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Machine Learning-Driven Prediction of Optical and Physical Properties in Lanthanum and Gold-Doped Zinc Borotellurite Glasses for Optoelectronic Applications

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Ceramics International 2025年

作者： S.N. Nazrin Camellia Doroody Liyana Adilla Burhanuddin Neesha Jothi N. Ibrahim Halimah Badioze Zaman M.H.M. Tahir Manzoore Elahi M. Soudagar S. Ramesh Sagar Shelare Shubham Sharma Institute of Informatics and Computing in Energy (IICE) College of Engineering Universiti Tenaga Nasional 43000 Kajang Selangor Malaysia Institute of Sustainable Energy (ISE) Universiti Tenaga Nasional (UNITEN @ The Energy University) Putrajaya Campus Jalan IKRAM-UNITEN 43000 Kajang Selangor Malaysia Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura-140401 Punjab India Zhejiang Xingyu Mechanical and Electrical Technology Company Ltd. Tongqin Wuyi County Jinhua Zhejiang 311400 China Department of Electronic Systems Engineering (ESE) Malaysia–Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia Department of Computing College of Computing and Informatics Universiti Tenaga Nasional (UNITEN) Malaysia Dept. of Digital Economy Technology Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman 31900 Kampar Perak Department of English Language and Literature Faculty of Languages and Communication Universiti Pendidikan Sultan Idris 35900 Tanjong Malim Perak Malaysia Center of Advanced Manufacturing and Materials Processing (AMMP) Faculty of Engineering University of Malaya Kuala Lumpur Chitkara Centre for Research and Development Chitkara University Himachal Pradesh 174103 India Division of Research and Development Lovely Professional University Phagwara Punjab 144411 India Department of Applied Chemistry Priyadarshini College of Engineering Nagpur Maharashtra 440019 India University Centre for Research and Development Chandigarh University Mohali Punjab 140413 India Department of Technical Sciences Western Caspian University Baku Azerbaijan Jadara University Research Center Jadara University Jordan

Recent advancements in glass science have focused on optimizing optical and structural properties through the incorporation of rare oxide nanoparticles, such as lanthanum and gold oxide, to enhance transparency, refractive index, and band gap energy for photonic applications. Additionally, the integration of machine learning techniques in material design accelerates the prediction and optimization of these properties, enabling more efficient discovery and development of advanced glass systems for optoelectronic and photonic devices. The melt-quenching technique was employed to fabricate zinc borotellurite glasses doped with lanthanum oxide and gold oxide. The glass's amorphous nature was confirmed through structural analysis, which detected absorption bands corresponding to TeO 3 , BO 4 , and BO 3 units. A drop in molar volume with an increase in gold oxide quantity prompted a suggestion for structural reorganisation. Optical investigations indicated an increase in the optical band gap energy and a blue shift in the absorption edge. Four machine learning models—Random Forest, Gradient Boosting, XGBoost, and Artificial Neural Networks—were employed to forecast critical optical and physical parameters, such as refractive index, density, molar volume, optical band gap, and Urbach energy, to expedite the discovery process. This data-driven approach illustrates the transformative capabilities of machine learning in materials science, facilitating the swift modification of glass compositions to enhance optical performance for photonic and optoelectronic applications. The enhanced optical properties of the synthesized glass system make it a promising candidate for photonic and optoelectronic applications, including optical fibers, solid-state lasers, and planar waveguides , where its tunable refractive index and improved transparency can optimize signal transmission and device efficiency. Additionally, the presence of gold oxide nanoparticles suggests potential use in nonl

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Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings

arXiv

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arXiv 2022年

作者： Bano, Sophia Casella, Alessandro Vasconcelos, Francisco Qayyum, Abdul Benzinou, Abdesslam Mazher, Moona Meriaudeau, Fabrice Lena, Chiara Cintorrino, Ilaria Anita De Paolis, Gaia Romana Biagioli, Jessica Grechishnikova, Daria Jiao, Jing Bai, Bizhe Qiao, Yanyan Bhattarai, Binod Gaire, Rebati Raman Subedi, Ronast Vazquez, Eduard Plotka, Szymon Lisowska, Aneta Sitek, Arkadiusz Attilakos, George Wimalasundera, Ruwan David, Anna L. Paladini, Dario Deprest, Jan De Momi, Elena Mattos, Leonardo S. Moccia, Sara Stoyanov, Danail Department of Computer Science University College London United Kingdom Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Italy The BioRobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna Italy Fetal Medicine Unit Elizabeth Garrett Anderson Wing University College London Hospital United Kingdom EGA Institute for Women's Health Faculty of Population Health Sciences University College London United Kingdom Department of Development and Regeneration University Hospital Leuven Belgium Department of Fetal and Perinatal Medicine Istituto Giannina Gaslini Italy ENIB UMR CNRS 6285 LabSTICC 29238 France Department of Computer Engineering and Mathematics University Rovira i Virgili Spain ImViA Laboratory University of Bourgogne Franche-Comté France Physics Department Lomonosov Moscow State University Russia Fudan University China Medical Computer Vision and Robotics Group Department of Mathematical and Computational Sciences University of Toronto Canada Co. Ltd China NepAL Applied Mathematics and Informatics Institute for Research Nepal Redev Technology United Kingdom Sano Center for Computational Medicine Poland Quantitative Healthcare Analysis Group Informatics Institute University of Amsterdam Amsterdam Netherlands Center for Advanced Medical Computing and Simulation Massachusetts General Hospital Harvard Medical School BostonMA United States

Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomoses to restore a physiological blood exchange among twins. The procedure is particularly challenging, from the surgeon's side, due to the limited field of view, poor manoeuvrability of the fetoscope, poor visibility due to amniotic fluid turbidity, and variability in illumination. These challenges may lead to increased surgery time and incomplete ablation of pathological anastomoses, resulting in persistent TTTS. Computer-assisted intervention (CAI) can provide TTTS surgeons with decision support and context awareness by identifying key structures in the scene and expanding the fetoscopic field of view through video mosaicking. Research in this domain has been hampered by the lack of high-quality data to design, develop and test CAI algorithms. Through the Fetoscopic Placental Vessel Segmentation and Registration (FetReg2021) challenge, which was organized as part of the MICCAI2021 Endoscopic Vision (EndoVis) challenge, we released the first large-scale multi-center TTTS dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms with a focus on creating drift-free mosaics from long duration fetoscopy videos. For this challenge, we released a dataset of 2060 images, pixel-annotated for vessels, tool, fetus and background classes, from 18 in-vivo TTTS fetoscopy procedures and 18 short video clips of an average length of 411 frames for developing placental scene segmentation and frame registration for mosaicking techniques. Seven teams participated in this challenge and their model performance was assessed on an unseen test dataset of 658 pixel-annotated images from 6 fetoscopic procedures and 6 short clips. The challenge provided an opportunity for creating generalized solutions for fetoscopic scene understanding and mosaicking. In this paper,

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Corrigendum to “Hybridizing flower pollination algorithm with particle swarm optimization for enhancing the performance of IPv6 intrusion detection system” [Alex. Eng. J. 104 (2024) 504–514]

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Alexandria Engineering Journal 2025年 110卷 376-376页

作者： Adnan Hasan Bdair AIghuraibawi Selvakumar Manickam Zaid Abdi Alkareem Alyasseri Rosni Abdullah Ayman Khallel Riyadh Rahef Nuiaa Al Ogaili Fahd N. Al-Wesabi Abdulsamad Ebrahim Yahya National Advanced IPv6 Centre (NAv6) Universiti Sains Malaysia Penang 11800 Malaysia Baghdad College of Economic Sciences University Baghdad Iraq Information Technology Research and Development Center University of Kufa Najaf Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq School of Computer Sciences Universiti Sains Malays Penang 11800 Malaysia Faculty of Computing and Informatics Universiti Malaysia Sabah Sabah Malaysia Department of Cybersecurity Engineering Technology Al Hikma University College Baghdad Iraq Department of Computer Science/ College of Computer Science and Information Technology Wasit University Kut Wasit 52001 Iraq Department of Computer Science College of Science & Art at Mahayil King Khalid University Saudi Arabia Department of Information Technology College of Computing and Information Technology Northern Border University Arar Saudi Arabia

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Coherent H ∞ control for Markovian jump linear quantum systems

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IFAC-PapersOnLine 2020年第2期53卷 269-274页

作者： Yanan Liu Daoyi Dong Ian R. Petersen Qing Gao Steven X. Ding Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen. 47057 Duisburg Germany Research School of Electrical Energy and Materials Engineering The Australian National University Canberra ACT 2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing and also with Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China

The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H ∞ control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H ∞ controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).

关键词： Coherent quantum feedback H∞ control fault-tolerant control Markovian jump linear quantum systems

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A threshold effect of coupling delays on intra-layer synchronization in duplex networks

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Science China(Technological Sciences) 2018年第12期61卷 1907-1914页

作者： TANG LongKun LU JunAn Lü JinHu Fujian Province University Key Laboratory of Computation Science School of Mathematical Sciences Huaqiao University Department of Mathematics & Statistics Georgia State University School of Mathematics and Statistics Wuhan University School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

This paper investigates the impact of inter-layer coupling functions and intra-layer coupling delays on intra-layer synchronization regions and sychronizability. It is found that the inter-layer coupling functions have great influence on intra-layer synchronization regions, as well as on the intra-layer synchronizability. In particular, there exists an inter-layer coupling function such that the inter-layer coupling strength neither improves nor weakens the intra-layer synchronizability. Furthermore, no matter which one of three inter-layer coupling functions is chosen, a small intra-layer delay always keeps the intra-layer synchronized regions almost unchanged, implying that the small delay neither enhances nor suppresses the intra-layer synchronizability. At the same time the delay greatly frustrates the synchronizability in each layer when it is greater than some threshold. Our results may have potential applications for interconnected technological networks where communication delays are inevitably present.

