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Articles 20311 - 20340 of 302510

Full-Text Articles in Physical Sciences and Mathematics

Constrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury Jan 2023

Constrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, for a Borel probability measure P on a Euclidean space Rk, we extend the definitions of nth unconstrained quantization error, unconstrained quantization dimension, and unconstrained quantization coefficient, which traditionally in the literature known as nth quantization error, quantization dimension, and quantization coefficient, to the definitions of nth constrained quantization error, constrained quantization dimension, and constrained quantization coefficient. The work in this paper extends the theory of quantization and opens a new area of research. In unconstrained quantization, the elements in an optimal set are the conditional expectations in their own Voronoi regions, and it is not true …

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Photocatalytic Reforming Of Lignocellulose: A Review, Xinyuan Xu, Lei Shi, Shu Zhang, Zhimin Ao, Jinqiang Zhang, Shaobin Wang, Hongqi Sun Jan 2023

Photocatalytic Reforming Of Lignocellulose: A Review, Xinyuan Xu, Lei Shi, Shu Zhang, Zhimin Ao, Jinqiang Zhang, Shaobin Wang, Hongqi Sun

Research outputs 2022 to 2026

Biomass has been considered as a promising energy resource to combat the exhaustion of fossil fuels, as it is renewable, sustainable, and clean. Photocatalytic reforming is a novel technology to utilize solar energy for upgrading biomass in relatively mild conditions. This process efficiently reforms and recasts biomass into hydrogen and/or valuable chemicals. To date, lignocellulose, including cellulose, hemicellulose and lignin, has attracted extensive studies in facile photocatalytic valorisation. This review summarizes and analyzes the most recent research advances on photoreforming of lignocellulose to provide insights for future research, with a particular emphasis on the reformation of lignin because of its …

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A Provable Secure And Efficient Authentication Framework For Smart Manufacturing Industry, Muhammad Hammad, Akhtar Badshah, Ghulam Abbas, Hisham Alasmary, Muhammad Waqas, Wasim A. Khan Jan 2023

A Provable Secure And Efficient Authentication Framework For Smart Manufacturing Industry, Muhammad Hammad, Akhtar Badshah, Ghulam Abbas, Hisham Alasmary, Muhammad Waqas, Wasim A. Khan

Research outputs 2022 to 2026

Smart manufacturing is transforming the manufacturing industry by enhancing productivity and quality, driving growth in the global economy. The Internet of Things (IoT) has played a crucial role in realizing Industry 4.0, where machines can communicate and interact in real-time. Despite these advancements, security remains a major challenge in developing and deploying smart manufacturing. As cyber-attacks become more prevalent, researchers are making security a top priority. Although IoT and Industrial IoT (IIoT) are used to establish smart industries, these systems remain vulnerable to various types of attacks. To address these security issues, numerous authentication methods have been proposed. However, many …

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A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung Jan 2023

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung

Research outputs 2022 to 2026

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …

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Biofilm Formation On The Surface Of Monazite And Xenotime During Bioleaching, Arya Van Alin, Melissa K. Corbett, Homayoun Fathollahzadeh, M. Christian Tjiam, William D. A. Rickard, Xiao Sun, Andrew Putnis, Jacques Eksteen, Anna H. Kaksonen, Elizabeth Watkin Jan 2023

Biofilm Formation On The Surface Of Monazite And Xenotime During Bioleaching, Arya Van Alin, Melissa K. Corbett, Homayoun Fathollahzadeh, M. Christian Tjiam, William D. A. Rickard, Xiao Sun, Andrew Putnis, Jacques Eksteen, Anna H. Kaksonen, Elizabeth Watkin

Research outputs 2022 to 2026

Microbial attachment and biofilm formation is a ubiquitous behaviour of microorganisms and is the most crucial prerequisite of contact bioleaching. Monazite and xenotime are two commercially exploitable minerals containing rare earth elements (REEs). Bioleaching using phosphate solubilizing microorganisms is a green biotechnological approach for the extraction of REEs. In this study, microbial attachment and biofilm formation of Klebsiella aerogenes ATCC 13048 on the surface of these minerals were investigated using confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). In a batch culture system, K. aerogenes was able to attach and form biofilms on the surface of three phosphate …

