Chang Wook Ahn

Chang Wook Ahn
Sungkyunkwan University | SKKU · Department of Computer Engineering

About

201
Publications
31,128
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6,816
Citations
Citations since 2016
79 Research Items
4333 Citations
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20162017201820192020202120220200400600
20162017201820192020202120220200400600
20162017201820192020202120220200400600
Introduction
Skills and Expertise

Publications

Publications (201)
Article
Accurate building energy consumption prediction is essential for achieving energy savings and boosting the HVAC system's efficiency of operations. Therefore, in this work, a novel ensemble predictive model, which combines the weighted linear aggregation of Gaussian process regression (GPR) and least squared boosted regression trees (LSB), leading t...
Article
Building energy consumption is heavily dependent on its heating load (HL) and cooling load (CL). Therefore, an efficient building demand forecast is critical for ensuring energy savings and improving the operating efficacy of the heating, ventilation, and air conditioning (HVAC) system. Modern and specialized energy-efficient building modeling tech...
Article
Full-text available
Control intelligence is a typical field where there is a trade-off between target objectives, and researchers in this field have longed for artificial intelligence that achieves the target objectives. Multi-objective deep reinforcement learning was sufficient to satisfy this need. In particular, multi-objective deep reinforcement learning methods b...
Article
Chemotherapy is one of the most extensively utilized cancer treatment strategies worldwide. It is intended to eliminate fast-developing cancer cells in a patient’s body. The amount of chemotherapeutic drug that must be administered precisely into a patient’s body determines the efficacy of the treatment and governs the patient survival during chemo...
Article
Full-text available
In the field of evolutionary algorithm music composition, most of the current researches focus on how to enhance environmental selection based on multi-objective evolutionary algorithms (MOEAs). However, the real music composition process defined as large-scale multi-optimization problems (LSMOP) involve the number of combinations, and the existing...
Article
Full-text available
A combined cycle power plant (CCPP) employs gas and steam turbines to generate 50% more power while utilizing the same fuel as a normal single cycle plant. The performance of a CCPP under full load is affected by a variety of factors such as weather, process interactions, and coupling, which makes it challenging to operate. Therefore, a reliable as...
Article
In this work, a robust image watermarking method is proposed based on the LWT (lifting wavelet transform) and DNN (Deep Neural Network). Watermark embedding uses wavelet transforms that help in maintaining a high value of imperceptibility and robustness. Different frequency bands are tested to find the optimum balance between robustness and imperce...
Article
Full-text available
Federated learning is a distributed learning algorithm designed to train a single server model on a server using different clients and their local data. To improve the performance of the server model, continuous communication with clients is required, and since the number of clients is very large, the algorithm must be designed in consideration of...
Article
Real-time strategy (RTS) games’ nature that, more complex than the turn-based, tabletop games such as Go, has been spotlighted in the field of artificial intelligence (AI) due to its similarity with real-world problems. In StarCraft II, agents cannot make decisions and control until they evaluate and compare the expected outcome of a choice. Among...
Article
Full-text available
While implementing Multiple Instance Learning (MIL) through Deep Neural Networks, the most important task is to design the bag-level pooling function that defines the instance-to-bag relationship and eventually determines the class label of a bag. In this article, Differential Evolutionary (DE) pooling—an MIL pooling function based on Differential...
Article
A new method for improving the optimization performance of a state-of-the-art differential evolution (DE) variant is proposed in this paper. The technique can increase the exploration by adopting the long-tailed property of the Cauchy distribution, which helps the algorithm generate a trial vector with great diversity. Compared to the previous appr...
Article
Full-text available
The global explosion of the COVID-19 pandemic has created worldwide unprecedented health and economic challenges which stimulated one of the biggest annual migrations globally. In the Indian context, even after proactive decisions taken by the Government, the continual growth of COVID-19 raises questions regarding its extent and severity. The prese...
Book
This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2020...
Article
Full-text available
The colossal increase in environmental pollution and degradation, resulting in ecological imbalance, is an eyecatching concern in the contemporary era. Moreover, the proliferation in the development of smart cities across the globe necessitates the emergence of a robust smart waste management system for proper waste segregation based on its biodegr...
