Byeong Ho Kang

• PhD
• Professor (Full) at University of Tasmania

Protagonists allege that artificial intelligence (AI) is revolutionising contemporaneous mindscapes. Here, we authoritatively review the status quo of AI and machine learning application in irrigated agriculture, evaluating the potential of, and challenges associated with, a wide range of existential AI approaches. We contend that aspiring develope...

Fog computing has become a prominent paradigm in providing shared resources to serve different applications near the edge. Similar to other computing paradigms such as cloud and grid, in fog computing, service-level agreements (SLAs) are essential between fog providers and end-users to guarantee the quality of service (QoS). However, due to the uni...

Knowledge fusion used for handling cross-domain or complex questions in conversation systems has received considerable attention and interest. However, most existing knowledge fusion methods rely on centralized server, which face many limitations and challenges, such as a single point of failure, content tampering, and entrusted contribution assign...

Conversation systems play an important role in the research and development of multidomain systems, in which the number of conversations increases rapidly with the number of domains. Multiple experts must maintain these conversation interactions, otherwise experts from different domains are unable to interact properly. For this reason, ensuring sec...

Blockchain technology has taken on a leading position in today’s industrial applications by providing salient features and showing significant performance since its beginning. Blockchain began its journey from the concept of cryptocurrency and is now part of a range of core applications to achieve resilience and automation between various tasks. Ho...

A clone node attack is one of the severe attacks on the Internet of Things (IoT) network. In a clone node attack, an adversary aims to physically capture the secret credentials of the deployed IoT devices to make the clone of devices look similar to the original devices. In recent years, several solutions for detecting clone node attacks have been...

The time-evolving large graph has received attention due to it's participation in real-world applications such as social networks and PageRank calculation. It is necessary to partition a large-scale dynamic graph in a streaming manner in order to overcome the memory bottleneck while partitioning the computational load. Reducing network communicatio...

The rapidly expanding nature of the Internet of Things (IoT) networks is beginning to attract interest across a range of applications, including smart homes, smart transportation, smart health, and industrial contexts such as smart robotics. This cutting-edge technology enables individuals to track and control their integrated environment in real-t...

Time-evolving large graph has received attention due to their participation in real-world applications such as social networks and PageRank calculation. It is necessary to partition a large-scale dynamic graph in a streaming manner to overcome the memory bottleneck while partitioning the computational load. Reducing network communication and balanc...

The proposed Intelligent Medical Platform is a dialoguebased medical decision-making system that provides medical coaching and recommendation services, based on incremental learning methodology. The prototype demonstrates 90% accuracy for knowledge acquisition, 80% satisfaction level of user interaction with the system, and 95% accuracy for system...

With the increasing number of Internet of Things (IoT) devices, the volume and variety of data being generated by these devices are increasing rapidly. Cloud computing cannot process this data due to its high latency and scalability. In order to process this data in less time, fog computing has evolved as an extension to Cloud computing. In a fog c...

Internet of Things (IoT) has transformed the network into a new pathway by connecting the surrounding smart objects to enable smart services that act spontaneously. The connection between these objects is contributing to shaping a new data-driven society. IoT network is an open-access network where the individual users not only use the services off...

Intelligent Personal Assistant (IPA) devices such as Google Home and Amazon Echo have become commodity hardware and are well-known in the public domain. Leveraging these devices as speech-based interfaces to bespoke conversation agent (CA) systems in vocabulary-specific domains exposes their underlying Automatic Speech Recognition (ASR) transcripti...

The emergence of Internet protocol suites and packet-switching technologies tend to considerations of security, privacy, scalability, and reliability in layered Internet service architectures. The existing service systems allow us to access big data, but few studies focus on the fundamental security and stability in these systems, especially when t...

The case‐based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer‐based domain knowledge to medical students for solving real‐world clinical cases during CBL practice. To automate CBL, clinical documents are bene...

In the recent years, the scale of graph datasets has increased to such a degree that a single machine is not capable of efficiently processing large graphs. Thereby, efficient graph partitioning is necessary for those large graph applications. Traditional graph partitioning generally loads the whole graph data into the memory before performing part...

