Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/1248

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  • Conference Object
    Citation Count: 0
    REFLECTIONS ON THE INTERNATIONAL NOISE AWARENESS DAY 2023 ACTIVITIES
    (Society of Acoustics, 2024) Şaher,K.; Dümen,A.Ş.; Sezgin,H.; Nas,S.; Kelle,D.; Demiral,Y.
    This paper presents an overview of the experiences and outcomes derived from the activities organized for International Noise Awareness Day 2023 in Turkey with the theme “Keep your hearing, keep your health”. Collaboratively organized by Turkish Acoustical Society, and Occupational Hygienists Society, the initiatives aimed to explore the role of sound in educational facilities, with a particular focus on the perspectives of students and teachers. These activities were a student drawing competition, an online International Symposium, a research project titled "Assessment of Acoustic Conditions in Schools and Health Effects on School," and an "Acoustics Workshop in Educational Buildings" conducted at the Izmir BLX Acoustics Laboratory. Drawing from our experiences and findings, we highlight the significance of actively involving researchers, acoustic consultants, occupational hygienists, teachers, students, and designers in such endeavours. Our findings indicate that inclusive approaches not only boost public engagement but also enhance awareness of behavioural, emotional, educational, administrative and design aspects related to sound. By promoting collaboration and participation in knowledge exchange, such activities significantly improve understanding of sound-related issues in schools. © 2024 Proceedings of the International Congress on Sound and Vibration. All rights reserved.
  • Book Part
    Citation Count: 0
    ENFORCED DEPARTURES, ANXIOUS ARRIVALS: A Turkish Diaspora in Israel
    (Taylor and Francis, 2024) Valansi,K.
    Drawing immigration was one of the main objectives of the newborn State of Israel, and this policy generated a strong pull factor for Jews worldwide. However, the mass emigration from Turkey was a surprise even to Israeli authorities who were not expecting such large numbers from a country where Jews were not expelled from or faced an existential threat. Nearly 40 per cent of Turkey’s Jewish community emigrated to Israel during 1948–1951. This mass migration was Turkey’s second-biggest emigration wave following labour emigration to Europe from the 1960s onwards. Despite its significance, Turkish Jewry is an understudied topic, especially in Turkish migration and diaspora studies. This chapter scrutinises the trajectory and current state of the Turkish Jewish diaspora in Israel. It presents an overview of the subject matter, including the historical background of Turkish Jews, their reasons for emigration, and how they have reconstructed their identity in Israel. © 2024 Taylor & Francis.
  • Conference Object
    Citation Count: 0
    Nigeria's Fossil Fuel Energy Consumption-GDP Relation and its Effect on National HDI:2005-2022
    (Institute of Electrical and Electronics Engineers Inc., 2024) Oyejide,O.; Akindele,G.; Efemena,O.
    The correlation between energy usage and economic growth is widely acknowledged. The placement within the dynamics of Nigeria's economic growth and fossil fuel usage is evaluated in this paper. Retrieved and processed data from reliable databases, such as "Our World in Data"and THE WORLD BANK, covering the years 2005 to 2022, were used to analyze the following: percentage of total primary energy consumption (fossil fuel), percentage of consumption per capita, percentage of total Gross Domestic Product (GDP), percentage of GDP per capita, and overall Human Development Index (HDI). The results showed fluctuations in GDP growth rates in tandem with stable energy consumption, a continuous reliance on fossil fuels in the face of a slow but steady rise in the HDI, and economic difficulties in certain years in spite of stable energy consumption. In contrast to predictions, the country's HDI, which has been rising steadily over time, was mostly unaffected by the non-linear link between GDP and fossil fuel usage. The study also showed variations in Adjusted Net Savings, indicating the unpredictability of the country's energy sector in the face of political and economic unpredictability. Notwithstanding these obstacles, the HDI showed a slow but noticeable improvement, suggesting that the income and savings Nigeria's petroleum resources provide to its population are not very beneficial. Considering the findings, policy-based recommendations were also offered. © 2024 IEEE.
  • Conference Object
    Citation Count: 0
    Probabilistic approach to assess and minimize the voltage violation risk in active distribution networks
    (Institute of Electrical and Electronics Engineers Inc., 2024) Kenari,M.T.; Ozdemir,A.; Heidari,A.
