• Journal of Power Electronics
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• 제11권4호
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• pp.490-498
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• 2011

This paper presents a novel analysis, design, and implementation of a battery charging three-phase high frequency semi-controlled power converter feasible for plug-in hybrid electric vehicles. The main advantages of the proposed topology include high efficiency; due to lower power losses and reduced number of switching elements, high output power density realization, and reduced passive component ratings proportionally to the frequency. Additional advantages also include grid economic utilization by insuring unity power factor operation under different possible conditions and robustness since short-circuit through a leg is not possible. A high but acceptable total harmonic distortion of the generator currents is introduced in the proposed topology which can be viewed as a minor disadvantage when compared to traditional boost rectifiers. A hysteresis control algorithm is proposed to achieve lower current harmonic distortion for the rectifier operation. The rectifier topology concept, the principle of operation, and control scheme are presented. Additionally, a dc-dc converter is also employed in the rectifier-battery connection. Test results on 50-kHz power converter system are presented and discussed to confirm the effectiveness of the proposed topology for PHEV applications.

• ETRI Journal
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• 제45권3호
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• pp.448-461
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• 2023

This article performs a detailed data scrutiny on a chronic kidney disease (CKD) dataset to select efficient instances and relevant features. Data relevancy is investigated using feature extraction, hybrid outlier detection, and handling of missing values. Data instances that do not influence the target are removed using data envelopment analysis to enable reduction of rows. Column reduction is achieved by ranking the attributes through feature selection methodologies, namely, extra-trees classifier, recursive feature elimination, chi-squared test, analysis of variance, and mutual information. These methodologies are ranked via Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using weight optimization to identify the optimal features for model building from the CKD dataset to facilitate better prediction while diagnosing the severity of the disease. An efficient hybrid ensemble and novel similarity-based classifiers are built using the pruned dataset, and the results are thereafter compared with random forest, AdaBoost, naive Bayes, k-nearest neighbors, and support vector machines. The hybrid ensemble classifier yields a better prediction accuracy of 98.31% for the features selected by extra tree classifier (ETC), which is ranked as the best by TOPSIS.

• 한국멀티미디어학회논문지
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• 제16권12호
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• pp.1357-1367
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• 2013

최근 얼굴 표정 인식에 있어 영상 기반의 방법의 하나로서 ULBP 블록 히스토그램 피쳐와 SVM을 분류기로 사용한 연구가 수행되었다. Ojala 등에 의해 소개된 LBP는 높은 식별력과 조명의 변화에 대한 내구성과 간단한 연산 때문에 영상 인식 분야에 많이 사용되고 있다. 본 논문에서는 ULBP 블록 히스토그램을 계산함에 있어 분할 영역의 이동, 크기 변화에 더하여 미세한 특징 요소를 표현할 수 있도록 $LBP_{8,2}$과 $LBP_{8,1}$를 결합하였다. $LBP_{8,1}$ 660개, $LBP_{8,2}$ 550개의 분할 창으로부터 1210개의 ULBP 히스토그램 피쳐를 추출하고 이로부터 AdaBoost를 이용하여 50개의 약 분류기를 생성하였다. $LBP_{8,1}$와 $LBP_{8,2}$가 결합된 하이브리드 형태의 ULBP 블록 히스토그램 피쳐와 SVM 분류기를 이용함으로써 표정 인식률을 향상시킬 수 있었으며 다양한 실험을 통하여 이를 확인하였다. 본 논문에서 제안한 하이브리드 Boosted ULBP 히스토그램의 경우에 표정의 인식률이 96.3%로 가장 높은 결과를 보였으며 제안한 방법의 우수성을 확인하였다.

• Journal of Power Electronics
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• 제17권1호
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• pp.200-211
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• 2017

Conventional boost-full-bridge and boost-hybrid-bridge two-stage inverters are widely applied in order to adapt to the wide dc input voltage range of photovoltaic arrays. However, the efficiency of the conventional topology is not fully optimized because additional switching losses are generated in the voltage conversion so that the input voltage rises and then falls. Moreover, the electrolytic capacitors in a dc-link lead to a larger volume combined with increases in both weight and cost. This paper proposes a higher efficiency inverter with time-sharing synchronous modulation. The energy transmission paths, wheeling branches and switching losses for the high-frequency switches are optimized so that the overall efficiency is greatly improved. In this paper, a contrastive analysis of the component losses for the conventional and proposed inverter topologies is carried out in MATLAB. Finally, the high-efficiency under different switching frequencies and different input voltages is verified by a 3 kW prototype.