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Catalytic Pollutant Upgrading To Dual-Asymmetric Mno2@Polymer Nanotubes As Self-Propelled And Controlled Micromotors For H2o2 Decomposition, Yangyang Yang, Kunsheng Hu, Zhong-Shuai Zhu, Yu Yao, Panpan Zhang, Peng Zhou, Pengwei Huo, Xiaoguang Duan, Hongqi Sun, Shaobin Wang Jan 2023

Catalytic Pollutant Upgrading To Dual-Asymmetric Mno2@Polymer Nanotubes As Self-Propelled And Controlled Micromotors For H2o2 Decomposition, Yangyang Yang, Kunsheng Hu, Zhong-Shuai Zhu, Yu Yao, Panpan Zhang, Peng Zhou, Pengwei Huo, Xiaoguang Duan, Hongqi Sun, Shaobin Wang

Research outputs 2022 to 2026

Industrial and disinfection wastewater typically contains high levels of organic pollutants and residue hydrogen peroxide, which have caused environmental concerns. In this work, dual-asymmetric MnO2@polymer microreactors are synthesized via pollutant polymerization for self-driven and controlled H2O2 decomposition. A hollow and asymmetric MnO2 nanotube is derived from MnO2 nanorods by selective acid etching and then coated by a polymeric layer from an aqueous phenolic pollutant via catalytic peroxymonosulfate (PMS)-induced polymerization. The evolution of particle-like polymers is controlled by solution pH, molar ratios of PMS/phenol, and reaction duration. The polymer-covered MnO2 tubing-structured micromotors presented a controlled motion velocity, due to the reverse …

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Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz Jan 2023

Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz

Research outputs 2022 to 2026

During production from oil wells, the deposition of asphaltene and wax at surface facilities and porous media is one of the major operational challenges. The crude oil production rate is significantly reduced due to asphaltene deposition inside the reservoir. In addition, the deposition of these solids inside the surface facilities is costly to oil companies. In this study, the efficiency of different solvents in dissolving asphaltene and wax was investigated through static and dynamic tests. The analysis of solid deposits from the surface choke of one of the Iranian carbonate oil fields showed that they consisted of 41.3 wt % …

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Decline Of Seagrass (Posidonia Oceanica) Production Over Two Decades In The Face Of Warming Of The Eastern Mediterranean Sea, Victoria Litsi-Mizan, Pavlos T. Efthymiadis, Vasilis Gerakaris, Oscar Serrano, Manolis Tsapakis, Eugenia T. Apostolaki Jan 2023

Decline Of Seagrass (Posidonia Oceanica) Production Over Two Decades In The Face Of Warming Of The Eastern Mediterranean Sea, Victoria Litsi-Mizan, Pavlos T. Efthymiadis, Vasilis Gerakaris, Oscar Serrano, Manolis Tsapakis, Eugenia T. Apostolaki

Research outputs 2022 to 2026

* The response of Posidonia oceanica meadows to global warming of the Eastern Mediterranean Sea, where the increase in sea surface temperature (SST) is particularly severe, is poorly investigated. * Here, we reconstructed the long-term P. oceanica production in 60 meadows along the Greek Seas over two decades (1997–2018), using lepidochronology. We determined the effect of warming on production by reconstructing the annual and maximum (i.e. August) SST, considering the role of other production drivers related to water quality (i.e. Chla, suspended particulate matter, Secchi depth). * Grand mean (±SE) production across all sites and the study period was 48 …

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Doa Estimation For Hybrid Massive Mimo Systems Using Mixed-Adcs: Performance Loss And Energy Efficiency, Baihua Shi, Qi Zhang, Rongen Dong, Qijuan Jie, Shihao Yan, Feng Shu, Jiangzhou Wang Jan 2023

Doa Estimation For Hybrid Massive Mimo Systems Using Mixed-Adcs: Performance Loss And Energy Efficiency, Baihua Shi, Qi Zhang, Rongen Dong, Qijuan Jie, Shihao Yan, Feng Shu, Jiangzhou Wang

Research outputs 2022 to 2026

Due to the power consumption and high circuit cost in antenna arrays, the practical application of massive multiple-input multiple-output (MIMO) in the sixth generation (6G) and future wireless networks is still challenging. Employing low-resolution analog-to-digital converters (ADCs) and hybrid analog and digital (HAD) structure is two low-cost choices with acceptable performance loss. In this paper, the combination of the mixed-ADC architecture and HAD structure employed at receiver is proposed for direction of arrival (DOA) estimation, which will be applied to the beamforming tracking and alignment in 6G. By adopting the additive quantization noise model, the exact closed-form expression of the …

