Jason Teo

Jason Teo
Universiti Malaysia Sabah (UMS) | ums · Faculty of Computing and Informatics

Doctor of Information Technology

About

166
Publications
24,839
Reads
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1,568
Citations
Citations since 2016
43 Research Items
865 Citations
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2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250

Publications

Publications (166)
Article
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Data redundancy or fusion is one of the common issues associated with the resource-constrained networks such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). To resolve this issue, numerous data aggregation or fusion schemes have been presented in the literature. Generally, it is used to decrease the size of the collected data and,...
Article
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Context Eye tracking is a technology to measure and determine the eye movements and eye positions of an individual. The eye data can be collected and recorded using an eye tracker. Eye-tracking data offer unprecedented insights into human actions and environments, digitizing how people communicate with computers, and providing novel opportunities t...
Article
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Emotions are viewed as an important aspect of human interactions and conversations, and allow effective and logical decision making. Emotion recognition uses low-cost wearable electroencephalography (EEG) headsets to collect brainwave signals and interpret these signals to provide information on the mental state of a person, with the implementation...
Article
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The IoT refers to the interconnection of things to the physical network that is embedded with software, sensors, and other devices to exchange information from one device to the other. The interconnection of devices means there is the possibility of challenges such as security, trustworthiness, reliability, confidentiality, and so on. To address th...
Article
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The increase of mental health problems and the need for effective medical health care have led to an investigation of machine learning that can be applied in mental health problems. This paper presents a recent systematic review of machine learning approaches in predicting mental health problems. Furthermore, we will discuss the challenges, limitat...
Article
Data integrity and authenticity are among the key challenges faced by the interacting devices of Internet of Things (IoT). The resource-constrained nature of sensor-embedded devices make it even more difficult to design lightweight security schemes for these networks. In view of limited resources of the IoT devices, this paper proposes a lightweigh...
Article
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The following research describes the potential of using a four-class emotion classification using a four-channel wearable EEG headset combined with VR for evoking emotions from each individual. Multiple researchers have conducted and established emotion recognition by using a 2-D monitor screen for stimulus responses but this introduces artifacts s...
Article
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This paper presented a preliminary investigation of a novel approach on emotion recognition using pupil position in Virtual Reality (VR). We explore pupil position as an eye-tracking feature for four-class emotion classification according to the four-quadrant model of emotions via a presentation of 360° videos in VR. A total of ten subjects partici...
Article
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Background Emotion prediction is a method that recognizes the human emotion derived from the subject’s psychological data. The problem in question is the limited use of heart rate (HR) as the prediction feature through the use of common classifiers such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Random Forest (RF) in emotion pred...
Article
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Design is a challenging task that is crucial to all product development. Advances in design computing may allow machines to move from a supporting role to generators of design content. Generative Design systems produce designs by algorithms and offer the potential for the exploration of vast design spaces, the fostering of creativity, the combinati...
Article
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Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions bet...
Article
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Background Emotion classification remains a challenging problem in affective computing. The large majority of emotion classification studies rely on electroencephalography (EEG) and/or electrocardiography (ECG) signals and only classifies the emotions into two or three classes. Moreover, the stimuli used in most emotion classification studies utili...
Article
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This paper reviews emotion classification investigations, focusing on the use of the Electrocardiogram (ECG) and Electrodermography (EDG)/Galvanic Skin Response (GSR) as input features. Currently, a large majority of emotion classification studies utilize Electroencephalograms (EEG) and facial expression recognition to perform emotion classificatio...
Article
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Emotion recognition and classification has become a popular topic of research among the area of computer science. In this paper, we present on the emotion classification approach using eye-tracking data solely with machine learning in Virtual Reality (VR). The emotions were classified into four distinct classes according to the Circumplex Model of...
Article
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The main objective of this paper is to conduct three experiments using Support Vector Machine (SVM) with different parameter settings to find and compare the accuracy of each SVM setting. Heart rate (HR) signals were collected with a medical-grade wearable heart rate monitor from Empatica (E4 Wristband) and processed using the Empatica Realtime Mon...
Article
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The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in...
Chapter
A novel method to generate memory aids for general forms of knowledge is presented. Mnemonic phrases are constructed using constraints of phonetic similarity to learning material, grammar, semantics, and factual consistency. The method has been implemented in Python using the CMU Pronouncing Dictionary, the CYC AI knowledge base, and Kneser-Ney 5-g...
