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Patient privacy in smart cities by blockchain technology and feature selection with Harris Hawks Optimization (HHO) algorithm and machine learning

Haedar Al-Safi | Jorge Munilla | CEVAT RAHEBİ

A medical center in the smart cities of the future needs data security and confidentiality to treat patients accurately. One mechanism for sending medical data is to send information to other medical centers without preserving confidentiality. This method is not impressive because in treating people, the privacy of medical information is a principle. In the proposed framework, the opinion of experts from other medical centers for the treatment of patients is received and consider the best therapy. The proposed method has two layers. In the first layer, data transmission uses blockchain. In the ...Daha fazlası

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Testing Job Satisfaction as a Mediator Between Managers Charismatic Leadership and Followers Affective Organizational Commitment

Burcu Ozgul

Leadership, affective organizational commitment, and job satisfaction have become important processes among the contemporary human resource functions in today's businesses. This research aims to determine how charismatic leadership of managers affects the level of affective organizational commitment of white-collar employees and whether job satisfaction has any mediation effect in this relationship. Based on this, data were collected through questionnaire method from 417 white-collar employess of 139 small and medium-sized enterprises operating in the manufacturing industry in Istanbul. Hierar ...Daha fazlası

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Predicting stock returns with financial ratios: A new methodology incorporating machine learning techniques to beat the market

Zeynep İltüzer

This study proposes a methodology incorporating machine learning algorithms to predict stock returns and construct portfolios that beat the market. The performance evaluation is based on the statistical metrics as well as the return and Sharpe ratios of the portfolios. Additionally, a new performance evaluation metric, Safe-Side, is introduced to address the needs of conservative portfolio managers and investors. The results provide strong evidence that the machine learning algorithms can be used to predict the stock returns with approximately 86 classification accuracy. The proposed methodolo ...Daha fazlası

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Some New Results on Bicomplex Bernstein Polynomials

Seda Karateke

The aim of this work is to consider bicomplex Bernstein polynomials attached to analytic functions on a compact C2-disk and to present some approximation properties extending known approximation results for the complex Bernstein polynomials. Furthermore, we obtain and present quantitative estimate inequalities and the Voronovskaja-type result for analytic functions by bicomplex Bernstein polynomials.

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Beta irradiation effects on impedance spectra of electrospun PEDOT:PSS nanofibres


Poly(3,4-ethylenedioxythio-phene):poly(styrenesulphonate) (PEDOT:PSS) nanofibres were first prepared via electrospinning method. Microstructural arrangement of the nanofibres was investigated by scanning electron microscopy technique. Then, the effect of beta irradiation with different absorbed doses on their impedance spectra were investigated in the frequency range from 5 to 13 x 10(6). It was observed that beta irradiation leads to a considerable decrease in both real and imaginary parts of the complex dielectric function, and alternating current conductivity of the nanofibres. The obtained ...Daha fazlası

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The impact of perceived education quality on tourism and hospitality students career choice: The mediating effects of academic self-efficacy

Derya Demirdelen Alrawadieh

Despite the importance of understanding tourism and hospitality (T&H) students' career choices for both high education institutions and industry practitioners, scarce empirical research exists which limits drawing reliable conclusions on the antecedents of T&H students' post graduate behavioral intentions. Drawing on data collected from 267 undergraduate T&H students in Turkey, the results show that perceived education quality is positively associated with T&H students' intention to join the industry but not to pursue a postgraduate degree. The findings also confirm the mediating role of acade ...Daha fazlası

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Automated evaluation of Cr-III coated parts using Mask RCNN and ML methodse

Metin Zontul

In this study, chrome coatings were carried out using a Cr-III electroplating bath. The coated parts were classified depending on their appearance. A new approach was developed to classify the coated parts automatically using artificial intelligence methods. Mask RCNN and machine learning (ML) methods such as Multilayer Perceptron (MLP), Support Vector Classifier (SVC), Gaussian Process (GP), K-nearest Neighbors (KNN), XGBoost, and Random Forest Classifier (RFC) were used together. Mask RCNN was used to clean the coated parts from the redundant data. The extracted data were flattened and conve ...Daha fazlası

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Cross-cultural aspects of tourism and hospitality: a services marketing and management perspective, 1st edition

Derya Demirdelen Alrawadieh

Cross-Cultural Aspects of Tourism and Hospitalityauthored by Erdogan Koc makes a timely andsignificant contribution not only to tourism and hospitality research but also to cross-culturaltheory. This elegant book involves 13 chapters and is supplemented with 15figures, 51 tables,and a comprehensive index. Each chapter provides important insights into the cross-culturalaspects of the tourism and hospitality industry. Each chapter begins with a set of learningobjectives showing what the reader is expected to know after reading the chapter. Theauthor is also to be acclaimed for enriching each cha ...Daha fazlası

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Inside out, exploring residential spaces during COVID-19 lockdown from the perspective of architecture students

Paria Valizadeh

The new preventative measures that have emerged from the Coronavirus crisis brought about changes in different aspects of daily life. Some of these changes may have a significant impact on how the built environment is being experienced. The current paper examines reconfigurations that happened in residential spaces and space allocations for transitioned activities in a small case study targeting a group of architecture students in Cyprus. Analysis and findings are structured in three sections, indoor activities, special organization, and quality of life. The result shows blurring boundaries be ...Daha fazlası

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Adapted-RRT: novel hybrid method to solve three-dimensional path planning problem using sampling and metaheuristic-based algorithms

Mohammed Ahmed Shah

Three-dimensional path planning for autonomous robots is a prevalent problem in mobile robotics. This paper presents three novel versions of a hybrid method designed to assist in planning such paths for these robots. In this paper, an improvement on Rapidly exploring Random Tree (RRT) algorithm, namely Adapted-RRT, is presented that uses three well-known metaheuristic algorithms, namely Grey Wolf Optimization (GWO), Incremental Grey Wolf Optimization (I-GWO), and Expanded Grey Wolf Optimization (Ex-GWO)). RRT variants, using these algorithms, are named Adapted-RRTGWO, Adapted-RRTI-GWO, and Ada ...Daha fazlası

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Evaluation of Multi-Objective Optimization Algorithms for NMR Chemical Shift Assignment

Sima Etaner Uyar

An automated NMR chemical shift assignment algorithm was developed using multi-objective optimization techniques. The problem is modeled as a combinatorial optimization problem and its objective parameters are defined separately in different score functions. Some of the heuristic approaches of evolutionary optimization are employed in this problem model. Both, a conventional genetic algorithm and multi-objective methods, i.e., the non-dominated sorting genetic algorithms II and III (NSGA2 and NSGA3), are applied to the problem. The multi-objective approaches consider each objective parameter s ...Daha fazlası

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Hybrid algorithms based on combining reinforcement learning and metaheuristic methods to solve global optimization problems

Mohammed Ahmed Shah

This paper introduces three hybrid algorithms that help in solving global optimization problems using reinforcement learning along with metaheuristic methods. Using the algorithms presented, the search agents try to find a global optimum avoiding the local optima trap. Compared to the classical metaheuristic approaches, the proposed algorithms display higher success in finding new areas as well as exhibiting a more balanced performance while in the exploration and exploitation phases. The algorithms employ reinforcement agents to select an environment based on predefined actions and tasks. A r ...Daha fazlası

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