Emerging Science Journal (ESJ)
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Multi-Fusion Algorithms for Detecting Land Surface Pattern Changes Using Multi-High Spatial Resolution Images and Remote Sensing Analysis
Get PDFProducing accurate Land-Use and Land-Cover (LU/LC) maps using low-spatial-resolution images is a difficult task. Pan-sharpening is crucial for estimating LU/LC patterns. This study aimed to identify the most precise procedure for estimating LU/LC by adopting two fusion approaches, namely Color Normalized Brovey (BM) and Gram-Schmidt Spectral Sharpening (GS), on high-spatial-resolution Multi-sensor and Multi-spectral images, such as (1) the Unmanned Aerial Vehicle (UAV) system, (2) the WorldView-2 satellite system, and (3) low-spatial-resolution images like the Sentinel-2 satellite, to generate six levels of fused images with the three original multi-spectral images. The Maximum Likelihood method (ML) was used for classifying all nine images. A confusion matrix was used to evaluate the accuracy of each single classified image. The obtained results were statistically compared to determine the most reliable, accurate, and appropriate LU/LC map and procedure. It was found that applying GS to the fused image, which integrated WorldView-2 and Sentinel-2 satellite images and was classified by the ML method, produced the most accurate results. This procedure has an overall accuracy of 88.47% and a kappa coefficient of 0.85. However, the overall accuracies of the three classified multispectral images range between 86.84% to 76.49%. Furthermore, the accuracy assessment of the fused images by the Brovey method and the rest of the GS method and classified by the ML method ranges between 85.75% to 76.68%. This proposed procedure shows a lot of promise in the academic sphere for mapping LU/LC. Previous researchers have mostly used satellite images or datasets with similar spatial and spectral resolution, at least for tropical areas like the study area of this research, to detect land surface patterns. However, no one has previously investigated and examined the use and application of different datasets that have different spectral and spatial resolutions and their accuracy for mapping LU/LC. This study has successfully adopted different datasets provided by different sensors with varying spectral and spatial levels to investigate this. Doi: 10.28991/ESJ-2023-07-04-013 Full Text: PD
Job Performance Evaluation of Medical Social Workers during Covid-19 Crisis: Tasks, Attitudes, and Difficulties
Get PDFObjectives: The objective of this study is to evaluate the job performance efficiency of social workers in medical institutions during the COVID-19 pandemic crisis, based on three factors "job tasks, attitudes of co-workers, and difficulties" faced by social workers in performing their duties. Methods/Analysis: This study is a descriptive-analytical study. A comprehensive social survey approach was used to collect data from 54 social workers in isolation hospitals for coronavirus patients. A questionnaire was employed to gather the required data. The collected data were analyzed using weight analysis to determine the value and weighted relative weight of job performance efficiency. Findings: The results of the study showed that the job performance efficiency of social workers in medical institutions during the COVID-19 pandemic crisis was at a middle level, with a total weight of 3611 and a weighted relative weight of 55.7%. Moreover, the study found statistically significant differences in the degree of job performance efficiency according to gender, age, educational qualification, number of experience years, and number of training courses at a 5% significance level. Novelty/Improvement:The study recommends the development of the knowledge and skills of medical social workers through training courses on how to deal with global health crises and disasters. Additionally, reducing the administrative burdens on medical social workers is important, as these burdens restrict their role and limit their ability to perform their tasks with the medical team. Doi: 10.28991/ESJ-2023-07-04-08 Full Text: PD
The Impact of the COVID-19 Epidemic on Gambling Behavior Intention: The Moderating Effect of Anti-Epidemic Measure
Get PDFThis study focuses on how the COVID-19 epidemic affects gambling motivation and behavior. This research also analyzes the behavioral intervention effects of the anti-epidemic measures on the COVID-19 epidemic and the relationship between the epidemic impact and gambling motivation and behavior. To investigate these connections, this research used Structural Equation Modeling to analyze 334 valid questionnaires collected during COVID-19 from gamblers from mainland China who visited the Macao Special Administrative Region. The results showed that the epidemic impact negatively affected gambling motivation and behavior, and gambling motivation partially mediated the relationship between epidemic impact and gambling behavior. Anti-epidemic measures positively moderated the epidemic's impact on gambling motivation and behavior. This paper offers a theoretical contribution by proving the influence of the social environment on human motivational behavior, especially the effect of the COVID-19 crisis, and the support of government and enterprise anti-epidemic measures for behavior intervention theory. The practicality of this study consists of behavioral interventions from anti-epidemic efforts by regional government and industry to cope with the epidemic. These measures should influence the gamblers' behavior intentions by considering the health and safety strategies that may reduce the impact of the COVID-19 epidemic on mainland Chinese gamblers. Doi: 10.28991/ESJ-2023-07-04-024 Full Text: PD
