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Exciton dynamics in 2D organic semiconductors

Materials Futures 2022年第4期1卷 5-16页

作者： Ankur Sharma md mehedi hasan Yuerui Lu School of Engineering College of Engineering and Computer ScienceThe Australian National UniversityCanberraACT 2601Australia

Two-dimensional(2D)semiconducting materials have been studied extensively for their interesting excitonic and optoelectronic properties arising from strong many-body interactions and quantum confinement at 2D *** of these materials have been inorganic,such as transition metal dichalcogenides,phosphorene,*** semiconductor materials,on the other hand been investigated for their excellent electrical conductivity and low dielectric coefficients for similar applications in the thin film or bulk material *** lack of crystallinity in the thin film and bulk phases has led to ambiguity over the excitonic and electronic/optical band gap *** recent emergence of 2D organic materials has opened a new domain of high crystallinity and controlled morphology,allowing for the study of low-lying excitonic states and optoelectronic *** have been demonstrated to have different excitonic properties compared with the Wannier–Mott excitons in inorganic 2D *** we present our recent experimental observations and analysis of 2D organic semiconductor *** discuss the role of high-crystalline and morphology-controlled growth of single-crystalline materials and their optoelectronic *** report explains the Frenkel(FR)and charge-transfer(CT)excitons and subsequent light emission and absorption properties in organic *** true nature of low-lying excitonic states,which arises from the interaction between CT and FR excitons,is experimentally studied and discussed to reveal the electronic band *** then discuss the pure FR behaviour we observed in J–type aggregated organic materials leading to coherent superradiant excitonic *** supertransport of excitons within the organic materials,facilitated by their pure FR nature,and the delocalization of excitons over a large number of molecules are also ***,we discuss the applications and our vision for these organic 2D materials in fast o

关键词： excitonic organic semiconductors two-dimensional

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iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features

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Genomics, Proteomics & Bioinformatics 2020年第5期18卷 593-600页

作者： md.mehedi hasan Mst.Shamima Khatun Hiroyuki Kurata Department of Bioscience and Bioinformatics Kyushu Institute of TechnologyIizukaFukuoka 820-8502Japan Biomedical Informatics R&D Center Kyushu Institute of TechnologyIizukaFukuoka 820-8502Japan

Linear B-cell epitopes are critically important for immunological applications,such as vaccine design,immunodiagnostic test,and antibody production,as well as disease diagnosis and *** accurate identification of linear B-cell epitopes remains challenging despite several decades of *** this work,we have developed a novel predictor,Identification of Linear B-cell Epitope(i LBE),by integrating evolutionary and sequence-based *** successive feature vectors were optimized by a Wilcoxon-rank sum *** the random forest(RF)algorithm using the optimal consecutive feature vectors was applied to predict linear B-cell *** combined the RF scores by the logistic regression to enhance the prediction *** yielded an area under curve score of 0.809 on the training dataset and outperformed other prediction models on a comprehensive independent *** is a powerful computational tool to identify the linear B-cell epitopes and would help to develop penetrating diagnostic tests.A web application with curated datasets for iLBE is freely accessible at http://***/iLBE/.

关键词： Linear B-cell epitope BLAST Feature encoding Feature selection Random forest

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Solution processed high performance perovskite quantum dots/ZnO phototransistors

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Nano Research 2022年第4期15卷 3660-3666页

作者： md mehedi hasan Eric Moyen Jewel Kumer Saha md Mobaidul Islam Arqum Ali Jin Jang Advanced Display Research Center(ADRC) Department of Information DisplayKyung Hee University26Kyungheedae-roDongdaemun-guSeoul 02447Republic of Korea

Phototransistors that can detect visible light have been fabricated using solution processed zinc oxide channel/zirconium oxide gate insulator thin film transistors(TFTs)and room temperature synthesized perovskite quantum dots(PeQDs)as active *** ZnO thin film transistors did not show a photocurrent under visible light ***,ZnO TFTs decorated with PeQDs exhibited enhanced photocurrent upon exposure to visible *** device had a responsivity of 567 A/W(617 A/W),a high detectivity of 6.59×10^(13)Jones(1.85×10^(14)J)and a high sensitivity of 10^(7)(10^(8))under green(blue)light at a low drain voltage of 0.1 *** high photo-responsivity and detectivity under green light resulted from the combination of short ligands in the QDs films and the high mobility of the spray coated ZnO *** results are relevant for the development of low cost and low energy consumption phototransistors working in the visible range.

