• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of The Korea Institute of Healthcare Architecture
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• v.13 no.2
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• pp.27-36
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• 2007

Recently, hospital patients experience anxiety, confusion, and stress about wayfinding as the spacial layout and treatment circulatory system of hospitals have become complicated due to their oversized and complex structure. As part of finding a solution to the problem, this study seeks to examine what are the essential elements of the wayfinding planning of O.P.D. in general hospitals, to develop the model of wayfinding, and to suggest the methods of improving the wayfinding system. The research methods of this study adopted were literature review in wayfinding cognition, plan analysis of ten general hospitals, space analysis of these hospitals through space syntax, analysis of the system of visual-perceptual information through a field study, and analysis of surveys and follow-up surveys conducted to support the results. Based on these results, the proposals for finding decision points, providing the information, and developing a model planning are listed as follows. 1) The comprehensive understanding of O.P.D. spacial layout and the visual-perceptual information system is necessary to find the essential elements of wayfinding. 2) The decision points are found through the full understanding of spacial functions, circulation systems, and facility configuration, considering the spacial layout, the bound of the visual-perceptual information system, and the circulatory system. Furthermore, the information decision points could be confined by space syntax. 3) The checklist and color compound & color codes, developed through the planning of signage system and color system could be applied to the methods of providing the information. 4) The planning of wayfinding system according to the whole process of practices for outpatients was mentioned above. The system of visual-perceptual information developed through the process of this study should be integrated in the spacial layout of the whole O.P.D.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.226-232
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• 2018

The rapid pace of growth in internet usage and rich mobile applications and with the advantage of incredible usage of internet enabled mobile devices the Green Mobile Crowd Computing will be the suitable area to research combining with cloud services architecture. Our proposed Framework will deploy the eHealth among various health care sectors and pave a way to create a Green Mobile Application to provide a better and secured way to access the Products/ Information/ Knowledge, eHealth services, experts / doctors globally. This green mobile crowd computing and cloud architecture for healthcare information systems are expected to lower costs, improve efficiency and reduce error by also providing better consumer care and service with great transparency to the patient universally in the field of medical health information technology. Here we introduced novel architecture to use of cloud services with crowd sourcing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.479-482
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• 2022

Recently, various artificial intelligence technologies are being applied to smart factory, finance, healthcare, and so on. When handling data requiring protection of privacy, distributed learning techniques are used. For distribution of information with privacy protection, encoding private information is required. Minimal codes has been used in such a secret-sharing scheme. In this paper, we explain the relationship between the characteristics of the minimal codes for application in distributed systems. We briefly deals with previously known construction methods, and presents extension methods for minimal codes. The new codes provide flexibility in distribution of private information. Furthermore, we discuss application scenarios for the extended codes.

• The Journal of Information Systems
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• v.19 no.4
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• pp.51-63
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• 2010

U-City applies ubiquitous information technologies such as RFID, GPS, USN to various components of city functions and services. The concept of U-City was popularized especially in Korea and currently more than 40 projects have been carrying out all over country. U-City incorporates advanced information communication technologies into ubiquitous information services to provide better quality of life. The purpose of this study is to analyze preferences for the U-City services by surveying experts in U-City developing companies. This study employs Analytic Hierarchy Process which is very useful tool for performing multi-criteria decision making. Total of 28 responses were used in the analysis. The results indicated that the first 7 most preferred items were from transportation and safety area and environment and healthcare area and 4 out of 6 items in transportation and safety area were ranked among them. It implies that respondents consider countering anxiety caused by congested traffic, natural disasters, crimes, etc most important aspect that U-City should deal with. On the other hand, U-Port, U-Convention, U-Logistics, U-Public Administration and U-City Portal were listed as the least preferred services.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.20-29
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• 2013

