Youngho Song

Lateral current spreading in GaN-based light-emitting diodes utilizing tunnel contact junctions

InGaN/GaN multiple-quantum-well light-emitting-diode structures utilizing tunnel contact junctions grown by metalorganic chemical vapor deposition have been demonstrated. The p+/n+ GaN tunnel junctions are located in the upper cladding layers of conventional devices, allowing n-type GaN instead of p-type GaN as a top contact layer. Thus, metal ohmic contacts are done at the same time on the top and the lower contact layers. The reverse-biased tunnel contact junction provides lateral current spreading without semitransparent electrode and spatially uniform luminescence exhibiting an improved radiative efficiency. The tunnel contact junction is shown to be an effective method to make possible hole injection via a lateral electron current, with only a small penalty in voltage drop compared to conventional devices.

Effect of indium composition on carrier escape in InGaN/GaN multiple quantum well solar cells

The influence of indium composition on carrier escape was studied considering recombination in InGaN/GaN multiple quantum well solar cells with indium compositions of 17% and 25%. Competition between tunneling and recombination turned out to act as a crucial role for the short-circuit current density (Jsc) and fill factor (FF). To enhance the Jsc and the FF, the tunneling-dominant carrier decay rather than recombination is required in the operating range of the solar cells which is possible by optimizing the band structures for a shorter tunneling time and by improving the crystalline quality for a longer recombination time.

Buried Tunnel Contact Junctions in GaN‐Based Light‐Emitting Diodes

InGaN/GaN multiple-quantum-well light-emitting diode structures utilizing tunnel contact junctions have been demonstrated. The heavily doped p + /n + GaN tunnel junctions are located in the upper cladding layers of conventional devices allowing n-type GaN instead of p-type GaN as a top contact layer. Accordingly, metal Ohmic contacts are performed at the same time on the upper and the lower contact layers. The reverse-biased thin tunnel contact junction provides lateral electron current spreading along the n + layer without the use of a semi-transparent electrode and spatially uniform luminescence exhibiting an improved radiative efficiency.

Improvement in Light Extraction Efficiency of 380 nm UV-LED Using Nano-patterned n-type Gan Substrate

Abstract Ultraviolet (UV) light emitting diodes (LEDs) were grown on a patterned n-type GaN substrate (PNS) with 200 nmsilicon-di-oxide (SiO2) nano pattern diameter to improve the light output efficiency of the diodes. Wet etched self assembledindium tin oxide (ITO) nano clusters serve as a dry etching mask for converting the SiO2 layer grown on the n-GaN templateinto SiO2 nano patterns by inductively coupled plasma etching. PNS is obtained by n-GaN regrowth on the SiO2 nano patternsand UV-LEDs were fabricated using PNS as a template. Two UV-LEDs, a reference LED without PNS and a 200 nm PNSUV-LEDs were fabricated. Scanning Electron microscopy (SEM), Transmission Electron Microscopy (TEM), X-Ray Diffraction(XRD), Photoluminescence (PL) and Light output intensity- Input current- Voltage (L-I-V) characteristics were used to evaluatethe ITO-SiO 2 nanopattern surface morphology, threading dislocation propagation, PNS crystalline property, PNS optical propertyand UVLED device performance respectively. The light out put intensity was enhanced by 1.6times@100mA for the LEDgrown on PNS compared to the reference LED with out PNS.Key wordspatterned n-GaN substrate, light extraction efficiency, InGaN, light-emitting diodes.

A Data Encryption Scheme Using Periodic Functions for Efficient Query Processing on Encrypted Data

Due to advancement in cloud computing technology, an order-preserving encryption schemes, called Programmable Order-Preserving Secure Index (POPIS), has been proposed. This scheme hides the original data while keeping the order of the encrypted values the same as that of the original data. So the service provider can perform query processing without decryption. However, because the encrypted data in POPIS is sorted by certain column values, it is weak to both order matching attacks and count attacks. To solve this problem, we propose a data encryption scheme using periodic functions. Our scheme generates encryption signatures based on data groups and periodic functions. With this, we can preserve the order of each data group and also can guarantee the data privacy. Finally, we show from the performance analysis that the proposed scheme is better in terms of the degree of privacy protection than the existing data encryption scheme.

