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Effectiveness of hybrid ensemble machine learning models for landslide susceptibility analysis:Evidence from Shimla district of North-west Indian Himalayan region

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Journal of Mountain Science 2024年第7期21卷 2368-2393页

作者： SHARMA Aastha SAJJAD Haroon rahaman md.hibjur SAHA Tamal Kanti BHUYAN Nirsobha Department of Geography Faculty of SciencesJamia Millia IslamiaNew Delhi-110025India

The Indian Himalayan region is frequently experiencing climate change-induced ***,landslide susceptibility assessment assumes greater significance for lessening the impact of a landslide *** paper makes an attempt to assess landslide susceptibility in Shimla district of the northwest Indian Himalayan *** examined the effectiveness of random forest(RF),multilayer perceptron(MLP),sequential minimal optimization regression(SMOreg)and bagging ensemble(B-RF,BSMOreg,B-MLP)models.A landslide inventory map comprising 1052 locations of past landslide occurrences was classified into training(70%)and testing(30%)*** site-specific influencing factors were selected by employing a multicollinearity *** relationship between past landslide occurrences and influencing factors was established using the frequency ratio *** effectiveness of machine learning models was verified through performance *** landslide susceptibility maps were validated by the area under the receiver operating characteristic curves(ROC-AUC),accuracy,precision,recall and *** key performance metrics and map validation demonstrated that the BRF model(correlation coefficient:0.988,mean absolute error:0.010,root mean square error:0.058,relative absolute error:2.964,ROC-AUC:0.947,accuracy:0.778,precision:0.819,recall:0.917 and F-1 score:0.865)outperformed the single classifiers and other bagging ensemble models for landslide *** results show that the largest area was found under the very high susceptibility zone(33.87%),followed by the low(27.30%),high(20.68%)and moderate(18.16%)susceptibility *** factors,namely average annual rainfall,slope,lithology,soil texture and earthquake magnitude have been identified as the influencing factors for very high landslide *** texture,lineament density and elevation have been attributed to high and moderate ***,the study calls for devising suitable landslide mitig

关键词： Landslide susceptibility Site-specific factors Machine learning models Hybrid ensemble learning Geospatial techniques Himalayan region

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Computer vision-based six layered ConvNeural network to recognize sign language for both numeral and alphabet signs

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Biomimetic Intelligence & Robotics 2024年第1期4卷 45-58页

作者： Muhammad Aminur rahaman Kabiratun Ummi Oyshe Prothoma Khan Chowdhury Tanoy Debnath Anichur Rahman md.Saikat Islam Khan Department of Computer Science and Engineering Green University of BangladeshDhakaBangladesh Department of Computer Science and Engineering National Institute of Textile Engineering and Research(NITER)Constituent Institute of Dhaka UniversityDhakaBangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversityTangailBangladesh

People who have trouble communicating verbally are often dependent on sign language,which can be difficult for most people to understand,making interaction with them a difficult *** Sign Language Recognition(SLR)system takes an input expression from a hearing or speaking-impaired person and outputs it in the form of text or voice to a normal *** existing study related to the Sign Language Recognition system has some drawbacks,such as a lack of large datasets and datasets with a range of backgrounds,skin tones,and *** research efficiently focuses on Sign Language Recognition to overcome previous *** importantly,we use our proposed Convolutional Neural Network(CNN)model,“ConvNeural”,in order to train our ***,we develop our own datasets,“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”,both of which have ambiguous backgrounds.“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”both include images of Bangla characters and numerals,a total of 24,615 and 8437 images,***“ConvNeural”model outperforms the pre-trained models with accuracy of 98.38%for“BdSL_OPSA22_STATIC1”and 92.78%for“BdSL_OPSA22_STATIC2”.For“BdSL_OPSA22_STATIC1”dataset,we get precision,recall,F1-score,sensitivity and specificity of 96%,95%,95%,99.31%,and 95.78%***,in case of“BdSL_OPSA22_STATIC2”dataset,we achieve precision,recall,F1-score,sensitivity and specificity of 90%,88%,88%,100%,and 100%respectively.

关键词： Conv NeuralSign language CNN Static Feature extraction Convolution2D Fully connected layer Dropout

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Deep learning methods for noisy sperm image classification from convolutional neural network to visual transformer:a comprehensive comparative study

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Intelligent Medicine 2024年第2期4卷 114-127页

作者： Ao Chen Chen Li md Mamunur rahaman Yudong Yao Haoyuan Chen Hechen Yang Peng Zhao Weiming Hu Wanli Liu Shuojia Zou Ning Xu Marcin Grzegorzek Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information EngineeringNortheastern UniversityShenyangLiaoning 110169China Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA School of Arts and Design Liaoning Petrochemical UniversityFushunLiaoning 113001China Institute of Medical Informatics University of LübeckLüebeckGermany