Digital Transformation Governance at the Organization Using IT Infrastructure Library Framework
Get PDFNowadays, most of our daily activities are assisted electronically due to not only time effectiveness but also activity efficiency. Processes that once could only be completed at the office are now able to be done anywhere and anytime, as long as there is internet access. One obvious example is the COVID-19 pandemic which leads to the work-from-home system. Therefore, this spurred the author on to innovation by adapting to the current phenomenon. Most of our daily activities are currently converted to digital, in which these digital users can reap abundant results. This manual-to-digital conversion is known as ‘digital transformation'. The purpose of digitalization in this organization is to transform the disposition distribution of the leaders from manual to digital. The result of the study is the adoption of e-Disposisi application (paperless office) in the organization, which causes the business processes to be more effective and more efficient concerning time, human resources, document storage, and paper use. This implementation results in changes in the business processes, the reduction of time needed to distribute documents, the lower purchase of paper and tint, and the minimized employment of human resources. Generally, the research contributes to the more effortless business processes in the organization, allowing operations to continue without direct contact. Data collection was done through various methods, namely observation, interview, questionnaire, focus group discussion (FGD), and literature. The methodologies used were Soft System Management, qualitative and quantitative referring to the IT Information Library framework. Doi: 10.28991/ESJ-2023-07-06-07 Full Text: PD
Ocular Microbiota of Severe Meibomian Gland Dysfunction (Chronic Dry Eyes) after Intense Pulsed Light (IPL)
Get PDFOcular IPL therapy has recently been widely used for MGD, especially for patients not showing improvement with traditional therapies (warm compresses and lid scrubs) to clean debris and reduce bacterial overgrowth. Insights on the ocular microbiome and quantitative microbiome in MGD after a course of IPL could provide useful data on bacterial community monitoring and associated mechanisms linked with IPL. Ocular swabs were obtained from a severe MGD patient and age-sex matched healthy for metagenomics, followed by 16S rRNA gene sequencing and qPCR. Of 10 samples, including left and right eyes (el, er) of severe MGD females before (Db) and after 2-4 IPLs (Da2, Da3, and Da4) and the matched non-MGD females (H), both of ~40 years Using 16S rRNA gene sequencing as microbiota and combined 16S rRNA gene qPCR as quantitative microbiota revealed significant disperse in the microbiome structures of Db compared with Da and H (HOMOVA, p<0.001). Bacterial Propionibacterium acnes and unclassified taxa in the family Propionibacteriaceae and order Actinomycetales represented the core Db microbiota and were reduced after 2-4 IPLs in Da, making the Da microbiome and clinical (mucocutaneous junction, corneal, and conjunctival fluorescein score) closer to H (NMDS with Pearson's correlation, p<0.05). The recovery of the Da microbiome also allowed Da metabolic potentials to be closer to H. Our findings first demonstrated the ocular microbiome dysbiosis in severe MGD, dispersed from Da and H, in Thai subjects, correlated with bacterial quantity and clinical MGD, including the mucocutaneous junction process. The results additionally provided taxa representing Db vs. Da and H and preliminarily underlie the idea that IPL could improve dysbiosis in the MGD microbiome. Doi: 10.28991/ESJ-2023-07-05-015 Full Text: PD
Towards Energy Analysis and Efficiency for Sustainable Buildings
Get PDFEnergy analysis that leads to energy efficiency becomes one of the most important factors in the building design process, especially considering the current energy crisis and the effects of global warming. Building designers greatly benefited from the review and analysis to optimize energy usage for the building in the design stage. While the current design approach is mostly done manually, this paper presents the automated version using the developed BIM plugin. It eases the designer's choice of alternative plans that yield an effectively designed building. The development of energy analysis in the application aims to promote energy efficiency by calculating the energy consumption estimation based on energy codes MS2680 and MS1525. This application is improved by a simulation that uses the Building Information Modeling (BIM) platform and extracts the necessary parameters from the BIM model with the aid of the created plugins. This study measured energy consumption and efficiency using the two primary parameters of Overall Thermal Transfer Value (OTTV) and Roof Thermal Transfer Value (RTTV). According to the results, OTTV reaches 42.72% and RTTV reaches 8.02%, both of which respectively meet Malaysian Energy Code limits of less than 50% and 25%. Doi: 10.28991/ESJ-2023-07-06-022 Full Text: PD
Recognition of Bangladeshi Sign Language (BdSL) Words using Deep Convolutional Neural Networks (DCNNs)
