Synchronous learning and teaching in engineering education in response to COVID situations
- Authors: Phung, Truong
- Date: 2021
- Type: Text , Conference paper
- Relation: 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 Vol. 2021-October
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- Description: COVID-19 and the government restrictions in place have seriously affected the face-to-face (F2F) mode of delivery in education and higher education has been one of the hardest hit. Universities around the world had to implement the transition from F2F to online on very short notice. In this paper, the author presents a case study that demonstrates the challenges, steps, and adjustments taken to bring a course that has significant components of communication, teamwork, and project management from a full F2F mode to fully online whilst maintaining as much learner-learner and learner-teacher interactions and students engagement as possible. This has been achieved, not without drawbacks and challenges, via synchronous delivery mode and with private channels and breakout room function to promote intra-team and inter-team communications, and teamwork. © 2021 IEEE.
- Authors: Phung, Truong
- Date: 2021
- Type: Text , Conference paper
- Relation: 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 Vol. 2021-October
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- Description: COVID-19 and the government restrictions in place have seriously affected the face-to-face (F2F) mode of delivery in education and higher education has been one of the hardest hit. Universities around the world had to implement the transition from F2F to online on very short notice. In this paper, the author presents a case study that demonstrates the challenges, steps, and adjustments taken to bring a course that has significant components of communication, teamwork, and project management from a full F2F mode to fully online whilst maintaining as much learner-learner and learner-teacher interactions and students engagement as possible. This has been achieved, not without drawbacks and challenges, via synchronous delivery mode and with private channels and breakout room function to promote intra-team and inter-team communications, and teamwork. © 2021 IEEE.
The agoraphilic navigation algorithm under dynamic environment with a moving goal
- Hewawasam, Hasitha, Ibrahim, Yousef, Kahandawa, Gayan, Choudhury, Tanveer
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2021
- Type: Text , Conference paper
- Relation: 30th IEEE International Symposium on Industrial Electronics, ISIE 2021 Vol. 2021-June
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- Description: This paper presents a research conducted in developing a new navigation algorithm to navigate robots under dynamically cluttered environments with a moving goal. There are only a few navigation algorithms capable of navigating robots under dynamic environments compared to static environments. The inability to track and reach a moving goal/target is a one of the common weakness of existing navigating algorithms operating in dynamic environments. The existing free space attraction (Agoraphilic) based navigation algorithms also suffer from this common problem. The proposed algorithm, in this paper was developed to overcome this issue. Agoraphilic Navigation Algorithm under Dynamic Environment, 'ANADE' consists of eight main modules. These modules are iteratively used to create the robot's driving force which pulls the robot towards the moving goal. An obstacle tracking module is used to identify the time varying free spaces by tracking moving obstacles. Furthermore, a tracking system is also used to track the moving goal. The capacity of the ANADE was further strengthen by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decision considering future environments around the robot. The proposed algorithm was tested under dynamic environment. These tests were focused on testing the behavior of the algorithm under the challenge of reaching a moving goal. Furthermore, the test results demonstrate that ANADE is successful in reaching a moving goal under an unknown dynamically cluttered environment. © 2021 IEEE.
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2021
- Type: Text , Conference paper
- Relation: 30th IEEE International Symposium on Industrial Electronics, ISIE 2021 Vol. 2021-June
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- Description: This paper presents a research conducted in developing a new navigation algorithm to navigate robots under dynamically cluttered environments with a moving goal. There are only a few navigation algorithms capable of navigating robots under dynamic environments compared to static environments. The inability to track and reach a moving goal/target is a one of the common weakness of existing navigating algorithms operating in dynamic environments. The existing free space attraction (Agoraphilic) based navigation algorithms also suffer from this common problem. The proposed algorithm, in this paper was developed to overcome this issue. Agoraphilic Navigation Algorithm under Dynamic Environment, 'ANADE' consists of eight main modules. These modules are iteratively used to create the robot's driving force which pulls the robot towards the moving goal. An obstacle tracking module is used to identify the time varying free spaces by tracking moving obstacles. Furthermore, a tracking system is also used to track the moving goal. The capacity of the ANADE was further strengthen by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decision considering future environments around the robot. The proposed algorithm was tested under dynamic environment. These tests were focused on testing the behavior of the algorithm under the challenge of reaching a moving goal. Furthermore, the test results demonstrate that ANADE is successful in reaching a moving goal under an unknown dynamically cluttered environment. © 2021 IEEE.
The implementation of Blockchain framework in MOOCs to support a freedom of learning in Indonesia
- Febrinanto, Falih, Dafik, Nisviasari, R.
- Authors: Febrinanto, Falih , Dafik , Nisviasari, R.
- Date: 2021
- Type: Text , Conference paper
- Relation: 4th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2020 Vol. 1836
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- Description: A freedom of learning program has been released by the Indonesian Ministry and Culture this year 2020. There are three ways for students to earn their credits, namely take the subject course in face-to-face based class, virtual based class or under Massive Open Online Courses (MOOCs). MOOCs is a model that is developed to help people to learn about certain skills through the online platform, without any limitation in the audience. MOOCs aim to enhance broad collaboration between individuals in creating learning environments that have high scalability and can be accessed by anyone and anywhere. The complexity arises when students undertake a subject course through MOOCs, how to certify the completion of their program in which the certification can be gained easily, and the last how secure the obtained certificate? Blockchain technology can help to improve the quality of MOOCs by providing control of academic records as evidence that someone has completed a learning process on MOOCs. Academic records generated will be stored in one place forever and safely stored in the Blockchain environment. This article will explore how the possible to implement the Blockchain framework in MOOCs to support a freedom of learning in Indonesia. © 2021 Published under licence by IOP Publishing Ltd.
