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Article Citation - WoS: 58Citation - Scopus: 66Country-Level and Individual-Level Predictors of Men's Support for Gender Equality in 42 Countries(Wiley, 2020) Kosakowska-Berezecka, Natasza; Besta, Tomasz; Bosson, Jennifer K.; Jurek, Pawel; Vandello, Joesph A.; Best, Deborah L.; Zukauskiene, RitaMen sometimes withdraw support for gender equality movements when their higher gender status is threatened. Here, we expand the focus of this phenomenon by examining it cross-culturally, to test if both individual- and country-level variables predict men's collective action intentions to support gender equality. We tested a model in which men's zero-sum beliefs about gender predict reduced collective action intentions via an increase in hostile sexism. Because country-level gender equality may threaten men's higher gender status, we also examined whether the path from zero-sum beliefs to collective action intentions was stronger in countries higher in gender equality. Multilevel modeling on 6,734 men from 42 countries supported the individual-level mediation model, but found no evidence of moderation by country-level gender equality. Both country-level gender equality and individual-level zero-sum thinking independently predicted reductions in men's willingness to act collectively for gender equality.Article Citation - WoS: 38Citation - Scopus: 59Career Abandonment Intentions among Software Workers(Wiley, 2014) Colomo-Palacios, Ricardo; Casado-Lumbreras, Cristina; Misra, Sanjay; Soto-Acosta, PedroWithin the software development industry, human resources have been recognized as one of the most decisive and scarce resources. Today, the retention of skilled IT (information technology) personnel is a major issue for employers and recruiters as well, since IT career abandonment is a common practice and means not only the loss of personnel, knowledge, and skills, but also the loss of business opportunities. This article seeks to discover the main motivations young practitioners abandon the software career. To achieve this objective, two studies were conducted. The first study was qualitative (performed through semistructured interviews) and intended to discover the main variables affecting software career abandonment. The second study was quantitative, consisting of a Web-based survey developed from the output of the first study and administered to a sample of 148 IT practitioners. Results show that work-related, psychological, and emotional variable are the most relevant group of variables explaining IT career abandonment. More specifically, the three most important variables that motivate employees to abandon the career are effort-reward imbalance, perceived workload, and emotional exhaustion. In contrast, variables such as politics and infighting, uncool work, and insufficient resources influence to a lesser extent the decision to leave the career. (c) 2012 Wiley Periodicals, Inc.Article Citation - Scopus: 1Stenotic Double-Orifice Mitral Valve After Surgical Repaired Partial Atrioventricular Septal Defect(Wiley, 2020) Duran Karaduman, Bilge; Torun, Ayse Nur; Ayhan, Huseyin; Keles, Telat; Bozkurt, EnginDouble-orifice mitral valve (DOMV) is an uncommon congenital anomaly account for 1% of congenital heart disease. However, accurate diagnosis and evaluation of valve stenosis or regurgitation and other concomitant congenital anomalies due to DOMV are required to obtain suitable treatment. Two- and three-dimensional echocardiography can contribute valuable functional and anatomic information that can support to reach this goal. Here, we present a case of complete bridge-type DOMV that causes mitral stenosis after surgical repair of the partial atrioventricular septal defect in childhood.Article Citation - WoS: 104Citation - Scopus: 163Cassava Disease Recognition From Low-Quality Images Using Enhanced Data Augmentation Model and Deep Learning(Wiley, 2021) Abayomi-Alli, Olusola Oluwakemi; Damasevicius, Robertas; Misra, Sanjay; Maskeliunas, RytisImprovement of deep learning algorithms in smart agriculture is important to support the early detection of plant diseases, thereby improving crop yields. Data acquisition for machine learning applications is an expensive task due to the requirements of expert knowledge and professional equipment. The usability of any application in a real-world setting is often limited by unskilled users and the limitations of devices used for acquiring images for classification. We aim to improve the accuracy of deep learning models on low-quality test images using data augmentation techniques for neural network training. We generate synthetic images with a modified colour value distribution to expand the trainable image colour space and to train the neural network to recognize important colour-based features, which are less sensitive to the deficiencies of low-quality images such as those affected by blurring or motion. This paper introduces a novel image