating the negative examples.
A Decomposition Algorithm for Single and Multiobjective Integrated Market Selection and Production Planning
(Informs, 2023) van den Heuvel, Wilco; Ağralı, Semra; Taşkın, Z. Caner
We study an integrated market selection and production planning problem. There is a set of markets with deterministic demand, and each market has a certain revenue that is obtained if the market's demand is satisfied throughout a planning horizon. The demand is satisfied with a production scheme that has a lot-sizing structure. The problem is to decide on which markets' demand to satisfy and plan the production simultaneously. We consider both single and multiobjective settings. The single objective problem maximizes the profit, whereas the multiobjective problem includes the maximization of the revenue and the minimization of the production cost objectives. We develop a decomposition-based exact solution algorithm for the single objective setting and show how it can be used in a proposed three-phase algorithm for the multiobjective setting. The master problem chooses a subset of markets, and the subproblem calculates an optimal production plan to satisfy the selected markets' demand. We investigate the subproblem from a cooperative game theory perspective to devise cuts and strengthen them based on lifting. We also propose a set of valid inequalities and preprocessing rules to improve the proposed algorithm. We test the efficacy of our solution method over a suite of problem instances and show that our algorithm substantially decreases solution times for all problem instances.
A Discourse Analysis of Bilateral Water Agreements Between Türkiye and Iraq: Legal Instruments of Water Diplomacy in the Euphrates-Tigris River Basin
(International Environmental Agreements: Politics, Law and Economics, 2026) Güleç, Cansu; Kibaroglu, Aysegul
This study examines the discursive dynamics of bilateral water diplomacy between T & uuml;rkiye and Iraq through a detailed analysis of the legal agreements governing the Euphrates-Tigris (ET) River system. Rather than focusing on the implementation or efficacy of these agreements, the paper investigates how discourse shapes the roles, identities, and power hierarchies of the involved actors over time. Employing a discourse-analytical framework, the research explores how water agreements position actors, embed values, and narrate cooperation in evolving geopolitical contexts. The paper begins with a historical overview of transboundary water relations in the ET basin, emphasizing the prevalence of bilateralism. It then lays out the conceptual and methodological foundations of discourse analysis, drawing on key literature and analytical categories such as presupposition, predication, and subject positioning. The core section applies this framework to four key water agreements between T & uuml;rkiye and Iraq, highlighting thematic shifts and evolving actor roles. A discussion section synthesizes findings through Doty's (1993) discourse model, emphasizing how identities and relations are constructed over time. Finally, the conclusion reflects on the implications of these discursive trends for the future of water diplomacy in the region. The T & uuml;rkiye-Iraq case reveals how bilateral agreements can evolve into discursive tools that align with evolving global water management paradigms, offering politically sensitive basins a transferable approach to linking contested transboundary water issues with more comprehensive and partnership-based water diplomacy.
A Distance-Dependent Random Graph Model and Its Analysis
(Taylor & Francis Inc, 2026) Arslan, İlker; Işlak, Ümit
Let W-1,..., Wn be non-negative random variables. We consider an undirected random graph model on the node set {1,. ..,n}, where two nodes i < j are adjacent if W-i < W-j. In our setting, the Wi's are independent but not necessarily identically distributed, resulting in a model that generalizes the classical random permutation graphs. The model exhibits a certain dependence among the edges. Moreover, when nodes have physical interpretations- such as points on the real line R with node i located at position x = i-the model gains spatial structure and becomes, in particular, distance-dependent. We derive theoretical results on degree distributions, the number of isolated vertices, and the number of close neighbors. Simulation-based observations are also provided for the average clustering and the global efficiency.
A Few Layers Graphene Encapsulated Fe-Based Nanoparticles Synthesized from Ferrocene Containing Precursors: CVD Optimization and Evaluation for Possible Nanocatalyst Performance towards H2 Production
(Pergamon-Elsevier Science Ltd, 2026) Demirbas, Derya; Kutluay, Sinan; Agaogullari, Duygu; Suzer-Cicek, Layda; Mertdinc-Ulkuseven, Siddika; Padberg, Gero; Felderhoff, Michael; Süzer-Çiçek, İlayda; Lütfi Öveçoğlu M.