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Further Investigation Of Lead Exposure As A Potential Threatening Process For A Scavenging Marsupial Species, D. J. Hutchinson, E. M. Jones, J. M. Pay, J. R. Clarke, Michael T. Lohr, J. O. Hampton Jan 2023

Further Investigation Of Lead Exposure As A Potential Threatening Process For A Scavenging Marsupial Species, D. J. Hutchinson, E. M. Jones, J. M. Pay, J. R. Clarke, Michael T. Lohr, J. O. Hampton

Research outputs 2022 to 2026

There is a growing recognition of the harmful effects of lead exposure on avian and mammalian scavengers. This can lead to both lethal and non-lethal effects which may negatively impact wildlife populations. Our objective was to assess medium-term lead exposure in wild Tasmanian devils (Sarcophilus harrisii). Frozen liver samples (n = 41), opportunistically collected in 2017–2022, were analysed using inductively coupled plasma mass spectrometry (ICP-MS) to determine liver lead concentrations. These results were then used to calculate the proportion of animals with elevated lead levels ( > 5 mg/kg dry weight) and examine the role of explanatory variables that may have …

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Co-Designing A Multi-Criteria Approach To Ranking Hazards To And From Australia’S Emerging Offshore Blue Economy, Mischa P. Turschwell, Christopher J. Brown, Myriam Lacharité, Jess Melbourne-Thomas, Keith R. Hayes, Rodrigo H. Bustamante, Jeffrey M. Dambacher, Karen Evans, Pedro Fidelman, Darla H. Macdonald, Ingrid Van Putten, Graham Wood, Nagi Abdussamie, Mathilda Bates, Damien Blackwell, Steven D'Alessandro, Ian Dutton, Jessica A. Ericson, Christopher L. J. Frid, Carmel Mcdougall, Mary-Anne Lea, David Rissik, Rowan Trebilco, Elizabeth A. Fulton Jan 2023

Co-Designing A Multi-Criteria Approach To Ranking Hazards To And From Australia’S Emerging Offshore Blue Economy, Mischa P. Turschwell, Christopher J. Brown, Myriam Lacharité, Jess Melbourne-Thomas, Keith R. Hayes, Rodrigo H. Bustamante, Jeffrey M. Dambacher, Karen Evans, Pedro Fidelman, Darla H. Macdonald, Ingrid Van Putten, Graham Wood, Nagi Abdussamie, Mathilda Bates, Damien Blackwell, Steven D'Alessandro, Ian Dutton, Jessica A. Ericson, Christopher L. J. Frid, Carmel Mcdougall, Mary-Anne Lea, David Rissik, Rowan Trebilco, Elizabeth A. Fulton

Research outputs 2022 to 2026

A multi-sectoral assessment of risks can support the management and investment decisions necessary for emerging blue economy industries to succeed. Traditional risk assessment methods will be challenged when applied to the complex socio-ecological systems that characterise offshore environments, and when data available to support management are lacking. Therefore, there is a need for assessments that account for multiple sectors. Here we describe the development of an efficient method for an integrated hazard analysis that is a precursor to full risk assessments. Our approach combines diverse disciplinary expertise, expert elicitation and multi-criteria analysis to rank hazards, so it encompasses all types …

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Cyber-Aidd: A Novel Approach To Implementing Improved Cyber Security Resilience For Large Australian Healthcare Providers Using A Unified Modelling Language Ontology, Martin Dart, Mohiuddin Ahmed Jan 2023

Cyber-Aidd: A Novel Approach To Implementing Improved Cyber Security Resilience For Large Australian Healthcare Providers Using A Unified Modelling Language Ontology, Martin Dart, Mohiuddin Ahmed

Research outputs 2022 to 2026

Purpose: This paper proposes a novel cyber security risk governance framework and ontology for large Australian healthcare providers, using the structure and simplicity of the Unified Modelling Language (UML). This framework is intended to mitigate impacts from the risk areas of: (1) cyber-attacks, (2) incidents, (3) data breaches, and (4) data disclosures. Methods Using a mixed-methods approach comprised of empirical evidence discovery and phenomenological review, existing literature is sourced to confirm baseline ontological definitions. These are supplemented with Australian government reports, professional standards publications and legislation covering cyber security, data breach reporting and healthcare governance. Historical examples of healthcare cyber …

