BEYZA NUR BİLGE KIRÇALI

Tez | 2021 | İstanbul Ayvansaray Üniversitesi Lisansüstü Eğitim Enstitüsü

2019 yılı sonuna doğru Çin Wuhan’da görülmeye başlayan, yüksek yayılım hızıyla başka ülkelere yayılarak pandemi haline gelen koronavirüs (CoV) enfeksiyonu (2019-nCoV), Dünya Sağlık Örgütü- DSÖ (World Health Organisaton-WHO) tarafından “Koronavirüs Hastalığı 2019”un kısaltması olan “COVİD-19” olarak adlandırılmıştır. SARS-CoV-2, kişiden kişiye bulaşan pozitif polariteli tek zincirli bir RNA virüsüdür. Salgının yüksek hızda yayılımıyla alakalı artış gösteren kaygılar sebebiyle Dünya Sağlık Örgütü tarafınca 11.02.2020 tarihi pandemi olarak açıklanmıştır. Ülkemizde Covid-19, 2020 Mart ayından beri görülmektedir. Bu süreçten en çok etkil . . .enen kesim sağlık çalışanları olmuştur. Sağlık çalışanlarının yoğun çalışmalarının dışında, kendilerinin yahut yakınlarının hastalanması, hastalık bulaştırma riski, bu süreci daha da zor geçirmelerine sebep olmuştur. Bununla beraber uygulanan tedavinin bireylerde farklı sonuçlar göstermesi, bazı vakaların ölümle sonuçlanması, salgının hızla yayılmaya devam etmesi sonucunda zaman zaman bireylerde umutsuzluğa sebep olmuştur. Bu çalışmada salgından etkilenen hastalara bakım veren sağlık çalışanlarının algıladıkları stres düzeyleri ile mesleki tükenmişlik düzeyleri arasındaki ilişkide umutsuzluğun aracı rolü incelenecektir. Çalışmamızda bilgi formundan gerçekleşen 15 soruluk anket, Maslach Tükenmişlik Ölçeği, Beck Umutsuzluk Ölçeği, Algılanan Stres Ölçeği kullanılacaktır. Bu araştırmanın evrenini sağlık çalışanları oluşturmaktadır. Çalışma İstanbul’da Beylikdüzü Devlet Hastanesi’ndeki sağlık çalışanlarından gerçekleşen 300 bireylik bir örneklem grubuna uygulanacaktır. Araştırma betimsel bir çalışma olup, Covid-19 hastalarına bakım veren sağlık çalışanları örnekleminde algılanan stres, umutsuzluk düzeyleri, mesleki tükenmişlik düzeyleri arasındaki münasebetleri ortaya koymak için ilişkisel tarama modeline uygun olarak gerçekleştirilecektir. Araştırmada IBM Spss, Lisrel 8.80 paket programı kullanılacaktır. Coronavirus (CoV) infection (2019-nCoV), which emerged in Wuhan, China in late 2019 and rapidly spread to other countries and became a pandemic, is the abbreviation of "Coronavirus Disease 2019" by the World Health OrganizationWHO (World Health Organisaton-WHO). It has been called "COVİD-19". SARSCoV-2 is a positive-polarity single-stranded RNA virus that can be transmitted from person to person. Due to the growing concerns about the rapid spread of the epidemic, it was declared a pandemic by World Health Organization on 11.02.2020. Covid-19 has been seen in our country since March 2020. Healthcare workers were the most affected by this process. Apart from the intense work of healthcare professionals, they or their relatives getting sick and the risk of contagion caused them to spend this process even more difficult. However, the different results of the treatment applied to the people and the death of some cases, the epidemic continued to spread rapidly, causing despair from time to time. In this study, the mediating role of hopelessness in the relationship between the perceived stress levels of healthcare workers who care for patients affected by the epidemic and their occupational burnout will be examined ven our study, a questionnaire consisting of 15 questions consisting of information form, Maslach Burnout Scale, Beck Hopelessness Scale and Perceived Stress Scale will be used. Healthcare professionals constitute the universe of this research. The study will be applied to a sample group of 300 people consisting of healthcare professionals in Beylikdüzü State Hospital in Istanbul. The research is a descriptive study and will be carried out in accordance with the relational screening model to reveal the relationships between perceived stress, hopelessness levels and occupational burnout levels in the sample of healthcare professionals caring for Covid-19 patients. IBM Spss and Lisrel 8.80 package program will be used in the research Daha fazlası Daha az