Conference Paper
While implementing Multiple Instance Learning (MIL) through Deep Neural Networks, the most important task is to design the bag level pooling function which defines the instance-to-bag relationship and eventually determines the class label of a bag. In this article, an MIL pooling function based on Differential Evolution (DE) – a bio-inspired metahe...
Article
Full-text available
Digital watermarking has become an essential and important tool for copyright protection, authentication, and security of multimedia contents. It is the process of embedding a watermark in the multimedia content and its extraction. Block-based discrete cosine transform (DCT) is a widely used method in digital watermarking. This paper proposes a nov...
Article
Full-text available
Vulnerable nature of price forecasts, such as an unpredictability of future and numbers of socio-economic factors that affect market stability, often makes investment risky. Earlier studies in Finance suggested that constructing a portfolio can promise risk-spread gains. While Fund Standardization improved the traditional theories by reducing the c...
Article
Although Reinforcement learning has already been considered one of the most important and well-known techniques of machine learning, its applicability remains limited in the real-world problems due to its long initial learning time and unstable learning. Especially, the problem of an overwhelming number of the branching factors under real-time cons...
Article
This paper proposes a novel stereo matching method with a matching cost function learned from training data. Because the cost function includes a considerably large number of parameters required to select their values, it is nearly impossible to manually select the values. We employ an evolutionary algorithm to automatically optimize the parameter...
Preprint
A new method for improving the optimization performance of a state-of-the-art differential evolution (DE) variant is proposed in this paper. The technique can increase the exploration by adopting the long-tailed property of the Cauchy distribution, which helps the algorithm to generate a trial vector with great diversity. Compared to the previous a...
Article
Full-text available
In this paper, we propose a method to select parameter values for stereo matching methods. The proposed method was trained in a supervised manner, and an evolutionary algorithm is used to select optimized parameter values for a given domain and a cost function constructed to measure the goodness level of candidate parameter values. Performance of t...
Article
Full-text available
This paper proposes an unsupervised approach to construct a deep learning based stereo matching method using single-view videos (SMV). From videos, a set of corresponding points are computed between images, and image patches that center at the computed points are extracted. Negative and positive samples constitute a dataset to train a similarity ne...
Article
In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations....
Chapter
Reinforcement learning has remarkable achievements in areas such as GO, Game, and autonomous vehicles, and is attracting attention as the most promising future technology among neural network-based technique. In spite of its capability, Reinforcement learning suffers from its greedy nature that causes selective behaviors. This is because the agent...
Chapter
We present a novel neural architecture search space and its search strategy with an evolutionary algorithm. It aims to find a set of inverted bottleneck structure blocks, which takes a low-dimensional input representation followed by a compressing layer. Primitive operation layers constitute flexible inverted bottleneck blocks and can be assembled...
Article
Full-text available
Digital images have become easy to generate and share with tremendous growth in communication technology. Therefore, the threat of forgery and tampering in digital images has also been increased. This study proposes a blind fragile watermarking scheme for color images to provide efficient image tamper detection and self-recovery. A secret key based...
Article
Full-text available
In this paper, we propose a novel data augmentation method with respect to the target context of the data via self-supervised learning. Instead of looking for the exact synonyms of masked words, the proposed method finds words that can replace the original words considering the context. For self-supervised learning, we can employ the masked languag...
Conference Paper
Reinforcement learning in general is suitable for putting actions in a specific order within a short sequence, but in the long run its greedy nature leads to eventual incompetence. This paper presents a brief description and implementative analysis of Action Sequence which was designed to deal with such a "penny-wise and pound-foolish" problem. Bas...
Article
Full-text available
Stereo matching has been under development for decades and is an important process for many applications. Difficulties in stereo matching include textureless regions, occlusion, illumination variation, the fattening effect, and discontinuity. These challenges are effectively solved in recently developed stereo matching algorithms. A new imperfect r...
Article
Driving assistance systems in the automotive industry are constantly evolving and are already commercialized in various areas to provide consumers with safety and convenience. The recognition of driver’s propensity is a key factor that can greatly affect the performance of such a driving assist system, but it still has numbers of technical limitati...
