Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1940

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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 - 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.
Predicting Animal Behaviours: Physical and Behavioural Classification Of Dog Walking Levels
(IEEE, 2022) Ozen, Guris; Karan, Baris; Çakar, Tuna
Methods of predicting canine behaviour is an area covered by canine behaviour experts. This study aims to predict the behaviour of dogs during walking based on available information about dogs. In this data-driven project based on up-to-date company data, the problem of predicting dog behaviour was addressed in two different ways. First, it is aimed to create a supervised classification model. Within the scope of this study, improvements were made to various classification algorithms. The results were analyzed in different axes. Secondly, it is aimed to create a new parameter that predicts dog walking difficulties by formulating the parameters.
Citation - WoS: 7
Citation - Scopus: 3
Facial Landmark Localization in Depth Images Using Supervised Ridge Descent
(2015) Camgoz, Necati Cihan; Gökberk, Berk; Akarun, Lale; Struc, Vitomir; Kindiroglu, Ahmet Alp
Supervised Descent Method (SDM) has proven successful in many computer vision applications such as face alignment, tracking and camera calibration. Recent studies which used SDM, achieved state of the-art performance on facial landmark localization in depth images [4]. In this study, we propose to use ridge regression instead of least squares regression for learning the SDM, and to change feature sizes in each iteration, effectively turning the landmark search into a coarse to fine process. We apply the proposed method to facial landmark localization on the Bosphorus 3D Face Database; using frontal depth images with no occlusion. Experimental results confirm that both ridge regression and using adaptive feature sizes improve the localization accuracy considerably.
Citation - Scopus: 5
High-Performance Real-Time Data Processing: Managing Data Using Debezium, Postgres, Kafka, and Redis
(IEEE, 2023) Çakar, Tuna; Ertuğrul, Seyit; Arslan, Şuayip; Sayar, Alperen; Akçay, Ahmet
This research focuses on monitoring and transferring logs of operations performed on a relational database, specifically PostgreSQL, in real-time using an event-driven approach. The logs generated from database operations are transferred using Apache Kafka, an open-source message queuing system, and Debezium running on Kafka, to Redis, a non-relational (No-SQL) key-value database. Time-consuming query operations and read operations are performed on Redis, which operates on memory (in-memory), instead of on the primary database, PostgreSQL. This approach has significantly improved query execution performance, data processing time, and backend service performance. The study showcases the practical application of an event-driven approach using Debezium, Kafka, Redis, and relational databases for real-time data processing and querying.
Evaluating Electrophysiological Responses Due To Identity Judgments
(Ieee, 2024) Çakar, Tuna; Hohenberger, Annette
This study was conducted to explore how the brain processes decisions about identity, employing event-related potentials (ERPs) as a measure. The aim was to ascertain if the EEG/ERP technique could be used to monitor the cognitive processing of identity judgments as they happen. The investigation focused on comparing two groups of statements: those that used the concept of 'same' and those that used 'different'. The researchers hypothesized that there would be notable differences in the ERPs, particularly around the 400-millisecond mark, correlating with the reaction time disparities observed behaviorally. The ERP data revealed that the 'different' statements generated a unique N400 response when contrasted with the 'same' statements, implying that the participants' cognitive responses to these two types of judgments were not the same.
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.
Citation - Scopus: 4
Openmp and Posix Threads Implementation of Jerasure 2.0
(2017) Arslan, Şuayb Şefik; Le, Hoa; Landman, Joseph; Goker, Turguy
In shared memory multiprocessor architectures, threads can be used to implement parallelism. POSIX threads (pthreads) is a low-level bare-bones programming interface for working with threads. Therefore, we have extremely fine-grained control over thread management (create/join/etc), mutexes, and so on. On the other hand, openMP, as a shared-memory standard, is much higher level and portable interface which makes it easier to use multi-threading capability and obtain satisfactory performance improvements. Since pthreads is more flexible, it helps programmers gain more control on performance optimizations. Jerasure 2.0 erasure coding library has encoding/decoding engines which comprise independent "for" loop iterations and hence possess huge potential for multi-threaded processing. In this short paper, we investigate multi-threaded implementations of encoder/decoder pair of Jerasure 2.0 using two different technologies: OpenMP and pthreads. We constrain our changes to a minimum possible and compare the pure encoding/decoding performance with respect to each other as well as against that of the original single-threaded version by running them on two different server systems.
