WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/256

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Now showing 1 - 20 of 154

Citation - WoS: 7
Citation - Scopus: 4
2D Modeling Temperature Development of Mass Concrete Structures at Early Age
(FIB. The International Federation for Structural Concrete, 2018) Yikici, 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. © 2022 Elsevier B.V., All rights reserved.
Citation - Scopus: 2
A Decade of Discriminative Language Modeling for Automatic Speech Recognition
(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 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.
Citation - WoS: 1
Citation - Scopus: 2
A Machine Learning Approach To Resolving Conflicts in Physical Human-Robot Interaction
(Association for Computing Machinery, 2025) Ulas Dincer, Enes; Al-Saadi, Zaid; Hamad, Y.M.; Aydın, Yusuf; Kucukyilmaz, A.; Basdogan, C.
As artificial intelligence techniques become more sophisticated, we anticipate that robots collaborating with humans will develop their own intentions, leading to potential conflicts in interaction. This development calls for advanced conflict resolution strategies in physical human-robot interaction (pHRI), a key focus of our research. We use a machine learning (ML) classifier to detect conflicts during co-manipulation tasks to adapt the robot's behavior accordingly using an admittance controller. In our approach, we focus on two groups of interactions, namely "harmonious"and "conflicting,"corresponding respectively to the cases of the human and the robot working in harmony to transport an object when they aim for the same target, and human and robot are in conflict when human changes the manipulation plan, e.g. due to a change in the direction of movement or parking location of the object.Co-manipulation scenarios were designed to investigate the efficacy of the proposed ML approach, involving 20 participants. Task performance achieved by the ML approach was compared against three alternative approaches: (a) a rule-based (RB) Approach, where interaction behaviors were rule-derived from statistical distributions of haptic features; (b) an unyielding robot that is proactive during harmonious interactions but does not resolve conflicts otherwise, and (c) a passive robot which always follows the human partner. This mode of cooperation is known as "hand guidance"in pHRI literature and is frequently used in industrial settings for so-called "teaching"a trajectory to a collaborative robot.The results show that the proposed ML approach is superior to the others in task performance. However, a detailed questionnaire administered after the experiments, which contains several metrics, covering a spectrum of dimensions to measure the subjective opinion of the participants, reveals that the most preferred mode of interaction with the robot is surprisingly passive. This preference indicates a strong inclination toward an interaction mode that gives more control to humans and offers less demanding interaction, even if it is not the most efficient in task performance. Hence, there is a clear trade-off between task performance and the preferred mode of interaction of humans with a robot, and a well-balanced approach is necessary for designing effective pHRI systems in the future. © 2025 Copyright held by the owner/author(s).
Citation - Scopus: 1
A Microwave Imaging Scheme for Detection of Pulmonary Edema and Hemorrhage
(IEEE, 2022) Ertek, Didem; Kucuk, Gokhan; Bilgin, Egemen
The microwave imaging systems have the potential to present a cost effective and less hazardous alternative to conventional medical imaging techniques. In this paper, a Contrast Source Inversion method based microwave imaging scheme is proposed and tested for the detection of pulmonary edema and hemorrhage. To this end, a realistic human torso phantom is used, and the electromagnetic parameters of the human tissues is determined via Cole-Cole model. The scattered field is simulated via Method of Moments at the operating frequency of 350 MHz, and a 50 dB white Gaussian noise is added to model a realistic measurement setup. The numerical tests performed with the proposed technique suggest that the method can be used to locate the pulmonary edema and hemorrhage, and it is capable of distinguishing these two medical conditions successfully.
A Practical PCB-Based Framework for Spiking Neural Networks with a Half-Adder Example
(IEEE, 2025) Cikikci, Sevde Vuslat; Orek, Eren; Aysoy, Ayhan; Ozgen, Ali Kagan; Yavuz, Arda; Ayhan, Tuba
This paper addresses the half-adder problem using Spiking Neural Networks (SNNs). In a previous study, the XOR operation was successfully realized on a breadboard and in this study it is integrated into the half-adder structure. The system uses input signals at frequencies of 50 Hz and 100 Hz and the neurons are generated by the Leaky Integrate and Fire (LIF) model. Unlike other neuron models, the LIF model is less complex. In addition, it was preferred because of its biological meaningfulness compared to the Integrate and Fire model. The network, consisting of 18 neurons in total, shows that basic arithmetic operations can be performed with SNN. Overall, this study demonstrates that basic logic operations can be implemented in neural networks, thus providing new perspectives for digital calculation. The successful solution of the Half Adder problem using SNNs not only proves the calculation capabilities of SNNs, but also opens new perspectives for the development of more complex logical circuits using these biologically inspired neural circuits.
