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Full-Text Articles in Engineering

Utilizing Qr Codes To Verify The Visual Fidelity Of Image Datasets For Machine Learning, Yang-Wai Chow, Willy Susilo, Jianfang Wang, Richard Buckland, Joon Sang Baek, Jongkil Kim, Nan Li Jan 2021

Utilizing Qr Codes To Verify The Visual Fidelity Of Image Datasets For Machine Learning, Yang-Wai Chow, Willy Susilo, Jianfang Wang, Richard Buckland, Joon Sang Baek, Jongkil Kim, Nan Li

Faculty of Engineering and Information Sciences - Papers: Part B

Machine learning is becoming increasingly popular in modern technology and has been adopted in various application areas. However, researchers have demonstrated that machine learning models are vulnerable to adversarial examples in their inputs, which has given rise to a field of research known as adversarial machine learning. Potential adversarial attacks include methods of poisoning datasets by perturbing input samples to mislead machine learning models into producing undesirable results. While such perturbations are often subtle and imperceptible from the perspective of a human, they can greatly affect the performance of machine learning models. This paper presents two methods of verifying the ...


Laboratory Learning Objectives Measurement: Relationships Between Student Evaluation Scores And Perceived Learning, Sasha Nikolic, Thomas Suesse, Kosta Jovanovic, Zarko Stanisavljevic Jan 2021

Laboratory Learning Objectives Measurement: Relationships Between Student Evaluation Scores And Perceived Learning, Sasha Nikolic, Thomas Suesse, Kosta Jovanovic, Zarko Stanisavljevic

Faculty of Engineering and Information Sciences - Papers: Part B

Contribution: This article provides evidence that perceived learning has a relationship and influences the way students evaluate laboratory experiments, facilities, and demonstrators. Background: Debate continues on the capability and/or reliability of students to evaluate teaching and/or learning. Understanding such relationships can help educators decode evaluation data to develop more effective teaching experiences. Research Question: Does a relationship exist between student evaluation scores and perceived learning? Methodology: Perceived learning across the cognitive, psychomotor, and affective domains was measured using the Laboratory Learning Objectives Measurement (LLOM) tool at an Australian (344 students) and Serbian (181 students) university. A multilevel statistical ...


Mlc Tracking For Lung Sabr Is Feasible, Efficient And Delivers High-Precision Target Dose And Lower Normal Tissue Dose, Jeremy Booth, Vincent Caillet, Adam Briggs, Nicholas G. Hardcastle, Georgios Angelis, Dasantha Jayamanne, Meegan Shepherd, Alexander Podreka, Kathryn Szymura, Doan Nguyen, Per Poulsen, Ricky O'Brien, Benjamin Harris, Carol Haddad, Thomas Eade, Paul Keall Jan 2021

Mlc Tracking For Lung Sabr Is Feasible, Efficient And Delivers High-Precision Target Dose And Lower Normal Tissue Dose, Jeremy Booth, Vincent Caillet, Adam Briggs, Nicholas G. Hardcastle, Georgios Angelis, Dasantha Jayamanne, Meegan Shepherd, Alexander Podreka, Kathryn Szymura, Doan Nguyen, Per Poulsen, Ricky O'Brien, Benjamin Harris, Carol Haddad, Thomas Eade, Paul Keall

Faculty of Engineering and Information Sciences - Papers: Part B

Background and purpose: The purpose of this work is to present the clinical experience from the first-in-human trial of real-time tumor targeting via MLC tracking for stereotactic ablative body radiotherapy (SABR) of lung lesions. Methods and materials: Seventeen patients with stage 1 non-small cell lung cancer (NSCLC) or lung metastases were included in a study of electromagnetic transponder–guided MLC tracking for SABR (NCT02514512). Patients had electromagnetic transponders inserted near the tumor. An MLC tracking SABR plan was generated with planning target volume (PTV) expanded 5 mm from the end-exhale gross tumor volume (GTV). A clinically approved comparator plan was ...


