Image Processing Approach to Investigate the Correlation between Machining Parameters and Burr Formation in Micro-Milling Processes of Selective-Laser-Melted AISI 316L.

In industrial manufacturing and research laboratories, precise machining of work materials is crucial to meet the demand for fast assembly and sustainable high-quality production. Precise machining procedures play a vital role in manufacturing compatible parts that meet the production requirements. This study investigates the impact of different parameters on burr formations and slot dimensions during the micro-milling of AISI 316 material. A careful examination was conducted using scanning electron microscopy (SEM) images under varying conditions. The variables considered include cutting speed, feed rate, and depth of cut. The main finding revealed that the feed rate and depth of cut significantly influence burr formation, with lower rates and depths resulting in noticeable reductions. A higher feed rate was associated with more pronounced burr formation. Moreover, burr widths on the down-milling sides were typically wider than those on the up-milling sides due to continuous chip formation and compressive forces during down-milling. Utilizing image processing, the study further quantified burr and slot widths with high accuracy, offering a reliable method to characterize burr formation. This research presents potential ways to minimize burr formation during micro-milling processes by effectively managing machining parameters.

Predicting Academic Self-Efficacy Based on Self-Directed Learning and Future Time Perspective.

The purpose of this study was to investigate the relationship between teacher candidates' academic self-efficacy, self-directed learning, and future time perspective. A dual-stage analytical approach, utilizing both traditional structural equation modeling (SEM) and Machine Learning Classification Algorithms, was employed to test the proposed hypotheses. The study included a sample of 879 teacher candidates. The SEM analysis revealed that self-directed learning had a significant positive effect on academic self-efficacy. Furthermore, future time perspective was found to significantly predict academic self-efficacy. The combined endogenous constructs accounted for a substantial portion of the explained variance. Additionally, the study employed LMT and Multiclass classifiers from Machine Learning algorithms to predict academic self-efficacy. In summary, the findings of this study suggest that self-directed learning and future time perspective are significant factors in predicting teacher candidates' academic self-efficacy. The study utilized both traditional SEM and Machine Learning algorithms to provide a comprehensive analysis of the relationships between these variables.

Ranking the Critical Success Factors for Hospital Information Systems Using a Fuzzy Analytical Hierarchy Process.

The design, development, and maintenance of hospital information systems face major challenges, which ultimately cause failures of these information systems. This study aimed to identify and rank critical success factors for hospital information systems by applying a fuzzy analytical hierarchy process. Potential critical success factors that could contribute to the success of hospital information systems were identified and extracted through a systematic review of the relevant studies. A questionnaire containing the critical success factors was designed and distributed to 250 hospital information system professionals. The hierarchical structure of the critical success factors was defined by using an exploratory factor analysis, and pairwise comparison matrices of the fuzzy analytical hierarchy process model were designed based on the identified factor structure. As a result, 50 potential critical success factors were extracted from 21 articles, and their content validity and face validity were assessed by the experts. Based on the exploratory factor analysis results, 36 critical success factors were classified into seven dimensions: organizational fitness, user-friendliness, maintainability, portability, productivity, reliability, and organizational and external support. The fuzzy analytical hierarchy process results indicated that reliability, user-friendliness, and organizational fitness (with 20.3, 19.9, and 18 points, respectively) had the greatest impact on the success of hospital information systems. The findings revealed that managers and policymakers should consider these critical success factors in designing and developing hospital information systems.

Air pollution in marmara region before and during the COVID-19 outbreak.

The lockdowns and curfews during the COVID-19 pandemic have halted economic and transportation activities across the world. This study aims to investigate air pollution levels in the Marmara region, particularly in Istanbul, before and during the COVID-19 pandemic. The study used real data provided by the General Directorate of Meteorology and applied three machine learning algorithms (ANN, RBFreg, and SMOreg) to analyze air pollution data. In addition, a one-sample t-test was performed to compare air pollution levels before and during the COVID-19 pandemic in the Marmara region and Istanbul. The results of the study showed a significant reduction in the particulate matter (PM) value, which indicates the degree of air pollution, in both the Marmara region and Istanbul during the COVID-19 pandemic. The one-sample t-test results showed that the reduction in air pollution levels was statistically significant in both areas (t = 11.45, p < .001 for the Marmara region, and t = 3.188, p < .001 for Istanbul). These findings have important practical implications for decision-makers planning for a more sustainable environment. Overall, the study provides valuable insights into the impact of the COVID-19 pandemic on air pollution levels in the Marmara region, particularly in Istanbul. The application of machine learning algorithms and statistical analysis provides a rigorous approach to the investigation of this important issue by comparing before and during the COVID-19 outbreak.

Reliability and validity of the Chinese version of the COVID-19 Phobia Scale.

