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Dual-Objective Mixed Integer Linear program and Memetic Algorithm for an Industrial Group Scheduling Problem

IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1199-1209页

作者： Ziyan Zhao Shixin Liu MengChu Zhou abdullah Abusorrah State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering Northeastern UniversityShenyang 110819China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah 21481Saudi Arabia Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

Group scheduling problems have attracted much attention owing to their many practical *** work proposes a new bi-objective serial-batch group scheduling problem considering the constraints of sequence-dependent setup time,release time,and due *** is originated from an important industrial process,i.e.,wire rod and bar rolling process in steel production *** objective functions,i.e.,the number of late jobs and total setup time,are minimized.A mixed integer linear program is established to describe the *** obtain its Pareto solutions,we present a memetic algorithm that integrates a population-based nondominated sorting genetic algorithm II and two single-solution-based improvement methods,i.e.,an insertion-based local search and an iterated greedy *** computational results on extensive industrial data with the scale of a one-week schedule show that the proposed algorithm has great performance in solving the concerned problem and outperforms its *** high accuracy and efficiency imply its great potential to be applied to solve industrial-size group scheduling problems.

关键词： Insertion-based local search iterated greedy algorithm machine learning memetic algorithm nondominated sorting genetic algorithm II(NSGA-II) production scheduling

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Enhanced Fault Detection in Industrial Process via a Hellinger Distance-Based Data-Driven Scheme

Enhanced Fault Detection in Industrial Process via a Helling...

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Modeling, Simulation & Intelligent Computing (MoSICom), International Conference on

作者： Mohammed Affan K. Ramakrishna Kini Muddu Madakyaru Fouzi Harrou Mukund Kumar Menon Ying Sun Department of Chemical Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

Accurate fault detection in modern chemical processes ensures safety and efficiency. However, detecting faults in noisy environments remains a significant challenge. This paper introduces an effective fault detection (FD) strategy that combines a supervised learning approach using partial least squares (PLS) with fault detection charts based on Hellinger distance (HD) and exponentially weighted moving average (EWMA). The PLS-HD-EWMA strategy utilizes PLS to generate residuals, while HD is employed to compute the divergence between actual residuals and fault-free residuals. EWMA is then applied to evaluate the HD, providing sensitivity to small changes for effective fault detection. The proposed strategy’s efficacy is demonstrated through simulations on a benchmark continuous stirred tank reactor process, evaluating three common fault scenarios. The monitoring performance indicates that the PLS-HD-EWMA approach outperforms all the other conventional methods, offering superior fault detection capabilities.

关键词： Training Sensitivity Fault detection Computational modeling Supervised learning Noise Safety Noise measurement Continuous-stirred tank reactor Monitoring

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Enabling Integrated Sensing and Communication using In-Band Full-Duplex Systems

Enabling Integrated Sensing and Communication using In-Band ...

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Asilomar Conference on Signals, Systems & computers

作者： Hao-Lun Weng Yung-Chih Chih Chung-An Shen Mohammed E. Fouda Ahmed Eltawil Electronic and Computer Engineering Dept. National Taiwan University of Science and Technology Taipei Taiwan Rain Neuromorphics Inc. USA King Abdullah University of Science and Technology Thuwal Saudi Arabia

Recently, in-band full-duplex (IBFD) integrated sensing and communication (ISAC) system has drawn much attention for applications such as 6G and vehicle-to-everything communications. In this system, due to the simultaneous reception and transmission, self-interference signals result in a significant impact on the performance and the feasibility of applications. This paper presents a two-stage scheme to recover the returned radar signal in the IBFD-ISAC systems. The self-interference cancellation (SIC) scheme based on the independent component analysis (ICA) algorithm is applied as the first stage. Furthermore, a delay-detecting scheme is employed to extract the returned radar signal. The simulation results verify that the proposed framework can successfully recover the returned radar signal in IBFD-ISAC systems.

