• Title/Summary/Keyword: Support performance

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A Methodology to Develop a Curriculum based on National Competency Standards - Focused on Methodology for Gap Analysis - (국가직무능력표준(NCS)에 근거한 조경분야 교육과정 개발 방법론 - 갭분석을 중심으로 -)

  • Byeon, Jae-Sang;Ahn, Seong-Ro;Shin, Sang-Hyun
    • Journal of the Korean Institute of Landscape Architecture
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    • v.43 no.1
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    • pp.40-53
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    • 2015
  • To train the manpower to meet the requirements of the industrial field, the introduction of the National Qualification Frameworks(hereinafter referred to as NQF) was determined in 2001 by National Competency Standards(hereinafter referred to as NCS) centrally of the Office for Government Policy Coordination. Also, for landscape architecture in the construction field, the "NCS -Landscape Architecture" pilot was developed in 2008 to be test operated for 3 years starting in 2009. Especially, as the 'realization of a competence-based society, not by educational background' was adopted as one of the major government projects in the Park Geun-Hye government(inaugurated in 2013) the NCS system was constructed on a nationwide scale as a detailed method for practicing this. However, in the case of the NCS developed by the nation, the ideal job performing abilities are specified, therefore there are weaknesses of not being able to reflect the actual operational problem differences in the student level between universities, problems of securing equipment and professors, and problems in the number of current curricula. For soft landing to practical curriculum, the process of clearly analyzing the gap between the current curriculum and the NCS must be preceded. Gap analysis is the initial stage methodology to reorganize the existing curriculum into NCS based curriculum, and based on the ability unit elements and performance standards for each NCS ability unit, the discrepancy between the existing curriculum within the department or the level of coincidence used a Likert scale of 1 to 5 to fill in and analyze. Thus, the universities wishing to operate NCS in the future measuring the level of coincidence and the gap between the current university curriculum and NCS can secure the basic tool to verify the applicability of NCS and the effectiveness of further development and operation. The advantages of reorganizing the curriculum through gap analysis are, first, that the government financial support project can be connected to provide quantitative index of the NCS adoption rate for each qualitative department, and, second, an objective standard is provided on the insufficiency or sufficiency when reorganizing to NCS based curriculum. In other words, when introducing in the subdivisions of the relevant NCS, the insufficient ability units and the ability unit elements can be extracted, and the supplementary matters for each ability unit element per existing subject can be extracted at the same time. There is an advantage providing directions for detailed class program and basic subject opening. The Ministry of Education and the Ministry of Employment and Labor must gather people from the industry to actively develop and supply the NCS standard a practical level to systematically reflect the requirements of the industrial field the educational training and qualification, and the universities wishing to apply NCS must reorganize the curriculum connecting work and qualification based on NCS. To enable this, the universities must consider the relevant industrial prospect and the relation between the faculty resources within the university and the local industry to clearly select the NCS subdivision to be applied. Afterwards, gap analysis must be used for the NCS based curriculum reorganization to establish the direction of the reorganization more objectively and rationally in order to participate in the process evaluation type qualification system efficiently.

NFC-based Smartwork Service Model Design (NFC 기반의 스마트워크 서비스 모델 설계)

