Earticle

한국은 1960년 초반부터 본격적인 산업화가 추진되면서 급속한 경제성장이 이루어졌으며, 정치·경제·사회·문화·교육 등 사회의 전 영역에 걸친 급속한 변화를 초래했다. 이러한 사회변동은 교육제도와 교육과정 등 교육에 있어 총체적인 변화를 불러일으켰다. 이 연구에서는 사회와 교육, 경제가 서로 긴밀하게 연결되어 있고 영향을 미치고 있으며 이러한 사회의 제 양상을 종합하여 통찰할 때만이 현상의 이면에 존재하는 본질을 파악할 수 있다는 문제의식을 바탕으로 하였다. 이에 교육현상을 정확하게 분석하기 위해서 한국의 사회변동과 교육과정 변천 간의 관련성을 North의 신제도주의 이론을 바탕으로 한‘적응적 효율성(adaptive efficiency)’개념을 통하여 설명하였다.

Since the early 1960s, the rapid industrialization of Korea has resulted in an outstanding economic growth. This change in economic development has brought about a multifaced transition embracing politics, economy, society, culture, and education. This study deals with the problem that schooling should match, either leading or lagging, changes in other social dimensions such as economic and social transition. In this context, central to this study is to examine the relationship between social and educational change focusing on the transition of school curriculum. The examination has been carried out through inquiring into North's new institutional economic theory. Especially, the concept of ‘adaptive efficiency' has been contributed to explain the link between education and economy.

무선 스마트카드는 빌딩 보안 어플리케이션에 주된 역할을 하고 있다. 본 연구는 사용자에게 보다 편리함을 주고 스마트카드 시스템의 성능 개선을 제안한다. 스마트카드는 카드 리더기에 삽입을 하지 않고 장치에서 수센티미터 떨어져도 접근이 허용된다. 적응형 변조와 오류 제어를 통해 전력소비를 제어하는 성능은 필요하다. 본 논문에서는 적응형 리드 솔로몬 코드 기반의 FEC와 링크에서 M계수를 변화시킨 M-FSK변조에 대하여 연구한다. 적응형 변조와 적응형 오류 정정은 다른 다양한 정적스키마와 에너지 효율을 비교한 결과 50% 이상 에너지를 저장한다.

Since the wireless smart card has played a main role in the identification security application for the building access; this research has its purpose to improve the performance of the smart card system and aims to offer more convenient to user. The contactless cards do not require insertion into a card reader and can work up to centimeters away from the reading device. To be able to cope with this performance the controlling of power consumption through the adaptive modulation and error control is needed. This paper addresses a forward error control (FEC) scheme with the adaptive Reed-Solomon code rate and an M-ary frequency shift keying (M-FSK) modulation scheme with the varying symbol size M over the link. The result of comparing energy efficiencies of adaptive error correction and adaptive modulation to other various static schemes shows to save over 50% of the energy consumption.

스케일러블 HEVC에서 상위계층의 계층 간 예측에서 기본계층의 부호화 잔차 영상에 대한 업샘플링 된 결과를 참조하여 예측하게 된다. 본 논문에서는 고효율 영상 압축 기반 스케일러블 부호화 (Scalable Extension of High Efficiency Video Coding)에서 상위계층 잔차 데이터 예측에 대한 개선 기법을 제안한다. 제안하는 적응적 필터 선택 기법은 스무싱 필터와 샤프닝 필터를 사용함으로써 계층 간 예측 방법에서 효율을 향상시킨다. 기존의 업샘플링 필터와 두 개의 필터를 추가하여 율-왜곡 비용함수 기반의 경쟁기법을 통한 계층 간 예측 알고리즘을 SHVC 5.0에 구현함으로써 Y, U, V 컴포넌트에 대한 평균 1.5%, 2.1%, 1.7%의 BD-rate 향상을 보여준다.

