• International journal of advanced smart convergence
• /
• v.9 no.1
• /
• pp.63-69
• /
• 2020

The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.

• Journal of Internet Computing and Services
• /
• v.23 no.3
• /
• pp.97-110
• /
• 2022

Federated learning is a learning method capable of performing model learning without transmitting learning data. The IoT or healthcare field is sensitive to information leakage as it deals with users' personal information, so a lot of attention should be paid to system design, but when using federated-learning, data does not move from devices where data is collected. Accordingly, many federated-learning implementations have been developed, but detailed research on system design for the development and operation of systems using federated learning is insufficient. This study shows that measures for the life cycle, code version management, model serving, and device monitoring of federated learning are needed to be applied to actual projects and distributed to IoT devices, and we propose a design for a development environment that complements these points. The system proposed in this paper considered uninterrupted model-serving and includes source code and model version management, device state monitoring, and server-client learning schedule management.

• Design Convergence Study
• /
• v.16 no.5
• /
• pp.125-140
• /
• 2017

This study explores potential capability of a machine learning approach for monitoring urban morphology based on an evident case study. The case study conveys year 2006 investigations on interpreting urban morphology of Boston Main Streets by applying a machine learning approach. From the lesson of the precedent study, in 2016, another field research and interview was conducted to compare changes in urban situation, data commons culture, and technology innovation during the decade. This paper describes open possibilities to advance urban monitoring for morphological changes. Most of all, a multi-participatory data platform enables managing urban data system in real time. Second, collaboration with machines with artificial intelligence can intervene the framework of the urban management system as well as transform it through new demands of innovative industries. Recently, urban regeneration became a dominant urban planning strategy in Korean, therefore, urban monitoring is on demand. It is timely important to correspond to in-situ problems based on empirical research.

• ALGAE
• /
• v.38 no.1
• /
• pp.1-22
• /
• 2023

An enormous body of research is focused on finding ways to commercialize carotenoids produced by the unicellular green alga, Haematococcus, often without the benefit of a sound phylogenetic assessment. Evidence of cryptic diversity in the genus means that comparing results of pigment studies may be confounded by the absence of a phylogenetic framework. Moreover, previous work has identified unnamed strains that are likely candidates for species status. We reconstructed the phylogeny of an expanded sampling of Haematococcus isolates utilizing data from nuclear ribosomal markers (18S rRNA gene, 26S rRNA gene, internal transcribed spacer [ITS]-1, 5.8S rRNA gene, and ITS-2) and the rbcL gene. In addition, we gathered morphological, ultrastructural and pigment data from key isolates of Haematococcus. Our expanded data and taxon sampling support the concept of a new species, H. privus, found exclusively in North America. Despite overlap in numerous morphological traits, results indicate that ratios of protoplast length to width and akinete diameter may be useful for discriminating Haematococcus lineages. High growth rate and robust astaxanthin yield indicate that H. rubicundus (SAG 34-1c) is worthy of additional scrutiny as a pigment source. With the description of H. privus, the evidence supports the existence of at least five, species-level lineages in the genus. Our phylogenetic assessment provides the tools to frame future pigment investigations of Haematococcus in an updated evolutionary context. In addition, our investigation highlighted open questions regarding polyploidy and sexuality in Haematococcus which demonstrate that much remains to be discovered about this green flagellate.

• Journal of Korea Multimedia Society
• /
• v.7 no.1
• /
• pp.12-26
• /
• 2004

In the past, geographic data is constructed and serviced through independent formats of its own according to each GIS(Geographic Information System). Recently the provision of interoperability in GIS is important to efficiently apply the various geographic data between conventional GIS's. Whereupon OGC(Open GIS Consortium) proposed GML(Geography Markup Language) to offer the interoperability between heterogeneous GISs in distributed environments. The GML is an XML encoding for the transport and storage of geographic information, including both the spatial and non-spatial properties of geographic features. Also, the GML includes Web Map Server Implementation Specification to service the GML documents. Accordingly the prototype to provide the reciprocal interchange of geographic information between conventional GIS's and GML documents is widely studied. In this paper, we propose a mapping method of geographic in formation between spatial database and GML for the prototype to support the interoperability between heterogeneous geographic information. For this method, firstly the scheme of converting geographic in Formation of the conventional spatial database into the GML document according to the GML specification is explained, and secondly the scheme to transform geographic information of GML documents to geographic data of spatial database is showed. Consequently, the proposed method is applicable to the framework for integrated geographic information services based on Web by making an offer the interoperability between already built geographic information of conventional GIS's using a mapping method of geographic information between spatial database and GML.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.123-139
• /
• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Korean Academy of Nursing
• /
• v.25 no.4
• /
• pp.790-806
• /
• 1995