Chapter
Human preferences play a key role in numerous decision-making processes. The ability to correctly identify likes and dislikes would facilitate novel applications in neuromarketing, affective entertainment, virtual rehabilitation and forensic neuroscience that leverage on sub-conscious human preferences. In this neuroinformatics investigation, we se...
Conference Paper
The use of machine learning approaches to detecting the human emotion of excitement via electroencephalography (EEG) while immersed in an immersive virtual reality environment is studied in this investigation. The ability to detect excitement has many potential applications such as in affective entertainment, neuromarketing and particularly in virt...
Article
Full-text available
Human emotions play a key role in numerous decision-making processes. The ability to correctly identify likes and dislikes as well as excitement and boredom would facilitate novel applications in neuromarketing, affective entertainment, virtual rehabilitation and forensic neuroscience that leverage on sub-conscious human affective states. In this n...
Article
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Two Crossover-first Differential Evolution (XDE) algorithms as well as four self-adaptive DE algorithms are compared in this study in terms of their optimization accuracy for solving a set of 15 complex, non-linear numerical optimization functions across 4 different dimensions of 10, 30, 50 and 100 optimization variables. XDE is a crossover-first v...
Article
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This paper demonstrates the significance of rule-based procedural generation of items in Role-Playing Game (RPG). The main aims of this project are to: implement rule-based randomized algorithm and totally randomized algorithm in generating item procedurally in RPG, and then compare the advantageous of rule-based randomized algorithm against totall...
Conference Paper
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Electroencephalogram (EEG)-based emotion classification is rapidly becoming one of the most intensely studied areas of brain-computer interfacing (BCI). The ability to passively identify yet accurately correlate brainwaves with our immediate emotions opens up truly meaningful and previously unattainable human-computer interactions such as in forens...
Article
This study conducts a scalability analysis of the popular evolutionary optimization algorithm known as Differential Evolution (DE) as implemented using a fixed parameter scheme versus four different self-adaptive parameter tuning schemes. This represents the first systematic and thorough investigation on how these different parameter tuning methods...
Article
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Differential Evolution (DE) is currently one of the most popular evolutionary-based global optimization algorithms being simple to understand and implement as well as having fast convergence and robustness across a wide range of problems. Although it is classed as an evolutionary algorithm (EA), its genetic operations are atypical of such classes o...
Article
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In this paper, we describe a research project that autonomously localizes and recognizes non-standardized Malaysian’s car plates using conventional Backpropagation algorithm (BPP) in combination with Ensemble Neural Network (ENN). We compared the results with the results obtained using simple Feed-Forward Neural Network (FFNN). This research aims t...
Article
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Parameter searching is one of the most important aspects in getting favorable results in optimization problems. It is even more important if the optimization problems are limited by time constraints. In a limited time constraint problems, it is crucial for any algorithms to get the best results or near-optimum results. In a previous study, Differen...
Article
Although the Differential Evolution (DE) algorithm is a powerful and commonly used stochastic evolutionary-based optimizer for solving non-linear, continuous optimization problems, it has a highly unconventional order of genetic operations when compared against canonical evolutionary-based optimizers whereby in DE, mutation is conducted rst before...
Article
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Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of...
Article
The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. The DE algorithm generates new candidate solutions by first conducting the mutation operation which is then followed by the crossover operation. This order of gene...
Article
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This paper demonstrates the research results obtained from a comparison of Evolutionary Programming (EP) and hybrid Differential Evolution (DE) and Feed Forward Neural Network (FFNN) algorithms in the Real Time Strategy (RTS) computer game, namely Warcraft III. The main aims of this research are to: test the feasibility of implementing EP and hybri...
Article
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AbstrakTeknik Kecerdasan Buatan (AI) berjaya digunakan dan diaplikasikan dalam pelbagai bidang, termasukpembuatan, kejuruteraan, ekonomi, perubatan dan ketenteraan. Kebelakangan ini, terdapat minat yangsemakin meningkat dalam Permainan Kecerdasan Buatan atau permainan AI. Permainan AI merujukkepada teknik yang diaplikasikan dalam permainan komputer...
Conference Paper
This paper presents the methodology from evolving a climbing Six Articulated-Wheeled Robot (SAWR) to realizing the simulation result for physical-testing with 3D printing fabrication. The design of the SAWR is obtained from a single-objective evolution process where the morphology of a climbing SAWR is optimized (minimized). The fittest SAWR obtain...
Article
This paper proposed an evolution method in designing the morphology of a six legged-wheeled hybrid mobile robot which has the ability to climb over obstacles. A single objective evolution algorithm has been proposed to obtain an optimized morphology of a six legged-wheeled hybrid mobile robot with a smaller body while having best performance to cli...
Article
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Emotion is an important part of human and it plays important role in human communication. Nowadays, as the use of machine getting more common, the human computer interaction (HCI) has become important. The understanding of user could bring across a better aiding machine. The exploration of using EEG in understanding human is widely studied for bene...