İmece-depo: İşbirlikçi Hücresel Ağlarda Veri Önbellekleme için Cihazdan Cihaza Iletişim ile Dağıtık Depolama, Optimale Yakın Kodlama ve Protokol Tasarımı.
(2023) Haytaoğlu, Elif; Pourmandı, Massoud; Kaya, Erdi; Arslan, Şefik Şuayb
Hücresel ağlarda popüler dosyaların cihazlarda önbelleklenmesi ile, cihazlar arası etkileşim baz istasyonu (Bİ) üzerine düşen iletişim yükünü oldukça azaltmaktadır. Dağıtık veri önbellekleme işlemi popüler bir dosyanın parçalarının kodlanmamış orijinal haliyle ya da herhangi bir silinti kodu kullanılarak kodlanmış halinin mobil cihazlar içerisinde dağıtık bir şekilde depolanması yardımıyla gerçekleştirilir. Dosyanın herhangi bir parçası, komşu mobil cihazlardan ya da mümkün değilse, doğrudan Bİ?lerden, yüksek bir iletişim maliyeti pahasına indirilebilir. Bir hücresel ağda, rastgele zamanlarda bazı düğümlerin hücreye katıldığı ve bazılarının ayrıldığı göz önüne alındığında, performans için Bİ ile iletişimin minimum düzeyde olmasını sağlayacak akıllı veri onarım yöntemlerine ihtiyaç duyulacaktır. Tek bir veya birden fazla Bİ?nin sisteme katılımı, önceki onarım paradigmalarına, özellikle de işbirlikçi düğüm onarım süreçlerine farklı bir boyut eklemektedir. Bunun nedeni, çalışma protokolü kurallarının yanı sıra iletişim kısıtlamalarının da değişmesidir. Literatür, bu durum için temel bant genişliği/depolama ödünleşim uzayını inceleyen bir çalışma içermemektedir. Yeni hücre mimarileri buna göre, yeni silinti kod yapılarını, verimli protokol tasarımlarını, veri erişim gecikmesi, gerçekçi kuyruk modelleri ve gerçekçi benzetim platformları dahil ancak bunlarla sınırlı olmamak üzere farklı tasarım değerlendirmelerini gerektirmektedir. Bu projede ilk olarak, daha önceki hiçbir çalışmada düşünülmemiş işbirliği yapan Bİ?lerin cihaz ayrılışlarında yaşanan kayıp verinin onarımı için bant genişliği ve depolama kapasitesinin iyileştirilmiş teorik sınırlarının veri akış diyagramları kullanılarak elde edilmesi amaçlanmıştır. Bununla beraber, bant genişliği ve depolama alanını en iyi kullanan kod yapılarından esinlenerek, veri önbellekleme işlemini optimale yakın bir maliyetle gerçekleştirecek tamamen özgün çizge tabanlı kod yapıları ve bu yeni kodlar için daha önce düğüm onarım problemine uygulanmamış genetik algoritma, optimize edilmiş artık veri dağıtımı gibi yeni yaklaşımlar kullanılarak önceden düşünülmemiş düğüm onarım algoritmaları önerilecektir. Ayrıca, düğümlerin hücreye katılma ve ayrılma süreçleri için, bant genişliği ve veri depolaması gereksinimlerini en aza indirmeye yardımcı olacak enerji tüketimi odaklı son derece özgün protokoller önerilecektir. Bu protokoller, düğümlerin bir hücreden diğerine geçiş yapabileceği ve hücre içi kaynakların etkin kullanılmasına yardımcı olmak için Bİ?lerin işbirliği yapmasını sağlayan geçiş senaryoları ile güçlendirilecektir. Bu durum, iki onarım işlemi arasındaki sürenin ayarlanması, veri erişim maliyetlerinin azaltılması, hücreye katılan düğüm içeriğinin kullanımı, artık veri kullanımı v.s. gibi yenilikleri içerecektir. Son olarak, önerilen kod yapıları ve protokol mimarisinin performansını analitik olarak türetmek için bilinen çeşitli ve daha gerçekçi kuyruklama modelleri değerlendirilecektir. Analitik sonuçlarımızı doğrulamak için daha sonra hücresel ağ tabanlı büyük ölçekli benzetimler yapılıp sayısal yöntemler ile toplam iletişim ve dosya onarım işlemlerinin maliyet hesaplamaları ve karşılaştırmaları yapılacaktır. MEF Üniversitesi öğretim üyesi Dr. Şuayb Arslan?ın yürütücüsü olduğu ve 36 ay sürecek projede, Pamukkale üniversitesi Bilgisayar Mühendisliği Bölümü öğretim üyesi Dr. Elif Haytaoğlu araştırmacı olarak görev alacaktır. Projede, iki doktora, iki yüksek lisans ve son iki senemizde iki lisans öğrencisi bursiyer olarak görev alacaktır.
Citation - Scopus: 2
Ssqem: Semi-Supervised Quantum Error Mitigation
(IEEE, 2022) Sayar, Alperen; Arslan Suayb S.; Çakar Tuna