- Authors: Febrinanto, Falih , Dafik , Nisviasari, R.
- Date: 2021
- Type: Text , Conference paper
- Relation: 4th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2020 Vol. 1836
- Full Text:
- Reviewed:
- Description: A freedom of learning program has been released by the Indonesian Ministry and Culture this year 2020. There are three ways for students to earn their credits, namely take the subject course in face-to-face based class, virtual based class or under Massive Open Online Courses (MOOCs). MOOCs is a model that is developed to help people to learn about certain skills through the online platform, without any limitation in the audience. MOOCs aim to enhance broad collaboration between individuals in creating learning environments that have high scalability and can be accessed by anyone and anywhere. The complexity arises when students undertake a subject course through MOOCs, how to certify the completion of their program in which the certification can be gained easily, and the last how secure the obtained certificate? Blockchain technology can help to improve the quality of MOOCs by providing control of academic records as evidence that someone has completed a learning process on MOOCs. Academic records generated will be stored in one place forever and safely stored in the Blockchain environment. This article will explore how the possible to implement the Blockchain framework in MOOCs to support a freedom of learning in Indonesia. © 2021 Published under licence by IOP Publishing Ltd.
Time-expanded method improving throughput in dynamic renewable networks
- Zhang, Jianhui, Guan, Siqi, Wang, Jiacheng, Liu, Liming, Wang, HanXiang, Xia, Feng
- Authors: Zhang, Jianhui , Guan, Siqi , Wang, Jiacheng , Liu, Liming , Wang, HanXiang , Xia, Feng
- Date: 2021
- Type: Text , Conference paper
- Relation: 29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021
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- Description: In the Dynamic Rechargeable Networks (DRNs), the existing studies usually consider the spatio-temporal dynamics of the harvested energy so as to maximize the throughput by efficient energy allocation. However, the network dynamics have seldom been considered simultaneously including the time variable link quality, communication power and battery charge efficiency. Furthermore, the wireless interference brings extra challenge. To take these dynamics into account together, this paper studies the quite challenging problem, the network throughput maximization in the DRNs, by proper energy allocation while considering the additional affection of wireless interference. We introduce the Time-Expanded Graph (TEG) to describe the above dynamics in a feasible easy way, and then look into the scenario where there is only one pair of source-target firstly. To maximize the throughput, this paper designs the Single Pair Throughput maximization (SPT) algorithm based on TEG while considering the wireless interference. In the case of multiple pairs of source-targets, it's quite complex to solve the network throughput maximization problem directly. This paper introduces the Garg and Könemanns framework and then designs the Multiple Pairs Throughput (MPT) algorithm to maximize the overall throughput of all pairs. MPT is a fast approximation solution with the ratio of 1-3ϵ, where 0 < ϵ < 1 is a small positive constant. This paper also conducts the extensive numerical evaluation based on the simulated data and the data collected by our real system. The numerical simulation results demonstrate the throughput improvement of our algorithms. © 2021 IEEE.
- Authors: Zhang, Jianhui , Guan, Siqi , Wang, Jiacheng , Liu, Liming , Wang, HanXiang , Xia, Feng
- Date: 2021
- Type: Text , Conference paper
- Relation: 29th IEEE/ACM International Symposium on Quality of Service, IWQOS 2021
- Full Text:
- Reviewed:
- Description: In the Dynamic Rechargeable Networks (DRNs), the existing studies usually consider the spatio-temporal dynamics of the harvested energy so as to maximize the throughput by efficient energy allocation. However, the network dynamics have seldom been considered simultaneously including the time variable link quality, communication power and battery charge efficiency. Furthermore, the wireless interference brings extra challenge. To take these dynamics into account together, this paper studies the quite challenging problem, the network throughput maximization in the DRNs, by proper energy allocation while considering the additional affection of wireless interference. We introduce the Time-Expanded Graph (TEG) to describe the above dynamics in a feasible easy way, and then look into the scenario where there is only one pair of source-target firstly. To maximize the throughput, this paper designs the Single Pair Throughput maximization (SPT) algorithm based on TEG while considering the wireless interference. In the case of multiple pairs of source-targets, it's quite complex to solve the network throughput maximization problem directly. This paper introduces the Garg and Könemanns framework and then designs the Multiple Pairs Throughput (MPT) algorithm to maximize the overall throughput of all pairs. MPT is a fast approximation solution with the ratio of 1-3ϵ, where 0 < ϵ < 1 is a small positive constant. This paper also conducts the extensive numerical evaluation based on the simulated data and the data collected by our real system. The numerical simulation results demonstrate the throughput improvement of our algorithms. © 2021 IEEE.
Towards a formal framework for partial compliance of business processes
- Lam, Ho-Pun, Hashmi, Mustafa, Kumar, Akhil
- Authors: Lam, Ho-Pun , Hashmi, Mustafa , Kumar, Akhil
- Date: 2021
- Type: Text , Conference paper
- Relation: International Workshops on AI Approaches to the Complexity of Legal Systems, AICOL 2018 and AICOL 2020, held jointly with the International Workshop on Explainable and Responsible AI and Law, XAILA 2020, Virtual online, 9 December 2020 Vol. 13048 LNAI, p. 90-105
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- Description: Binary “YES-NO” notions of process compliance are not very helpful to managers for assessing the operational performance of their company because a large number of cases fall in the grey area of partial compliance. Hence, it is necessary to have ways to quantify partial compliance in terms of metrics and be able to classify actual cases by assigning a numeric value of compliance to them. In this paper, we formulate an evaluation framework to quantify the level of compliance of business processes across different levels of abstraction (such as task, trace and process level) and across multiple dimensions of each task (such as temporal, monetary, role-, data-, and quality-related) to provide managers more useful information about their operations and to help them improve their decision making processes. Our approach can also add social value by making social services provided by local, state and federal governments more flexible and improving the lives of citizens. © 2021, Springer Nature Switzerland AG.
