WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/4465

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Now showing 1 - 20 of 136

Citation - WoS: 0
Citation - Scopus: 0
The Acquisition and Use of Relative Clauses in Turkish-Learning Children's Conversational Interactions: a Cross-Linguistic Approach (vol 46, Pg 1142, 2019)
(Cambridge Univ Press, 2022) Uzundag, Berna A.; Arslan Uzundağ, Berna; Kuntay, Aylin C.
[Abstract Not Available]
Citation - WoS: 7
The Act of Killing an Interview With Joshua Oppenheimer
(CINEASTE, 2013) Behlil, Melis; Behlil, Melis; Oppenheimer, Joshua
[Abstract Not Available]
Citation - WoS: 60
Citation - Scopus: 65
Adventures in Data Analysis: a Systematic Review of Deep Learning Techniques for Pattern Recognition in Cyber-Physical Systems
(Springer, 2023) Amiri, Zahra; Jafari Navimipour, Nima; Heidari, Arash; Navimipour, Nima Jafari; Unal, Mehmet; Mousavi, Ali
Machine Learning (ML) and Deep Learning (DL) have achieved high success in many textual, auditory, medical imaging, and visual recognition patterns. Concerning the importance of ML/DL in recognizing patterns due to its high accuracy, many researchers argued for many solutions for improving pattern recognition performance using ML/DL methods. Due to the importance of the required intelligent pattern recognition of machines needed in image processing and the outstanding role of big data in generating state-of-the-art modern and classical approaches to pattern recognition, we conducted a thorough Systematic Literature Review (SLR) about DL approaches for big data pattern recognition. Therefore, we have discussed different research issues and possible paths in which the abovementioned techniques might help materialize the pattern recognition notion. Similarly, we have classified 60 of the most cutting-edge articles put forward pattern recognition issues into ten categories based on the DL/ML method used: Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Generative Adversarial Network (GAN), Autoencoder (AE), Ensemble Learning (EL), Reinforcement Learning (RL), Random Forest (RF), Multilayer Perception (MLP), Long-Short Term Memory (LSTM), and hybrid methods. SLR method has been used to investigate each one in terms of influential properties such as the main idea, advantages, disadvantages, strategies, simulation environment, datasets, and security issues. The results indicate most of the articles were published in 2021. Moreover, some important parameters such as accuracy, adaptability, fault tolerance, security, scalability, and flexibility were involved in these investigations.
Citation - WoS: 0
Aid and Technological Cooperation as a Foreign Policy Tool for Emerging Donors: the Case of Brazil
(Uluslararasi Iliskiler Konseyi Dernegi, 2022) Akinci, Basri Alp
[Abstract Not Available]
Citation - WoS: 113
Citation - Scopus: 146
Applications of Ml/Dl in the Management of Smart Cities and Societies Based on New Trends in Information Technologies: a Systematic Literature Review
(Elsevier, 2022) Heidari, Arash; Jafari Navimipour, Nima; Navimipour, Nima Jafari; Unal, Mehmet
The goal of managing smart cities and societies is to maximize the efficient use of finite resources while enhancing the quality of life. To establish a sustainable urban existence, smart cities use some new technologies such as the Internet of Things (IoT), Internet of Drones (IoD), and Internet of Vehicles (IoV). The created data by these technologies are submitted to analytics to obtain new information for increasing the smart societies and cities' efficiency and effectiveness. Also, smart traffic management, smart power, and energy management, city surveillance, smart buildings, and patient healthcare monitoring are the most common applications in smart cities. However, the Artificial intelligence (AI), Machine Learning (ML), and Deep Learning (DL) approach all hold a lot of promise for managing automated activities in smart cities. Therefore, we discuss different research issues and possible research paths in which the aforementioned techniques might help materialize the smart city notion. The goal of this research is to offer a better understanding of (1) the fundamentals of smart city and society management, (2) the most recent developments and breakthroughs in this field, (3) the benefits and drawbacks of existing methods, and (4) areas that require further investigation and consideration. IoT, cloud computing, edge computing, fog computing, IoD, IoV, and hybrid models are the seven key emerging de-velopments in information technology that, in this paper, are considered to categorize the state-of-the-art techniques. The results indicate that the Conventional Neural Network (CNN) and Long Short-Term Memory (LSTM) are the most commonly used ML method in the publications. According to research, the majority of papers are about smart cities' power and energy management. Furthermore, most papers have concentrated on improving only one parameter, where the accuracy parameter obtains the most attention. In addition, Python is the most frequently used language, which was used in 69.8% of the papers.
