Papers by Taechoong Chung
Journal of Earthquake Engineering, 2021
This research proposes a surrogate model to predict the seismic response of individual structural... more This research proposes a surrogate model to predict the seismic response of individual structural elements in structures whose inherent vertical and horizontal irregularities result in components w...
2021 2nd Asia Conference on Computers and Communications (ACCC), 2021
Healthcare service delivery has been greatly impacted by the current Covid-19 pandemic. One of th... more Healthcare service delivery has been greatly impacted by the current Covid-19 pandemic. One of the key drawbacks of the current Healthcare Management Information Systems (HMIS) is the lack of research towards improving the user's experience before, during, or after interacting with the digital system, product, or service. This has further increased the amount of cognitive load experienced by healthcare providers. Adaptive Digital Encounters (ADE) provide a mechanism for dynamically generating and upgrading the user interfaces of healthcare and wellness applications, by incorporating past histories of the patient data. It also integrates various medical devices to automate the process of collecting vital signs and reduces the burden of inserting data. This paper provides the basic building blocks which were employed to incorporate the ADE into a live application. Our results indicate an above-average score of 1.13 (-3 to +3) using the UEQ-S questionnaire, indicating a positive UX evaluation from 11 participants.
2018 18th International Conference on Control, Automation and Systems (ICCAS), 2018
This paper improves the method for learning a bicycle which can itself balance and go to any spec... more This paper improves the method for learning a bicycle which can itself balance and go to any specified locations. The bicycle is controlled by a neural network policy which is learned by deep deterministic policy gradient algorithm (DDPG). We propose a procedure which allows the controller can be gradually learned until it can stably balance and lead the bicycle to any specified places.
Smart city solutions are often formulated as adaptive optimization problems in which a cost objec... more Smart city solutions are often formulated as adaptive optimization problems in which a cost objective function w.r.t certain constraints is optimized using off-the-shelf optimization libraries. Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is an efficient derivative-free optimization algorithm where a black-box objective function is defined on a parameter space. This modeling makes its performance strongly depends on the quality of chosen features. This paper considers modeling the input space for optimization problems in reproducing kernel Hilbert spaces (RKHS). This modeling amounts to functional optimization whose domain is a function space that enables us to optimize in a very rich function class. Our CMA-ES-RKHS framework performs black-box functional optimization in the RKHS. Adaptive representation of the function and covariance operator is achieved with sparsification techniques. We evaluate CMA-ES-RKHS on simple functional optimization problems which are motivate...
In this paper, we suggest an experiment environment that considers actuality and new capture stra... more In this paper, we suggest an experiment environment that considers actuality and new capture strategy that using direction vector to solve prey pursuit problem that is typical experiment model of multi agent system. General prey pursuit problem used capture strategy between agents from limited grid space. But, this causes actuality deficiency problem of experiment environment itself. Also, in prey pursuit problem, there are a lot of problems such as occurrence of collision between agents, imperfection capture that can be produced from corner of restricted grid space. Therefore, we proposed continuous experiment space of grid space of circular type that is environment similar to the actuality world in this paper, and agents in proposed experiment space solved prey pursuit problem through direction vector that uses distance information and direction information between each others. The proposed method could capture prey effectively through using direction vector in new environment, an...
In this paper, the Q-Learning based univector field method is proposed for mobile robot to accomp... more In this paper, the Q-Learning based univector field method is proposed for mobile robot to accomplish the obstacle avoidance and the robot orientation at the target position. Univector field method guarantees the desired posture of the robot at the target position. But it does not navigate the robot to avoid obstacles. To solve this problem, modified univector field is used and trained by Q-learning. When the robot following the field to get the desired posture collides with obstacles, univector fields at collision positions are modified according to the reinforcement of Q-learning algorithm. With this proposed navigation method, robot navigation task in a dynamically changing environment becomes easier by using double action Qlearning [8] to train univector field instead of ordinary Qlearning. Computer simulations and experimental results are carried out for an obstacle avoidance mobile robot to demonstrate the effectiveness of the proposed scheme.
