Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Travma Sonrasi Stres Bozukluǧu Hastalarinda Üstbilişlere İlişkin İnançlar(ANP Publishing, 2019) Yazihan, N.; Yelboǧa, Z.Objective: The concept of metacognition can be described as metacognitive structures controlling, arranging and assessing the cognitions. The aim of this study was to investigate metacognitive beliefs and their relationship with the psychological symptoms of posttrumatic stress disorder (PTSD) patients. Method: The sample consisted of 52 posttraumatic stress disorder patients (mean age=31,67±6,54) and 54 healthy participants (mean age=29,00±6,61). Metacognitive beliefs were measured through Metacognitive Questionnaire-30 which is accepted as a measuring device of metacognitive beliefs, metacognitive processes and judgment. To describe symptom profiles Symtom Checklist-90 was used. Results: Data were analyzed by using MANCOVA. PTSD group scores were significantly higher than control group for uncontrallability and danger (includes items that worry and rumination are negative, dangerous and difficult to control); need to control thoughts (includes items that some thoughts are need to be controlled and suppressed) and finally lack of "cognitive confidence" (includes items about problems related to memory and attention). On the other hand, positive beliefs about thoughts which involves the items related to the idea that worry and rumination is functional was lower among individuals with PTSD. Discussion: Trauma patients think that worry and rumination have negative consequences, and some thoughts need to be controlled and supressed as they are dangerous. The elevation of clinical symptoms such as obsession, depression and psychotic symptoms were correlated with the increase of abnormal metacognitive belifs. Thoughts are dangerous and need to be controlled, appear to be related to obsesive thoughts, anger and hostility and interpersonal sensitivity sypmtoms. © 2019 ANP Publishing. All rights reserved.Article Citation - WoS: 5Citation - Scopus: 7About Fractional Calculus of Singular Lagrangians(Fuji Technology Press Ltd, 2005) Baleanu, DumitruIn this paper the solutions of the fractional Euler-Lagrange equations corresponding to singular fractional Lagrangians were examined. We observed that if a Lagrangian is singular in the classical sense, it remains singular after being fractionally generalized. The fractional Lagrangian is non-local but its gauge symmetry was preserved despite complexity of equations in fractional cases. We generalized four examples of singular Lagrangians admitting gauge symmetry in fractional case and found solutions to corresponding Euler-Lagrange equations.Article Citation - WoS: 3Citation - Scopus: 9Data Mining Applications in Risk Research: a Systematic Literature Review(Sage Publications inc, 2025) Sicakyuz, Cigdem; Edalatpanah, Seyyed Ahmad; Pamucar, Dragan; Sicakyuez, CigdemDespite the rising literature on data mining (DM) approaches, there is a lack of a complete literature review and categorization system within risk research. This paper presents the first recognized academic literature review on the application of data mining tools in risk research provides an up-to-date SCOPUS literature database. Based on bibliometric analysis, 5422 papers related torisk were identified from a total of 77,410 studies on data mining and thoroughly analyzed. Each of the selected 5422 papers was classified into four risk categories: global risk, public health risk, molecular and biomedical risk, and pharmaceutical risk. Each primary risk category was further subdivided to highlight the specific research focuses within each domain. Global risks encompass business, environmental, and social risks. Scholars have predominantly focused on the banking, market, and construction sectors within business risk, while environmental risk includes catastrophe-related risks. Social risks encompass areas such as education, traffic safety, and transportation concerns. Clinical data is usually employed in public health risk research, while various radiomic databases are utilized in genetic and molecular biology research. In pharmaceutical research, DM is primarily used to detect adverse drug effects. According to the findings of this review, the fields of computer science and medicine received the most significant research attention. The review also discusses limitations and provides a roadmap to guide future research, aiming to enhance knowledge development related to the application of data mining techniques in risk-related studies.Conference Object Citation - WoS: 16Citation - Scopus: 21Spend: Linked Data Sparql Endpoints Discovery Using Search Engines(Ieice-inst Electronics information Communication Engineers, 2017) Yumusak, Semih; Dogdu, Erdogan; Kodaz, Halife; Kamilaris, Andreas; Vandenbussche, Pierre-YvesLinked data endpoints are online query gateways to semantically annotated linked data sources. In order to query these data sources, SPARQL query language is used as a standard. Although a linked data endpoint (i.e. SPARQL endpoint) is a basic Web service, it provides a platform for federated online querying and data linking methods. For linked data consumers, SPARQL