One of the fundamental obstacles for quantum computation (especially in noisy intermediate-scale quantum (NISQ) era) to be a near-term reality is the manufacturing gate/measurement technologies that make the system state quite fragile due to decoherence. As the world we live in is quite far away from the ideal, complex particle-level material imperfections due to interactions with the environment are an inevitable part of the computation process. Hence keeping the accurate state of the particles involved in the computation becomes almost impossible. In this study, we posit that any physical quantum computer sys-tem manifests more multiple error source processes as the number of qubits as well as depth of the circuit increase. Accordingly, we propose a semi-supervised quantum error mitigation technique consisting of two separate stages each based on an unsupervised and a supervised machine learning model, respectively. The proposed scheme initially learns the error types/processes and then compensates the error due to data processing and the projective measurement all in the computational basis. © 2022 IEEE.
Citation - WoS: 13
Citation - Scopus: 16
Face Recognition With Patch-Based Local Walsh Transform
(Elsevier, 2018) Uzun-Per, Meryem; Gökmen, Muhittin
In this paper, we present a novel dense local image representation method called Local Walsh Transform (LWT)by applying the well-known Walsh Transform (WT) to each pixel of an image. The LWT decomposes an image into multiple components, and produces LWT complex images by using the symmetrical relationship between them. Cascaded LWT (CLWT) is also a dense local image representation obtained by applying the LWT again to real and imaginary parts of LWT complex images. Applying the LWT once more to real and imaginary parts of LWT complex images increases the success rate especially on low resolution images. In order to combine the advantages of sparse and dense local image representations, we present Patch-based LWT (PLWT) and Patch-based CLWT (PCLWT) by applying the LWT and CLWT, respectively, to patches extracted around landmarks of multi-scaled face images. The extracted high dimensional features of the patches are reduced through the application of the Whitened Principal Component Analysis (WPCA). Experimental results show that both thePLWT and PCLWT are robust to illumination and expression changes, occlusion and low resolution. The state-of-the-art performance is achieved on the FERET and SCface databases, and the second best unsupervised category result is achieved on the LFW database.
Neural Coreference Resolution for Turkish
(2023) Demir, Şeniz
Coreference resolution deals with resolving mentions of the same underlying entity in a given text. This challenging task is an indispensable aspect of text understanding and has important applications in various language processing systems such as question answering and machine translation. Although a significant amount of studies is devoted to coreference resolution, the research on Turkish is scarce and mostly limited to pronoun resolution. To our best knowledge, this article presents the first neural Turkish coreference resolution study where two learning-based models are explored. Both models follow the mention-ranking approach while forming clusters of mentions. The first model uses a set of hand-crafted features whereas the second coreference model relies on embeddings learned from large-scale pre-trained language models for capturing similarities between a mention and its candidate antecedents. Several language models trained specifically for Turkish are used to obtain mention representations and their effectiveness is compared in conducted experiments using automatic metrics. We argue that the results of this study shed light on the possible contributions of neural architectures to Turkish coreference resolution.
