• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4617-4632
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• 2021

IEEE 802.11ax is a protocol being developed for high-density Wireless Local Area Networks (WLAN). Several algorithms have been proposed to improve the level of spatial reuse applied in IEEE 802.11ax. However, these algorithms are tentative and do not specify how to select the transmit power and carrier sense threshold in practice; It is unclear when and why the tuned parameters lead to better network performance. In this paper, we restricted the scale of transmit power tuning to prevent the case of backfire in which spatial reuse will result in transmission failure. If the restrictions cannot be satisfied, spatial reuse will be abandoned. This is why we named the proposed scheme as Arbitration based Spatial Reuse (ASR). We quantified the network performance after spatial reuse, and formulate a corresponding maximum problem whose solution is the optimal carrier sense threshold and transmit power. We verified our theoretical analysis by simulation and compared it with previous studies, and the results show that ASR improves the throughput up to 8.6% compared with 802.11ax. ASR can avoid failure of spatial reuse, while the spatial reuse failure rate of existing schemes can up to 36%. To use the ASR scheme in practice, we investigate the relation between the optimal carrier sense threshold and transmit power. Based on the relations got from ASR, the proposed Relation based Spatial Reuse (RSR) scheme can get a satisfactory performance by using only the interference perceived and the previously found relations.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.293-300
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• 2014

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.8
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• pp.490-495
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• 2015

This paper was proposed the theoretical research and optimal design 3,000 V IGBT for using electrical automotive, high speed train and first power conversion. To obtaining 3,000 V breakdown voltage, the design parameters was showed $160{\Omega}{\cdot}cm$ resistivity and $430{\mu}m$ drift length. And to maintain 5 V threshold voltage, we obtained $6.5{\times}10^{13}cm^{-2}$ p-base dose. We confirmed $24{\mu}m$ cell pitch for maintain optimal on state voltage drop and thermal characteristics. This 3,000 V IGBT was replaced to thyristor devices using first power conversion and high speed train, presently.

• Journal of Korean Society of Water and Wastewater
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• v.16 no.6
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• pp.710-716
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• 2002

A General Pipe Break Prediction Model that incorporates linear and exponential models in its form is developed. The model is capable of fitting pipe break trends that have linear, exponential or in between of linear and exponential trend by using a weighting factor. The weighting factor is adjusted to obtain a best model that minimizes the sum of squared errors of the model. The model essentially plots a best curve (or a line) passing through "cumulative number of pipe breaks" versus "break times since installation of a pipe" data points. Therefore, it prevents over-predicting future number of pipe breaks compared to the conventional exponential model. The optimal replacement time equation is derived by using the Threshold Break Rate equation by Loganathan et al. (2002).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4625-4641
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• 2016

The performances of two commonly used feature detectors for wireless energy-harvesting cognitive radio systems are compared with the energy detector under energy causality and collision constraints. The optimal sensing duration is obtained by analyzing the effect of the detection threshold on the average throughput and collision probability. Numerical examples show that the covariance detector has the optimal sensing duration depending on an appropriate choice of the detection threshold, but no optimal sensing duration exists for the ratio of average energy to minimum eigenvalue detector.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.93-100
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• 2005

We propose an optimal thresholding method for the voxel coloring in the reconstruction of a 3D shape. Our purposed method is a new approach to resolve the trade-off error of the threshold value on determining the photo-consistency in the conventional method. Optimal thresholding value is decided to compare the photo-consistency of a surface with inside voxel on the optic ray of the center camera. As iterating the process of the vokels, the threshold is approached to the optimal value for the individual surface voxel. And also, graph cut method is reduced to the surface noise on eliminating neighboring voxel. To verify the proposed algorithm, we simulated in the virtual and real environment. It is advantaged to speed up and accuracy of a 3D face reconstruction by applying the methods of optimal threshold and graph as compare with conventional algorithms.

• The Korean Journal of Food And Nutrition
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• v.30 no.2
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• pp.257-268
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• 2017

The purpose of this research was to evaluate the correlation between obesity, threshold of salty taste, optimal saltiness and blood pressure in middle school students in a fishing village. The subjects were 115 boys and 103 girls in middle school in a fishing village. The BMI index and systolic and diastolic blood pressures of subjects were measured, and the subjects were divided into a normal and obese group according to their BMI. The threshold of salty taste and salt preference for a semisolid dish (steamed egg dish), liquid dish (bean sprout soup), and a solid dish (raw radish salad), were estimated by sensory evaluation. Calorie intake was measured using the weighing plate method. The boys in the obese group showed significantly higher systolic and diastolic blood pressures than those in the normal, but girls did not. Furthermore, calorie intakes of the boys in the obese group were significantly higher than those in the normal group, but this was not shown in girls. On the threshold of salty taste, both boys and girls in the obese group needed higher concentration of salt than those in the normal group. The threshold of salty taste were significantly positively correlated with systolic pressure and diastolic pressure in boys. Regarding the salt preference in the steamed egg dish, bean-sprout soup, and raw radish salad, both boys and girls in the obese group preferred higher concentrations. The higher concentration they preferred, the higher the systolic and diastolic pressures were in boys, but only systolic blood pressure was higher in girls. From these results, it is evident that a nutritional education program is needed in school to help restricting middle school students salt consumption and decreasing obesity to prevent hypertension.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.6
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• pp.213-224
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• 2003

The proposed algorithm can always set up the optimal threshold value regardless of channel characteristics using an adaptive threshold establishment method that determines the threshold level according to channel noise power, and then it uses the specially designed training symbols that can make the algorithm's estimation performance be less sensitive to power delay profile variation in a multipath channel. In result, the estimation performance of the proposed technique is less affected by channel characteristic variation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.581-586
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• 2017

The well-known Integral Pulse Frequency Modulation (IPFM) cardiac oscillator has been used to generate the heart beat fluctuations as a representation of the modulatory autonomic nervous activity in terms of sympathetic and parasympathetic state. The IPFM model produces heartbeats by integrating the modulated sinusoid signals and applying the threshold of unity or chaotic threshold levels. This study aims at evaluating the performance of IPFM model by analyzing the influence of the threshold level with comparatively applying preset threshold of unity and Logistic-map and Henon-map chaotic-threshold. Based on our simulated results with interpreting the spectral features of Heart Rate Variability (HRV), we can conclude that the IPFM model with preset threshold level of unity can generate the optimal heartbeat variations int the sense of clinically valid heartbeats.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.334-349
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• 2022

The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CW_Threshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.