BACKGROUND: The COVID-19 pandemic has become a source of fear worldwide and has negative mental health effects on the general population. In 2022, the epidemic continues to be characterized by many points, widespread and frequent in China, and the situation is serious and complex. To provide an effective and scientific tool, the study validated the Chinese version of the COVID-19 Phobia Scale (C19P-SC). METHODS: This study selected 1138 Chinese individuals (age ranged 13 to 80). RESULTS: Cronbach's alpha coefficient for the C19P-SC was 0.93 (the coefficients of the four dimensions ranged from 0.75 to 0.85). The results of the confirmatory factor analysis supported the four-factor structure of the C19P-SC. Meanwhile, there was a positive and significant correlation between coronaphobia and state anxiety (r = 0.48, p < 0.001). The metric invariance hypothesis and the scalar invariance hypothesis were valid in the different subgroups. Significant multivariate effects of gender, education level, and identity differences on coronaphobia were found. CONCLUSIONS: The Chinese version of the COVID-19 Phobia Scale has good psychometric properties and is suitable for measuring COVID-19 phobia in Chinese individuals.

Depression as a mediator between fear of COVID-19 and death anxiety.

The COVID-19 pandemic has affected the world deeply and an increase in psychological distress have been observed in globally. Therefore, investigation of the psychological problems associated with the COVID-19 has become an important research area. Accordingly, this study aimed to examine the relationships among Fear of COVID-19 (FoC), depression, and death anxiety. Further, the study investigated the mediating role of depression in the relationship between FoC and death anxiety. The "Fear of COVID-19 scale", "Depression Scale" and "Death Anxiety Scale" were used to collect data from 372 emerging adults aged between 18 and 25 years. The results indicated that FoC was a positive and significant predictor of both depression and death anxiety. The results further indicated that depression was a positive and significant predictor of death anxiety. Depression partially mediated the relationship between FoC and death anxiety. The findings suggested that the FoC may trigger depression and death anxiety, and therefore, preventive measures should be more emphasized. The findings have implications for mental health professionals and practitioners in counseling.

Mediating role of positivity in the relationship between state anxiety and problematic social media use during the COVID-19 pandemic.

This study investigated the mediating role of positivity in the relationship between state anxiety and problematic social media use during the COVID-19 pandemic. The Positivity Scale, State-Trait Anxiety Inventory, and Bergen Social Media Addiction Scale were used to collect data from 834 social media users. SEM-based mediation analysis was used to test hypothesized relationships. Results indicated that positivity has a direct negative effect on problematic social media use. Furthermore, the results indicated that state anxiety has a direct negative effect on positivity and state anxiety has a direct positive effect on problematic social media use. Positivity significantly mediates the relationship between state anxiety and problematic social media use.

COVID-19 Phobia in the United States: Validation of the COVID-19 Phobia Scale (C19P-SE).

This study validated the COVID-19 Phobia Scale (C19P-SE) based on data collected from 227 adults in the United States. Results indicated that the C19P-SE has adequate reliability (α = .93) along with factorial, discriminant, and convergent validity. Results of confirmatory factor analysis (CFA) supported the four-factor structure of the C19P-SE. Concurrent validity results indicate a significant positive correlation between coronaphobia and state anxiety (r = .67, p < .001), suggesting that individuals with higher levels of coronaphobia may also have higher levels of state anxiety or vice versa. Further, we found a multivariate difference in coronaphobia between men and women.

Validity, Reliability, and Optimal Cut-off Scores of the WHO-5, PHQ-9, and PHQ-2 to Screen Depression Among University Students in Iran.

This study aimed to investigate the validity, reliability, and optimal cut-off points for the Patient Health Questionnaire-2 (PHQ-2), Patient Health Questionnaire-9 (PHQ-9), and Well-being Index (WHO-5) to screen mild depression among 400 Iranian students who completed these tools and Beck Depression Inventory (BDI-13). Further, a psychiatrist diagnosed the depression by using the "Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders." The validity and internal consistency of tools assessed and the accuracy were computed using the receiver operating characteristic (ROC) and area under the curve (AUC). The internal consistency values of PHQ-2, PHQ-9, and WHO-5 were .73, .88, and .94, respectively. The PHQ-2 (.53), PHQ-9 (.60), and WHO-5 (.54) were significantly associated with the BDI. The PHQ-2, PHQ-9, and WHO-5 had optimal cut-off points of 2, 5, and 9 with an AUC of .809, .851, and .823, respectively. Based on these findings, it is recommended to use the PHQ-9 for mild depression screening among medical university students in Iran because of its high sensitivity and specificity.

A Multi-Flow Production Line for Sorting of Eggs Using Image Processing.