Scalable extension of High Efficiency Video Coding (SHVC) standard uses the up-sampled residual data from the base layer to make a residual data in the enhancement layer. This paper describes an efficient algorithm for improving coding gain by using the filtered residual signal of base layer in the Scalable extension of High Efficiency Video Coding (SHVC). The proposed adaptive filter selection mechanism uses the smoothing and sharpening filters to enhance the quality of inter-layer prediction. Based on two filters and the existing up-sampling filter, a rate-distortion (RD)-cost fuction-based competitive scheme is proposed to get better quality of video. Experimental results showed that average BD-rate gains of 1.5%, 2.1%, and 1.7% for Y, U and V components, respectively, were achieved, compared with SHVC reference software 5.0, which is based on HEVC reference model (HM) 13.

In this paper, the high efficiency and linearity Doherty power amplifier using DGS and adaptive bias technique has been designed and realized for 2.3GHz WiBro applications. The Doherty amplifier has been implemented using silicon MRF 281 LDMOS FET. The RF performances of the Doherty power amplifier (a combination of a class AB carrier amplifier and a bias-tuned class C peaking amplifier) have been compared with those of a class AB amplifier alone, and conventional Doherty amplifier. The Maximum PAE of designed Doherty power amplifier with DGS and adaptive bias technique has been 36.6% at 34.01dBm output power. The proposed Doherty power amplifier showed an improvement 1dB at output power and 7.6% PAE than a class AB amplifier alone.

Energy Efficient in the VoIP transmission is the major criteria and issues to be maintained the packet and data while processing VoIP (QoS) over Manet environment. Mobile Adhoc network (MANETs) presents a good platform for the fast deployment of VoIP services in many application scenarios. The energy efficiency mechanism for the data packet of voice in the queuing system have not been concentrated which actually consumes the more power while in the queue buffer management. Manet provide a considerable complexity that makes the transmission of real-time applications like VoIP a great challenge due to insufficient energy for packet transmission. In this research a new algorithm is proposed which enhance the performance of energy in manet carrying VoIP traffic. Through a simulation and mathematical expression we analyze and evaluate QoS indicators such as Distance, power, Bandwidth. Several voice codec are studied to determine their effect of insufficient energy. In the existing methods queuing energy have been used depend on number of nodes in certain environment which is drawbacks with mobile nodes. Hence a QoS based Intelligent Adaptive Energy Efficiency & Effective signal buffer management algorithm for voip(QoS) over Manet. The main objective of this paper is to segregate the energy altitude as per detachment the bandwidth is assign by using our IAE3 signal barrier algorithm in manet environment. In great and dynamic networks, central algorithms are not suitable due to the lack of responsiveness. The bandwidth allocation is done by IAE3 signal buffer algorithm.

Ethernet is one of the most widely-deployed and utilized local-loop networking technology across the world, and IEEE 802.3az working group has confirmed EEE(Energy Efficient Ethernet) standard proposal based on LPI (Low Power Idle) mode. This paper suggests Synchronizing Adaptive LPI Control Mechanism in a bid to improve the energy efficiency between interfacing terminals on Ethernet network and the Ethernet switches. This mechanism determines ON and OFF durations of consecutive cycles based on the measured incoming traffic quantities from the terminals. It keeps transferring cycle information which is the most proximate to the traffic bursting cycles while resting in idle is left to LPI mode by conveying the corresponding information to the switch. This paper conducts the performance evaluations with simulations on Poisson distribution traffic and burst traffic. The result has shown that the suggested mechanism in this paper improves the overall performance by reducing the energy consumption rate compared to the existing mechanism, keeping the average packet delay to the similar state as before.

Ethernet is one of the most widely-deployed and utilized local-loop networking technology across the world, and IEEE 802.3az working group has confirmed EEE(Energy Efficient Ethernet) standard proposal based on LPI (Low Power Idle) mode. This paper suggests Synchronizing Adaptive LPI Control Mechanism in a bid to improve the energy efficiency between interfacing terminals on Ethernet network and the Ethernet switches. This mechanism determines ON and OFF durations of consecutive cycles based on the measured incoming traffic quantities from the terminals. It keeps transferring cycle information which is the most proximate to the traffic bursting cycles while resting in idle is left to LPI mode by conveying the corresponding information to the switch. This paper conducts the performance evaluations with simulations on Poisson distribution traffic and burst traffic. The result has shown that the suggested mechanism in this paper improves the overall performance by reducing the energy consumption rate compared to the existing mechanism, keeping the average packet delay to the similar state as before.