关键词： ZnO thin film transistors perovskite quantum dots photo-detectors photo-transistors

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Efficient Feature Selection and Machine Learning Based ADHD Detection Using EEG Signal

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Computers, Materials & Continua 2022年第9期72卷 5179-5195页

作者： md.Maniruzzaman Jungpil Shin md.Al mehedi hasan Akira Yasumura School of Computer Science and Engineering The University of AizuAizuwakamatsuFukushima965-8580Japan Faculty of Humanities and Social Science Kumamoto UniversityChuo-kuKumamotoJapan

Attention deficit hyperactivity disorder(ADHD)is one of the most common psychiatric and neurobehavioral disorders in children,affecting 11%of children *** study aimed to propose a machine learning(ML)-based algorithm for discriminating ADHD from healthy children using their electroencephalography(EEG)*** study included 61 children with ADHD and 60 healthy children aged 7–12 *** morphological and time-domain features were extracted from EEG *** t-test(p-value<0.05)and least absolute shrinkage and selection operator(LASSO)were used to select potential features of children with ADHD and enhance the classification *** selected potential features were used in four ML-based algorithms,including support vector machine(SVM),k-nearest neighbors,multilayer perceptron(MLP),and logistic regression,to classify ADHD and healthy *** overall prevalence of boys and girls with ADHD was 48.9%and 56.5%,*** average age of children with ADHD was 9.6±1.8 *** results illustrated that the combination of LASSO with SVM classifier achieved the highest accuracy of 94.2%,sensitivity of 93.3%,F1-score of 91.9%,and AUC of *** results also illustrated that MLP was the second-best ML-based classifier,which gave 93.4%accuracy,91.7%sensitivity,91.1%F1-score,and 0.960 *** findings indicated that the combination of the LASSO-based feature selection method and SVM classifier can be a useful tool for selecting reliable/potential features and classifying ADHD and healthy *** proposed ML-based algorithms could be useful for the early diagnosis of children with ADHD.

关键词： ADHD feature extraction feature selection classification machine learning

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Investigation of accuracy of pavement mechanistic empirical prediction performance by incorporating Level 1 inputs

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Journal of Traffic and Transportation Engineering(English Edition) 2020年第2期7卷 259-268页

作者： md mehedi hasan A.S.M.Asifur Rahman Rafiqul A.Tarefder Department of Civil Engineering University of New MexicoAlbuquerqueNM 87131USA Texas A&M Transportation Institute Texas A&M UniversityCollege StationTX 77845USA

The recently developed AASHTOWare pavement mechanistic empirical(M-E)design requires advanced characterization of pavement *** particular,M-E Level 1 analysis requires materials input parameters to be obtained from the laboratory test *** cooperation with the New Mexico Department of Transportation(NmdOT),six pavement sites were selected to compare M-E Level 1 predicted performances from laboratory tested data with the field *** materials such as subgrade,base,asphalt concrete,binder,aggregate,etc.,were collected from these pavements sites during *** dynamic modulus,fatigue endurance limit(FEL),dynamic shear rheometer,and resilient modulus tests were conducted on the collected *** these parameters,pavement sections,as constructed,were modeled and analyzed in M-E at Levels 1,2 and *** predicted distress quantities for international roughness index(IRI)and rutting were compared with the field collected data as well as among the three design *** analysis results demonstrated that M-E overpredicts IRI and rutting in the pavement compared to the field *** was also observed that Level 1 showed the lowest rutting,whereas the maximum rutting was found at Level *** dynamic modulus of AC layer was underpredicted at Levels 2 and 3 resulting in higher rutting and IRI.

关键词： Pavement M-E Rutting Validation IRI Design

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Rotation,Translation and Scale Invariant Sign Word Recognition Using Deep Learning

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Computer Systems Science & Engineering 2023年第3期44卷 2521-2536页

作者： Abu Saleh Musa Miah Jungpil Shin md.Al mehedi hasan md Abdur Rahim Yuichi Okuyama School of Computer Science and Engineering The University of AizuAizuwakamatsuFukushima965-8580Japan Department of Computer Science and Engineering Pabna University of Science and TechnologyPabnaBangladesh

Communication between people with disabilities and people who do not understand sign language is a growing social need and can be a tedious *** of the main functions of sign language is to communicate with each other through hand *** of hand gestures has become an important challenge for the recognition of sign *** are many existing models that can produce a good accuracy,but if the model test with rotated or translated images,they may face some difficulties to make good performance *** resolve these challenges of hand gesture recognition,we proposed a Rotation,Translation and Scale-invariant sign word recognition system using a convolu-tional neural network(CNN).We have followed three steps in our work:rotated,translated and scaled(RTS)version dataset generation,gesture segmentation,and sign word ***,we have enlarged a benchmark dataset of 20 sign words by making different amounts of Rotation,Translation and Scale of the ori-ginal images to create the RTS version *** we have applied the gesture segmentation *** segmentation consists of three levels,i)Otsu Thresholding with YCbCr,ii)Morphological analysis:dilation through opening morphology and iii)Watershed ***,our designed CNN model has been trained to classify the hand gesture as well as the sign *** model has been evaluated using the twenty sign word dataset,five sign word dataset and the RTS version of these *** achieved 99.30%accuracy from the twenty sign word dataset evaluation,99.10%accuracy from the RTS version of the twenty sign word evolution,100%accuracy from thefive sign word dataset evaluation,and 98.00%accuracy from the RTS versionfive sign word dataset ***,the influence of our model exists in competitive results with state-of-the-art methods in sign word recognition.