Medical errors such as adverse drug event, improper transfusion, wrong-site surgery, mistaken patient identity and so on commonly occur at health care practice. Information technology, like Drug Utilization Review(DUR) system which reviews, analyzes, and interprets medication data when prescribing, can play a key role in reducing such medical errors and improving patient safety. Korean Government has guided all hospitals to implement concurrent DUR(cDUR) system, which is the first case worldwide in that all healthcare providers have to use cDUR system when prescribing. This paper introduced a case study that a tertiary hospital has integrated the cDUR system into its comprehensive Hospital Information System(HIS) and analyzed the whole prescription data during a week right after adoption of cDUR system. Considering technical strength and weakness, the cDUR system was integrated into the HIS, using Broker Servers for minimizing doctors' anxiety. As the quantitative analysis of the whole prescription data, DUR conflict events, which mainly included duplicate medications and contra-indicated drug interactions for outpatients, were 2.77%. Although only 0.7% is for the contra-indicated drug interactions, it will be greatly devoted to achieve the purpose of DUR such as improving patient safety.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.269-276
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• 2013

Information and communication technology (ICT) is a promising solution for mitigating road traffic congestion. ICT allows road users and vehicles to be managed based on real-time road status information. In Tanzania, traffic congestion causes losses of TZS 655 billion per year. The main objective of this study was to develop an optimal approach for integrating real-time road information (RRI) to mitigate traffic congestion. Our research survey focused on three cities that are highly affected by traffic congestion, i.e., Arusha, Mwanza, and Dar es Salaam. The results showed that ICT is not yet utilized fully to solve road traffic congestion. Thus, we established a possible approach for Tanzania based on an analysis of road traffic data provided by organizations responsible for road traffic management and road users. Furthermore, we evaluated the available road information management techniques to test their suitability for use in Tanzania. Using the floating car data technique, fuzzy logic was implemented for real-time traffic level detection and decision making. Based on this solution, we propose a RRI system architecture, which considers the effective utilization of readily available communication technology in Tanzania.

• Management & Information Systems Review
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• v.34 no.4
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• pp.67-81
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• 2015

The purpose of this study was to evaluate the effect of this factor on the macroeconomic variables for the healthcare industry market. First, the government bond interest rates and the exchange rate is the cause variable of drug industry index. Drug industry index is a mutual influence between the Call interest rate. Second, the medical equipment index haver mutual cause variable such as call rate index, government bond interest rates, and exchange rate. A current account balance variable is the cause variable of drug industry index. Third, the drug industry index has a negative relationship with a Call interest rate and an exchange rate. but it has a positive relationship with a government bond interest rates. the medical equipment index has a negative relationship with an exchange rate. but it has a positive relationship with a government bond interest rates.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.10
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• pp.1149-1156
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• 2012

In this study, we proposed the most efficient driving posture based on the analysis of quantitative muscular strength and fatigue degree according to posture. Since driving include complicated actions required by a variety of ability and cause by extremes concentration or strain, drivers tend to feel tired easily. However, drivers can't recognize the fatigue degree by themselves. Moreover, the method for measuring the quantitative fatigue degree exactly is quite difficult to be secured. 9 professional bus drivers were participated. We analyzed the quantitative legs' muscular strength when operating each pedal. And then we also analyzed the muscular strength and muscular fatigue degree according to driving pattern during bus driving. Therefore, we suggested the most efficient driving posture.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.69-84
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• 2020

This study is conducted to improve the quality of healthcare services responding to COVID-19 by applying the public service quality management framework that is developed from ISO18091:2019 by the Ministry of the Interior and Safety of South Korea. The COVID-19 pandemic has been impacting the world since early 2020, and now in November 2020, it still has not been eliminated. The Korean medical institutions were able to prevent the spread of COVID-19 by agile test and strict cohort isolation. As a result, the so-called K-medical defense has achieved a positive reputation from around the world. In this study, we check and evaluate the current status of the COVID-19 response targeting some Korean hospitals by applying a quality control checklist based on the public service quality management framework. Status of 7 categories are analyzed based on the interview with 3 medical institutions. We also suggest improvements for better medical service quality in case of COVID-19 being prolonged.