  • Park, Arum;Kang, Min Su;Jun, Jungho;Lee, Kyoung Jun
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.157-175
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    • 2013
  • Since Korean government announced 'Smartwork promotion strategy' in 2010, Korean firms and government organizations have started to adopt smartwork. However, the smartwork has been implemented only in a few of large enterprises and government organizations rather than SMEs (small and medium enterprises). In USA, both Yahoo! and Best Buy have stopped their flexible work because of its reported low productivity and job loafing problems. In addition, according to the literature on smartwork, we could draw obstacles of smartwork adoption and categorize them into the three types: institutional, organizational, and technological. The first category of smartwork adoption obstacles, institutional, include the difficulties of smartwork performance evaluation metrics, the lack of readiness of organizational processes, limitation of smartwork types and models, lack of employee participation in smartwork adoption procedure, high cost of building smartwork system, and insufficiency of government support. The second category, organizational, includes limitation of the organization hierarchy, wrong perception of employees and employers, a difficulty in close collaboration, low productivity with remote coworkers, insufficient understanding on remote working, and lack of training about smartwork. The third category, technological, obstacles include security concern of mobile work, lack of specialized solution, and lack of adoption and operation know-how. To overcome the current problems of smartwork in reality and the reported obstacles in literature, we suggest a novel smartwork service model based on NFC(Near Field Communication). This paper suggests NFC-based Smartwork Service Model composed of NFC-based Smartworker networking service and NFC-based Smartwork space management service. NFC-based smartworker networking service is comprised of NFC-based communication/SNS service and NFC-based recruiting/job seeking service. NFC-based communication/SNS Service Model supplements the key shortcomings that existing smartwork service model has. By connecting to existing legacy system of a company through NFC tags and systems, the low productivity and the difficulty of collaboration and attendance management can be overcome since managers can get work processing information, work time information and work space information of employees and employees can do real-time communication with coworkers and get location information of coworkers. Shortly, this service model has features such as affordable system cost, provision of location-based information, and possibility of knowledge accumulation. NFC-based recruiting/job-seeking service provides new value by linking NFC tag service and sharing economy sites. This service model has features such as easiness of service attachment and removal, efficient space-based work provision, easy search of location-based recruiting/job-seeking information, and system flexibility. This service model combines advantages of sharing economy sites with the advantages of NFC. By cooperation with sharing economy sites, the model can provide recruiters with human resource who finds not only long-term works but also short-term works. Additionally, SMEs (Small Medium-sized Enterprises) can easily find job seeker by attaching NFC tags to any spaces at which human resource with qualification may be located. In short, this service model helps efficient human resource distribution by providing location of job hunters and job applicants. NFC-based smartwork space management service can promote smartwork by linking NFC tags attached to the work space and existing smartwork system. This service has features such as low cost, provision of indoor and outdoor location information, and customized service. In particular, this model can help small company adopt smartwork system because it is light-weight system and cost-effective compared to existing smartwork system. This paper proposes the scenarios of the service models, the roles and incentives of the participants, and the comparative analysis. The superiority of NFC-based smartwork service model is shown by comparing and analyzing the new service models and the existing service models. The service model can expand scope of enterprises and organizations that adopt smartwork and expand the scope of employees that take advantages of smartwork.

Predicting the Direction of the Stock Index by Using a Domain-Specific Sentiment Dictionary (주가지수 방향성 예측을 위한 주제지향 감성사전 구축 방안)

  • Yu, Eunji;Kim, Yoosin;Kim, Namgyu;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.95-110
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    • 2013
  • Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

Animal Infectious Diseases Prevention through Big Data and Deep Learning (빅데이터와 딥러닝을 활용한 동물 감염병 확산 차단)

  • Kim, Sung Hyun;Choi, Joon Ki;Kim, Jae Seok;Jang, Ah Reum;Lee, Jae Ho;Cha, Kyung Jin;Lee, Sang Won
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.137-154
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    • 2018
  • Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)

  • Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.163-177
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    • 2019
  • As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

Analysis of shopping website visit types and shopping pattern (쇼핑 웹사이트 탐색 유형과 방문 패턴 분석)

  • Choi, Kyungbin;Nam, Kihwan
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.85-107
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    • 2019
  • Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

Edge to Edge Model and Delay Performance Evaluation for Autonomous Driving (자율 주행을 위한 Edge to Edge 모델 및 지연 성능 평가)

  • Cho, Moon Ki;Bae, Kyoung Yul
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.191-207
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    • 2021
  • Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

A Study on Practical Curriculum Development of the Education for Love based on the Understanding of Psychoanalytic 'Desire of Subject' (정신분석학적 '욕망의 주체' 이해에 기초한 사랑의 교육 교육과정 개발)