Genetic Variation For Fusarium Crown Rot Tolerance In Durum Wheat, Gururaj Pralhad Kadkol, Jess Meza, Steven Simpfendorfer, Steve Harden, Brian R. Cullis Professor Jan 2021

Genetic Variation For Fusarium Crown Rot Tolerance In Durum Wheat, Gururaj Pralhad Kadkol, Jess Meza, Steven Simpfendorfer, Steve Harden, Brian R. Cullis Professor

Faculty of Engineering and Information Sciences - Papers: Part B

Tolerance to the cereal disease Fusarium crown rot (FCR) was investigated in a set of 34 durum wheat genotypes, with Suntop, (bread wheat) and EGA Bellaroi (durum) as tolerant and intolerant controls, in a series of replicated field trials over four years with inoculated (FCR-i) and non-inoculated (FCR-n) plots of the genotypes. The genotypes included con- ventional durum lines and lines derived from crossing durum with 2–49, a bread wheat geno- type with the highest level of partial resistance to FCR. A split plot trial design was chosen to optimize the efficiency for the prediction of FCR tolerance for ...


Electrospun Nanofibers For Efficient Adsorption Of Heavy Metals From Water And Wastewater, Maryam Salehi, Donya Sharafoddinzadeh, Fatemeh Mokhtari, Mitra Salehi Esfandarani, Shafieh Karami Jan 2021

Electrospun Nanofibers For Efficient Adsorption Of Heavy Metals From Water And Wastewater, Maryam Salehi, Donya Sharafoddinzadeh, Fatemeh Mokhtari, Mitra Salehi Esfandarani, Shafieh Karami

Faculty of Engineering and Information Sciences - Papers: Part B

Heavy metals (HMs) are persistent and toxic environmental pollutants that pose critical risks toward human health and environmental safety. Their efficient elimination from water and wastewater is essential to protect public health, ensure environmental safety, and enhance sustainability. In the recent decade, nanomaterials have been developed extensively for rapid and effective removal of HMs from water and wastewater and to address the certain economical and operational challenges associated with conventional treatment practices, including chemical precipitation, ion exchange, adsorption, and membrane separation. However, the complicated and expensive manufacturing process of nanoparticles and nanotubes, their reduced adsorption capacity due to the aggregation ...


Infinitesimal Knowledges, Rodney Nillsen Jan 2021

Infinitesimal Knowledges, Rodney Nillsen

Faculty of Engineering and Information Sciences - Papers: Part B

The notion of indivisibles and atoms arose in ancient Greece. The continuum—that is, the collection of points in a straight line segment, appeared to have paradoxical properties, arising from the ‘indivisibles’ that remain after a process of division has been carried out throughout the continuum. In the seventeenth century, Italian mathematicians were using new methods involving the notion of indivisibles, and the paradoxes of the continuum appeared in a new context. This cast doubt on the validity of the methods and the reliability of mathematical knowledge which had been regarded as established by the axiomatic method in geometry expounded ...


A Hybrid Unsupervised Clustering-Based Anomaly Detection Method, Guo Pu, Lijuan Wang, Jun Shen, Fang Dong Jan 2021

A Hybrid Unsupervised Clustering-Based Anomaly Detection Method, Guo Pu, Lijuan Wang, Jun Shen, Fang Dong

Faculty of Engineering and Information Sciences - Papers: Part B

In recent years, machine learning-based cyber intrusion detection methods have gained increasing popularity. The number and complexity of new attacks continue to rise; therefore, effective and intelligent solutions are necessary. Unsupervised machine learning techniques are particularly appealing to intrusion detection systems since they can detect known and unknown types of attacks as well as zero-day attacks. In the current paper, we present an unsupervised anomaly detection method, which combines Sub-Space Clustering (SSC) and One Class Support Vector Machine (OCSVM) to detect attacks without any prior knowledge. The proposed approach is evaluated using the well-known NSL-KDD dataset. The experimental results demonstrate ...


Towards A More Effective Bidirectional Lstm-Based Learning Model For Human-Bacterium Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Yaochu Jin Jan 2021

Towards A More Effective Bidirectional Lstm-Based Learning Model For Human-Bacterium Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Yaochu Jin

Faculty of Engineering and Information Sciences - Papers: Part B

The identification of protein-protein interaction (PPI) is one of the most important tasks to understand the biological functions and disease mechanisms. Although numerous databases of biological interactions have been published in debt to advanced high-throughput technology, the study of inter-species protein-protein interactions, especially between human and bacterium pathogens, remains an active yet challenging topic to harness computational models tackling the complex analysis and prediction tasks. In this paper, we comprehensively revisit the prediction task of human-bacterium protein-protein interactions (HB-PPI), which is a first ever endeavour to report an empirical evaluation in learning and predicting HB-PPI based on machine learning models ...