The present study examined the causal relationships among nurses' job environment /job characteristics(work overload, lack of autonomy, professional role conflict, interpersonal relationships), maturity, job stress, job satisfaction and turnover intention by constructing and testing a theoretial framework. Based on Katz and Kahn's (1978) theory of organizational open system and Kahn, Wolfe, Quinn, and Snoek's (1964) theory of stress, nurses' turnover intention, job satisfaction and job stress were conceived of as outcomes of the interplay between personal characteristics and work environment. Personal aspects associated with outcome variables included professional knowlege and skill, and maturity(challenge, commitment, control, responsibility). The work environment factors involved work overload, lack of autonomy, professional role conflict, and interpersonal relationships (social support). Three university hospitals located in Seoul were selected to participate. The total sample of 443 registered nurses represents a response rate of 96 percent. Linear structural relationships (LISREL) technique was used to test the fit of the proposed conceptual model to the data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently, revealing considerable explanatinal power for job stress and job satisfaction. The explanatory power of turnover intention was relatively lower than those of stress and satisfaction. In predicting nurses' stress, satisfaction and turnover intention, the findings of this study clearly demonstrated that professional role conflict might be the most important variable of the all the environmental variables and personal characteristics. The results were dis-cussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.2
• /
• pp.126-136
• /
• 2020

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.5
• /
• pp.631-636
• /
• 2019

Over the last decade, many researchers have investigated a number of vision-based construction object detection algorithms for the purpose of construction site monitoring. However, previous methods require the ground truth labeling, which is a process of manually marking types and locations of target objects from training image data, and thus a large amount of time and effort is being wasted. To address this drawback, this paper proposes a vision-based construction object detection framework that employs an active learning technique while reducing manual labeling efforts. For the validation, the research team performed experiments using an open construction benchmark dataset. The results showed that the method was able to successfully detect construction objects that have various visual characteristics, and also indicated that it is possible to develop the high performance of an object detection model using smaller amount of training data and less iterative training steps compared to the previous approaches. The findings of this study can be used to reduce the manual labeling processes and minimize the time and costs required to build a training database.

• Journal of Preventive Medicine and Public Health
• /
• v.54 no.5
• /
• pp.330-339
• /
• 2021

Objectives: Tobacco control in Indonesia is very lenient compared to international standards. This study explored the perspectives of tobacco control stakeholders (TCSs) on the likelihood of advancing tobacco marketing regulation in Indonesia. Methods: Data were collected from TCSs who were members of the Indonesia Tobacco Control Network group in a modified Delphi study. We collected the data in 2 waves using a questionnaire that comprised a set of closed and open-ended questions. For this paper, we analysed 2 of the 3 sections of the questionnaire: (1) tobacco advertising, promotions, and sponsorship (TAPS) bans, and (2) marketing and retailing regulations. We conducted a descriptive analysis of the scores using Stata/IC.13 and summarised the comments for each item. Results: The TCSs viewed the measures/strategies across all aspects of TAPS and tobacco marketing regulation as highly desirable, but provided varied responses on their feasibility. They rated political feasibility lower than technical feasibility for most measures. Advancing TAPS measures and prohibition of selling to minors were considered more attainable by sub-national governments, while prohibition of tobacco corporate social responsibility was considered as the least feasible measure in the next 5 years. Conclusions: Despite little optimism for substantial national-level change, there is a positive expectation that sub-national governments will strengthen their tobacco control regulation. It is paramount that the government reduce tobacco industry leverage by implementing Article 5.3 of the World Health Organization Framework Convention on Tobacco Control. Extending advocacy networks beyond tobacco control groups and framing tobacco control more effectively are necessary steps.