사람의 얼굴 표정을 실제 환경에서 인식하는 데에는 여러 가지 난이한 점이 존재한다. 그래서 학습에 사용된 데이터베이스와 실험 데이터가 여러 가지 조건이 비슷할 때에만 그 성능이 높게 나온다. 이러한 문제점을 해결하려면 수많은 얼굴 표정 데이터가 필요하다. 본 논문에서는 능동준지도 학습을 통해 다양한 조건의 얼굴 표정 데이터를 쉽게 모으고 보다 빠르게 성능을 확보할 수 있는 방법을 제안한다. 제안하는 알고리즘은 딥러닝 네트워크와 능동 학습 (Active Learning)을 통해 초기 모델을 학습하고, 이후로는 준지도 학습(Semi-Supervised Learning)을 통해 라벨이 없는 추가 데이터를 확보하며, 성능이 확보될 때까지 이러한 과정을 반복한다. 위와 같은 능동준지도 학습(Active Semi-Supervised Learning)을 통해서 보다 적은 노동력으로 다양한 환경에 적합한 데이터를 확보하여 성능을 확보할 수 있다.

It is difficult to recognize Human’s facial expression in the real-world. For these reason, when database and test data have similar condition, we can accomplish high accuracy. Solving these problem, we need to many facial expression data. In this paper, we propose the algorithm for gathering many facial expression data within various environment and gaining high accuracy quickly. This algorithm is training initial model with the ASSL (Active Semi-Supervised Learning) using deep learning network, thereafter gathering unlabeled facial expression data and repeating this process. Through using the ASSL, we gain proper data and high accuracy with less labor force.

최근 스마트폰 앱의 위치 기반 서비스 사용이 늘어남에 따라 GPS로 인한 배터리 소모가 심각한 수준에 이르 고 있다. 본 논문에서는 배터리 효율적인 위치 탐지 기법인 ALD(Adaptive Location Detection) 기법을 제안한다. ALD는 스마트폰 사용자의 이동 패턴과 실행 중인 앱의 특성, 잔여 배터리 수준 등에 따라 적절한 위치 추정 방법을 실시간으로 전환하여 위치 기반 서비스의 전력소모를 극소화한다. 다양한 실제 안드로이드 앱과 가상 시나리오 환경에 서의 시뮬레이션 결과 제안한 방법이 GPS에 비해 전력소모를 평균 37% 줄임을 확인하였다. 그럼에도 각 앱이 필요로 하는 위치 정확성을 제공함을 검증하였다.

As Location-Based Services (LBSs) of smartphones increases, the power consumption of a smartphone due to Global Positioning System (GPS) is becoming increasingly serious. This paper presents a new location estimation scheme for smartphones called Adaptive Location Detection (ALD). ALD adaptively detects the location of a smartphone considering the movement pattern of a user, category of applications executed in the smartphone, and the battery level. Simulation with various real applications and scenarios show that ALD reduces 37% of energy consumption compared to GPS. Nevertheless, it satisfies the accuracy requirement of each situation.

무선 센서 네트워크 기술은 4차 산업혁명의 발전과 함께 중요성이 더욱 부각되고 있다. 이에 따라 LEACH, PEGASIS, 그리고 EEACP와 같은 다양한 프로토콜이 개발되어 에너지 효율을 높이는 시도가 이루어지고 있다. 그러 나 EEACP 프로토콜은 여전히 전송 간 에너지 소모 측면에서 개선의 여지가 남아있다. 특히 데이터 수신 각 설정과 관련된 비효율적인 경로로 인해 네트워크의 생존성이 저하될 수 있다. 제안하는 A-EEACP 프로토콜은 이러한 문제를 해결하기 위해 싱크 노드를 중심으로 데이터 전송 방향을 최적화하여 에너지 소모를 줄이고 네트워크의 생존성을 향상시켰다.