Citation - WoS: 0
Artisans Abroad: British Migrant Workers in Industrialising Europe, 1815-1870
(Routledge Journals, Taylor & Francis Ltd, 2023) Sefer, Akin; Sefer, Akın
[No Abstract Available]
Citation - WoS: 8
Citation - Scopus: 8
Beyond Sightseeing: How Can Tourism Affect Public/Global Health in Modern Society?
(Int Soc Global Health, 2022) Wen, Jun; Kozak, Metin; Kozak, Metin; Jiang, Yangyang
[Abstract Not Available]
Citation - WoS: 11
Citation - Scopus: 15
Bidding of Price Taker Power Generators in the Deregulated Turkish Power Market
(Pergamon-Elsevier Science Ltd, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Yücekaya, Ahmet
In deregulated power markets power firms bid into the day-ahead power market either with buy offers or sell offers. The auction mechanism and competition determine the equilibrium price and quantity for each hour. If the bid price of a company is below the market clearing price then the offer of the company is accepted and rewarded with the market price. A company can be a price maker or price taker depending on the capacity it offers to the market. A price-taker unit must determine the right offer that will maximize their profit given price uncertainty and blind auction rules. This paper first examines power supply in the Turkish electricity market and bidding process. Then a marginal cost-based Monte Carlo method is developed to determine hourly and block bidding strategies of price taker units. Historical market prices are then implemented in a normal distribution to generate hourly price scenarios. A solution methodology is developed that maximizes the expected profit of each hourly and block bidding strategy over price scenarios. The generator is able to both evaluate the hourly bidding and block bidding strategies and find the best bidding strategy that will be submitted to the market using the proposed methodology. The model is illustrated for two coal units in Turkish power market and the results are presented. (C) 2013 Elsevier Ltd. All rights reserved.
Citation - WoS: 53
Citation - Scopus: 58
Biodegradable Piezoelectric Polymers: Recent Advancements in Materials and Applications
(Wiley, 2023) Istıf, Emın; Bathaei, Mohammad Javad; Istif, Emin; Karimi, Seyed Nasir Hosseini; Beker, Levent
Recent materials, microfabrication, and biotechnology improvements have introduced numerous exciting bioelectronic devices based on piezoelectric materials. There is an intriguing evolution from conventional unrecyclable materials to biodegradable, green, and biocompatible functional materials. As a fundamental electromechanical coupling material in numerous applications, novel piezoelectric materials with a feature of degradability and desired electrical and mechanical properties are being developed for future wearable and implantable bioelectronics. These bioelectronics can be easily integrated with biological systems for applications, including sensing physiological signals, diagnosing medical problems, opening the blood-brain barrier, and stimulating healing or tissue growth. Therefore, the generation of piezoelectricity from natural and synthetic bioresorbable polymers has drawn great attention in the research field. Herein, the significant and recent advancements in biodegradable piezoelectric materials, including natural and synthetic polymers, their principles, advanced applications, and challenges for medical uses, are reviewed thoroughly. The degradation methods of these piezoelectric materials through in vitro and in vivo studies are also investigated. These improvements in biodegradable piezoelectric materials and microsystems could enable new applications in the biomedical field. In the end, potential research opportunities regarding the practical applications are pointed out that might be significant for new materials research.
Citation - WoS: 3
Citation - Scopus: 1
The Black Sea Region: The Neighbourhood Too Close To Yet Still Far From the European Union
(Routledge Journals Taylor & Francis Ltd, 2014) Acikmese Akgul, Sinem; Trıantafyllou, Dımıtrıos; Triantaphyllou, Dimitrios; Akgül Açıkmeşe, Sinem
[Abstract Not Available]
Citation - WoS: 3
Citation - Scopus: 3
Blockchain Systems in Embedded Internet of Things: Systematic Literature Review, Challenges Analysis, and Future Direction Suggestions
(Mdpi, 2022) Darbandi, Mehdi; Jafari Navimipour, Nima; Al-Khafaji, Hamza Mohammed Ridha; Nasab, Seyed Hamid Hosseini; AlHamad, Ahmad Qasim Mohammad; Ergashevich, Beknazarov Zafarjon; Navimipour, Nima Jafari
Internet of Things (IoT) environments can extensively use embedded devices. Without the participation of consumers; tiny IoT devices will function and interact with one another, but their operations must be reliable and secure from various threats. The introduction of cutting-edge data analytics methods for linked IoT devices, including blockchain, may lower costs and boost the use of cloud platforms. In a peer-to-peer network such as blockchain, no one has to be trusted because each peer is in charge of their task, and there is no central server. Because blockchain is tamper-proof, it is connected to IoT to increase security. However, the technology is still developing and faces many challenges, such as power consumption and execution time. This article discusses blockchain technology and embedded devices in distant areas where IoT devices may encounter network shortages and possible cyber threats. This study aims to examine existing research while also outlining prospective areas for future work to use blockchains in smart settings. Finally, the efficiency of the blockchain is evaluated through performance parameters, such as latency, throughput, storage, and bandwidth. The obtained results showed that blockchain technology provides security and privacy for the IoT.
