Second Half of 2023

Optimizing LRU Lock Management in the Linux Kernel for Improving Parallel Write Throughout in Many-Core CPU Systems

Eun-Kyu Byun  Gibeom Gu  Kwang-Jin Oh  Jiwoo Bang
Modern HPC systems are equipped with many-core CPUs with dozens of cores. When performing parallel I/O in such a system, there is a limit to scalability due to the problem of the LRU lock management policy of the Linux system. The study proposes an i...

Effect Analysis of Data Imbalance for Emotion Recognition Based on Deep Learning

Hajin Noh  Yujin Lim
In recent years, as online counseling for infants and adolescents has increased, CNN-based deep learning models are widely used as assistance tools for emotion recognition. However, since most emotion recognition models are trained on mainly adult da...

Unlicensed Band Traffic and Fairness Maximization Approach Based on Rate-Splitting Multiple Access

Jeon Zang Woo  Kim Sung Wook
As the spectrum shortage problem has accelerated by the emergence of various services, New Radio-Unlicensed (NR-U) has appeared, allowing users who communicated in licensed bands to communicate in unlicensed bands. However, NR-U network users reduce ...

A Study on the Image/Video Data Processing Methods for Edge Computing-Based Object Detection Service

Jang Shin Won  Yong-Geun Hong
Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source...

A Study on Improving Performance of Software Requirements Classification Models by Handling Imbalanced Data

Jong-Woo Choi  Young-Jun Lee  Chae-Gyun Lim  Ho-Jin Choi
Software requirements written in natural language may have different meanings from the stakeholders’ viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because...

Extending StarGAN-VC to Unseen Speakers Using RawNet3 Speaker Representation

Bogyung Park  Somin Park  Hyunki Hong
Voice conversion, a technology that allows an individual’s speech data to be regenerated with the acoustic properties(tone, cadence, gender) of another, has countless applications in education, communication, and entertainment. This paper proposes a...

A Study on Classification Models for Predicting Bankruptcy Based on XAI

Jihong Kim  Nammee Moon
Efficient prediction of corporate bankruptcy is an important part of making appropriate lending decisions for financial institutions and reducing loan default rates. In many studies, classification models using artificial intelligence technology hav...

Detecting Common Weakness Enumeration(CWE) Based on the Transfer Learning of CodeBERT Model

Chansol Park  So Young Moon  R. Young Chul Kim
Recently the incorporation of artificial intelligence approaches in the field of software engineering has been one of the big topics. In the world, there are actively studying in two directions: 1) software engineering for artificial intelligence an...

First Half of 2023

Digital Twin-Based Communication Optimization Method for Mission Validation of Swarm Robot

Gwanhyeok Kim  Hanjin Kim  Junhyung Kwon  Beomsu Ha  Seok Haeng Huh  Jee Hoon Koo  Ho Jung Sohn  Won-Tae Kim
Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming f...

Development of a Real-Time Control & Management System with In-Vitro Diagnostic Medical Device for Dengue Fever

Changsun Ahn  Yongho Park  Jungdae Moon  Jongchan Park  Youngkon Seo  Allen Sohn  Yoonjong Choi  Yanghwa Ha  Bongsu Jung  Youngjoo Kim
Dengue virus transmission is a viral infection disease between humans and Aedes mosquitoes. Dengue is ubiquitous throughout the tropics and subtropical zones, where 1/3 of the global population live. The weather in Korea is also changing to subtropic...

Performance Evaluation Using Neural Network Learning of Indoor Autonomous Vehicle Based on LiDAR

Yonghun Kwon  Inbum Jung
Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative applicatio...

Post-Quantum Security Strength Evaluation through Implementation of Quantum Circuit for SIMECK

Song Gyeong Ju  Jang Kyung Bae  Sim Min Joo  Seo Hwa Jeong
Block cipher is not expected to be safe for quantum computer, as Grover's algorithm reduces the security strength by accelerating brute-force attacks on symmetric key ciphers. So it is necessary to check the post-quantum security strength by implemen...