    The increasing trend in using renewable energy resources in distribution systems has encouraged system operators to find the best methods to decrease the growing uncertainty's impact on system operation. A probabilistic approach based on the combination of Monte Carlo simulation and Particle Swarm Algorithm is proposed in this paper to reduce the risk of voltage magnitude violations. Also, a novel criterion is used to assess the risk of voltage magnitude violations in distribution system operation. This index is based on providing voltage samples using a probabilistic approach. Therefore, enhancing the confidence level of voltage risk is considered an objective function in finding the optimum location of energy storage systems. The proposed approach is applied to the IEEE 33-bus test system, and the results show that two ESS units installed at appropriate locations can solve all the voltage magnitude violation problems. © 2024 IEEE.
  • Book Part
    Citation Count: 0
    Co-insurance and rights of subrogation post-Gard Marine And Energy v China National Chartering Company Ltd
    (Edward Elgar Publishing Ltd., 2024) Noussia,K.; Aslan,Y.C.
    [No abstract available]
  • Conference Object
    Citation Count: 0
    Comparing Deep Neural Networks and Machine Learning for Detecting Malicious Domain Name Registrations
    (Institute of Electrical and Electronics Engineers Inc., 2024) Çolhak,F.; Ecevit,M.İ.; Daǧ,H.; Creutzburg,R.
    This study highlights the effectiveness of deep neural network (DNN) models, particularly those integrating natural language processing (NLP) and multilayer perceptron (MLP) techniques, in detecting malicious domain registrations compared to traditional machine learning (ML) approaches. The integrated DNN models significantly outperform traditional ML models. Notably, DNN models that incorporate both textual and numeric features demonstrate enhanced detection capabilities. The utilized Canine + MLP model achieves 85.81% accuracy and an 86.46% Fl-score on the MTLP Dataset. While traditional ML models offer advantages such as faster training times and smaller model sizes, their performance generally falls short compared to DNN models. This study underscores the trade-offs between computational efficiency and detection accuracy, suggesting that their superior performance often justifies the added costs despite higher resource requirements, © 2024 IEEE.
  • Conference Object
    Citation Count: 0
    Voltage Profile Improvement in Unbalanced Distribution Networks for Probabilistic Generation and Consumption
    (Institute of Electrical and Electronics Engineers Inc., 2024) Bamatraf,M.; Ceylan,O.; Pisica,I.; Özdemir,A.
    Due to their technical, economical, and environmental advantages, active distribution networks implement renewable energy resources (RERs) such as photovoltaic (PV) units in distribution networks DNs. However, some drawbacks may arise due to the intermittent nature of RERs, such as voltage fluctuations and increased system losses. This paper presents an optimization problem that is solved by sequential linear programming (SLP) to improve the voltage profile of the unbalanced distribution network. A probabilistic approach was applied to both the load profile and the active power generation of the PV units. SLP is applied to the modified IEEE 34 Bus Test system. The method optimizes the voltage deviations by changing the taps of the voltage regulators and the reactive power injected by the inverters of the PV systems and, in some cases, by switching a shunt capacitor. MATLAB simulations are done at different times of the day with different loads and PV outputs to compare base case and optimal case voltage profiles. The results show better voltage profiles after applying the presented approach. © 2024 IEEE.
  • Review
    Citation Count: 0
    PROTECTING SOCIOECONOMIC INTERESTS OF THE WEAKER PARTY IN THE FREE MARKET: THE EXPLOITATION OF RELIGIOUS BELIEFS IN THE TURKISH CONTRACT LAW
    (University of Zagreb Faculty of Economics and Business, 2024) Atasoy,K.
    Despite being the ultimate rule in the free market, the freedom of contract is fading away against the aim to protect the weaker party in contract law. The weaker party’s socioeconomic interest can be breached in a specific way that would be summarized as the exploitation of religious beliefs. This type of exploitation is usually seen across Turkish society, but there is almost no jurisprudence concerning this subject. The paper evaluates potential legal solutions from the Turkish Code of Obligations (TCO). Theoretical views are compared to achieve an adequate way of compensation against the stronger party for the weaker party whose pecuniary damages occurred because of the contract that the latter signed with religious thoughts and inexplicable generosity for the former. Common law’s undue influence and civil law’s sandpile theory can suggest founded solutions against religious exploitation in the contract. Still, TCO art. 27 can give a suitable cause for the illegality: the contrariety to economic public order. This notion can prevent copied future contracts against the same group of weaker parties when the pioneer illegal contract is invalidated, and the exploiter must compensate the pecuniary damages of the counterparty. © 2024, University of Zagreb Faculty of Economics and Business. All rights reserved.