关键词： multiplex network master stability function intra-layer synchronization synchronized region time delay

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A Theoretical Review: Risk Mitigation Through Trusted Human Framework for Insider Threats

A Theoretical Review: Risk Mitigation Through Trusted Human ...

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International Conference on Cybersecurity (ICoCSec)

作者： Mohd Nazer Apau Muliati Sedek Rabiah Ahmad Faculty of Information and Communication Technology Information Security and Network Research Group Center for Advanced Computing Technology Department of Computer Science Department of Language and Human Development Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka MALAYSIA

This paper discusses the possible effort to mitigate insider threats risk and aim to inspire organizations to consider identifying insider threats as one of the risks in the company's enterprise risk management activities. The paper suggests Trusted Human Framework (THF) as the on-going and cyclic process to detect and deter potential employees who bound to become the fraudster or perpetrator violating the access and trust given. The mitigation's control statements were derived from the recommended practices in the “Common Sense Guide to Mitigating Insider Threats” produced by the Software Engineering Institute, Carnegie Mellon University (SEI-CMU). The statements validated via a survey which was responded by fifty respondents who work in Malaysia.

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Residue-to-Binary converters for the seven moduli set {2n-5-1, 2n-3-1, 2n-2+1, 2n-1-1, 2n-1+1, 2n, 2n+1} for n even

Residue-to-Binary converters for the seven moduli set {2n-5-...

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Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia)

作者： M.V.N. Madhavi Latha Rashmi Ramesh Rachh P. V. Ananda Mohan GITAM School of Technology Rudraram Patancheru Mandal Hyderabad Medak Dist. Telangana Center for P.G. Studies JnanaSangama Visvesvaraya Technological University Belagavi India Centre for Development of Advanced Computing Bengaluru India

The following topics are dealt with: integrated circuit design; CMOS integrated circuits; operational amplifiers; residue number systems; set theory; digital-analogue conversion; analogue-digital conversion; data acqu...

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Targeting druggable proteins hisB, aroC, and trpD in the co-diphtheria infection caused by Corynebacterium ulcerans with Traditional Chinese Medicine

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Heliyon 2025年

作者： Sania Kanwal Ayesha Wisal Saman Sohail Paulo VS. Daltron Muhammad Shafique Muhammad Imran Ihosvany Camps Syed S. Hassan Department of Chemistry Islamia College Peshawar Peshawar-KP Pakistan 25000 Centre for Technological Development in Health (CDTS) Fiocruz Rio de Janeiro RJ 21040-361 Brazil Department of Pharmaceutical Sciences College of Pharmacy Shaqra University Shaqra Saudi Arabia Research Center for Advanced Materials Science (RCAMS) Department of Chemistry Faculty of Science King Khalid University Abha Aseer 61413 P.O. Box 9004 Saudi Arabia High Performance & Quantum Computing Labs Waterloo Canada Laboratório de Modelagem Computacional—LaModel Instituto de Ciências Exatas—ICEx. Universidade Federal de Alfenas—UNIFAL-MG Alfenas Minas Gerais Brazil JRC Genome Research International Center for Chemical and Biological Sciences (PCMD-ICCBS) University of Karachi Pakistan 75270

Corynebacterium ulcerans is a rod-shaped emerging zoonotic pathogen responsible for diphtheria-like infections in humans, posing a significant health threat to public due to its toxigenic potential and ability to affect multiple hosts. This study employed a subtractive genomics / proteomics approach to identify novel therapeutic targets. A total of 900 conserved non-host homologous proteins were identified across 20 C. ulcerans strains, of which 49 essential proteins were shortlisted based on their essential role in bacterial survival. Among these, hisB , aroC , and trpD were prioritized as potential drug targets due to their gene essentiality, PPI, critical roles in metabolic pathways, virulence, cellular localization, and druggability. These targets were subjected to molecular docking studies against a Traditional Chinese Medicine (TCM) compound library of 36,043 molecules. Lead compounds displayed strong binding affinities and favorable interactions with the active sites of the target proteins. Molecular dynamics simulations validated the stability of the protein-ligand complexes over 200 ns, further confirming the favorable interaction of the therapeutic targets. Functional pathways analysis highlighted the essential role in histidine, aromatic amino acid, and tryptophan biosynthesis, critical for bacterial viability. These findings provide valuable insights into the design of novel antimicrobial agents targeting C. ulcerans and pave the way for experimental validation of the identified drug candidates.

