• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.337-347
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• 2021

This study is a qualitative study conducted to provide basic data for therapists working in long-term care hospitals to improve their countermeasure strategies for new infectious diseases and improvement of the treatment room infection management system, and to help therapists understand their infection management work. Colaizzi's phenomenological research method was applied as the research method. Telephone interviews were conducted with nine occupational therapists and physical therapists working in nursing hospitals. The contents of the interview were recorded with the consent of the study subjects, and additional confirmation was received by email. The recorded content was analyzed after transcription, and the meaning and nature of the experience coping with COVID-19 were described. The content was organized into 6 themes, 17 main meaning and 49 meaning units. In accordance with the COVID-19 situation, the infection control system has been strengthened by reinforcing infection control education in nursing hospitals, practicing infection control, and supervising infection control outside business hours. It was found that the treatment environment was changed due to the restriction of treatment activities by practicing distancing in the treatment room, adjusting rest and meal times during working hours, and strengthening infection control. In addition, the therapist's role has been expanded and the paradigm of treatment has changed, such as considering the untact intervention, and they have experienced cohort quarantine, pre-tested for COVID-19, vaccinations, and side effects from COVID-19. However, due to the infection work, the therapist's work burden is increased, and the person is experiencing fear, depression, and work stress from the spread of COVID-19. They were also aware of the need for nursing hospital care personnel support, such as guaranteeing rest after vaccination and providing infection control tools and equipment. The results of this study are expected to be used as basic data for human and physical support for the development of infectious disease response strategy programs in nursing hospital treatment rooms and for infection control in nursing hospitals.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.8
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• pp.759-769
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• 2013

Electronic equipment has been applied to virtually every area associated with commercial, industrial, and military applications. Specifically, electronics have been incorporated into avionics components installed in aircraft. This equipment is exposed to dynamic loads such as vibration, shock, and acceleration. Especially, avionics components installed in a helicopter are subjected to simultaneous sine and random base excitations. These are denoted as sine on random vibrations according to MIL-STD-810F, Method 514.5. In the past, isolators have been applied to avionics components to reduce vibration and shock. However, an isolator applied to an avionics component installed in a helicopter can amplify the vibration magnitude, and damage the chassis, circuit card assembly, and the isolator itself via resonance at low-frequency sinusoidal vibrations. The objective of this study is to investigate the dynamic characteristics of an avionics component installed in a helicopter and the structural dynamic modification of its tray plate without an isolator using both a finite element analysis and experiments. The structure is optimized by dynamic loads that are selected by comparing the vibration, shock, and acceleration loads using vibration and shock response spectra. A finite element model(FEM) was constructed using a simplified geometry and valid element types that reflect the dynamic characteristics. The FEM was verified by an experimental modal analysis. Design parameters were extracted and selected to modify the structural dynamics using topology optimization, and design of experiments(DOE). A prototype of a modified model was constructed and its feasibility was evaluated using an FEM and a performance test.

• Journal of Science Education
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• v.42 no.1
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• pp.49-65
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• 2018

Astronomy is the subject that can easily draw students' interest in studying science, therefore plays an important role in developing scientific core competence. However, it is difficult to develop spatial thinking that is required in understanding astronomical concepts through the classroom lessons. Planetarium, along with the science museum, is one of the most representative informal educational institution where astronomical concepts can be taught beyond time and space constraints. In this study, we developed the astronomy education program that is operated in the planetarium and applied the program to the elementary, middle and high-school students to investigate the effects of the planetarium lesson compared to the classroom lesson. The duration of this research was about 8 months, and the number of the students involved is 761, including participants of the 1 night and 2 days camps in the Daegu National Science Museum. The newly developed planetarium lesson is comparable to the previous classroom lesson of which topics are cardinal points, constellation, and the rotation of the earth. Test items were developed to evaluate the understanding of the astronomical concepts. The study was conducted based on the pre- and post-test with non-equivalent groups design comparing classroom and planetarium lessons. The results of this study are as follows. First, planetarium lesson is more effective for understanding astronomical concepts such as the cardinal points, earth's rotation, and the constellation than classroom lesson. Second, planetarium has a positive effect irrespective of gender and previous knowledge. Third, planetarium for high school students has the same effect as additional observation activities followed by the classroom instruction. Therefore, planetarium can be used as an alternative, effective tool when night observation is not available. In summary, planetarium is an effective tool that helps students to understand the astronomical concepts.