A Blockchain Based System For Safe Vaccine Supply And Supervision, Binbin Yong, Jun Shen, Xin Liu, Fucun Li, Huaming Chen, Qingguo Zhou Jan 2020

A Blockchain Based System For Safe Vaccine Supply And Supervision, Binbin Yong, Jun Shen, Xin Liu, Fucun Li, Huaming Chen, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

Immunization is an indispensable mechanism for preventing infectious diseases in modern society, and vaccine safety is closely related to public health and national security. However, issues such as vaccine expiration and vaccine record fraud are still widespread in vaccine supply chains. Therefore, an effective management system for the supervision of vaccine supply chains is urgently required. As the next generation of core technology after the Internet, blockchain is designed to build trust mechanisms that can change current information management methods. Meanwhile, the development of machine learning technologies provides additional ways to analyze the data in information management systems. The main ...


Validation Of Geant4 For Silicon Microdosimetry In Heavy Ion Therapy, David Bolst, Susanna Guatelli, Linh T. Tran, Lachlan Chartier, Jeremy A. Davis, Giordano Biasi, Dale A. Prokopovich, Alex Pogossov, Mark I. Reinhard, Marco Petasecca, Michael L. F Lerch, N Matsufuji, M Povoli, A Summanwar, Angela Kok, Michael A. Jackson, Anatoly B. Rosenfeld Jan 2020

Validation Of Geant4 For Silicon Microdosimetry In Heavy Ion Therapy, David Bolst, Susanna Guatelli, Linh T. Tran, Lachlan Chartier, Jeremy A. Davis, Giordano Biasi, Dale A. Prokopovich, Alex Pogossov, Mark I. Reinhard, Marco Petasecca, Michael L. F Lerch, N Matsufuji, M Povoli, A Summanwar, Angela Kok, Michael A. Jackson, Anatoly B. Rosenfeld

Faculty of Engineering and Information Sciences - Papers: Part B

Microdosimetry is a particularly powerful method to estimate the relative biological effectiveness (RBE) of any mixed radiation field. This is particularly convenient for therapeutic heavy ion therapy (HIT) beams, referring to ions larger than protons, where the RBE of the beam can vary significantly along the Bragg curve. Additionally, due to the sharp dose gradients at the end of the Bragg peak (BP), or spread out BP, to make accurate measurements and estimations of the biological properties of a beam a high spatial resolution is required, less than a millimetre. This requirement makes silicon microdosimetry particularly attractive due to the ...


Extraction Of Strategically Important Elements From Brines: Constraints And Opportunities, Biplob K. Pramanik, Long D. Nghiem, Faisal I. Hai Jan 2020

Extraction Of Strategically Important Elements From Brines: Constraints And Opportunities, Biplob K. Pramanik, Long D. Nghiem, Faisal I. Hai

Faculty of Engineering and Information Sciences - Papers: Part B

Strategically important elements are those that are vital to advanced manufacturing, low carbon technologies and other growing industries. Ongoing depletion and supply risks to these elements are a critical concern, and thus, recovery of these elements from low-grade ores and brines has generated significant interest worldwide. Among the strategically important elements, this paper focuses on rare earth elements (REEs), the platinum-group metals and lithium due to their wide application in the advanced industrial economics. We critically review the current methods such as precipitation, ion exchange and solvent extraction for extracting these elements from low-grade ores and brines and provide insight ...


Improved Integrated Nucleus-Nucleus Inelastic Cross Sections For Light Nuclides In Geant4, Dosatsu Sakata, Susanna Guatelli, E Simpson Jan 2020

Improved Integrated Nucleus-Nucleus Inelastic Cross Sections For Light Nuclides In Geant4, Dosatsu Sakata, Susanna Guatelli, E Simpson

Faculty of Engineering and Information Sciences - Papers: Part B

We propose a new root-mean-square radius parameterization for light nuclei A≤30 suitable for use in Geant4 calculations of nucleus-nucleus total hadronic inelastic scattering cross sections. The new approach takes into account the proton-neutron asymmetry of the reactants, and was fit to 360 measured total inelastic cross sections from the EXFOR database. Measured nuclear radii are better described in the new approach than the current Geant4 implementation, particularly for unstable nuclides, and there is better agreement with measured cross sections for both stable and unstable nuclides. The improved parameterization should help in carbon-ion therapy applications in particular.


