检索结果-内蒙古大学图书馆

RSC Applied Interfaces 2024年第1期2卷 220-229页

作者： Aleem, Mahaboobbatcha Vishnuraj, Ramakrishnan Pullithadathil, Biji Nanosensors & Clean Energy Laboratory Department of Chemistry & Nanoscience and Technology PSG Institute of Advanced Studies Coimbatore 641 India Advanced Self-Powered Systems of Integrated Sensors and Technology Center Department of Electrical and Computer Engineering North Carolina State University Raleigh 27695 NC United States Center of Excellence in Advanced Materials and Green Technologies Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India Department of Chemical Engineering and Materials Science Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India

Nitrogen dioxide (NO2) is a toxic gas that can cause respiratory problems, and sensing its presence is crucial for environmental monitoring and industrial safety. This investigation presents a novel approach towards s...

Nitrogen dioxide (NO₂) is a toxic gas that can cause respiratory problems, and sensing its presence is crucial for environmental monitoring and industrial safety. This investigation presents a novel approach towards sensing NO₂ gas by utilizing partially completed/recycled silicon solar cells employing a metal-assisted etching process to fabricate a high-performance p-black-silicon based sensor. Structural and morphological analyses using X-ray diffraction patterns, Raman spectroscopy and cross sectional FESEM characterization confirm the integrity of the p-B-silicon sensor. By combining recycling techniques with advanced fabrication methods, the resulting sensor exhibits exceptional sensitivity, a low detection limit of 1 ppm, and rapid response times (12-14 s) when exposed to NO₂ gas concentrations ranging from 1 to 5 ppm. The enhanced sensitivity is attributed to the unique nanostructured comb-like morphology of the sensor material, which facilitates fast charge transport mechanisms, and a plausible sensing mechanism has been proposed and explained using a depletion model diagram and energy model diagram. This eco-friendly and cost-effective solution not only addresses electronic waste concerns but also highlights the potential of sustainable practices in scientific research. The findings emphasize on the importance of environmental consciousness and innovation, showcasing a promising future for gas sensing technology. By utilizing recycled materials and advanced fabrication techniques, this study contributes to the development of efficient, eco-friendly sensors for environmental monitoring applications, paving the way for a more sustainable and technologically advanced future in the field of gas sensors. © 2025 RSC.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Acquire Carriage for Disabled people in a Visual Surveillance Using Character Recognition

Design and Implementation of Acquire Carriage for Disabled p...

引用

International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication and Computational Intelligence 2022, RAEEUCCI 2022

作者： Nivash, S. Ganesh, E.N. Manikandan, T. Vels Institute of Science Technology and Advanced Studies Chennai India Rajalakshmi Engineering College Chennai India

In certain cases, persons with disabilities may be forced to rely on others for the performance of their duties. Blindness is one of the impairments that might be encountered. Up to this point, there has been N number of solutions presented that make life easier for visually impaired individuals. One of the problems they face on a daily basis is making an independent purchase of a product they need. To solve this issue, the approach is to utilize a camera to record a picture, which is then processed using the tesseract method to extract text from the image, which is then transformed into an audio file that can be heard using headphones. Following the implementation of this strategy, during this shopping trolley technology to detect the item put with machine learning and precision location discover a person will be used to locate a person in the shopping trolley. © Published under licence by IOP Publishing Ltd.

关键词： Purchasing

来源：评论

学校读者我要写书评

暂无评论

Utilizing Gradient Boosting Models to Identify Risk Factors for Stroke 2

Utilizing Gradient Boosting Models to Identify Risk Factors ...

引用

2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Tamilselvi, P. Harini, C. Rao, Guduri Padma Narasimha Raju, P.V. Subbulakshmi, R. Channabasava, Ugranada Department of Computer Science Vels Institute of Science Technology and Advanced Studies Chennai India Maisammaguda Secunderabad India SRKR Engineering College Andhra Pradesh Bhimavaram India Sagi Rama Krishnam Raju Engineering College Bhimavaram India Department of Computer Science and Engineering Karpagam Institute of Technology Coimbatore India Department of Information Science and Engineering Don Bosco Institute of Technology VTU Karnataka Belagavi India

ISBN: (纸本)9798350383867

This research looks at the usage of the models of gradient boosting to find out the ones that are relevant in the stroke incidence. With the help of a large dataset ranging from demographics to clinical and imaging characteristics, the three most effective gradient boosting algorithms (XGBoost with LightGBM and CatBoost) were evaluated in terms of their ability for stroke risk prediction. Model performance metrics, including accuracy, area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, precision, and F1 score, were estimated through re-scheduling validation proses. Through feature importance analysis, I discovered which of predictors, such as age, hypertension, diabetes and others contribute to the stroke risk prediction and where age and hypertension occupy the highest positions. The result of external validation in separate cohorts was the confirmation of the predictive properties of the data assortment as well as the generalizability of the presented models in variety of populations. Also, the role of these models has been examined from the perspective of their clinical usefulness and ability to inform the implementation of targeted preventive interventions that will result in improved outcomes regarding heart health. We evaluated various lifestyle adjustments, medications and precision monitoring plans as being the most likely to have a positive effect on stroke rates and patient outcomes. Overall the present study proves the problem-solving capability of the gradient boosting model in a tailored risk assessment of stroke and stroke prevention, enabling us to implement the necessary interventions to minimize the impact of the diseases on the healthcare systems and individuals. © 2024 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Study the enhanced mechanical properties of Al/B4C metal matrix composite

Study the enhanced mechanical properties of Al/B4C metal mat...

