Sunghoon Lim

Sunghoon Lim
Ulsan National Institute of Science and Technology | UNIST · Department of Industrial Engineering

Doctor of Philosophy

About

20
Publications
2,549
Reads
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200
Citations
Additional affiliations
August 2018 - February 2019
Ulsan National Institute of Science and Technology
Position
  • Professor (Assistant)
September 2017 - November 2017
Pennsylvania State University
Position
  • Lecturer
Description
  • EDSGN 100 Introduction to Engineering Design (Instructor: Dr. Conrad S. Tucker): Three guest lectures in Fall 2017
October 2016 - May 2018
Pennsylvania State University
Position
  • Research Assistant
Description
  • Phase 2: I/UCRC for Center for Healthcare Organization Transformation (CHOT), (Sponsor: National Science Foundation)
Education
January 2014 - May 2018
Pennsylvania State University
Field of study
  • Industrial Engineering
August 2012 - December 2013
University of Pittsburgh
Field of study
  • Industrial Engineering
March 2006 - January 2009
Korea Advanced Institute of Science and Technology
Field of study
  • Industrial and Systems Engineering

Publications

Publications (20)
Article
Full-text available
Introduction: The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a communicable disease that has not yet been formalized by national public health institutes and explicitl...
Article
The authors of this work propose an algorithm that determines optimal search keyword combinations for querying online product data sources in order to minimize identification errors during the product feature extraction process. Data-driven product design methodologies based on acquiring and mining online product-feature-related data are presented...
Article
This paper considers a problem of locating both distribution centers and retailers in a zone-dependent two-level distribution network where either a distribution center or a retailer should be located in each zone. Customer demands of each zone should be satisfied directly from either its own distribution center or its own retailer being supplied f...
Article
Full-text available
Crowdsourcing has become an important tool for gathering knowledge for urban planning problems. The questions posted to the crowd for urban planning problems are quite different from the traditional crowdsourcing models. Unlike the traditional crowdsourcing models, due to the constraints among the multiple components (e.g., multiple locations of fa...
Article
Full-text available
Detecting and preventing industrial machine failures are significant in the modern manufacturing industry because machine failures substantially increase both maintenance and manufacturing costs. Recently, state-of-the-art deep learning techniques that use acoustic signals have been widely applied to solve industrial machine malfunction detection p...
Article
Full-text available
Every year, maritime accidents cause severe damages not only to humans but also to maritime instruments like vessels. The authors of this work therefore propose a machine learning-based maritime accident prediction system that can be used to prevent maritime accidents from happening by predicting and interpreting the accidents. This work overcomes...
Article
Full-text available
Cryptocurrency has recently attracted substantial interest from investors due to its underlying philosophy of decentralization and transparency. Considering cryptocurrency’s volatility and unique characteristics, accurate price prediction is essential for developing successful investment strategies. To this end, the authors of this work propose a n...
Article
Full-text available
The explosion of online information with the recent advent of digital technology in information processing, information storing, information sharing, natural language processing, and text mining techniques has enabled stock investors to uncover market movement and volatility from heterogeneous content. For example, a typical stock market investor r...
Article
Full-text available
The authors of this work propose a deep learning-based fault detection model that can be implemented in the field of plastic injection molding. Compared to conventional approaches to fault detection in this domain, recent deep learning approaches prove useful for on-site problems involving complex underlying dynamics with a large number of variable...
Article
The author proposes a time series model that predicts future values of various types of liquid cargo traffic based on long short-term memory (LSTM), a deep learning technique. Existing liquid cargo traffic prediction models are based on traditional time series models, such as autoregressive integrated moving average (ARIMA) and vector autoregressio...
Article
Due to the increase in motor vehicle accidents, there is a growing need for high-performance car crash detection systems. The authors of this research propose a car crash detection system that uses both video data and audio data from dashboard cameras in order to improve car crash detection performance. While most existing car crash detection syste...
Article
Full-text available
An anomaly-based intrusion detection system (A-IDS) provides a critical aspect in a modern computing infrastructure since new types of attacks can be discovered. It prevalently utilizes several machine learning algorithms (ML) for detecting and classifying network traffic. To date, lots of algorithms have been proposed to improve the detection perf...
Article
Intrusion detection systems (IDSs) are intrinsically linked to a comprehensive solution of cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design an improved detection framework is sought after, particularly when utilizing ensemble learners. Designing an ensemble often lies in two main challenges such as the...
Article
Full-text available
Classification algorithms are widely taken into account for clinical decision support systems. However, it is not always straightforward to understand the behavior of such algorithms on a multiple disease prediction task. When a new classifier is introduced, we, in most cases, will ask ourselves whether the classifier performs well on a particular...
Article
Full-text available
Crowdsourcing has already been shown to be a promising tool in solving many real-life problems in time and cost-effective way. For example, in city planning, to install some specific facilities it is required to acquire knowledge about various factors like demand, demographic information, suitability of the resources in that area, etc. However, obt...
Article
The authors present an expert and intelligent system that (1) identifies influential term groups having causal relationships with real-world enterprise outcomes from Twitter data and (2) quantifies the appropriate time lags between identified influential term groups and enterprise outcomes. Existing expert and intelligent systems, which are defined...
Article
Due to the increasing global availability of the internet, online learning platforms such as Massive Open Online Courses (MOOCs), have become a new paradigm for distance learning in engineering education. While interactions between instructors and students are readily observable in a physical classroom environment, monitoring student engagement is...
Article
Recently, social media has emerged as an alternative, viable source to extract large-scale, heterogeneous product features in a time and cost-efficient manner. One of the challenges of utilizing social media data to inform product design decisions is the existence of implicit data such as sarcasm, which accounts for 22.75% of social media data, and...
Article
The authors of this work present a model that reduces product rating biases that are a result of varying degrees of customers' optimism/pessimism. Recently, large-scale customer reviews and numerical product ratings have served as substantial criteria for new customers who make their purchasing decisions through electronic word-of-mouth. However, d...
Conference Paper
Full-text available
Due to the internet’s increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest...

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