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Li-Fi Sistemlerinde MIMO-Genelleştirilmiş Uzay Kaydırmalı Anahtarlama Modülasyonu Tekniğiyle Fiziksel Katman Güvenliği
No full textBerdan Civata B.C.; et al.; Figes; Koluman; Loodos; Tarsus UniversityIn this study, a physical layer security algorithm based on generalized space shift keying modulation for visible light communication systems has been developed. Initially, the algorithm selects the most suitable index combinations for ideally activating the photodiodes in the receiver through a designed linear encoder, thereby enhancing error correction capabilities. Subsequently, a customized precoding matrix is developed using this index information and the channel state information to provide an optimum bit error rate for the legitimate receiver, Bob. This approach also degrades the bit error performance of the illegitimate receiver, Eve, thus ensuring high-level security at the physical layer in Li-Fi systems. Experiments conducted with Monte-Carlo simulations demonstrate the effectiveness of this methodology for scenarios requiring secure communication.Conference Proceedings Citation Index - Scienc
Selection of Tramcars for Sustainable Urban Transportation by Using the Modified Waspas Approach Based on Heronian Operators
No full textküçükönder, hande/0000-0002-0853-8185The wrong design of rail system vehicle fleets is one of the most critical problems in terms of urban transportation. Light rail system fleets in many large cities, including Istanbul, consist of various types and feature vehicles. It creates significant problems in integrating each rail system vehicle into the system. In addition, while it is necessary to keep an inventory of spare parts for each different type of vehicle, it requires different qualifications for professionals involved in processes such as maintenance and repair, leading to extra costs. In this context, the study's primary purpose is to determine the most suitable light rail vehicles for urban transportation systems and create vehicle fleets accordingly. In that regard, the study aims to provide a reliable and practical decision-making model that can be used as a roadmap for decision-makers when choosing tramcars to solve these problems. The present work proposes a hybrid procedure integrating the Best and Worst Method (BWM) and Power-Heronian Weighted Aggregated Sum Product Assessment (WASPAS'PH) approaches. The most critical implication of the work indicated that the acquisition cost per tramcar set (0.148) is still the most influential factor. The economic lifespan of tramcars (0.037), the number of seats in a vehicle set (0.041), and energy consumption (0.072) have followed the most significant criterion, respectively. Besides, it highlighted that the A14 Brand CR (0.7819) is the most appropriate option for well-structuring the urban light rail system fleet. An extensive validation test to check the suggested model's robustness confirmed the procedure's stability and consistency
A reliable method for data aggregation on the industrial internet of things using a hybrid optimization algorithm and density correlation degree
No full textHeidari, Arash/0000-0003-4279-8551The Internet of Things (IoT) is a new information technology sector in which each device may receive and distribute data across a network. Industrial IoT (IIoT) and related areas, such as Industrial Wireless Networks (IWNs), big data, and cloud computing, have made significant strides recently. Using IIoT requires a reliable and effective data collection system, such as a spanning tree. Many previous spanning tree algorithms ignore failure and mobility. In such cases, the spanning tree is broken, making data delivery to the base station difficult. This study proposes an algorithm to construct an optimal spanning tree by combining an artificial bee colony, genetic operators, and density correlation degree to make suitable trees. The trees' fitness is measured using hop count distances of the devices from the base station, residual energy of the devices, and their mobility probabilities in this technique. The simulation outcomes highlight the enhanced data collection reliability achieved by the suggested algorithm when compared to established methods like the Reliable Spanning Tree (RST) construction algorithm in IIoT and the Hop Count Distance (HCD) based construction algorithm. This proposed algorithm shows improved reliability across diverse node numbers, considering key parameters including reliability, energy consumption, displacement probability, and distance.Kadir Has UniversityNo Statement Availabl
Building Damage Assessment To Facilitate Post-Earthquake Search and Rescue Missions by Leveraging a Machine Learning Algorithm
No full textIEEE SMC; IEEE Turkiye SectionEarthquakes have a severe impact on people's lives and infrastructure. Many emergency institutes and search and rescue missions need accurate post-earthquake response strategies, particularly in building damage assessment. Traditional methods, relying on manual inspections, are inefficient compared to Machine Learning (ML) algorithms. Thus, Random Forest (RF) algorithms stand out because they handle diverse datasets effectively and minimize overfitting. The study outlines the methodology encompassing data preparation, exploratory analysis, feature engineering, and model building, employing a preprocessing pipeline integrating numerical and categorical features. Additionally, Principal Component Analysis (PCA) is applied to reduce dimensionality. The results of the RF model showed an accuracy of 94% and the highest F1-score of 97% among all the grades, demonstrating its efficacy in predicting damage grades post-earthquake. The results can help support better disaster management plans by helping to prioritize rescue operations and allocate resources wisely. © 2024 IEEE
