• Journal of the Korean Society of Propulsion Engineers
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• v.3 no.2
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• pp.1-9
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• 1999

Applicability of the pressure gradient method which is formulated based on pressure gradient is verified against turbulent flow analysis. In the pressure gradient method, pressure gradient instead of pressure itself is obtained using continuity constraint. Since correct pressure gradient is found only when mass conservation is satisfied, pressure gradient method can reflect physics of flow field properly The pressure gradient method is formulated with semi-staggered grid system which locates each primitive variables on the same grid point but evaluates pressure gradient in-between. This grid system ensures easy programming and reflection of correct physics in analysis. For verifying applicability of this method, the pressure gradient method is applied to turbulent flow analysis with low Reynolds number $\kappa$-$\varepsilon$ model. Turbulent flows include fully developed channel flow, backward-facing step flow, and conical diffuser flow. Prediction results show that the pressure gradient method can be applied to turbulent flow analysis. However, the pressure gradient method requires somewhat long computation time. Proper way to find optimum under-relaxation factor, $\gamma$, is also need to be developed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1854-1868
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• 2018

A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.305-312
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• 2018

This study investigates moderating effects of positive psychological capital between job stress and depression focusing on hotel employees. Data were collected for 3 weeks from November 7 to November 27, 2017. 6 five-star and deluxe hotels in Seoul and Gyeonggi province were chosen for this study and samples were collected from employees working the hotel. A total of 330 employees were attended in this research and finally 308 samples were used for the empirical analysis. The result of this study showed that 3 factors(self-efficacy, restoration ability, optimism) of positive psychological capital but hope factor moderated the relationship between job stress(working environment, time pressure constraint, communication factors among them) and depression. However, all factors of positive psychological capital did not moderated between job instability and depression.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.4
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• pp.83-88
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• 2020

In Solar-powered wireless sensor networks(SP-WSN), the battery is periodically charged, so the best use of harvested energy is more important, rather than minimizing energy consumption. Meanwhile, as is well known, the reliability of communication between sensor nodes is very limited due to the resource-constraint of sensor nodes. In this paper, we propose an advanced FEC (forward error correction) scheme which can give SP-WSN more reliability for communication. Firstly, the proposed scheme uses energy modeling to calculate the amount of surplus energy which can be utilized for extra operations, and then determines the number of additional parity bits according to this amount of surplus energy. At the same time, link quality modeling calculates the optimal parity bits for error recovery in the current data communication environment. Finally, by considering these two parity sizes, it is possible to determine the optimal parity size that can maximize the data reliability without affecting the node black out. Performance verification was performed by comparing the amount of data collected at the sink and the number of outage nodes with other schemes.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.478-488
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• 2009

Using solar power in wireless sensor networks (WSNs) requires adaptation to a highly varying energy supply and to a battery constraint. From an application's perspective, however, it is often preferred to operate at a constant quality level as opposed to changing application behavior frequently. Reconciling the varying supply with the fixed demand requires good tools for allocating energy such that average of energy supply is computed and demand is fixed accordingly. In this paper, we propose a probabilistic observation-based model for harvested solar energy. Based on this model, we develop a time-slot-based energy allocation scheme to use the periodically harvested solar energy optimally, while minimizing the variance in energy allocation. We also implement the testbed and demonstrate the efficiency of the approach by using it.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of Environmental Health Sciences
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• v.43 no.4
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• pp.298-306
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• 2017

Objectives: Since 1998, the Korea National Health and Nutrition Examination Survey (KNHANES) has been conducted in order to investigate the health and nutritional status of Koreans. The food intake data of individuals in the KNHANES has also been utilized as source dataset for risk assessment of chemicals via food. To improve the reliability of intake estimation and prevent missing data for less-responded foods, the structure of integrated long-standing datasets is significant. However, it is difficult to merge multi-year survey datasets due to ineffective cleaning processes for handling extensive numbers of codes for each food item along with changes in dietary habits over time. Therefore, this study aims at 1) cleaning the process of abnormal data 2) generation of integrated long-standing raw data, and 3) contributing to the production of consistent dietary exposure factors. Methods: Codebooks, the guideline book, and raw intake data from KNHANES V and VI were used for analysis. The violation of the primary key constraint and the $1^{st}-3rd$ normal form in relational database theory were tested for the codebook and the structure of the raw data, respectively. Afterwards, the cleaning process was executed for the raw data by using these integrated codes. Results: Duplication of key records and abnormality in table structures were observed. However, after adjusting according to the suggested method above, the codes were corrected and integrated codes were newly created. Finally, we were able to clean the raw data provided by respondents to the KNHANES survey. Conclusion: The results of this study will contribute to the integration of the multi-year datasets and help improve the data production system by clarifying, testing, and verifying the primary key, integrity of the code, and primitive data structure according to the database normalization theory in the national health data.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.29-37
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• 2015

Entering the convergence education era, the emergence of smart devices removed the constraint of time and space for study, so if we use smart devices appropriately for education, it will strengthen students' abilities and cultivate creative human resource. Therefore the current study analyzed the general application condition of the smart devices through surveys targeted to students and proposed a measure in applying the smart device as an educational information. In relation to information application, a test was proceeded after carrying out education targeted to experiment group students by naming the group information search, communication, cooperation, sharing, report generation, data storage, online assessment and project management activity. Through the test and survey analysis, it was discovered that the experiment group students displayed higher self-efficacy and ability in applying the smart device as information compared to the control group.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.283-289
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• 2015

In this study, the lightweight design of a brake bracket for a composite bogie was studied by considering two brake bracket models with thicknesses of 12t and 9t, respectively. For achieving this goal, finite element analysis and topology optimization were conducted. Firstly, the largest cross-sectional areas of the vertical and horizontal plates of the brake bracket were selected as the design variables. As the constraint, the Z-axis displacement of the brake bracket was increased by 2.5 units from the initial displacement value. The minimum volume fraction of the design regions was chosen as the objective function. The full model comprised a composite bogie frame and brackets attached together. However, to reduce the analysis time, 1D beam elements were used instead of the composite bogie frame by ensuring its equivalence with the full model. The result revealed that the weights of the 12t and 9t models of the brake bracket were reduced to 60 kg and 31 kg, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2577-2596
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• 2013

In this paper, we present an Energy-Aware Self-Stabilizing Distributed Clustering protocol based on message-passing model for Ad Hoc networks. The latter does not require any initialization. Starting from an arbitrary configuration, the network converges to a stable state in a finite time. Our contribution is twofold. We firstly give the formal proof that the stabilization is reached after at most n+2 transitions and requires at most $n{\times}log(2n+{\kappa}+3)$ memory space, where n is the number of network nodes and ${\kappa}$ represents the maximum hops number in the clusters. Furthermore, using the OMNeT++ simulator, we perform an evaluation of our approach. Secondly, we propose an adaptation of our solution in the context of Wireless Sensor Networks (WSNs) with energy constraint. We notably show that our protocol can be easily used for constructing clusters according to multiple criteria in the election of cluster-heads, such as nodes' identity, residual energy or degree. We give a comparison under the different election metrics by evaluating their communication cost and energy consumption. Simulation results show that in terms of number of exchanged messages and energy consumption, it is better to use the Highest-ID metric for electing CHs.