In the recent years, the scale of graph datasets has increased to such a degree that a single machine is not capable of efficiently processing large graphs. Thereby, efficient graph partitioning is necessary for those large graph applications. Traditional graph partitioning generally loads the whole graph data into the memory before performing part...

Recently, virtual laboratories have popping up in online learning for students to self‐enroll in the experiments. Like in‐class teaching methodology, virtual laboratories need to meet the requirements as same as real world laboratories and support efficient learning and communication services. In this paper, we detail the development of our distrib...

This work reports a novel method by fusing Laplacian Eigenmaps feature conversion and deep neural network (DNN) for machine condition assessment. Laplacian Eigenmaps is adopted to transform data features from original high dimension space to projected lower dimensional space, the DNN is optimized by the particle swarm optimization algorithm, and th...

As wind energy is experiencing an unprecedented development in today's world, the condition monitoring of wind turbine systems which can avoid serious accidents and economic losses are gathering more and more attentions. Considering the evaluation methods based on machine learning are complicated and unstable in terms of model training and paramete...

Feature selection is considered to be one of the most critical methods for choosing appropriate features from a larger set of items. This task requires two basic steps: ranking and filtering. Of these, the former necessitates the ranking of all features, while the latter involves filtering out all irrelevant features based on some threshold value....

Blockchain has attracted a great deal of attention due to its secure way of distributing transactions between different nodes without a trust entity, and tracking the validity of data. Although many experts argue the solutions to several problems in today’s inherently insecure Internet lies with blockchain technology because of its security and pri...

Clinical Decision Support System (CDSS) plays an indispensable role in decision making and solving complex problems in the medical domain. However, CDSS expects complete information to deliver an appropriate recommendation. In real scenarios, the user may not be able to provide complete information while interacting with CDSS. Therefore, the CDSS m...

We introduce an extension to Multiple Classification Ripple Down Rules (MCRDR), called Contextual MCRDR (C-MCRDR). We apply C-MCRDR knowledge-base systems (KBS) to the Textual Question Answering (TQA) and Natural Language Interface to Databases (NLIDB) paradigms in restricted domains as a type of spoken dialog system (SDS) or conversational agent (...

Objective: A considerable number of frameworks and platforms are available to model terminologies in the clinical domains, but wellness domain lacks a development framework. The objective of this study is to develop a clinically influenced and harmonized wellness concepts model (WCM) in order to support diverse wellness applications and services. T...

The peer assessment approach is considered to be one of the best solutions for scaling both assessment and peer learning to global classrooms, such as MOOCs. However, some academic staff hesitate to use a peer assessment approach for their classes due to concerns about its credibility and reliability. The focus of our research is to detect the cred...

Preventive maintenance is required in large scale industries to facilitate highly efficient performance. The efficiency of production can be maximized by preventing the failure of facilities in advance. Typically, regular maintenance is conducted manually in which case, it is hard to prevent repeated failures. Also, since measures to prevent failur...

Data-driven knowledge acquisition is one of the key research fields in data mining. Dealing with large amounts of data has received a lot of attention in the field recently, and a number of methodologies have been proposed to extract insights from data in an automated or semi-automated manner. However, these methodologies generally target a specifi...

Despite impressive achievements in image processing and artificial intelligence in the past decade, understanding video-based action remains a challenge. However, the intensive development of 3D computer vision in recent years has brought more potential research opportunities in pose-based action detection and recognition. Thanks to the advantages...

Cyber Physical System(CPS) allows to collect different sensor and alarm data from large number of facilities in industrial plants. Failure and faulty diagnosis is one of the most complicated and dynamic problems in the industrial plant management since most of failures are extremely ambiguous which needs to be solved based on an expert's experience...

Embedded Systems are integrated into our daily life in many ways. Embedded systems education requires at least two major components: (1) a teacher with expertise in both hardware and software; (2) a hands-on experimental environment. Recent developments in educational tool kits for learning embedded systems, such as Ardu-EZ, increase the feasibilit...

In artificial intelligence, knowledge engineering is one of the key research areas in which knowledge-based systems are developed to solve the real-world problems and helps in decision making. For constructing a rule-based knowledge base, normally single decision tree classifier is used to produce If-Then rules (i.e. production rules). In the healt...

