• Journal of The Korea Institute of Healthcare Architecture
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• v.11 no.1
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• pp.15-22
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• 2005

Healthcare design has been considered as one of the most complex design types. In this study, healthcare design complexity is analysed by the following categories: (1) function; (2) medical technology; (3) scientific knowledge; (4) aesthetics; and (5) interest group complexity. The central questions here are: (1) What is the impact of specialized knowledge on the professional practice; and (2) What are the relationships between design complexity and specialized knowledge. To answer these questions, this study utilizes two approaches, including mail-out questionnaires survey and in-person and focus group interviews. This study found that healthcare design architects emphasize the technical component of specialized healthcare design knowledge. Thus they perceive that architectural research, as a tool to increase specialized healthcare design knowledge, is beneficial to solve the technical components including medical technology and functional problems. In the professional practice, however, architectural research is hardly conducted due mainly to the lack of money and time for it. Different perceptions regarding healthcare design complexity and architectural research among the firms exist, depending on the firm size. These results imply that the knowledge management strategy of large firms can be more efficient to the organizational growth than the small firms.

• Journal of The Korea Institute of Healthcare Architecture
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• v.16 no.2
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• pp.47-54
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• 2010

This paper is a longitudinal study, comparing survey results between two time periods. A previous survey was conducted in 1999. After 10 years of the first survey, the second survey was conducted while utilizing the same questionnaire. A list of membership of Korea Institute of Heallthcare Architecture was used as a sampling frame. At the first survey in 1999, questionnaires of 27.3 percentage were returned, and 15.5 percentage in the 2008 survey. Healthcare design is one of the highly specialized design types in architecture. In addition, it is demanded highly specialized knowledge to solve healthcare design problems. As a professional service firm(PSF), architectural firm utilizes knowledge assets to provide design service to clients. Specialized knowledge in question is one of the core assets of PSF. The knowledge generates competitive advantages and plays an effective role as a marketing tool for PSF. However, empirical studies dealing with the knowledge characteristics of specialized design(healthcare) firms were hardly found. Thus, this study aims to trace the professional architects' perception of knowledge demands for task performance and architectural knowledge assets. The results can be used as a reference when a specialized firm in healthcare design initiates to build knowledge assets in it.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.33-40
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• 2016

Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.66-71
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• 2021

Recent healthcare environments have characteristics of expanding the scope of healthcare-impacting healthcare, complexity resulting from diversification of components, and accelerating the pace of change. Drugs are used for the prevention, mitigation, and treatment of diseases, so they can inevitably cause harm, while they have efficacy and effectiveness, which are key elements of health recovery. Therefore, many countries regulate permits for safe and effective medicines, and also designate essential drugs directly related to life as pay targets and guarantee health insurance. Especially Pharmacist relying on manpower for composition medicine is liable for mal-manufacture due to combination of toxic medical substances or other chemical usage. In this paper, we focus on using Kiosk and Optical Character Recognition (OCR) for automated pharmacy to level up medical service and create labor friendly environment for pharmacist themselves through maintenance of prescription data and automated manufacturing solution. Presentation of drug substances and precautions will lead to efficient drug prescription and prevent misuse of information while auto manufacturing system efficiently maintain labor force and raise patient satisfaction level by reduction of waiting time.

• Journal of IKEEE
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• v.25 no.1
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• pp.212-217
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• 2021

Premature contraction arrhythmia is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Most of arrhythmia clasification methods have been developed with the primary objective of the high detection performance without taking into account the computational complexity. Also, personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Therefore it is necessary to design efficient method that classifies arrhythmia by analyzing the persons's physical condition and decreases computational cost by accurately detecting minimal feature point based on only QRS features. We propose method for personalized specific classification of premature contraction arrhythmia based on QRS features in smart healthcare environments. For this purpose, we detected R wave through the preprocessing method and SOM and selected abnormal signal sets.. Also, we developed algorithm to classify premature contraction arrhythmia using QRS pattern, RR interval, threshold for amplitude of R wave. The performance of R wave detection, Premature ventricular contraction classification is evaluated by using of MIT-BIH arrhythmia database that included over 30 PVC(Premature Ventricular Contraction) and PAC(Premature Atrial Contraction). The achieved scores indicate the average of 98.24% in R wave detection and the rate of 97.31% in Premature ventricular contraction classification.