FATMA ALTUNTAŞ

Makale | 2023 | Springer

Renewable energy management is critical for obtaining a significant number of practical benefits. Wind energy is one of the most important sources of renewable energy. It is extremely valuable to manage this type of energy well and monitor its development. Data-driven analysis of wind energy technology provides essential clues for energy management. Patent documents are extensively used to follow technology development and find exciting patterns. Patent analysis is an excellent way to conduct a data-driven analysis of the technology under concern. This study aims to define concepts related to wind energy technologies and cluster the . . .se concepts to manage wind energy well in practice. Although many efforts have been made in the literature on wind energy, no study defines the concepts related to wind energy technologies and clusters these concepts. This study proposes a text mining and clustering-based patent analysis approach to overcome the limitations of previous studies. Data-driven analysis collects and assesses patent documents related to wind energy technologies. Patent documents are collected from the United States Patent and Trademark Office. Text mining is applied to the abstracts of patent documents, and the k-means clustering algorithm is utilized to determine the distribution of the keywords among the clusters. The results of this study show that the contents of the patent documents are mostly related to the tower, and the propeller blades placed at the top of the tower should rotate smoothly with the wind speed for better energy production Daha fazlası Daha az

AREF YELGHI

Makale | 2023 | Studies in Computational Intelligence , pp.109 - 126

Recent work has attempted to determine the appropriate global minimum for complex problems. The paper presents a population and direct-based swarm optimization algorithm called the happiness optimizer (HPO) algorithm. An HPO algorithm is designed based on personal behavior and demonstrated in 30 and 100 dimensions on benchmark functions. The model includes four questions: “what do you want?”, “what do you have?”, “what do others have?”, and “what happened?”, which guide the development of a happiness behavior model. By considering the balancing between exploration and exploitation operators in the search space problem, efficiency, r . . .obustness, and stability were demonstrated for synthetic and real cases. For comparison, our proposed algorithm and some well-known algorithms will be 30 times applied on the benchmark functions and then compared with statistical value and Wilcoxon signed-rank test. As a consequence, the performance, reliability, and stability of our work have been demonstrated better than the others. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG Daha fazlası Daha az

TAYMAZ AKAN

Makale | 2023 | Book Series

Object and shape detection in digital image were one of the hot topic over the last two decades. Especially automatic multi circle detection has received more attention over last years. Hough transform (HT) is a well-known and most popular method for lines and circles detection. However, HT has huge computational complexity expense. This paper proposed a new successful heuristic method to reduce computation time and improve the speed of HT for circle detection. In this proposed method the edges information of the image is obtained by means of Robert edge detection. Then, multimodal particle swarm optimization (PSO) and local search . . .is employed to locate all exciting circle in the image. The experiments on benchmark images show that our scheme can perform multi circle detection successfully. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG Daha fazlası Daha az

ELİF DELİCE

Makale | 2022 | Nova Science Publishers, Inc.

In recent years, researchers have highlighted how large volumes of data can be transformed into information to determine customer behaviors, and data mining applications have become a major trend. It has become critical for organizations to use a tool for understanding the relationships between data to protect their marketplace by increasing customer loyalty. Thanks to data mining applications, data can be processed and transformed into information, and in this way, target audiences can be determined while developing marketing strategies. This chapter aims to increase the market share with products specific to the customer portfolio . . ., introduce strategic marketing tools for retaining old customers, introduce effective methods for acquiring new customers, and increase the retail sales chart, based on purchasing habits of customers. The data set was collected under pandemic conditions during the COVID-19 process and analyzed to support retail businesses in their online shopping orientation. By examining the local customer base, it was assumed that the customer group would display similar behaviors in online or teleordering methods, customer identification and order estimation were made to follow an effective sales policy. Segmentation was performed with data mining applications, and the grouped data were separated according to their similarities. The data set consisting of demographic characteristics and various product information of the enterprise's customers were analyzed with Decision Tree and Random Forest, which are data mining methods, the best performing algorithm in the data set was selected by comparing the performance of the methods. As a result of the findings, appropriate suggestions were given to the business to determine the purchasing tendencies of the customers and to increase the level of effectiveness in sales-marketing strategies. In this way, materials were presented to assist the enterprise in developing strategies to increase the number of sales by taking faster and more accurate action by avoiding the time and expense that would be lost by the trial-error method. © 2022 Nova Science Publishers, Inc. All rights reserved Daha fazlası Daha az