A Code Clustering Technique for Unifying Method Full Path of Reusable Cloned Code Sets of a Product Family

Kim Taeyoung  Lee Jihyun  Kim Eunmi
Similar software is often developed with the Clone-And-Own (CAO) approach that copies and modifies existing artifacts. The CAO approach is considered as a bad practice because it makes maintenance difficult as the number of cloned products increases...

Towards Carbon-Neutralization: Deep Learning-Based Server Management Method for Efficient Energy Operation in Data Centers

Sang-Gyun Ma  Jaehyun Park  Yeong-Seok Seo
As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours ...

Proposal for Decoding-Compatible Parallel Deflate Algorithm by Inserting Control Header Composed of Non-Compressed Blocks

Jung Hoon Kim
For decoding-compatible parallel Deflate algorithm, this study proposed a new method of the control header being made in such a way that essential information for parallel compression and decompression are stored in the Disposed Bit Area (DBA) of th...

Context-Dependent Video Data Augmentation for Human Instance Segmentation

HyunJin Chun  JongHun Lee  InCheol Kim
Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame...

Second Half of 2022

Dynamic Resource Adjustment Operator Based on Autoscaling for Improving Distributed Training Job Performance on Kubernetes

Jinwon Jeong  Heonchang Yu
One of the many tools used for distributed deep learning training is Kubeflow, which runs on Kubernetes, a container orchestration tool. TensorFlow jobs can be managed using the existing operator provided by Kubeflow. However, when considering the di...

Automobile Cruise Control System Using PID Controller and Kalman Filter

Su Yeol Kim  Pyung Soo Kim
In this paper, the PID controller and Kalman filter are applied to improve the automobile cruise control in the environment with disturbance and noise, and the performance is verified through diverse simulation. First, a mathematical model for a auto...

A Study on the System for AI Service Production

Yong-Geun Hong
As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service p...

GPU Resource Contention Management Technique for Simultaneous GPU Tasks in the Container Environments with Share the GPU

Jihun Kang
In a container-based cloud environment, multiple containers can share a graphical processing unit (GPU), and GPU sharing can minimize idle time of GPU resources and improve resource utilization. However, in a cloud environment, GPUs, unlike CPU or m...

Electric Power Demand Prediction Using Deep Learning Model with Temperature Data

Hyoup-Sang Yoon  Seok-Bong Jeong
Recently, researches using deep learning-based models are being actively conducted to replace statistical-based time series forecast techniques to predict electric power demand. The result of analyzing the researches shows that the performance of the...

Grasping a Target Object in Clutter with an Anthropomorphic Robot Hand via RGB-D Vision Intelligence, Target Path Planning and Deep Reinforcement Learning

Ga Hyeon Ryu  Ji-Heon Oh  Jin Gyun Jeong  Hwanseok Jung  Jin Hyuk Lee  Patricio Rivera Lopez  Tae-Seong Kim
Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of r...

CKFont2: An Improved Few-Shot Hangul Font Generation Model Based on Hangul Composability

Jangkyoung Park  Ammar Ul Hassan  Jaeyoung Choi
A lot of research has been carried out on the Hangeul generation model using deep learning, and recently, research is being carried out how to minimize the number of characters input to generate one set of Hangul (Few-Shot Learning). In this paper, ...

Semantic Occlusion Augmentation for Effective Human Pose Estimation

Hyun-Jae Bae  Jin-Pyung Kim  Jee-Hyong Lee
Human pose estimation is a method of estimating a posture by extracting a human joint key point. When occlusion occurs, the joint key point extraction performance is lowered because the human joint is covered. The occlusion phenomenon is largely div...

First Half of 2022

Design and Evaluation of 32-Bit RISC-V Processor Using FPGA

Sungyeong Jang  Sangwoo Park  Guyun Kwon  Taeweon Suh
RISC-V is an open-source instruction set architecture which has a simple base structure and can be extensible depending on the purpose. In this paper, we designed a small and low-power 32-bit RISC-V processor to establish the base for research on RIS...

Teacher-Student Architecture Based CNN for Action Recognition

Yulan Zhao  Hyo Jong Lee
Convolutional neural network (CNN) generally uses two-stream architecture RGB and optical flow stream for its action recognition function. RGB frames stream display appearance and optical flow stream interprets its action. However, the standard metho...