关键词： Corynebacterium ulcerans Diphtheria co-infection Subtractive proteomics Drug Discovery MD simulations

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Workability, compressive strength, and efflorescence characteristics of one-part mix alkali-activated circulating fluidised bed combustion fly ash-based mortars

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CEMENT 2024年 18卷

作者： Jason Shun Fui Pei Chung Siung Choo Deni Shidqi Khaerudini Sing Muk Ng Dominic Ek Leong Ong Melvina Tan Jaka Sunarso Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga 93350 Kuching Sarawak Malaysia Research Centre for Sustainable Technologies Swinburne University of Technology Jalan Simpang Tiga 93350 Kuching Sarawak Malaysia Research Centre for Innovative Society Swinburne University of Technology Jalan Simpang Tiga 93350 Kuching Sarawak Malaysia Research Center for Advanced Materials National Research and Innovation Agency Bld. 440 Kawasan Puspiptek Serpong Indonesia Research and Development Department Sarawak Energy Berhad No. 1 The Isthmus 93050 Kuching Sarawak Malaysia School of Engineering and Built Environment Griffith University Nathan Queensland 4111 Australia

In this study, one-part alkali-activated mortars are formulated using circulating fluidised bed combustion (CFBC) fly ash, derived from lignite (brown coal) combustion, as the precursor, and sodium hydroxide (NaOH) and sodium metasilicate (Na 2 SiO 3 ) as the solid activators. Experimental findings indicate that an increase in solid activator-to-precursor ratio correlates with improved workability and compressive strength of the mortars. The influence of Na 2 SiO 3 -to-NaOH ratio on the compressive strength of the mortars is apparent only in mixes with a high solid activator-to-precursor ratio of 0.4 and 0.5, indicating its relatively lesser significance compared to the solid activator-to-precursor ratio. The mechanism through which an increase in the solid activator-to-precursor ratio improves the compressive strength of the mortars is elucidated using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The results indicate that increasing the solid activator-to-precursor ratio enhances the degree of alkali-activation for fly ash, thereby improving the compressive strength with increasing solid activator-to-precursor ratio.

关键词： Alkali-activated Just-add water One-part Solid activator Dry powder

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An integrated cyberGIS and machine learning framework for fine-scale prediction of Urban Heat Island using satellite remote sensing and urban sensor network data

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Urban informatics 2022年第1期1卷 6页

作者： Fangzheng Lyu Shaohua Wang Su Yeon Han Charlie Catlett Shaowen Wang cyberGIS Center for Advanced Digital and Spatial Studies University of Illinois at Urbana-Champaign Urbana IL USA. Department of Geography and Geographic Information Science University of Illinois at Urbana-Champaign Urbana IL USA. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. Computing Environment and Life Sciences Argonne National Laboratory Chicago IL USA.

Due to climate change and rapid urbanization, Urban Heat Island (UHI), featuring significantly higher temperature in metropolitan areas than surrounding areas, has caused negative impacts on urban communities. Temporal granularity is often limited in UHI studies based on satellite remote sensing data that typically has multi-day frequency coverage of a particular urban area. This low temporal frequency has restricted the development of models for predicting UHI. To resolve this limitation, this study has developed a cyber-based geographic information science and systems (cyberGIS) framework encompassing multiple machine learning models for predicting UHI with high-frequency urban sensor network data combined with remote sensing data focused on Chicago, Illinois, from 2018 to 2020. Enabled by rapid advances in urban sensor network technologies and high-performance computing, this framework is designed to predict UHI in Chicago with fine spatiotemporal granularity based on environmental data collected with the Array of Things (AoT) urban sensor network and Landsat-8 remote sensing imagery. Our computational experiments revealed that a random forest regression (RFR) model outperforms other models with the prediction accuracy of 0.45 degree Celsius in 2020 and 0.8 degree Celsius in 2018 and 2019 with mean absolute error as the evaluation metric. Humidity, distance to geographic center, and PM concentration are identified as important factors contributing to the model performance. Furthermore, we estimate UHI in Chicago with 10-min temporal frequency and 1-km spatial resolution on the hottest day in 2018. It is demonstrated that the RFR model can accurately predict UHI at fine spatiotemporal scales with high-frequency urban sensor network data integrated with satellite remote sensing data.

关键词： Machine learning Remote sensing Urban Heat Island Urban sensor network cyberGIS

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