Citation - WoS: 7
Citation - Scopus: 6
Botnets Unveiled: a Comprehensive Survey on Evolving Threats and Defense Strategies
(Wiley, 2024) Jafari Navimipour, Nima; Jamali, Mohammad Ali Jabraeil; Heidari, Arash; Navimipour, Nima Jafari
Botnets have emerged as a significant internet security threat, comprising networks of compromised computers under the control of command and control (C&C) servers. These malevolent entities enable a range of malicious activities, from denial of service (DoS) attacks to spam distribution and phishing. Each bot operates as a malicious binary code on vulnerable hosts, granting remote control to attackers who can harness the combined processing power of these compromised hosts for synchronized, highly destructive attacks while maintaining anonymity. This survey explores botnets and their evolution, covering aspects such as their life cycles, C&C models, botnet communication protocols, detection methods, the unique environments botnets operate in, and strategies to evade detection tools. It analyzes research challenges and future directions related to botnets, with a particular focus on evasion and detection techniques, including methods like encryption and the use of covert channels for detection and the reinforcement of botnets. By reviewing existing research, the survey provides a comprehensive overview of botnets, from their origins to their evolving tactics, and evaluates how botnets evade detection and how to counteract their activities. Its primary goal is to inform the research community about the changing landscape of botnets and the challenges in combating these threats, offering guidance on addressing security concerns effectively through the highlighting of evasion and detection methods. The survey concludes by presenting future research directions, including using encryption and covert channels for detection and strategies to strengthen botnets. This aims to guide researchers in developing more robust security measures to combat botnets effectively. Exploring botnets: evolution, tactics, countermeasures. This survey dives into botnets, covering life cycles, communication, and evasion tactics. It highlights challenges and future strategies for combating cyber threats. image
Citation - WoS: 6
Citation - Scopus: 9
Can Law Impose Competition? a Critical Discussion and Evidence From the Turkish Electricity Generation Market
(Pergamon-Elsevier Science Ltd, 2014) Oğuz, Fuat; Akkemik, Küçük Ali; Akkemik, K. Ali; Göksal, Koray
Electricity markets have undergone regulatory reforms since the early 1980s around the world. Technical analyses of these reforms usually pay lip service to the influence of politics over regulatory processes. Existing studies examine certain aspects of the market such as demand pricing and efficiency and they touch upon political issues only passingly when economic models cannot provide sufficient explanation This approach problematically takes politics as an ad hoc variable. This study shows that electricity is intrinsically a 'political good' and argues that any meaningful reform effort should take institutions as the starting point rather than a residual. The argument that politics has to be an endogenous variable in any model aspiring to explain behavior in electricity markets is demonstrated in the paper. The evidence for the political good character of electricity is found by examining the Turkish regulatory reform for Which it is argued that there is not a satisfactory relationship between expected and realized gains. (C) 2013 Elsevier Ltd. All rights reserved.