Transfer Learning Technique for Accelerating Learning of Reinforcement Learning-Based Horizontal Pod Autoscaling Policy

Yonghyeon Jang  Heonchang Yu  SungSuk Kim
Recently, many studies using reinforcement learning-based autoscaling have been performed to make autoscaling policies that are adaptive to changes in the environment and meet specific purposes. However, training the reinforcement learning-based Hori...

A Study on the Blockchain-Based Access Control Using Random-List in Industrial Control System

Kang Myung Joe  Kim Mi Hui
Industrial control systems that manage and maintain various industries were mainly operated in closed environment without external connection, but with the recent development of the Internet and the introduction of ICT technology, the access to the i...

Performance Improvement Method of Fully Connected Neural Network Using Combined Parametric Activation Functions

Young Min Ko  Peng Hang Li  Sun Woo Ko
Deep neural networks are widely used to solve various problems. In a fully connected neural network, the nonlinear activation function is a function that nonlinearly transforms the input value and outputs it. The nonlinear activation function plays a...

De Novo Drug Design Using Self-Attention Based Variational Autoencoder

Piao Shengmin  Jonghwan Choi  Sangmin Seo  Kyeonghun Kim  Sanghyun Park
De novo drug design is the process of developing new drugs that can interact with biological targets such as protein receptors. Traditional process of de novo drug design consists of drug candidate discovery and drug development, but it requires a lo...

Automatic Adaptation Based Metaverse Virtual Human Interaction

Jin-Ho Chung  Dongsik Jo
Recently, virtual human has been widely used in various fields such as education, training, information guide. In addition, it is expected to be applied to services that interact with remote users in metaverse. In this paper, we propose a novel metho...

Korean Morphological Analysis Method Based on BERT-Fused Transformer Model

Changjae Lee  Dongyul Ra
Morphemes are most primitive units in a language that lose their original meaning when segmented into smaller parts. In Korean, a sentence is a sequence of eojeols (words) separated by spaces. Each eojeol comprises one or more morphemes. Korean morph...

Second Half of 2021

Hybrid All-Reduce Strategy with Layer Overlapping for Reducing Communication Overhead in Distributed Deep Learning

Daehyun Kim  Sangho Yeo  Sangyoon Oh
Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distri...

Optimized Implementation of Block Cipher PIPO in Parallel-Way on 64-bit ARM Processors

Si Woo Eum  Hyeok Dong Kwon  Hyun Jun Kim  Kyoung Bae Jang  Hyun Ji Kim  Jae Hoon Park  Gyeung Ju Song  Min Joo Sim  Hwa Jeong Seo
The lightweight block cipher PIPO announced at ICISC’20 has been effectively implemented by applying the bit slice technique. In this paper, we propose a parallel optimal implementation of PIPO for ARM processors. The proposed implementation enables ...

Equal Energy Consumption Routing Protocol Algorithm Based on Q-Learning for Extending the Lifespan of Ad-Hoc Sensor Network

Kim Ki Sang  Kim Sung Wook
Recently, smart sensors are used in various environments, and the implementation of ad-hoc sensor networks (ASNs) is a hot research topic. Unfortunately, traditional sensor network routing algorithms focus on specific control issues, and they can’t b...

Task Migration in Cooperative Vehicular Edge Computing

Sungwon Moon  Yujin Lim
With the rapid development of the Internet of Things(IoT) technology recently, multi-access edge computing(MEC) is emerged as a next-generation technology for real-time and high-performance services. High mobility of users between MECs with limited s...

Graph Reasoning and Context Fusion for Multi-Task, Multi-Hop Question Answering

Sangui Lee  Incheol Kim
Recently, in the field of open domain natural language question answering, multi-task, multi-hop question answering has been studied extensively. In this paper, we propose a novel deep neural network model using hierarchical graphs to answer effectiv...

Distracted Driver Detection and Characteristic Area Localization by Combining CAM-Based Hierarchical and Horizontal Classification Models

Sooyeon Go  Yeongwoo Choi
Driver negligence accounts for the largest proportion of the causes of traffic accidents, and research to detect them is continuously being conducted. This paper proposes a method to accurately detect a distracted driver and localize the most charact...