colour histogram transformation technique for generating synthetic images for data augmentation in image classification tasks. The approach is based on the convolution of the Chebyshev orthogonal functions with the probability distribution functions of image colour histograms. To validate our proposed model, we used four methods (resolution down-sampling, Gaussian blurring, motion blur, and overexposure) for reducing image quality from the Cassava leaf disease dataset. The results based on the modified MobileNetV2 neural network showed a statistically significant improvement of cassava leaf disease recognition accuracy on lower-quality testing images when compared with the baseline network. The model can be easily deployed for recognizing and detecting cassava leaf diseases in lower quality images, which is a major factor in practical data acquisition.Article Citation - WoS: 1How Do Visual, Auditory and Motor Dual-Tasking Each Affect Swallowing and Chewing Function?(Wiley, 2024) Begen, Sena Nur; Arslan, Selen Serel; Serel Arslan, SelenBackground: It can be challenging to perform a second task at the same time as swallowing. Objective(s)The study aimed to investigate the effect of visual, auditory and motor dual-tasking on swallowing and chewing function in healthy young adults. Method: Right-handed healthy adults without any psychological and cognitive problems were included in the study. Swallowing was evaluated based on the dysphagia limit in different liquid textures such as water and nectar consistencies, and chewing was evaluated by the Test of Masticating and Swallowing Solids. For the second task, visual and auditory performance was assessed using reaction time, and the motor performance was assessed using a bilateral tapping task. Assessments were performed in two steps: baseline and dual-task. For baseline, all evaluation methods were applied individually. After completing the baseline assessment, dual-task assessment were carried out the following day. For dual-task assessment, the swallowing and chewing tasks were performed simultaneously with visual, auditory and motor tasks. Results: Results showed a significant decrease in dysphagia limit in the nectar consistency, and significant increase in chewing time, visual reaction time and tapping rate (right-left) when compared to baseline and dual-task conditions (chi(2)(3) = 9.61, p = .02; chi(2)(3) = 9.02, p = .02; chi(2)(3) = 28.09, p < .001; chi(2)(3) = 28.97, p < .001; chi(2)(3) = 21.56, p < .001, respectively). However, there were no differences in dysphagia limit in the water and auditory reaction time compared to baseline and dual-task conditions (chi(2)(3) = 3.18, p = .36; chi(2)(3) = 2.56, p = .50, respectively). Conclusion: Results shedding light on how simultaneous dual tasks can influence swallowing and chewing. Dual-tasking cause a decrease in both swallowing/chewing and the visual/motor performances. These results may provide valuable information for designing interventions or strategies aimed at improving or maintaining optimal swallowing and chewing during in various populations during daily life.Article Citation - WoS: 31Citation - Scopus: 50Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: a Case Study of an International Bank(Wiley, 2015) Ogwueleka, Francisca Nonyelum; Misra, Sanjay; Colomo-Palacios, Ricardo; Fernandez, LuisThe customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six-step procedure. The back-propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.Article Citation - WoS: 5Citation - Scopus: 5Development and Psychometric Analysis of a Pediatric Oncology Nurses' Educational Needs Scale(Wiley, 2023) Kudubes, Asli Akdeniz; Semerci, Remziye; Ozbay, Sevil Cinar; Ay, Ayse; Boztepe, HandanBackground/objectivesIt is important to determine the educational needs of pediatric oncology nurses in order to maximize and implement nursing care interventions. Therefore, this study aims to develop a valid and reliable measurement tool to determine pediatric oncology nurses' educational needs and examine its psychometric properties. Design/methodsThis methodological study was conducted with 215 pediatric oncology nurses in Turkey between December 2021 and July 2022. Data were collected with the "Nurse Information Form" and "Pediatric Oncology Nurses' Educational Needs Scale." IBM SPSS 21.0 and IBM AMOS 25.0 software programs were used for data analysis, and descriptive statistics were used to analyze numeric variables. Exploration and confirmatory factor analyses were performed to determine the scale's factorial structure. ResultsThe factorial analysis was used to test the structural validity of the scale. A five-factor structure consisting of 42 items was developed. The Cronbach's alpha coefficient for "Illness" was .978, "Chemotherapy and Side Effect" was .978, "Another Therapy and Side Effect" was .974, "Palliative Care" was .967, "Supportive Care" was .985, and the total score was .990. Fit indices resulting from the study