Metin Zontul

Makale | 2022 | Conference Proceedings

Since increasing oil prices and vehicle costs increase transportation costs in order delivery systems, the optimal vehicle loading and routing is very crucial for the companies in competitive conditions. Although there are many studies related to optimal vehicle loading and routing by using linear programming and heuristic algorithms, there is not enough practical web service-based application in the literature. In this study, we propose a hybrid model to solve the problem of two-dimensional vehicle pallet loading with routing for a real-world data by combining Knapsack Problem solver algorithms such as MaxRects, Skyline and Guillot . . .ine with Dijkstra's algorithm for loading and routing respectively as a web service-based application. © 2022 IEEE Daha fazlası Daha az

METİN ZONTUL | SEDA KARATEKE

Makale | 2022 | Conference Proceedings

Today Artificial Intelligence (AI) algorithms need to represent different kinds of input items in numeric or vector format. Some input data can easily be transformed to numeric or vector format but the structure of some special data prevents direct and easy transformation. For instance, we can represent air condition using humidity, pressure, and temperature values with a vector that has three features and we can understand the similarity of two different air measurements using cosine-similarity of two vectors. But if we are dealing with a general ontology tree, which has elements "entity"as the root element, its two children "livin . . .g things"and "non-living things"as first- level elements repeatedly children of "living things"that are "Animals", "Plants"as second level elements, it is harder to represent this kind of data with numeric values. The ontology tree starts from the general items and goes to specific items. If we want to represent an element of this tree with a vector; how can it be possible? And if we want the measured similarity using some methods like cosine-similarity, which one similarity is higher, ("Animal"and "non-living thing") or ("Animal"and "Living thing")? How should we select the values of this vector for each item of the hierarchical tree? In this paper, we propose an original and basic idea to represent the hierarchical tree items with 2D vectors and in the proposed method the cosine-similarity metric works for measuring the semantic similarity of represented items at the same level as parent items. There are two important results related to our representation: (1) The "y"values of the items give the hierarchical level of the item. (2) For the same level items, the cosine similarities between the parent item and child items are higher if the child belongs to this parent compared to other childrens'. In other words, the cosine similarity between the parent item and child items is highest if the child belongs to this parent. © 2022 IEEE Daha fazlası Daha az

AREF YELGHI

Makale | 2022 | Conference Proceedings

In recent years, many applications based on the Neural Network, Neuro-Fuzzy, and optimization algorithms have been more common for solving regression and classification problems. In the Adaptive Neuro-fuzzy inference system(ANFIS), many researchers used the adaption of metaheuristic algorithms with ANFIS to propose the best estimation model. However, many researchers only focused on the experiment without the demonstration mathematical or indicating which characteristic of optimization algorithm, during the run, affect and settable in coordination with ANFIS. The paper provides an adaption of metaheuristic algorithms with ANFIS whic . . .h has been performed by considering accuracy parameters in layer 1 and layer 4 for the estimation problem. It is integrated six well-known metaheuristic algorithms and extracting the characteristic of them. In the experiment, the metaheuristic algorithms based on the evolutionary computation have been demonstrated more stable than swarm intelligence methods in tuning parameters of ANFIS. © 2022 IEEE Daha fazlası Daha az