  • Book Part
    Citation Count: 0
    Interdependency of Passive Design Strategies for Energy-Efficient Building Envelope
    (Springer Science and Business Media Deutschland GmbH, 2024) Reffat,R.M.; Cetin,M.; Abdou,A.A.
    Achieving energy efficiency in buildings is quite important since it significantly contributes to the reduction of energy consumption and leads to better utilization of existing energy resources. This paper investigates and identifies a set of passive design strategies of building shape and proportion, orientation, envelope materials, glazing that helps in minimizing the energy consumption of buildings and achieves an energy-efficient building envelope. A set of 51 passive design rules for achieving energy-efficient building envelope in a hot humid climate is induced from a thorough investigation of the related literature. An interdependency matrix that represents the consequential effects and embodiment among these rules is established. The paper introduces an interdependency analysis of passive design strategies for energy-efficient building envelope leading to the identification of both the influential and interdependency levels among the induced rules. The obtained results are expected to be beneficial to building designers during the conceptual designing of buildings to better achieve energy efficiency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
  • Conference Object
    Citation Count: 0
    Improving COVID-19 Detection: Leveraging Convolutional Neural Networks in Chest X-Ray Imaging
    (SPIE, 2024) Jamil,M.; Chukwu,I.J.; Creutzburg,R.
    The global impact of the COVID-19 pandemic has significantly disrupted healthcare systems w orldwide. Amidst challenges, there is a crucial demand for efficient me thodologies to ex pedite di sease de tection. Th is research underscores the potential of Deep Neural Networks in enhancing pandemic management over the past five years. Focusing on Artificial Intelligence (AI) application in COVID-19 detection through X-ray imaging, this research advocates using Visual Geometry Group (VGG’16), a Convolutional Neural Network (CNN) used for image classification w ith m ultiple l ayers. T hese C NNs a ct a s c lassifier-based sy stems, tr eating im ages as structured data arrays to identify and learn patterns. Quantifying the model’s effectiveness t hrough t he a ccuracy s core, t his r esearch r eveals a 0 .90% accuracy, indicating the model’s accurate detection of COVID-19 cases in X-ray images. Additionally, the study highlights a significant a chievement w ith a l ess t han 1 0% f alse p ositive r ate, c rucial f or r eliable a nd p rompt COVID-19 diagnoses in the healthcare industry. In conclusion, this research presents an AI-driven approach, utilizing VGG’16 and convolutional neural networks to enhance the efficiency an d ac curacy of CO VID-19 de tection in X-ray imaging. The high accuracy score and low false positive rate positions this methodology as a valuable contribution, offering robust pandemic management and healthcare decision-making. © 2024 SPIE
  • Book Part
    Citation Count: 0
    Turkey’s Black Sea Policies (1991–2023) and Changing Regional Security Since the Russian Invasion of Ukraine
    (Springer Nature, 2024) Aydın,M.
    This chapter deals with the historical context and evolving dynamics of Turkey’s security policies in the Black Sea region. It discusses Turkey’s efforts to promote regional cooperation as a tool to contain Russia and preserve the regional balance of power, as well as its responses to challenges, including Russia’s recent aggression and further Western involvement. The chapter also addresses the impact of the Russian invasion of Ukraine in 2022 on Turkey’s Black Sea policies, arguing that Turkey aims to balance its relationships with Russia and other regional actors while seeking to maintain stability and security in the Black Sea region. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
  • Article
    Citation Count: 1
    Predicting and optimizing the fair allocation of donations in hunger relief supply chains
    (Elsevier B.V., 2024) Sharmile,N.; Nuamah,I.A.; Davis,L.; Samanlioglu,F.; Jiang,S.; Crain,C.
    Non-profit hunger relief organizations primarily depend on donors’ benevolence to help alleviate hunger in their communities. However, the quantity and frequency of donations they receive may vary over time, thus making fair distribution of donated supplies challenging. This paper presents a hierarchical forecasting methodology to determine the quantity of food donations received per month in a multi-warehouse food aid network. We further link the forecasts to an optimization model to identify the fair allocation of donations, considering the network distribution capacity in terms of supply chain coordination and flexibility. The results indicate which locations within the network are under-served and how donated supplies can be allocated to minimize the deviation between overserved and underserved counties. © 2024 International Institute of Forecasters
  • Conference Object
    Citation Count: 0
    The Impact of Evolutionary Computation on Robotic Design: A Case Study with an Underactuated Hand Exoskeleton
    (Institute of Electrical and Electronics Engineers Inc., 2024) Akbas,B.; Yuksel,H.T.; Soylemez,A.; Zyada,M.E.; Sarac,M.; Stroppa,F.