A parallel computation of skyline using multiple regression analysis-based filtering on MapReduce

In the last decade, skyline query processing has become widely important because of its usefulness in decision making applications. Since the size of the datasets used for skyline query processing are huge, algorithms for MapReduce-based skyline query processing have been widely studied. However, existing algorithms suffer from low-filtering efficiency for local skyline computation, and unrealistically assume both uniform data distributions and dimensional independence. In this paper, we propose a parallel skyline query processing algorithm for MapReduce using multiple regression analysis. The goal of our algorithm is to efficiently find a set of skylines from a large dataset by reducing the number of candidates prior to the skyline computation. To develop the skyline computation algorithm on anti-correlated datasets, we computed a data filtering threshold line based on a multiple regression analysis of the sampled dataset. To guarantee the accuracy of the skyline result, we considered both a filtering threshold line and a grid-based cell dominance condition. Thus, only relevant data could be computed in the real skyline computation step. For local skyline computation, we utilized an angle-based partitioning of data space that effectively eliminates non-promising points in partitions. For the global skyline computation, we used the dominance relationship among grid-based partitions to prune out unnecessary skyline points. Performance analyses showed that our parallel skyline query processing algorithm outperformed existing algorithms, under various settings.

A Density-Aware Similarity Join Query Processing Algorithm on MapReduce

Recently, the amount of data is rapidly increasing and thus MapReduce has attracted much interest as a new paradigm for such data-intensive applications. Similarity join is an essential operation for data analytics, including record linkage, near duplicate detection, document clustering. However, the performance of MapReduce is limited when applied on complex data analytical task involving joins of multiple datasets. Hence, workload-aware data partitioning techniques are required, which ensure the balance of computation of each machine. In this paper, we propose a similarity join algorithm using MapReduce that provides scalability and high performance by using grid-based data mapping technique for joining datasets. From the experiment analysis, we prove that our algorithm outperforms the existing algorithm under various data size and similarity thresholds.

Design and Implementation of HDFS Data Encryption Scheme Using ARIA Algorithms on Hadoop

요 약 최근 스마트폰 기기의 보급 및 소셜 서비스 산업의 고도화로 인해, 빅데이터가 등장하였다. 한편 빅 데이터에서 효율적으로 정보를 분석하는 대표적인 플랫폼으로 하둡이 존재한다. 하둡은 클러스터 환경 에 기반한 우수한 확장성, 장애 복구 기능 및 사용자가 기능을 정의할 수 있는 맵리듀스 프레임워크 등을 지원한다. 아울러 하둡은 개인정보나 위치 데이터 등의 민감한 정보를 보호하기 위해 Kerberos를 통한 사용자 인증 기법을 제공하고, HDFS 압축 코덱을 활용한 AES 코덱 기반 데이터 암호화를 지원 하고 있다. 그러나 하둡 기반 소프트웨어를 사용하고 있는 국내 기관 및 기업은 국내 ARIA 데이터 암 호화를 적용하지 못하고 있다. 이를 해결하기 위해 본 논문에서는 하둡을 기반으로 ARIA 암호화를 지 원하는 HDFS 데이터 암호화 기법을 제안한다.

A New Query Integrity Verification Method for Encrypted Data in Database Outsourcing

In database outsourcing, two issues of data security emerge: data confidentiality and data integrity. Existing data transformation schemes were widely studied for preserving data confidentiality, but they are vulnerable to data leakage problem because they do not consider data distribution when encrypting data. Meanwhile, query authentication schemes verifying data integrity, suffer from transmission overhead for verification data. In this paper, we propose a privacy-aware query authentication scheme which guarantees the data confidentiality and the query result integrity of sensitive data. To solve the original data leakage problem, we propose a bitmap-based data transformation scheme with anchor selection based on data distribution. Also, we devise a query result authentication index that stores an encrypted signature for each anchor so that it can reduce the amount of auditing data. Through performance evaluation, we show that our scheme outperforms the state-of-the-art method in terms of query processing time and verification overhead.