关键词： Sign word recognition convolution neural network(cnn) rotation translation and scaling(rts) otsu segmentation

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Characterization of subgrade soil mixed with recycled asphalt pavement

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Journal of Traffic and Transportation Engineering(English Edition) 2018年第3期5卷 207-214页

作者： md mehedi hasan md Rashadul Islam Rafiqul A.Tarefder Department of Civil Engineering University of New Mexico Civil Engineering Technology Colorado State University-Pueblo

Due to awareness to greener environment, use of recycled asphalt material has become popular in asphalt pavement industry. The use of recycled asphalt pavement （RAP） ma- terials in subgrade soil can be an additional scope of utilizing RAP. This study investigates the effect of RAP on the resilient modulus （MR） of subgrade soils mixed with RAP materials. Note that MR is the principal material input parameter for designing asphalt pavement using the recent mechanistic-empirical pavement design software. As a first step of the current study, different percentages of RAP and moisture were thoroughly mixed with subgrade soils. Then, the MR of these RAP mixed soils were determined using the AASHTO T 307 （1999） at different stress levels in the laboratory. Results show that the MR of RAP mixed soil increases with the applied deviatoric and bulk stresses, however, it is less sensitive to applied confining pressure. Use of RAP materials has made the soils stiff enough not to respond to the confining pressure. As expected, the MR value reaches a maximum at the optimum moisture content and increases linearly with RAP content. The MR values and characteristics of the RAP mixed subgrade soils, as determined by the current study, can be used for subgrade design and stabilization using RAP for better pavement design.

关键词： Subgrade Recycled asphalt pavement Moisture Resilient modulus Stress

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Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin md.Al mehedi hasan Abu Saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer Science and Engineering The University of AizuAizuwakamatsu965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet

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Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

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Protection and Control of Modern Power Systems 2023年第3期8卷 97-138页

作者： Faiaz Ahsan Nazia hasan Dana Subrata K.Sarker Li Li S.M.Muyeen md.Firoj Ali Zinat Tasneem md.mehedi hasan Sarafat Hussain Abhi md.Robiul Islam md.Hafiz Ahamed md.Manirul Islam Sajal K.Das md.Faisal R.Badal Prangon Das Department of Mechatronics Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh School of Electrical and Data Engineering Faculty of Engineering and ITUniversity of Technology SydneyUltimoAustralia Electrical Engineering Department Qatar UniversityDohaQatar

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO_(2) *** structure of these technologies relies on the deep inte-gration of advanced data-driven techniques which can ensure efficient energy generation,transmission,and *** conducting thorough research for more than a decade,the concept of the smart grid(SG)has emerged,and its practice around the world paves the ways for efficient use of reliable energy ***,many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid(NGSG).Also,to deal with the non-linearity and uncertainty,the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of *** paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation,including intelligent control,agent-based energy conversion,edge computing for energy management,internet of things(IoT)enabled inverter,agent-oriented demand side management,***,a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques(DDTs)for the sustainable operation of the *** prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering,technology,et ***,the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied,while some major future issues are *** paper can offer extended support for engineers and researchers in the context of data-driven technology and the SG.

关键词： Data-driven technology Smart grid Sustainable energy evolution Next-generation smart grid Intelligent

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拜耳作物科学有限公司在中国的发展战略

拜耳作物科学有限公司在中国的发展战略

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作者： md mehedi hasan 石家庄铁道大学

学位级别：硕士

拜耳作物科学有限公司是一家全球化企业，2001年进入中国，在作物保护、生物科学、农业领域方面有很强的竞争力，是农业研究最大的机构之一。本文基于战略管理和竞争战略理论，对拜耳作物科学（中国）有限公司当前所面临的问题进行了研... 详细信息

拜耳作物科学有限公司是一家全球化企业，2001年进入中国，在作物保护、生物科学、农业领域方面有很强的竞争力，是农业研究最大的机构之一。本文基于战略管理和竞争战略理论，对拜耳作物科学（中国）有限公司当前所面临的问题进行了研究，并且制定了该公司在未来五年的发展战略计划。本文运用战略管理的分析方法和模型，对该公司的战略进行分析。采用SWOT分析方法，深入地分析了其外部环境的机会和威胁。以外部环境的研究作为战略计划的基础。基于人力资源管理和市场营销的优势，对该公司内部环境的优势和劣势进行分析。通过对该公司进行BCG矩阵分析，基于人力资源和财务管理体系以及中国农作物的市场环境，提出了拜耳作物科学有限公司在中国发展的战略措施。本论文综述了SWOT和BCG等传统战略管理的研究方法，全面分析了拜耳作物科学有限公司在发展中出现的问题。其研究目的是使公司进一步发展，核心思想是使该公司通过与其他农业公司合作，共享生产技术如生产线和管理方法等资源，实现双赢。

关键词：拜耳作物科学有限公司农业战略战略管理战略分析工具战略分析模型战略发展模式

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