A Takagi-Sugeno Fuzzy Model-Based Control Strategy For Variable Stiffness And Variable Damping Suspension, Xin Tang, Donghong Ning, Haiping Du, Weihua Li, Yibo Gao, Weijia Wen Jan 2020

A Takagi-Sugeno Fuzzy Model-Based Control Strategy For Variable Stiffness And Variable Damping Suspension, Xin Tang, Donghong Ning, Haiping Du, Weihua Li, Yibo Gao, Weijia Wen

Faculty of Engineering and Information Sciences - Papers: Part B

© 2013 IEEE. As the concept of variable stiffness and variable damping (VSVD) has increasingly drawn attention, suspensions applied with magnetorheological (MR) dampers to achieve varying stiffness and damping have been an attractive method to improve vehicle performance and driver comfort further. As highly nonlinearity of MR damper dynamics and coupled interconnections in the case of multi-output control, to build a direct control system for VSVD suspension based on multiple MR dampers is difficult. Applying Takagi-Sugeno (T-S) fuzzy model on the VSVD system enables the linear control theory to be directly utilized to build the multi-output controller for multi-MR dampers. In ...


Mechanistic-Empirical Permanent Deformation Models: Laboratory Testing, Modelling And Ranking, Ana Ramos, Antonio Gomes, Buddhima Indraratna, Ngoc Trung Ngo, Rui Calcada, Pedro Costa Jan 2020

Mechanistic-Empirical Permanent Deformation Models: Laboratory Testing, Modelling And Ranking, Ana Ramos, Antonio Gomes, Buddhima Indraratna, Ngoc Trung Ngo, Rui Calcada, Pedro Costa

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier Ltd Geomaterials exhibit elastoplastic behaviour during dynamic and repeated loading conditions. These loads are induced by the passage of a train or vehicle which then generates recoverable (resilient) deformation and/or permanent (plastic) deformation. Modelling this behaviour is still a challenge for geotechnical engineers as it implies the understanding of the complex deformation mechanism and application of advanced constitutive models. This paper reviews on the major causes of permanent deformation and the factors that influence the long-term performance of materials. It will also present the fundamental concepts of permanent deformation as well as the models and approaches used ...


Fault-Tolerant Analysis And Design Of Afpmsm With Multi-Disc Type Coreless Open-End Winding, Xiaoguang Wang, Meng Zhao, Lei Tang, Wei Xu, Md Rabiul Islam Jan 2020

Fault-Tolerant Analysis And Design Of Afpmsm With Multi-Disc Type Coreless Open-End Winding, Xiaoguang Wang, Meng Zhao, Lei Tang, Wei Xu, Md Rabiul Islam

Faculty of Engineering and Information Sciences - Papers: Part B

This article presents a multi-disc coreless axial flux permanent magnet synchronous machine (MDC-AFPMSM) with N pole and S pole type series magnetic circuit and open-end winding for high reliability applications, such as small power actuator system. Firstly, the topology and driving modes of MDC-AFPMSM are presented in details. In this article, a multi-objective optimization function is proposed to design the machine with full consideration of various influence factors. The drive performance indexes of four-phase, five-phase and six-phase machines are analyzed and discussed. Furthermore, main parameters of the five-phase MDC-AFPMSM with open-end winding are calculated. In order to reduce the torque ...


On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin Jan 2020

On Masking And Releasing Smart Meter Data At Micro-Level: The Multiplicative Noise Approach, John Brackenbury, P. Y. O'Shaughnessy, Yan-Xia Lin

Faculty of Engineering and Information Sciences - Papers: Part B

Smart meter electricity data presents privacy risks when malicious agents gain insights of private information, including residents’ lifestyle and daily habits. When allowing access to record-level data, we apply the multiplicative noise method to mask individual smart meter data, which simultaneously aims to minimise disclosure of a dwelling’s consumption signal to any third party and to enable accurate estimation of the sum of a cluster of households. Three testing criteria are introduced to measure the performance of multiplicative noise masking approach relevant to the smart meter data. We propose a novel ‘Twin Uniform’ noise distribution and derive relevant theoretical ...