Citation - Scopus: 1
Improved Bounds on the Moments of Guessing Cost
(IEEE, 2022) Arslan, Suayb S.; Haytaoglu, Elif
Guessing a random variable with finite or countably infinite support in which each selection leads to a positive cost value has recently been studied within the context of "guessing cost". In those studies, similar to standard guesswork, upper and lower bounds for the rho-th moment of guessing cost are described in terms of the known measure Renyi's entropy. In this study, we non-trivially improve the known bounds using previous techniques along with new notions such as balancing cost. We have demonstrated that the novel lower bound proposed in this work, achieves 5.84%, 18.47% higher values than that of the known lower bound for rho = 1 and rho = 5, respectively. As for the upper bound, the novel expression provides 10.93%, 5.54% lower values than that of the previously presented bounds for rho = 1 and rho = 5, respectively.
What Is Neuroentrepreneurship? the Theoretical Framework, Critical Evaluation, and Research Program
(2021) Çakar,Tuna; Girişken, Arzu
As interest in entrepreneurship research to identify the possible economic development opportunities that entrepreneurs can provide, entrepreneurship research's objective tools are reaching their limits. Researchers in entrepreneurship are striving to discover new techniques and methodologies to answer questions about what makes a person an entrepreneur and perhaps identify and encourage an entrepreneur in the next step. Although a great deal of research has been done to answer these questions scientifically, traditional techniques have failed to produce the desired answers. For this reason, researchers working in the entrepreneurship field have recently been increasingly interested in applying neuroscience methods, especially after the proliferation of research fields such as neuroeconomics, neuromarketing, and neuropolitics. Although the population of neuroentrepreneurship research is gradually increasing, we cannot say that the field has been studied theoretically enough yet. In this article, a theoretical definition of neuroentrepreneurship is made, and a scientific framework is tried to be gained on the way to future research.
Citation - WoS: 2
Citation - Scopus: 2
Warning Notes in a Learner’s Dictionary: a Study of the Effectiveness of Different Formats
(International Journal of Lexicography, 2022) Çakar, Tuna; Nesi, Hilary; Nural, Şükrü
This study used an online correction task to explore the extent to which different types of warning notes in Longman Dictionary of Contemporary English Online were heeded when users tried to correct errors in the use of L2 target words. The task was completed by 332 participants, yielding 1,819 answers produced after clicking on links to relevant entries. Warning notes were categorised in terms of their formatting features, but there were found to be inconsistencies in the way the dictionary associated different categories with different kinds of learner error. Participants judged warning notes with more visual enhancements to be more useful, but in the correction task the position of the warning notes also seemed to affect the degree to which the warnings were successfully applied. Different types of warning notes in learners’ dictionaries have not been examined previously in any depth, and the results suggest that some adjustments to formatting and placement might make them more effective.
Citation - WoS: 8
Citation - Scopus: 5
Recognizing Non-Manual Signs in Turkish Sign Language
(IEEE, 2019) Gökberk, Berk; Akarun, Lale; Aktaş, Müjde
Recognition of non-manual components in sign language has been a neglected topic, partly due to the absence of annotated non-manual sign datasets. We have collected a dataset of videos with non-manual signs, displaying facial expressions and head movements and prepared frame-level annotations. In this paper, we present the Turkish Sign Language (TSL) non-manual signs dataset and provide a baseline system for non-manual sign recognition. A deep learning based recognition system is proposed, in which the pre-trained ResNet Convolutional Neural Network (CNN) is employed to recognize question, negation side to side and negation up-down, affirmation and pain movements and expressions. Our subject independent method achieves 78.49% overall frame-level accuracy on 483 TSL videos performed by six subjects, who are native TSL signers. Prediction results of consecutive frames are filtered for analyzing the qualitative results.