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Treatment with metal–organic frameworks (MOFs) elicits secondary metabolite accumulation in Aquilaria crassna (agarwood) callus culture

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Discover Plants 2025年第1期2卷 1-9页

作者： Overmans, Sebastian Alflayyeh, Yazan Gutiérrez, Sergio Aldlaigan, Yousef Lauersen, Kyle J. Bioengineering Program Biological and Environmental Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Jeddah Kingdom of Saudi Arabia Plant Tissue Culture & Biotechnology Center Ministry of Environment Water and Agriculture of Saudi Arabia (MEWA) Riyadh Kingdom of Saudi Arabia

Thymelaceaous trees are prized for accumulating fragrant resins composed of hundreds of secondary metabolites in their woody tissues. Slow growth and increasing consumer demand have stretched natural sources of agarwood trees to being endangered and alternative production modes, including silviculture and tissue culture, are currently being investigated. Dedifferentiated tissue culture of agarwood trees provides a means of cell propagation independent of environmental context. However, secondary metabolite accumulation, as found in fragrant resins, occurs largely in response to wounding. Here, we investigated the application of metal-organic frameworks (MOFs) as potential elicitors of secondary metabolite formation in Aquilaria crassna tissue culture. Callus cultures were exposed to five commercially available MOFs (UiO-67, MOF-808, HKUST-1, ZIF-67, and MOF-74) and ethanol extracts were analysed using GC-MS to quantify secondary metabolite accumulation in MOF-exposed cultures compared to untreated cultures. Samples that were exposed to either of the two Zr-based MOFs exhibited metabolite production profiles that were similar to each other, (trans-2-Carboxy-cyclo-hexyl)-acetic acid was reduced in the presence of all MOFs, the Cu-containing HKUST-1 MOF increased palmitic acid levels, and ZIF-67 (at 20 mg/L) was found to elicit the highest accumulation of secondary metabolites with potential fragrance applications. These results demonstrate the possibility of eliciting secondary metabolites from dedifferentiated agarwood tree cell culture and may provide an alternative means of sourcing fragrant specialty chemicals from these plants.

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JARVIS-Leaderboard:a large scale benchmark of materials design methods

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npj Computational Materials 2024年第1期10卷 2280-2296页

作者： Kamal Choudhary Daniel Wines Kangming Li Kevin F.Garrity Vishu Gupta Aldo H.Romero Jaron T.Krogel Kayahan Saritas Addis Fuhr Panchapakesan Ganesh Paul R.C.Kent Keqiang Yan Yuchao Lin Shuiwang Ji Ben Blaiszik Patrick Reiser Pascal Friederich Ankit Agrawal Pratyush Tiwary Eric Beyerle Peter Minch Trevor David Rhone Ichiro Takeuchi Robert B.Wexler Arun Mannodi-Kanakkithodi Elif Ertekin Avanish Mishra Nithin Mathew Mitchell Wood Andrew Dale Rohskopf Jason Hattrick-Simpers Shih-Han Wang Luke E.K.Achenie Hongliang Xin Maureen Williams Adam J.Biacchi Francesca Tavazza Material Measurement Laboratory National Institute of Standards and TechnologyGaithersburgMD20899USA Department of Materials Science and Engineering University of Toronto27 King’s College CirTorontoONCanada Department of Electrical and Computer Engineering Northwestern UniversityEvanstonIL 60208USA Lewis-Sigler Institute for Integrative Genomics Princeton UniversityPrincetonNJ 08544USA Ludwig Institute for Cancer Research Princeton UniversityPrincetonNJ 08544USA Department of Physics and Astronomy West Virginia UniversityMorgantownWV 26506USA Materials Science and Technology Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Center for Nanophase Materials Science Oak Ridge National LaboratoryOak RidgeTN 37831USA Computational Sciences and Engineering Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science and Engineering Texas A&M UniversityCollege StationTX 77843USA Globus University of ChicagoChicagoIL 60637USA Data Science and Learning Division Argonne National LabLemontIL 60439USA Institute of Nanotechnology Karlsruhe Institute of TechnologyKaiserstraße 1276131 KarlsruheGermany Institute of Theoretical Informatics Karlsruhe Institute of TechnologyKaiserstraße 1276131 KarlsruheGermany Department of Chemistry and Biochemistry and Institute for Physical Science and Technology University of MarylandCollege ParkMD 20742USA Department of Physics Applied Physics and AstronomyRensselaer Polytechnic InstituteTroyNY12180USA Department of Materials Science and Engineering University of MarylandCollege ParkMD20742USA Department of Chemistry and Institute of Materials Science and Engineering Washington University in St.LouisSt.LouisMO63130USA School of Materials Engineering Purdue UniversityWest LafayetteIN47907USA Department of Mechanical Science and Engineering University of Illinois Urbana-ChampaignUrbanaIllinois 61801USA Materials Research Laboratory University of Illinois Urbana-ChampaignUrbanaIL 61801USA Theore

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many *** science,in particular,encompasses a variety of experimental and theoretical approaches that require careful *** efforts have been developed previously to mitigate these ***,a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still *** work introduces JARVIS-Leaderboard,an open-source and community-driven platform that facilitates benchmarking and enhances *** platform allows users to set up benchmarks with customtasks and enables contributions in the form of dataset,code,and meta-data *** cover the following materials design categories:Artificial Intelligence(AI),Electronic Structure(ES).