Using Cost-Sensitive Learning And Feature Selection Algorithms To Improve The Performance Of Imbalanced Classification, Fang Feng, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Xuhui Yang Jan 2020

Using Cost-Sensitive Learning And Feature Selection Algorithms To Improve The Performance Of Imbalanced Classification, Fang Feng, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Xuhui Yang

Faculty of Engineering and Information Sciences - Papers: Part A

Imbalanced data problem is widely present in network intrusion detection, spam filtering, biomedical engineering, finance, science, being a challenge in many real-life data-intensive applications. Classifier bias occurs when traditional classification algorithms are used to deal with imbalanced data. As already known, the General Vector Machine (GVM) algorithm has good generalization ability, though it does not work well for the imbalanced classification. Additionally, the state-of-the-art Binary Ant Lion Optimizer (BALO) algorithm has high exploitability and fast convergence rate. Based on these facts, we have proposed in this paper a Cost-sensitive Feature selection General Vector Machine (CFGVM) algorithm based on GVM and ...


Seismic Performance Of Concrete-Filled Shs Column-To-Beam Connections With Slip-Critical Blind Bolts, Weifeng Jiao, Wei Wang, Yiyi Chen, Lip H. Teh Jan 2020

Seismic Performance Of Concrete-Filled Shs Column-To-Beam Connections With Slip-Critical Blind Bolts, Weifeng Jiao, Wei Wang, Yiyi Chen, Lip H. Teh

Faculty of Engineering and Information Sciences - Papers: Part A

© 2020 Elsevier Ltd This paper investigates the use of slip-critical blind bolts to connect I-beams to concrete-filled steel square hollow section (SHS) columns. The strength and stiffness of the resulting joints are determined experimentally for the purpose of classifying them according to the Eurocode. Their suitability for use in special moment frames is also assessed through cyclic bending tests. Three types of beam sections are tested, being a compact welded section, a reduced beam (flange) section, and a reduced beam section with concrete slab at the top. All tested joints are full strength according to the Eurocode, allowing the connected ...


Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin Jan 2020

Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin

Faculty of Engineering and Information Sciences - Papers: Part A

As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains ...


Autonomous Control Strategy For Microgrid Operating Modes Smooth Transition, Yaran Li, Long Fu, Ke Meng, Zhao Dong, Kashem M. Muttaqi, Wenli Du Jan 2020

Autonomous Control Strategy For Microgrid Operating Modes Smooth Transition, Yaran Li, Long Fu, Ke Meng, Zhao Dong, Kashem M. Muttaqi, Wenli Du

Faculty of Engineering and Information Sciences - Papers: Part A

© 2013 IEEE. Microgrid transition between standalone and grid-connected modes is a promising alternative to provide the grid with increasing flexibility and availability. However, transition smoothness relies heavily on control topologies and corresponding parameters, which thus remains challengeable. Existing microgrid transition strategies have two major deficiencies: 1) Inverter control mode alters subjected to microgrid operating mode, for instance, the inverter in current control will switch to voltage control when microgrid disconnects to the utility grid; 2) Controller parameters are selected based on practice and experience, where a systematic and efficient approach does not exist. Motivated by these limitations, in this paper ...


Reachable Set Estimation For Neutral Markovian Jump Systems With Mode-Dependent Time-Varying Delays, Xiangli Jiang, Guihua Xia, Zhiguang Feng, Zhengyi Jiang Jan 2020

Reachable Set Estimation For Neutral Markovian Jump Systems With Mode-Dependent Time-Varying Delays, Xiangli Jiang, Guihua Xia, Zhiguang Feng, Zhengyi Jiang

Faculty of Engineering and Information Sciences - Papers: Part A

© 2020 John Wiley & Sons Ltd This study, under zero initial condition, aims to characterize the reachable set bound for a class of neutral Markovian jump systems (NMJSs) with interval time-varying delays and bounded disturbances. To begin with, the time-delays are considered to be mode-dependent while delay mode and system mode are different. By utilizing free-weighting matrix method and reciprocally convex combination technique, an ellipsoid-like bound is characterized for the concerned NMJS with completely known transition probabilities. Based on the provided analytical framework, the case of same delay mode and system mode is also handled. Then, benefitting from a group of ...