In egg production facilities, the classification of eggs is carried out either manually or by using sophisticated systems such as load cells. However, there is a need for the classification of eggs to be carried out with faster and cheaper methods. In the agri-food industry, the use of image processing technology is continuously increasing due to the data processing speed and cost-effective solutions. In this study, an image processing approach was used to classify chicken eggs on an industrial roller conveyor line in real-time. A color camera was used to acquire images in an illumination cabinet on a motorized roller conveyor while eggs are moving on the movement halls. The system successfully operated for the grading of eggs in the industrial multi-flow production line in real-time. There were significant correlations among measured weights of the eggs after image processing. The coefficient of linear correlation (R2) between measured and actual weights was 0.95.

Predicting the COVID-19 infection with fourteen clinical features using machine learning classification algorithms.

While the RT-PCR is the silver bullet test for confirming the COVID-19 infection, it is limited by the lack of reagents, time-consuming, and the need for specialized labs. As an alternative, most of the prior studies have focused on Chest CT images and Chest X-Ray images using deep learning algorithms. However, these two approaches cannot always be used for patients' screening due to the radiation doses, high costs, and the low number of available devices. Hence, there is a need for a less expensive and faster diagnostic model to identify the positive and negative cases of COVID-19. Therefore, this study develops six predictive models for COVID-19 diagnosis using six different classifiers (i.e., BayesNet, Logistic, IBk, CR, PART, and J48) based on 14 clinical features. This study retrospected 114 cases from the Taizhou hospital of Zhejiang Province in China. The results showed that the CR meta-classifier is the most accurate classifier for predicting the positive and negative COVID-19 cases with an accuracy of 84.21%. The results could help in the early diagnosis of COVID-19, specifically when the RT-PCR kits are not sufficient for testing the infection and assist countries, specifically the developing ones that suffer from the shortage of RT-PCR tests and specialized laboratories.

A review of recent research in problematic internet use: gender and cultural differences.

The present study reviewed current trends in the literature on problematic Internet use. The review included a total of 48 studies published within the last two years and covered by the Web of Science and Scopus databases. Despite frequently investigated in the literature, results of the studies suggest that there is still much to be unveiled regarding problematic Internet use and its relation to gender and cultural differences. In terms of gender, although more studies show that men are further vulnerable to problematic Internet use symptoms, results differ regarding the moderator effect(s) or differences in various cultural settings. Recent studies mostly employed quantitative methods; but, it is also noted that problematic Internet use studies increasingly focus on meta-analysis and literature reviews. Research also tends to investigate large-sample cross-cultural groups, but their results are far from achieving consensus. Studies mostly used cross-sectional approaches with self-report instruments and focused on adolescents and young adults who were students.

The development and initial tests for the psychometric properties of the COVID-19 Phobia Scale (C19P-S).

Researchers predict that the negative effects of the novel coronavirus 2019 (COVID-19) pandemic will continue . These negative effects are not solely limited to psycho-pathological problems. Serious physiological, social, and economical difficulties due to COVID-19 have already been observed in various nations. In this study, we suggest a new type of specific phobia, which may be categorized under DSM-V 300.29. The current study developed a self-report instrument whose items address the specific phobia diagnosis criteria of the DSM-V and tested its initial psychometric properties. Results show that the scale has initial evidence of construct, convergent, and discriminant validity, and internal consistency reliability. The scale should be further tested; however, the COVID-19 Phobia Scale (C19P-S) items provide support for assessing the levels of phobia reactions among a wide range of age groups.

Mediating Effect of Internet Addiction on the Relationship Between Individualism and Cyberbullying: Cross-Sectional Questionnaire Study.

BACKGROUND: Among a variety of dynamics that may have effects on internet-related behaviors, cultural orientation is particularly important. Previous studies suggest that individualism is a strong determinant of certain behaviors. In addition, findings suggest that vertical individualism may lead to the development of more tolerance for addiction and aggression on the internet. OBJECTIVE: This study aimed to investigate whether vertical individualism has significant positive effects on cyberbullying and internet addiction and whether horizontal individualism has significant negative effects on cyberbullying and internet addiction. A theoretical model was specified to test the relationships among vertical versus horizontal individualism, cyberbullying, and internet addiction. METHODS: A total of 665 college students were selected using a convenience sampling method and willingly participated in the study. Participants' ages ranged from 17 to 19 years (mean 17.94 years, SD 1.12 years). Of the group, 462 were women (462/665, 69.5%), and 203 were men (203/665, 30.5%). Study majors represented were mathematics (113/665, 17%), sciences (102/665, 15.3%), instructional technology (99/665, 14.9%), psychology (98/665, 14.7%), and others (253/665, 38.1%). Self-report instruments were used to measure vertical/horizontal individualism, cyberbullying, and internet addiction. RESULTS: Results show a significant positive effect of vertical individualism (effect size 0.10) and significant negative effect of horizontal individualism (effect size -0.12) on cyberbullying. In addition, the direct effect of vertical individualism on internet addiction was significant (effect size 0.28), but the direct effect of horizontal individualism was not (effect size -0.05). Internet addiction had a significant direct effect on cyberbullying (effect size 0.39) as well as an intervening effect on the relationship between vertical individualism and cyberbullying. Results also indicate significant gender differences in cultural patterns and internet addiction. CONCLUSIONS: The findings suggest that horizontal and vertical individualism have significant effects on internet addiction. The findings also suggest that vertical individualists are more vulnerable to internet addiction. Further, the findings indicate a significant relationship between internet addiction and cyberbullying.

