• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.675-684
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• 2021

This paper aims to analyze factors influencing earnings of workers in Vietnam using provincial-level data from 2016 to 2018. We show the important determinants of earnings of workers of more than 15 years old including working hour, labor force, life expectancy, education, regulation measured by Provincial Competitiveness Index (PCI) and especially Industry 4.0, our major depart from literature proxies by government expenditure on science and technology, number of phone lines, and number of internet users. Working hours are a typical measurement of quantity of labor supplied. Labor force represents market size from the supply side. Life expectancy measures the health of laborers, a physical quality measure of workers. PCI stands for institutional status of the locality. Two most important factors of our interest are education, representing qualification of workers, and Industry 4.0, reflecting the new working environment of workers. By estimating a robust standard error fixed-effect model, we have evidence that all factors are significant in explaining earnings of Vietnamese workers. Education and IR4.0 play an important role in earnings of workers of Vietnam. Results also provide an estimation of Vietnam's labor supply in the context of Industry 4.0. In addition, findings contribute to explain the income discrepancy among Vietnamese provinces.

• Food Science and Industry
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• v.49 no.4
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• pp.31-39
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• 2016

The reasons for selecting insects as future food are high growth and feed conversion rates, reproduce quickly, low environmental footprint, valuable source of nutrients, and source of a various undeveloped functional materials. Since 2014, Tenebrio molitor larva, Protaetia brevitarsis larva, Allomyrina dichotoma larva, and Gryllus bimaculatus were registered as new food in Korea because it has been scientifically proven that they are not harmful to eat and nutritious. Therefore they can be legally produced and sold as food. Accordingly, there are 7 species of edible insects including grasshopper, silkworm pupa, and Baekgangjam in Korea. To improve aversion to edible insects, using their powder, chop, and gravy hidden their morphology, we developed more than 100 different kinds of recipes for general food menu, held several times tasting events to be familiar with edible insect food, and published cookbooks. Moreover, we developed more than 50 kinds of recipes for patients. To eat the insect food more and more people, we have been analyzed various function of insects. If health food based on the results of functional analysis is developed, edible insect's value will be raised. If various insect foods are developed and consumed by people, edible insect market will grow up more than 100 billion won in 2020.

• Food Science and Industry
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• v.50 no.1
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• pp.2-10
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• 2017

Human have eaten various traditional fermented foods for a numbers of million years for health benefit as well as survival. The beneficial effects of fermented foods have been resulted from complex microbial communications within the fermented foods. Therefore, the holistic approaches for individual identification and complete microbial profiling involved in their communications have been of interest to food microbiology fields. Microbiome is the ecological community of microorganisms that literally share our environments including foods as well as human body. However, due to the limitation of culture-dependent methods such as simple isolations of just culturable microorganisms, the culture-independent methods have been consistently developed, resulting in new light on the diverse non-culturable and hitherto unknown microorganisms, and even microbial communities in the fermented foods. For the culture-independent approaches, the food microbiome has been deciphered by employing various molecular analysis tools such as fluorescence in situ hybridization, quantitative PCR, and denaturing gradient gel-electrophoresis. More recently, next-generation-sequencing (NGS) platform-based microbiome analysis has been of interest, because NGS is a powerful analytical tool capable of resolving the microbiome in respect to community structures, dynamics, and activities. In this overview, the development status of analysis tools for the fermented food microbiome is covered and research trend for NGS-based food microbiome analysis is also discussed.

• Electronics and Telecommunications Trends
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• v.37 no.2
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• pp.30-41
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• 2022

As the society is superaging, the number of patients with movement disabilities due to musculoskeletal or nervous system illness is rapidly increasing. To improve public health and reduce medical expenses, it is essential to develop rehabilitation systems that allow patients to resume their daily-life activities. However, the existing musculoskeletal illness diagnosis and rehabilitation method is limited in terms of precision and efficiency because it is based on an empirical diagnosis and prescription without regard for individual characteristics. To overcome these limits, it is critical to design a novel concept of routine rehabilitation therapy device that is capable of inducing musculoskeletal balance by the precise analysis of musculoskeletal usage patterns via the motion and the muscle activity tracking of linked muscles. This study introduces the trend of on-skin sensor device technology for routine musculoskeletal monitoring and therapy. For on-skin rehabilitation systems, skin-adhesive and stretchable motion/posture, electromyography, pressure sensors, small-size and low-power wireless sensor interfaces, and user-friendly rehabilitation contents based on new algorithms are combined.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.29-41
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• 2021