Unsupervised Abstractive Summarization Method that Suitable for Documents with Flows

Hoon-suk Lee  Soon-hong An  Seung-hoon Kim
Recently, a breakthrough has been made in the NLP area by Transformer techniques based on encoder-decoder. However, this only can be used in mainstream languages where millions of dataset are well-equipped, such as English and Chinese, and there is a...

A Study of Tram-Pedestrian Collision Prediction Method Using YOLOv5 and Motion Vector

Young-Min Kim  Hyeon-Uk An  Hee-gyun Jeon  Jin-Pyeong Kim  Gyu-Jin Jang  Hyeon-Chyeol Hwang
In recent years, autonomous driving technologies have become a high-value-added technology that attracts attention in the fields of science and industry. For smooth Self-driving, it is necessary to accurately detect an object and estimate its movemen...

First Half of 2021

High Quality Video Streaming System in Ultra-Low Latency over 5G-MEC

Jeongseok Kim  Jaeho Lee
The Internet including mobile networks is developing to overcoming the limitation of physical distance and providing or acquiring information from remote locations. However, the systems that use video as primary information require higher bandwidth f...

Fat Client-Based Abstraction Model of Unstructured Data for Context-Aware Service in Edge Computing Environment

Do Hyung Kim  Jong Hyeok Mun  Yoo Sang Park  Jong Sun Choi  Jae Young Choi
With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context informatio...

Performance Analysis of QUIC Protocol for Web and Streaming Services

Hye-Been Nam  Joong-Hwa Jung  Dong-Kyu Choi  Seok-Joo Koh
The IETF has recently been standardizing the QUIC protocol for HTTP/3 services. It is noted that HTTP/3 uses QUIC as the underlying protocol, whereas HTTP/1.1 and HTTP/2 are based on TCP. Differently from TCP, the QUIC uses 0-RTT or 1-RTT transmissi...

A New Incentive Based Bandwidth Allocation Scheme For Cooperative Non-Orthogonal Multiple Access

Kim Jong Won  Kim Sung Wook
Non Orthogonal Multiple Access (NOMA) is a technology to guarantee the explosively increased Quality of Service(QoS) of users in 5G networks. NOMA can remove the frequent orthogonality in Orthogonal Multiple Access (OMA) while allocating the power d...

Improving Fidelity of Synthesized Voices Generated by Using GANs

Moon-Ki Back  Seung-Won Yoon  Sang-Baek Lee  Kyu-Chul Lee
Although Generative Adversarial Networks (GANs) have gained great popularity in computer vision and related fields, generating audio signals independently has yet to be presented. Unlike images, an audio signal is a sampled signal consisting of discr...

C-COMA: A Continual Reinforcement Learning Model for Dynamic Multiagent Environments

Kyueyeol Jung  Incheol Kim
It is very important to learn behavioral policies that allow multiple agents to work together organically for common goals in various real-world applications. In this multi-agent reinforcement learning (MARL) environment, most existing studies have a...

LSTM(Long Short-Term Memory)-Based AbnormalBehavior Recognition Using AlphaPose

Hyun-Jae Bae  Gyu-Jin Jang  Young-Hun Kim  Jin-Pyung Kim
A person's behavioral recognition is the recognition of what a person does according to joint movements. To this end, we utilize computer vision tasks that are utilized in image processing. Human behavior recognition is a safety accident response se...

Korean Dependency Parsing Using Stack-Pointer Networksand Subtree Information

Yong-Seok Choi  Kong Joo Lee
In this work, we develop a Korean dependency parser based on a stack-pointer network that consists of a pointer network and an internal stack. The parser has an encoder and decoder and builds a dependency tree for an input sentence in a depth-first ...

Second Half of 2020

Design of a Lightweight Security Protocol Using Post Quantum Cryptography

Kyung Bae Jang  Min Joo Sim  Hwa Jeong Seo
As the IoT (Internet of Things) era is activated, a lot of information including personal information is being transmitted through IoT devices. For information protection, it is important to perform cryptography communication, and it is required to u...