A Strategic Management Approach To Financial Management Practices in Small and Medium Sized Businesses
(Emerald Group Publishing Ltd., 2015) Karadağ, Hande
...
Citation - Scopus: 2
A Visualization Platfom for Disk Failure Analysis
(IEEE, 2018) Arslan, Şuayb Şefik; Yiğit, İbrahim Onuralp; Zeydan, Engin
It has become a norm rather than an exception to observe multiple disks malfunctioning or whole disk failures in places like big data centers where thousands of drives operate simultaneously. Data that resides on these devices is typically protected by replication or erasure coding for long-term durable storage. However, to be able to optimize data protection methods, real life disk failure trends need to be modeled. Modelling helps us build insights while in the design phase and properly optimize protection methods for a given application. In this study, we developed a visualization platform in light of disk failure data provided by BackBlaze, and extracted useful statistical information such as failure rate and model-based time to failure distributions. Finally, simple modeling is performed for disk failure predictions to alarm and take necessary system-wide precautions.
Citation - Scopus: 1
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.
AI-Driven Digital Soil Mapping: Leveraging Generative AI, Ensemble Learning and Geospatial Technologies for Data-Scarce Regions
(Springer Science and Business Media Deutschland GmbH, 2025) Drias, Yassine; Drias, Habiba; Belkadi, Widad Hassina; Cakar, Tuna; Abdelhamid, Zakaria; Bensemmane, Riad Yacine
This study presents a methodology for generating highresolution digital soil maps by integrating artificial intelligence (AI) with geospatial technologies. The research begins with comprehensive data collection and the extraction of relevant soil properties with the help of generative AI. To improve predictive accuracy, ensemble learning algorithms were employed due to their ability to capture complex relationships within soil characteristics. Additionally, a structured preprocessing pipeline was developed to refine and standardize the collected soil data, ensuring its suitability for modeling. The model's performance was evaluated using spatial cross-validation techniques to identify the most effective predictive approach. To validate the proposed methodology, experiments were conducted in northern Algeria, a region characterized by diverse landscapes ranging from arid zones to fertile plains. The results demonstrate the potential of AI-driven approaches to enhance soil mapping, particularly in regions where high-quality and up-to-date soil data are limited. This study underscores the efficacy of AI and geospatial technologies in advancing precision agriculture and land management.
Citation - WoS: 2
Citation - Scopus: 10
An Fpga Implementation of a Risc-V Based Soc System for Image Processing Applications
(IEEE, 2021) Gholizadehazari, Erfan; Ayhan, Tuba; Ors, Berna
The Laplacian filter is one of the fundamental applications in image processing. In our work, the Laplacian filter has been applied to an image, and both hardware and software implementation of the filter has been studied. Our system consists of an OV7670 Camera module, Nexys 4 DDR FPGA board and VGA monitor to display the processed video stream. Mentioned process has forwarding tasks: camera module captures raw RGB data and writes to RAM, Laplacian filter IP processes raw image and the results written back to memory. VGA modules show output images to monitor. The Laplacian filter part considered in hardware and software implementation is compared in terms of time and area.
Citation - WoS: 14
Citation - Scopus: 40
An Overview of Blockchain Technologies: Principles, Opportunities and Challenges
(IEEE, 2018) Arslan, Şuayb Şefik; Mermer, Gültekin Berahan; Zeydan, Engin
Blokzincir, toplumumuzun birbiriyle iletişim kurma ve ticaret yapma biçiminde devrim yapma potansiyeline sahip, yakın zamanda ortaya çıkmış olan bir teknolojidir. Bu teknolojinin sağladığı en önemli avantaj aracı gerektiren bir oluşumda güvenilir bir merkezi kuruma ihtiyaç duymadan değer taşıyan işlemleri değiş tokuş edebilmesidir. Ayrıca, veri bütünlüğü, dahili orijinallik ve kullanıcı şeffaflığı sağlayabilir. Blokzincir, birçok yenilikçi uygulamanın temel alınacağı yeni internet olarak görülebilir. Bu çalışmada, genel çalışma prensibi, oluşan fırsatlar ve ileride karşılaşılabilecek zorlukları içerecek şekilde güncel blokzincir teknolojilerinin genel bir görünümünü sunmaktayız.
