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Impact of climate change on hydropower generation in Rio Jubones Basin, Ecuador

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Water Science and Engineering 2018年第2期11卷 157-166页

作者： Mohammad mehedi hasan Guido Wyseure Hydraulic Research Directorate River Research Institute Department of Earth and Environmental Sciences KU Leuven

This study attempted to use the soil and water assessment tool(SWAT), integrated with geographic information systems(GIS), for assessment of climate change impacts on hydropower generation. This methodology of climate change impact modeling was developed and demonstrated through application to a hydropower plant in the Rio Jubones Basin in Ecuador. ArcSWAT 2012 was used to develop a model for simulating the river flow. The model parameters were calibrated and validated on a monthly scale with respect to the hydro-meteorological inputs observed from 1985 to 1991 and from 1992 to 1998, respectively. Statistical analyses produced Nash-Sutcliffe efficiencies(NSEs) of 0.66 and 0.61 for model calibration and validation, respectively, which were considered acceptable. Numerical simulation with the model indicated that climate change could alter the seasonal flow regime of the basin, and the hydropower potential could change due to the changing climate in the *** analysis indicates that, though the hydropower generation will increase in the wet season, the plant will face a significant power shortage during the dry season, up to 13.14% from the reference scenario, as a consequence of a 17% reduction of streamflow under an assumption of a 2.9℃ increase in temperature and a 15% decrease in rainfall. Overall, this study showed that hydrological processes are realistically modeled with SWAT and the model can be a useful tool for predicting the impact of climate change.

关键词： SWAT Hydropower generation Climate change Sensitivity analysis Nash-Sutcliffe efficiency(NSE)

Exciton dynamics in 2D organic semiconductors

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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

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

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

Chloride ingress and macro-cell corrosion of steel in concrete made with recycled brick aggregate

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Frontiers of Structural and Civil Engineering 2021年第6期15卷 1358-1371页

作者： Tarek Uddin MOHAMMED Mahfuzur RAHMAN Ahmed SABBIR Mohammad mehedi hasan Abdullah Al MAMUN Department of Civil and Environmental Engineering Islamic University of TechnologyBoard BazarGazipur 1704Bangladesh Department of Civil Engineering University of Information Technology and SciencesBaridharaDhaka 1202Bangladesh Bangladesh Road Research Laboratory Roads and Highways DepartmentMirpurDhaka 1216Bangladesh

An investigation on chloride ingress and macro-cell corrosion of steel bars in concrete made with recycled brick aggregate(RBA)was carried *** control cases,virgin brick aggregate(BA)and stone aggregate(SA)were also *** cylindrical and cracked prism specimens were studied for 16 different *** prism specimens were made with a segmented steel bar providing electrical connection from outside of the specimens to measure macro-cell corrosion current continuously under seawater splash exposure for a period of 30 d using a data *** specimens were submerged in 3%NaCl solution at a temperature of 40℃ to investigate chloride ingress in concrete made with RBA,BA,and SA after 120 and 180 ***-cell potential,corrosion area,and depths of corrosion were also *** chloride ingress as well as corrosion of steel bars in concrete made with the different types of aggregate is ordered as RBA>BA>SA.

关键词： brick aggregate chloride ingress macro-cell corrosion recycled brick aggregate

Wafer map defect patterns classification based on a lightweight network and data augmentation

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1029-1042页

作者： Naigong Yu Huaisheng Chen Qiao Xu Mohammad mehedi hasan Ouattara Sie Faculty of Information Technology Beijing University of TechnologyBeijingChina Beijing Key Laboratory of Computational Intelligence and Intelligent System BeijingChina Engineering Research Center of Digital Community Ministry of EducationBeijingChina College of Robotic UniversitéFélix Houphouët‐BoignyAbidjanCôte d'Ivoire

Accurately identifying defect patterns in wafer maps can help engineers find abnormal failure factors in production *** the wafer testing stage,deep learning methods are widely used in wafer defect detection due to their powerful feature extraction ***,most of the current wafer defect patterns classification models have high complexity and slow detection speed,which are difficult to apply in the actual wafer production *** addition,there is a data imbalance in the wafer dataset that seriously affects the training results of the *** reduce the complexity of the deep model without affecting the wafer feature expression,this paper adjusts the structure of the dense block in the PeleeNet network and proposes a lightweight network WM‐PeleeNet based on the PeleeNet *** addition,to reduce the impact of data imbalance on model training,this paper proposes a wafer data augmentation method based on a convolutional autoencoder by adding random Gaussian noise to the hidden *** method proposed in this paper has an average accuracy of 95.4%on the WM‐811K wafer dataset with only 173.643 KB of the parameters and 316.194 M of FLOPs,and takes only 22.99 s to detect 1000 wafer *** with the original PeleeNet network without optimization,the number of parameters and FLOPs are reduced by 92.68%and 58.85%,*** augmentation on the minority class wafer map improves the average classification accuracy by 1.8%on the WM‐811K *** the same time,the recognition accuracy of minority classes such as Scratch pattern and Donut pattern are significantly improved.

关键词： convolutional autoencoder lightweight network wafer defect detection

Climate Change and Livelihood Vulnerability of the Local Population on Sagar Island, India

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Chinese Geographical Science 2019年第3期29卷 417-436页

作者： MUKHERJEE Nabanita SIDDIQUE Giyasuddin BASAK Aritra ROY Arindam MANDAL mehedi hasan Department of Geography the University of Burdwan

This paper attempts to assess the vulnerability to climate change of human communities in selected mouzas of Sagar Island,South 24 Parganas District of India. A primary household survey has been conducted to collect data on socio-demographic profile, livelihood strategy, health, food, water, social network, natural disaster and climate variation indicators, were selected for Livelihood Vulnerability Index(LVI) and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change(LVI-IPCC) analyses to measure and compare the vulnerability of mouzas(administrative unit) currently suffering from frequent flooding, coastal erosion and embankment breaching on an annual basis. Secondary data collected from the Indian Meteorological Department, the Water Resources Information System of India and the Global Sea Level Observing System have been used to identify dynamics of climate change by employing statistical and Geographic Information System(GIS) techniques. A GPS survey has been conducted to identify locations of embankment breaching, and satellite images obtained from the National Aeronautics and Space Administration and U.S. Geological Survey(NASA USGS) Government website have been applied to shoreline and land use change detection, using a supervised maximum likelihood classification. The results indicate that the study area has experienced increasing temperature, changing precipitation patterns, rise in sea level, higher storm surges, shoreline change, constant land loss, embankment breaching and changing land use, which have had impact on vulnerability, particularly of poorer people. The LVI(0.48 to 0.68) and LVI-IPCC(0.04 to 0.14) scores suggest that the populations of Dhablat, Bankimnagar, Sumatinagar, Muri Ganga and Sibpur mouzas are highly vulnerable(LVI scores of 0.60 to 0.68 and LVI-IPCC scores of 0.11 to 0.14) to climate change both because the communities are more exposed to it, and because poor access to food, health facilities and water makes them

关键词： climate change livelihood vulnerability index(LVI) adaptation strategies estuarine ecosystem vulnerable population

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

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