A 3d Printed Modular Soft Gripper For Conformal Grasping, Charbel Tawk, Rahim Mutlu, Gursel Alici Jan 2020

A 3d Printed Modular Soft Gripper For Conformal Grasping, Charbel Tawk, Rahim Mutlu, Gursel Alici

Faculty of Engineering and Information Sciences - Papers: Part A

© 2020 IEEE. In this work, a 3D printed modular soft gripper with highly conformal soft fingers was developed. A soft auxetic structure with compliant ribs is 3D printed simultaneously with each soft pneumatic finger for conformal grasping. The fingers of the soft gripper were printed monolithically, without requiring support material and postprocessing, using a low-cost and open-source fused deposition modeling (FDM) 3D printer that employs a commercially available thermoplastic polyurethane (TPU). The soft fingers of the gripper were optimized using finite element modeling (FEM). The FE simulations accurately predicted the performance of the fingers in terms of deformation and blocked ...


Pressure-Drop Modelling In The Softening And Melting Test For Ferrous Burden, Subhasish Mitra, Xinliang Liu, Tom Honeyands, Geoffrey Evans, Damien O'Dea, Paul Zulli Jan 2020

Pressure-Drop Modelling In The Softening And Melting Test For Ferrous Burden, Subhasish Mitra, Xinliang Liu, Tom Honeyands, Geoffrey Evans, Damien O'Dea, Paul Zulli

Faculty of Engineering and Information Sciences - Papers: Part A

© 2020 ISIJ The softening and melting (SM) under load test is routinely conducted to assess the quality of ferrous burden materials and to predict their possible performance in blast furnace. Due to complex phase interactions coupled with chemical reactions at an elevated temperature range (~973 to 1 873 K), the flow dynamics in the test system are quite complex. This study systematically investigates the contraction behaviour and associated pressure drop in a SM test bed for sinter, lump (NBLL, Newman Blend Lump) and a mixture of these two types of ore (21 wt% NBLL + 79 wt% sinter). To quantify the ...


Recent Advancements In G-C3n4-Based Photocatalysts For Photocatalytic Co2reduction: A Mini Review, Runlu Liu, Zhixin Chen, Yao Yao, Yao Li, Waqas A. Cheema, Dawei Wang, Shenmin Zhu Jan 2020

Recent Advancements In G-C3n4-Based Photocatalysts For Photocatalytic Co2reduction: A Mini Review, Runlu Liu, Zhixin Chen, Yao Yao, Yao Li, Waqas A. Cheema, Dawei Wang, Shenmin Zhu

Faculty of Engineering and Information Sciences - Papers: Part A

© 2020 The Royal Society of Chemistry. Carbon dioxide (CO2) is a very important micro-molecular resource. Using CO2 captured from the atmosphere for high-output synthesis of chemicals as raw materials has great significance and potential for various industrial applications. Since the industrial revolution in the 18th century, manmade CO2 emission has increased by 45%, which negatively impacts the planetary climate by the so-called greenhouse effect. Therefore, high-efficiency photocatalysis and photocatalysts for CO2 conversion have become the most important challenges and milestones throughout the world. In consideration of this, various catalysts have been explored. Among these, graphitic carbon nitride (g-C3N4) as a ...


Towards Mr-Guided Electron Therapy: Measurement And Simulation Of Clinical Electron Beams In Magnetic Fields, R Kueng, Bradley M. Oborn, N Roberts, Trent Causer, M Stampanoni, P Manser, P Keall, M Fix Jan 2020

Towards Mr-Guided Electron Therapy: Measurement And Simulation Of Clinical Electron Beams In Magnetic Fields, R Kueng, Bradley M. Oborn, N Roberts, Trent Causer, M Stampanoni, P Manser, P Keall, M Fix

Faculty of Engineering and Information Sciences - Papers: Part A

© 2020 Associazione Italiana di Fisica Medica Purpose: In the current era of MRI-linac radiotherapy, dose optimization with arbitrary dose distributions is a reality. For the first time, we present new and targeted experiments and modeling to aid in evaluating the potential dose improvements offered with an electron beam mode during MRI-linac radiotherapy. Methods: Small collimated (1 cm diameter and 1.5 × 1.5 cm2 square) electron beams (6, 12 and 20 MeV) from a clinical linear accelerator (Varian Clinac 2100C) are incident perpendicular and parallel to the strong and localized magnetic fields (0–0.7 T) generated by a permanent ...