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Seagrass Posidonia Escarpments Support High Diversity And Biomass Of Rocky Reef Fishes, Oscar Serrano Gras, Karina Inostroza, Glenn Hyndes, Alan M. Friedlander, Eduard Serrano, Caitlin Rae, Enric Ballesteros Jan 2023

Seagrass Posidonia Escarpments Support High Diversity And Biomass Of Rocky Reef Fishes, Oscar Serrano Gras, Karina Inostroza, Glenn Hyndes, Alan M. Friedlander, Eduard Serrano, Caitlin Rae, Enric Ballesteros

Research outputs 2022 to 2026

Although seagrass meadows form a relatively homogenous habitat, escarpments, which form three-dimensional structures and originate from the erosion of seagrass peat, can provide important habitat for reef fishes. Here, we compare fish assemblages and habitat structural complexity among seagrass Posidonia australis escarpments and canopies, as well as limestone reef habitats, to understand the role of seagrass escarpments as reef fish habitat in Shark Bay, Western Australia. The total number of fish species, fish biomass, and top predator biomass were significantly higher in seagrass escarpments and reef habitats than in seagrass canopies due to lower habitat structural complexity and thus becoming …

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Voltammetric Determination Of Inorganic Arsenic In Mildly Acidified (Ph 4.7) Groundwaters From Mexico And India, Martijn Eikelboom, Yaxuan Wang, Gemma Portlock, Arthur Gourain, Joseph Gardner, Jay Bullen, Paul Lewtas, Matthieu Carriere, Alexandra Alvarez, Arun Kumar, Shane O'Prey, Tamás Tölgyes, Dario Omanović, Subhamoy Bhowmick, Dominik Salaun, Pascal Salaun Jan 2023

Voltammetric Determination Of Inorganic Arsenic In Mildly Acidified (Ph 4.7) Groundwaters From Mexico And India, Martijn Eikelboom, Yaxuan Wang, Gemma Portlock, Arthur Gourain, Joseph Gardner, Jay Bullen, Paul Lewtas, Matthieu Carriere, Alexandra Alvarez, Arun Kumar, Shane O'Prey, Tamás Tölgyes, Dario Omanović, Subhamoy Bhowmick, Dominik Salaun, Pascal Salaun

Research outputs 2022 to 2026

Routine monitoring of inorganic arsenic in groundwater using sensitive, reliable, easy-to-use and affordable analytical methods is integral to identifying sources, and delivering appropriate remediation solutions, to the widespread global issue of arsenic pollution. Voltammetry has many advantages over other analytical techniques, but the low electroactivity of arsenic(V) requires the use of either reducing agents or relatively strong acidic conditions, which both complicate the analytical procedures, and require more complex material handling by skilled operators. Here, we present the voltammetric determination of total inorganic arsenic in conditions of near-neutral pH using a new commercially available 25 m diameter gold microwire (called …

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Development Of A 3-D-Printable Device For Continuous Measuring Of Heavy Metal Ion Concentrations, Charl De Villiers, Magdalena Wajrak, Alex Lubansky Jan 2023

Development Of A 3-D-Printable Device For Continuous Measuring Of Heavy Metal Ion Concentrations, Charl De Villiers, Magdalena Wajrak, Alex Lubansky

Research outputs 2022 to 2026

Three-dimensional (3-D) printing offers the potential to create a range of tailored devices within many different industrial facilities. In this article, devices were designed and fabricated using 3-D printing to house electrodes for the testing of heavy metal concentration in hazardous fluids, particularly for biological samples such as urine or blood. The devices, connected to a syringe pump, were shown to be able to be operated without leaking. Proof of concept experiments were performed using Anodic Stripping Voltammetry (ASV) methods, demonstrating that the devices are able to be used for quick, cheap testing, showing the potential of the technique as …

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Hybrid Warfare And Disinformation: A Ukraine War Perspective, Sascha-Dominik Dov Bachmann, Dries Putter, Guy Duczynski Jan 2023

Hybrid Warfare And Disinformation: A Ukraine War Perspective, Sascha-Dominik Dov Bachmann, Dries Putter, Guy Duczynski