An Overview on the Structural Monitoring, Assessment and Retrofitting of Historical Structures With a Focus on 13th Century Monuments
(Springer international Publishing Ag, 2024) Ilki, Alper; Inci, Pinar; Halici, Omer F.; Demir, Cem; Comert, Mustafa; Kuran, Fikret
Monumental historical structures affirm natural and cultural identity and hence they should be transmitted to future generations. The protection and preservation of these structures against aging and natural hazards, particularly seismic actions, requires a comprehensive approach including diagnosis of the present condition of the structure and enhancement of structural capacity for disaster mitigation, if necessary. It is obvious that due to their historical values, any attempt towards the preservation of the monumental historical structures must be carried out with respect to the principles of integrity and authenticity. In this study, the structural performance assessment procedures, implementation of structural health monitoring systems and seismic strengthening strategies are discussed and described with reference to 13th-century monumental historical structures in Turkiye. The structural engineering aspects of recent activities for the restoration and preservation of the Great Mosque and Hospital of Divrigi (a world heritage listed structure) and Sivas Ulu Cami (Mosque) Minaret are briefly presented. In light of the structural analysis and monitoring results, recommendations for interventions to these monumental structures are outlined.
Citation - Scopus: 3
An Xml Parser for Turkish Wikipedia
(IEEE, 2019) Demir, Şeniz; Vardar, Uluç Furkan; Devran, İlkay Tevfik
Nowadays, visual and written data that can be easily accessed over the internet has enabled the development of research in many different fields. However, the availability of data is not sufficient by itself. It is of great importance that these data can be effectively utilized and interpreted in accordance with the requirements. Access to written content in the Wikipedia encyclopedia, which is becoming increasingly common in Turkish natural language processing, can be done via XML dumps. In this study, our aim is to develop and demonstrate the applicability of an XML parser for the processing of Turkish Wikipedia dumps. The use of the open-source parser, which allows information extraction at different levels of granularity, is reported on pages containing biography infoboxes and textual contents.
Anamorphic Projection as a Novel Game Mechanic for Investigating Impossible Spaces in 3D Puzzle Games
(IEEE Computer Society, 2025) Aydındoğan, Irem; Alaçam, Sema
This study introduces a novel game mechanic for 3D puzzle games based on anamorphic projection to explore impossible spaces. By using perspective-driven spatial interactions, the mechanic creates environments that challenge conventional Euclidean logic. Players advance by aligning their viewpoint with distorted projections, making perception a central element of gameplay. A usability test with 33 participants assessed the mechanic's effectiveness through a structured questionnaire focusing on six dimensions: Ease of Control, Goals and Rules, Challenge, Mastery, Curiosity, and Immersion. Results indicate high engagement and cognitive stimulation, especially in mastery and goal clarity. These findings highlight the potential of anamorphic projection to support perceptually rich and mentally engaging puzzle experiences in future game design. © 2025 Elsevier B.V., All rights reserved.
Citation - WoS: 2
Citation - Scopus: 2
Approximate Closed-Form Solutions for Vibration of Nano-Beams of Local/Non-local Mixture
(Springer, 2022) Ruta, Giuseppe; Eroğlu, Uğurcan
This paper presents an approach to natural vibration of nano-beams by a linear elastic constitutive law based on a mixture of local and non-local contributions, the latter based on Eringen's model. A perturbation in terms of an evolution parameter lets incremental field equations be derived; another perturbation in terms of the non-local volume fraction yields the variation of the natural angular frequencies and modes with the 'small' amount of non-locality. The latter perturbation does not need to comply with the so-called constitutive boundary conditions, the physical interpretation of which is still debated. The possibility to find closed-form solutions is highlighted following a thorough discussion on the compatibility conditions needed to solve the steps of the perturbation hierarchy; some paradigmatic examples are presented and duly commented.
