Seonwoo Kim

With the advent of 5G era, network slicing has received a great deal of attention as a means to support a variety of wireless services in a flexible manner. Network slicing is a technique to divide a single physical resource network into multiple slices supporting independent services. In beyond 5G (B5G) systems, the main goal of network slicing is to assign the physical resource blocks (RBs) such that the quality of service (QoS) requirements of eMBB, URLLC, and mMTC services are satisfied. Sin

This paper presents an artificial neural network (ANN) based approach to improve the speed of a differential equation based distance relaying algorithm. As the differential equation used for the transmission line protection is valid only at low frequencies, the distance relaying algorithm requires a lowpass filter, removing frequency components higher than those for relaying. However, the lowpass filter causes the time delay of the components for relaying. Thus, the calculated resistances and re

In this letter, we propose a deep learning-based technique to recover a Euclidean distance matrix <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</b> in IoT network localization. In contrast to conventional localization algorithms that search <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</b> over a whole set of matrices, the proposed technique, called multiple deep neural networks for localizati

Millimeter wave (mmWave) and terahertz (THz) communications have been considered as the key techniques to support extremely high data rates in the 6G system. One main limitation of the mmWave/THz communications is the severe path loss and low penetration power. For these reasons, it is expected that mmWave/THz communication will be mainly employed in the ultra-dense network (UDN) environment. In order to get the most out of the mmWave/THz UDN, a mobile should be associated to the base stations (

The purpose of this study was to increase the current understanding of the acoustic characteristics of voices with advancing age. The relationship between age-related changes in body physiology and certain acoustic characteristics of voice was studied in a sample of 80 men representing four chronological age groupings (20-29, 50-59, 60-69, 70-79) who were all of good physical condition. Each subject was asked to phonate the vowel /a/, /i/, and /u/ for as long as possible at comfortable frequency

A rendering regression is a bug introduced by a web browser where a web page no longer functions as users expect. Such rendering bugs critically harm the usability of web browsers as well as web applications. The unique aspect of rendering bugs is that they affect the presented visual appearance of web pages, but those web pages have no pre-defined correct appearance. Therefore, it is challenging to automatically detect errors in their appearance. In practice, web browser vendors rely on non-tri

Recently, terahertz (THz) communication supported by the ultra-dense network (UDN) has received a great deal of attention as a means to satisfy stringent requirements in throughput, latency, and energy consumption in 6G. In the UDN supported by THz beamforming, handover, an action to change the base station (BS) serving the user, occurs frequently due to the small cell coverage and sudden line-of-sight (LoS) link blockage caused by the interruption of obstacles. To ensure the seamless connectivi

A motion-based control interface promises flexible robot operations in dangerous environments by combining user intuitions with the robot's motor capabilities. However, designing a motion interface for non-humanoid robots, such as quadrupeds or hexapods, is not straightforward because different dynamics and control strategies govern their movements. We propose a novel motion control system that allows a human user to operate various motor tasks seamlessly on a quadrupedal robot. We first retarge

Background: Speech production requires accurate coordination of the speech musculature, and is dependent upon cooperation among cortical and subcortical structures. Multiple subcortical structures, including the basal ganglia,thalamus, and cerebellum, are involved in several parallel and segregated cortical-subcortical-cerebellum circuits. These circuits serve critical functions in integrating neural networks that modulate speech motor behaviors. Previous studies on speech disorders linked to su

Image-text retrieval is a task to search for the proper textual descriptions of the visual world and vice versa. One challenge of this task is the vulnerability to input image/text corruptions. Such corruptions are often unobserved during the training, and degrade the retrieval model’s decision quality substantially. In this paper, we propose a novel image-text retrieval technique, referred to as robust visual semantic embedding (RVSE), which consists of novel image-based and text-based augmenta

배경 및 목적: 고령화 사회 진입에 따른 퇴행성 신경질환의 유병률과 발병률 증가는 임상에서 효과적인 질환 중재의 방향 설정을 위한 감별 진단의 중요성을 부각시켰다. 본 연구는 퇴행성 신경질환의 마비말장애를 보고한 국외문헌을 수집하여 각 질환 별로 말특성을 기술하고, 개별적 말특성이 질환 간의 감별에 유용한 요소인지를 검토하였다. 방법: 50세를 기준으로 한 준고령자 이상의 연령층에서 뇌신경 손상을 동반하는 대표적 퇴행성 신경질환인 파킨슨병, 피질기저핵변성, 진행성 핵상마비, 다계통위축증, 그리고 전두측두엽치매 분야에 해당하는 논문들을 검색한 뒤, 이 자료에서 마비말장애를 보고한 관련 연구들을 정리하였다. 결과: 관련 퇴행성 신경질환 군에서 마비말장애 특성이 보고된 논문의 수는 1978년에서 2008년까지 총 58편이었다. 한 편의 논문에서 두 개 이상의 질환군이 언급된 경우는 개별 논문으로 취급하여 파킨슨병 42편, 피질기저핵변성 6편, 진행성 핵상마비 5편, 다계통위축증 3편, 그

Recent advances in sensing and computer vision (CV) technologies have opened the door for the application of deep learning (DL)-based CV technologies in the realm of 6G wireless communications. For the successful application of this emerging technology, it is crucial to have a qualified vision dataset tailored for wireless applications (e.g., RGB images containing wireless devices such as laptops and cell phones). An aim of this paper is to propose a large-scale vision dataset referred to as Vis

With the emergence of 5G era, network slicing has received much attention due to its ability to support various services. Network slicing is an approach to partition a single physical network into multiple slices supporting separate services and has been extended to the handover scenario (where the UE moves from one cell to another) recently. In this paper, we propose a deep reinforcement learning (DRL)-based handover-aware network slicing technique for the cell selection and network slicing. Ke

In this paper, we propose a technique to acquire the sensor map of Internet of Things (IoT) network. Our approach consists of two main steps to reconstruct the Euclidean distance matrix. First, we recast Euclidean distance matrix completion problem into the alternating minimization problem. We next employ a cascade of multiple deep neural networks to recover the location map of sensors (and the original distance matrix) from the noisy observed matrix. From the numerical experiments, we demonstra