• Journal of Communications and Networks
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• 제15권3호
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• pp.283-291
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• 2013

In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3811-3815
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• 2022

Ni-63 is pure beta source which emits low energy beta particles. The Ni-63 sources were fabricated to develop the beta-voltaic battery which converts decay energy into electrical energy for power generation. Activity distribution of the source was important factor of power producibility of the beta-voltaic battery. Liquid scintillation counter widely used for measurement of low energy beta emitters was not suitable to measure activity distribution. In this study, we used the peeled-off Gafchromic™ EBT3 film to measure the activity distribution of the Ni-63 source. Absorbed dose was increased proportionally to the source activity and exposure duration. The low energy beta particles could transport the energy into the active layer without the polyester protective layer. Also, Activity distribution was measured by using the peeled-off EBT3 film. Two-dimensional dosimetric distribution was suitable to measure the activity distribution. To use the peeled-off EBT3 film is user-friendly and cost-effective method for quality assurance of the Ni-63 sources for the beta-voltaic battery.

• 한국환경복원기술학회지
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• 제11권6호
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• pp.91-103
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• 2008

The purpose of this study is to compare the satisfaction of the urban parks and to classify and assess the environmentally-friendly behaviors in the urban parks. For this purpose, the park user's behaviors and satisfactions were surveyed in 10 parks in Seoul and its suburb area. Parks are divided into 2 types, the walking-distance parks and the metropolitan parks, by time to reach, visit frequency and visit purpose. The park users are generally satisfied with the facilities, but not satisfied with some specific items, such as cultural facilities, accommodations for the handicapped, safety facilities and sports facilities. The environmentally-friendly behaviors are positively assessed in general, but the behavior of the natural experience was negatively assessed. The environmentally-friendly behaviors in the urban parks are classified into 2 factors; the experience factor and the activity factor. The parks are categorized into 3 types by these factors. For type I parks, the experience factor is dominant, but the activity factor is relatively low. For type II parks, the both factors are low and the parks are necessary to improve. And type III parks are positively assessed in the aspect of the environmentally-friendly behaviors, even though some park are necessary to complement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5344-5356
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• 2018

Nowadays with the help of Location-Based Social Networks (LBSNs), users of Point-of-Interest (POI) recommendation service in LBSNs are able to publish their geo-tagged information and physical locations in the form of sign-ups and share their experiences with friends on POI, which can help users to explore new areas and discover new points-of-interest, and promote advertisers to push mobile ads to target users. POI recommendation service in LBSNs is attracting more and more attention from all over the world. Due to the sparsity of users' activity history data set and the aggregation characteristics of sign-in area, conventional recommendation algorithms usually suffer from low accuracy. To address this problem, this paper proposes a new recommendation algorithm based on a novel Preference-Content-Region Model (PCRM). In this new algorithm, three kinds of information, that is, user's preferences, content of the Point-of-Interest and region of the user's activity are considered, helping users obtain ideal recommendation service everywhere. We demonstrate that our algorithm is more effective than existing algorithms through extensive experiments based on an open Eventbrite data set.

• 한국조경학회지
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• 제32권1호
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• pp.23-32
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• 2004

This study aims to examine constraints on visits to urban community parks and to find ways to elevate the efficient use of parks. To achieve this, the study relied on empirical study method and the descriptive method; additionally, present condition survey was performed with a user interview, on the assumption that a park visit is a form of leisure. As a result, the item of 'insufficient lighting facilities' shows the highest mean and the item of 'low quality of park' follows Previous research also revealed that the item of 'the lack of lighting facilities' is a major factor on user dissatisfaction, so a design and management program for night time users are fully researched and elaborately accomplished. Also, the high response of 'low quality of park' shows that the park supply policy in Korea focusses mainly on quantity so far, and it shows that user's dissatisfaction for park facilities becomes one of the major constraints of park visit. The factor analysis, on the object of 35 items except 2 items, appeared 5 factors: accessibility, inner discord, companion, family matters, park-itself-matters. Oneway Anova test showed that 4 factors except 'park-itself-matters' have reliable difference in constraint cognition by age and education. The visit constraint of 'park-itself-matters' did not appear different by any personal characteristics. Without regard to personal characteristics, it is regarded that this factor has the greatest effect upon park visits. In general, people who are disadvantaged strongly cognize constraints even in leisure such as a park visit, which is a simple and inexpensive leisure activity. Therefore, a park like a pocket park, which is small but located in a neighborhood, is more needed than a central park like a symbolic and huge park in every new city. Careful concern for night activity should be accomplished in the planning process.

• 디지털산업정보학회논문지
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• 제4권3호
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• pp.77-83
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• 2008

In this paper, CPLD low power technology mapping for reuse module design under the time constraint is proposed. Traditional high-level synthesis do not allow reuse of complex, realistic datapath component during the task of scheduling. On the other hand, the proposed algorithm is able to approach a productivity of the design the low power to reuse which given a library of user-defined datapath component and to share of resource sharing on the switching activity in a shared resource. Also, we are obtainable the optimal the scheduling result in experimental results of our using chaining and multi-cycling in the scheduling techniques. Low power circuit make using CPLD technology mapping algorithm for selection reuse module by scheduling.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1638-1641
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• 2004

Many walking stands, and assisting tools have been developed for the people with low-limb disability to prevent diseases from bedridden state and to help them walk again. But many of those equipments require user to have some physical strength or balancing ability. In our last research, we developed walking assist system for the people with lower-limb disability. With the system, user can be assisted by actuators, and do not have to worry about falling down. The system adapted the unique closed links structure with four servomotors, three PICs as controller, and four limit switches as HMI (human man interface). We confirmed the adaptability of the system by the experiment. In this research, Muscle Stiffness Sensor was tested as the advanced HMI for walking assist system, and confirmed the adaptability by the experiment. As Muscle Stiffness Sensor can attain the muscle activity, user can interface with any device he want to control. Experimental result with Muscle Stiffness sonsor showed that user could easily control the walking assist system as his will, just by changing his muscle strength.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1812-1824
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• 2019

The location and human activity are usually used as one of the important parameters to monitor the health status in healthcare devices. However, nearly all existing location and monitoring systems have the limitation of short-range communication and high power consumption. In this paper, we propose a new mechanism to collect and transmit monitoring information based on LoRa technology. The monitoring device with sensors can collect the real-time activity and location information and transmit them to the cloud server through LoRa gateway. The user can check all his history and current information through the specific designed mobile applications. Experiment was carried out to verify the communication, power consumption and monitoring performance of the entire system. Experimental results demonstrate that this system can collect monitoring and activity information accurately and provide the long rang coverage with low power consumption.