The spread of COVID-19 has been changed the tourism industry. Travelers changed their traveling style and started to consider congestion of the spot for their health and safety. In Jeju, a famous tourist destination in South Korea, managing the congestion of tourists has become an important issue. This example introduces the Jeju Tourism Organization's development of a system as a smart tourism information service that manages congestion in real-time big data. Combining with congestion theory and behavior immune system, we would like to assure the necessity of the system. Also, by analyzing the system, we understand how deducing congestion information from big data and the new paradigm of the tourism industry combined with congestion theory. Data was collected by Korea's telecommunication company SKT to develop the system. The paper explains the reason for choosing the company and the pros of data quality. We expect this system to be a solution for any other city in the world under a similar situation. Finally, several suggestions for the system are included to promote and better future usage.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.39-46
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• 2022

The spread of Omicron, a mutated version of COVID-19 across several countries is leading to the discussion of lockdown once again for curbing the spread of the new virus. In this context, this research is showing the impact of lockdown for the successful control of the COVID-19 pandemic in Saudi Arabia. The outbreak of the COVID-19 pandemic around the globe has affected Saudi Arabia with around 2,37,803 confirmed cases within the initial 4 months of transmission. Saudi Arabia has announced a 21-day lockdown from March 23, 2020, to reduce the transmission of the COVID-19 pandemic. Machine Learning-based, Multinomial logistic regression was applied to understand the relationship between daily COVID-19 confirmed cases and lockdown in the 17 most-affected cities of KSA. We used secondary published data from the Ministry of Health, KSA daily dataset of COVID-19 confirmed case counts. These 17 cities were categorized into 4 classes based on lockdown dates. A total of three scenarios such as night lockdown, full lockdown, and no lockdown have been analyzed with the total number of confirmed cases with 4 classes. 15 out of 17 cities have shown a strong correlation with a confidence interval of 95%. These findings provide evidence that the COVID-19 pandemic may be partially suppressed with lockdown measures.

• Parasites, Hosts and Diseases
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• v.60 no.6
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• pp.379-391
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• 2022

Leishmaniasis is a serious parasitic disease caused by Leishmania spp. transmitted through sandfly bites. This disease is a major public health concern worldwide. It can occur in 3 different clinical forms: cutaneous, mucocutaneous, and visceral leishmaniasis (CL, MCL, and VL, respectively), caused by different Leishmania spp. Currently, licensed vaccines are unavailable for the treatment of human leishmaniasis. The treatment and prevention of this disease rely mainly on chemotherapeutics, which are highly toxic and have an increasing resistance problem. The development of a safe, effective, and affordable vaccine for all forms of vector-borne disease is urgently needed to block transmission of the parasite between the host and vector. Immunological mechanisms in the pathogenesis of leishmaniasis are complex. IL-12-driven Th1-type immune response plays a crucial role in host protection. The essential purpose of vaccination is to establish a protective immune response. To date, numerous vaccine studies have been conducted using live/attenuated/killed parasites, fractionated parasites, subunits, recombinant or DNA technology, delivery systems, and chimeric peptides. Most of these studies were limited to animals. In addition, standardization has not been achieved in these studies due to the differences in the virulence dynamics of the Leishmania spp. and the feasibility of the adjuvants. More studies are needed to develop a safe and effective vaccine, which is the most promising approach against Leishmania infection.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Advances in materials Research
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• v.12 no.2
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• pp.119-131
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• 2023

The development of sustainable composites materials, from recycled polymeric materials and waste from the wood industry and stone processing, allows reducing the volume of these by-products, minimizing impacts on health and the environment. Nowadays, Polypropylene (PP) is the most recycled polymer in industry, while the furniture industry has increasingly used timber felled from sustainable forest plantations as a eucalypt. The powder tailing from the ornamental stone extraction and processing industry is commonly disposed of in the environment without previous treatment. Thus, the technological option for the development of composite materials presents itself as a sustainable alternative for processing and manufacturing industries, enabling the development of new materials with special technical features. The results showed that powder granite particles may be incorporated into the polypropylene matrix associated with short eucalyptus fibres forming green hybrid composites with potential application in structural engineering, such as transport and civil construction industries.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.786-790
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• 2005

As the scale of building construction is larger and more complex and the adaptation of new technology is increasing, the tendency of the risk serious accident cases is increasing now. Especially, the accident rate is below 10% at the building construction workers in Korea but among the total industrial accidents it exceeded by 35%. To prevent a construction accident, it is essential that not only to have a through grasp of the characteristic of safety problem but also to establish of efficient safety counter plan are required. According to the type and situation of building construction, the acquirement of necessary information is useful to prevent the hazard of work and establish the counter plan. Among the safety information it is a thing of especial importance that to estimate the hazard of work types for building construction to prepare the counter plan of safety. This study will analyze all of the1600 accidents of the building construction works from the data of KOSHA(Korea Occupational Safety &Health Agency) which were collected during 11 years(1992~2002) data relating to serious accidents of the building construction works, and suggest the counter plan according to the each work type in building construction works.