• Nutrition Research and Practice
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• v.16 no.6
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• pp.801-812
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• 2022

BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1680-1691
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• 2009

To improve the quality of healthcare and build up the health delivery system, electronic health record system is important for healthcare institutions providing health services. However, the systems currently operated in domestic healthcare institutions use independent software interface with distributed environment for data search and process. Therefore, it raises an additional expense to buy or develop each interface module when there is a link to new system and the problem of complexity. To solve these problems, this study implemented the service oriented architecture basis for home nursing service and carried out an assessment. The study defined the process modeling and business requirements based on the scenario of service and drew 17 suitable services based on five verification items for service design. To draw the final service, seven services were selected by service litmus test (SLT). The study found that, by the improvement of business process for healthcare service support department, SOA based information system has an effect of time reduction of patient processing time. In conclusion, to enable the hospital information system to cope with various demands of healthcare consumers, it is necessary to consider the application of SOA technology which has excellent interoperability, reusability and maintenance.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.683-688
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• 2011

The wireless sensor network (WSN) is well known for an enabling technology for the ubiquitous environment such as real-time surveillance system, habitat monitoring, home automation and healthcare applications. However, the WSN featuring wireless communication through air, a resource constraints device and irregular network topology, is threatened by malicious nodes such as eavesdropping, forgery, illegal modification or denial of services. For this reason, security in the WSN is key factor for utilizing the sensor network into the commercial way. There is a series of symmetric cryptography proposed by laboratory or industry for a long time. Among of them, recently proposed HUMMINGBIRD algorithm, motivated by the design of the well-known Enigma machine, is much more suitable to resource constrained devices, including smart card, sensor node and RFID tags in terms of computational complexity and block size. It also provides resistance to the most common attacks such as linear and differential cryptanalysis. In this paper, we implements ultra-lightweight cryptography, HUMMINGBIRD algorithm into the resource constrained device, sensor node as a perfectly customized design of sensor node.

• Journal of The Korea Institute of Healthcare Architecture
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• v.24 no.1
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• pp.25-32
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• 2018

Purpose: This study was conducted to figure out the cognitive characteristics of the elderly living in apartment complex in order to construct basic data for the design of sustainable and age friendly apartment area. Methods: Cognitive map was used to identify and analyze the elderly residents' status of residential environment cognitions. The elderly living in Gongreung-dong apartment was randomly interviewed outdoor area and requested to draw cognitive maps on their living environment. 26 valid cognitive maps collected were analyzed, classified into two different types: Line type and Dot type. The average age, cognitive distance, length of residence, number of elements in the map(complexity) were then compared by Line and Dot type, as well as by gender. Correlations among variables also were analysed. Results: Males showed a tendency to draw dot types, which means they are place-centered, and females drew line types more than males, which means they are way-centered. The average cognitive distance of male group was greater than that of female group. As the age went up, the number of perceived place and the cognitive distance decreased. Oder people tended to draw line types rather than dot types. As the cognitive distance was longer, the perceived place and the number of lines increased. Implications: The age was more related to the recognition of the residential environment. The younger the residents were, the more they recognized the elements. The points that were represented by dots in the cognitive maps are places for memories for the individuals. Creating more memorable spaces will affect the cognition of residents on living environment. It is better to improve the cognitive environments before cognitive abilities of residents decrease.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.3-12
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• 2015

Recently, various studies have been attempted to provide a biological information monitoring service through integrating with the web service. The medical information transmission standard ISO/IEEE 11073 PHD defines the optimized exchange protocol ISO/IEEE 11073-20601 based on the No-IP to exchange the biometric information between the ISO/IEEE 11073 agent and the manager. It's system structure based on the No-IP using ISO/IEEE 11073-20601 is not suitable for providing a remote biological information monitoring services. That is because it is difficult to provide to control and manage the biological information measurement devices, which have installed IP protocol stack at the remote. Furthermore, ACSE and CMDISE in ISO/IEEE 11073-20601 are not suitable to provide U-healthcare services based on IoT because they are complicated and difficult to implement it caused by the structural complexity. In order to solve the problems, in this paper, we propose the biological information monitoring architecture based on ISO/IEEE 11073 DIM/REST of IoT environment to provide the biological information monitoring service based on IoT. To do this, we designed biological information monitoring system architecture based on IoT and the message exchange protocol of ISO/IEEE 11073 DIM/REST between the ISO/IEEE 11073 agent and the ISO/IEEE 11073 manager. In order to verify the realistic possibility of the proposed system architecture, we developed the service prototype.