• ETRI Journal
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• 제39권1호
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• pp.62-68
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• 2017

In this paper, we present the design and characterization analysis of a cascode GaN field-effect transistor (FET) for switching power conversion systems. To enable normally-off operation, a cascode GaN FET employs a low breakdown voltage (BV) enhancement-mode Si metal-oxide-semiconductor FET and a high-BV depletion-mode (D-mode) GaN FET. This paper demonstrates a normally-on D-mode GaN FET with high power density and high switching frequency, and presents a theoretical analysis of a hybrid cascode GaN FET design. A TO-254 packaged FET provides a drain current of 6.04 A at a drain voltage of 2 V, a BV of 520 V at a drain leakage current of $250{\mu}A$, and an on-resistance of $331m{\Omega}$. Finally, a boost converter is used to evaluate the performance of the cascode GaN FET in power conversion applications.

• 한국자동차공학회논문집
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• 제25권1호
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• pp.82-91
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• 2017

This paper is a study on the bi-directional DC-DC converter, one of the key elements of 48V-12V dual systems in mild hybrid electric vehicles. Mild hybrid electric vehicles require a bi-directional DC-DC converter that can efficiently transmit power in two directions between a 48V battery and a 12V battery. To develop a bi-directional DC-DC converter with better price competitiveness, upgraded fuel economy, excellent performance and smaller size, this study designed, produced and presented a circuit that improved on the existing one. In the proposed 8-phase bi-directional DC-DC converter, the size of the passive element was reduced through the 8-phase interleaved topology, whereas downscaling had previously posed a difficulty. This study also designed and produced a 2.5kW class prototype. Based on the proposed 8-phase interleaved topology, a size of 227.5 (W) * 172 (L) * 64.35 (H) was achieved. In the boost mode operation and buck operation modes, the maximum efficiency was recorded at 94.04 % and 95.78 %, respectively.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• 전력전자학회:학술대회논문집
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• 전력전자학회 2009년도 정기총회 및 추계학술대회 논문집
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• pp.158-160
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• 2009

HEV(Hybrid Electrical Vehicle)의 배터리와 전동기/발전기용 인버터 사이에 장착되는 양방향 컨버터는 boost/buck 동작을 수행함으로써 차량이 효율적으로 동작되도록 한다. 대표적인 단상(single-phase)의 Half bridge topology를 기준으로 효율을 분석 하였으며 효율 개선을 위하여 다상(multi-phase) 인터리빙, 소프트 스위칭 기술 등이 사용되고 있으나 여기서는 하드 스위칭 상태만 다룬다. Ideal한 컨버터의 경우 단순히 Duty비와 동작 영역에 따라서 출력 상태가 결정 되며 입력전력과 출력전력은 동일하다. 그러나 손실이 있는 경우 입/출력 전력은 동일하지 않게 되고, Duty 역시 변화 한다. 따라서 각 손실 파라미터를 Ideal한 Duty로 가정하고 구할 경우 오차가 발생한다. 또한, 스위칭 소자의 on/off시 발생하는 스위칭 손실은 실험 측정값과 계산값의 차이가 크기 때문에 이 역시 오차의 원인이 된다. 본 논문에서는 각 손실 파라미터와 입/출력 전력을 Duty에 대한 다항식으로 표현 하였다. 고차 다항식의 근을 수치 해석적으로 구하여 손실을 고려한 Duty비를 찾아 낼 수 있다. 스위칭 손실의 경우 데이터 시트에 주어진 손실 그래프를 테스트 영역까지 1차 근사하여 사용함으로써 정확한 효율 측정이 가능하도록 하였다.

• 전력전자학회논문지
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• 제16권4호
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• pp.326-333
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• 2011

본 논문에서는 Plug-in Hybrid Electric Vehicles (PHEVs)의 배터리 충전을 위해 필요한 추가적인 충전기 없이, 구동모터의 인덕턴스와 구동 드라이버인 3상 인버터를 이용하는 배터리 충전 기법들을 소개한다. 모터의 코일을 승압용 에너지 저장장치로 사용하고 인버터 스위치 제어를 통해 부스트 컨버터로 동작되도록 하여 추가적인 충전기를 제거함으로써, 충전장치가 차지하는 부피, 무게 및 단가를 저감할 수 있다. PHEVs의 시스템 구조와 제어기 구성에 따라 분류된 다양한 배터리 충전 기법들을 비교분석하고 시뮬레이션 결과를 통해 검증한다.

• 전력전자학회논문지
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• 제21권5호
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• pp.381-387
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• 2016

Many efforts have focused on the improvement of power density and efficiency by downsizing the motor and inverter. Recently, Toyota, Honda, and GM realized that the compact-sized motor uses the hairpin structure with increased space factor. Reducing the maximum torque from high-speed technique also makes it possible to design the high-power density model. Toyota and Honda used the newly developed power semiconductor IGBT to decrease conduction loss for high-efficiency inverter. In particular, Toyota used the boost converter to increase the DC link voltage for high efficiency in low-torque high-speed region. Toyota and GM also used the double-sided cooling structure for miniaturization of inverter for high-power density.