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Review Citation - WoS: 88Citation - Scopus: 95Vision 2023: Forecasting Turkey's Natural Gas Demand Between 2013 and 2030(Pergamon-elsevier Science Ltd, 2013) Melikoglu, MehmetNatural gas is the primary source for electricity production in Turkey. However, Turkey does not have indigenous resources and imports more than 98.0% of the natural gas it consumes. In 2011, more than 20.0% of Turkey's annual trade deficit was due to imported natural gas, estimated at US$ 20.0 billion. Turkish government has very ambitious targets for the country's energy sector in the next decade according to the Vision 2023 agenda. Previously, we have estimated that Turkey's annual electricity demand would be 530,000 GWh at the year 2023. Considering current energy market dynamics it is almost evident that a substantial amount of this demand would be supplied from natural gas. However, meticulous analysis of the Vision 2023 goals clearly showed that the information about the natural gas sector is scarce. Most importantly there is no demand forecast for natural gas in the Vision 2023 agenda. Therefore, in this study the aim was to generate accurate forecasts for Turkey's natural gas demand between 2013 and 2030. For this purpose, two semi-empirical models based on econometrics, gross domestic product (GDP) at purchasing power parity (PPP) per capita, and demographics, population change, were developed. The logistic equation, which can be used for long term natural gas demand forecasting, and the linear equation, which can be used for medium term demand forecasting, fitted to the timeline series almost seamlessly. In addition, these two models provided reasonable fits according to the mean absolute percentage error, MAPE %, criteria. Turkey's natural gas demand at the year 2030 was calculated as 76.8 billion m(3) using the linear model and 83.8 billion m(3) based on the logistic model. Consequently, found to be in better agreement with the official Turkish petroleum pipeline corporation (BOTAS) forecast, 76.4 billion m(3), than results published in the literature. (C) 2013 Elsevier Ltd. All rights reserved.Review Citation - WoS: 35Citation - Scopus: 38Aptamer Hybrid Nanocomplexes as Targeting Components for Antibiotic/Gene Delivery Systems and Diagnostics: a Review(Dove Medical Press Ltd, 2020) Rabiee, Navid; Ahmadi, Sepideh; Arab, Zeynab; Bagherzadeh, Mojtaba; Safarkhani, Moein; Nasseri, Behzad; Tayebi, Lobat; Rabiee, Mohammad; Tahriri, MohammadrezaWith the passage of time and more advanced societies, there is a greater emergence and incidence of disease and necessity for improved treatments. In this respect, nowadays, aptamers, with their better efficiency at diagnosing and treating diseases than antibodies, are at the center of attention. Here, in this review, we first investigate aptamer function in various fields (such as the detection and remedy of pathogens, modification of nanoparticles, antibiotic delivery and gene delivery). Then, we present aptamer-conjugated nanocomplexes as the main and efficient factor in gene delivery. Finally, we focus on the targeted co-delivery of genes and drugs by nanocomplexes, as a new exciting approach for cancer treatment in the decades ahead to meet our growing societal needs.Review Citation - WoS: 42Citation - Scopus: 57Drawing the Big Picture of Games in Education: a Topic Modeling-Based Review of Past 55 Years(Pergamon-elsevier Science Ltd, 2023) Ekin, Cansu C.; Polat, Elif; Hopcan, SinanThe literature of games in education has a rich and multidisciplinary content. Due to the large number of studies in the field, it is not easy to analyze all relevant studies. There are few studies exploring the big picture of research trends in the field. For this reason, the purpose of this study is to examine longitudinal trends of game-based research in education using text mining tech-niques. 4980 publications were retrieved as an experimental dataset indexed by the SCOPUS database in the period 1968 to mid-2021. The results include descriptive statistics of game-based research, trends of the research topics, and trends in the frequency of each topic over time. They show that the number of studies focusing on the use of games in education has increased, particularly since the 2000s when Internet use accelerated and became widespread. Approxi-mately 70% of all the studies were conducted in the last 10 years. One third of the studies is related to the main topic of game-based learning. It is significant that in the last three decades the topic of serious games has been among the top three trends. Considering usage acceleration of the topics, the highest values belong to game-based learning, serious games and student science games, in that order. The findings of this study are expected to guide the field by providing a better understanding of the trends of games in education and offer a direction for future research.Review Citation - WoS: 90Citation - Scopus: 105Recommendations for Head and Neck Surgical Oncology Practice in a Setting of Acute Severe Resource Constraint During the Covid-19 Pandemic: an International Consensus(Elsevier Science inc, 2020) Mehanna, Hisham; Hardman, John C.; Shenson, Jared A.; Abou-Foul, Ahmad K.; Topf, Michael C.; AlFalasi, Mohammad; Holsinger, F. ChristopherThe speed and scale of the global COVID-19 pandemic has resulted in unprecedented pressures on health services worldwide, requiring new methods of service delivery during the health crisis. In the setting of severe resource