• Korea Journal of Hospital Management
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• v.27 no.3
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• pp.26-38
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• 2022

Purposes: We analyzed the profitability determinants of regional public hospitals during the entire period between 2010 and 2020 and the period before and after COVID-19. We intended to provide fundamental data for developing publicness evaluation index and task of establishing and expanding regional public hospitals. Methodology: The financial and non-financial information of the regional public hospitals were used as the main analysis data; The financial data was established by the Center for Public Healthcare Policy of National Medical Center, and the non-financial data by the Health Insurance Review and Assessment Service. T-test and regression analysis were used. Findings: The results can be summarized in two. First, the main determinants of profitability of the regional public hospitals were appeared to be the total asset turnover rate and the labor cost rate. Second, during the COVID-19 pandemic in the regional public hospitals, the number of sickbeds, the number of isolation rooms, the total asset turnover rate and the labor cost rate appeared to be the factor worsening the profitability. Practical Implication: The results of this study suggests that the management of the regional public hospitals is not aiming for the profit making, but it performs the functions as the community healthcare safety net such as controlling infectious diseases.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.886-889
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• 2008

Today, digital technology can be possible U-city, U-healthcare because network and wireless communication have developed very rapidly and widely. In this paper we implemented embedded server and Zigbee sensor boards. For the development, Implemented home server platform has a Intel PXA255 processor, web server, USB camera and TFT LCD. The other hand, Zigbee sensor boards are attached the AVR microprocessor and the several sensors to get the environment variables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2853-2873
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• 2013

Over the last few years, one of the most common purposes of smart homes is to provide human centric services in the domain of u-healthcare by analyzing inhabitants' daily living. Currently, the major challenges in activity recognition include the reliability of prediction of each classifier as they differ according to smart homes characteristics. Smart homes indicate variation in terms of performed activities, deployed sensors, environment settings, and inhabitants' characteristics. It is not possible that one classifier always performs better than all the other classifiers for every possible situation. This observation has motivated towards combining multiple classifiers to take advantage of their complementary performance for high accuracy. Therefore, in this paper, a method for activity recognition is proposed by optimizing the output of multiple classifiers with Genetic Algorithm (GA). Our proposed method combines the measurement level output of different classifiers for each activity class to make up the ensemble. For the evaluation of the proposed method, experiments are performed on three real datasets from CASAS smart home. The results show that our method systematically outperforms single classifier and traditional multiclass models. The significant improvement is achieved from 0.82 to 0.90 in the F-measures of recognized activities as compare to existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1052-1070
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• 2016

Wireless Body Area Networks (WBANs) have received a lot of attention as a promising technology for medical and healthcare applications. A WBAN should guarantee energy efficiency, data reliability, and low data latency because it uses tiny sensors that have limited energy and deals with medical data that needs to be timely and correctly transferred. To satisfy this requirement, many multi-radio multi-channel MAC protocols have been proposed, but these cannot be implemented on current off-the-shelf sensor nodes because they do not support multi-radio transceivers. Thus, recently single-radio multi-channel MAC protocols have been proposed; however, these methods are energy inefficient due to data duplication. This paper proposes a TDMA-based single-radio, multi-channel MAC protocol that uses the Unbalanced Star+Mesh topology to satisfy the requirements of WBANs. Our analytical analysis together experiments using real sensor nodes show that the proposed protocol outperforms existing methods in terms of energy efficiency, reliability, and low data latency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1805-1824
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• 2013

Recently, the use of wireless body area networks (WBAN) has been increasing rapidly in medical healthcare applications. WBANs consist of smart nodes that can be used to sense and transmit vital data such as heart rate, temperature and ECG from a human body to a medical centre. WBANs depend on limited resources such as energy and bandwidth. In order to utilise these resources efficiently, a very well organized medium access control (MAC) protocol must be considered. In this paper, a new, adaptive and energy-efficient MAC protocol, entitled isMAC, is proposed for WBANs. The proposed MAC is based on multi-channel communication and aims to prolong the network lifetime by effectively employing (i) a collision prevention mechanism, (ii) a coordinator node (WCN) selection algorithm and (iii) a transmission power adjustment approach. The isMAC protocol has been developed and modelled, by using OPNET Modeler simulation software. It is based on a networking scenario that requires especially high data rates such as ECG, for performance evaluation purposes. Packet delay, network throughput and energy consumption have been chosen as performance metrics. The comparison between the simulation results of isMAC and classical IEEE 802.15.4 (ZigBee) protocol shows that isMAC significantly outperforms IEEE 802.15.4 in terms of packet delay, throughput and energy consumption.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2339-2345
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• 2020