- Authors: Lam, Ho-Pun , Hashmi, Mustafa , Kumar, Akhil
- Date: 2021
- Type: Text , Conference paper
- Relation: International Workshops on AI Approaches to the Complexity of Legal Systems, AICOL 2018 and AICOL 2020, held jointly with the International Workshop on Explainable and Responsible AI and Law, XAILA 2020, Virtual online, 9 December 2020 Vol. 13048 LNAI, p. 90-105
- Full Text:
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- Description: Binary “YES-NO” notions of process compliance are not very helpful to managers for assessing the operational performance of their company because a large number of cases fall in the grey area of partial compliance. Hence, it is necessary to have ways to quantify partial compliance in terms of metrics and be able to classify actual cases by assigning a numeric value of compliance to them. In this paper, we formulate an evaluation framework to quantify the level of compliance of business processes across different levels of abstraction (such as task, trace and process level) and across multiple dimensions of each task (such as temporal, monetary, role-, data-, and quality-related) to provide managers more useful information about their operations and to help them improve their decision making processes. Our approach can also add social value by making social services provided by local, state and federal governments more flexible and improving the lives of citizens. © 2021, Springer Nature Switzerland AG.
A coarse representation of frames oriented video coding by leveraging cuboidal partitioning of image data
- Ahmmed, Ashe, Paul, Manoranjan, Murshed, Manzur, Taubman, David
- Authors: Ahmmed, Ashe , Paul, Manoranjan , Murshed, Manzur , Taubman, David
- Date: 2020
- Type: Text , Conference paper
- Relation: 22nd IEEE International Workshop on Multimedia Signal Processing, MMSP 2020, Virtual Tampere, Finland 21-24 September 2020
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- Description: Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence. Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. In this work, we form a coarse representation of the current frame by minimizing commonality within that frame while preserving important structural properties of the frame. The building blocks of this coarse representation are rectangular regions called cuboids, which are computationally simple and has a compact description. Then we propose to employ the coarse frame as an additional source for predictive coding of the current frame. Experimental results show an improvement in bit rate savings over a reference codec for HEVC, with minor increase in the codec computational complexity. © 2020 IEEE.
- Authors: Ahmmed, Ashe , Paul, Manoranjan , Murshed, Manzur , Taubman, David
- Date: 2020
- Type: Text , Conference paper
- Relation: 22nd IEEE International Workshop on Multimedia Signal Processing, MMSP 2020, Virtual Tampere, Finland 21-24 September 2020
- Full Text:
- Reviewed:
- Description: Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence. Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. In this work, we form a coarse representation of the current frame by minimizing commonality within that frame while preserving important structural properties of the frame. The building blocks of this coarse representation are rectangular regions called cuboids, which are computationally simple and has a compact description. Then we propose to employ the coarse frame as an additional source for predictive coding of the current frame. Experimental results show an improvement in bit rate savings over a reference codec for HEVC, with minor increase in the codec computational complexity. © 2020 IEEE.
An approach to map geography mark-up language data to resource description framework schema
- Faqir, Ammara, Mahmood, Aqsa, Qazi, Kiran, Malik, Saleem
- Authors: Faqir, Ammara , Mahmood, Aqsa , Qazi, Kiran , Malik, Saleem
- Date: 2020
- Type: Text , Conference paper
- Relation: 2nd International Conference on Intelligent Technologies and Applications, INTAP 2019 Vol. 1198, p. 343-354
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- Description: GML serves as premier modeling language used to represent data of geographic information related to geography locations. However, a problem of GML is its ability to integrate with a variety of geographical and GPS applications. Since, GML saves data in coordinates and in topology for the purpose to integrate data with variety of applications on semantic web, data be mapped to Resource Description Framework (RDF) and Resource Description Framework Schema (RDFS). An approach of mapping GML metadata to RDFS is presented in this paper. This study focuses on the methodology to convert GML data in semantics to represent in extended and enriched form such as RDFS as representation in RDF is not sufficient over semantic web. Firstly, we have GML script from case study and parse it using GML parser and get XML file. XML file parse using Java and get text file to extract GML features and then get a graph form of these features. After that we designed methodology of prototype tool to map GML features to RDFS. Tool performed features by features mapping and extracted results are represented in the tabular form of mapping GML metadata to RDFS. © 2020, Springer Nature Singapore Pte Ltd.
- Description: E1
- Authors: Faqir, Ammara , Mahmood, Aqsa , Qazi, Kiran , Malik, Saleem
- Date: 2020
- Type: Text , Conference paper
- Relation: 2nd International Conference on Intelligent Technologies and Applications, INTAP 2019 Vol. 1198, p. 343-354
- Full Text:
- Reviewed:
- Description: GML serves as premier modeling language used to represent data of geographic information related to geography locations. However, a problem of GML is its ability to integrate with a variety of geographical and GPS applications. Since, GML saves data in coordinates and in topology for the purpose to integrate data with variety of applications on semantic web, data be mapped to Resource Description Framework (RDF) and Resource Description Framework Schema (RDFS). An approach of mapping GML metadata to RDFS is presented in this paper. This study focuses on the methodology to convert GML data in semantics to represent in extended and enriched form such as RDFS as representation in RDF is not sufficient over semantic web. Firstly, we have GML script from case study and parse it using GML parser and get XML file. XML file parse using Java and get text file to extract GML features and then get a graph form of these features. After that we designed methodology of prototype tool to map GML features to RDFS. Tool performed features by features mapping and extracted results are represented in the tabular form of mapping GML metadata to RDFS. © 2020, Springer Nature Singapore Pte Ltd.
