Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Article Citation - WoS: 1Citation - Scopus: 1Transcoding Web Pages Via Stylesheets and Scripts for Saving Energy on the Client(Wiley, 2022) Ünlü, Hüseyin; Yeşilada, YelizMobile devices and accessing the web have become essential in our daily lives. However, their limitations in terms of both hardware such as the battery, and software capabilities can affect the user experience such as battery drain. There are some best practices for the web page design that are shown to affect the downloading time of web pages. In this study, we report our experience in applying these practices to see their effect on energy saving. We propose two techniques: (1) concatenating external script and stylesheet files and (2) minifying external script and stylesheets that can be used to transcode web pages to improve energy consumption on the client-side and therefore improve the battery life. We present our experimental architecture, implementation, and a systematic evaluation of these two techniques. The evaluation results show that the proposed techniques can achieve approximately 12% processor energy-saving and 4% power saving in two different client types, 13% improvement in a typical laptop battery life, and 4% improvement in a typical mobile phone battery life.Article Citation - WoS: 55Citation - Scopus: 56Evaluation of an Artificial Intelligence System for Diagnosing Scaphoid Fracture on Direct Radiography(Springer Verlag, 2020) Özkaya, Emre; Topal, Fatih Esad; Bulut, Tuğrul; Gürsoy, Merve; Özuysal, Mustafa; Karakaya, ZeynepPurpose The aim of this study is to determine the diagnostic performance of artificial intelligence with the use of convolutional neural networks (CNN) for detecting scaphoid fractures on anteroposterior wrist radiographs. The performance of the deep learning algorithm was also compared with that of the emergency department (ED) physician and two orthopaedic specialists (less experienced and experienced in the hand surgery). Methods A total 390 patients with AP wrist radiographs were included in the study. The presence/absence of the fracture on radiographs was confirmed via CT. The diagnostic performance of the CNN, ED physician and two orthopaedic specialists (less experienced and experienced) as measured by AUC, sensitivity, specificity, F-Score and Youden index, to detect scaphoid fractures was evaluated and compared between the groups. Results The CNN had 76% sensitivity and 92% specificity, 0.840 AUC, 0.680 Youden index and 0.826Fscore values in identifying scaphoid fractures. The experienced orthopaedic specialist had the best diagnostic performance according to AUC. While CNN's performance was similar to a less experienced orthopaedic specialist, it was better than the ED physician. Conclusion The deep learning algorithm has the potential to be used for diagnosing scaphoid fractures on radiographs. Artificial intelligence can be useful for scaphoid fracture diagnosis particularly in the absence of an experienced orthopedist or hand surgeon.Article Citation - WoS: 5Citation - Scopus: 9Modeling Cultures of the Embedded Software Industry: Feedback From the Field(Springer Verlag, 2021) Akdur, Deniz; Say, Bilge; Demirörs, OnurEngineering of modern embedded systems requires complex technical, managerial and operational processes. To cope with the complexity, modeling is a commonly used approach in the embedded software industry. The modeling approaches in embedded software vary since the characteristics of modeling such as purpose, medium type and life cycle phase differ among systems and industrial sectors. The objective of this paper is to detail the use of a characterization model MAPforES ("Modeling Approach Patterns for Embedded Software"). This paper presents the results of applying MAPforES in multiple case studies. The applications are performed in three sectors of the embedded software industry: defense and aerospace, automotive and transportation, and consumer electronics. A series of both structured and semi-structured interviews with 35 embedded software professionals were conducted as part of the case studies. The characterization model was successfully applied to these cases. The results show that identifying individual patterns provides insight for improving both individual behavior and the behavior of projects and organizations.Article Citation - WoS: 9Citation - Scopus: 8Scalable Parallel Implementation of Migrating Birds Optimization for the Multi-Objective Task Allocation Problem(Springer Verlag, 2021) Öz, Dindar; Öz, IşılAs the distributed computing systems have been widely used in many research and industrial areas, the problem of allocating tasks to available processors in the system efficiently has been an important concern. Since the problem is proven to be NP-hard, heuristic-based optimization techniques have been proposed to solve the task allocation problem. Particularly, the current cloud-based systems have been grown massively requiring multiple features like lower cost, higher reliability, and higher throughput; therefore, the problem has become more challenging and approximate methods have gained more importance. Migrating birds optimization (MBO) algorithm offers successful solutions, especially for quadratic assignment problems. Inspired by the movement of the birds, it exhibits good results by its population-based approach . Since the algorithm needs to deal with many individuals in the population, and the neighbor solution generation phase takes substantial time for large problem instances, we need parallelism to have execution time improvements and make the algorithm practical for large-scale problems. In this work, we propose a scalable parallel implementation of the MBO algorithm, PMBO, for the multi-objective task allocation problem. We redesigned the implementation of the MBO algorithm so that its computationally heavy independent tasks are executed concurrently in separate threads. We compare our implementation with three parallel island-based approaches. The experimental results demonstrate that our implementation exhibits substantial solution quality improvements for difficult problem instances as the computing resources, namely parallelism, increase. Our scalability analysis also presents that higher parallelism levels offer larger solution improvement for the PMBO over the island-based parallel implementations on very hard problem instances.