Article
Differential Evolution (DE) algorithm is one of the popular evolutionary algorithms that is designed to find a global optimum on multi-dimensional continuous problems. In this paper, we propose a new variant of DE algorithm by combining a self-adaptive DE algorithm called dynNP-DE with Elite Opposition-Based Learning (EOBL) scheme. Since dynNP-DE a...
Preprint
Full-text available
Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality, by either selecting a subset of features or removing unrelated ones. This paper presents a new feature selection method...
Conference Paper
Real-time video game problems are very challenging because of short response times and numerous state space issues. As global companies and research institutes such as Google, Facebook, Intel and Carnegie Mellon university continue to develop Artificial Intelligence(AI) and participated in various Game AI competitions, many AI developers are implem...
Conference Paper
Differential Evolution (DE) is a robust optimization algorithm, but it suffers from the stagnation problem in which individuals may not escape from a local optimum. In this article, we proposed a new Cauchy mutation using multiple exponential recombination, self-adaptive parameter control, and linear failure threshold reduction. The proposed method...
Article
We propose a framework to detect lug position and orientation in robotics that is insensitive to the lug orientation, incorporating a proposed optimization based on the artificial bee colony genetic algorithm. Experimental results show that the proposed optimization method outperformed traditional artificial bee colony and other meta-heuristics in...
Article
Full-text available
Although Differential Evolution (DE) is a simple yet powerful evolutionary algorithm, it requires an adaptive parameter control to achieve its optimal performance. In this paper, DE with an adaptive parameter control using the \(\alpha\)-stable distribution is proposed. First, the proposed algorithm allocated a carefully calculated stable distribut...
Conference Paper
Artificial neural networks are a computational system, and usually, backpropagation algorithm is used for learning a task, because of its simplicity. However, backpropagation algorithm is likely to converge to a local minimum or saddle point, so that a global minimum may not be found. Differential Evolution (DE) is a simple yet powerful global opti...
Article
Full-text available
The ownership verification of digital images is possible by the help of image watermarking. Watermarking make the image secure towards unlawful use; but at the same time, it causes some information loss too. Medical and defense are few fields, where even a small change in data can be very problematic. So there is need of reliable and lossless water...
Article
In this letter, we integrate domain information into the original artificial bee colony algorithm to create a novel, neighbor-interactive bee colony algorithm. We use the Hamming distance measure to compute variable dependency between two binary variables and employ the Gini correlation coefficient to compute variable relation between integer varia...
Article
In this paper, we propose a multi-agent based art production framework. In existing artwork creation systems, images were generated using artificial life and evolutionary computation approaches. In artificial life, swarm intelligence or Boids model, and in evolutionary computation, genetic algorithm or genetic programming are commonly used to creat...
Article
Full-text available
Purpose Although Roux-en-Y (R-Y) reconstruction after distal gastrectomy has several advantages, such as prevention of bile reflux into the remnant stomach, it is rarely used because of the technical difficulty. This prospective randomized clinical trial aimed to show the efficacy of a novel method of R-Y reconstruction involving the use of 2 circu...
Article
Existing evolutionary approaches to automatic composition generate only a few melodies in a certain style that is specified by the setting of parameters or the design of fitness functions. Thus, their composition results cannot cover the various tastes of music. In addition, they are not able to deal with the multidimensional nature of music. This...
Article
Full-text available
The modernization of smart devices has emerged in exponential growth in data traffic for a high-capacity wireless network. 5G networks must be capable of handling the excessive stress associated with resource allocation methods for its successful deployment. We also need to take care of the problem of causing energy consumption during the dense dep...
Article
Probabilistic robustness evaluation is a promising approach to evolutionary robust optimization; however, high computational time arises. In this paper, we apply this approach to the Bayesian optimization algorithm (BOA) with a view to improving its computational time. To this end, we analyze the Bayesian networks constructed in BOA in order to ext...