This study focuses on optimizing the synthesis of a few-layer graphene-encapsulated iron-based nanoparticles (Fe/Fe3C@C), prepared through spray drying, chemical vapor deposition (CVD), and leaching processes using ferrocene-based precursors, and their application as nanocatalysts for hydrogen (H2) production via sodium borohydride (NaBH4) methanolysis. Ferrocene-impregnated silica powders were prepared by spray drying them from a solution containing ferrocene, fumed silica, and ethanol. Then, these prepared powders, known as precursor powders, were subsequently introduced into the CVD system. Both the reduction of ferrocene and the encapsulation of Fe-based nanoparticles by graphene layers occurred in-situ during the CVD process. CVD temperature and the flow rates of CH4 and H2 gases are critical parameters that effects of the microstructural, thermal, and magnetic properties of synthesized nanoparticles. The CVD system was performed at temperatures ranging from 850 to 1000 degrees C, with variable gas flow rates of 50 or 100 mL/min. Additionally, acid leaching with hydrofluoric (HF) and hydrochloric (HCl) acids ensured the synthesis of pure powders free from silica and uncoated Fe, confirming the chemical stability of the nanoparticles. The presence of graphene in all synthesized samples within these parameter ranges were confirmed by Raman spectroscopy. Phase identifications were carried out using X-ray diffraction (XRD) and Mo & uml;ssbauer spectroscopy, revealing the Fe and trace amount Fe3C as core phases. Transmission electron microscopy (TEM) revealed the core-shell structure of the nanoparticles with a few layers of graphene coatings. Based on the coercivity and magnetic saturation values obtained from vibrating sample magnetometry (VSM), synthesized core-shell nanoparticles exhibited soft magnetic properties (Ms = 22.4-33.5 emu/g, Hc = 82.3-278.3 Oe). Fe/Fe3C@C nanoparticles obtained under optimum conditions achieved very high H2 production rate (HPR = 54200 mLH2 gcat h- 1) values, with low activation energy (Ea = 20.08 kJ mol- 1) value, highlighting their potential as an efficient and promising candidate catalyst for industrial-scale H2 production via the NaBH4 methanolysis reaction. In addition, it was found that the Fe/Fe3C@C nanoparticles retained 48% and 71% of their initial activity after 5 consecutive cycles, as measured by the HPR and TOF values, respectively.
A Historical Perspective To Fabrication in Architecture for Preserving Heritage
(Education and research in Computer Aided Architectural Design in Europe, 2019) Özgan, Sibel Yasemin; Özkar, Mine; Hamzaoğlu, Begüm
Digital technologies have recently been at the forefront of the causal link between making and design. A growing number of architecture programs of universities incorporates fabrication to the educational environment, and even to the curriculum. Fabrication technology is now considered among the set of tools students are expected to acquire a basic knowledge of and skills in. Nevertheless, the pedagogical potential of fabrication in communicating traditions of making is underused in an oversight of the continuity of the relevant know-how. Our position is that traditions of making can be the subject matter of fabrication with the objective to remedy the role of fabrication tools in architectural history, sustainable architectural production, and in the field of digital heritage. In this paper, we report on two comparative studies that illustrate how the instrumental factors of two historical crafts can be articulated using fabrication. © 2019, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.
A Joint Dedupe-Fountain Coded Archival Storage
(IEEE, 2017) Arslan, Şuayb Şefik; Göker, Turguy; Wideman, Rod
An erasure-coded archival file storage system is presented using a chunk-based deduplication mechanism and fountain codes for space/time efficient operation. Unlike traditional archival storage, this proposal considers the deduplication operation together with correction coding in order to provide a reliable storage solution. The building blocks of deduplication and fountain coding processes are judiciously interleaved to present two novel ideas, reducing memory footprint with weaker hashing and dealing with the increased collisions using correction coding, and applying unequal error protection to deduplicated chunks for increased availability. The combination of these two novel ideas made the performance of the proposed system stand out. For example, it is shown to outperform one of the replication-based as well as RAID data protection schemes. The proposed system also addresses some of the fundamental challenges of today's low-cost deduplicated data storage systems such as hash collisions, disk bottleneck and RAM overflow problems, securing savings up to 90% regular RAM use.
A Longitudinal Assessment of Variability in Covid-19 Vaccine Hesitancy and Psychosocial Correlates in a National United States Sample
(Elsevier Sci Ltd, 2023) Shook, Natalie J.; Oosterhoff, Benjamin; Sevi, Barış
Recent evidence suggests that COVID-19 vaccine hesitancy is not static. In order to develop effective vaccine uptake interventions, we need to understand the extent to which vaccine hesitancy fluctuates and identify factors associated with both between- and within-person differences in vaccine hesitancy. The goals of the current study were to assess the extent to which COVID-19 vaccine hesitancy varied at an individual level across time and to determine whether disgust sensitivity and germ aversion were associated with between- and within-person differences in COVID-19 vaccine hesitancy. A national sample of U.S. adults (N = 1025; 516 woman; M-age = 46.34 years, SDage = 16.56, range: 18 to 85 years; 72.6 % White) completed six weekly online surveys (March 20 - May 3, 2020). Between-person mean COVID-19 vaccine hesitancy rates were relatively stable across the six-week period (range: 38-42 %). However, there was considerable within-person variability in COVID-19 vaccine hesitancy. Approximately, 40 % of the sample changed their vaccine hesitancy at least once during the six weeks. There was a significant between-person effect for disgust sensitivity, such that greater disgust sensitivity was associated with a lower likelihood of COVID-19 vaccine hesitance. There was also a significant within-person effect for germ aversion. Participants who experienced greater germ aversion for a given week relative to their own six week average were less likely to be COVID-19 vaccine hesitant that week relative to their own six-week average. This study provides important information on rapidly changing individual variability in COVID-19 vaccine hesitancy on a weekly basis, which should be taken into consideration with any efforts to decrease vaccine hesitancy and increase vaccine uptake. Further, these findings identify-two psychological factors (disgust sensitivity and germ aversion) with malleable components that could be leveraged in developing vaccine uptake interventions.