• Journal of the Korea Safety Management & Science
• /
• v.13 no.2
• /
• pp.147-155
• /
• 2011

For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system based on the active RFID is developed to satisfy such a demand. The performance of the developed system is tested and verified through various experiments. Furthermore the feasibility test of the active RFID tag is performed to verify whether it can be used as a location-based occupancy sensor. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

• Journal of Korea Multimedia Society
• /
• v.11 no.12
• /
• pp.1697-1705
• /
• 2008

Several studies made for wireless mesh networks aim to optimize the capacity for wireless networks. Aside from protocol improvements, researches were also done on the physical layer particularly on modulation techniques and antenna efficiency schemes. This paper is concerned with the capacity improvements derived from using spatial diversity with smart adaptive array antennas. The use of spatial diversity, which has been widely proposed for use in cellular networks in order to lessen frequency re-use, can be used in mesh networks both to minimize co-channel interference (CCI) and enable multiple transmissions. This paper aims to study the capacity region and bounds in using smart antennas for single-channel multi-radio systems in relation to the number of spatial diversity or sectors as defined by the beam angle $\beta$.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.4
• /
• pp.117-123
• /
• 2012

For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system using the active RFID is developed to satisfy such a demand based on the results of previous research. First of all the design considerations and functions of the system are introduced. In sequence the functions of the system is presented, and then the performance of the developed system is tested and verified through various field tests. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

• International journal of advanced smart convergence
• /
• v.8 no.3
• /
• pp.87-94
• /
• 2019

IoT-based services are being released in accordance with the aging population and the demand for well-being pursuit needs. In addition to medical device companies, companies with ideas ranging from global ICT companies to startup companies are accelerating their market entry. The areas where these services are most commonly applied are health/medical, life/safety, city/energy, automotive and transportation. Furthermore, by expanding IoT technology convergence into the area of life care services, it contributes greatly to the development of service models in the public sector. It also provides an important opportunity for IoT-related companies to open up new markets. By addressing the problems of life care services that are still insufficient. We are providing opportunities to pursue the common interests of both users and workers and improve the quality of life. In order to establish IoT-based digital life care services, it is necessary to develop convergence technologies using cloud computing systems, big data analytics, medical information, and smart healthcare infrastructure.

• Nuclear Engineering and Technology
• /
• v.53 no.11
• /
• pp.3675-3684
• /
• 2021

Human reliability analysis (HRA) is a proactive approach to model and evaluate human systematic errors, and has been extensively applied in various complicated systems. Dependence assessment among human errors plays a key role in the HRA, which relies heavily on the knowledge and experience of experts in real-world cases. Moreover, there are ofthen different types of uncertainty when experts use linguistic labels to evaluate the dependencies between human failure events. In this context, this paper aims to develop a new method based on linguistic hesitant fuzzy sets and the technique for human error rate prediction (THERP) technique to manage the dependence in HRA. This method handles the linguistic assessments given by experts according to the linguistic hesitant fuzzy sets, determines the weights of influential factors by an extended best-worst method, and confirms the degree of dependence between successive actions based on the THERP method. Finally, the effectiveness and practicality of the presented linguistic hesitant fuzzy THERP method are demonstrated through an empirical healthcare dependence analysis.

• Asian Journal of Innovation and Policy
• /
• v.12 no.2
• /
• pp.216-228
• /
• 2023

Expectations and demands for the paradigm of healthcare systems are changing in response to changes in the characteristics of population properties and industrial structures; therefore, it is time to prepare for the career diversification of nursing students who have mainly entered the clinical field. The study tested the pathway of financial literacy on the relationship between entrepreneurship and nursing start-up attitude among nursing students. We obtained data from 177 South Korean nursing students through email and mobile phone. The analysis of the mediating effect was performed by hierarchical multiple regression. The SPSS WIN program was adopted. Entrepreneurship and financial literacy of subjects had a significantly positive effect on nursing start-up attitudes. Financial literacy indirectly affected the relationship between nursing students' entrepreneurship and nursing start-up attitude, and significance was verified by Process Macro. Financial literacy can mediate between entrepreneurship and nursing start-up attitudes. These factors will provide an important basis for nursing students to grow into talented people with business capabilities. Nursing education should strengthen the foundation that promotes business competence in nursing students.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.8
• /
• pp.3852-3864
• /
• 2016

Patients' health data is very sensitive and the access to individual's health data should be strictly restricted. However, many data consumers may need to use the aggregated health data. For example, the insurance companies needs to use this data to setup the premium level for health insurances. Therefore, privacy-preserving data aggregation solutions for health data have both theoretical importance and application potentials. In this paper, we propose a privacy-preserving health data aggregation scheme using differential privacy. In our scheme, patients' health data are aggregated by the local healthcare center before it is used by data comsumers, and this prevents individual's data from being leaked. Moreover, compared with the existing schemes in the literature, our work enjoys two additional benefits: 1) it not only resists many well known attacks in the open wireless networks, but also achieves the resilience against the human-factor-aware differential aggregation attack; 2) no trusted third party is employed in our proposed scheme, hence it achieves the robustness property and it does not suffer the single point failure problem.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.6
• /
• pp.2767-2780
• /
• 2016

Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.

• Journal of Information Processing Systems
• /
• v.9 no.1
• /
• pp.1-30
• /
• 2013

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.654-656
• /
• 2015

In today's world a monitoring system for managing obesity is very important in accordance with the trend of increasing obesity all through out the world. Most of the monitoring systems available today are quite basic and it simply calculate's only the BMI figures and the weight. Because it shows only basic information, this kind of system is not quite efficiently or effective. In this paper, our research concludes that there is a scop for a more efficient BMI system and we have designated a web-based monitoring system that recommends not just weight and BMI but also detailed graphs and recommends equipments in accordance with the users BMI level.