Wireless sensor network technology is becoming increasingly important with the advancement of the Fourth Industrial Revolution. Consequently, various protocols such as LEACH, PEGASIS, and EEACP have been developed in an attempt to increase energy efficiency. However, the EEACP protocol still has room for improvement in terms of energy consumption during transmission. Particularly, inefficient paths associated with data reception settings may compromise the network's survivability. The proposed A-EEACP protocol optimizes data transmission direction around the sink node to reduce energy consumption and enhance the network's survivability.

WSN환경에서는 센서노드들은 수집한 데이터를 클러스터헤더노드로 전송하고 클러스터 헤더는 전달받은 데 이터를 취압하여 기지국으로 전송하게 된다. 이 과정에서 센서노드가 클러스터헤더로 선출되어 많은 에너지를 소비하게 되는 문제를 고려하지 않을 수 없다. 따라서 이미 배포된 센서필드를 기준으로 에너지 효율적인 클러스터링 알고리즘 을 적용함으로 전체 네트워크의 신뢰성을 향상시킬 수 있는 센서 필드의 환경을 이용한 클러스터 알고리즘을 자동 선 별하는 기법을 제안하였다. 실험 결과 제안알고리즘을 이용해 실험한 결과 FDN은 약 3배 연장함을 실험을 통해 증명 하였다. 또한 네트워크 에너지는 기존 방식보다 최대 30% 연장하여 센서네트워크의 신뢰성을 향상시켰다.

In the WSN environment, the sensor node is selected as the cluster header and consumes a lot of energy. Therefore, we proposed a method to automatically select a cluster algorithm using the sensor field environment that can improve the reliability of the whole network by applying an energy efficient clustering algorithm based on already deployed sensor field. Experimental results show that FDN is extended about 3 times by using the proposed algorithm. In addition, the network energy is extended by up to 30% compared to the conventional method, thereby improving the reliability of the sensor network.

When a part of data is unobserved the marginal likelihood of parameters given the observed data often involves analytically intractable high dimensional integral and hence it is hard to find the maximum likelihood estimate of the parameters. Simulated maximum likelihood(SML) method which estimates the marginal likelihood via Monte Carlo importance sampling and optimize the estimated marginal likelihood has been used in many applications. A key issue in SML is to find a good proposal density from which Monte Carlo samples are generated. The optimal proposal density is the conditional density of the unobserved data given the parameters and the observed data, and attempts have been given to find a good approximation to the optimal proposal density. Algorithms which adaptively improve the proposal density have been widely used due to its simplicity and efficiency. In this paper, we describe a fully adaptive algorithm which has been used by some practitioners but has not been well recognized in statistical literature, and evaluate its estimation performance and robustness via a simulation study. The simulation study shows a great improvement in the order of magnitudes in the mean squared error, compared to non-adaptive or partially adaptive SML methods. Also, it is shown that the fully adaptive SML is robust in a sense that it is insensitive to the starting points in the optimization routine.

This paper presents an energy-efficient photovoltaic energy harvesting system achieving an ultra-wide input power (PIN) range by optimizing both maximum-power-point-tracking efficiency (ηMPPT) and power-conversion efficiency (ηCONV). An MPPT based on an adaptive fractional open-circuit voltage method is proposed to tune the fraction k based on PIN with only little power overhead, unlike other complex and power-hungry hybrid MPPTs. Also, the harvester maintains high ηCONV at low PIN levels thanks to its modified hybrid topology that operates as a buck-boost converter with three different control techniques. The proposed zero-current detection circuit reduces the control bit size and response time because it actively changes the tuning resolution according to PIN. The proposed system achieves ηMPPT >98% across a 10,000× PIN dynamic range, and the achieved ηCONV is greater than 81% across the whole range with a peak efficiency of 96.5%. Compared to other previous state-of-the-art works, this design provides the highest peak ηCONV as well as the widest PIN ranges, over which it achieves >98% ηMPPT and >80% ηCONV.

This paper proposes an LLC resonant converter based battery charger which utilizes an adaptive turn ratio scheme to achieve a wide output voltage range and high efficiency. The high frequency transformer of the LLC converter of the proposed strategy has an adaptively changed turn ratio through the auxiliary control circuit. As a result, an optimized converter design with high magnetizing inductance is possible, while minimizing conduction and turn-off losses and providing a regulated voltage gain to properly charge the lithium ion battery. For a step-by-step explanation, operational principle and optimal design considerations of the proposed converter are illustrated in detail. Finally, the effectiveness of the proposed strategy is verified through various experimental results and efficiency analysis based on prototype 300W Li-ion battery charger and battery pack.