Deployment and Performance Analysis of Data Transfer Node Cluster for HPC Environment

Wontaek Hong  Dosik An  Jaekook Lee  Jeonghoon Moon  Woojin Seok
Collaborative research in science applications based on HPC service needs rapid transfers of massive data between research colleagues over wide area network. With regard to this requirement, researches on enhancing data transfer performance between m...

Natural Language Processing Model for Data Visualization Interaction in Chatbot Environment

Sang Heon Oh  Su Jin Hur  Sung-Hee Kim
With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualiza...

Distributed Edge Computing for DNA-Based Intelligent Services and Applications: A Review

Temesgen Seyoum Alemayehu  We-Duke Cho
Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the val...

Performance Improvement Method of Convolutional Neural Network Using Agile Activation Function

Na Young Kong  Young Min Ko  Sun Woo Ko
The convolutional neural network is composed of convolutional layers and fully connected layers. The nonlinear activation function is used in each layer of the convolutional layer and the fully connected layer. The activation function being used in a...

Digital Mirror System with Machine Learning and Microservices

Myeong Ho Song  Soo Dong Kim
Mirror is a physical reflective surface, typically of glass coated with a metal amalgam, and it is to reflect an image clearly. They are available everywhere anytime and become an essential tool for us to observe our faces and appearances. With the a...

Hybrid Learning for Vision-and-Language Navigation Agents

Suntaek Oh  Incheol Kim
The Vision-and-Language Navigation(VLN) task is a complex intelligence problem that requires both visual and language comprehension skills. In this paper, we propose a new learning model for visual-language navigation agents. The model adopts a hybri...

Clustering Performance Analysis of Autoencoder with Skip Connection

In-su Jo  Yunhee Kang  Dong-bin Choi  Young B. Park
In addition to the research on noise removal and super-resolution using the data restoration (Output result) function of Autoencoder, research on the performance improvement of clustering using the dimension reduction function of autoencoder are acti...

First Half of 2020

CNN Architecture Predicting Movie Rating from Audience’s Reviews Written in Korean

Hyungchan Kim  Heung-Seon Oh  Duksu Kim
In this paper, we present a movie rating prediction architecture based on a convolutional neural network (CNN). Our prediction architecture extends TextCNN, a popular CNN-based architecture for sentence classification, in three aspects. First, charac...

Fully Automatic Heart Segmentation Model Analysis Using Residual Multi-Dilated Recurrent Convolutional U-Net

Sang Heon Lim  Myung Suk Lee
In this paper, we proposed that a fully automatic multi-class whole heart segmentation algorithm using deep learning. The proposed method is based on U-Net architecture which consist of recurrent convolutional block, residual multi-dilated convolutio...

Advanced FEC Scheme Considering Energy and Link-Quality for Solar-Powered WSNs

Gun Wook Gil  Minjae Kang  Dong Kun Noh
In Solar-powered wireless sensor networks(SP-WSN), the battery is periodically charged, so the best use of harvested energy is more important, rather than minimizing energy consumption. Meanwhile, as is well known, the reliability of communication be...

Proactive Caching Strategy Based on Optimal Content Distribution in Content Centric Vehicular Networks

Sungjin Park  Euisin Lee
In vehicular communications environment, content pre-caching can reduce the delay time from the user to the content server. However, the problem of where and how much pre-caching is still not solved. In this paper, based on the movement probability o...

Development of Application to Deal with Large Data Using Hadoop for 3D Printer

Kang Eun Lee  Sungsuk Kim
3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer’s operations. Facet, which is a small triangle, represents a small surfac...

Topic Analysis of the National Petition Site and Prediction of Answerable Petitions Based on Deep Learning

Woo Yun Hui  Hyon Hee Kim
Since the opening of the national petition site, it has attracted much attention. In this paper, we perform topic analysis of the national petition site and propose a prediction model for answerable petitions based on deep learning. First, 1,500 peti...

Estimating Gastrointestinal Transition Location Using CNN-based Gastrointestinal Landmark Classifier

Hyeon Woong Jang  Chang Nam Lim  Ye-Suel Park  Gwang Jae Lee  Jung-Won Lee
Since the performance of deep learning techniques has recently been proven in the field of image processing, there are many attempts to perform classification, analysis, and detection of images using such techniques in various fields. Among them, the...

