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Role of self-help groups on socioeconomic development and the achievement of Sustainable Development Goals(SDGs)among rural women in Cooch Behar District,India

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Regional Sustainability 2024年第2期5卷 63-74页

作者： Debanjan BASAK Indrajit Roy chowdhury Department of Geography and Applied Geography University of North BengalSiliguri734013India

This study e.amines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(SDGs)of the United *** this study,we explored the effect of SHGs on rural women by specifically addressing SDGs,such as no poverty(SDG 1),zero hunger(SDG 2),good health and well-being(SDG 3),quality education(SDG 4),and gender equality(SDG 5).Given this issue,a cross-sectional survey and comparison analyses are needed to assess the socioeconomic development of rural women and their awareness level before and after the participation of rural women in *** survey conducted as part of this study was divided into three sections,namely,demographic characteristics,socioeconomic development,and awareness level,with each focusing on different aspects.A group of 400 individuals who were part of SHGs completed the questionnaire survey *** results showed that the participation of rural women in SHGs significantly improved their socioeconomic development and awareness level,as supported by both mean values and t test *** in SHGs and microcredit programs were the major elements that boosted the socioeconomic development of rural women,which also achieves SDGs 1,2,3,4,and *** study revealed that participation in SHGs and related financial services significantly aided rural women in economically disadvantaged communities in accumulating savings and initiating entrepreneurial ***,participation in SHGs was instrumental in enhancing the self-confidence,self-efficacy,and overall self-esteem of rural ***,doing so enabled them to move more freely for work and other activities and to make family and common decisions.

关键词： Self-help groups Rural women Socioeconomic development Sustainable Development Goals(SDGs) Microcredit India

Detailed characterization of kHz-rate laser-driven fusion at a thin liquid sheet with a neutron detection suite

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High Power Laser Science and engineering 2024年第1期12卷 13-23页

作者： Benjamin M.Knight Connor M.Gautam Colton R.Stoner Bryan V.egner Joseph R.Smith Chris M.Orban Juan J.Manfredi Kyle D.Frische Michael L.Dexter e.am a.chowdhury Anil K.Patnaik Department of engineering Physics Air Force Institute of TechnologyWPAFBOHUSA Physics Department Marietta CollegeMariettaOHUSA Department of Physics The Ohio State UniversityColumbusOHUSA Department of Materials Science and engineering and Department of Electrical and Computer ScienceThe Ohio State UniversityColumbusOHUSA Intense energy Solutions LLCPlain CityOHUSA

We present detailed characterization of laser-driven fusion and neutron production(-10^(5)/second) using 8 mJ, 40 fs laser pulses on a thin(<1 μm) D_2O liquid sheet employing a measurement suite. At relativistic inte... 详细信息

We present detailed characterization of laser-driven fusion and neutron production(-10^(5)/second) using 8 mJ, 40 fs laser pulses on a thin(eet employing a measurement suite. At relativistic intensity(~ 5 × 10^(18)W/cm^(2))and high repetition rate(1 kHz), the system produces deuterium±deuterium(D-D) fusion, allowing for consistent neutron generation. evidence of D-D fusion neutron production is verified by a measurement suite with three independent detection systems: an eJ-309 organic scintillator with pulse-shape discrimination, a ~3He proportional counter and a set of 36 bubble detectors. Time-of-flight analysis of the scintillator data shows the energy of the produced neutrons to be consistent with 2.45 MeV. Particle-in-cell simulations using the WarpX code support significant neutron production from D-D fusion events in the laser±target interaction region. This high-repetition-rate laser-driven neutron source could provide a low-cost, on-demand test bed for radiation hardening and imaging applications.

关键词： high-repetition-rate laser-driven fusion laser-plasma interaction liquid target neutron detectors

enhancing Telemarketing Success Using ensemble-Based Online Machine Learning

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Big Data Mining and Analytics 2024年第2期7卷 294-314页

作者： Shahriar Kaisar Md Mamunur Rashid Abdullahi chowdhury Sakib Shahriar Shafin Joarder Kamruzzaman Abebe Diro Department of Information Systems and Business Analytics RMIT UniversityMelbourne 3000Australia School of engineering and Technology Central Queensland UniversityRockhampton 4700Australia Faculty of engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide 5005Australia Centre for Smart Analytics Federation University AustraliaBallarat 3350Australia School of Accounting Information Systems and Supply ChainRMIT UniversityMelbourne 3000Australia