- Description: E1
An exploratory study of the adoption of blockchain technology among Australian organizations : a theoretical model
- Malik, Saleem, Chadhar, Mehmood, Chetty, Madhu, Vatanasakdakul, Savanid
- Authors: Malik, Saleem , Chadhar, Mehmood , Chetty, Madhu , Vatanasakdakul, Savanid
- Date: 2020
- Type: Text , Conference paper
- Relation: 17th European, Mediterranean, and Middle Eastern Conference on Information Systems, EMCIS 2020; Dubai; 25-26 November 2020 Vol. 402, p. 205-220
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- Description: Scholarly and commercial literature indicates several applications of Blockchain Technology (BCT) in different industries e.g. health, finance, supply chain, government, and energy. Despite abundant benefits reported and growing prominence, BCT has been facing various challenges across the globe, including low adoption by organizations. There is a dearth of studies that examined the organizational adoption of blockchain technology, particularly in Australia. This lack of uptake provides the rationale to initiate this research to identify the factors influencing the Australian organizations to adopt BCT. To achieve this, we conducted a qualitative study based on the Technology, Organization, Environment (TOE) framework. The study proposes a theoretical model grounded on the findings of semi-structured interviews of blockchain experts in Australia. The proposed model shows that the organizational adoption of blockchain is influenced by perceived benefits, compatibility, and complexity, organization innovativeness, organizational learning capability, competitive intensity, government support, trading partner readiness, and standards uncertainty. © 2020, Springer Nature Switzerland AG.
- Authors: Malik, Saleem , Chadhar, Mehmood , Chetty, Madhu , Vatanasakdakul, Savanid
- Date: 2020
- Type: Text , Conference paper
- Relation: 17th European, Mediterranean, and Middle Eastern Conference on Information Systems, EMCIS 2020; Dubai; 25-26 November 2020 Vol. 402, p. 205-220
- Full Text:
- Reviewed:
- Description: Scholarly and commercial literature indicates several applications of Blockchain Technology (BCT) in different industries e.g. health, finance, supply chain, government, and energy. Despite abundant benefits reported and growing prominence, BCT has been facing various challenges across the globe, including low adoption by organizations. There is a dearth of studies that examined the organizational adoption of blockchain technology, particularly in Australia. This lack of uptake provides the rationale to initiate this research to identify the factors influencing the Australian organizations to adopt BCT. To achieve this, we conducted a qualitative study based on the Technology, Organization, Environment (TOE) framework. The study proposes a theoretical model grounded on the findings of semi-structured interviews of blockchain experts in Australia. The proposed model shows that the organizational adoption of blockchain is influenced by perceived benefits, compatibility, and complexity, organization innovativeness, organizational learning capability, competitive intensity, government support, trading partner readiness, and standards uncertainty. © 2020, Springer Nature Switzerland AG.
Capability building through workplace based learning in maintenance and reliability engineering (MRE) postgraduate programmes
- Chattopadhyay, Gopinath, Larkins, Jo-ann
- Authors: Chattopadhyay, Gopinath , Larkins, Jo-ann
- Date: 2020
- Type: Text , Conference paper
- Relation: 31st Annual Conference of the Australasian Association for Engineering Education (AAEE 2020) : Disrupting Business as Usual in Engineering Education
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- Authors: Chattopadhyay, Gopinath , Larkins, Jo-ann
- Date: 2020
- Type: Text , Conference paper
- Relation: 31st Annual Conference of the Australasian Association for Engineering Education (AAEE 2020) : Disrupting Business as Usual in Engineering Education
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Characterizations of robust and stable duality for linearly perturbed uncertain optimization problems
- Dinh, Nguyen, Goberna, Miguel, López, Marco, Volle, Michel
- Authors: Dinh, Nguyen , Goberna, Miguel , López, Marco , Volle, Michel
- Date: 2020
- Type: Text , Conference paper
- Relation: Jonathan Borwein Commemorative Conference, JBCC 2017 Vol. 313, p. 43-74
- Relation: http://purl.org/au-research/grants/arc/DP180100602
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- Description: We introduce a robust optimization model consisting in a family of perturbation functions giving rise to certain pairs of dual optimization problems in which the dual variable depends on the uncertainty parameter. The interest of our approach is illustrated by some examples, including uncertain conic optimization and infinite optimization via discretization. The main results characterize desirable robust duality relations (as robust zero-duality gap) by formulas involving the epsilon-minima or the epsilon-subdifferentials of the objective function. The two extreme cases, namely, the usual perturbational duality (without uncertainty), and the duality for the supremum of functions (duality parameter vanishing) are analyzed in detail. © Springer Nature Switzerland AG 2020.