Citation - WoS: 0
Citation - Scopus: 0
Capital Markets Trade Openness and Productivity in Emerging Economies Introduction
(M.E Sharpe Inc., 2011) Bilgin, Mehmet Hüseyin; Danis, Hakan
[Abstract Not Available]
Citation - WoS: 73
Citation - Scopus: 73
Characteristics and Geochemistry of Precambrian Ophiolites and Related Volcanics From the Istanbul-Zonguldak Unit Northwestern Anatolia Turkey: Following the Missing Chain of the Precambrian South European Suture Zone To the East
(Elsevier Science Bv, 2004) Yiğitbaş, Erdinç; Kerrich, Robert; Yılmaz, Yücel; Elmas, Ali; Xie, QL
The Precambrian metamorphic basement of the Istanbul-Zonguldak Unit (IZU) NW Anatolia Turkey is represented by the Sunnice Group composed essentially of four different metamorphic assemblages: (1) Cele metaophiolite (2) Yellice metavolcanics (3) Demirci metamorphics and (4) Dirgine metagranite. The field relations and structural characteristics of these units were studied and representative geochemical analyses of Cele metaophiolite and related volcanics were obtained from the Sunnice Almacik and Arrnutlu areas. Collectively the results are interpreted as the Cele Magmatic suite displaying disrupted components of a complete suprasubduction ophiolite. The Yellice metavolcanic sequence contains fragments of both an intra oceanic island arc and a back-arc basin association built on the ophiolite. The Demirci metamorphics represent reworked continental fragments forming the base of the metamorphic massifs. These three different metamorphic units were intruded after their amalgamation by the Dirgine granitic pluton dated at 570-590 Ma [Geol. Mag. 136 (5) (1999) 579
Citation - WoS: 0
Climate Crisis and Global Green New Deal: the Political Economy of Saving the Planet
(Routledge Journals, Taylor & Francis Ltd, 2022) Karabacak, Sumeyye
[Abstract Not Available]
Citation - WoS: 8
Citation - Scopus: 13
Cloud Healthcare Services: a Comprehensive and Systematic Literature Review
(Wiley, 2022) Rahimi, Morteza; Jafari Navimipour, Nima; Navimipour, Nima Jafari; Hosseinzadeh, Mehdi; Moattar, Mohammad Hossein; Darwesh, Aso
Over the last decade, the landscape of cloud computing has been significantly changed. It has been known as a paradigm in which a shared pool of computing resources is accessible for users. The rapid growth of the healthcare environment provides better medical services to reduce costs and increase competition among healthcare providers. Despite its crucial role in the cloud, no thorough study exists in this domain. This article presents a systematic study for healthcare services in the cloud environment. A well-organized overview of all the databases has been explored. By clustering the research goals of the found papers, we have derived four main research groups. We have further evaluated the papers concerning the background of the paper, QoS parameters, application area, or methods used for applying and formulating the main ideas presented in the works. This survey emphasizes the challenges, needs, benefits of using cloud computing in healthcare systems and provides a comprehensive and detailed study on cloud healthcare services, strengths, and weaknesses of the existing methods. Highlighting cloud health services can be the major focus of research for developing the urban healthcare system.
Citation - WoS: 17
Citation - Scopus: 17
Cognitive Styles and Religion
(Elsevier B.V., 2021) Yılmaz, Onurcan; Yılmaz, Onurcan
I discuss recent research suggesting that individual differences in cognitive style give rise to and explain religious and related supernatural and paranormal beliefs. To do so, I illustrate intuitive cognitive biases (e.g., anthropomorphism) underlying these beliefs and then review the accumulated evidence indicating that non-believers are more open-minded, reflective, and less susceptible to holding epistemically suspect beliefs (e.g., conspiracy theories) on average than those who believe in supernatural events or paranormal experiences such as astrology or magic. However, seeing religion as a search for truth positively predicts reasoning performance. Although these findings are robust across diverse measures, evidence for a causal relationship remains mixed. Stronger and more precise manipulations and cross-cultural investigations are needed.
Citation - WoS: 0
A Companion To Early Modern Istanbul
(Penn State Univ Press, 2023) Songulen, Nazli
[Abstract Not Available]
Citation - WoS: 27
Citation - Scopus: 34
A Comprehensive and Systematic Literature Review on the Big Data Management Techniques in the Internet of Things
(Springer, 2023) NaghibnAff, Arezou; Jafari Navimipour, Nima; Navimipour, Nima Jafari; Hosseinzadeh, Mehdi; Sharifi, Arash
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for BDM in IoT. This paper aims to study the important mechanisms in this area systematically. This paper studies articles published between 2016 and August 2022. Initially, 751 articles were identified, but a paper selection process reduced the number of articles to 110 significant studies. Four categories to study BDM mechanisms in IoT include BDM processes, BDM architectures/frameworks, quality attributes, and big data analytics types. Also, this paper represents a detailed comparison of the mechanisms in each category. Finally, the development challenges and open issues of BDM in IoT are discussed. As a result, predictive analysis and classification methods are used in many articles. On the other hand, some quality attributes such as confidentiality, accessibility, and sustainability are less considered. Also, none of the articles use key-value databases for data storage. This study can help researchers develop more effective BDM in IoT methods in a complex environment.

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