Moderating Role of Gender in the Relationship between Big Five Personality Traits and Smartphone Addiction.

This study contributed to cyberpsychology literature by identifying moderating role of gender in the relationship between personality traits and smartphone addiction. A multi-group SEM analysis was employed to investigate the relationship between five factor personality traits (i.e. Big Five) and smartphone addiction among men and women. Big-Five-Inventory (BFI) and Smartphone Addiction Inventory (SPAI) were used to collect data from 320 undergraduate students. The results suggested a positively significant relationship between neuroticism (emotional imbalance) and smartphone addiction for women only. Whereas, conscientiousness was negatively related with smartphone addiction for women. Further, there was a negatively significant relationship between agreeableness and smartphone addiction for both genders. The findings suggested that gender has a moderating role in the relationship between neuroticism and smartphone addiction.

Individual Differences in the Relationship Between Attachment and Nomophobia Among College Students: The Mediating Role of Mindfulness.

BACKGROUND: There is a growing interest in nomophobia, which is defined as the fear of being out of cellular phone contact, or "feelings of discomfort or anxiety experienced by individuals when they are unable to use their mobile phones or utilize the affordances these devices provide". However, only limited research can be found in terms of its determinants at present. Contemporary literature suggests that the relationships among attachment styles, mindfulness, and nomophobia have not been investigated. OBJECTIVE: This study aims to investigate the mediating effect of mindfulness on the relationship between attachment and nomophobia. In addition, the study also focuses on gender differences in attachment, mindfulness, and nomophobia. A theory-based structural model was tested to understand the essentials of the associations between the constructs. METHODS: The Experiences in Close Relationships Scale, Nomophobia Questionnaire, and Mindful Attention Awareness Scale were used to collect data from undergraduate students (N=450; 70.9% women [319/450]; mean age=21.94 years [SD 3.61]). Two measurement models (ie, attachment and mindfulness) and a structural model were specified, estimated, and evaluated. RESULTS: The structural equation model shows that the positive direct effects of avoidant (.13, P=.03) and anxious attachment (.48, P<.001) on nomophobia were significant. The negative direct effects of avoidant (-.18, P=.01) and anxious attachment (-.33, P<.001) on mindfulness were also significant. Moreover, mindfulness has a significant negative effect on nomophobia for women only (-.13, P=.03). Finally, the Sobel test showed that the indirect effects of avoidant and anxious attachment on nomophobia via mindfulness were significant (P<.001). The direct and indirect effects of anxious attachment, avoidant attachment, and mindfulness altogether accounted for 33% of the total variance in nomophobia. Gender comparison results show that there is a significant difference in attachment based on gender (F2,447=6.97, P=.01, Wilk λ=.97, partial η2=.03). Women (mean 68.46 [SD 16.96]) scored significantly higher than men (mean 63.59 [SD 15.97]) in anxious attachment (F1=7.93, P=.01, partial η2=.02). Gender differences in mindfulness were not significant (F4,448=3.45, P=.69). On the other hand, results do show significant gender differences in nomophobia (F4,445=2.71, P=.03, Wilk λ=.98, partial η2=.02) where women scored significantly higher than men. CONCLUSIONS: In general, individuals who are emotionally more dependent and crave more closeness and attention in the relationship tend to display higher levels of fear or discomfort when they have no access to their mobile phones. However, gender has a differential impact on the relationship between avoidant attachment and nomophobia. This study establishes the impact of mindfulness on nomophobia for women; therefore, future studies should test the effectiveness of mindfulness-based therapy approaches and confirm whether they are effective and efficient. On the basis of significant gender difference in nomophobia and attachment, we conclude that gender should be taken into account in mindfulness-based treatments dealing with nomophobia.

Impact of Perceived Security on Organizational Adoption of Smartphones.

Organizational adoption of new technologies is a practically important research area. The present study aims to investigate the impact of perceived security on organizational adoption of mobile communication technologies, specifically smartphones. For this purpose, a research model is developed extending the Technology Acceptance Model (TAM). The research model is tested using a structural equation modeling based on data that were collected from senior managers of 201 private sector organizations in Turkey. The results show that, along with the traditional constructs of perceived ease of use and perceived usefulness, perceived security significantly affects organizations' adoption of smartphones. Both the theoretical and practical implications of these results are discussed.