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Book Part Citation - Scopus: 2A Multi Source Graph-Based Hybrid Recommendation Algorithm(Springer Science and Business Media Deutschland GmbH, 2021) Kurt,Z.; Gerek,Ö.N.; Bilge,A.; Özkan,K.Images that widely exist on e-commerce sites, social networks, and many other applications are one of the most important information resources integrated into the recently deployed image-based recommender systems. In the latest studies, researchers have jointly considered ratings and images to generate recommendations, many of which are still restricted to limited information sources, sources namely, ratings with another input data, or which require the pre-existence of domain knowledge to generate recommendations. In this paper, a new graph-based hybrid framework is introduced to generate recommendations and overcome these challenges. Firstly, a simple overview of the framework is provided and, then, two different information sources (visual images and numerical ratings) are utilized to describe how the proposed framework can be developed in practice. Furthermore, the users’ visual preferences are determined based on which item they have already purchased. Then, each user is represented as a visual feature vector. Finally, the similarity factors between the users or items are evaluated from the user visual-feature or item visual-feature matrices, to be included the proposed algorithm for more efficiency. The proposed hybrid recommendation method depends on a link prediction approach and reveals the significant potential for performance improvement in top-N recommendation tasks. The experimental results demonstrate the superior performance of the proposed appraoch using three quality measurements - hit-ratio, recall, and precision - on the three subsets of the Amazon dataset, as well as its flexibility to incorporate different information sources. Finally, it is concluded that hybrid recommendation algorithms that use the integration of multiple types of input data perform better than previous recommendation algorithms that only utilize one type of input data. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Conference Object Citation - Scopus: 4Quantum Machine Learning in Intrusion Detection Systems: a Systematic Mapping Study(Springer Science and Business Media Deutschland GmbH, 2024) Faker,O.; Cagiltay,N.E.The integration between quantum computing (QC) and machine learning algorithms (ML) aims to speed up computing processes and increase model accuracy rates, and this is what led developers and researchers to exploit this feature to study improving the performance of intrusion detection systems (IDSs). In this work, we present a systematic mapping review (SMR) of the most important works in the field of using quantum machine learning (QML) to increase the efficiency of anomaly detection techniques, which depend mainly on ML. After defining and applying the research methodology, the preliminary search results amounted to 240 studies from four databases. According to the exclusion and inclusion reports, we obtained 21 main studies. After reviewing and analyzing the results, the four research questions were answered. The review focused on the development of integration of intrusion detection systems with QML, the characteristics of such integration, increasing the efficiency of ML algorithms, and future research opportunities in this field. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Conference Object Citation - Scopus: 1Extractive Text Summarization for Turkish: Implementation of Tf-Idf and Pagerank Algorithms(Springer Science and Business Media Deutschland GmbH, 2023) Akülker,E.; Turhan,Ç.Due to the massive amount of information available on the web, reaching the desired content has become more and more difficult. Automatic text summarization helps to solve the problem by minimizing the document size while keeping its core information. In this study, two extractive single document automatic text summarization systems for Turkish are presented which implement the statistical-based TF-IDF algorithm as well as the combination of TF-IDF with the graph-based PageRank algorithm. The study aims to reveal the usability and effectiveness of these algorithms for Turkish documents. Moreover, the results of the TF-IDF implementation and the hybrid approach are compared using the co-selection measures, precision, recall, and F-score. In the evaluation phase, the system-generated summaries are categorized and tested based on their word sizes and the predetermined thresholds and compared against the human-generated summaries. The results indicate that the hybrid system performs better than the TF-IDF system even in lower thresholds, and also both systems are inclined to improve average F-scores in higher threshold generated summarization. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Article Differences of Microbial Growth and Biofilm Formation Among Periprosthetic Joint Infection-Causing Species: an Animal Study(Springer Science and Business Media Deutschland GmbH, 2025) Ertan, M.B.; Ayduğan, M.Y.; Evren, E.; İnanç, İ.; Erdemli, E.; Erdemli, B.Purpose: The most frequently used surgical procedures for periprosthetic joint infections (PJIs) are debridement, antibiotics, and implant retention (DAIR), as well as single- or two-stage revision arthroplasty. The choice of surgery is made depending on the full maturation of the biofilm layer. The purpose of this study was to evaluate the biofilm formation and microbial growth using common PJI-causing agents and compare its development on the implant surface. Methods: The in vivo study was performed using 40 Sprague–Dawley rats divided into five groups (n = 8/group): Staphylococcus aureus, Staphylococcus epidermidis, Pseudomonas aeruginosa, Candida albicans, and control. Six standard titanium alloy discs were placed into the subcutaneous air pouches of the interscapular areas of the rats. After the inoculation of microorganisms, disc and soft tissue cultures were collected at 2-week intervals for 6 weeks, and the microbial load and the microscopic appearance of the biofilm were compared. Results: The disc samples from the S. aureus group had the highest infection load at all time points; however, in soft tissue samples, this was only observed at week 4 and 6. Electron microscopic images showed no distinctive differences in the biofilm structures between the groups. Conclusion: S. aureus microbial burden was significantly higher in implant cultures at week 2 compared to other PJI-causing agents examined. These results may explain the higher failure rate seen if the DAIR procedure was performed at < 3–4 weeks after the PJI symptom onset and support the observation that DAIR may not be effective against PJIs caused by S. aureus. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.Book Part Citation - Scopus: 2Novel Covid-19 Recognition Framework Based on Conic Functions Classifier(Springer Science and Business Media Deutschland GmbH, 2022) Karim,A.M.; Mishra,A.The new coronavirus has been declared as a global emergency. The first case was officially declared in Wuhan, China, during the end of 2019. Since then, the virus has spread to nearly every continent, and case numbers continue to rise. The scientists and engineers immediately responded to the virus and presented techniques, devices and treatment approaches to fight back and eliminate the virus. Machine learning is a popular scientific tool and is applied to several medical image recognition problems, involving tumour recognition, cancer detection, organ transplantation and COVID-19 diagnosis. It is proved that machine learning presents robust, fast and accurate results in various medical image recognition problems. Generally, machine learning-based frameworks consist of two stages: feature extraction and classification. In the feature extraction, overwhelmingly unsupervised learning techniques are applied to reduce the input data’s size. This step extracts appropriate features by reducing the computational time and increasing the performance of the classifiers. A classifier is the second step that aims to categorise the input. Within the proposed step, the unsupervised part relies on the feature extraction by using local binary patterns (LBP), followed by feature selection relying on factor analysis technique. The LBP is a kind of visual descriptor, mainly applied for image recognition problem. The aim of using LBP is to analyse the input COVID-19 image and extract salient features. Furthermore, factor analysis is a statistical technique applied to define variability among observed variables in less unnoticed variables named factors. The factor analysis applied to the LBP wavelet aims to select sensitive features from input data (LBP output) and reduce the size input. In the last stage, conic functions classifier is applied to classify two sets of data, categorising the extracted features by using LBP and factor analysis as positive or negative COVID-19 cases. The proposed solution aims to diagnose COVID-19 by using LBP and factor analysis, based on conic functions classifier. The conic functions classifier presents remarkable results compared with these popular classifiers and state-of-the-art studies presented in the literature. © 2022, Springer Nature Switzerland AG.Conference Object Structural Analyses of Rc Buildings With Various Support Types(Springer Science and Business Media Deutschland GmbH, 2024) Tunc,G.; Tanfener,T.; Khayyat,Z.K.The seismic design of buildings is performed based on dynamic analyses by considering fixed-base supports. The effect of soil’s elastic behavior is usually ignored during the analysis and design phases of buildings. Due to differences in the seismic responses of rigidly and elastically supported buildings, it is essential to study the impact of the elastic behavior of soil on overall building design. In this study, the structural behavior of rigid basement walls with various support conditions will be investigated. For this purpose, a parametric study will be conducted on a total of 60 reinforced concrete buildings with two different layouts. For this purpose, five support types will be studied. These supports types in their correct order are as follows: (1) vertical area springs at the base coupled with horizontal area springs all around the basement walls, (2) fixity at the base coupled with horizontal joint springs only at the