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Quantum Particle Swarm Optimization with Deep learning-Based Arabic Tweets Sentiment Analysis

Computers, Materials & Continua 2023年第5期75卷 2575-2591页

作者： Badriyya BAl-onazi Abdulkhaleq Q.A.Hassan Mohamed K.Nour Mesfer Al Duhayyim Abdullah Mohamed Amgad Atta Abdelmageed Ishfaq Yaseen Gouse Pasha Mohammed Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of English College of Science and Arts at MahayilKing Khalid UniversityAbha62217Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24231Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16828Saudi Arabia Research centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16436Saudi Arabia

Sentiment Analysis(SA),a Machine learning(ML)technique,is often applied in the *** SA technique is specifically applied to the data collected from social media *** research studies conducted earlier upon the SA of the tweets were mostly aimed at automating the feature extraction *** this background,the current study introduces a novel method called Quantum Particle Swarm Optimization with Deep learning-Based Sentiment Analysis on Arabic Tweets(QPSODL-SAAT).The presented QPSODL-SAAT model determines and classifies the sentiments of the tweets written in ***,the data pre-processing is performed to convert the raw tweets into a useful ***,the word2vec model is applied to generate the feature *** Bidirectional Gated Recurrent Unit(BiGRU)classifier is utilized to identify and classify the ***,the QPSO algorithm is exploited for the optimal finetuning of the hyperparameters involved in the BiGRU *** proposed QPSODL-SAAT model was experimentally validated using the standard *** extensive comparative analysis was conducted,and the proposed model achieved a maximum accuracy of 98.35%.The outcomes confirmed the supremacy of the proposed QPSODL-SAAT model over the rest of the approaches,such as the Surface Features(SF),Generic Embeddings(GE),Arabic Sentiment Embeddings constructed using the Hybrid(ASEH)model and the Bidirectional Encoder Representations from Transformers(BERT)model.

关键词： Sentiment analysis Arabic tweets quantum particle swarm optimization deep learning word embedding

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FSPM-P： towards a general functional-structural plant model for robust and comprehensive model development

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Frontiers of Computer Science 2016年第6期10卷 1103-1117页

作者： Michael HENKE Winfried KURTH Gerhard H. BUCK-SORLIN Department of Ecoinformatics Biometrics and Forest Growth University of Gottingen Gottingen 37077 Germany UMR1345 Institut de Recherche en Horticulture et Semences (IRHS) AGROCAMPUS OUEST Centre d'Angers Angers 49045 France

In the last decade, functional-structural plant modelling （FSPM） has become a more widely accepted paradigm in crop and tree production, as 3D models for the most important crops have been proposed. Given the wider portfolio of available models, it is now appropriate to enter the next level in FSPM development, by introducing more efficient methods for model development. This includes the consideration of model reuse （by modularisafion）, combination and comparison, and the enhancement of existing mod- els. To facilitate this process, standards for design and communication need to be defined and established. We present a first step towards an efficient and general, i.e., not speciesspecific FSPM, presently restricted to annual or bi-annual plants, but with the potential for extension and further generalization. Model structure is hierarchical and object-oriented, with plant organs being the base-level objects and plant individual and canopy the higher-level objects. Modules for the majority of physiological processes are incorporated, more than in other platforms that have a similar aim （e.g., photosynthesis, organ formation and growth）. Simulation runs with several general parameter sets adopted from the literature show that the present prototype was able to reproduce a plausible output range for different crops （rapeseed, barley, etc.） in terms of both the dynamics and final values （at harvest time） of model state variables such as assimilate production, organ biomass, leaf area and architecture.

关键词： functional-structural plant model prototyping,modelling standards teaching / learning FSPM GroIMP

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Variational quantum simulation of thermal statistical states on a superconducting quantum processer

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Chinese Physics B 2023年第1期32卷 74-87页

作者：郭学仪李尚书效骁相忠诚葛自勇李贺康宋鹏涛彭益王战许凯张潘王磊郑东宁范桁 Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100190China The Chinese University of Hong Kong ShatinNew TerritoriesHong KongChina CAS Center for excellence in Topological Quantum Computation University of Chinese Academy of SciencesBeijing 100190China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China International centre for Theoretical Physics Asia-Pacific Beijing/HangzhouChina Songshan Lake Materials Laboratory Dongguan 523808China Beijing Academy of Quantum Information Sciences Beijing 100193China

Quantum computers promise to solve finite-temperature properties of quantum many-body systems,which is generally challenging for classical computers due to high computational ***,we report experimental preparations of Gibbs states and excited states of Heisenberg X X and X X Z models by using a 5-qubit programmable superconducting *** the experiments,we apply a hybrid quantum–classical algorithm to generate finite temperature states with classical probability models and variational quantum *** reveal that the Hamiltonians can be fully diagonalized with optimized quantum circuits,which enable us to prepare excited states at arbitrary energy *** demonstrate that the approach has a self-verifying feature and can estimate fundamental thermal observables with a small statistical *** on numerical results,we further show that the time complexity of our approach scales polynomially in the number of qubits,revealing its potential in solving large-scale problems.