  • Kim, Sun Ah
    • Journal of Christian Education in Korea
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    • v.68
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    • pp.77-112
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    • 2021
  • This study is based on the research of the first year, which is the National Research Foundation of Korea's R&D subject for middle-grade researchers. In this study, the practical curriculum development of the education for love - an according to the psychoanalytic perspectives of F. Dolto(1908-1988) - is suggested as follows. The first is 'the reconstruction of the directions of curriculum and its specific aims in accordance with such directions.' The reconstruction of the directions of curriculum aims at leading our future generation to live as a subject of desire through the mutual-communication of love. The second is 'the reconstruction of the tasks of curriculum and its specific contents in accordance with such tasks.' The reconstruction of the tasks of curriculum pursuit to help our future generation through the converting the education for love into the paradigm of desire of Agape to live as a subject of desire forming a whole personality and practicing the desire of Agape in daily life. as a source of desire. According to these aims, the reconstruction of directions of curriculum are presented as following: firstly, 'curriculum for the mutual-communication between subjects of love' and secondly, 'curriculum for the subject of desire'. The reconstruction of tasks of curriculum are like these: firstly, 'converting the education for love into the paradigm of desire of Agape', and secondly, 'forming a whole personality through the education for love'. Thus, with respect to two specific aims in accordance with the reconstruction of directions are suggested like these: Firstly, 'constructing a subject as a speaking existence' and secondly, 'realizing the subject as the autonomous source of desire'. In the two specific contents in accordance with the reconstruction of tasks are presented as following: Firstly, 'realizing the truth of the desire of Agape'.' Secondly, 'practicing the desire of Agape in daily life.' The third is 'the reconstruction of curriculum by life cycle' are suggested. They include the fetal life, infants and preschool children life, and childhood life. In further study, it is required to contain adolescent period. It will be useful to help them to recover their self-esteem with the experience of true love, especially, out-of-school young generation overcome negative perspectives and prejudice in the society, and challenges to their dreams and future through proper utilization of the study outcome. The outcome of this study, which presented practical curriculum development of the education for love based on the understanding of psychoanalytic 'desire of subject' can be used as basic teaching materials for our future generations. Furthermore, the results can be used as a resource for educating ministers and lay leaders in the religious world to build capabilities to heal their inner side as well as the society that is tainted with various forms of conflict. These include general conflicts, anger, pleasure and addiction, depression and suicide, violence and murder, etc. The study outcome can contribute to the prevention of antisocial incidents against humanity that have recently been occurring in our free-semester system implemented in all middle schools across the country to be operated effectively. For example, it is possible to provide the study results as lecture and teaching materials for 'character camp' (self-examination and self-esteem improvement training) and 'family healing camp' (solution of a communication gap between family members and love communication training), which help students participate in field trip activities and career exploration activities voluntarily, independently, and creatively. Ultimately, it can visibly present the convergent research performance by providing the study outcome as preliminary data for the development of lecture videos and materials including infant care and preschool education, parental education, family consultation education, and holistic healing education. Support from the religious world, including the central government and local governments, are urgently required in order for such educational possibilities to be fulfilled both in the society and the fields of church education and to be actively linked to follow-up studies.

Effect of the Community-Based Chronic Disease Management Service Using Information and Communication Technology (정보통신기술을 이용한 지역사회 기반 만성질환관리 서비스 효과 평가)

  • Eun Jin Park;Yun Su Lee;Tae Yon Kim;Seung Hee Yoo;Hye Ran Jin;Noor Afif Mahmudah;MinSu Ock;Tae-Yoon Hwang;Yeong Mi KIm;Jung Jeung Lee
    • Journal of agricultural medicine and community health
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    • v.49 no.3
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    • pp.257-270
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    • 2024
  • Objective: This study aimed to empirically evaluate the effectiveness of chronic disease management services utilizing ICT for patients with chronic illnesses. Methods: From May to December, 2023, 452 people who were diagnosed with hypertension and diabetes at 9 participating public health centers were provided with customized health care services for 24 weeks, and 15 performance indicators were analyzed to evaluate their effectiveness. Results: Health behavior indicators and health risk factors decreased before and after participation in the project, blood pressure control rate, hypertension and diabetes management rate, medication compliance, weight, BMI, BP, WC, FBG, and HDL-cholesterol improved(p<0.001). Service factors that influence the improvement of health behaviors included the number of activity monitor transmissions(p=0.049), confirmed concentrated consultations on physical activity(p=0.003) and nutrition(p=0.005), and the adherence to medication missions for hypertension(p=0.020). As for service factors influencing chronic disease management, the improvement in blood pressure regulation rate was due to the number of times the blood pressure monitor was linked(p=0.004), and the number of confirmed intensive consultations on physical activity(p=0.026), and nutrition(p=0.049); the improvement in hypertension control rate was due to the number of times the activity monitor and blood pressure monitor were linked(p<0.001), and the number of hypertension medication missions carried out (p=0.004); and the improvement in diabetes control rate was due to the number of times the blood pressure monitor(p=0.022) and blood sugar system were linked(p=0.017). Conclusion: Although this study has limitations as a comparative study before and after the service, it has proved that chronic disease management using ICT has a positive effect on improvement of health behavior indicator, reduction of health risk factors, hypertension, diabetes management index, weight, BMI, TG, BP, FBG improvement.

