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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.
Citation - WoS: 3
Citation - Scopus: 3
A Benchmark Dataset for Turkish Data-To Generation
(Elsevier, 2022) 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.
Citation - WoS: 19
Citation - Scopus: 23
A Capacitated Lot Sizing Problem With Stochastic Setup Times and Overtime
(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
...
Citation - WoS: 5
Citation - Scopus: 8
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.
Citation - WoS: 9
Citation - Scopus: 9
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.
Citation - WoS: 1
Citation - Scopus: 3
A Meta-Analytic Review of the Association Between Theory of Mind and Aggression
(Elsevier, 2023) Imuta, Kana; Selçuk, Bilge; Yavuz-Müren, Melis; Turunç, Gamze; Ekerim-Akbulut, Müge
Although the association between theory of mind (ToM) and aggression has been theorized, empirical findings have not revealed a clear link between these constructs. In the current meta-analytic review, we integrated findings from 83 studies (141 effect sizes) involving 41,650 participants from 18 countries to elucidate the association between ToM and aggression in typically developing children, adolescents, and adults. We found a significant negative association between ToM and aggression overall (r = −0.15). Moreover, each type and function of aggression were negatively associated with Theory of Mind (ToM). Bullying—a distinct form of aggression—was not associated with ToM. The strength of the association between overall aggression and ToM varied as a function of methodological variables: First, studies that used self-report questionnaires to measure ToM and aggression yielded the strongest effect sizes, compared to those that used task-based assessments or questionnaires completed by others (parents, teachers, peers). Second, there was a difference in the ToM measurement with the measures examining ToM with non-false belief understanding tasks yielding a stronger mean effect than those that focused exclusively on false-belief understanding. Third, the magnitude of the negative association was found to increase with participants' age, though significant negative associations between ToM and aggression held across the lifespan. These results point to the critical link between ToM and aggressive tendencies and suggest the value in implementing interventions to improve mental state understanding across the age range to foster positive social interactions.
Citation - WoS: 9
Citation - Scopus: 12
A New Triangular Composite Shell Element With Damping Capability
(Elsevier, 2014) Körük, Hasan; Şanlıtürk, Kenan Yüce
This paper presents a new triangular composite shell element with damping capability. Formulation of the composite triangular shell element is based on stacking individual homogeneous triangular shell ele- ments on top of each other. The homogeneous shell element is an assembly of a triangular membrane element with drilling degrees of freedoms and a plate element. Damping capability is provided by means of complex element stiffness matrix of individual flat layers of the composite element. These elements with damping capability allow modelling general structures with damping treatments. A few test cases are modelled using triangular finite element developed here and the results of the complex eigenvalue analyses are compared with those of the quadrilateral shell elements proposed recently. The results obtained using the presented triangular and previous quadrilateral composite elements are also com- pared with those based on modal strain energy method and experimental results. Comparisons of the experimental and the theoretical results confirm that the modal properties including modal damping lev- els of structures with damping treatments can be predicted with high accuracy using the proposed finite element.
Citation - WoS: 1
Citation - Scopus: 1
A Preliminary Study on the Role of Personal History of Infectious and Parasitic Diseases on Self-Reported Health Across Countries
(W B Saunders Co Ltd, 2025) Pfuhl, Gerit; Prazeres, Filipe; Kowal, Marta; Aavik, Toivo; Abad-Villaverde, Beatriz; Afhami, Reza; Sorokowski, Piotr; Toplu-Demirtaş, Ezgi
Objectives: Infectious diseases are often associated with decline in quality of life. The aim of this study is to analyze the relationship between personal history of communicable, i.e., infectious and parasitic diseases and self-rated health. Study design: Secondary analysis of a large dataset multi-country observational study. Methods: We used a four-pronged analysis approach to investigate whether personal history of infectious and parasitic diseases is related to self-reported health, measured with a single item. Results: Three of the four analyses found a small positive effect on self-reported health among those reporting a history of pathogen exposure. The meta-analysis found no support but large heterogeneity that was not reduced by two classifications of countries. Conclusion: Personal history of infectious and parasitic diseases does not reduce self-reported health across a global sample.
Citation - WoS: 1
A Randomized Clinical Trial Comparing the Effects of Mindfulness-Based and Cognitive Behavioral Therapy-Based Stress Reduction in Medical Students
(Cambridge Univ Press, 2024) Pence, A. Yay; Coldur, M.; Atalay, Z.; Aslan, S.; Beba, B.; Sayin, C. Coskun; Ertek, I. Ekmekci
[No Abstract Available]
Citation - WoS: 6
Citation - Scopus: 7
A Reliability Model for Dependent and Distributed Mds Disk Array Units
(IEEE Transactions on Reliability, 2018) Arslan, Şuayb Şefik
Archiving and systematic backup of large digital data generates a quick demand for multi-petabyte scale storage systems. As drive capacities continue to grow beyond the few terabytes range to address the demands of today’s cloud, the likelihood of having multiple/simultaneous disk failures became a reality. Among the main factors causing catastrophic system failures, correlated disk failures and the network bandwidth are reported to be the two common source of performance degradation. The emerging trend is to use efficient/sophisticated erasure codes (EC) equipped with multiple parities and efficient repairs in order to meet the reliability/bandwidth requirements. It is known that mean time to failure and repair rates reported by the disk manufacturers cannot capture life-cycle patterns of distributed storage systems. In this study, we develop failure models based on generalized Markov chains that can accurately capture correlated performance degradations with multiparity protection schemes based on modern maximum distance separable EC. Furthermore, we use the proposed model in a distributed storage scenario to quantify two example use cases: Primarily, the common sense that adding more parity disks are only meaningful if we have a decent decorrelation between the failure domains of storage systems and the reliability of generic multiple single-dimensional EC protected storage systems.