    Robotic exoskeletons can enhance human strength and aid people with physical disabilities. However, designing them to ensure safety and optimal performance presents significant challenges. Developing exoskeletons should incorporate specific optimization algorithms to find the best design. This study investigates the potential of Evolutionary Computation (EC) methods in robotic design optimization, with an underactuated hand exoskeleton (U-HEx) used as a case study. We propose improving the performance and usability of the U-HEx design, which was initially optimized using a naive brute-force approach, by integrating EC techniques such as Genetic Algorithm and Big Bang-Big Crunch Algorithm. Comparative analysis revealed that EC methods consistently yield more precise and optimal solutions than brute force in a significantly shorter time. This allowed us to improve the optimization by increasing the number of variables in the design, which was impossible with naive methods. The results show significant improvements in terms of the torque magnitude the device transfers to the user, enhancing its efficiency. These findings underline the importance of performing proper optimization while designing exoskeletons, as well as providing a significant improvement to this specific robotic design. © 2024 IEEE.
  • Book Part
    Citation Count: 0
    Machine/Deep learning techniques for multimedia security
    (Institution of Engineering and Technology, 2024) Heidar,A.; Navimipour,N.J.; Azad,P.
    Multimedia security based on Machine Learning (ML)/Deep Learning (DL) is a field of study that focuses on using ML/DL techniques to protect multimedia data such as images, videos, and audio from unauthorized access, manipulation, or theft. Developing and implementing algorithms and systems that use ML/DL techniques to detect and prevent security breaches in multimedia data is the main subject of this field. These systems use techniques like watermarking, encryption, and digital signature verification to protect multimedia data. The advantages of using ML/DL in multimedia security include improved accuracy, scalability, and automation. ML/DL algorithms can improve the accuracy of detecting security threats and help identify multimedia data vulnerabilities. Additionally, ML models can be scaled up to handle large amounts of multimedia data, making them helpful in protecting big datasets. Finally, ML/DL algorithms can automate the process of multimedia security, making it easier and more efficient to protect multimedia data. The disadvantages of using ML/DL in multimedia security include data availability, complexity, and black box models. ML and DL algorithms require large amounts of data to train the models, which can sometimes be challenging. Developing and implementing ML algorithms can also be complex, requiring specialized skills and knowledge. Finally, ML/DL models are often black box models, which means it can be difficult to understand how they make their decisions. This can be a challenge when explaining the decisions to stakeholders or auditors. Overall, multimedia security based on ML/DL is a promising area of research with many potential benefits. However, it also presents challenges that must be addressed to ensure the security and privacy of multimedia data. © The Institution of Engineering and Technology 2024. All rights reserved.
  • Article
    Citation Count: 0
    Multimodal language in child-directed versus adult-directed speech
    (SAGE Publications Ltd, 2024) Kandemir,S.; Özer,D.; Aktan-Erciyes,A.
    Speakers design their multimodal communication according to the needs and knowledge of their interlocutors, phenomenon known as audience design. We use more sophisticated language (e.g., longer sentences with complex grammatical forms) when communicating with adults compared with children. This study investigates how speech and co-speech gestures change in adult-directed speech (ADS) versus child-directed speech (CDS) for three different tasks. Overall, 66 adult participants (Mage = 21.05, 60 female) completed three different tasks (story-reading, storytelling and address description) and they were instructed to pretend to communicate with a child (CDS) or an adult (ADS). We hypothesised that participants would use more complex language, more beat gestures, and less iconic gestures in the ADS compared with the CDS. Results showed that, for CDS, participants used more iconic gestures in the story-reading task and storytelling task compared with ADS. However, participants used more beat gestures in the storytelling task for ADS than CDS. In addition, language complexity did not differ across conditions. Our findings indicate that how speakers employ different types of gestures (iconic vs beat) according to the addressee’s needs and across different tasks. Speakers might prefer to use more iconic gestures with children than adults. Results are discussed according to audience design theory. © Experimental Psychology Society 2023.
  • Article
    Citation Count: 0
    Joint Resource Allocation in Multi-RIS and Massive MIMO Aided Cell-Free IoT Networks
    (Institute of Electrical and Electronics Engineers Inc., 2024) Li,B.; Hu,Y.; Dong,Z.; Panayirci,E.; Jiang,H.; Wu,Q.