A Blind Ring Signature Based On The Short Integer Solution Problem, Quoc Huy Le, Dung Hoang Duong, Willy Susilo Jan 2020

A Blind Ring Signature Based On The Short Integer Solution Problem, Quoc Huy Le, Dung Hoang Duong, Willy Susilo

Faculty of Engineering and Information Sciences - Papers: Part B

2020, Springer Nature Switzerland AG. A blind ring signature scheme is a combination of a ring signature and a blind signature, which allows not only any member of a group of signers to sign on a message on behalf of the group without revealing its identity but also the user who possesses the message to blind it before sending to the group to be signed. Blind ring signature schemes are essential components in e-commercial, e-voting etc. In this paper, we propose the first blind ring signature scheme based on lattices. More precisely, our proposed scheme is proven to be secure ...


Interfacial Characteristics And Mechanical Properties Of Duplex Stainless Steel Bimetal Composite By Heat Treatment, Zhou Li, Jingwei Zhao, Fanghui Jia, Xiaojun Liang, Qingfeng Zhang, Xiangqian Yuan, Sihai Jiao, Zhengyi Jiang Jan 2020

Interfacial Characteristics And Mechanical Properties Of Duplex Stainless Steel Bimetal Composite By Heat Treatment, Zhou Li, Jingwei Zhao, Fanghui Jia, Xiaojun Liang, Qingfeng Zhang, Xiangqian Yuan, Sihai Jiao, Zhengyi Jiang

Faculty of Engineering and Information Sciences - Papers: Part B

© 2020 Elsevier B.V. The interfacial morphologies play a crucial role in mechanical properties of laminated/bimetal composite. This study investigates the effects of heat treatments on the interfacial characteristics, mechanical properties and fracture behaviour of a 2205 duplex stainless steel/AH36 carbon steel bimetal composite with varying interface situations fabricated by the hot-rolling and subsequent heat treatments. The bimetal composite was annealed from 850 °C to 1150 °C in steps of 100 °C with soaking 1 h. Heterogeneities of grain size and element concentration exist in the microstructural evolution of bonding zone adjacent to interface after annealing treatments, which ...


Conditions For The Existence, Identification And Calculus Rules Of The Threshold Of Prox-Boundedness, Chayne Planiden Jan 2020

Conditions For The Existence, Identification And Calculus Rules Of The Threshold Of Prox-Boundedness, Chayne Planiden

Faculty of Engineering and Information Sciences - Papers: Part B

2020, Springer-Verlag GmbH Germany, part of Springer Nature. This note advances knowledge of the threshold of prox-boundedness of a function; an important concern in the use of proximal point optimization algorithms and in determining the existence of the Moreau envelope of the function. In finite dimensions, we study general prox-bounded functions and then focus on some useful classes such as piecewise functions and Lipschitz continuous functions. The thresholds are explicitly determined when possible and bounds are established otherwise. Some calculus rules are constructed; we consider functions with known thresholds and find the thresholds of their sum and composition.


Systematic Evaluation Of Machine-Learning Methods For Identifying Human-Pathogen Protein-Protein Interactions, Huaming Chen, Fuyi Li, Lei Wang, Yaochu Jin, Chi-Hung Chi, Lukasz Kurgan, Jiangning Song, Jun Shen Jan 2020

Systematic Evaluation Of Machine-Learning Methods For Identifying Human-Pathogen Protein-Protein Interactions, Huaming Chen, Fuyi Li, Lei Wang, Yaochu Jin, Chi-Hung Chi, Lukasz Kurgan, Jiangning Song, Jun Shen

Faculty of Engineering and Information Sciences - Papers: Part B

In recent years, high-throughput experimental techniques have significantly enhanced the accuracy and coverage of protein–protein interaction identification, including human–pathogen protein–protein interactions (HP-PPIs). Despite this progress, experimental methods are, in general, expensive in terms of both time and labour costs, especially considering that there are enormous amounts of potential protein-interacting partners. Developing computational methods to predict interactions between human and bacteria pathogen has thus become critical and meaningful, in both facilitating the detection of interactions and mining incomplete interaction maps. In this paper, we present a systematic evaluation of machine learning-based computational methods for human–bacterium protein–protein ...


Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun Jan 2020

Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun

Faculty of Engineering and Information Sciences - Papers: Part B

Micro learning aims to assist users in making good use of smaller chunks of spare time and provides an effective online learning service. However, to provide such personalized online services on the Web, a number of information overload challenges persist. Effectively and precisely mining and extracting valuable information from massive and redundant information is a significant preprocessing procedure for personalizing online services. In this study, we propose a deep sequence labelling model for locating, extracting, and classifying key information for micro learning services. The proposed model is general and combines the advantages of different types of classical neural network. Early ...