Article
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The design, programming and deployment of autonomous mobile robots is a highly complex, time-consuming and expensive endeavor. In this research, we propose an approach which combines evolutionary robotics with 3D printing as an approach for rapid and cheaper method for the fabrication of autonomous mobile robots. We have purposefully chosen the dom...
Article
This study investigates on aesthetics preference measurement of human using electroencephalogram (EEG) for virtual motion 3D shapes. The 3D shapes are generated using the Gielis superformula in bracelet-like shapes. EEG signals were collected by using a wireless medical grade EEG device, B-Alert X10 from Advance Brain Monitoring. Wavelet transforms...
Conference Paper
This paper proposed a multi-objective evolutionary algorithm (MOEA) in designing the morphology of a six articulated-wheeled robot (SAWR) which has the ability to perform climbing motion. The first objective is to minimize the morphology design while the second objective is to maximize the performance of the SAWR in performing the climbing motion....
Conference Paper
This paper explores the use of evolutionary algorithm approach to automatically design and optimize the snake-like modular robot to automatically design and optimize the snake-like modular robot to acquire the forward moving behaviour. A hybridized Genetic Programming and self-adaptive Differential Evolution algorithm is implemented to co-evolving...
Conference Paper
This paper presented the fabrication of a six articulated-wheeled robot (SAWR) with 3D printing technology. The SAWR is obtained from a evolution process where the morphology of the SAWR is optimized. A single objective evolution algorithm is implemented to optimize the SAWR with a smaller body while having best performance to climb over obstacles...
Conference Paper
This paper explores the use of multi-objective evolutionary algorithm to automatically design and optimize heterogeneous snake-like modular robot through artificial evolutionary process by taking consideration of two contradiction objectives which is to maximize the modular robot forward moving behaviour and minimize the complexity of the snake-mod...
Conference Paper
This paper explores the use of hybridized Genetic Programming and self-adaptive Differential Evolution algorithm to automatically design and co-evolve both the controller and morphology of heterogeneous swarm modular robots. A novel tree-based structure is proposed and implemented for the modular robot structure and ANN representation, which allows...
Article
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AbstrakKini, semakin ramai penyelidik telah menunjukkan minat mengkaji permainan Kecerdasan Buatan (KB).Permainan seumpama ini menyediakan tapak uji yang sangat berguna dan baik untuk mengkaji asasdan teknik-teknik KB. Teknik KB, seperti pembelajaran, pencarian dan perencanaan digunakan untukmenghasilkan agen maya yang mampu berfikir dan bertindak...
Article
The creation of intelligent video game controllers has recently become one of the greatest challenges in game artificial intelligence research, and it is arguably one of the fastest-growing areas in game design and development. The learning process, a very important feature of intelligent methods, is the result of an intelligent game controller to...
Article
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Recently, the growth of Artificial Intelligence (AI) has provided a set of effective techniques for designing computer-based controllers to perform various tasks autonomously in game area, specifically to produce intelligent optimal game controllers for playing video and computer games. This paper explores the use of the competitive fitness strateg...
Article
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This paper presents an initial approach for creating autonomous controllers for the car racing game using a hybrid technique. The Differential Evolution (DE) algorithm is combined with Feed-forward Artificial Neural Networks (FFANNs) to generate the required intelligent controllers in a well-known car racing game, namely The Open Racing Car Simulat...
Chapter
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This paper presents the research result of implementing evolutionary algorithms towards computational intelligence in Tower Defense game (TD game). TD game is a game where player(s) need to build tower to prevent the creeps from reaching their based. Penalty will be given if player losses any creeps during gameplays. It is a suitable test bed for p...
Article
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The objective of this study is to focus on the automatic generation of game artificial intelligence (AI) controllers for Ms. Pac-Man agent by using artificial neural network (ANN) and multiobjective artificial evolution. The Pareto Archived Evolution Strategy (PAES) is used to generate a Pareto optimal set of ANNs that optimize the conflicting obje...
Article
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In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network (PAESNet), with the attempt to find a set of Pareto optimal solutions by simultan...
Conference Paper
Full-text available
Evolutionary multi-objective optimization (EMO) has gained popularity and it has been successfully applied in several research areas. Based on the literature review conducted, EMO approach has not been applied in any Go game application. In this study, artificial neural networks (ANNs) are evolved with an EMO algorithm, Pareto Archived Evolution St...
Conference Paper
The main objective of this paper is to investigate online evolution of military unit combination strategies for winning an offensive rush in a real-time strategy (RTS) game. A modified version of Evolutionary Programming (EP) is used as the evolutionary optimizer while WARGUS is used as the RTS gaming environment. Evolution of the military unit com...
Conference Paper
Full-text available
This paper presents the design and evaluation of a full AI controller for Real-Time Strategy (RTS) games using techniques from Evolutionary Computing (EC). The design is novel in its use of a modified Pareto Differential Evolution (PDE) algorithm for bi-objective optimization of the weights of an Artificial Neural Network (ANN) controller when only...