A Study for Improvement of Nursing Service Administration (병원 간호행정 개선을 위한 연구)

  • 박정호
    • Journal of Korean Academy of Nursing
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    • v.3 no.1
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    • pp.13-40
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    • 1972
  • Much has teed changed in the field of hospital administration in the It wake of the rapid development of sciences, techniques ana systematic hospital management. However, we still have a long way to go in organization, in the quality of hospital employees and hospital equipment and facilities, and in financial support in order to achieve proper hospital management. The above factors greatly effect the ability of hospitals to fulfill their obligation in patient care and nursing services. The purpose of this study is to determine the optimal methods of standardization and quality nursing so as to improve present nursing services through investigations and analyses of various problems concerning nursing administration. This study has been undertaken during the six month period from October 1971 to March 1972. The 41 comprehensive hospitals have been selected iron amongst the 139 in the whole country. These have been categorized according-to the specific purposes of their establishment, such as 7 university hospitals, 18 national or public hospitals, 12 religious hospitals and 4 enterprise ones. The following conclusions have been acquired thus far from information obtained through interviews with nursing directors who are in charge of the nursing administration in each hospital, and further investigations concerning the purposes of establishment, the organization, personnel arrangements, working conditions, practices of service, and budgets of the nursing service department. 1. The nursing administration along with its activities in this country has been uncritical1y adopted from that of the developed countries. It is necessary for us to re-establish a new medical and nursing system which is adequate for our social environments through continuous study and research. 2. The survey shows that the 7 university hospitals were chiefly concerned with education, medical care and research; the 18 national or public hospitals with medical care, public health and charity work; the 2 religious hospitals with medical care, charity and missionary works; and the 4 enterprise hospitals with public health, medical care and charity works. In general, the main purposes of the hospitals were those of charity organizations in the pursuit of medical care, education and public benefits. 3. The survey shows that in general hospital facilities rate 64 per cent and medical care 60 per-cent against a 100 per cent optimum basis in accordance with the medical treatment law and approved criteria for training hospitals. In these respects, university hospitals have achieved the highest standards, followed by religious ones, enterprise ones, and national or public ones in that order. 4. The ages of nursing directors range from 30 to 50. The level of education achieved by most of the directors is that of graduation from a nursing technical high school and a three year nursing junior college; a very few have graduated from college or have taken graduate courses. 5. As for the career tenure of nurses in the hospitals: one-third of the nurses, or 38 per cent, have worked less than one year; those in the category of one year to two represent 24 pet cent. This means that a total of 62 per cent of the career nurses have been practicing their profession for less than two years. Career nurses with over 5 years experience number only 16 per cent: therefore the efficiency of nursing services has been rated very low. 6. As for the standard of education of the nurses: 62 per cent of them have taken a three year course of nursing in junior colleges, and 22 per cent in nursing technical high schools. College graduate nurses come up to only 15 per cent; and those with graduate course only 0.4 per cent. This indicates that most of the nurses are front nursing technical high schools and three year nursing junior colleges. Accordingly, it is advisable that nursing services be divided according to their functions, such as professional, technical nurses and nurse's aides. 7. The survey also shows that the purpose of nursing service administration in the hospitals has been regulated in writing in 74 per cent of the hospitals and not regulated in writing in 26 per cent of the hospitals. The general purposes of nursing are as follows: patient care, assistance in medical care and education. The main purpose of these nursing services is to establish proper operational and personnel management which focus on in-service education. 8. The nursing service departments belong to the medical departments in almost 60 per cent of the hospitals. Even though the nursing service department is formally separated, about 24 per cent of the hospitals regard it as a functional unit in the medical department. Only 5 per cent of the hospitals keep the department as a separate one. To the contrary, approximately 12 per cent of the hospitals have not established a nursing service department at all but surbodinate it to the other department. In this respect, it is required that a new hospital organization be made to acknowledge the independent function of the nursing department. In 76 per cent of the hospitals they have advisory committees under the nursing department, such as a dormitory self·regulating committee, an in-service education committee and a nursing procedure and policy committee. 