Bilgisayar Mühendisliği Bölümü Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1940
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Article Citation - WoS: 16Citation - Scopus: 20Physicians’ Ethical Concerns About Artificial Intelligence in Medicine: a Qualitative Study: “the Final Decision Should Rest With a Human”(Frontiers Media SA, 2024-11-27) Kahraman, F.; Aktas, A.; Bayrakceken, S.; Çakar, T.; Tarcan, H.S.; Bayram, B.; Ulman, Y.I.Background/aim: Artificial Intelligence (AI) is the capability of computational systems to perform tasks that require human-like cognitive functions, such as reasoning, learning, and decision-making. Unlike human intelligence, AI does not involve sentience or consciousness but focuses on data processing, pattern recognition, and prediction through algorithms and learned experiences. In healthcare including neuroscience, AI is valuable for improving prevention, diagnosis, prognosis, and surveillance. Methods: This qualitative study aimed to investigate the acceptability of AI in Medicine (AIIM) and to elucidate any technical and scientific, as well as social and ethical issues involved. Twenty-five doctors from various specialties were carefully interviewed regarding their views, experience, knowledge, and attitude toward AI in healthcare. Results: Content analysis confirmed the key ethical principles involved: confidentiality, beneficence, and non-maleficence. Honesty was the least invoked principle. A thematic analysis established four salient topic areas, i.e., advantages, risks, restrictions, and precautions. Alongside the advantages, there were many limitations and risks. The study revealed a perceived need for precautions to be embedded in healthcare policies to counter the risks discussed. These precautions need to be multi-dimensional. Conclusion: The authors conclude that AI should be rationally guided, function transparently, and produce impartial results. It should assist human healthcare professionals collaboratively. This kind of AI will permit fairer, more innovative healthcare which benefits patients and society whilst preserving human dignity. It can foster accuracy and precision in medical practice and reduce the workload by assisting physicians during clinical tasks. AIIM that functions transparently and respects the public interest can be an inspiring scientific innovation for humanity. Copyright © 2024 Kahraman, Aktas, Bayrakceken, Çakar, Tarcan, Bayram, Durak and Ulman.Article Citation - WoS: 3Citation - Scopus: 3A Benchmark Dataset for Turkish Data-To Generation(Elsevier, 2023-01-01) Demir, Şeniz; Öktem, SezaIn 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.Article Citation - WoS: 3Citation - Scopus: 3Exact Construction of Bs-Assisted Mscr Codes With Link Constraints(IEEE Communications Letters, 2022-02-01) Arslan, Şuayb ŞefikIt is clear that 5G network resources would be consumed by heavy data traffic owing to increased mobility, slicing, and layered/distributed storage system architecture. The problem is elevated when multiple node failures are repaired to address service quality requirements. Typical approaches include individual or cooperative data regeneration to efficiently utilize the available bandwidth. It is observed that storage systems of 5G and beyond technologies shall have a multi–layer architecture in which base stations (BS) would be present. Moreover, communication with each layer would be subject to various communication costs and link constraints. Under limited BS assistance and cooperation, the trade-off between storage per node and communication bandwidth has been established. In this trade–off, two operating points, namely minimum storage, and bandwidth regeneration are particularly important. In this study, we first identify the optimal number of BS use at the minimum storage regeneration point. An explicit code construction is provided subsequently for the exact minimum storage regeneration whereby each layer may help the repair process subject to a communication link constraint.Article Citation - WoS: 4Citation - Scopus: 6Data Repair-Efficient Fault Tolerance for Cellular Networks Using Ldpc Codes(IEEE, 2022-01-01) Haytaoglu, Elif; Kaya, Erdi; Arslan, Şuayb ŞefikThe base station-mobile device communication traffic has dramatically increased recently due to mobile data, which in turn heavily overloaded the underlying infrastructure. To decrease Base Station (BS) interaction, intra-cell communication between local devices, known as Device-to-Device, is utilized for distributed data caching. Nevertheless, due to the continuous departure of existing nodes and the arrival of newcomers, the missing cached data may lead to permanent data loss. In this study, we propose and analyze a class of LDPC codes for distributed data caching in cellular networks. Contrary to traditional distributed storage, a novel repair algorithm for LDPC codes is proposed which is designed to exploit the minimal direct BS communication. To assess the versatility of LDPC codes and establish performance comparisons to classic coding techniques, novel theoretical and experimental evaluations are derived. Essentially, the theoretical/numerical results for repair bandwidth cost in presence of BS are presented in a distributed caching setting. Accordingly, when the gap between the cost of downloading a symbol from BS and from other local network nodes is not dramatically high, we demonstrate that LDPC codes can be considered as a viable fault-tolerance alternative in cellular systems with caching capabilities for both low and high code rates.Article Citation - WoS: 6Citation - Scopus: 9A Data-Assisted Reliability Model for Carrier-Assisted Cold Data Storage Systems(Elsevier, 2020-04-01) Arslan, Şuayb Şefik; Göker, Turguy; Peng, JamesCold 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.Article Citation - WoS: 6Citation - Scopus: 7A Reliability Model for Dependent and Distributed Mds Disk Array Units(IEEE Transactions on Reliability, 2019-03-01) Arslan, Şuayb ŞefikArchiving 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.Article Citation - WoS: 13Citation - Scopus: 16Face Recognition With Patch-Based Local Walsh Transform(Elsevier, 2018-02-01) Uzun-Per, Meryem; Gökmen, MuhittinIn 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.