关键词： rigorous perfect enable

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Butterfly-Accelerated Solution of Coupled Volume Integral and Hydrodynamic Equations

Butterfly-Accelerated Solution of Coupled Volume Integral an...

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USNC-URSI Radio science Meeting (Joint with AP-S Symposium)

作者： Doolos Aibek Uulu Yang Liu Abdulkadir C. Yucel Hakan Bagci Department of Mathematics and Natural Sciences University of Central Asia (UCA) Naryn Kyrgyzstan Applied Mathematics & Computational Research Division Lawrence Berkeley National Laboratory Berkeley USA School of Electrical and Electronic Engineering Nanyang Technological University (NTU) Singapore Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

ISBN: (数字)9789463968119

ISBN: (纸本)9798350359497

In recent years, advancements in plasmonic devices have enabled the localization of electromagnetic fields at subwavelength scales, contributing to breakthroughs in various scientific and engineering fields (J. C. Ndukaife, et al., ACS Nano, 2014,8,9,9035-9043). These structures are often made of metals and their electric properties are typically represented by the classical Drude model (S. A. Maier, 2007, Springer, New York). As the size of the plasmonic structures approaches the nanoscale, the classical Drude model falls short in explaining the collective movement of free electrons in metals. The interaction between moving charges and the electromagnetic fields can be described by a coupled system of the Maxwell and hydrodynamic equations (X. Zheng, et al., IEEE Trans. Antennas Propag., 2018,66,9, 4759-4771).

关键词： Location awareness Conferences Integral equations Metals Plasmons Hydrodynamics Mathematical models

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Wide-field-of-view Perovskite Quantum-dots Fibers Array for Easing Pointing, Acquisition and Tracking in Underwater Wireless Optical Communication

Wide-field-of-view Perovskite Quantum-dots Fibers Array for ...

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Optical Fiber Communication (OFC) Conference

作者： Chun Hong Kang Omar Alkhazragi Lutfan Sinatra Sultan Alshaibani Yue Wang Kuang-Hui Li Meiwei Kong Marat Lutfullin Osman M. Bakr Tien Khee Ng Boon S. Ooi Division of Computer Electrical and Mathematical Sciences and Engineering Photonics Laboratory King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Quantum Solutions Southampton United Kingdom Division of Physical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

We demonstrated, for the first time, perovskite quantum-dots optical fibers array successfully eases the pointing, acquisition and tracking requirement facing visible-laser-based underwater wireless optical communicat... 详细信息

ISBN: (纸本)9781557524669

关键词： Wireless communication Optical fibers Quantum dots Optical fiber communication Perovskites Optical receivers Optical arrays

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Differentially Private ℓ1-norm Linear Regression with Heavy-tailed Data

Differentially Private ℓ1-norm Linear Regression with Heavy...

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IEEE International Symposium on Information Theory

作者： Di Wang Jinhui Xu Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Computer Science and Engineering State University of New York at Buffalo Buffalo NY

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

We study the problem of Differentially Private Stochastic Convex Optimization (DP-SCO) with heavy-tailed data. Specifically, we focus on the ℓ 1 -norm linear regression in the ϵ-DP model. While most of the previous work focuses on the case where the loss function is Lipschitz, here we only need to assume the variates has bounded moments. Firstly, we study the case where the ℓ 2 norm of data has bounded second order moment. We propose an algorithm which is based on the exponential mechanism and show that it is possible to achieve an upper bound of $\tilde O\left( {\sqrt {\frac{d}{{n\varepsilon }}} } \right)$ (with high probability). Next, we relax the assumption to bounded θ-th order moment with some θ ∈ (1,2) and show that it is possible to achieve an upper bound of $\tilde O\left( {{{\left( {\sqrt {\frac{d}{{n\varepsilon }}} } \right)}^{\frac{{\theta - 1}}{\theta }}}} \right)$. Our algorithms can also be extended to more relaxed cases where only each coordinate of the data has bounded moments, and we can get an upper bound of $\tilde O\left( {\sqrt {\frac{d}{{n\varepsilon }}} } \right)$ and $\tilde O\left( {\frac{d}{{{{\left( {n\varepsilon } \right)}^{\frac{{\theta - 1}}{\theta }}}}}} \right)$ in the second and θ-th moment case respectively.