Telemarketing is a well-established marketing approach to offering products and services to prospective *** effectiveness of such an approach,however,is highly dependent on the selection of the appropriate consumer base,as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested *** introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base,and the existing literature in this direction shows promising ***,the selection of influential features and the construction of effective learning models for improved performance remain a ***,from the modelling perspective,the class imbalance nature of the training data,where samples with unsuccessful outcomes highly outnumber successful ones,further compounds the problem by creating biased and inaccurate ***,customer preferences are likely to change over time due to various reasons,and/or a fresh group of customers may be targeted for a new product or service,necessitating model retraining which is not addressed at all in existing works.A major challenge in model retraining is maintaining a balance between stability(retaining older knowledge)and plasticity(being receptive to new information).To address the above issues,this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately.A novel online learning method is proposed for model retraining when new samples are available over *** newly introduced method equips the proposed approach to deal with dynamic data,leading to improved readiness of the proposed model for practical adoption,and is a highly useful addition to the *** experiments with real-world data show that the proposed approach achieves excellent results in all cases(e.g.,98.6

关键词： machine learning online learning oversampling telemarketing imbalanced dataset ensemble model

Multiplexed fluorescence and scatter detection with single cell resolution using on-chip fiber optics for droplet microfluidic applications

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Microsystems & Nanoengineering 2024年第2期10卷 207-218页

作者： Preksha Gupta ambili Mohan Apurv Mishra Atindra Nair Neeladri chowdhury Dhanush Balekai Kavyashree Rai Anil Prabhakar Taslimarif Saiyed Discovery Innovation Accelerator Centre for Cellular and Molecular PlatformsBellary RoadBengaluru560065KarnatakaIndia Department of electrical engineering Indian Institute of Technology MadrasChennai600036Tamil NaduIndia

Droplet microfluidics has emerged as a critical component of several high-throughput single-cell analysis techniques in biomedical research and *** significant progress in the development of individual assays,multiparametric optical sensing of droplets and their encapsulated contents has been *** current approaches,most commonly involving microscopy-based high-speed imaging of droplets,are technically complex and require expensive instrumentation,limiting their widespread *** address these limitations,we developed the OptiDrop platform;this platform is a novel optofluidic setup that leverages the principles of flow *** platform enables on-chip detection of the scatter and multiple fluorescence signals from the microfluidic droplets and their contents using optical *** highly customizable on-chip optical fiber-based signal detection system enables simplified,miniaturized,low-cost,multiparametric sensing of optical signals with high sensitivity and single-cell resolution within each *** demonstrate the ability of the OptiDrop platform,we conducted a differential expression analysis of the major histocompatibility complex(MHC)protein in response to IFNγ*** results showed the platform’s ability to sensitively detect cell surface biomarkers using fluorescently labeled ***,the OptiDrop platform combines the versatility of flow cytometry with the power of droplet microfluidics to provide wide-ranging,scalable optical sensing solutions for research and diagnostics.

关键词： scatter enable resolution

Microstrip Patch Antenna with an Inverted T-Type Notch in the Partial Ground for Breast Cancer Detections

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Computer Modeling in engineering & Sciences 2024年第2期138卷 1301-1322页

作者： Nure Alam chowdhury Lulu Wang Md Shazzadul Islam Linxia Gu Mehmet Kaya Department of Biomedical engineering and Science Florida Institute of TechnologyMelbourneFL 32901USA Biomedical Device Innovation Center Shenzhen Technology UniversityShenzhen518118China Department of electrical and Computer engineering International Islamic University MalaysiaJalan GombakSelangor53100Malaysia

This study designs a microstrip patch antenna with an inverted T-type notch in the partial ground to detect tumorcells inside the human *** size of the current antenna is small enough(18mm×21mm×1.6mm)todistribute around the breast *** operating frequency has been observed from6–14GHzwith a minimumreturn loss of−61.18 dB and themaximumgain of current proposed antenna is 5.8 dBiwhich is flexiblewith respectto the size of *** the distribution of eight antennas around the breast phantom,the return loss curveswere observed in the presence and absence of tumor cells inside the breast phantom,and these observations showa sharp difference between the presence and absence of tumor *** simulated results show that this proposedantenna is suitable for early detection of cancerous cells inside the breast.

关键词： Antenna microwave wideband cancer breast phantom tumor detection

XPS Studies on electroless As-Deposited and Annealed Ni-P Films

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engineering（科研） 2024年第5期16卷 123-133页

作者： Towhid Adnan chowdhury Department of electrical & electronic engineering Ahsanullah University of Science & Technology Dhaka Bangladesh

electroless deposition has been used to deposit Ni-P films on glass slides using the reducing agent sodium hypophosphite. This has been done with a purpose to use Ni-P films as back contact for silicon carbide radiation detectors. By keeping deposition time, temperature, pH and concentration of the precursor solution constant, the film deposition has been done. XPS studies were done to analyze the composition and stoichiometry of Ni-P thin films.