关键词： superconducting qubit quantum simulation variational quantum algorithm quantum statistical mechanics machine learning

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The critical role of electrochemically activated adsorbates in neutral OER

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Science China Materials 2020年第12期63卷 2509-2516页

作者： Longsheng Zhang Haiyang Yuan Liping Wang Hui Zhang Yijing Zang Yao Tian Yunzhou Wen Fenglou Ni Hao Song Haifeng Wang Bo Zhang Huisheng Peng State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular Science and Laboratory of Advanced MaterialsFudan UniversityShanghai 200438China Key Laboratory for Advanced Materials Key Laboratory for Advanced MaterialsCentre for Computational Chemistry and Research Institute of Industrial CatalysisEast China University of Science and TechnologyShanghai 200237China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesCAS Center for Excellence in Superconducting ElectronicsShanghai 200050China Key Laboratory of Systems Bioengineering School of Chemical Engineering and TechnologySynBio Research PlatformCollaborative Innovation Centre of Chemical Science and EngineeringTianjin UniversityTianjin 300072China

Developing efficient electrocatalysts for the oxygen evolution reaction(OER)under neutral conditions is important for microbial electrolysis cells(MECs).However,the OER kinetics in neutral electrolytes at present are extremely sluggish,resulting in high overpotentials that greatly limit the energy conversion efficiencies of *** studies failed to probe the adsorbates on surface metal sites of catalysts at the atomic scale and elucidate their influence on the catalytic activities,which has impeded the rational design of efficient neutral OER catalysts with optimal surface ***,using in situ transmission electron microscopy(TEM),in situ X-ray photoelectron spectroscopy(XPS)and in situ low-energy ion scattering studies,we have identified,for the first time,that the electrochemically activated adsorbates on surface metal sites play a critical role in boosting the neutral OER activities of Ru-Ir binary oxide(RuxIryO2)*** adsorbate-activated RuxIryO2on a glassy carbon electrode achieved a low overpotential of 324 m V at10 m A cm-2in neutral electrolyte,with a 36-fold improvement in turnover frequency compared with that of Ir *** application in an MEC system,the resulting full cell showed a decreased voltage of 1.8 V,200 m V lower than the best value reported to date,facilitating efficient synthesis of poly(3-hydroxybutyrate)from bioelectrochemical *** functional theory(DFT)studies revealed that the enhanced OER activity of RuxIryO2catalyst arose from local structural distortion of adjacent adsorbate-covered Ru octahedra at the catalyst surface and the consequently decreased adsorption energies of OER intermediates on Ir active center.

关键词： electrocatalysis oxygen evolution reaction adsorbates neutral electrolytes

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Enhanced light-matter interactions in dielectric nanostructures via machine-learning approach

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Advanced Photonics 2020年第2期2卷 57-67页

作者： Lei Xu Mohsen Rahmani Yixuan Ma Daria ASmirnova Khosro Zangeneh Kamali Fu Deng Yan Kei Chiang Lujun Huang Haoyang Zhang Stephen Gould Dragomir N.Neshev Andrey E.Miroshnichenko University of New South Wales School of Engineering and Information TechnologyCanberraAustralia Nottingham Trent University School of Science&TechnologyDepartment of EngineeringAdvanced Optics and Photonics LaboratoryNottinghamUnited Kingdom Australian National University Research School of PhysicsNonlinear Physics CentreCanberraAustralia Australian National University Research School of PhysicsARC Centre of Excellence for Transformative Meta-Optical Systems(TMOS)CanberraAustralia Queensland University of Technology School of Electrical Engineering and Computer ScienceBrisbaneQueenslandAustralia Australian National University College of Engineering and Computer ScienceCanberraAustralia