Comparing Virtual Reality To Augmented Reality: Over Eye-Hand Coordination and Stiffness Discrimination
No full textBu tez 2 kullanıcı çalışmasından oluşmaktadır. İlk çalışma için Fitts yasasına dayalı bir El-Göz Koordinasyon Eğitimi (EHCT) sistemi tasarlanmıştır. Bu çalışmada kullanıcı motor performansı uzun süreli bir çalışma kapsamında Sanal Gerçeklik (VR), Artırılmış Gerçeklik (AR) ve 2 boyutlu (2D) dokunmatik ekran kullanırken karşılaştırılmıştır. Yirmi katılımcının motor performansını, doğruluk, hassasiyet, hız, hata oranı ve hiçbirine odaklanan beş görev talimatı kullanarak on günlük bir kullanıcı çalışması boyunca inceledik. Çalışmanın bulguları, her bir görev talimatının katılımcıların bir veya daha fazla psikomotor özelliği üzerinde benzersiz bir etkiye sahip olduğunu ortaya koyarak özelleştirilmiş eğitim sistemlerinin önemini vurgulamıştır. Çeşitli ekran teknolojilerini incelediğimizde, çoğu katılımcının VR kullanırken gösterdiği performans gelişimlerinin 2D veya AR kullanmaya kıyasla daha iyi olduğunu gözlemledik. Ayrıca, EHCT sistemlerinde genel motor performansının gelişimini izlemek için etkili bir verimliliğin mükemmel bir seçim olabileceğini bulduk. İkinci çalışma için ise, iki farklı ortamda dokunsal geri bildirim sağlarken algı ve performanstaki farklılıkları araştırmak için tasarlanmıştır: VR ve AR. Bu kullanıcı çalışmasında, katılımcılar aynı görünen ancak farklı sertlik seviyelerine sahip sanal kutularla etkileşime girmiş ve Doğrusal Motor tabanlı bileğe takılan Haptik cihaz (LAWrHap) aracılığıyla aldıkları haptik geri bildirime dayanarak daha yüksek sertlik seviyesine sahip nesneleri belirleyebilmişlerdir. Bu çalışmanın bulguları, dokunsal geribildirimin VR ve AR sistemlerine entegre edilmesinin, VR ile karşılaştırıldığında, hassasiyeti ve verimliliği artıran gerçek dünya bağlamsal ipuçları sayesinde görev performansını ve algısını geliştirdiğini ortaya koymuştur. Doğruluk ve hassasiyet ortamlar arasında benzer olsa da VR veya AR kullanmak bilişsel yükün azaltılması ve daha etkili kullanıcı etkileşimleri açısından farklı avantajlar sunmuştur. Anahtar Sözcükler: Sanal Gerçeklik Etkileşimleri, Artırılmış Gerçeklik Etkileşimleri, Göz-El Koordinasyonu, Ekran teknolojileri, Görev talimatları, Dokunsal ArayüzlerThis thesis is consisted of 2 user studies. A Eye-Hand Coordination Training (EHCT) system was designed based on the fitts' law. In this study user motor performance was compared in Virtual Reality (VR), Augmented Reality (AR), and on a 2D touchscreen display in a longitudinal study. We studied twenty participants' motor performance over the course of a ten-days user study using five task instructions that focused on accuracy, precision, speed, error rate, and none. The study's findings revealed that each task instruction has a unique effect on one or more of the trainees psycho motor characteristics, highlighting the significance of customized training systems. When it came to various display technologies, most participants could see their improvement in VR was better than 2D or AR. Another study was designed to investigates the differences in perception and performance while providing haptic feedback in two different environments: VR and AR. In this user study, participants interacted with virtual boxes that looked the same but had varying stiffness levels, and they were able to identify the objects with a higher stiffness level based on the haptic feedback they got through Linear Actuator based wristworn Haptic device (LAWrHap). The findings of this study reveled that integrating haptic feedback into VR and AR systems improves task performance and perception when compared to VR, owing to real-world contextual cues that increase precision and efficiency. Although accuracy and sensitivity were similar across environments, VR and AR offered distinct advantages in terms of cognitive load reduction and more effective user interactions. Keywords: Virtual Reality Interactions, Augmented Reality Interactions, Eye-Hand Coordination, Display technologies, Task instructions, Haptic Interface
Dewids: Dew Computing for Intrusion Detection System in Edge of Things
No full textEdge of Things (EoT) is a network of edge devices in which sensors, networks, electronics, and software are included. EoT enables uninterrupted data transfer from the cloud layer to edge devices through the Internet. In this transmission, there need strong privacy and security concerns. Although day by day throughout the universe the number of devices is increasing with new features, shapes, sizes, usage, protocol, etc., the conventional method of security and privacy systems are not sufficient to control the ubiquitous EoT. The conventional IDS system does not work on unstable Internet so to overcome this issue we will use Dew computing in the IDS system. With the assistance of the dew server, an individual has more control and adaptability to access data in the absence of an unstable Internet connection. IDS is used to detect different kinds of attacks in the edge layer. But sometimes it fails to detect the false alarm, which may create a severe problem. Various types of network attacks like Malware, MITM, Remote Code Execution, etc. in different networks are detected by Intrusion Detection System (IDS) and prevented by Intrusion Prevention System (IPS). At the time of the detection procedure, several alarms are generated, which decreases the effectiveness of IDS. Using an alarm filter can be a better solution to overcome this type of problem. An intelligent alarm filtration mechanism can be designed by a selective machine-learning-based classifier in DewIDS then DewIPS can block the attempted intrusion or remediate the incident after SOC investigation. This work aims to present a comprehensive survey of existing Dew Computing for Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) in Edge of Things. © 2023 The Author(s),. All rights reserved