Research outputs 2022 to 2026

Misinformation, disinformation and mal information are part of the information disorder construct, dominating the information warfare domain. These are key enablers associated with grey zone operations, and an integral part of current adversaries' and competitors' hybrid warfare tool kit. Disinformation, in combination with influence operations, also plays an important role within the concept of hybrid warfare; both from a threat–and own resilience perspective. This article reflects on these information warfare tools and their application by Russia in the current Russo-Ukraine war, offering potentially considerable force multipliers in the information domain for the Russian aggressor. Hybrid warfare and associated threats, specifically …

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Disintegration Evaluation Of Mudrock Fragment Through Wet-Dry Cycle By Quantitative Indices, Misbahudin Misbahudin, Dian Yesy Fatimah, Elfarino Trizani Jan 2023

Disintegration Evaluation Of Mudrock Fragment Through Wet-Dry Cycle By Quantitative Indices, Misbahudin Misbahudin, Dian Yesy Fatimah, Elfarino Trizani

ASEAN Journal on Science and Technology for Development

The disintegration of mudrock during moisture content change caused severe cases in several engineering works in Indonesia. One interesting site is Hambalang, Bogor Regency, West Java Province. The wetting and drying cycle is the easiest and fastest test to evaluate disintegration. After undergoing the process, samples of mudrocks disintegrate into smaller fragments. This paper evaluated the characteristics of the slaked material of mudrock by quantitative indices. The mudrock evaluated in this study underwent rapid disintegration in a short period, indicated by megascopic description and quantitative indices. In addition, evolutionary disintegration up to eight cycles has the same characteristics as the …

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Aspect Sentiment Triplet Extraction Incorporating Syntactic Constituency Parsing Tree And Commonsense Knowledge Graph, Zhenda Hu, Zhaoxia Wang, Yinglin Wang, Ah-Hwee Tan Jan 2023

Aspect Sentiment Triplet Extraction Incorporating Syntactic Constituency Parsing Tree And Commonsense Knowledge Graph, Zhenda Hu, Zhaoxia Wang, Yinglin Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The aspect sentiment triplet extraction (ASTE) task aims to extract the target term and the opinion term, and simultaneously identify the sentiment polarity of target-opinion pairs from the given sentences. While syntactic constituency information and commonsense knowledge are both important and valuable for the ASTE task, only a few studies have explored how to integrate them via flexible graph convolutional networks (GCNs) for this task. To address this gap, this paper proposes a novel end-to-end model, namely GCN-EGTS, which is an enhanced Grid Tagging Scheme (GTS) for ASTE leveraging syntactic constituency parsing tree and a commonsense knowledge graph based on …

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Is A Pretrained Model The Answer To Situational Awareness Detection On Social Media?, Siaw Ling Lo, Kahhe Lee, Yuhao Zhang Jan 2023

Is A Pretrained Model The Answer To Situational Awareness Detection On Social Media?, Siaw Ling Lo, Kahhe Lee, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Social media can be valuable for extracting information about an event or incident on the ground. However, the vast amount of content shared, and the linguistic variants of languages used on social media make it challenging to identify important situational awareness content to aid in decision-making for first responders. In this study, we assess whether pretrained models can be used to address the aforementioned challenges on social media. Various pretrained models, including static word embedding (such as Word2Vec and GloVe) and contextualized word embedding (such as DistilBERT) are studied in detail. According to our findings, a vanilla DistilBERT pretrained language …

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Analytics-Enabled Authentic Assessment Design Approach For Digital Education, Tristan Lim, Swapna Gottipati, Michelle L. F. Cheong, Jun Wei Ng, Christopher Pang Jan 2023

Analytics-Enabled Authentic Assessment Design Approach For Digital Education, Tristan Lim, Swapna Gottipati, Michelle L. F. Cheong, Jun Wei Ng, Christopher Pang

Research Collection School Of Computing and Information Systems

There are known issues in authentic assessment design practices in digital education, which include the lack of freedom-of-choice, lack of focus on the multimodal nature of the digital process, and shortage of effective feedbacks. This study looks to identify an assessment design construct that overcomes these issues. Specifically, this study introduces an authentic assessment that combines gamification (G) with heutagogy (H) and multimodality (M) of assessments, building upon rich pool of multimodal data and learning analytics (A), known as GHMA. This is a skills-oriented assessment approach, where learners determine their own goals and create individualized multimodal artefacts, receive cognitive challenge …