A key concept underlying the specific functionalities of metasurfaces is the use of constituent components to shape the wavefront of the light on *** are versatile,novel platforms for manipulating the scattering,color,phase,or intensity of ***,one of the typical approaches for designing a metasurface is to optimize one or two variables among a vast number of fixed parameters,such as various materials’properties and coupling effects,as well as the geometrical ***,this would require multidimensional space optimization through direct numerical ***,an alternative,popular approach allows for reducing the computational cost significantly based on a deep-learning-assisted *** utilize a deep-learning approach for obtaining high-quality factor(high-Q)resonances with desired characteristics,such as linewidth,amplitude,and spectral *** exploit such high-Q resonances for enhancedlight–matter interaction in nonlinearoptical metasurfaces and optomechanical vibrations,*** demonstrate that optimized metasurfaces achieve up to 400-fold enhancement of the third-harmonic generation;at the same time,they also contribute to 100-fold enhancement of the amplitude of optomechanical *** approach can be further used to realize structures with unconventional scattering responses.

关键词： machine learning dielectric nanostructures Fano resonance third-harmonic generation optoacoustics

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Producing Knowledge in the War Zones: Challenges and Risks of Academia in Rojava

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Asian Journal of Middle Eastern and Islamic Studies 2023年第3期17卷 296-308页

作者： Seevan Saeed centre for Black Sea Studies Shaanxi Normal UniversityXi'anChina

This paper is based on the ongoing studies that examines the notion of producing knowledge and pursuing academic activities under exceptional *** is argued that academia and scientific institutions are under scrutiny in terms of their inde-pendence,neutrality and quality of producing knowledge and sci-entific *** the countries that have lesser chance for freedom of expression and dialogue atmosphere,scientific institu-tions are naturally under less advantage academic ***,they are directly connected to the interests and the will of the state or powerful groups in ***,this paper tries to shed light on the conditions within which universities and aca-demic institutions in war zones and areas besieged by chaos and state *** paper is written with a focus on Syria and par-ticularly on North Eastern Self Administration entity of *** paper tries to look at the challenges that these institutions are facing,in terms frameworks and recognition,freedom of works and limitations,risk of life and safety,and most importantly,the quality of producing knowledge and their academic *** aspect that this paper tries to highlight is the claim of providing new and different style of knowledge productions out of the frame of mainstream style of academia in the *** alterna-tive and radical modes and methods of teaching and learning can develop in such an environment?What forms of relations between academia and society are developed,and what are the main obstacles in front of these relations?For this purpose,the focus will be on two recently established universities in Rojava,'University of Rojava and Kobane University'.My contribution is based on my experiences of working as an instructor of social and political thoughts at the Institute of Social Sciences at the University of Rojava as well as my multiple visits to the actual Area of Syria and Rojava and conducting interviews with students,staff,and education p

关键词： University producing knowledge war zone Rojava challenges

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THE PRACTICE OF GOOD LEADERSHIP WITHIN THE MEDICAL PROFESSION

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临床误诊误治 2008年第2期21卷 1-4页

作者： Victor Yu Melbourne Australia Monash University Monash Medical centre Victoria

My university studies and postgraduate training equipped me to be a competent doctor and medical specialist,but in 1976 when I was 30 years old,I was invited to come to Melbourne to establish a Neonatal Intensive Care Unit in an university teaching hospital and to be its Director.I had never taken any leadership or management course to equip me to be a *** over 30 years later,on the eve of my retirement from medicine,I look back to reflect on what kind of leader I was over the course of my medical *** wisdom did I gain over the past 30 years on becoming a good leader,based on learning from the mistakes I had made in exercising the leadership roles I was given within the hospital and university,as well as in the national and international professional arenas? This essay begins with a general principle of good leadership followed by an examination of aspects of pride,power and submission,which if misused or abused,constitute a trilogy of harmful influences on the character of leaders and their wise exercise of good leadership.

关键词： Hospital management Leadership Ability

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Prediction of chromatin looping using deep hybrid learning(DHL)

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Quantitative Biology 2023年第2期11卷 155-162页

作者： Mateusz Chilinski Anup Kumar Halder Dariusz Plewczynski Faculty of Mathematics and Information Sciences Warsaw University of Technology00-662 WarsawPoland Laboratory of Functional and Structural Genomics centre of New Technologies University of Warsaw 02-097 WarsawPoland

Background:With the development of rapid and cheap sequencing techniques,the cost of whole-genome sequencing(WGS)has dropped ***,the complexity of the human genome is not limited to the pure sequenceand additional experiments are required to learn the human genome's influence on complex *** of the most exciting aspects for scientists nowadays is the spatial organisation of the genome,which can be discovered using spatial experiments(e.g.,Hi-C,ChIA-PET).The information about the spatial contacts helps in the analysis and brings new insights into our understanding of the disease ***:We have used an ensemble of deep learning with classical machine learning *** deep learning network we used was DNABERT,which utilises the BERT language model(based on transformers)for the genomic *** classical machine learning models included support vector machines(SVMs),random forests(RFs),and K-nearest neighbor(KNN).The whole approach was wrapped together as deep hybrid learning(DHL).Results:We found that the DNABERT can be used to predict the ChIA-PET experiments with high ***,the DHL approach has increased the metrics on CTCF and RNAPII ***:DHL approach should be taken into consideration for the models utilising the power of deep *** straightforward in the concept,it can improve the results significantly.

