• The Journal of Industrial Distribution & Business
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• v.11 no.6
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• pp.29-39
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• 2020

Purpose: The purpose of this study is, in the situation where rapid response to the rapidly changing environment is required due to the development of the fourth industrial revolution such as artificial intelligence, virtual reality, and the internet of things, robotics, big data, additive manufacturing, bio-health, sharing economy and in the organizational culture aspiring toward the innovation of a major company, small business and a public institution, to analyze what influence a job-engagement and stress make, and what influence individual's self-efficacy as a moderator mediator makes, and to offer basic data for improving job-engagement and lowering job-stress. Research design, data, and methodology: For doing this, the literature and the empirical studies were combined. Deriving innovation-oriented organizational culture as factors affecting the job engagement and job stress through the literature, and have established hypotheses to verify them. We have collected data of 281 from ex,ecutives and staff-members working in areas including major company, small business and officials (the central government, a local public service, the prosecution, the police, and school). And these data were analyzed by SPSS 23 version. Results: Based on these data, the results of analysis were as follows; First, the innovation-oriented organizational culture which was recognized by organizational members had effect on job-stress. Second, the innovation-oriented organizational culture which was recognized by organizational members influenced job-stress. Third, in the relationship between the innovation-oriented organizational culture and job-engagement, self-efficacy did not influenced job-engagement. Finally, in the relationship between the innovation-oriented organizational culture and job-stress, self-efficacy influenced job-stress. Conclusions: Innovation-oriented organizational culture places importance on the organization's adaptability and flexibility in the external environment, so companies need to establish an innovation-oriented organizational culture favorable to achieving survival and successful innovation, and to develop and disseminate programs of positive and continuous organizations to improve task enthusiasm, reduce task stress, and enhance organizational performance. In the future, it will be necessary to verify the effectiveness of various organizational culture types through comparative analysis with companies that actively maintain an innovation-oriented organizational culture (Google, Kakao, etc.) and companies that prefer hierarchy-oriented organizational culture, relationship-oriented organizational culture, and market-oriented organizational culture.

• Journal of Korean Society of Rural Planning
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• v.23 no.2
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• pp.55-65
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• 2017

This study is to estimate the circuity factors which can be used to assess for public facilities accessibility and analyze traffic in the area. We set the range of the administrative districts by Si Gun Gu unit and Eup Myeon Dong unit (more subdivided unit than Si Gun Gu unit). The average circuity factor in Si Gun Gu unit is 1.364 (maximum 2.953 and minimum 1.711). The region indicated the highest value of circuity factor is wando-gun in jeollanam-do, which area consists of 4 island and is connected to the bridges. Having to use the bridges for using public facilities hinders its accessibility. In the case of Eup Myeon Dong unit, the average circuity factor is 1.353 (maximum 2.950 and minimum 1.154). The region indicated the highest value of circuity factor is buksan-myeon in chuncheon-si, Gangwon-do. This region also has to use bridges for using public facilities because there is the largest lake, called Soyangho. This circuity factor is used to analyze the location of public facilities and assess vulnerability of accessibility. And also the factor can be applied to some policies, such as rural public service planning based on spatial big data.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.317-325
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• 2021

By analyzing the recognition analysis and motivation method of the determinants, this study investigates the future development direction of health exercise biodata analysis face-to-face practice education content. The participants were 40 millennial and zoomers (MZ) generation college graduates. Factors related to the decision to participate in face-to-face practice classes in the field of health exercise biodata and bio-digital content convergence technology in the era of COVID-19 were measured. Of the participants, 67.5% voluntarily decided to participate in small group classes while observing social distancing rules. This study presented the most effective and learning motive methods to participate in face-to-face training. Health exercise biodata needs improvement in terms of integrating with adjacent disciplines such as big data.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.7-15
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• 2022