An Energy Consumption Prediction Model for Smart Factory Using Data Mining Algorithms

Sathishkumar V E  Myeongbae Lee  Jonghyun Lim  Yubin Kim  Changsun Shin  Jangwoo Park  Yongyun Cho
Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's ...

Second Half of 2019

Transmission Latency-Aware MAC Protocol Design for Intra-Body Communications

Seungmin Kim  JongSung Park  JeongGil Ko
Intra-Body Communication (IBC) is a communication method using the human body as a communication medium. The fact that our human body consists of water and electrolyte allow such communication method could work and have strength in low-power. Howeve...

Parallelization of Genome Sequence Data Pre-Processing on Big Data and HPC Framework

Eun-Kyu Byun  Jae-Hyuck Kwak  Jihyeob Mun
Analyzing next-generation genome sequencing data in a conventional way using single server may take several tens of hours depending on the data size. However, in order to cope with emergency situations where the results need to be known within a few ...

Multi-Hop Vehicular Cloud Construction and Resource Allocation in VANETs

Hyunseok Choi  Youngju Nam  Euisin Lee
Vehicular cloud computing is a new emerging technology that can provide drivers with cloud services to enable various vehicular applications. A vehicular cloud is defined as a set of vehicles that share their own resources. Vehicles should collaborat...

Evaluation of Distributed Intrusion Detection System Based on MongoDB

HyoJoon Han  HyukHo Kim  Yangwoo Kim
Due to the development and increased usage of Internet services such as IoT and cloud computing, a large number of packets are being generated on the Internet. In order to create a safe Internet environment, malicious data that may exist among these ...

A Node2Vec-Based Gene Expression Image Representation Method for Effectively Predicting Cancer Prognosis

Jonghwan Choi  Sanghyun Park
Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients’ outcomes based on their g...

Perceptual Generative Adversarial Network for Single Image De-Snowing

Weiguo Wan  Hyo Jong Lee
Image de-snowing aims at eliminating the negative influence by snow particles and improving scene understanding in images. In this paper, a perceptual generative adversarial network based a single image snow removal method is proposed. The residual U...

A Technique for Detecting Companion Groups from Trajectory Data Streams

Suhyun Kang  Ki Yong Lee
There have already been studies analyzing the trajectories of objects from data streams of moving objects. Among those studies, there are also studies to discover groups of objects that move together, called companion groups. Most studies to discover...

First Half of 2019

Blockchain Based Financial Portfolio Management Using A3C

Ju-Bong Kim  Joo-Seong Heo  Hyun-Kyo Lim  Do-Hyung Kwon  Youn-Hee Han
In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have...

Distributed Processing System Design and Implementation for Feature Extraction from Large-Scale Malicious Code

Hyunjong Lee  Seongyul Euh  Doosung Hwang
Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and repla...

Machine Learning Approach for Pattern Analysis of Energy Consumption in Factory

Jong Hoon Sung  Yeong Sik Cho
This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, ma...

MSHR-Aware Dynamic Warp Scheduler for High Performance GPUs

Gwang Bok Kim  Jong Myon Kim  Cheol Hong Kim
Recent graphic processing units (GPUs) provide high throughput by using powerful hardware resources. However, massive memory accesses cause GPU performance degradation due to cache inefficiency. Therefore, the performance of GPU can be improved by re...

Enhanced Sound Signal Based Sound-Event Classification

Yongju Cho  Jonguk Lee  Daihee Park  Yongwha Chung
The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. I...

Deep Neural Network-Based Scene Graph Generation for 3D Simulated Indoor Environments

Donghyeop Shin  Incheol Kim
Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only objec...

Evaluation of Sentimental Texts Automatically Generated by a Generative Adversarial Network

Cheon-Young Park  Yong-Seok Choi  Kong Joo Lee
Recently, deep neural network based approaches have shown a good performance for various fields of natural language processing. A huge amount of training data is essential for building a deep neural network model. However, collecting a large size of ...

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