2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2017
Based on state-of-the-art deep reinforcement learning (Deep RL) algorithms, two controllers are p... more Based on state-of-the-art deep reinforcement learning (Deep RL) algorithms, two controllers are proposed to pass a ship through a specified gate. Deep RL is a powerful approach to learn a complex controller which is expected to adapt to different situations of systems. This paper explains how to apply these algorithms to ship steering problem. The simulation results show advantages of these algorithms in reproducing reliable and stable controllers.
The KIPS Transactions:PartB, 2004
2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)
Data Interoperability provides a bridge between information systems to store, exchange and consum... more Data Interoperability provides a bridge between information systems to store, exchange and consume heterogeneous data. In order to achieve this goal, schema maps provide the necessary foundations. Traditional solutions rely on expert generated rules, ontologies, and syntactic matching to identify the similarity between attributes in the various data schema. While previously we have presented the effectiveness of transformer based models and unsupervised learning to calculate attribute similarities, in this paper we present the additional application of a naive syntactic similarity measurement We have evaluated the results of agreement between the computed and human annotated results, in terms of Mathews Correlation Coefficient (MCC). These results indicate that on weighted comparison there is no positive effect of including naive syntactic similarity in addition to semantic similarity.
Journal of the Korea Society of Computer and Information, Oct 1, 2018
International Journal of Environmental Research and Public Health, 2021
Clinical decision support systems (CDSSs) represent the latest technological transformation in he... more Clinical decision support systems (CDSSs) represent the latest technological transformation in healthcare for assisting clinicians in complex decision-making. Several CDSSs are proposed to deal with a range of clinical tasks such as disease diagnosis, prescription management, and medication ordering. Although a small number of CDSSs have focused on treatment selection, areas such as medication selection and dosing selection remained under-researched. In this regard, this study represents one of the first studies in which a CDSS is proposed for clinicians who manage patients with end-stage renal disease undergoing maintenance hemodialysis, almost all of whom have some manifestation of chronic kidney disease–mineral and bone disorder (CKD–MBD). The primary objective of the system is to aid clinicians in dosage prescription by levering medical domain knowledge as well existing practices. The proposed CDSS is evaluated with a real-world hemodialysis patient dataset acquired from Kyung H...
2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM), 2021
The advent of digital era has brought great advances in the quality and accuracy of Bio medical s... more The advent of digital era has brought great advances in the quality and accuracy of Bio medical sensors and other physiological devices. Similarly, digital games have also witnessed massive improvements in their scale, mechanics, graphics, and reach, which has led to a fierce debate on their human and societal impact, especially in terms of identifying the correlation, if any, between the gamer and violent transgressors. From a pure technological perspective, it is thus imperative that advances in sensory technologies and machine learning are then utilized to build a model for identifying the stress experienced by the gamer, during any game session. Galvanic Skin Response(GSR), can act as a good indicator of this experienced stress, by measuring the change in skin conductance and skin resistance of the user. However, GSR data, in its raw form, is very much user dependent, often biased, and is difficult to analyze, as it gives a long term measure of the user behavior changes, based on skin precipitation. In this research work, we have collected user's perceived notion of stress along with sensory data from a GSR device, which was then analyzed using various machine learning models, before creating a majority voting based ensemble model for stress modeling. Showing comparable values of accuracy(63.39%) and precision(51.22%), our model was able to substantially increase the class recall rate for identifying stress (27.08%), from the individual approaches (0-8.95%).
Finding the minimum distance between two obstacles is very crucial for robot path planning and lo... more Finding the minimum distance between two obstacles is very crucial for robot path planning and localization, especially for the cleaning and industrial robots. Knowledge of minimum distance is needed for a mobile robot to avoid the obstacles and have the efficient trajectory. This problem has been solved in many different ways. In this paper we present an approach to find the minimum distance between two obstacles that leads to a computationally linear time solution O(pq) in the number of vertices producing minimum number of p and q. The algorithm performs in two phases. Model the obstacle first to build the efficient Bounding Volume Hierarchy (BVH) Tree by generating minimum number of potential points (p and q) to provide the minimum distance and then it finds the required minimum distance using the BVH tree. This method can also handle the case of non-convex objects.