9. Personnel arrangement and working conditions of nurses 1) The ratio of nurses to patients is as follows: In university hospitals, 1 to 2.9 for hospitalized patients and 1 to 4.0 for out-patients; in religious hospitals, 1 to 2.3 for hospitalized patients and 1 to 5.4 for out-patients. Grouped together this indicates that one nurse covers 2.2 hospitalized patients and 4.3 out-patients on a daily basis. The current medical treatment law stipulates that one nurse should care for 2.5 hospitalized patients or 30.0 out-patients. Therefore the statistics indicate that nursing services are being peformed with an insufficient number of nurses to cover out-patients. The current law concerns the minimum number of nurses and disregards the required number of nurses for operation rooms, recovery rooms, delivery rooms, new-born baby rooms, central supply rooms and emergency rooms. Accordingly, tile medical treatment law has been requested to be amended. 2) The ratio of doctors to nurses: In university hospitals, the ratio is 1 to 1.1; in national of public hospitals, 1 to 0.8; in religious hospitals 1 to 0.5; and in private hospitals 1 to 0.7. The average ratio is 1 to 0.8; generally the ideal ratio is 3 to 1. Since the number of doctors working in hospitals has been recently increasing, the nursing services have consequently teen overloaded, sacrificing the services to the patients. 3) The ratio of nurses to clerical staff is 1 to 0.4. However, the ideal ratio is 5 to 1, that is, 1 to 0.2. This means that clerical personnel far outnumber the nursing staff. 4) The ratio of nurses to nurse's-aides; The average 2.5 to 1 indicates that most of the nursing service are delegated to nurse's-aides owing to the shortage of registered nurses. This is the main cause of the deterioration in the quality of nursing services. It is a real problem in the guest for better nursing services that certain hospitals employ a disproportionate number of nurse's-aides in order to meet financial requirements. 5) As for the working conditions, most of hospitals employ a three-shift day with 8 hours of duty each. However, certain hospitals still use two shifts a day. 6) As for the working environment, most of the hospitals lack welfare and hygienic facilities. 7) The salary basis is the highest in the private university hospitals, with enterprise hospitals next and religious hospitals and national or public ones lowest. 8) Method of employment is made through paper screening, and further that the appointment of nurses is conditional upon the favorable opinion of the nursing directors. 9) The unemployment ratio for one year in 1971 averaged 29 per cent. The reasons for unemployment indicate that the highest is because of marriage up to 40 per cent, and next is because of overseas employment. This high unemployment ratio further causes the deterioration of efficiency in nursing services and supplementary activities. The hospital authorities concerned should take this matter into a jeep consideration in order to reduce unemployment. 10) The importance of in-service education is well recognized and established. 1% has been noted that on the-job nurses. training has been most active, with nursing directors taking charge of the orientation programs of newly employed nurses. However, it is most necessary that a comprehensive study be made of instructors, contents and methods of education with a separate section for in-service education. 10. Nursing services'activities 1) Division of services and job descriptions are urgently required. 81 per rent of the hospitals keep written regulations of services in accordance with nursing service manuals. 19 per cent of the hospitals do not keep written regulations. Most of hospitals delegate to the nursing directors or certain supervisors the power of stipulating service regulations. In 21 per cent of the total hospitals they have policy committees, standardization committees and advisory committees to proceed with the stipulation of regulations. 2) Approximately 81 per cent of the hospitals have service channels in which directors, supervisors, head nurses and staff nurses perform their appropriate services according to the service plans and make up the service reports. In approximately 19 per cent of the hospitals the staff perform their nursing services without utilizing the above channels. 3) In the performance of nursing services, a ward manual is considered the most important one to be utilized in about 32 percent of hospitals. 25 per cent of hospitals indicate they use a kardex; 17 per cent use ward-rounding, and others take advantage of work sheets or coordination with other departments through conferences. 4) In about 78 per cent of hospitals they have records which indicate the status of personnel, and in 22 per cent they have not. 5) It has been advised that morale among nurses may be increased, ensuring more efficient services, by their being able to exchange opinions and views with each other. 6) The satisfactory performance of nursing services rely on the following factors to the degree indicated: approximately 32 per cent to the systematic nursing activities and services; 27 per cent to the head nurses ability for nursing diagnosis; 22 per cent to an effective supervisory system; 16 per cent to the hospital facilities and proper supply, and 3 per cent to effective in·service education. This means that nurses, supervisors, head nurses and directors play the most important roles in the performance of nursing services. 11. About 87 per cent of the hospitals do not have separate budgets for their nursing departments, and only 13 per cent of the hospitals have separate budgets. It is recommended that the planning and execution of the nursing administration be delegated to the pertinent administrators in order to bring about improved proved performances and activities in nursing services.

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