Second Half of 2023

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

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...
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Extending StarGAN-VC to Unseen Speakers Using RawNet3 Speaker Representation

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...
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A Study on Classification Models for Predicting Bankruptcy Based on XAI

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

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...
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First Half of 2023

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

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

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

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...
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Context-Dependent Video Data Augmentation for Human Instance Segmentation

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...
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Second Half of 2022

Electric Power Demand Prediction Using Deep Learning Model with Temperature Data

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

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

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, ...
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Semantic Occlusion Augmentation for Effective Human Pose Estimation

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...
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First Half of 2022

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

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...
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De Novo Drug Design Using Self-Attention Based Variational Autoencoder

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...
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Automatic Adaptation Based Metaverse Virtual Human Interaction

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...
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Korean Morphological Analysis Method Based on BERT-Fused Transformer Model

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...
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Second Half of 2021

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

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

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...
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Unsupervised Abstractive Summarization Method that Suitable for Documents with Flows

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

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...
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First Half of 2021

Improving Fidelity of Synthesized Voices Generated by Using GANs

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

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

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...
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Korean Dependency Parsing Using Stack-Pointer Networksand Subtree Information

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 ...
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Second Half of 2020

Performance Improvement Method of Convolutional Neural Network Using Agile Activation Function

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...
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Digital Mirror System with Machine Learning and Microservices

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...
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Hybrid Learning for Vision-and-Language Navigation Agents

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...
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Clustering Performance Analysis of Autoencoder with Skip Connection

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...
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First Half of 2020

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

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

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...
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Estimating Gastrointestinal Transition Location Using CNN-based Gastrointestinal Landmark Classifier

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

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 ...
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Second Half of 2019

Enhanced Sound Signal Based Sound-Event Classification

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

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...
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Perceptual Generative Adversarial Network for Single Image De-Snowing

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...
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A Technique for Detecting Companion Groups from Trajectory Data Streams

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...
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First Half of 2019

Sentiment Analysis of Foot-and-Mouth Disease Using Tweet Text-Mining Technique

Due to the FMD(foot-and-mouth disease), the domestic animal husbandry and related industries suffer enormous damage every year. Although various academic researches related to FMD are ongoing, engineering studies on the social effects of FMD are very...
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A Study on the Identification of Open Source License Compatibility Violations

Open source software is used in various ways when developing new softwares all around the world. It requires rights and responsibilities as a form of an open source software license. Because the license is a contract between original software develop...
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Deep Neural Network-Based Scene Graph Generation for 3D Simulated Indoor Environments

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...
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Evaluation of Sentimental Texts Automatically Generated by a Generative Adversarial Network

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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All publications of KTSDE is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

KTSDE is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

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