• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3479-3492
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• 2022

Longitudinal quantification of brain changes due to development, aging or disease plays an important role in the filed of personalized-medicine applications. However, due to the temporal variability in shape and different imaging equipment and parameters, estimating anatomical changes in longitudinal studies is significantly challenging. In this paper, a longitudinal Magnetic Resonance(MR) brain image segmentation algorithm proposed by combining intensity information and anisotropic smoothness term which contain a spatial smoothness constraint and longitudinal consistent constraint into a variational framework. The minimization of the proposed energy functional is strictly and effectively derived from a fast optimization algorithm. A large number of experimental results show that the proposed method can guarantee segmentation accuracy and longitudinal consistency in both simulated and real longitudinal MR brain images for analysis of anatomical changes over time.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제33권4A호
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• pp.450-457
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• 2008

One of very essential techniques for enlarging lifetime of energy-constrained wireless personal area network (WPAN) devices is energy-efficient transmission technique. If the WPAN is operated based on a TDMA protocol, the satisfaction of QoS requirements at each allocated time slot is another important factor to be considered. We therefore propose an energy-efficient transmission scheme for WPANs operating with a contention-free medium access protocol such as TDMA, as well as satisfying QoS requirement. The proposed algorithm determines the optimum combination of transmit power, physical data rate and fragment size required to simultaneously minimize the energy consumption and satisfy the required QoS in each assigned time duration, considering all the possible energy-minimization related parameters. The proposed algorithm demonstrated the improved performance results in terms of throughput and energy consumption via computer simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.750-753
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• 2013

In respect of consuming energy, the optimization is the main objective in the solar energy harvesting sensor system (while battery-based sensor system aims at the minimization), due to the periodicity of solar energy. Aimed at the optimization of the network topology, we suggest 3-level transmission power control algorithm of which level is determined by the amount of residual energy on the rechargeable battery. Additionally, we experiment the effects of our scheme on network-wide performance such as the latency and the duty-cycle, and verify that our scheme shows the best performance in most of the metrics, compared to the schemes with fixed transmission power.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• 제25권11호
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• pp.39-49
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• 2011

Smart Grid has two main objectives on both supply and demand aspects which are to distribute the renewable energy sources on supply side and to develop realtime price responses on demand side. Renewable energy does not consume fossil fuels, therefore it improves the eco-friendliness and saves the cost of power system operation at the same time. Demand response increases the flexibility of the power system by mitigating the fluctuation from renewable energies, and reduces the capacity investment cost by shedding the peak load to off-peak periods. Currently Smart Grid technologies mainly focus on energy monitoring and display services but it has been proved that enabling technologies can induce the higher demand responses through many pilot projects in USA. On this context, this paper provides a price responsive algorithm for HEMS (home energy management system) on the real time pricing environment. This paper identifies the demand response as a core function of HEMS and classifies the demand into 3 categories of fixed, transferable, and realtime responsive loads which are coordinated and operated for the utility maximization or cost minimization with the optimal usage combination of three kinds of demand.

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권3호
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• pp.465-472
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• 2017

Security has become one of the most important requirements for various devices for multi-sensor based embedded systems. The AES (Advanced Encryption Standard) algorithm is widely used for security, however, it requires high computing power. In order to reduce the CPU power for the data encryption of images, we propose a new image encryption module using hardware memoization, which can reuse previously generated data. However, as image pixel data are slightly different each other, the reuse rate of the simple memoization system is low. Therefore, we further apply an approximate concept to the memoization system to have a higher reuse rate by sacrificing quality. With the novel technique, the throughput can be highly improved by 23.98% with 14.88% energy savings with image quality loss minimization.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제6권8호
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• pp.1146-1152
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• 2002

This paper proposed a scheme for finding an optimal adaptive data association for multi-target between measurements and tracks. First, we assume the relationships between measurements as Mrkov Random Field. Also assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints. Through the experiments, we analyzed and compared this algorithm with other representative algorithms. The result is that it is stable, robust, fast enough for real timecomputation, as well as more accurate than other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.195-215
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• 2021

Multipath Transport Control Protocol (MPTCP) is a transport layer protocol that enables multiple TCP connections across various paths. Due to path heterogeneity, it incurs more energy in a multipath wireless network. Recent work presents a set of approaches described in the literature to support systems for energy consumption in terms of their performance, objectives and address issues based on their design goals. The existing solutions mainly focused on the primary system model but did not discourse the overall system performance. Therefore, this paper capitalized a novel stochastically multipath scheduling scheme for data and path capacity variations. The scheduling problem formulated over MPTCP as a stochastic optimization, whose objective is to maximize the average throughput, avoid network congestion, and makes the system more stable with greater energy efficiency. To design an online algorithm that solves the formulated problem over the time slots by considering its mindrift-plus penalty form. The proposed solution was examined under extensive simulations to evaluate the anticipated stochastic optimized MPTCP (so-MPTCP) outcome and compared it with the base MPTCP and the energy-efficient MPTCP (eMPTCP) protocols. Simulation results justify the proposed algorithm's credibility by achieving remarkable improvements, higher throughput, reduced energy costs, and lower-end to end delay.

• Proceedings of the KIEE Conference
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1838-1839
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• 2006

In this paper, a loss-minimization nonlinear torque control for Electrical Vehicle(EV) induction motors is proposed. To improve the efficiency of the induction motors, it is important to find the optimal flux reference that minimize power losses. The proposed optimal flux reference is derived using a power loss function that is constructed with stator resistance losses, rotor resistance losses and core losses. And the time-varying load torque and the rotor resistance variation are considered in the power loss function. An algorithm that identifying the load torque is used. The rotor flux observer is used to obtain an accurate flux value regardless of the rotor resistance variation. Simulation results show a significant reduction in energy losses.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제20권1호
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• pp.213-221
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• 1996

An assembly sequence is considered to be optimal when is minimizes assembly cost while satisfying assembly constraints. To derive such an optimal sequence for robotic assembly, this paper proposes a method using a simulated annealing algorithm. In this method, an energy funciton is derived inconsideration of both the assembly constraints and the assembly cost. The energy function thus derived is iteratively minimized until no further change in energy occurs. During the minimization, the energy is occationally perturbed probabilistically in order to escape from local minima. The minimized energy yields an optimal assembly sequence. To show the effectiveness of the proposed method, case studies are presented for industrial products such as an electrical relay and an automobil alternator. The performance is analyzed by comparing the results with those of a neural network-based method, based upon the optimal solutions of an expert system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.854-857
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• 2015

As the number of devices integrated on system-on-chip(SoC) increases exponentially, energy reduction technology is essential. Dynamic Voltage and Frequency Scaling (DVFS) is a very effective technique for reducing power consumption. Since it requires complex voltage regulators and PLL circuits, DVFS tends to have significant overheads. In this paper, we propose a new voltage selection algorithm to minimize transition overhead for multiprocessor SoC (MPSoC). Simulation results show that proposed algorithm appears less energy consumption with transition overhead even though maintains performance.