- Authors: Dinh, Nguyen , Goberna, Miguel , López, Marco , Volle, Michel
- Date: 2020
- Type: Text , Conference paper
- Relation: Jonathan Borwein Commemorative Conference, JBCC 2017 Vol. 313, p. 43-74
- Relation: http://purl.org/au-research/grants/arc/DP180100602
- Full Text:
- Reviewed:
- Description: We introduce a robust optimization model consisting in a family of perturbation functions giving rise to certain pairs of dual optimization problems in which the dual variable depends on the uncertainty parameter. The interest of our approach is illustrated by some examples, including uncertain conic optimization and infinite optimization via discretization. The main results characterize desirable robust duality relations (as robust zero-duality gap) by formulas involving the epsilon-minima or the epsilon-subdifferentials of the objective function. The two extreme cases, namely, the usual perturbational duality (without uncertainty), and the duality for the supremum of functions (duality parameter vanishing) are analyzed in detail. © Springer Nature Switzerland AG 2020.
Conservation, agriculture, sustainable, development and strong communities
- Authors: Martin, Jennifer
- Date: 2020
- Type: Text , Conference paper
- Relation: Strategies for the promotion of conservation agriculture in Central Asia, Proceedings of the International Conference, Tashkent, Uzbekistan, 5–7 September 2018 p. 278-287
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- Description: Four decades have passed since the introduction of Conservation Agriculture research and development. We also mark forty years since the introduction of the Declaration of Alma-Ata at the International Conference on Primary Health Care, Alma-Ata, Kazakhstan, 6–12 September 1978. Furthermore, of significance to the future development of sustainable agriculture practices and healthy communities, is the introduction of the United Nations Sustainable Development Goals in January 2016. These follow on from the Millennium Development goals that will guide the United Nations Development Program policy and development unti l 2030. An Australian case study on Conservation Agriculture is presented examining the relationship between Conservation Agriculture, health and wellbeing and sustainable development. It is argued that an ecosystems approach is useful for strategic sustainable development to understand the connectedness and inter-relationship between climate change agricultural practices, sense of place, identity, health and wellbeing. Community development processes can assist to build strong communities through collaboration between farmers, farmer organizations, local experts, and national and regional public and private institutions.
- Authors: Martin, Jennifer
- Date: 2020
- Type: Text , Conference paper
- Relation: Strategies for the promotion of conservation agriculture in Central Asia, Proceedings of the International Conference, Tashkent, Uzbekistan, 5–7 September 2018 p. 278-287
- Full Text:
- Reviewed:
- Description: Four decades have passed since the introduction of Conservation Agriculture research and development. We also mark forty years since the introduction of the Declaration of Alma-Ata at the International Conference on Primary Health Care, Alma-Ata, Kazakhstan, 6–12 September 1978. Furthermore, of significance to the future development of sustainable agriculture practices and healthy communities, is the introduction of the United Nations Sustainable Development Goals in January 2016. These follow on from the Millennium Development goals that will guide the United Nations Development Program policy and development unti l 2030. An Australian case study on Conservation Agriculture is presented examining the relationship between Conservation Agriculture, health and wellbeing and sustainable development. It is argued that an ecosystems approach is useful for strategic sustainable development to understand the connectedness and inter-relationship between climate change agricultural practices, sense of place, identity, health and wellbeing. Community development processes can assist to build strong communities through collaboration between farmers, farmer organizations, local experts, and national and regional public and private institutions.
DEFINE: friendship detection based on node enhancement
- Pan, Hanxiao, Guo, Teng, Bedru, Hayat, Qing, Qing, Zhang, Dongyu, Xia, Feng
- Authors: Pan, Hanxiao , Guo, Teng , Bedru, Hayat , Qing, Qing , Zhang, Dongyu , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 31st Australasian Database Conference, ADC 2019 Vol. 12008 LNCS, p. 81-92
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- Description: Network representation learning (NRL) is a matter of importance to a variety of tasks such as link prediction. Learning low-dimensional vector representations for node enhancement based on nodes attributes and network structures can improve link prediction performance. Node attributes are important factors in forming networks, like psychological factors and appearance features affecting friendship networks. However, little to no work has detected friendship using the NRL technique, which combines students’ psychological features and perceived traits based on facial appearance. In this paper, we propose a framework named DEFINE (No enhancement based r e dship D tection) to detect students’ friend relationships, which combines with students’ psychological factors and facial perception information. To detect friend relationships accurately, DEFINE uses the NRL technique, which considers network structure and the additional attributes information for nodes. DEFINE transforms them into low-dimensional vector spaces while preserving the inherent properties of the friendship network. Experimental results on real-world friendship network datasets illustrate that DEFINE outperforms other state-of-art methods. © 2020, Springer Nature Switzerland AG.
- Description: E1
- Authors: Pan, Hanxiao , Guo, Teng , Bedru, Hayat , Qing, Qing , Zhang, Dongyu , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 31st Australasian Database Conference, ADC 2019 Vol. 12008 LNCS, p. 81-92
- Full Text:
- Reviewed:
- Description: Network representation learning (NRL) is a matter of importance to a variety of tasks such as link prediction. Learning low-dimensional vector representations for node enhancement based on nodes attributes and network structures can improve link prediction performance. Node attributes are important factors in forming networks, like psychological factors and appearance features affecting friendship networks. However, little to no work has detected friendship using the NRL technique, which combines students’ psychological features and perceived traits based on facial appearance. In this paper, we propose a framework named DEFINE (No enhancement based r e dship D tection) to detect students’ friend relationships, which combines with students’ psychological factors and facial perception information. To detect friend relationships accurately, DEFINE uses the NRL technique, which considers network structure and the additional attributes information for nodes. DEFINE transforms them into low-dimensional vector spaces while preserving the inherent properties of the friendship network. Experimental results on real-world friendship network datasets illustrate that DEFINE outperforms other state-of-art methods. © 2020, Springer Nature Switzerland AG.