Citation - WoS: 6
Citation - Scopus: 6
A Strong Integer Programming Formulation for Hybrid Flowshop Scheduling
(Taylor & Francis, 2019) Ağralı, Semra; Ünal, A. Tamer; Taşkın, Z. Caner
We consider a hybrid flowshop scheduling problem that includes parallel unrelated discrete machines or batch processing machines in different stages of a production system. The problem is motivated by a bottleneck process within the production system of a transformer producer located in the Netherlands. We develop an integer programming model that minimises the total tardiness of jobs over a finite planning horizon. Our model is applicable to a wide range of production systems organised as hybrid flowshops. We strengthen our integer program by exploiting the special properties of some constraints in our formulation. We develop a decision support system (DSS) based on our proposed optimisation model. We compare the results of our initial optimisation model with an improved formulation as well as with a heuristic that was in use at the company before the implementation of our DSS. Our results show that the improved optimisation model significantly outperforms the heuristic and the initial optimisation model in terms of both the solution time and the strength of its linear programming relaxation.
Citation - WoS: 25
Citation - Scopus: 26
Acoustic Particle Palpation for Measuring Tissue Elasticity
(American Institute of Physics, 2015) El Ghamrawy, Ahmed; Körük, Hasan; Choi, James J; Pouliopoulos, Antonios N
We propose acoustic particle palpation—the use of sound to press a population of acoustic particles against an interface—as a method for measuring the qualitative and quantitative mechanical properties of materials. We tested the feasibility of this method by emitting ultrasound pulses across a tunnel of an elastic material filled with microbubbles. Ultrasound stimulated the microbubble cloud to move in the direction of wave propagation, press against the distal surface, and cause deformations relevant for elasticity measurements. Shear waves propagated away from the palpation site with a velocity that was used to estimate the material’s Young’s modulus.
Citation - WoS: 3
Citation - Scopus: 4
Adaptive Reuse of High-Rise Buildings for Housing: a Study of Istanbul Central Business District
(Cogitatio Press, 2024) Aydemir, Ayşe Zeynep; Akın, Tomris
The abrupt shift to remote work due to the Covid-19 pandemic increased vacant office spaces globally, especially in high -rent central business districts (CBDs). These vacant office spaces offer the potential for conversion into housing, addressing the shortage of affordable housing in central areas. Additionally, this topic presents a unique experimental ground for architecture students. This study focuses on the Istanbul CBD as a case study, examining the historical developments that led to a rise in office vacancy rates and housing inequality, and exploring the potential for adaptive reuse of these vacant office buildings. A key focus of this study is to underline the pedagogical value of adaptive reuse, highlighting how such projects can inspire more diverse and equitable housing models, fostering experimental and sustainable design approaches. It systematically evaluates the outcomes of a 4th -year architectural design studio that focuses on the adaptive reuse of the Tat Towers in the Istanbul CBD, a structurally vacant high-rise office building, and asks: How does the context of adaptive reuse enable a different design approach, and, potentially, new spatial norms and standards to emerge, and how might this hold a pedagogical value for architecture education? Following these questions, the article discusses how norms and standards are not only culturally but also typologically contextual, and how the students have explored how norms and standards might change, outlining new design approaches to adaptive reuse.
Citation - WoS: 13
Citation - Scopus: 21
Advancements in Distributed Ledger Technology for Internet of Things
(Elsevier, 2020) Jurdak, Raja; Arslan, Şuayb Şefik; Krishnamachari, Bhaskar; Jelitto, Jens
Internet of Things (IoT) is paving the way for different kinds of devices to be connected and properly communicated at a mass scale. However, conventional mechanisms used to sustain security and privacy cannot be directly applied to IoT whose topology is increasingly becoming decentralized. Distributed Ledger Technologies (DLT) on the other hand comprise varying forms of decentralized data structures that provide immutability through cryptographically linking blocks of data. To be able to build reliable, autonomous and trusted IoT platforms, DLT has the potential to provide security, privacy and decentralized operation while adhering to the limitations of IoT devices. The marriage of IoT and DLT technology is not very recent. In fact many projects have been focusing on this interesting combination to address the challenges of smart cities, smart grids, internet of everything and other decentralized applications, most based on blockchain structures. In this special issue, the focus is on the new and broader technical problems associated with the DLT-based security and backend platform solutions for IoT devices and applications.