    To meet the needs of high energy efficiency (EE) and various heterogeneous services for 6G, in this paper, we probe into the EE of reconfigurable intelligent surfaces (RISs) sub-surface (SSF) architecture-aided cell-free Internet of Things (CF-IoT) networks. Specifically, we jointly optimize the base station (BS)-RIS-IoT device (ID) joint associations, the RIS's phase shift matrix (PSM), and the BS's transmit power to enhance CF-IoT's EE. The elevated complexity (NP-hard) and non-convexity of the formulated problem pose significant challenges, making the solution highly difficult and intricate. To handle this challenging problem, we first develop an alternating optimization framework based on block coordinate descent, which can decouple the original problem into several subproblems. We then carefully design the corresponding low-complexity algorithm for each subproblem to solve it. Moreover, the proposed joint optimization framework serves as a versatile solution applicable to a wide range of scenarios aiming to maximize EE with the assistance of RISs. Simulations confirm that deploying RISs in CF-IoT scenarios is beneficial for improving the EE of the system, and the SSF architecture can further enhance the EE of the system. © 2014 IEEE.
  • Editorial
    Citation Count: 0
    Preface
    (Taylor and Francis, 2024) Mair,J.; Aktaş,G.; Kozak,M.
    [No abstract available]
  • Conference Object
    Citation Count: 0
    An Effective low-cost laboratory-Scale Rotarod Device for Resource-constrained Research Environment
    (Institute of Electrical and Electronics Engineers Inc., 2024) Oyejide,A.; Zaccheus,J.; Ugo,H.; Oni,B.; Adeyemi,A.; Chukwudi,F.; Okpale,G.-O.
    Local fabrication of rotarod devices, employed in medical researches for studies on exploration of motor coordination for effective intervention in neurological impairment in underdeveloped countries has been a commendable effort to overcome financial constraints. However, such alternative often lacks functionalities for reliable research activities. Therefore, this work presents the development of an effective low-cost rotarod device for laboratory research in resource-constrained research settings. The main features of the rotarod device include a gear motor for the rotation of the rotary rod, a timer which measures the real time to time the rotation of the rotary rod, Passive Infrarade Sensors (PIR) to detect the fall of the rodents, and an LCD screen to display information about the test such as the time of fall of each rodent. The design and fabrication of the rotarod device totaled approximately 97 USD compared to the Nigerian naira, with most of the materials 3D-printed and sourced locally. Ten albino mice (5 male and 5 female) which are 10 weeks of age, were employed in the performance evaluation of the five compartments of the rotarod device in 3 different experiments. The rotarod device performed effectively, with an average mean fall time of ≈25.13 and ≈31.46 for all male and female mice, respectively in the overall experiment. © 2024 IEEE.
  • Conference Object
    Citation Count: 0
    EXPLORING THE ACOUSTIC IDENTITY OF DERINKUYU UNDERGROUND CITY
    (Society of Acoustics, 2024) Nas,S.; Şaher,K.; Mıhçı,G.; Aytıs,S.
    Sounds play a significant role in shaping the identity of spaces and places, yet the acoustic environment of underground cities remains relatively unexplored in the existing literature. Derinkuyu Underground City stands as a prominent cultural heritage site, boasting a capacity of 20,000 people and serving as one of the largest underground cities globally. While geological and structural studies have been conducted on such sites, investigations into indoor acoustics, a crucial aspect of the physical environment, are notably lacking. This study initiates an initial examination of the sound environment within Derinkuyu Underground City, aiming to analyse its features acoustically. Undertaking a PhD study, our research endeavours to gather essential data essential for the preservation of the site's current acoustic environment as a cultural heritage site while also generating valuable insights for the design and construction of future underground cities. In this paper, we present a preliminary assessment of the typologies of various spaces within Derinkuyu Underground City, exploring their unique acoustic features. By characterizing and understanding the acoustic properties of diverse spaces within the underground city, we seek to understand how acoustic might contribute to the identity of these spaces and provide foundational knowledge for both preservation efforts and future underground urban design initiatives. © 2024 Proceedings of the International Congress on Sound and Vibration. All rights reserved.
  • Editorial
    Citation Count: 0
    INTRODUCTION TO THE SERIES
    (Taylor and Francis, 2024) Aktaş,G.; Kozak,M.
    [No abstract available]