Medical students should be able to actively apply clinical reasoning skills to further their interpretative, diagnostic, and treatment skills in a non-obtrusive and scalable way. Case-Based Learning (CBL) approach has been receiving attention in medical education as it is a student-centered teaching methodology that exposes students to real-world s...

A huge array of personalized healthcare and wellness systems are introduced into the portfolio of digital health and quantified-self movement in recent years. These systems share common capabilities including self-tracking/monitoring and self-quantifications, based on the raw sensory data. These capabilities provide solid ground for the users to be...

In this paper, we propose a novel robust blind color image watermarking method, namely SMLE, that allows to embed a gray-scale image as watermark into a host color image in the wavelet domain. After decomposing the gray-scale watermark to component binary images in digits ordering from least significant bit (LSB) to most significant bit (MSB), the...

A lot of mobile applications which provided location information by using a location-based service are being developed recently. For instance, a smart phone would find my location and destination by running a program using a GPS chip in a device. However, the information leakage and the crime that misused the leaked information caused by the cybera...

Recent advances in distributed information technologies are providing the means to capture and process abundant data, and to reveal associations between variables describing the crop-environment-management interaction. This review describes the determinants and moderating factors influencing how much value a crop producer and his or her advisor can...

Objective: Technologically integrated healthcare environments can be realized if physicians are encouraged to use smart systems for the creation and sharing of knowledge used in clinical decision support systems (CDSS). While CDSSs are heading toward smart environments, they lack support for abstraction of technology-oriented knowledge from physic...

Case-Based Learning (CBL) has become an effective pedagogy for student-centered learning in medical education, which builds its foundation on persisted patient cases. Flip learning and Internet of Things (IoTs) concepts have gained much attention in the recent years. These concepts with CBL can improve learning capabilities by providing real and ev...

Preventive maintenance is required for best performance of facilities in large scale industry. Ultimately, the efficiency of production is maximized by preventing the failure of facilities in advance. Typically, regular maintenance is conducted manually; however, it is hard to prevent repeated failures. Also, since measures to prevent failure depen...

Retraction Note to: Chapter 8 Characteristics Analysis of the Motor Block Lattice Resistor of a High Speed Train by Structure Improvement DOI: 10.1007/978-3-642-26010-0_8 The chapter starting on page 65 of this publication has been retracted due to multiple publication Retraction Note to: Chapter 38 Characteristics Analysis of the Motor Block Latti...

Artificial Neural Network has shown its impressive ability on many real world problems such as pattern recognition, classification and function approximation. An extension of ANN, higher order neural network (HONN), improves ANN's computational and learning capabilities. However, the large number of higher order attributes leads to long learning ti...

This paper explores the feasibility of implementing a model for an open domain, automated question and answering framework that leverages Wikipedia’s knowledgebase. While Wikipedia implicitly comprises answers to common questions, the disambiguation of natural language and the difficulty of developing an information retrieval process that produces...

Feature subset selection is an important data reduction technique. Effects of feature selection on classifier’s accuracy are extensively studied yet comprehensibility of the resultant model is given less attention. We show that a weak feature selection method may significantly increase the complexity of a classification model. We also proposed an e...

Trending topics is the most popular term list in the different web services, such as Twitter and Google. The changes in people’s interest in a specific trending topic are reflected in the changes of its popularity rank (up, down, and unchanged). This paper proposes a temporal modelling framework for predicting rank change of trending topics, and de...

In the past few years the role of e-health applications has taken a remarkable lead in terms of services and features inviting millions of people with higher motivation and confidence to achieve a healthier lifestyle. Induction of smart gadgetries, people lifestyle equipped with wearables, and development of IoT has revitalized the feature scale of...

Online trending topics represent the most popular topics among users in certain online community, such as a country community. Trending topics in one community are different from others since the users in the community may discuss different topics from other communities. Surprisingly, almost 90 % of trending topics are diffused among multiple onlin...