AREF YELGHI

Makale | 2022 | Conference Proceedings

The aim of this study is to provide a novel method routing in ad hoc networks using ant colony algorithm. Hence for this study the researcher attempts to discover and create routes with less number of crossings, nodes sustainable and less energy transfer, to reduce latency end-to-end, save bandwidth and to extend the life and increase the lifetime of the network nodes. Research methodology for simulation algorithm has been OPNET software. Therefore, the proposed algorithm's performance was compared with one of the most routing algorithms in mobile ad hoc networks Ant Hoc Net. The results showed that the proposed algorithm compared w . . .ith Ant Hoc Net has more end-to-end delay, more package shipping, and less routing overhead can reduce energy consumption and thus increases the lifetime of the network nodes. The results of this study indicate that the latency end-to-end, saving bandwidth and increasing lifetime of nodes and network lifetime can be predicted by the proposed algorithm. © 2022 IEEE Daha fazlası Daha az

DENİZ BERKER

Makale | 2021 | Handbook of Research on Contemporary Approaches to Orientalism in Media and Beyond , pp.953 - 973

The place and importance of mass media as an ideological device is accepted without any discussion today. The sovereign states, trying to impose their ideology and world view to "others," impose the dominant ideology by using the media as well as economic and political pressure. Cinema is like a mirror that reveals the socio-cultural and economic structures in societies and reflects all changes and conflicts. Therefore, the relationship between cinema and social structure is quite strong. At this point, the relationship between cinema and orientalism, which is the subject of the study, becomes important. Orientalism is constantly be . . .ing reproduced through cinema, which is one of the most effective mass media. In this context, the movie Aladdin produced in 2019 will be analyzed in order to analyze how the orientalist perspective is reproduced with cinema and how the eastern image is "otherized." In the study, critical discourse analysis method was preferred for the purpose of analyzing the social and political backgrounds of the ideologies in the film. © 2021, IGI Global Daha fazlası Daha az

DERYA DEMİRDELEN ALRAWADIEH

Makale | 2021 | Edward Elgar Publishing Ltd.

The current COVID-19 pandemic has gained unprecedented scholarly attention across almost all disciplines and hospitality and tourism industry is no exception. Given the persistence of the pandemic, there seems to be much to know about its possible impacts and how countries react to build resilience and help businesses to recover and rest. Drawing on the case of Turkey and focusing on the hospitality and tourism industry, this chapter maps the governmental response to the pandemic in terms of measures taken and restrictions imposed. The chapter begins with a brief description of the key observed and projected impacts of COVID-19 on t . . .he hospitality and tourism industry including hotels, airlines, and restaurants. It proceeds with scrutinizing governmental circulars and notices aiming at regulating different aspects of the hospitality and tourism industry. The chapter concludes by reflecting on the governmental strategies to help individuals and businesses cope with the pandemic, Äôs adverse impacts. © Dogan Gursoy, Mehmet Sarıışık, Robin Nunkoo and Erhan Boğan 2021 Daha fazlası Daha az

Metin Zontul

Makale | 2022 | JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES15 ( 1 ) , pp.59 - 65

With the increase in unstructured data, the importance of classification of text-based documents has increased. In particular, the classification of news texts and digital documentation provides easy access to the information sought. In this study, a large amount of news textual data was used. After the data set was preprocessed, Bag of Words (BoW), TF-IDF, Word2Vec and Doc2Vec word embedding methods were applied. In the classification phase, Random Forest (RF), Multilayer Perceptron (MLP), Support Vector Machine (SVM) and Deep Neural Network (DNN) algorithms were applied. As a result of the experimental studies, using the Word2Vec . . .method together with the DNN algorithm performed the best result. Yapısal olmayan verilerin artmasıyla birlikte metin tabanlı belgelerin sınıflandırılmasının önemi artmıştır. Özellikle haber metinlerinin sınıflandırılması ve dijital dokümantasyon, aranan bilgilere kolay erişim sağlar. Bu çalışmada, büyük miktarda metinsel haber verisi kullanılmıştır. Veri seti ön işlemeye tabi tutulduktan sonra, Bag of Words (BoW), TF-IDF, Word2Vec ve Doc2Vec kelime temsil yöntemleri uygulanmıştır. Sınıflandırma aşamasında Random Forest (RF), Multilayer Perceptron (MLP), Support Vector Machine (SVM) ve Deep Neural Network (DNN) algoritmaları uygulanmıştır. Deneysel çalışmalar sonucunda DNN algoritması ile birlikte Word2Vec yönteminin kullanılması en iyi sonucu vermiştir Daha fazlası Daha az