Citation - WoS: 1
Citation - Scopus: 1
Average Bandwidth-Cost Vs. Storage Trade-Off for Bs-Assisted Distributed Storage Networks
(IEEE, 2021) Tengiz, Ayse Ceyda; Haytaoğlu, Elif; Pusane, Ali Emre; Arslan, Şuayb Şefik; Pourmandi, Massoud
In this study, we consider a hierarchically structured base station (BS)-assisted cellular system equipped with a backend distributed data storage in which nodes randomly arrive and depart the cell. We numerically motivate and characterize the fundamental trade-off between the average repair bandwidth cost versus storage space where BS communication cost (higher than that of local) and link capacity constraints exist while the number of failed nodes can vary dynamically. We establish the capacity region that is most relevant to 5G and beyond networks, which are layered by design. We hope that this study shall motivate novel regeneration code constructions that will be able to achieve the presented limits.
Base Station-Assisted Cooperative Network Coding for Cellular Systems With Link Constraints
(IEEE, 2022) Arslan, Suayb S.; Pourmandi, Massoud; Haytaoglu, Elif
We consider a novel distributed data storage/caching scenario in a cellular network, where multiple nodes may fail/depart simultaneously To meet reliability, we allow cooperative regeneration of lost nodes with the help of base stations allocated in a set of hierarchical layers1. Due to this layered structure, a symbol download from each base station has a different cost, while the link capacities between the nodes of the cellular system and the base stations are also constrained. Under such a setting, we formulate the fundamental trade-off with closed form expressions between repair bandwidth cost and the storage space per node. Particularly, the minimum storage as well as bandwidth cost points are formulated. Finally, we provide an explicit optimal code construction for the minimum storage regeneration point for a special set of system parameters.
Citation - WoS: 2
Citation - Scopus: 2
Between a Rock and a Hard Place: How To Make Sense of Turkey’s S-400 Choice
(SETA Foundation, 2020) Kibaroğlu, Mustafa
With the wrap-up of the S-400 deal with Russia in December 2017, critics argue that Turkey is caught between a rock and a hard place due to the adamant opposition of its NATO allies, the United States in particular, which has threatened Ankara with imposing severe sanctions. Would this be the correct representation of the situation at hand? Does it make any sense for Turkey to engage Russia, an archrival nation, to enhance the security of the country? Is the S-400 deal worth the risk of alienating the allied nations whose projected sanctions may have wide-ranging political, economic and military repercussions? With these questions in mind, this paper will try to shed light on the specifics of the S-400 deal that make one think that it may indeed make sense for Turkey to bear the brunt of engaging Russia. In the same vein, the paper will assess the impact of the S-400 deal on Turkey’s defense industries. The paper will also present the author’s conception of the current “international political non-order” as an underlying factor behind the deal. Finally, the paper will suggest that the S-400 deal must be approached from a wider perspective so as to grasp the extent of the service it has done in bolstering Turkey’s military-industrial complex. © 2020, SETA Foundation. All rights reserved.
Citation - WoS: 58
Bidirectional Recurrent Neural Network Language Models for Automatic Speech Recognition
(2015) Chen, Stanley; Sethy, Abhinav; Ramabhadran, Bhuvana; Arısoy, Ebru
Recurrent neural network language models have enjoyed great success in speech recognition, partially due to their ability to model longer-distance context than word n-gram models. In recurrent neural networks (RNNs), contextual information from past inputs is modeled with the help of recurrent connections at the hidden layer, while Long Short-Term Memory (LSTM) neural networks are RNNs that contain units that can store values for arbitrary amounts of time. While conventional unidirectional networks predict outputs from only past inputs, one can build bidirectional networks that also condition on future inputs. In this paper, we propose applying bidirectional RNNs and LSTM neural networks to language modeling for speech recognition. We discuss issues that arise when utilizing bidirectional models for speech, and compare unidirectional and bidirectional models on an English Broadcast News transcription task. We find that bidirectional RNNs significantly outperform unidirectional RNNs, but bidirectional LSTMs do not provide any further gain over their unidirectional counterparts.

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