Article
Full-text available
A new differential evolution (DE) algorithm is presented in this paper. The proposed algorithm monitors the evolutionary progress of each individual and assigns appropriate control parameters depends on whether the individual is successfully evolved or not. We conducted the performance evaluation on CEC 2014 benchmark problems and confirmed that th...
Article
Full-text available
This paper proposes a novel fragile watermarking approach for digital image tamper localization (TL) along with the self-recovery (SR) capability. The host image is first divided into blocks of size 4 × 4 and then, singular value decomposition is performed on each block. The trace of singular matrix is used to compute the TL bits for each block. Th...
Conference Paper
In any corporation and organizations, the owner wants to introduce a best and efficient security solution with low cost and wants to get the high efficiency. In this paper, we suggest a method to select the best security solution among various security solutions using multi-objective genetic algorithm that considers the trade-off between cost and s...
Conference Paper
In this paper, we proposed a multi-agent system for creating art that can produce a set of abstract and complex style images given an input image. The proposed system consists of Boids, and each Boid object contains the genetic programming trees and neural networks. The role of genetic programming is to create unique color patterns, which will be e...
Article
In this paper, a new approach to grammatical evolution is presented. The aim is to generate complete programs using probabilistic modeling and sampling of (probability) distribution of given grammars. To be exact, probabilistic context free grammars are employed and a modified mapping process is developed to create new individuals from the distribu...
Article
We present a new univariate model based grammatical evolution (UMBGE) that performs automatic program generation in accordance with the given probabilistic context-free grammars. To this end, we evolve a population of candidate solutions comprised of genotypic real-coded strings and employ a mapping process in order to translate from genotypes (i.e...
Article
Operating swarm robots has the virtues of improved performance, fault tolerance, distributed sensing, and so on. The problem is, high overall system costs are the main barrier in managing a system of foraging swarm robots. Moreover, its control algorithm should be scalable and reliable as the foraging (search) spaces become wider. This paper analyz...
Article
Nature-inspired meta-heuristics have gained popularity for the solution of many real world complex problems, and the artificial bee colony algorithm is one of the most powerful optimisation methods among the meta-heuristics. However, a major drawback prevents the artificial bee colony algorithm from accurately and efficiently finding final solution...
Article
In this paper, we proposed a evolutionary music composition method based on a reference song. The proposed system automatically compose melody which is similar style with the reference. Hardwired fitness function which is independent to specific style, guarantees a quality of the compositions. Extracted features from the reference song adjust the p...
Article
The cleaning robot is popularly used as a home appliance. The state-of-the-art cleaning robot can clean more efficiently by using information gathered from its sensor, which is difficult for low-price cleaning robots due to limitation in this aspect. In this paper, we suggested a method for the moving pattern of cleaning robot based on grammatical...
Article
Watermarking is used to protect the copyrighted materials from being misused and help us to know the lawful ownership. The security of any watermarking scheme is always a prime concern for the developer. In this work, the robustness and security issue of IWT (integer wavelet transform) and SVD (singular value decomposition) based watermarking is ex...
Article
Digital image watermarking is one the powerful means to find out the unauthorized use of copyrighted images. It inserts secret information (watermark) into the host image that helps in finding the rightful ownership of image. SVD (singular value decomposition) based watermarking is known for providing high capacity, robustness an imperceptibility b...
Article
Full-text available
Digital image watermarking is the process of concealing secret information in a digital image for protecting its rightful ownership. Most of the existing block based singular value decomposition (SVD) digital watermarking schemes are not robust to geometric distortions, such as rotation in an integer multiple of ninety degree and image flipping, wh...
Article
In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that...
Chapter
The present study proposed a robust and secure watermarking scheme to authenticate the digital images for ownership claim. The proposed watermarking scheme is making use of 2-level of DWT (Discrete wavelet transform) to provide high capacity of watermark embedding. The SVD (singular value decomposition) is performed on the host and watermark images...
Article
Full-text available
Driving tendency recognition is important for constructing Advanced Driver Assistance Systems (ADAS). However, it had not been a lot of research using vehicle sensing data, due to the high difficulty to define it. In this paper, we attempt to improve the learning capability of a machine learning method using evolutionary computation. We propose a d...