were chi(2)/SD: 3.961, root mean square error of approximation (RMSEA): 0.072, goodness-of-fit index (GFI): 0.95, comparative-of-fit index (CFI): 0.96, and normed fit index (NFI): 0.95. ConclusionThe Pediatric Oncology Nurses' Educational Needs Scale is a valid and reliable scale for pediatric oncology nurses to determine their educational needs.Article Citation - WoS: 20Citation - Scopus: 21Electrochemical Behaviour and Electrochemical Polymerization of Fluoro-Substituted Anilines(Wiley, 2002) Cihaner, A; Önal, AMThe electrochemical behaviour of three fluoro-substituted aniline monomers, 2-fluoroaniline (2FAN), 3-fluoroaniline (3FAN) and 4-fluoroaniline (4FAN), was investigated in aqueous acidic and organic media by means of cyclic voltammetry (CV) studies. Constant potential electrolysis (CPE) of the monomers in acetonitrile-water mixture (1: 1 by volume) using NaClO4 as supporting electrolyte yielded soluble polymers. The mechanism of electrochemical polymerization was investigated using in situ electron spin resonance (ESR) and in situ UV-VIS spectroscopic techniques for one of the monomers (4FAN). Both CV and in situ LTV-VIS measurements indicated that the polymers obtained are in the emeraldine base form. In situ ESR studies indicated that electrochemical polymerization involves a radical-cation as an intermediate. Characterization of polymer products have been carried out using FTIR and NMR spectroscopic techniques, and thermal behaviour was studied using differential scanning calorimetry (DSC). It was found that conductivity can be imparted to assynthesized polyfluoroanilines via iodine doping. (C) 2002 Society of Chemical Industry.Article Citation - WoS: 3Evaluation of the Effects of Avatar on Learning Temporomandibular Joint in a Metaverse-Based Training(Wiley, 2024) Basmaci, Fulya; Bulut, Ali Can; Ozcelik, Erol; Ekici, Saliha Zerdali; Kilicarslan, Mehmet Ali; Cagiltay, Nergiz ErcilPurposeAvatars, representing users in the digital world, can influence users' behavior and attitudes. This study evaluates the impact of representing dental students receiving temporomandibular joint (TMJ) education in the metaverse via an anonymous or identified avatar.MethodsParticipants included 80 dental students in their fourth and fifth years of study. They were randomly assigned to either the avatar group (identified avatar) or the control group (anonymous avatar). Prior to training, participants completed a demographic questionnaire and a pretraining knowledge assessment. TMJ training was conducted in the metaverse for both groups. Pre- and post-training assessments included the Spielberger State-Trait Anxiety Inventory and a shyness scale to ensure group comparability. A post-test consisting of five questions was administered to both groups after 2 weeks of training.ResultsThere were no significant differences in pretraining scores for prior knowledge (p = 0.67), trait anxiety (p = 0.28), state anxiety (p = 0.92), or shyness (p = 0.42) between the avatar and control groups, indicating comparability at baseline. Post-training analysis revealed significantly higher post-test scores in the avatar group (median = 80) compared to the control group (median = 60) (p = 0.03).ConclusionsMetaverse environments offer various benefits for students, educators, and educational institutions in health education programs. Representing learners and their identities in training environments can enhance learning outcomes.Article Citation - WoS: 11Citation - Scopus: 15A Study on the Performance Evaluation of Wavelet Decomposition in Transient-Based Radio Frequency Fingerprinting of Bluetooth Devices(Wiley, 2022) Almashaqbeh, Hemam; Dalveren, Yaser; Kara, AliRadio frequency fingerprinting (RFF) is used as a physical-layer security method to provide security in wireless networks. Basically, it exploits the distinctive features (fingerprints) extracted from the physical waveforms emitted from radio devices in the network. One of the major challenges in RFF is to create robust features forming the fingerprints of radio devices. Here, dual-tree complex wavelet transform (DT-CWT) provides an accurate way of extracting those robust features. However, its performance on the RFF of Bluetooth transients which fall into narrowband signaling has not been reported yet. Therefore, this study examines the performance of DT-CWT features on the use of transient-based RFF of Bluetooth devices. Initially, experimentally collected Bluetooth transients from different smartphones are decomposed by DT-CWT. Then, the characteristics and statistics of the wavelet domain signal are exploited to create robust features. Next, the support vector machine (SVM) is used to classify the smartphones. The classification accuracy is demonstrated by varying channel signal-to-noise ratio (SNR) and the size of transient duration. Results show that reasonable accuracy can be achieved (lower bound of 88%) even with short transient duration (1024 samples) at low SNRs (0-5 dB).