ground floor level, (3) vertical joint springs at the base, (4) only fixity at the base with no joint or area springs, and (5) vertical joint springs at the base coupled with horizontal joint springs only at the ground floor level. The results revealed that the buildings with support type 2 exhibited the most rigid behavior, while the buildings with support types 1 and 3 exhibited the most flexible behavior. The fundamental periods from support type 5 were always smaller than those from support type 1, pronouncing the significance of the presence of horizontal springs. Based on the results, it was also concluded that the choice of support type had almost no impact on the design of a mat foundation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Conference Object Citation - Scopus: 21Examining the Use of Non-Fungible Tokens (nfts) as a Trading Mechanism for the Metaverse(Springer Science and Business Media Deutschland GmbH, 2022) Yilmaz,M.; Hacaloğlu,T.; Clarke,P.The notion of a metaverse seems hard to define but encourages the impression that it can be considered as a new virtual metaphysical landscape that somehow goes beyond our geographical locations and understanding (i.e., independent of time and space). Based on virtual reality, augmented reality, and blockchain, it is envisioned as an independent but extended world that is planned to be a digital virtuality entrenched not only in our old habits such as gaming and entertainment but also in virtual asset trade. In particular, trading is a pillar of the virtual economy, and auction houses will be crucial for Metaverse trading. This exploratory study examines the possibility of using an auction environment to improve the trading capabilities in a virtual universe. We investigate the cases of creating a virtual auction house with the potential of social trading of virtual assets with crypto coins and bartering. To this end, we built a virtual auction house and tested it initially using a set of scenarios. Our preliminary findings suggest that creating a virtual trading environment would be beneficial as an environment for buying and selling virtual assets and exploring their consequences. © 2022, Springer Nature Switzerland AG.Conference Object Citation - Scopus: 67A Step by Step Guide for Choosing Project Topics and Writing Research Papers in Ict Related Disciplines(Springer Science and Business Media Deutschland GmbH, 2021) Misra,S.ICT is fast-growing and changing field. A lot of researches are being done in various area of ICT, and results are presented in various platforms like conferences, journal and books. This is common observations in the publications from developing countries (especially in sub – Saharan africa) are not being published in reputed and established publishers even their technical/experiments are good. This is due to lack of several factors including professional presentation, the novelty of the topic, quality of literature review etc. This work guides final year bachelor’s students, PG students (masters and PhD) and young researchers, especially working in computing-related disciplines, on how to convert their project works into quality publications. The authors provide details on how these researchers can select suitable project topics, do a proper review, write up the key components of a paper and present their results in an appropriate form (that is, writing style starting from abstract to conclusion). This paper also presents and guides on how to write various types of review papers. © 2020, Springer Nature Switzerland AG.Book Part Transition Period to Renewable Energy Usage: Turkey Case(Springer Science and Business Media Deutschland GmbH, 2022) Turan,İ.; Uyar,T.S.Turkey is a country with all kinds of renewable resources due to its geography and the adventure of generating electricity from these resources has the potential to be a case study. The first period of power generation applications, which started with the coal-fired “Silahtarağa Thermal Power Plant” that was opened in 1914 to meet Istanbul’s electricity needs, continued with small sized water and coal fired power plants. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Conference Object Security Requirements in Iot Environments(Springer Science and Business Media Deutschland GmbH, 2022) Binglaw,F.; Koyuncu,M.; Pusatlı,T.The Internet of Things (IoT) is a relatively new concept as it connects things (or objects) that do not have high computational power. The IoT helps these things see, listen, and take action by interoperating with minimal human intervention to make people’s lives easier. However, these systems are vulnerable to attacks and security threats that could potentially undermine consumer confidence in them. For this reason, it is critical to understand the characteristics of IoT security and their requirements before starting to discuss how to protect them. In this scope, the present work reviews the importance of security in IoT applications, factors that restrict the use of traditional security methods to protect IoTs, and the basic requirements necessary to judge them as secure environments. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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