With the limited battery life of mobile devices and the full usage of shared network resources, mobile users are required to devise canny and amicable plans for energy and data consumption. In this paper, we propose an efficient chunk-scheduling strategy for adaptive video streaming which enhances per-power data utility. We first reveal that currently available chunk-scheduling strategies for adaptive video streaming do not consider the general viewing patterns of streaming users, causing a severe inefficiency in terms of not only data usage but also energy consumption. We then propose a energy- and data-efficient chunk scheduling algorithm that increases the per-power data utility for single bitrate encoded videos. We further extend the basic algorithm customizing it to dynamic adaptive streaming over HTTP (DASH) formatted video streaming systems, the most popular video streaming technique. We implemented the proposed scheme and the experiment results show that, while consuming 2% less energy, the scheme reduces the overall data wastage by 55% compared to a prior competing scheme.

For some low-frequency applications such as power-related circuits, NEM relays have been known to show better performance than MOSFETs. For example, in a step-down charge pump circuit, the NEM relays showed much smaller layout area and better energy efficiency than MOSFETs. However, severe process variations of NEM relays hinder them from being widely used in various low-frequency applications. To mitigate the process-variation problems of NEM relays, in this paper, a new NEM-relay charge pump circuit with the self-adjustment is proposed. By self-adjusting a pulse amplitude voltage according to process variations, the power consumption can be saved by 4.6%, compared to the conventional scheme without the self-adjustment. This power saving can also be helpful in improving the power efficiency of the proposed scheme. From the circuit simulation of NEM-relay charge pump circuit, the efficiency of the proposed scheme is improved better by 4.1% than the conventional.

지그비(zigbee) 장비는 센서 네트워크 장비 중에서도 규모가 큰 축에 속하고 배터리로 동작하기 때문에 전력 소비가 큰 문제점으로 부각되고 있다. 지그비에서 비콘(beacon)을 사용하는 네트워크를 구성하면, 센서 장치들은 데이터 전송 빈도가 낮을 때도 중앙 데이터 처리기(coordinator)가 전송하는 비콘 패킷을 매번 받아야 하기 때문에 그에 따른 전력소모가 상당히 높다. 이러한 지그비 네트워크의 중앙 데이터 처리기와 주변 센서 장치(device)에 비콘 수신 주기를 동적으로 설정할 수 있는 프로토콜을 추가 함으로써 기존의 데이터 응답 속도를 유지하면서 전력 소모도 줄이는 방안을 제시하고자 한다.

본 논문은 400 MHz 대역 시스템에 적용할 수 있는 고 효율을 유지하는 적응형 E급 증폭기를 제안하였다. 이 증폭기는 입력 주파수 변화에 공진기 주파수가 적응되도록 마이크로프로세서를 사용하여 고 효율을 유지하도록 하였다. 이러한 적응형 E급 증폭기의 동작을 보이기 위해서 중심 주파수는 450 MHz 이고, 대역폭은 100 MHz인 증폭기를 제작하여 이 주파수 구간에서는 60% 이상의 효율을 유지하였고, 최대 효율은 74.8%를 얻었다.

This paper proposes the adaptive class-E power amplifier with maintaining high power added efficiency (PAE) in 400MHz range. This amplifier is used a microprocessor to adapt a resonator circuits and to maintain high efficiency in case of input frequency variation. To validate the adaptive amplifier operation, which is a 450MHz operating frequency and a 100MHz bandwidth, the class E amplifier is implemented. As a result, the adaptive amplifier is maintained above 60% efficiency and has a 74.8% maximum efficiency.

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. In order to maximize the efficiency in such applications, this paper proposes the Adaptive-FNIS(Fuzzy Neural Network Inference System). The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal d-axis current $i_d$. This paper considers the parameter variation about the motor operation. The operating characteristics controlled by efficiency optimization control are examined in detail.