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Problems with ERP Education at College and How to Solve the Problems (대학에서의 ERP교육의 문제점 및 개선방안)

  • Kim, Mang-Hee;Ra, Ki-La;Park, Sang-Bong
    • Management & Information Systems Review
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    • v.31 no.2
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    • pp.41-59
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    • 2012
  • ERP is a new technique of process innovation. It indicates enterprise resource planning whose purpose is an integrated total management of enterprise resources. ERP can be also seen as one of the latest management systems that organically connects by using computers all business processes including marketing, production and delivery and control those processes on a real-time basis. Currently, however, it's not easy for local enterprises to have operators who will be in charge of ERP programs, even if they want to introduce the resource management system. This suggests that it's urgently needed to train such operators through ERP education at school. But in the field of education, actually, the lack of professional ERP instructors and less effective learning programs for industrial applications of ERP are obstacles to bringing up ERP workers who are competent as much as required by enterprises. In ERP, accounting is more important than any others. Accountants are assuming more and more roles in ERP. Thus, there's a rapidly increasing demand for experts in ERP accounting. This study examined previous researches and literature concerning ERP education, identified problems with current ERP education at college and proposed how to solve the problems. This study proposed the ways of improving ERP education at college as follows. First, a prerequisite learning of ERP, that is, educating the principle of accounting should be intensified to make students get a basic theoretical knowledge of ERP enough. Second, lots of different scenarios designed to try ERP programs in business should be created. In association, students should be educated to get a better understanding of incidents or events taken place in those scenarios and apply it to trying ERP for themselves. Third, as mentioned earlier, ERP is a system that integrates all enterprise resources such as marketing, procurement, personnel management, remuneration and production under the framework of accounting. It should be noted that under ERP, business activities are organically connected with accounting modules. More importantly, those modules should be recognized not individually, but as parts comprising a whole flow of accounting. This study has a limitation because it is a literature research that heavily relied on previous studies, publications and reports. This suggests the need to compare the efficiency of ERP education between before and after applying what this study proposed to improve that education. Also, it's needed to determine students' and professors' perceived effectiveness of current ERP education and compare and analyze the difference in that perception between the two groups.

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A Study on Differences of Opinions on Home Health Care Program among Physicians, Nurses, Non-medical personnel, and Patients. (가정간호 사업에 대한 의사, 간호사, 진료관련부서 직원 및 환자의 인식 비교)

  • Kim, Y.S.;Lim, Y.S.;Chun, C.Y.;Lee, J.J.;Park, J.W.
    • The Korean Nurse
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    • v.29 no.2
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    • pp.48-65
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    • 1990
  • The government has adopted a policy to introduce Home Health Care Program, and has established a three stage plan to implement it. The three stage plan is : First, to amend Article 54 (Nurses for Different Types of Services) of the Regulations for Implementing the Law of Medical Services; Second, to tryout the new system through pilot projects established in public hospitals and clinics; and third, to implement at all hospitals and equivalent medical institutions. In accordance with the plan, the Regulation has been amend and it was promulgated on January 9,1990, thus establishing a legal ground for implementing the policy. Subsequently, however, the Medical Association raised its objection to the policy, causing a delay in moving into the second stage of the plan. Under these circumstances, a study was conducted by collecting and evaluating the opinions of physicians, nurses, non-medical personnel and patients on the need and expected result from the home health care for the purpose of help facilitating the implementation of the new system. As a result of this study, it was revealed that: 1. Except the physicians, absolute majority of all other three groups - nurses, non-medical personnel and patients -gave positive answers to all 11 items related to the need for establishing a program for Home Health Care. Among the physicians, the opinions on the need for the new services were different depending on their field of specialty, and those who have been treating long term patients were more positive in supporting the new system. 2. The respondents in all four groups held very positive view for the effectiveness and the expected result of the program. The composite total of scores for all of 17 items, however, re-veals that the physicians were least positive for the- effectiveness of the new system. The people in all four groups held high expectation on the system on the ground that: it will help continued medical care after the discharge from hospitals; that it will alleviate physical and economic burden of patient's family; that it will offer nursing services at home for the patients who are suffering from chronic disease, for those early discharge from hospital, or those who are without family members to look after the patients at home. 3. Opinions were different between patients( who will receive services) and nurses (who will provide services) on the types of services home visiting nurses should offer. The patients wanted "education on how to take care patients at home", "making arrangement to be admitted into hospital when need arises", "IV injection", "checking blood pressure", and "administering medications." On the other hand, nurses believed that they can offer all 16 types of services except "Controlling pain of patients", 4. For the question of "what types of patients are suitable for Home Health Care Program; " the physicians, the nurses and non-medical personnel all gave high score on the cases of "patients of chronic disease", "patients of old age", "terminal cases", and the "patients who require long-term stay in hospital". 5. On the question of who should control Home Health Care Program, only physicians proposed that it should be done through hospitals, while remaining three groups recommended that it should be done through public institutions such as public health center. 6. On the question of home health care fee, the respondents in all four groups believed that the most desireable way is to charge a fixed amount of visiting fee plus treatment service fee and cost of material. 7. In the case when the Home Health Care Program is to be operated through hospitals, it is recommended that a new section be created in the out-patient department for an exclusive handling of the services, instead of assigning it to an existing section. 8. For the qualification of the nurses for-home visiting, the majority of respondents recommended that they should be "registered nurses who have had clinical experiences and who have attended training courses for home health care". 9. On the question of if the program should be implemented; 74.0% of physicians, 87.5% of non-medical personnel, and 93.0% of nurses surveyed expressed positive support. 10. Among the respondents, 74.5% of -physicians, 81.3% of non-medical personnel and 90.9% of nurses said that they would refer patients' to home health care. 11. To the question addressed to patients if they would take advantage of home health care; 82.7% said they would if the fee is applicable to the Health Insurance, and 86.9% said they would follow advises of physicians in case they were decided for early discharge from hospitals. 12. While 93.5% of nurses surveyed had heard about the Home Health Care Program, only 38.6% of physicians surveyed, 50.9% of non-medical personnel, and 35.7% of patients surveyed had heard about the program. In view of above findings, the following measures are deemed prerequisite for an effective implementation of Home Health Care Program. 1. The fee for home health care to be included in the public health insurance. 2. Clearly define the types and scope of services to be offered in the Home Health Care Program. 3. Develop special programs for training nurses who will be assigned to the Home Health Care Program. 4. Train those nurses by consigning them at hospitals and educational institutions. 5. Government conducts publicity campaign toward the public and the hospitals so that the hospitals support the program and patients take advantage of them. 6. Systematic and effective publicity and educational programs for home heath care must be developed and exercises for the people of medical professions in hospitals as well as patients and their families. 7. Establish and operate pilot projects for home health care, to evaluate and refine their programs.

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The Intelligent Determination Model of Audience Emotion for Implementing Personalized Exhibition (개인화 전시 서비스 구현을 위한 지능형 관객 감정 판단 모형)

  • Jung, Min-Kyu;Kim, Jae-Kyeong
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.39-57
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    • 2012
  • Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

Application of Machine Learning Algorithm and Remote-sensed Data to Estimate Forest Gross Primary Production at Multi-sites Level (산림 총일차생산량 예측의 공간적 확장을 위한 인공위성 자료와 기계학습 알고리즘의 활용)

  • Lee, Bora;Kim, Eunsook;Lim, Jong-Hwan;Kang, Minseok;Kim, Joon
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1117-1132
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    • 2019
  • Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.