constraint and high risk of infection to patients and clinicians, there is an urgent need to identify consensus statements on head and neck surgical oncology practice. We completed a modified Delphi consensus process of three rounds with 40 international experts in head and neck cancer surgical, radiation, and medical oncology, representing 35 international professional societies and national clinical trial groups. Endorsed by 39 societies and professional bodies, these consensus practice recommendations aim to decrease inconsistency of practice, reduce uncertainty in care, and provide reassurance for clinicians worldwide for head and neck surgical oncology in the context of the COVID-19 pandemic and in the setting of acute severe resource constraint and high risk of infection to patients and staff.Review Citation - WoS: 120Citation - Scopus: 142Dynamic Thermal and Hygrometric Simulation of Historical Buildings: Critical Factors and Possible Solutions(Pergamon-elsevier Science Ltd, 2020) Akkurt, G. G.; Aste, N.; Borderon, J.; Buda, A.; Calzolari, M.; Chung, D.; Turhan, C.Building dynamic simulation tools, traditionally used to study the hygrothermal performance of new buildings during the preliminary design steps, have been recently adopted also in historical buildings, as a tool to investigate possible strategies for their conservation and the suitability of energy retrofit scenarios, according to the boundary conditions. However, designers often face with the lack of reliable thermophysical input data for various envelope components as well as with some intrinsic limitations in the simulation models, especially to describe the geometric features and peculiarities of the heritage buildings. This paper attempts to bridge this knowledge gap, providing critical factors and possible solutions to support hygrothermal simulations of historical buildings. The information collected in the present work could be used by researchers, specialists and policy-makers involved in the conservation of building's heritage, who need to address a detailed study of the hygrothermal performance of historical buildings thorugh dynamic simulation tools.Review Citation - WoS: 18Citation - Scopus: 24A Literature Review on Mhe Selection Problem: Levels, Contexts, and Approaches(Taylor & Francis Ltd, 2015) Saputro, Thomy Eko; Masudin, Ilyas; Rouyendegh (Babek Erdebilli), Babak Daneshvar; Rouyendegh , Babak DaneshvarThis paper presents a review on selection problem of material handling equipment (MHE) and general equipment used in industry area. The issue on MHE is widely paid attention since MHE has contribution on material, good and product accomplishment. Few methods and softwares have been proposed and developed to select the most appropriate MHE for a complex selection problem. Today's high diverisity of MHE categories and types influence the generation of many possible choices which leads to the complexity. In this paper, a further discussion in terms of MHE and equipment including three major points namely level of selection, the context of selection problem and the approaches are served to highlight the complex MHE selection according to the number of possible choices provided, to analyse the consideration for the problem context, and to reveal the superior method for complex MHE selection. Forty-two papers collected from the past study are presented asscociating each point of the discussion.Review Citation - WoS: 10Citation - Scopus: 10Latest Developments in Engineered Skeletal Muscle Tissues for Drug Discovery and Development(Taylor & Francis Ltd, 2023) Ostrovidov, Serge; Ramalingam, Murugan; Bae, Hojae; Orive, Gorka; Fujie, Toshinori; Shi, Xuetao; Kaji, HirokazuIntroductionWith the advances in skeletal muscle tissue engineering, new platforms have arisen with important applications in biology studies, disease modeling, and drug testing. Current developments highlight the quest for engineering skeletal muscle tissues with higher complexity . These new human skeletal muscle tissue models will be powerful tools for drug discovery and development and disease modeling.Areas coveredThe authors review the latest advances in in vitro models of engineered skeletal muscle tissues used for testing drugs with a focus on the use of four main cell culture techniques: Cell cultures in well plates, in microfluidics, in organoids, and in bioprinted constructs. Additional information is provided on the satellite cell niche.Expert opinionIn recent years, more sophisticated in vitro models of skeletal muscle tissues have been fabricated. Important developments have been made in stem cell research and in the engineering of human skeletal muscle tissue. Some platforms have already started to be used for drug testing, notably those based on the parameters of hypertrophy/atrophy and the contractibility of myotubes. More developments are expected through the use of multicellular types and multi-materials as matrices . The validation and use of these models in drug testing should now increase.Review Citation - WoS: 7Citation - Scopus: 9A Survey of Covid-19 Diagnosis Using Routine Blood Tests With the Aid of Artificial Intelligence Techniques(Mdpi, 2023) Habashi, Soheila Abbasi; Koyuncu, Murat; Alizadehsani, Roohallah; Abbasi Habashi, SoheilaSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causing a disease called COVID-19, is a class of acute respiratory syndrome that has considerably affected the global economy and healthcare system. This virus is diagnosed using a traditional technique known