Citation - WoS: 4
Citation - Scopus: 6
Aggression Begets Aggression: Psychological Dating Aggression Perpetration in Young Adults From the Perspective of Intergenerational Transmission of Violence
(Springer, 2021) Toplu-Demirtaş, Ezgi; Hatipoğlu-Sümer, Zeynep
The aim of this study was threefold: (1) to evaluate the factorial validity of the Psychological Aggression (PA) subscale of the Conflict Tactics Scales–Adult Recall version (CTS2-CA), (2) to investigate the prevalence of and gender differences in psychological dating aggression perpetration (PDAP; restrictive engulfment, denigration, hostile withdrawal, and dominance/intimidation), and (3) to explore a proposed path from witnessing interparental psychological aggression perpetration to PDAP via acceptance of psychological aggression as a mediator and gender as a moderator of the mediation. For the first purpose, college students (N = 275) completed father to mother and mother to father forms of the PA subscale of the CTS2-CA. Exploratory factor analyses yielded a single-factor solution for the father to mother (55.86% of the variance) and mother to father (49.12% of the variance) forms. For the second and third purposes, a separate sample of 1015 dating college students (69.6% women) completed the Multidimensional Measure of Emotional Abuse and Abuse subscale of the Intimate Partner Violence Attitude Scale-Revised, along with the PA subscale of the CTS2-CA. Gender differences emerged in the prevalence of restrictive engulfment (85.8% for women and 80.3% for men) and hostile withdrawal (96.3% for women and 91.1% for men). Moderated-mediation analyses revealed that women college students who witnessed more mother to father psychological aggression perpetration tended to hold more accepting attitudes towards psychological aggression and, in turn, perpetrated more psychological aggression against their partners. Common assumptions that boys are more likely to imitate fathers, whereas girls are more likely to imitate mothers and women [but not men] commit verbal aggression may together explain our findings from the perspective of the intergenerational transmission of violence hypothesis. For future research, we suggest investigating the proposed model with the experience of psychological aggression from the parents to the child, which may provide further insights.
Citation - WoS: 30
Citation - Scopus: 44
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.
Citation - WoS: 30
Citation - Scopus: 42
An Efficient Framework for Visible-Infrared Cross Modality Person Re-Identification
(Elsevier, 2020) Gökmen, Muhittin; Başaran, Emrah; Kamasak, Mustafa E.
Visible-infrared cross-modality person re-identification (VI-ReId) is an essential task for video surveillance in poorly illuminated or dark environments. Despite many recent studies on person re-identification in the visible domain (ReId), there are few studies dealing specifically with VI-ReId. Besides challenges that are common for both ReId and VI-ReId such as pose/illumination variations, background clutter and occlusion, VI-ReId has additional challenges as color information is not available in infrared images. As a result, the performance of VI-ReId systems is typically lower than that of ReId systems. In this work, we propose a four-stream framework to improve VI-ReId performance. We train a separate deep convolutional neural network in each stream using different representations of input images. We expect that different and complementary features can be learned from each stream. In our framework, grayscale and infrared input images are used to train the ResNet in the first stream. In the second stream, RGB and three-channel infrared images (created by repeating the infrared channel) are used. In the remaining two streams, we use local pattern maps as input images. These maps are generated utilizing local Zernike moments transformation. Local pattern maps are obtained from grayscale and infrared images in the third stream and from RGB and three-channel infrared images in the last stream. We improve the performance of the proposed framework by employing a re-ranking algorithm for post-processing. Our results indicate that the proposed framework outperforms current state-of-the-art with a large margin by improving Rank-1/mAP by 29.79%/30.91% on SYSU-MM01 dataset, and by 9.73%/16.36% on RegDB dataset.
Citation - WoS: 26
Citation - Scopus: 26
An Efficient Linear Programming Based Method for the Influence Maximization Problem in Social Networks
(Elsevier, 2019) Güney, Evren
The influence maximization problem (IMP) aims to determine the most influential individuals within a social network. In this study first we develop a binary integer program that approximates the original problem by Monte Carlo sampling. Next, to solve IMP efficiently, we propose a linear programming relaxation based method with a provable worst case bound that converges to the current state-of-the-art 1-1/e bound asymptotically. Experimental analysis indicate that the new method is superior to the state-of-the-art in terms of solution quality and this is one of the few studies that provides approximate optimal solutions for certain real life social networks.
An Efficient Linear Programming Based Method for the Influence Maximization Problem in Social Networks (vol 503, Pg 589, 2019)
(Elsevier, 2020) Güney, Evren
The influence maximization problem (IMP) aims to determine the most influential individuals within a social network. In this study first we develop a binary integer program thatapproximates the original problem by Monte Carlo sampling. Next, to solve IMP efficiently,we propose a linear programming relaxation based method with a provable worst casebound that converges to the current state-of-the-art 1 − 1/e bound asymptotically. Experimental analysis indicate that the new method is superior to the state-of-the-art in termsof solution quality and this is one of the few studies that provides approximate optimalsolutions for certain real life social networks.