关键词： Ni-P X-Ray Photoelectron Spectroscopy Annealing electroless Deposition Binding energy Reducing Agent

Spatio-temporal variation and relationship between agricultural efficiency and irrigation intensity in a semi-arid region of India

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Regional Sustainability 2024年第2期5卷 123-139页

作者： Shibu DAS Kaushal Kumar SHARMA Suranjan MAJUMDeR Debabrata DAS Indrajit Roy chowdhury Centre for the Study of Regional Development School of Social SciencesJawaharlal Nehru UniversityNew Delhi110067India Department of Geography&Applied Geography University of North BengalDarjeeling734013India Geography Department of Krishnagar Government College Krishnagar741101India

A surging population in Karnataka State,a semi-arid region in India,poses a threat to both food security and livelihood sustainability,necessitating a concentrated effort to bolster agricultural efficiency and achieve United Naton’s Sustainable Development Goal 2(zero hunger).Therefore,in order to address the pressing issue of food scarcity in Karnataka,this study meticulously e.amined the spatio-temporal variation of agricultural efficiency and irrigation intensity in Karnataka,uncovering its significant dependence of agricultural efficiency on irrigation ***,this study used a one-way analysis of variance(ANOVA)to ascertain significant differences in the means of agricultural efficiency and irrigation intensity during 2004-2005 and *** study showed that the maximum improvement in agricultural efficiency index was recorded in Belgaum(40.24),Gulbarga(24.77),and Yadgir districts(22.92)between 2004-2005 and 2018-2019,which indicated the progressing trend and better scope for agriculture *** the contrary,some districts expressed threat(a decline of above 20.00 of agricultural efficiency index)and needed special care for the improvement of agricultural efficiency in four northern districts(Bagalkot,Bidar,Raichur,and Bijapur),three southern districts(Chitradurga,Chikballapur and Hassan),and two southern districts(Koppal and Gadag)in *** 2004-2005,irrigation intensity varied from 3.19%to 56.39%,with the lowest irrigation intensity in Kodagu District and the highest irrigation intensity in Shimoga *** 2018-2019,irrigation intensity changed from 0.77%to 72.77%,with the lowest irrigation intensity in Kodagu District and the highest in Dakshin Kannad ***,the research scrutinized the complex relationship between agricultural efficiency and irrigation intensity,with the correlation coefficient increased from 0.162 during 2004-2005 to 0.255 during *** implies that in both periods,a low positive

关键词： Agricultural efficiency Irrigation intensity One-way analysis of variance(ANOVA) Food security Karnataka

Radiography Image Classification Using Deep Convolutional Neural Networks

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Journal of Computer and Communications 2024年第6期12卷 199-209页

作者： Ahmad chowdhury Haiyi Zhang Department of Computer Science Acadia University Wolfville Canada

Research has shown that chest radiography images of patients with different diseases, such as pneumonia, COVID-19, SARS, pneumothorax, etc., all exhibit some form of abnormality. Several deep learning techniques can be used to identify each of these anomalies in the chest x-ray images. Convolutional neural networks (CNNs) have shown great success in the fields of image recognition and image classification since there are numerous large-scale annotated image datasets available. The classification of medical images, particularly radiographic images, remains one of the biggest hurdles in medical diagnosis because of the restricted availability of annotated medical images. However, such difficulty can be solved by utilizing several deep learning strategies, including data augmentation and transfer learning. The aim was to build a model that would detect abnormalities in chest x-ray images with the highest probability. To do that, different models were built with different features. While making a CNN model, one of the main tasks is to tune the model by changing the hyperparameters and layers so that the model gives out good training and testing results. In our case, three different models were built, and finally, the last one gave out the best-predicted results. From that last model, we got 98% training accuracy, 84% validation, and 81% testing accuracy. The reason behind the final model giving out the best evaluation scores is that it was a well-fitted model. There was no overfitting or underfitting issues. Our aim with this project was to make a tool using the CNN model in R language, which will help detect abnormalities in radiography images. The tool will be able to detect diseases such as Pneumonia, Covid-19, effusions, Infiltration, Pneumothorax, and others. Because of its high accuracy, this research chose to use supervised multi-class classification techniques as well as Convolutional Neural Networks (CNNs) to classify different chest x-ray images. CNNs are extr

关键词： CNN Radiography Image Classification R Keras Chest X-Ray Machine Learning

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