- Description: E1
Discovery of small group interactions and performance from project emails
- Ivkovic, Sasha, Oseni, Taiwo, Chadhar, Mehmood, Firmin, Sally
- Authors: Ivkovic, Sasha , Oseni, Taiwo , Chadhar, Mehmood , Firmin, Sally
- Date: 2020
- Type: Text , Conference paper
- Relation: 24th Pacific Asia Conference on Information Systems: Information Systems (IS) for the Future, PACIS 2020
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- Description: Despite latest advances in small group research, discovery of group interactions and performance from analysis of small group communication, such as project emails, is still minimally represented. This paper presents a novel approach of studying small groups through analysis of the participants' emails sent to the project manager. We examined 1,105 email messages from managers' email in-boxes across five distinct ICT projects from the personal, social, collaborative, and engaging perspective of the email senders and link the findings to group performance. The study provides theoretical evidence that analysis of incoming communication from project managers' email in-box can be used to measure a group's success. For project managers the approach has the potential to be highly beneficial for monitoring of indicators for the state of project health. © Proceedings of the 24th Pacific Asia Conference on Information Systems: Information Systems (IS) for the Future, PACIS 2020. All rights reserved.
- Authors: Ivkovic, Sasha , Oseni, Taiwo , Chadhar, Mehmood , Firmin, Sally
- Date: 2020
- Type: Text , Conference paper
- Relation: 24th Pacific Asia Conference on Information Systems: Information Systems (IS) for the Future, PACIS 2020
- Full Text:
- Reviewed:
- Description: Despite latest advances in small group research, discovery of group interactions and performance from analysis of small group communication, such as project emails, is still minimally represented. This paper presents a novel approach of studying small groups through analysis of the participants' emails sent to the project manager. We examined 1,105 email messages from managers' email in-boxes across five distinct ICT projects from the personal, social, collaborative, and engaging perspective of the email senders and link the findings to group performance. The study provides theoretical evidence that analysis of incoming communication from project managers' email in-box can be used to measure a group's success. For project managers the approach has the potential to be highly beneficial for monitoring of indicators for the state of project health. © Proceedings of the 24th Pacific Asia Conference on Information Systems: Information Systems (IS) for the Future, PACIS 2020. All rights reserved.
Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations
- Hewawasam, Hasitha, Ibrahim, Yousef, Kahandawa, Gayan, Choudhury, Tanveer
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th IEEE International Symposium on Industrial Electronics, ISIE 2020 Vol. 2020-June, p. 536-542
- Full Text:
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- Description: This paper presents a summary of the research which was conducted in developing a new free-space based (Agoraphilic) navigation algorithm. This new methodology is capable of maneuvering robots in static as well as dynamically cluttered unknown environments. The new algorithm uses only one force to drive the robot. This force is always an attractive force created by the freespace. This force is focused towards the goal by a force shaping module. Consequently, the robot is motivated to follow free-space directing towards the goal. As this method only based on the attractive forces, the robot always moves towards the goal as long as there is free-space . This method has eradicated many drawbacks of the traditional APF method. Several experimental tests were conducted using Turtlebot3 research platform. These tests were focused on testing the behavior of the new algorithm under dead-lock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method. © 2020 IEEE.
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th IEEE International Symposium on Industrial Electronics, ISIE 2020 Vol. 2020-June, p. 536-542
- Full Text:
- Reviewed:
- Description: This paper presents a summary of the research which was conducted in developing a new free-space based (Agoraphilic) navigation algorithm. This new methodology is capable of maneuvering robots in static as well as dynamically cluttered unknown environments. The new algorithm uses only one force to drive the robot. This force is always an attractive force created by the freespace. This force is focused towards the goal by a force shaping module. Consequently, the robot is motivated to follow free-space directing towards the goal. As this method only based on the attractive forces, the robot always moves towards the goal as long as there is free-space . This method has eradicated many drawbacks of the traditional APF method. Several experimental tests were conducted using Turtlebot3 research platform. These tests were focused on testing the behavior of the new algorithm under dead-lock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method. © 2020 IEEE.