Detecting phishing websites has been noted as complex and dynamic problem area because of the subjective considerations and ambiguities of detection mechanism. We propose a novel approach that uses Ripple-down Rule (RDR) to acquire knowledge from human experts with the modified RDR model-generating algorithm (Induct RDR), which applies machine-lear...

Background The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people’s conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main en...

An effective knowledge representation has always proved its importance for mankind intelligence. Among various kinds of knowledge, declarative knowledge has a vital role in medical domain and is critical for health-care safety and quality. A large volume of declarative knowledge is hidden in multiple knowledge resources such as clinical notes, stan...

Most of the association rule mining algorithms use a single seed for initializing a population without paying attention to the effectiveness of an initial population in an evolutionary learning. Recently, researchers show that an initial population has significant effects on producing good solutions over several generations of a genetic algorithm....

In recent years, a large number of entities (ontology classes and properties) are found in different datasets over the Semantic Web. Due to the open and distributed nature of the Web, it is necessary to manage the heterogeneity problem between entities. In this context, the mapping of ontology entities from different datasets is important for data...

This paper presents a robust foreground detection method capable of adapting to different motion speeds in scenes. A key contribution of this work is the background estimation using a proposed novel algorithm, Neighbor-based Intensity Correction (NIC), that identifies and modifies the motion pixels from the difference of the background and the curr...

This book constitutes the refereed proceedings of the 29th Australasian Joint Conference on Artificial Intelligence, AI 2016, held in Hobart, TAS, Australia, in December 2016. The 40 full papers and 18 short papers presented together with 8 invited short papers were carefully reviewed and selected from 121 submissions. The papers are organized in t...

Artificial Neural Network has shown its impressive ability on many real world problems such as pattern recognition, classification and function approximation. An extension of ANN, higher order neural network (HONN), improves ANN's computational and learning capabilities. However, the large number of higher order attributes leads to long learning ti...

Biomedical systems have been using ontology matching as a primary technique for heterogeneity resolution. However, the natural intricacy and vastness of biomedical data have compelled biomedical ontologies to become large-scale and complex; consequently, biomedical ontology matching has become a computationally intensive task. Our parallel heteroge...

Customized wellness care is a progressing area to promote self-care management, utilizing the state of the art techniques and technologies to monitor user daily life activities. Mining Minds Platform is one such effort that lies in customized wellness care domain with objective to support personalized health and wellness. This paper focuses on the...

Association rule mining is the process of discovering useful and interesting rules from large datasets. Traditional association rule mining algorithms depend on a user specified minimum support and confidence values. These constraints introduce two major challenges in real world applications: exponential search space and a dataset dependent minimum...

Data mining techniques involve extracting useful, novel and interesting patterns from large data sets. Traditional association rule mining algorithms generate a huge number of unnecessary rules because of using support and confidence values as a constraint for measuring the quality of generated rules. Recently, several studies defined the process o...

Many web services, such as Twitter and Google, provide a list of their most popular terms, called a trending topics list, in descending order of popularity ranking. The changes in people’s interest in a specific trending topic are reflected in the changes of its popularity rank (up, down, and unchanged). This paper analyses the nature of trending t...

Objective: The objective of this study is to help a team of physicians and knowledge engineers acquire clinical knowledge from existing practices datasets for treatment of head and neck cancer, to validate the knowledge against published guidelines, to create refined rules, and to incorporate these rules into clinical workflow for clinical decisio...

Personalized healthcare envisions providing customized treatment and management plans to individuals at their doorstep. Key factors to ensure personalized healthcare is to involve with the individual in their daily life activities and process the gathered information to provide recommendations. We identified the mostly exposed domains for gathering...

It is a fact that the attention of research community in computer science, business executives, and decision makers is drastically drawn by big data. As the volume of data becomes bigger, it needs performance-oriented data-intensive processing frameworks such as MapReduce, which can scale computation on large commodity clusters. Hadoop MapReduce pr...

Ontology matching is among the core techniques used for heterogeneity resolution by information and knowledge-based systems. However, due to the excess and ever-evolving nature of data, ontologies are becoming large-scale and complex; consequently, leading to performance bottlenecks during ontology matching. In this paper, we present our performanc...