Citation - Scopus: 4
Multi-View Reconstruction of 3d Human Pose With Procrustes Analysis
(IEEE, 2019) Gökberk, Berk; Akarun, Lale; Temiz, Hüseyin
Recovery of 3D human pose from cameras has been the subject of intensive research in the last decade. Algorithms that can estimate the 3D pose from a single image have been developed. At the same time, many camera environments have an array of cameras. In this paper, after aligning the poses obtained from single images using Procrustes Analysis, median filtering is utilized to eliminate outliers to find final reconstructed 3D body joint coordinates. Experiments performed on the CMU Panoptic, and Human3.6M databases demonstrate that the proposed system achieves accurate 3D body joint reconstructions. Additionally, we observe that camera selection is useful to decrease the system complexity while attaining the same level of reconstruction performance.
The Neural Correlates of the Effect of Belief in Free Will on Third-Party Punishment: an Optical Brain Imaging (fnirs) Study
(Cognitive Science Society, 2022) Çakar, Tuna; Akyürek, Güçlü; Erözden, Ozan; Şahin, Türkay; Keskin, İrem Nur; Ünlü, Meryem; Özen, Deniz Hazal; Özen, Zeynep
Third party punishment (TPP), or altruistic punishment, is specifically human prosocial behavior. TPP denotes the administration of a sanction to a transgressor by an individual that is not affected by the transgression. In some evolutionary accounts, TPP is considered crucial for the stability of cooperation and solidarity in larger groups formed by genetically unrelated individuals. Belief in free will (BFW), on the other hand, is the idea that humans have control over their behavior. BFW is a human universal notion that, in some studies, has been found to be supportive of prosocial behavior. In our study, we examined the effect of BFW on TPP under high and low affect scenarios through optical brain imaging (fNIRS). We hypothesized that in low affect cases, there would be a positive correlation between the strength of the BFW and the severity of the punishment inflicted. Obtained results and related statistical analyses indicate that participants with higher degree of BFW have more neural activation in their right dorsolateral prefrontal cortex (DLPFC) (hbo and hbt measures) in high affect scenarios, whereas the participants with lower degree of BFW have higher levels of neural activation in the medial PFC (hbo and hbt measures) in low affect scenarios. These empirical findings are in line with the research findings in the relevant academic literature and support the hypothesis that the degree of BFW influences punishment decisions.
An Exploratory Study on the Effect of Contour Types on Decision Making Via Optic Brain Imaging Method (fnirs)
(eScholarship, 2023) Demircioglu, Esin Tuna; Girişken, Yener; Çakar, Tuna
Decision-making is a combination of our positive anticipations from the future with the contribution of our past experiences, emotions, and what we perceive at the moment. Therefore, the cues perceived from the environment play an important role in shaping the decisions. Contours, which are the hidden identity of the objects, are among these cues. Aesthetic evaluation, on the other hand, has been shown to have a profound impact on decision-making, both as a subjective experience of beauty and as having an evolutionary background. The aim of this empirical study is to explain the effect of contour types on preference decisions in the prefrontal cortex through risk-taking and aesthetic appraisal. The obtained findings indicated a relation between preference decision, contour type, and PFC subregion. The results of the current study suggest that contour type is an effective cue in decision-making, furthermore, left OFC and right dlPFC respond differently to contour types.
Dog Walker Segmentation
(IEEE, 2022) Ercan, Alperen; Karan, Baris; Çakar, Tuna
In this study dog walkers were separated into clusters according to walkers' walk habits. Due to the fact that the distributions were non-normal, normalization algorithms were applied before the onset of clustering. After normalizing, K Means algorithm and Gaussian Mixture Models used for finding optimum cluster count. According to these clusters, walkers' consecutive months separated to follow-up their behavioral traits. This part of the study adds value to the project to examine walkers' behaviors closer.