Get PDFIn a world where effective communication is fundamental, individuals who are Deaf and Dumb (D&D) often face unique challenges due to their primary mode of communication”sign language. Despite the interpreters' invaluable roles, their lack of availability causes communication difficulties for the D&D individuals. This study explores whether the field of Human-Computer Interaction (HCI) could be a potential solution. The primary objective is to assist D&D individuals with computer applications that could act as mediators to bridge the communication gap between them and the wider hearing population. To ensure their independent communication, we propose an automated system that could detect specific Bangla Sign Language (BdSL) words, addressing a critical gap in the sign language detection and recognition literature. Our approach leverages deep learning and transfer learning principles to convert webcam-captured hand gestures into textual representations in real-time. The model's development and assessment rest upon 992 images created by the authors, categorized into ten distinct classes representing various BdSL words. Our findings show the DenseNet201 and ResNet50-V2 models achieve promising training and testing accuracies of 99% and 93%, respectively. Doi: 10.28991/ESJ-2023-07-06-019 Full Text: PD
The Relationship between Organizational Culture, Job Satisfaction, and Commitment of Lecturers at Universities
Get PDFPurpose: The study aimed to determine the influence of factors on job satisfaction and the relationship between satisfaction, organizational culture, and the organizational commitment of lecturers at universities in Ho Chi Minh City. Design/Methodology/Approach: This was a quantitative study in which the authors compile theories, analyze and synthesize scales for research concepts, and propose research models. The online survey collected 532 answer sheets from professors and lecturers from universities in Ho Chi Minh City, of which 525 were valid and included in SmartPLS 3 to evaluate the validity and reliability of the scale and to analyze the relationship among the concepts in the suggested model. Findings: The results show that several factors significantly impact employee satisfaction in the field of education, such as job promotion, leadership or supervision, working environment, income, and the job itself. In addition, both satisfaction and organizational culture impact organizational commitment. The study's findings have implications for educational institutions, lecturers, policymakers, researchers, and funding agencies. They highlight the importance of factors like leadership development and organizational culture in enhancing job satisfaction and commitment among lecturers, offering valuable insights for improving the educational environment in Ho Chi Minh City and beyond. Originality: The results aligned with previous studies presented in the literature section. However, this study revealed some specific characteristics of lecturers in universities in Ho Chi Minh City, Vietnam, where lecturers focused on personal development but were committed to the organization via job satisfaction and culture. Doi: 10.28991/ESJ-2023-SIED2-021 Full Text: PD
Evaluation of Online Learning Platforms in Latin America
Get PDFIntroduction: The use of online learning platforms has made a huge contribution to the online learning process. A key tool in this world is videoconferencing, which allows the efficient advancement of knowledge of a specific subject during synchronized timing. Objective: With this proposed context, the objective of this investigation is to determine which online video-conference platform has more benefits to be applied in Latin America. Method: A study was carried out with a quantitative method, transversal temporality, and a correlational and comparative process. There was a sample of 272 participants between 12 and 55 years old. Results and conclusion: It was found that the platform with the most benefits according to the analysis of gender, age, and profession is ZOOM. These results allow us to analyze the usefulness of this platform and its benefits in the learning process in Latin America. Doi: 10.28991/ESJ-2022-SIED-018 Full Text: PD
Probabilistic Analysis Depending on the Distance from A COVID-19 Outbreak
Get PDFCOVID-19 has been affecting human beings since the end of 2019. Studying the characteristics of a COVID-19 outbreak is significant because it will add to the knowledge that is necessary for protecting the general public and controlling future viral outbreaks. The aims of the present research are to analyze COVID-19 outbreaks in Thailand depending on the distance from the outbreak center by using a differential equation, to construct a probability density function from the solution of the differential equation, and to prove the theorem for the probability density function depending on the distance from the outbreak. The least-squares-error method is adopted to estimate the parameters of the function describing the COVID-19 outbreak. Moreover, a cumulative distribution function, a quantile function, a sojourn function, a hazard function, the median, the expected value, variance, skewness, and kurtosis are derived, and their practicability is shown. Applying the exponentially weighted moving average control chart to monitor a COVID-19 outbreak based on distance is proposed and compared with monitoring the COVID-19 outbreak based on time. The results show that using the former more quickly detected the out-of-control first passage time of the COVID-19 outbreak than the latter. Doi: 10.28991/ESJ-2023-SPER-012 Full Text: PD