as the Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. However, RT-PCR customarily outputs a lot of false-negative and incorrect results. Current works indicate that COVID-19 can also be diagnosed using imaging resolutions, including CT scans, X-rays, and blood tests. Nevertheless, X-rays and CT scans cannot always be used for patient screening because of high costs, radiation doses, and an insufficient number of devices. Therefore, there is a requirement for a less expensive and faster diagnostic model to recognize the positive and negative cases of COVID-19. Blood tests are easily performed and cost less than RT-PCR and imaging tests. Since biochemical parameters in routine blood tests vary during the COVID-19 infection, they may supply physicians with exact information about the diagnosis of COVID-19. This study reviewed some newly emerging artificial intelligence (AI)-based methods to diagnose COVID-19 using routine blood tests. We gathered information about research resources and inspected 92 articles that were carefully chosen from a variety of publishers, such as IEEE, Springer, Elsevier, and MDPI. Then, these 92 studies are classified into two tables which contain articles that use machine Learning and deep Learning models to diagnose COVID-19 while using routine blood test datasets. In these studies, for diagnosing COVID-19, Random Forest and logistic regression are the most widely used machine learning methods and the most widely used performance metrics are accuracy, sensitivity, specificity, and AUC. Finally, we conclude by discussing and analyzing these studies which use machine learning and deep learning models and routine blood test datasets for COVID-19 detection. This survey can be the starting point for a novice-/beginner-level researcher to perform on COVID-19 classification.Review Citation - WoS: 247Citation - Scopus: 446Transformative Effects of Iot, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges(Elsevier, 2019) Gill, Sukhpal Singh; Tuli, Shreshth; Xu, Minxian; Singh, Inderpreet; Singh, Karan Vijay; Lindsay, Dominic; Garraghan, PeterCloud computing plays a critical role in modern society and enables a range of applications from infrastructure to social media. Such system must cope with varying load and evolving usage reflecting societies' interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Enabling these systems are a cohort of conceptual technologies, synthesized to meet demand of evolving computing applications. In order to understand current and future challenges of such system, there is a need to identify key technologies enabling future applications. In this study, we aim to explore how three emerging paradigms (Blockchain, IoT and Artificial Intelligence) will influence future cloud computing systems. Further, we identify several technologies driving these paradigms and invite international experts to discuss the current status and future directions of cloud computing. Finally, we proposed a conceptual model for cloud futurology to explore the influence of emerging paradigms and technologies on evolution of cloud computing. (C) 2019 Elsevier B.V. All rights reserved.Review Citation - WoS: 67Citation - Scopus: 81Software Test Maturity Assessment and Test Process Improvement: a Multivocal Literature Review(Elsevier, 2017) Garousi, Vahid; Felderer, Michael; Hacaloglu, TunaContext: Software testing practices and processes in many companies are far from being mature and are usually conducted in ad-hoc fashions. Such immature practices lead to various negative outcomes, e.g., ineffectiveness of testing practices in detecting all the defects, and cost and schedule overruns of testing activities. To conduct test maturity assessment (TMA) and test process improvement (TPI) in a systematic manner, various TMA/TPI models and approaches have been proposed. Objective: It is important to identify the state-of-the-art and the-practice in this area to consolidate the list of all various test maturity models proposed by practitioners and researchers, the drivers of TMA/TPI, the associated challenges and the benefits and results of TMA/TPI. Our article aims to benefit the readers (both practitioners and researchers) by providing the most comprehensive survey of the area, to this date, in assessing and improving the maturity of test processes. Method: To achieve the above objective, we have performed a Multivocal Literature Review (MLR) study to find out what we know about TMA/TPI. A MLR is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). We searched the academic literature using the Google Scholar and the grey literature using the regular Google search engine. Results: Our MLR and its results are based on 181 sources, 51 (29%) of which were grey literature and 130 (71%) were formally published sources. By summarizing what we know about TMA/TPI, our review identified 58 different test maturity models and a large number of sources with varying degrees of empirical evidence on this topic. We also conducted qualitative analysis (coding) to synthesize the drivers, challenges and benefits of TMA/TPI from the primary sources. Conclusion: We show that current maturity models and techniques in TMA/TPI provides reasonable advice for industry and the research community. We suggest directions for follow-up work, e.g., using the findings of this MLR in industry-academia collaborative projects and empirical evaluation of models and techniques in the area of TMA/TPI as reported in this article. (C) 2017 Elsevier B.V. All rights reserved.