关键词： deep learning 3D genomics transformers spatial organisation of nucleus ChIA-PET DNA-Seq

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Polynomial chaos surrogate and bayesian learning for coupled hydro-mechanical behavior of soil slope

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Rock Mechanics Bulletin 2023年第1期2卷 27-37页

作者： Lulu Zhang Fang Wu Xin Wei Hao-Qing Yang Shixiao Fu Jinsong Huang Liang Gao State Key Laboratory of Ocean Engineering Department of Civil EngineeringShanghai Key Laboratory for Digital Maintenance of Buildings and InfrastructureShanghai Jiao Tong University800 Dongchuan RoadShanghaiChina Department of Civil Engineering Shanghai Jiao Tong University800 Dongchuan RoadShanghaiChina State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University800 Dongchuan RoadShanghaiChina ARC centre of excellence for Geotechnical Science and Engineering University of NewcastleCallaghanNSW2308Australia Faculty of Science and Technology University of MacaoE11Avenida da UniversidadeTaipaMacaoChina

As rainfall infiltrates into soil slopes,the hydraulic and mechanical behaviors of soils are *** this study,an efficient probabilistic parameter estimation method for coupled hydro-mechanical behavior in soil slope is *** method integrates the Polynomial Chaos Expansion(PCE)method,the coupled hydro-mechanical modeling,and the Bayesian learning method.A coupled hydro-mechanical numerical model is established for the simulation of behaviors of unsaturated soil slope under rainfall infiltration,following by training a cheap-to-run PCE surrogate to replace *** estimation of soil parameters is conducted based on the Bayesian learning technique with the Markov Chain Monte Carlo(MCMC)simulation.A numerical example of an unsaturated slope under rainfall infiltration is presented to illustrate the proposed *** effects of measurement durations and response types on parameter estimation are *** result shows that with the increase of measurement duration,the uncertainties of soil parameters are significantly *** uncertainties of hydraulic properties are reduced significantly using the pore water pressure data,while the uncertainties of soil strength parameters are reduced greatly using the measured displacement data.

关键词： Landslide Hydro-mechanical Polynomial chaos expansion Bayesian learning Markov chain Monte Carlo

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Multi-Versus Optimization with Deep Reinforcement learning Enabled Affect Analysis on Arabic Corpus

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Computer Systems Science & Engineering 2023年第12期47卷 3049-3065页

作者： Mesfer Al Duhayyim Badriyya B.Al-onazi Jaber S.Alzahrani Hussain Alshahrani Mohamed Ahmed Elfaki Abdullah Mohamed Ishfaq Yaseen Gouse Pasha Mohammed Mohammed Rizwanullah Abu Sarwar Zamani Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAflaj16273Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Research centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sentiment analysis(SA)of the Arabic language becomes important despite scarce annotated corpora and confined *** affect Analysis has become an active research zone *** still,the Arabic language lags behind adequate language sources for enabling the SA ***,Arabic still faces challenges in natural language processing(NLP)tasks because of its structure complexities,history,and distinct *** has gained lesser effort than the other *** paper developed a Multi-versus Optimization with Deep Reinforcement learning Enabled Affect Analysis(MVODRL-AA)on Arabic *** presented MVODRL-AAmodelmajorly concentrates on identifying and classifying effects or emotions that occurred in the Arabic ***,the MVODRL-AA model follows data pre-processing and word ***,an n-gram model is utilized to generate word embeddings.A deep Q-learning network(DQLN)model is then exploited to identify and classify the effect on the Arabic *** last,the MVO algorithm is used as a hyperparameter tuning approach to adjust the hyperparameters related to the DQLN model,showing the novelty of the work.A series of simulations were carried out to exhibit the promising performance of the MVODRL-AA *** simulation outcomes illustrate the betterment of the MVODRL-AA method over the other approaches with an accuracy of 99.27%.

关键词： Arabic language Arabic corpus natural language processing affect analysis deep learning

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