Recently, due to the development of AI and big data technologies following the advent of the era of the 4th Industrial Revolution, the emerging metaverse industry is emerging as a new business, and in particular, from this point of view, this paper analyzes the history of metaverse and the pros and cons of "Geppetto", which is the most popular in the Korean metaverse market, and aims to give an appropriate direction for future development based on this. In order to carry out this study, we first used SWOT analysis techniques as an initial enterprise analysis method to examine the strengths and weaknesses, opportunities and threat requirements, and derive the status of each factor. Based on the factors in each of the subsequent derivatives, we wanted to explore the TOWS development strategy and present significant implications based on this.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.749-760
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• 2022

Omics-driven synthetic biology is a multidisciplinary research field that creates new artificial life by employing genetic components, biological devices, and engineering technique based on genetic knowledge and technological expertise. It is also utilized to make valuable biomaterials with limited production via current organisms faster, more efficient, and in huge quantities. As the bioeconomic age begins, and the global synthetic biology market becomes more competitive, investment in research and development (R&D) and associated sectors has grown considerably. By overcoming the constraints of present biotechnologies through the merging of big data and artificial intelligence technologies, huge ripple effects are envisaged in the pharmaceutical, chemical, and energy industries. In agriculture, synthetic biology is being used to solve current agricultural problems and develop sustainable agricultural systems by increasing crop productivity, implementing low-carbon agriculture, and developing plant-based, high-value-added bio-materials such as vaccines for diagnosing and preventing livestock diseases. As international regulatory debates on synthetic biology are now underway, discussions should also take place in our country for the growth of bioindustries and the dissemination of research findings. Furthermore, the system must be improved to facilitate practical application and to enhance the risk evaluation technology and management system.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.607-617
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• 2020

Human bio-monitoring (HBM) data is a very important resource for tracking total exposure and concentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to execute the integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemical description and coding system between different sources in Korea. In this study, we presented a standardized code system and HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 raw datasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed the HBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. In addition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This study will contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.699-706
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• 2009

The convergence tendency accelerates the realization of the ubiquitous healthcare (u-Healthcare) between the technology including the power generaation and IT-BT-NT of the ubiquitous computing technology. By rapidly analyzing a large amount of collected from the sensor network with processing and delivering to the medical team an u-Healthcare can provide a patient for an inappropriate regardless of the time and place. As to the existing u-Healthcare, since the sensor node all transmitted collected data by using with the Zigbee protocol the processing burden of the base node was big and there was many communication frequency of the sensor node. In this paper, the u-Healthcare system in which it can efficiently apply to mobile apparatuses it provided the transfer rate in which it is superior to the bio-signal delivery where there are the life and direct relation which by using the Bluetooth instead of the Zigbee protocol and in which it is variously used in the ubiquitous environment was designed. Moreover, by applying the EEF(Embedded Event Filtering) technique in which data in which it includes in the event defined in advance selected and it transmits with the base node, the communication frequency and were reduced. We confirmed to be the system in which it is efficient through the simulation result than the existing Electrocardiogram Measurement system.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.469-480
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• 2013

In this paper, we propose new method to reduce variance and express mixed feelings in Russell's emotional dimension(A Circumplex model). A Circumplex model shows mean and variance of emotions(joy, sad, happy, enjoy et. al.) in PAD(Pleasure, Arousal, Dominace, et. al.) dimension using self-diagnostic method(SAM: Self-Assessment-Manikin). But other researchers consistently insisted that Russell's model had two problems. First, data(emotional words) gathered by Russell's method have too big variance. So, it is difficult to separate valid value. Second, Russell's model can not properly represent mixed feelings because it has structural problem(It has a single Pleasure dimension). In order to solve these problems, we change survey methods, so that we reduce value of variance. And then we conduct survey(which can induce mixed feelings) to prove Positive/Negative(Pleasure) part in emotion and confirm that Russell's model can be used to express mixed feelings. Using this method, we can obtain high reliability and accuracy of data and Russell's model can be applied in many other fields such as bio-signal, mixed feelings, realistic broadcasting, et. al.