Finding appropriate evidence to support clinical practices is always challenging, and the construction of a query to retrieve such evidence is a fundamental step. Typically, evidence is found using manual or semi-automatic methods, which are time-consuming and sometimes make it difficult to construct knowledge-based complex queries. To overcome the...

Schema mapping that provides a unified view to the users is necessary to manage schema heterogeneity among different data sources. Schema matching is a required task for schema mapping that finds semantic correspondences between entity pairs of schemas. Semi-automatic schema matching systems were developed to overcome manual works for schema mappin...

A wide array of biomedical data are generated and made available to healthcare experts. However, due to the diverse nature of data, it is difficult to predict outcomes from it. It is therefore necessary to combine these diverse data sources into a single unified dataset. This paper proposes a global unified data model (GUDM) to provide a global uni...

Baidu, the most popular Chinese search engine, monitors what their users are currently searching and provides top 50 search terms, called trending search terms, in descending order of popularity ranking. The paper focused on predicting the popularity ranking trends of this top trending search terms in Baidu. Based on the data analysis, two issues w...

Legacy Case-Based Learning (CBL) medical educational systems aim to boost the learning and educational process but lacks the support of Systematized Nomenclature of Medicine (SNOMED) and flip learning concepts. Integrating these vocabularies can exploit the learning outcomes and build confidence in students while making decision to rehearsal in adv...

In the data mining research area, discovering frequent item sets is an important issue and key factor for mining association rules. For large datasets, a huge amount of frequent patterns are generated for a low support value, which is a major challenge in frequent pattern mining tasks. A Maximal frequent pattern mining task helps to resolve this pr...

The world is witnessing a spectacular shift in the delivery of health and wellness care. The key ingredient of this transformation consists in the use of revolutionary digital technologies to empower people in their self-management as well as to enhance traditional care procedures. While substantial domain-specific contributions have been provided...

Multi-layer perception (MLP) neural networks are widely used in automatic credit scoring systems with high accuracy and efficiency. This paper presents a higher accuracy credit scoring model based on MLP neural networks that have been trained with the back propagation algorithm. Our work focuses on enhancing credit scoring models in three aspects:...

Modern digital technologies are paving the path to a revolutionary new concept of health and wellness care. Nowadays, many new solutions are being released and put at the reach of most consumers for promoting their health and wellness self-management. However, most of these applications are of very limited use, arguable accuracy and scarce interope...

The user authentication is very crucial in developing an e-learning system. Emerging standards for distance learning and education influence in a major way the development of e-learning systems. E-learningsystem must be secured against manipulation from the side of the studentsand also it protects user's privacy. This paper examines privacy and sec...

Schema mapping is essential to manage schema heterogeneity among different sources. Schema mapping can be conducted by using machine learning algorithms or by knowledge engineering approaches. These two approaches have advantages and disadvantages. The machine learning approaches can learn their model using the data, but they are static, so they ca...

Healthcare systems provide suitable services in different domains to help people in fitting themselves into their best pattern of life. This study is focused on the development of a hybrid reasoning engine called KARE (knowledge acquisition and reasoning engine) which is the core reasoning module of ATHENA (activity-awareness for human-engaged well...

Cloud computing has become a prevalent technology and with its increased maturity more and more data including sensitive and non sensitive, is being centralized into it . While outsourcing the sensitive data into public cloud, its prior encryption is strongly recommended. Provisioning of encryption and existing work that guarantee security and priv...

Private matching (PM) has a vast domain of applications to get its benefit including social media, e-health and commerce. The core concept of PM comprises on revealing only common values between two parties and ensuring the privacy of the remaining ones. In this paper we have proposed a protocol ReSet, for PM that works with random values rather th...

With rise in energy costs, operational costs for managing cloud infrastructures are also increasing. This is an opportunity to present an energy-aware recommendation system for cloud platforms. This paper presents one such system that implements a pure software approach for generating energy efficient recommendations for cloud infrastructures. This...

Wearable devices and the data generated by them gives a unique opportunity to understand the user behavior and predict future needs due to its personal nature. In coming years this data will grow exponentially due to huge popularity of wearable devices. Analysis will become a challenge with the personal data explosion and also to maintain a updated...