• 한국정보통신학회논문지
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• 제7권7호
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• pp.1520-1526
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• 2003

본 논문에서는 마이크로프로세서를 이용하여 소비전력 모니터링이 가능한 100[W]급 직류입력/교류출력변환 인버터를 설계하였다. 또한 입출력 제어와 소비전력정보 모니터링을 외부환경에 적응적으로 대응하기 위해 퍼지추론 시스템을 설계하였다. 추론결과를 PIC16C711 프로세서에서 처리함으로서 입력전압의 변화와 소자의 온도특성 등에 적응적인 인버터 설계가 가능함을 보였다. 제작된 시스템을 이용하여 효율실험 및 부하실험을 수행하였고 오차는 2% 이내임을 확인하였다.

• 한국정보통신학회논문지
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• 제17권7호
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• pp.1702-1708
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• 2013

OLED(Organic Light-Emitting Diode)는 LCD와 달리 자체발광 특성 때문에 흰색을 표현할 때에는 R,G,B 소자가 모두 발광하여야 하므로 전력소비가 상대적으로 커지게 되는 문제점이 있다. 본 논문은 OLED 패널을 사용한 기기의 저전력 디스플레이 방법 및 하드웨어 구현에 관한 것이다. 입력 이미지의 휘도 정보를 기반으로 하여 실시간으로 화소 별 휘도 변환 값을 생성하여 적응적 휘도 조절 방법과 색도 축소 알고리즘의 기본 개념을 사용하여 새로운 색상보정 알고리즘을 사용하여 OLED 패널의 저전력 디스플레이 방법을 제안한다. 기존의 방법과 비교함으로써 제안한 방법의 성능을 확인한 결과 최대 48.43%의 전류 감소를 확인하였다. 최종적으로 제안된 알고리즘은 Verilog HDL로 하드웨어를 구현하였으며, OpenCV와 Window 프로그램을 사용하여 소프트웨어적으로 알고리즘을 검증하였다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.402-403
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• 2009

A variety of power reduction technologies is introduced and the benefits of the technologies are discussed. PenTile$^{(R)}$ DBLC (Dynamic Brightness LED Control) combined with SABC (Sensor-Based Adaptive Brightness Control) enables to achieve the average LED power consumption to one third. The panel power reduction of 25% can be achieved with low power driving technology, ALS (Active Level Shifter). MIP (Memory In Pixel) is expected to be useful in transflective display because the whole display area can be utilized in reflective mode with power consumption of 1mW.

• 한국시뮬레이션학회논문지
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• 제21권4호
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• pp.47-56
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• 2012

본 연구에서는 센서 네트워크용 병렬 시뮬레이터인 PASENS(Parallel SEnsor Network Simulator)를 이용하여 센서 네트워크에 이용되는 라우팅 알고리즘 중에서 계층적 라우팅 프로토콜의 대표적인 방식인 LEACH(Low-Energy Adaptive Clustering Hierarchy)와 그의 변형인 TL-LEACH(Two Level Low-Energy Adaptive Clustering Hierarchy), M-LEACH(Multihop Low-Energy Adaptive Clustering Hierarchy), 그리고 LEACH-C(LEACH-Centralized)의 전력 소모량과 데이터의 수신율을 비교하고 분석하였다. 시뮬레이션을 이용한 분석 결과에 따르면, M-LEACH 라우팅 프로토콜의 경우에는 여러 센서 노드들을 통하여 데이터가 전달되기 때문에 일정한 크기 이상의 넓은 공간에서 높은 수신율을 보였으며, LEACH-C 라우팅 프로토콜은 싱크 노드(서버)가 전체 센서 노드의 잔여 에너지와 위치를 고려하여 클러스터 헤드를 결정하기 때문에 좁은 공간에서 보다 오랜 수명을 필요로 하는 센서 네트워크를 구축하는데 가장 효율적이라는 것을 확인 할 수 있었다.

• Journal of Communications and Networks
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• 제12권5호
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• pp.510-517
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• 2010

In this paper, an adaptive MAC protocol (variable load adaptive (VLA)-MAC) is proposed for wireless sensor networks. This protocol can achieve high energy efficiency and provide low latency under variable-traffic-load conditions. In the case of VLA-MAC, traffic load is measured online and used for adaptive adjustment. Sensor nodes transmit packets in bursts under high load conditions to alleviate packet accumulation and reduce latency. This also removes unnecessary listen action and decreases energy consumption in low load conditions. Simulation results show that the energy efficiency, latency, and throughput achieved by VLA-MAC are higher than those achieved by some traditional approaches.

• 반도체디스플레이기술학회지
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• 제7권1호
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• pp.23-27
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• 2008

Wireless sensor networks are emerging as a solution for a wide range of data gathering applications. The most difficult challenge for the design of sensor nodes is the need for significant reductions in energy consumption. The threshold methods which filter redundant and similar data can be used to save energy. In this paper, we propose the adaptive threshold method to effectively manage the energy in wireless sensor nodes. In the adaptive threshold method, wireless sensor nodes can change the thresholds dynamically as the sensing environments vary. The simulation results show that the adaptive threshold method works very effectively even when we experience the significant volatility in the data. This scheme can be used in order to monitor the malfunction in the equipment of semiconductor manufacturing line.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.1987-2001
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• 2017

Low-density parity-check (LDPC) codes have attracted a great attention because of their excellent error correction capability with reasonably low decoding complexity. Among decoding algorithms for LDPC codes, the min-sum (MS) algorithm and its modified versions have been widely adopted due to their high efficiency in hardware implementation. In this paper, a self-adaptive MS algorithm using the difference of the first two minima is proposed for faster decoding speed and lower power consumption. Finding the first two minima is an important operation when MS-based LDPC decoders are implemented in hardware, and the found minima are often compressed using the difference of the two values to reduce interconnection complexity and memory usage. It is found that, when these difference values are bounded, decoding is not successfully terminated. Thus, the proposed method dynamically decides whether the termination-checking step will be carried out based on the difference in the two found minima. The simulation results show that the decoding speed is improved by 7%, and the power consumption is reduced by 16.34% by skipping unnecessary steps in the unsuccessful iteration without any loss in error correction performance. In addition, the synthesis results show that the hardware overhead for the proposed method is negligible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권1호
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• pp.105-122
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• 2011

The fundamental design goal of wireless sensor MAC protocols is to minimize unnecessary power consumption of the sensor nodes, because of its stringent resource constraints and ultra-power limitation. In existing MAC protocols in wireless sensor networks (WSNs), duty cycling, in which each node periodically cycles between the active and sleep states, has been introduced to reduce unnecessary energy consumption. Existing MAC schemes, however, use a fixed duty cycling regardless of multi-hop communication and traffic fluctuations. On the other hand, there is a tradeoff between energy efficiency and delay caused by duty cycling mechanism in multi-hop communication and existing MAC approaches only tend to improve energy efficiency with sacrificing data delivery delay. In this paper, we propose two different MAC schemes (ADS-MAC and ELA-MAC) using closed-loop control in order to achieve both energy savings and minimal delay in wireless sensor networks. The two proposed MAC schemes, which are synchronous and asynchronous approaches, respectively, utilize an adaptive timer and a successive preload frame with closed-loop control for adaptive duty cycling. As a result, the analysis and the simulation results show that our schemes outperform existing schemes in terms of energy efficiency and delivery delay.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.