Background With the gradual increase of infertility in the world,among which male sperm problems are the main factor for infertility,more and more couples are using computer-assisted sperm analysis(CASA)to assist in the analysis and treatment of ***,the rapid development of deep learning(DL)has led to strong results in image classification ***,the classification of sperm images has not been well studied in current deep learning methods,and the sperm images are often affected by noise in practical CASA *** purpose of this article is to investigate the anti-noise robustness of deep learning classification methods applied on sperm *** The SVIA dataset is a publicly available large-scale sperm dataset containing three *** this work,we used subset-C,which provides more than 125,000 independent images of sperms and impurities,including 121,401 sperm images and 4,479 impurity *** investigate the anti-noise robustness of deep learning classification methods applied on sperm images,we conducted a comprehensive comparative study of sperm images using many convolutional neural network(CNN)and visual transformer(VT)deep learning methods to find the deep learning model with the most stable anti-noise *** This study proved that VT had strong robustness for the classification of tiny object(sperm and impurity)image datasets under some types of conventional noise and some adversarial *** particular,under the influence of Poisson noise,accuracy changed from 91.45%to 91.08%,impurity precison changed from 92.7%to 91.3%,impurity recall changed from 88.8%to 89.5%,and impurity F1-score changed 90.7%to 90.4%.Meanwhile,sperm precision changed from 90.9%to 90.5%,sperm recall changed from 92.5%to 93.8%,and sperm F1-score changed from 92.1%to 90.4%.Conclusion Sperm image classification may be strongly affected by noise in current deep learning methods;the robustness with regard to noise of VT methods based

关键词： Computer-assisted sperm analysis Anti-noise Robustness Deep learning .Image classification Sperm image Conventional noise Adversarial attacks Convolutional neural network Visual transformer

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Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and Communications 2024年第6期12卷 135-151页

作者： md. Mehedi Hasan md. Masud Rana Abu Sayed md. Mostafizur rahaman Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

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Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

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Geoscience Frontiers 2022年第2期13卷 21-33页

作者： md Masroor Haroon Sajjad Sufia Rehman Roshani Singh md.hibjur rahaman Mehebub Sahana Raihan Ahmed Ram Avtar Department of Geography Faculty of Natural SciencesJamia Millia IslamiaNew DelhiIndia School of Environment Education and Development(SEED)University of ManchesterUnited Kingdom Graduate School of Environment Earth Science Hokkaido UniversityJapan

Drought is a natural phenomenon posing severe implications for soil,groundwater and agricultural *** has been recognized as one of the most pervasive global change drivers to affect the *** being a weakly renewable resource takes a long time to form,but it takes no time to ***,the response of soil to drought conditions as soil loss is not manifested in the existing ***,this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in *** remote sensing data was utilized for driving drought indices during ***,we constricted Temperature condition index(TCI)and Vegetation Condition Index(VCI)from Land Surface Temperature(LST)and Enhanced Vegetation Index(EVI)derived from MODIS *** and VCI were then integrated to determine the Vegetation Health Index(VHI).Revised Universal Soil Loss Equation(RUSLE)was utilized for estimating soil *** relationship between drought condition and vegetation was ascertained using the Pearson *** of the northern and southern watersheds experienced severe drought condition in the sub-basin *** mean frequency of the drought occurrence was 7.95 *** average soil erosion in the sub-basin was estimated to be 9.88 t ha^(-1)year^(-1).A positive relationship was observed between drought indices and soil erosion values(r value being 0.35).However,wide variations were observed in the distribution of spatial *** various factors,the slope length and steepness were found to be the main drivers of soil erosion in the ***,the study calls for policy measures to lessen the impact of drought and soil erosion.

关键词： Drought vulnerability Soil erosion RUSLE Vegetation Health Index(VHI) Godavari middle sub-basin

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How do board features and auditor characteristics shape key audit matters disclosures?Evidence from emerging economies

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China Journal of Accounting Research 2023年第4期16卷 51-69页

作者： md Mustafizur rahaman md.Rezaul Karim UQ Business School The University of QueenslandBrisbaneQLD 4072Australia Department of Accounting and Information Systems University of DhakaDhaka 1000Bangladesh

This study examines how corporate board features and auditor characteristics in Bangladesh influence the disclosure of key audit matters(KAM)in annual reports from 2018 to *** ordinary least squares(OLS)regressions,the study finds that factors such as chair gender,the presence of women on the board,audit committee(AC)size,auditor tenure,and client-auditor relationship significantly affect KAM ***,AC expertise,family CEO succession,and board political connections do not have significant ***,having a family member CEO with a long-tenured auditor has a negative association with KAM disclosure,while a politically connected family CEO has a positive association with such ***,Big-4 auditors of important clients are negatively associated with KAM disclosure.