endpoint availability and discovery are crucial for live querying and semantic information retrieval. Current studies show that availability of linked datasets is very low, while the locations of linked data endpoints change frequently. There are linked data respsitories that collect and list the available linked data endpoints or resources. It is observed that around half of the endpoints listed in existing repositories are not accessible (temporarily or permanently offline). These endpoint URLs are shared through repository websites, such as Datahub. io, however, they are weakly maintained and revised only by their publishers. In this study, a novel metacrawling method is proposed for discovering and monitoring linked data sources on the Web. We implemented the method in a prototype system, named SPARQL Endpoints Discovery (SpEnD). SpEnD starts with a "search keyword" discovery process for finding relevant keywords for the linked data domain and specifically SPARQL endpoints. Then, the collected search keywords are utilized to find linked data sources via popular search engines (Google, Bing, Yahoo, Yandex). By using this method, most of the currently listed SPARQL endpoints in existing endpoint repositories, as well as a significant number of new SPARQL endpoints, have been discovered. We analyze our findings in comparison to Datahub collection in detail.Article Citation - WoS: 3Citation - Scopus: 4Demans Hastalarında Ajitasyonun Bakım Veren Yüküne Etkisi(Gunes Kitabevi Ltd Sti, 2014) Altunöz, Umut; Baştu, Gülbahar; Ozel Kızıl, Erguvan Tugba; Altıntaş, H Özge; Çelik, Nazlı Durmaz; Ozel, Erguvan Tugba; Ozel-Kizil, Erguvan Tugba; Bastug, Gulbahar; Bafituğ, Gülbahar; Altintafi, H. Özge; Durmaz, NazlGiriş: Bu çalışmanın amacı demans hastalarına bakım veren yakınlarında ajitasyonun öznelbakım veren yüküne etkisinin depresif belirtiler, bilişsel işlevler, demans süresi, bakım verenin yaşı, eğitimi, cinsiyeti gibi diğer etmenlerle birlikte araştırılmasıdır. Gereç ve Yöntem: Araştırmaya toplam 49 demans hastası (Ort. yaş: 76.5; Ss: 5.6) ve 49 bakım vereni katılmıştır. Verilerin toplanmasında, hastalara Standardize Mini Mental Test ve CornellDemansta Depresyon Ölçeği, bakım verenlere ise Cohen-Mansfield Ajitasyon Envanteri, Bilişsel Kayıp için Bilgilendiriciye Uygulanan Anket ve Zarit Bakıcı Yükü Ölçeği uygulanmıştır. Bulgular: Bakım verenin cinsiyeti ve yakınlık türü ile Zarit Bakıcı Yükü Ölçeği puanları açısından istatistiksel olarak anlamlı fark bulunmadığı gibi Standardize Mini Mental Test ve Cornell Demansta Depresyon Ölçeği puanları, bakım verenin eğitim süresi, hastanın yaşı, eğitim süresi vehastalık süresi ile de anlamlı korelasyon bulunmamıştır. Zarit Bakıcı Yükü Ölçeği ile Cohen-Mansfield Ajitasyon Envanteri puanı, bakım veren yaşı ve Bilişsel Kayıp için Bilgilendiriciye UygulananAnket puanı arasında anlamlı korelasyon saptanmıştır. Lineer regresyon analizinde ise bakıcı yükünün yalnızca ajitasyon puanı ile ilişkili olduğu bulunmuştur. Sonuç: Bu çalışmada elde edilen sonuçlar demans hastalarında Cohen-Mansfield AjitasyonEnvanteri ile değerlendirilen ajitasyon sıklığının öznel bakım veren yükünü belirleyen temel faktörolduğuna işaret etmektedir. Bakım verme işinin kolaylaştırılması için psikofarmakolojik tedavilerinyanı sıra bakım verenlere yönelik psikososyal girişimler de etkili olmaktadır. Ülkemizde ajitasyonayönelik müdahaleler içeren evde ve gündüz bakım hizmetlerinin, bakım verenlere yönelik psikososyal destek ve bilgilendirme programlarının yaygınlaştırılması gereklidir.Article Covariance Features for Trajectory Analysis(Kaunas Univ Technology, 2018) Karadeniz, Talha; Maras, Hakan HadiIn this work, it is demonstrated that covariance estimator methods can be used for trajectory classification. It is shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. Compared to Dynamic Time Warping, application of explained technique is faster and yields more accurate results. An improvement of Dynamic Time Warping based on counting statistical comparison of base distance measures is also achieved. Results on Australian Sign Language and Character Trajectories datasets are reported. Experiment realizations imply feasibility through covariance attributes on time series.Article Prediction Models With Multiple Linear Regression for Improving Acoustic Performance of Textile Industry Plants(Polska Akad Nauk, Polish Acad Sciences, inst Fundamental Tech Res Pas, 2025) Yaman, Muammer; Kurtay, Cuneyt; Harputlugil, Gulsu U. L. U. K. A. V. A. K.; Ulukavak Harputlugil, GülsuIn industrial plants noise is a major threat to the mental and physical health of employees. The risk increases more due to the presence of high noise sources and the presence of too many employees in textile industry plants. This paper aims to predict the consequences of variables that may arise in the plants for acoustic improvement in textile industry plants. For this purpose, scenario plants have been created according to architectural properties and source-transmission path-receiver characteristics. The acoustic analyses of the scenario plants were performed in the ODEON Auditorium, and A-weighted sound pressure level (LA), noise reduction (NR), and reverberation time (RT) were determined. From the data, prediction equations were created with a multiple linear regression (MLR) model. To test the prediction equations, acoustic measurements were made, and acoustics improvements were carried out at a textile industry plant located in Tu<spacing diaeresis>rkiye. When the obtained results, the success, validity, and reliability of the prediction method are provided. In conclusion, the effect of architectural properties and the surface absorption on acoustic improvements in the textile industry was revealed. It was emphasized that prediction methods can be used to determine the effectiveness of interventions that can be applied in different facilities and can be improved in future studies.Article Citation - WoS: 1Citation - Scopus: 4Assessing Traffic Performance: Comparative Study of Human and Automated Hgvs in Urban Intersections and Highway Segments(Univ Tun Hussein onn Malaysia, 2024) Almusawi, Ali; Albdairi, Mustafa; Qadri, Syed Shah Sultan MohiuddinThis study conducts a comparative analysis of traffic dynamics at urban signalized intersections and on highways, incorporating both human-operated and automated heavy goods vehicles (HGVs) using the PTV VISSIM simulation model. It examines the impacts of automated driving technologies on critical traffic performance metrics such as queue length, travel time, vehicle delay, emissions, and fuel consumption. Initial findings indicate that automation in HGVs enhances traffic flow, particularly by reducing queue lengths and vehicle delays. However, varying levels of automation from cautious to aggressive reveal complex trade-offs between operational efficiency and environmental impacts. On highways, automated HGVs demonstrate superior performance by reducing travel times and delays while increasing throughput compared to human-driven HGVs. These results underscore the operational benefits of automated HGVs under diverse traffic conditions and highlight their significant implications for transportation planning and policy-making. This research contributes valuable insights into the integration of automated technologies in transportation systems, facilitating informed decision-making for stakeholders considering the adoption of these advancements in the current infrastructure.Article A Classifier for Automatic Categorisation of Chronic Venous Insufficiency Images(Kaunas Univ Technology, 2024) Karadeniz, Talha; Tokdemir, Gul; Maras, H. Hakan; Hakan Maras, H.Chronic venous insufficiency (CVI) is a serious disease characterised by the inability of the veins to effectively return blood from the legs back to the heart. This condition represents a significant public health issue due to its prevalence and impact on quality of life. In this work, we propose a tool to help doctors effectively diagnose CVI. Our research is based on extracting Visual Geometry Group network 16 (VGG-16) features and integrating a new classifier, which exploits mean absolute deviation (MAD) statistics to classify samples. Although simple in its core, it outperforms state-of-the-art method which is known as the CVI-classifier in the literature, and additionally it performs better than the methods such as multi-layer perceptron (MLP), Naive Bayes (NB), and gradient boosting machines (GBM) in the context of VGG-based classification of CVI. We had 0.931 accuracy, 0.888 Kappa score, and 0.916 F1-score on a publicly available CVI dataset which outperforms the state-of-the-art CVI-classifier having 0.909, 0.873, and 0.900 for accuracy, Kappa score, and F1-score, respectively. Additionally, we have shown that our classifier has a generalisation capacity comparable to support vector machines (SVM), by conducting experiments on eight different datasets. In these experiments, it was observed that our classifier took the lead on metrics such as F1-score, Kappa score, and receiver operating characteristic area under the curve (ROC AUC).Article Analysis of Maritime Transportation Sector Through Econometric Modelling Concerning Relationship Between Foreign Trade and Freight Transportation in Türkiye(Univ Rijeka, Fac Maritime Studies, 2024) Gurses, Cemre; Temiz, Dilek; Yurtseven, Omer; Kanik, Zehra B.; Gokmen, AytacThe main objective of this study is to investigate the effect of freight transportation on foreign trade in the Turkish maritime transportation sector. Data gathered from the Turkish Statistical Institute and the Ministry of Transport and Infrastructure's official websites, between the years 2013 and 2023, were utilized and time series analysis was conducted. The Industrial Production Index was used as a proxy for economic expansion. This research used five variables, all shown in logarithmic form (Export, Import, Volume, Handling, and Index). Unit root tests were done to examine the stationarity of the series. Regression analysis was conducted utilizing the Ordinary Least Squares (OLS) method to ascertain the short-term direction of the relationship between the variables. The findings from the Toda-Yamamoto causality test align with those derived from OLS and affirm that within the maritime sector, sea freight transportation exerts a positive impact on foreign trade, particularly in the short term.