Unveiling the Significance of Individual Level Predictions: a Comparative Analysis of Gru and Lstm Models for Enhanced Digital Behavior Prediction
No full textKiyakoglu, Burhan Yasin/0000-0001-9254-3181; Aydin, Mehmet/0000-0002-3995-6566The widespread use of technology has led to a transformation of human behaviors and habits into the digital space; and generating extensive data plays a crucial role when coupled with forecasting techniques in guiding marketing decision-makers and shaping strategic choices. Traditional methods like autoregressive moving average (ARMA) can-not be used at predicting individual behaviors because we can-not create models for each individual and buy till you die (BTYD) models have limitations in capturing the trends accurately. Recognizing the paramount importance of individual-level predictions, this study proposes a deep learning framework, specifically uses gated recurrent unit (GRU), for enhanced behavior analysis. This article discusses the performance of GRU and long short-term memory (LSTM) models in this framework for forecasting future individual behaviors and presenting a comparative analysis against benchmark BTYD models. GRU and LSTM yielded the best results in capturing the trends, with GRU demonstrating a slightly superior performance compared to LSTM. However, there is still significant room for improvement at the individual level. The findings not only demonstrate the performance of GRU and LSTM models but also provide valuable insights into the potential of new techniques or approaches for understanding and predicting individual behaviors.Burhan Y. KiyakogluThe APC was funded by Burhan Y. Kiyakoglu.Science Citation Index Expande
For Centenary of the Lausanne Treaty Re-Interpretation and Re-Implementation of Linguistic Minority Rights of Lausanne
No full textThe Treaty of Lausanne was signed on 24th July 1923 as a peace treaty that ended the first world war for Turkey and the allied powers. In a section entitled "protection of minorities", it provides rights for minorities. However, the beneficiaries of minority rights in Lausanne are more narrow than those provided in other treaties and declarations of the time. With a legal basis in domestic law, Turkey traditionally applied the rights provided in the Lausanne Treaty only for three so-called non-Muslim groups, i.e. Greeks, Armenians and Jews. Neither the Turkish delegation nor the members of the allied forces' delegations could foresee that some members of the Muslim groups of 1923 might quit Islam in the future and recourse to Lausanne rights as new beneficiaries. This article, by referring to preparatory works of the Treaty, examining its legal validity internationally and nationally, and applying interpretative principles of international treaties, argues for the extension of Lausanne rights to other groups via re-interpretation and re-implementation.Emerging Sources Citation Inde
Pious People, Patronage Jobs, and the Labor Market: Turkey Under Erdoğan's Akp
No full textIn fragmented societies, electoral competition often entails using public office to advance group interests. Using individual-level polling data from 2012 to 2018, we analyze whether age cohorts entering the labor market before and after the religiously conservative Justice and Development Party (AKP) assumed power in Turkey experienced different public employment outcomes based on their religion and religiosity. Our analysis reveals that under the AKP rule, pious Sunnis (who constitute a large part of the society) significantly increased their presence in public sector employment (notably among women) and in high-status private jobs (notably among men). Furthermore, the subset of highly religious Sunnis (only 9.3% of the population) improved their likelihood of being employed in the public sector compared to other pious Sunnis and everyone else. Our findings are likely to be driven by the lifting of the headscarf ban in public employment and AKP's strategic use of public employment and resources to reward like-minded groups in both the public and private spheres.Social Science Citation Inde
Design and Analysis of a Fault Tolerance Nano-Scale Code Converter Based on Quantum-Dots
No full textQuantum-dot cellular automata (QCA), QCA ), a nano-scale computer framework, is developing as a potential alternative to current transistor-based technologies. However, it is susceptible to a variety of fabrication-related errors and process variances because it is a novel technology. As a result, QCA-based circuits pose reliability-related problems since they are prone to faults. To address the dependability challenges, it is becoming increasingly necessary to create fault-tolerance QCA-based circuits. On the other hand, the applications of code converters in digital systems are essential for rapid signal processing. Using fault-tolerance XOR and multiplexer, this research suggests a nano-based binary-to-gray and gray-to-binary code converter circuit in a single layer to increase efficiency and reduce complexity. The fault-tolerance performance of the suggested circuits against cell omission, misalignment, displacement, and extra cell deposition faults has significantly improved. Concerning the generalized design metrics of QCA circuits, the fault-tolerance designs have been contrasted with the existing structures. The proposed fault-tolerance circuits' energy dissipation findings have been calculated using the precise QCADesigner-E power estimator tool. Using the QCADesigner-E program, the proposed circuits' functionality has been confirmed. The results implied the high efficiency and applicability of the proposed designs.Science Citation Index Expande