Journal of Heuristics, 2021
In this paper, we propose a heuristic search algorithm based on maximum conflicts to find a weakl... more In this paper, we propose a heuristic search algorithm based on maximum conflicts to find a weakly stable matching of maximum size for the stable marriage problem with ties and incomplete lists. The key idea of our approach is to define a heuristic function based on the information extracted from undominated blocking pairs from the men’s point of view. By choosing a man corresponding to the maximum value of the heuristic function, we aim to not only remove all the blocking pairs formed by the man but also reject as many blocking pairs as possible for an unstable matching from the women’s point of view to obtain a solution of the problem as quickly as possible. Experiments show that our algorithm is efficient in terms of both execution time and solution quality for solving the problem.
Journal of Biomedical Informatics, 2021
Objective: Causality mining is an active research area, which requires the application of state-o... more Objective: Causality mining is an active research area, which requires the application of state-of-the-art natural language processing techniques. In the healthcare domain, medical experts create clinical text to overcome the limitation of well-defined and schema driven information systems. The objective of this research work is to create a framework, which can convert clinical text into causal knowledge.
IEEE Access, 2020
Chronic kidney disease (CKD) is one of the leading medical ailments in developing countries. Due ... more Chronic kidney disease (CKD) is one of the leading medical ailments in developing countries. Due to the limited healthcare infrastructure and the lack of trained human resources, the CKD problem aggravates if it is not addressed in its earlier stages. In this regard, the role of machine learning-based automated diagnosis systems plays a vital role to deal with the CKD problem. In most of the studies conducted on the automated CKD decision modeling, the main emphasis is given to enhancing the predictive accuracy of the system. In this study, we focus on the applicability challenges of automated decision systems taking CKD diagnosis as a case study within the purview of developing countries. In this regard, we propose a cost-sensitive ensemble feature ranking method that takes a more realistic approach to groupbased feature selection. Two candidate solutions are proposed for group-based feature selection to meet different objectives. Subsequently, both the candidate solutions are combined into a consolidated solution. It is pertinent to note that it is one of the first studies in which cost-sensitive ensemble feature ranking for non-overlapping groups is successfully demonstrated to achieve the stated objectives i.e. low-cost and high-accuracy solution. Based on an extensive set of experiments, we demonstrate that a cost-effective and accurate solution for the CKD problem can be obtained. The experimentation includes 7 well-known classification algorithms and 8 comparative feature selection methods to show the efficacy of the proposed approach. It is concluded that the applicability of the automated CKD systems can be enhanced by including the cost consideration into the objective space of the solution formulation. Therefore, a trade-off solution can be obtained that is cost-effective and yet accurate enough to serve as a CKD screening system. INDEX TERMS Ensemble feature ranking, cost-based feature selection, threshold selection, filter methods.
The KIPS Transactions:PartB, 2004
Ant Colony System(ACS) Algorithm is new meta-heuristic for hard combinational optimization proble... more Ant Colony System(ACS) Algorithm is new meta-heuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. Recently, various methods and solutions are proposed to solve optimal solution of graph coloring problem that assign to color for adjacency node(v, v) that they has not same color. In this paper introducing ANTCOL Algorithm that is method to solve solution by Ant Colony System algorithm that is not method that it is known well as solution of existent graph coloring problem. After introducing ACS algorithm and Assignment Type Problem, show the wav how to apply ACS to solve ATP And compare graph coloring result and execution time when use existent generating functions(ANT_Random, ANT_LF, ANT_SL, ANT_DSATUR, ANT_RLF method) with ANT_XRLF method that use XRLF that apply Randomize to RLF to solve ANTCOL. Also compare graph coloring result and execution time when use method to add re-search to ANT_XRLF(ANT_XRLF_R) with existent generating functions.
2016 International Conference on Advanced Computing and Applications (ACOMP), 2016
This paper proposes a bidirectional local search algorithm to find the egalitarian and the sex-eq... more This paper proposes a bidirectional local search algorithm to find the egalitarian and the sex-equal stable matchings in the stable marriage problem. Our approach simultaneously searches forward from the man-optimal stable matching and backwards from the woman-optimal stable matching until the search frontiers meet. By employing a breakmarriage strategy to find stable neighbor matchings of the current stable matching and moving to the best neighbor matching, the forward local search finds the solutions while moving towards the woman-optimal stable matching and the backward local search finds the solutions while moving towards the man-optimal stable matching. Simulations show that our proposed algorithm is efficient for the stable marriage problem.
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Papers by Taechoong Chung