• Korean Journal of Food Science and Technology
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• v.36 no.5
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• pp.701-710
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• 2004

Uncertainty was quantified to evaluate calcium determination result in infant formula with AAS (Atomic Absorption Spectrometry) and ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry). Uncertainty sources in measurand, such as sample weight, final volume of sample, sample dilution and the instrumental result were identified and used as parameters for combined standard uncertainty based on the GUM (Guide to the expression of uncertainty in measurement) and Draft EURACHEM/CITAC Guide. Uncertainty components of each sources in measurand were identified as resolution, reproducibility and stability of chemical balance, standard material purity, standard material molecular weight, standard solution concentration, standard solution dilution factor, sample dilution factor, calibration curve, recovery, instrumental precision, reproducibility, and stability, Each uncertainty components were evaluated by uncertainty types and included to calculate combined uncertainty. The kinds of uncertainty sources and components in the analytical method by AAS and ICP-AES were same except sample dilution factor for AAS. The analytical results and combined standard uncertainties of calcium content were estimated within the certification range $(367{\pm}20\;mg/100g)$ of CRM (Certified Reference Material) and were not significantly different between method by AAS followed by ashing and method by ICP-AES followed by acid digestion as $359.52{\pm}23.61\;mg/100g\;and\;354.75{\pm}16.16\;mg/100g$, respectively. Identifying uncertainty sources related with precision, repeatability, stability, and maintaining proper instrumental conditions as well as personal proficiency was needed to reduce analytical error.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.121-137
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• 2020

Data from the Ozone Monitoring Instrument (OMI) satellite and national emission inventories were used in this study to analyze air quality in East Asia and estimate the impact of domestic and foreign emissions on South Korea's air quality, based on which future emissions were predicted. The concentration trends of nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) in East Asia from 2005 to 2015 showed that both substances were highest in North East China (NEC), followed by South East China (SEC) and Seoul Metropolitan Area (SMA). The average SO₂ concentration was 1.63 times higher in NEC than in SMA. Analysis on the ratios of NO₂/SO₂ and NO_x/SO_x provides an indirect picture of the effect of transboundary air pollutants on atmospheric composition in Korea. The concentration ratio of NO₂/SO₂ in all study areas peaked in 2013 and SMA's emission ratio of NO_x/SO_x increased in 2015 by over 22% from 2013. Despite the reduction in domestic emissions, the concentration-to-emission ratios (NO₂/NO_x, SO₂/SO_x) rose gradually, which implies that other factors besides domestic emissions (e.g., foreign sources, lifetime, etc.) influence air quality in SMA. We estimated future emissions of NO_x and SO_x in SMA to be 296.2 and 39.0 ktons in 2025 and 284.4 and 33.8 ktons in 2035, respectively. Application of the inter-comparison techniques of this study to the data from the Geostationary Environment Monitoring Instrument (GEMS) is expected to provide concrete information which can be used to improve national emission inventories and figure out factors and sources that affect domestic air quality.

• Korean small business review
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• v.42 no.1
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• pp.79-105
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• 2020

While individual enterprises with different objectives each other within supply chains require a variety of resources to achieve their own seeking goals and performances, it is necessary to form interdependent relationships among the enterprises to secure the resources what they need, as the individual enterprises are supposed to have limitations on such as time, space and cost to secure all the resources. In this process, conflict possibilities rise and opportunistic behaviors increase due to those environmental factors such as unbalanced information among enterprises, limited rationality, pursuit of interests, and risk aversion. Those existing studies on conflicts in the field of supply chains have limitations in that they failed to present specific conflict management strategies based on the conflict types from the perspective of the conflict resolution mechanism as the studies have made only focused on investigating the causes of conflicts and the impact of conflicts on performance. In this study, therefore, it used the TKI model of Kilmann and Thomas(1977) to subdivide the conflict management strategies in the process of transactions within supply chains by enterprises, and looked into the impact on partnership and performance according to each strategy. As the results, it showed that those types of conflict management strategies such as concession type and cooperation type had a positive(+) impact on the relationship commitment as a factor of partnership, and it was identified that the relationship commitment had a positive(+) impact on performance. In other words, it can be considered that the enterprises making use of the concession type & the cooperation type conflict management strategies under the situation of conflict would be able to have a very positive impact on their performances if they can make good relationship commitment such as investments in and efforts for the sustainable relationship along with the conflict management, while recognizing the importance of relationship. The most important meaning of this study lies on in terms of that it would be contributable to strengthening the partnership between enterprises and minimizing the risk of supply chains caused by conflicts through these results from the study.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.