Radiation imaging systems consisting of a large number of channels greatly benefit from multiplexing methods to reduce the number of channels with minimizing the system complexity and development cost. In conventional pixelated radiation detector modules, such as anger logic, is used to reduce a large number of channels that transmit signals to a data acquisition system. However, these methods have limitations of electrical noise and distortion at the detector edge. To solve these problems, a multiplexing concept using a digital signal encoding technique based on a time delay method for signals from detectors was developed in this study. The digital encoding multiplexing (DEM) method was developed based on the time-over-threshold (ToT) method to provide more information including the activation time, position, and energy in one-bit line. This is the major advantage of the DEM method as compared with the traditional ToT method providing only energy information. The energy was measured and calibrated by the ToT method. The energy resolution and coincidence time resolution were observed as 16% and 2.4 ns, respectively, with DEM. The position was successfully distributed on each channel. This study demonstrated the feasibility that DEM was useful to reduce the number of detector channels.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.1010-1032
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• 2018

Recent advances in medical science have made people live longer, which has affected many aspects of life, such as caregiver burden, increasing cost of healthcare, increasing number of disabled and depressive disorder persons, and so on. Researchers are now focused on elderly living assistance services in smart home environments. In recent years, assisted living technologies have rapidly grown due to a faster growing aging society. Many smart devices are now interconnected within the home network environment and such a home setup supports collaborations between those devices based on the Internet of Things (IoT). One of the major challenges in providing elderly living assistance services is to consider each individual's requirements of different needs. In order to solve this, the virtualization of physical things, as well as the collaboration and composition of services provided by these physical things should be considered. In order to meet these challenges, Web of Objects (WoO) focuses on the implementation aspects of IoT to bring the assorted real world objects with the web applications. We proposed a semantic modelling technique for manual and semi-automated service composition. The aim of this work is to propose a framework to enable RESTful web services composition using semantic ontology for elderly living assistance services creation in WoO based smart home environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1518-1539
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• 2024

Artificial intelligence-enabled business models aim to improve decision-making, operational efficiency, innovation, and productivity. The presented systematic literature review is conducted to highlight elucidating the utilization of artificial intelligence (AI) methods and techniques within AI-enabled businesses, the significance and functions of AI-enabled organizational models and frameworks, and the design parameters employed in academic research studies within the AI-enabled business domain. We reviewed 39 empirical studies that were published between 2010 and 2023. The studies that were chosen are classified based on the artificial intelligence business technique, empirical research design, and SLR search protocol criteria. According to the findings, machine learning and artificial intelligence were reported as popular methods used for business process modelling in 19% of the studies. Healthcare was the most experimented business domain used for empirical evaluation in 28% of the primary research. The most common reason for using artificial intelligence in businesses was to improve business intelligence. 51% of main studies claimed to have been carried out as experiments. 53% of the research followed experimental guidelines and were repeatable. For the design of business process modelling, eighteen AI mythology were discovered, as well as seven types of AI modelling goals and principles for organisations. For AI-enabled business models, safety, security, and privacy are key concerns in society. The growth of AI is influencing novel forms of business.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.73-79
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• 2020

Due to the rapidly ageing population and low birth rates, most countries have faced with the problems of an ageing population. As a result, research into aging and the means to support an aging population has therefore become a priority for many governments around the world. Ambient Assisted Living(AAL) approach is the way to guarantee better life conditions for the aged and for monitoring their health conditions by the development of innovative technologies and services. AAL technologies can provide more safety for the elderly, offering emergency response mechanisms and fall detection solutions. Since the information transmitted in AAL systems is very personal, however, the security and privacy of such data are becoming important issues that must be dealt with. In this paper, we propose a Chameleon hash-based secure authentication protocol for AAL systems. The proposed authentication protocol not only supports several important security requirements needed by the AAL systems, but can also withstand various types of attacks. In addition, the security analysis results show that the proposed authentication protocol is more efficient and secure than the existing authentication protocols.