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How To Find Actionable Static Analysis Warnings: A Case Study With Findbugs, Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies Jan 2023

How To Find Actionable Static Analysis Warnings: A Case Study With Findbugs, Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies

Research Collection School Of Computing and Information Systems

Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict which static code warnings should ot be ignored, we suggest that analysts need to look deeper into their algorithms to find choices that better improve the particulars of their specific problem. Specifically, we show here that effective predictors of such warnings can be created by methods that ocally adjust the decision boundary (between actionable warnings and others). These methods yield a new high water-mark for recognizing actionable static code warnings. For eight …

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A Secure Emr Sharing System With Tamper Resistance And Expressive Access Control, Shengmin Xu, Jianting Ning, Yingjiu Li, Yinghui Zhang, Guowen Xu, Xinyi Huang, Robert H. Deng Jan 2023

A Secure Emr Sharing System With Tamper Resistance And Expressive Access Control, Shengmin Xu, Jianting Ning, Yingjiu Li, Yinghui Zhang, Guowen Xu, Xinyi Huang, Robert H. Deng

Research Collection School Of Computing and Information Systems

To reduce the cost of human and material resources and improve the collaborations among medical systems, research laboratories and insurance companies for healthcare researches and commercial activities, electronic medical records (EMRs) have been proposed to shift from paperwork to friendly shareable electronic records. To take advantage of EMRs efficiently and reduce the cost of local storage, EMRs are usually outsourced to the remote cloud for sharing medical data with authorized users. However, cloud service providers are untrustworthy. In this paper, we propose an efficient, secure, and flexible EMR sharing system by introducing a novel cryptosystem called dual-policy revocable attribute-based encryption …

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Contextual Path Retrieval: A Contextual Entity Relation Embedding-Based Approach, Pei-Chi Lo, Ee-Peng Lim Jan 2023

Contextual Path Retrieval: A Contextual Entity Relation Embedding-Based Approach, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Contextual path retrieval (CPR) refers to the task of finding contextual path(s) between a pair of entities in a knowledge graph that explains the connection between them in a given context. For this novel retrieval task, we propose the Embedding-based Contextual Path Retrieval (ECPR) framework. ECPR is based on a three-component structure that includes a context encoder and path encoder that encode query context and path, respectively, and a path ranker that assigns a ranking score to each candidate path to determine the one that should be the contextual path. For context encoding, we propose two novel context encoding methods, …

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Taurus: Towards A Unified Force Representation And Universal Solver For Graph Layout, Mingliang Xue, Zhi Wang, Fahai Zhong, Yong Wang, Mingliang Xu, Oliver Deussen, Yunhai Wang Jan 2023

Taurus: Towards A Unified Force Representation And Universal Solver For Graph Layout, Mingliang Xue, Zhi Wang, Fahai Zhong, Yong Wang, Mingliang Xu, Oliver Deussen, Yunhai Wang

Research Collection School Of Computing and Information Systems

Over the past few decades, a large number of graph layout techniques have been proposed for visualizing graphs from various domains. In this paper, we present a general framework, Taurus, for unifying popular techniques such as the spring-electrical model, stress model, and maxent-stress model. It is based on a unified force representation, which formulates most existing techniques as a combination of quotient-based forces that combine power functions of graph-theoretical and Euclidean distances. This representation enables us to compare the strengths and weaknesses of existing techniques, while facilitating the development of new methods. Based on this, we propose a new balanced …

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Learning Large Neighborhood Search For Vehicle Routing In Airport Ground Handling, Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhenghua Chen Jan 2023

Learning Large Neighborhood Search For Vehicle Routing In Airport Ground Handling, Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhenghua Chen

Research Collection School Of Computing and Information Systems

Dispatching vehicle fleets to serve flights is a key task in airport ground handling (AGH). Due to the notable growth of flights, it is challenging to simultaneously schedule multiple types of operations (services) for a large number of flights, where each type of operation is performed by one specific vehicle fleet. To tackle this issue, we first represent the operation scheduling as a complex vehicle routing problem and formulate it as a mixed integer linear programming (MILP) model. Then given the graph representation of the MILP model, we propose a learning assisted large neighborhood search (LNS) method using data generated …

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A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu Jan 2023