Graduate employment prediction with bias
- Guo, Teng, Xia, Feng, Zhen, Shihao, Bai, Xiaomei, Zhang, Dongyu
- Authors: Guo, Teng , Xia, Feng , Zhen, Shihao , Bai, Xiaomei , Zhang, Dongyu
- Date: 2020
- Type: Text , Conference paper
- Relation: AAAI 2020 - 34th AAAI Conference on Artificial Intelligence p. 670-677
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- Description: The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide. In addition to academic performance, unconscious biases can become one key obstacle for hunting jobs for graduating students. Thus, it is necessary to understand these unconscious biases so that we can help these students at an early stage with more personalized intervention. In this paper, we develop a framework, i.e., MAYA (Multi-mAjor emploYment stAtus) to predict students’ employment status while considering biases. The framework consists of four major components. Firstly, we solve the heterogeneity of student courses by embedding academic performance into a unified space. Then, we apply a generative adversarial network (GAN) to overcome the class imbalance problem. Thirdly, we adopt Long Short-Term Memory (LSTM) with a novel dropout mechanism to comprehensively capture sequential information among semesters. Finally, we design a bias-based regularization to capture the job market biases. We conduct extensive experiments on a large-scale educational dataset and the results demonstrate the effectiveness of our prediction framework. Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Feng Xia” is provided in this record**
- Authors: Guo, Teng , Xia, Feng , Zhen, Shihao , Bai, Xiaomei , Zhang, Dongyu
- Date: 2020
- Type: Text , Conference paper
- Relation: AAAI 2020 - 34th AAAI Conference on Artificial Intelligence p. 670-677
- Full Text:
- Reviewed:
- Description: The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide. In addition to academic performance, unconscious biases can become one key obstacle for hunting jobs for graduating students. Thus, it is necessary to understand these unconscious biases so that we can help these students at an early stage with more personalized intervention. In this paper, we develop a framework, i.e., MAYA (Multi-mAjor emploYment stAtus) to predict students’ employment status while considering biases. The framework consists of four major components. Firstly, we solve the heterogeneity of student courses by embedding academic performance into a unified space. Then, we apply a generative adversarial network (GAN) to overcome the class imbalance problem. Thirdly, we adopt Long Short-Term Memory (LSTM) with a novel dropout mechanism to comprehensively capture sequential information among semesters. Finally, we design a bias-based regularization to capture the job market biases. We conduct extensive experiments on a large-scale educational dataset and the results demonstrate the effectiveness of our prediction framework. Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Feng Xia” is provided in this record**
Graph Force Learning
- Sun, Ke, Liu, Jiaying, Yu, Shuo, Xu, Bo, Xia, Feng
- Authors: Sun, Ke , Liu, Jiaying , Yu, Shuo , Xu, Bo , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 8th IEEE International Conference on Big Data, Big Data 2020 p. 2987-2994
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- Description: Features representation leverages the great power in network analysis tasks. However, most features are discrete which poses tremendous challenges to effective use. Recently, increasing attention has been paid on network feature learning, which could map discrete features to continued space. Unfortunately, current studies fail to fully preserve the structural information in the feature space due to random negative sampling strategy during training. To tackle this problem, we study the problem of feature learning and novelty propose a force-based graph learning model named GForce inspired by the spring-electrical model. GForce assumes that nodes are in attractive forces and repulsive forces, thus leading to the same representation with the original structural information in feature learning. Comprehensive experiments on three benchmark datasets demonstrate the effectiveness of the proposed framework. Furthermore, GForce opens up opportunities to use physics models to model node interaction for graph learning. © 2020 IEEE.
- Authors: Sun, Ke , Liu, Jiaying , Yu, Shuo , Xu, Bo , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 8th IEEE International Conference on Big Data, Big Data 2020 p. 2987-2994
- Full Text:
- Reviewed:
- Description: Features representation leverages the great power in network analysis tasks. However, most features are discrete which poses tremendous challenges to effective use. Recently, increasing attention has been paid on network feature learning, which could map discrete features to continued space. Unfortunately, current studies fail to fully preserve the structural information in the feature space due to random negative sampling strategy during training. To tackle this problem, we study the problem of feature learning and novelty propose a force-based graph learning model named GForce inspired by the spring-electrical model. GForce assumes that nodes are in attractive forces and repulsive forces, thus leading to the same representation with the original structural information in feature learning. Comprehensive experiments on three benchmark datasets demonstrate the effectiveness of the proposed framework. Furthermore, GForce opens up opportunities to use physics models to model node interaction for graph learning. © 2020 IEEE.
Implicit feedback-based group recommender system for internet of things applications
- Guo, Zhiwei, Yu, Keping, Guo, Tan, Bashir, Ali, Imran, Muhammad, Guizani, Mohsen
- Authors: Guo, Zhiwei , Yu, Keping , Guo, Tan , Bashir, Ali , Imran, Muhammad , Guizani, Mohsen
- Date: 2020
- Type: Text , Conference paper
- Relation: 2020 IEEE Global Communications Conference, GLOBECOM 2020, Virtual Taipei, 7-11 December 2020 Vol. 2020-January
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- Description: With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedbacks. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game (GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods. © 2020 IEEE.
- Authors: Guo, Zhiwei , Yu, Keping , Guo, Tan , Bashir, Ali , Imran, Muhammad , Guizani, Mohsen
- Date: 2020
- Type: Text , Conference paper
- Relation: 2020 IEEE Global Communications Conference, GLOBECOM 2020, Virtual Taipei, 7-11 December 2020 Vol. 2020-January
- Full Text:
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- Description: With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedbacks. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game (GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods. © 2020 IEEE.
Motivational factors of Australian mobile gamers
- Greenwood, Jordan, Achterbosch, Leigh, Meredith, Grant, Vamplew, Peter
- Authors: Greenwood, Jordan , Achterbosch, Leigh , Meredith, Grant , Vamplew, Peter
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: Proceedings of the Australasian Computer Science Week Multiconference (ACSW 2020); Melbourne, Australia; 4th-6th February 2020 p. 6
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- Description: Mobile games are a fast growing industry, overtaking all other video game platforms with year on year increases in revenue. Many studies have been conducted to explore the motivations of why video games players play their selected games. However very little research has focused on mobile gamers. In addition, Australian studies on the topic are sparse. This paper aimed to discover what motivates a mobile gamer from the perspective of the initial motivational factors attracting them to a mobile game, and the motivational factors that provide interest to continue playing and thereby increase game longevity. A survey was conducted online for Australian participants, which attracted 123 respondents. The survey was formulated by focusing on the 12 key subcomponents as motivational factors of the Gamer Motivational Profile v2 model devised by Quantic Foundry. It was discovered that mobile gamers are a completely different breed of gamer in contrast to the general video gamer. Strategy and challenge which are subcomponents of mastery proved popular among all mobile gamers, while destruction and excitement, subcomponents of action, were often the least motivating factors of all. With the newly discovered data, perhaps mobile game developers can pursue the correct avenues of game design when catering to their target audience.