关键词： Upper bound Linear regression Stochastic processes Convex functions Information theory

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Identifying Novel Drug Targets by iDTPnd:A Case Study of Kinase Inhibitors

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Genomics, Proteomics & Bioinformatics 2021年第6期19卷 986-997页

作者： Hammad Naveed Corinna Reglin Thomas Schubert Xin Gao Stefan T.Arold Michael L.Maitland Toyota Technological Institute at Chicago ChicagoIL 60637USA Department of Computer Science National University of Computer and Emerging SciencesIslamabad 44000Pakistan 2bind GmbH D-93053 RegensburgGermany King Abdullah University of Science and Technology(KAUST) Computational Bioscience Research Center(CBRC)ComputerElectrical and Mathematical Sciences and Engineering(CEMSE)DivisionThuwal 23955Saudi Arabia King Abdullah University of Science and Technology(KAUST) Computational Bioscience Research Center(CBRC)Biological and Environmental Sciences and Engineering(BESE)DivisionThuwal 23955Saudi Arabia Inova Center for Personalized Health and Schar Cancer Institute Falls ChurchVA 22042USA University of Virginia Cancer Center AnnandaleVA 22003USA

Current FDA-approved kinase inhibitors cause diverse adverse effects,some of which are due to the me-chanism-independent effects of these *** these mechanism-independent interactions could improve drug safety and support drug ***,we develop iDTPnd(integrated Drug Target Predictor with negative dataset),a computational approach for large-scale discovery of novel targets for known *** a given drug,we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding *** facilitate assessment of unintended targets,iDTPnd also provides a docking-based interaction score and its statistical *** confirm the interactions of sorafenib,imatinib,dasatinib,sunitinib,and pazopanib with their known targets at a sensitivity of 52%and a specificity of 55%.We also validate 10 predicted novel targets by using in vitro *** results suggest that proteins other than kinases,such as nuclear receptors,cytochrome P450,and MHC class I molecules,can also be physiologically relevant targets of kinase *** method is general and broadly applicable for the identification of protein–small molecule interactions,when sufficient drug–target 3D data are *** code for constructing the structural signatures is available at https://***/Documents/***.

关键词： Protein-drug interaction iDTPnd Kinase inhibitor Drug-binding site signature Drug repurposing

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Is machine learning redefining the perovskite solar cells?

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Journal of Energy Chemistry 2022年第3期31卷 74-90,I0004页

作者： Nishi Parikh Meera Karamta Neha Yadav Mohammad Mahdi Tavakoli Daniel Prochowicz Seckin Akin Abul Kalam Soumitra Satapathi Pankaj Yadav Department of Science School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Electrical Engineering School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Telecommunication Ministry of CommunicationMumbai LSAMumbai 400072MaharashtraIndia Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Institute of Physical Chemistry Polish Academy of SciencesKasprzaka 44/5201-224 WarsawPoland Department of Metallurgical and Materials Engineering Karamanoglu Mehmetbey University70200 KaramanTurkey Department of Chemistry Faculty of ScienceKing Khalid UniversityAbha 61413P.O.Box 9004Saudi Arabia Department of Physics Indian Institute of Technology RoorkeeRoorkeeHaridwarUttarakhand 247667India Department of Solar Energy School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia

Development of novel materials with desirable properties remains at the forefront of modern scientific *** learning(ML),a branch of artificial intelligence,has recently emerged as a powerful technology in optoelectronic devices for the prediction of various properties and rational design of *** halide perovskites(MHPs)have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell ***,the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of ***,we comprehensively reviewed different applications of ML in the designing of both MHP absorber layers as well as complete perovskite solar cells(PSCs).At the end,the challenges of ML along with the possible future direction of research are *** believe that this review becomes an indispensable roadmap for optimizing materials composition and predicting design strategies in the field of perovskite technology in the future.

关键词： Machine learning Metal halide perovskites Perovskite solar cell Lead free perovskites

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