A Diversity-Enhanced Memetic Algorithm For Solving Electric Vehicle Routing Problems With Time Windows And Mixed Backhauls, Jianhua Xiao, Jingguo Du, Zhiguang Cao, Xingyi Zhang, Yunyun Niu

Research Collection School Of Computing and Information Systems

The electric vehicle routing problem (EVRP) has been studied increasingly because of environmental concerns. However, existing studies on the EVRP mainly focus on time windows and sole linehaul customers, which might not be practical as backhaul customers are also ubiquitous in reality. In this study, we investigate an EVRP with time windows and mixed backhauls (EVRPTWMB), where both linehaul and backhaul customers exist and can be served in any order. To address this challenging problem, we propose a diversity-enhanced memetic algorithm (DEMA) that integrates three types of novel operators, including genetic operators based on adaptive selection mechanism, a selection operator …

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Neighbor-Anchoring Adversarial Graph Neural Networks, Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng Jan 2023

Neighbor-Anchoring Adversarial Graph Neural Networks, Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng

Research Collection School Of Computing and Information Systems

Graph neural networks (GNNs) have witnessed widespread adoption due to their ability to learn superior representations for graph data. While GNNs exhibit strong discriminative power, they often fall short of learning the underlying node distribution for increased robustness. To deal with this, inspired by generative adversarial networks (GANs), we investigate the problem of adversarial learning on graph neural networks, and propose a novel framework named NAGNN (i.e., Neighbor-anchoring Adversarial Graph Neural Networks) for graph representation learning, which trains not only a discriminator but also a generator that compete with each other. In particular, we propose a novel neighbor-anchoring strategy, where …

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Crowdfa: A Privacy-Preserving Mobile Crowdsensing Paradigm Via Federated Analytics, Bowen Zhao, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Yingjiu Li, Robert H. Deng Jan 2023

Crowdfa: A Privacy-Preserving Mobile Crowdsensing Paradigm Via Federated Analytics, Bowen Zhao, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Mobile crowdsensing (MCS) systems typically struggle to address the challenge of data aggregation, incentive design, and privacy protection, simultaneously. However, existing solutions usually focus on one or, at most, two of these issues. To this end, this paper presents CROWD FA, a novel paradigm for privacy-preserving MCS through federated analytics (FA), which aims to achieve a well-rounded solution encompassing data aggregation, incentive design, and privacy protection. Specifically, inspired by FA, CROWD FA initiates an MCS computing paradigm that enables data aggregation and incentive design. Participants can perform aggregation operations on their local data, facilitated by CROWD FA, which supports various …

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A Secure And Robust Knowledge Transfer Framework Via Stratified-Causality Distribution Adjustment In Intelligent Collaborative Services, Ju Jia, Siqi Ma, Lina Wang, Yang Liu, Robert H. Deng Jan 2023

A Secure And Robust Knowledge Transfer Framework Via Stratified-Causality Distribution Adjustment In Intelligent Collaborative Services, Ju Jia, Siqi Ma, Lina Wang, Yang Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

The rapid development of device-edge-cloud collaborative computing techniques has actively contributed to the popularization and application of intelligent service models. The intensity of knowledge transfer plays a vital role in enhancing the performance of intelligent services. However, the existing knowledge transfer methods are mainly implemented through data fine-tuning and model distillation, which may cause the leakage of data privacy or model copyright in intelligent collaborative systems. To address this issue, we propose a secure and robust knowledge transfer framework through stratified-causality distribution adjustment (SCDA) for device-edge-cloud collaborative services. Specifically, a simple yet effective density-based estimation is first employed to obtain …

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Seven Pillars For The Future Of Artificial Intelligence, Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho Jan 2023

Seven Pillars For The Future Of Artificial Intelligence, Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho

Research Collection School Of Computing and Information Systems

In recent years, AI research has showcased tremendous potential to impact positively humanity and society. Although AI frequently outperforms humans in tasks related to classification and pattern recognition, it continues to face challenges when dealing with complex tasks such as intuitive decision-making, sense disambiguation, sarcasm detection, and narrative understanding, as these require advanced kinds of reasoning, e.g., commonsense reasoning and causal reasoning, which have not been emulated satisfactorily yet. To address these shortcomings, we propose seven pillars that we believe represent the key hallmark features for the future of AI, namely: Multidisciplinarity, Task Decomposition, Parallel Analogy, Symbol Grounding, Similarity Measure, …

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