- Authors: Greenwood, Jordan , Achterbosch, Leigh , Meredith, Grant , Vamplew, Peter
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: Proceedings of the Australasian Computer Science Week Multiconference (ACSW 2020); Melbourne, Australia; 4th-6th February 2020 p. 6
- Full Text:
- Reviewed:
- Description: Mobile games are a fast growing industry, overtaking all other video game platforms with year on year increases in revenue. Many studies have been conducted to explore the motivations of why video games players play their selected games. However very little research has focused on mobile gamers. In addition, Australian studies on the topic are sparse. This paper aimed to discover what motivates a mobile gamer from the perspective of the initial motivational factors attracting them to a mobile game, and the motivational factors that provide interest to continue playing and thereby increase game longevity. A survey was conducted online for Australian participants, which attracted 123 respondents. The survey was formulated by focusing on the 12 key subcomponents as motivational factors of the Gamer Motivational Profile v2 model devised by Quantic Foundry. It was discovered that mobile gamers are a completely different breed of gamer in contrast to the general video gamer. Strategy and challenge which are subcomponents of mastery proved popular among all mobile gamers, while destruction and excitement, subcomponents of action, were often the least motivating factors of all. With the newly discovered data, perhaps mobile game developers can pursue the correct avenues of game design when catering to their target audience.
On the correlation between research complexity and academic competitiveness
- Ren, Jing, Lee, Ivan, Wang, Lei, Chen, Xiangtai, Xia, Feng
- Authors: Ren, Jing , Lee, Ivan , Wang, Lei , Chen, Xiangtai , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Kyoto, Japan, 30 November to 1 December 2020, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12504 LNCS, p. 416-422
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- Description: Academic capacity is a common way to reflect the educational level of a country or district. The aim of this study is to explore the difference between the scientific research level of institutions and countries. By proposing an indicator named Citation-weighted Research Complexity Index (CRCI), we profile the academic capacity of universities and countries with respect to research complexity. The relationships between CRCI of universities and other relevant academic evaluation indicators are examined. To explore the correlation between academic capacity and economic level, the relationship between research complexity and GDP per capita is analysed. With experiments on the Microsoft Academic Graph data set, we investigate publications across 183 countries and universities from the Academic Ranking of World Universities in 19 research fields. Experimental results reveal that universities with higher research complexity have higher fitness. In addition, for developed countries, the development of economics has a positive correlation with scientific research. Furthermore, we visualize the current level of scientific research across all disciplines from a global perspective. © 2020, Springer Nature Switzerland AG.
- Authors: Ren, Jing , Lee, Ivan , Wang, Lei , Chen, Xiangtai , Xia, Feng
- Date: 2020
- Type: Text , Conference paper
- Relation: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Kyoto, Japan, 30 November to 1 December 2020, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12504 LNCS, p. 416-422
- Full Text:
- Reviewed:
- Description: Academic capacity is a common way to reflect the educational level of a country or district. The aim of this study is to explore the difference between the scientific research level of institutions and countries. By proposing an indicator named Citation-weighted Research Complexity Index (CRCI), we profile the academic capacity of universities and countries with respect to research complexity. The relationships between CRCI of universities and other relevant academic evaluation indicators are examined. To explore the correlation between academic capacity and economic level, the relationship between research complexity and GDP per capita is analysed. With experiments on the Microsoft Academic Graph data set, we investigate publications across 183 countries and universities from the Academic Ranking of World Universities in 19 research fields. Experimental results reveal that universities with higher research complexity have higher fitness. In addition, for developed countries, the development of economics has a positive correlation with scientific research. Furthermore, we visualize the current level of scientific research across all disciplines from a global perspective. © 2020, Springer Nature Switzerland AG.
Partial undersampling of imbalanced data for cyber threats detection
- Moniruzzaman, Md, Bagirov, Adil, Gondal, Iqbal
- Authors: Moniruzzaman, Md , Bagirov, Adil , Gondal, Iqbal
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 2020 Australasian Computer Science Week Multiconference, ACSW 2020
- Full Text:
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- Description: Real-time detection of cyber threats is a challenging task in cyber security. With the advancement of technology and ease of access to the internet, more and more individuals and organizations are becoming the target for various cyber attacks such as malware, ransomware, spyware. The target of these attacks is to steal money or valuable information from the victims. Signature-based detection methods fail to keep up with the constantly evolving new threats. Machine learning based detection has drawn more attention of researchers due to its capability of detecting new and modified attacks based on previous attack's behaviour. The number of malicious activities in a certain domain is significantly low compared to the number of normal activities. Therefore, cyber threats detection data sets are imbalanced. In this paper, we proposed a partial undersampling method to deal with imbalanced data for detecting cyber threats. © 2020 ACM.
- Description: E1
- Authors: Moniruzzaman, Md , Bagirov, Adil , Gondal, Iqbal
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 2020 Australasian Computer Science Week Multiconference, ACSW 2020
- Full Text:
- Reviewed:
- Description: Real-time detection of cyber threats is a challenging task in cyber security. With the advancement of technology and ease of access to the internet, more and more individuals and organizations are becoming the target for various cyber attacks such as malware, ransomware, spyware. The target of these attacks is to steal money or valuable information from the victims. Signature-based detection methods fail to keep up with the constantly evolving new threats. Machine learning based detection has drawn more attention of researchers due to its capability of detecting new and modified attacks based on previous attack's behaviour. The number of malicious activities in a certain domain is significantly low compared to the number of normal activities. Therefore, cyber threats detection data sets are imbalanced. In this paper, we proposed a partial undersampling method to deal with imbalanced data for detecting cyber threats. © 2020 ACM.
- Description: E1