关键词： Key audit matters Board characteristics Auditor characteristics Corporate governance Bangladesh

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Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language

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Frontiers of Computer Science 2020年第3期14卷 45-64页

作者： Muhammad Aminur rahaman Mahmood JASIM md.Haider ALI md.HASANUZZAMAN Department of Computer Science and Engineering University of DhakaDhaka-1000Bangladesh

Because of using traditional hand-sign segmentation and classification algorithm,many diversities of Bangla language including joint-letters,dependent vowels *** representing 51 Bangla written characters by using only 36 hand-signs,continuous hand-sign-spelled Bangla sign language(BdSL)recognition is *** paper presents a Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language which consists of two *** phase is designed for hand-sign classification and the second phase is designed for Bangla language modeling algorithm(BLMA)for automatic recognition of hand-sign-spelled Bangla sign *** first phase,we have proposed two step classifiers for hand-sign classification using normalized outer boundary vector(NOBV)and window-grid vector(WGV)by calculating maximum inter correlation coefficient(ICC)between test feature vector and pre-trained feature *** first,the system classifies hand-signs using *** classification score does not satisfy specific threshold then another classifier based on WGV is *** system is trained using 5,200 images and tested using another(5,200×6)images of 52 hand-signs from 10 signers in 6 different challenging environments achieving mean accuracy of 95.83%for classification with the computational cost of 39.972 milliseconds per *** the Second Phase,we have proposed Bangla language modeling algorithm(BLMA)which discovers all"hidden characters"based on"recognized characters"from 52 hand-signs of BdSL to make any Bangla words,composite numerals and sentences in BdSL with no training,only based on the result of first *** the best of our knowledge,the proposed system is the first system in BdSL designed on automatic recognition of hand-sign-spelled BdSL for large *** system is tested for BLMA using hand-sign-spelled 500 words,100 composite numerals and 80 sentences in BdSL achieving mean accuracy of 93.50%,95.50%and 90.50%respectively.

关键词： Bangla sign language(BdSL) hand-sign classification Bangla language modeling rules(BLMR) Bangla language modeling algorithm(BLMA)

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Electrical analysis of single-walled carbon nanotube as gigahertz on-chip interconnects

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Frontiers of Information Technology & Electronic Engineering 2017年第2期18卷 262-271页

作者： Zamshed Iqbal CHOWDHURY md. Istiaque rahaman M. Shamim KAISER Institute of Information Technology Jahangirnagar University Dhaka 1342 Bangladesh Department of Electrical & Electronic Engineering Ahsanullah University of Science & Technology Dhaka 1208 Bangladesh

在未来的高频系统芯片,特别是片上网络的设计中,知识产权模块之间的联系至为关键,而单壁纳米碳管则是其中一种很有前景的纳米结构。电路及系统尺寸的不断缩减限制了对1000 GH级别高频信号特征的利用。本文针对不同结构构型的单壁纳米碳... 详细信息

在未来的高频系统芯片,特别是片上网络的设计中,知识产权模块之间的联系至为关键,而单壁纳米碳管则是其中一种很有前景的纳米结构。电路及系统尺寸的不断缩减限制了对1000 GH级别高频信号特征的利用。本文针对不同结构构型的单壁纳米碳管,对高质量互联中四项重要的四项电参数——阻抗,传播常量,电流密度以及信号延时进行了推导。每个参数均表现出了对其设计互联频率范围和构型的强相关性。与现有理论和实验结果相比,本文所提出的模型在解决下一代高速集成电路互联问题上有其新颖性。

关键词：互联碳纳米管电流密度传播常量特性阻抗片上系统

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Design and analysis of high birefringence and nonlinearity with small confinement loss photonic crystal fiber

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Frontiers of Optoelectronics 2019年第2期12卷 165-173页

作者： Rekha SAHA md.Mahbub HOSSAIN md. Ekhlasur rahaman Himadri Shekhar MONDAL Electronics and Communication Engineering Discipline Khulna UniversityKhulna 9208Bangladesh

High birefringence with low confinement loss photonic crystal fiber (PCF) has significant advantages in the field of sensing, dispersion compensation devices, nonlinear applications, and polarization filter. In this report, two different models of PCFs are presented and compared. Both the models contain five air holes rings with combination of circular and elliptical air holes arrangement. Moreover, the elliptical shaped air holes polarization and the third ring air holes rotational angle are varied. To examine different guiding characteristics, finite element method (FEM) with perfectly matched layer (PML) absorbing boundary condition is applied from 1.2 to 1.8 |im wavelength range. High birefringence, low confinement loss, high nonlinearity, and moderate disper-sion values are successfully achieved in both the PCFs models. Numeric analysis shows that model-1 gives higher birefringence (2.75 ×10^-2) and negative dispersion (-540.67 ps/(nm ·km)) at 1.55 |im wavelength. However, model-2 gives more small confinement loss than model-1 at the same wavelength. In addition, the proposed design demonstrates the variation of rotation angle has great impact to enhance guiding properties especially the birefringence.

关键词： birefringence dispersion polarization main-taining photonic crystal fiber (PCF) polarization-selective devices polarization

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A real-time hand-signs segmentation and classification system using fuzzy rule based RGB model and grid-pattern analysis

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Frontiers of Computer Science 2018年第6期12卷 1258-1260页

作者： Muhammad Aminur rahaman Mahmood JASIM md.Haider ALI Tao ZHANG md.HASANUZZAMAN Department of Computer Science and Engineering University of DhakaDhaka-1000Bangladesh Department of Automation School of Information Science &EngineeringTsinghua UniversityBeijing 100084China

Computer vision based researches of automatic hand-signs classification using simple camera based image are increasing rapidly in the present world. Hand-signs are the basic unit of the sign languages. So, successful ...

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