引用

作者： Abhishek Krishna Sai, A. Chandrasekaran, M. Vinod Kumar, T. Pugazhenthi, R. Department of Mechanical Engineering Vels Institute of Science Technology & Advanced Studies Chennai600 117 India

The purpose of this study is to see how Boron carbide (B4C) reinforcement affects the mechanical and wear behaviour of Al7010 alloy in dry sliding conditions at room temperature. The liquid casting method was used to create the aluminium 7010 with B4C metal matrix composites. The flux K2TiF6 was used to address in composites with 5–20 vol% B4C, the wetting problem between AA7010 and B4C, which aids in the development of undesirable phases at interfaces. A pin on disc equipment was used to conduct wear tests on AA7010- composites against an OHNS disc. The wear tests were carried out at a sliding speed of 0.6 m/s, a distance of 1200 m, and loads of 25 and 50 N. The wear resistance of AA 7010 –B4C composites was found to be superior to that of the base alloy. After a short sliding distance, the coefficient of friction achieved a steady-state value. The composites' wear rate and coefficient of friction are significantly reduced when compared to base alloy, and it reaches its lowest value at 10 vol% B4C under all load conditions. The coefficient of friction reduces as the sliding distance rises. The B4C reinforced AA7010 composites had good wear resistance, with 10 vol% B4C being the best for achieving the lowest wear rate under all load circumstances. The composites' hardness and tensile strength improve as the B4C level rises. SEM photos were used to examine the microstructures of the worn surfaces. © 2022

关键词： Wear of materials

来源：评论

学校读者我要写书评

暂无评论

Quantum Machine Learning Techniques based on Nurturing Agri-Ontology Framework in Agricultural Science 3

Quantum Machine Learning Techniques based on Nurturing Agri-...

引用

3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Deepa, R. Jayalakshmi, V. Thilakavathy, P. Bennet Prabhu, A. Surendran, R. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Drbccc Hindu College Department of Computer Applications Chennai India Computer Science and Engineering Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Kone Elevator India Technology & Engineering Centre Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350375190

The absence of a consistent ontological framework often impedes efficient knowledge organization and sharing within the agricultural community, despite the quantity of data created in agricultural research. The lack of defined vocabulary and conceptual frameworks hinders data integration, agricultural research, and innovation by preventing interoperability between databases and systems. To address these issues, this research work proposes the Nurturing Agri-Ontology Framework (NAOF), which offers a systematic approach to creating and updating agricultural ontologies. Ontologies that faithfully portray agricultural ideas and connections can be more easily created with the help of NAOF, which combines ideas from knowledge management, agricultural science, and ontology engineering. NAOF aims to ensure that the ontologies produced reflect the wide range of viewpoints and terminology used in agricultural research by encouraging cooperation among stakeholders, ontology engineers, and domain specialists. In this study, the improvement of knowledge organization, sharing and integration in the agricultural area is shown with the application of NAOF. Using this research study, scientists can build ontologies that improve agricultural decision-making, data interoperability, and the discovery of new information. Using quantum machine learning techniques, a strong foundation of knowledge can be laid for several agricultural applications, such as precision agriculture, crop management, and the formulation of agricultural policies. Ontology coverage, interoperability, scalability, and usability are established evaluation parameters that are used to assess the efficacy of NAOF in this research work. The analysis shows that NAOF effectively solves the problems and creates a better agricultural knowledge ecosystem by thoroughly evaluating it using these standards. © 2024 IEEE.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Cutting edge preparation of microdrills by shear thickening polishing for improved hole quality in electronic PCBs

引用

Frontiers of Mechanical engineering 2024年第2期19卷 99-107页

作者： Jiahuan WANG Mingfeng KE Jiepei LIAO Yu ZHOU Saurav GOEL Jaya VERMA Xu WANG Weigang GUO Julong YUAN Binghai LYU College of Mechanical Engineering Zhejiang University of TechnologyHangzhou 310000China Ultra-precision Machining Center Key Laboratory of Special Purpose Equipment and Advanced Manufacturing TechnologyZhejiang University of TechnologyHangzhou 310000China School of Engineering London South Bank UniversityLondon SE10AAUK Shenzhen Jinzhou Precision Technology Corporation Shenzhen 518116China Department of Mechanical Engineering University of Petroleum and Energy StudiesDehradun 248007India Special Equipment Institute Hangzhou Vocational&Technical CollegeHangzhou 310018China

Printed circuit boards(PCBs)are representative composite materials,and their high-quality drilling machining remains a persistent challenge in the *** finishing of the cutting edge of a microdrill is crucial to drill performance in machining fine-quality holes with a prolonged tool *** miniature size involving submicron scale geometric dimensions,a complex flute shape,and low fracture toughness makes the cutting edge of microdrills susceptible to breakage and has been the primary limiting factor in edge preparation for *** this study,a newly developed cutting edge preparation method for microdrills was tested experimentally on electronic printed circuit *** proposed method,namely,shear thickening polishing,limited the cutting edge burrs and chipping on the cutting edge,and this in turn transformed the cutting edge’s radius from being sharp to ***,the edge–edge radius could be regulated by adjusting the processing *** drilling experiments were conducted to investigate the influence of different cutting edge radii on wear,hole position accuracy,nail head value,and hole wall *** proposed approach showed 20%enhancement in hole position accuracy,33%reduction in the nail head value,and 19%reduction in hole wall roughness compared with the original ***,a threshold is needed;without it,excessive shear thickening polishing will result in a blunt edge,which may accelerate the wear of the *** was identified as the primary factor that reduced hole *** study indicates that in printed circuit board machining,microdrills should effectively eliminate grinding defects and maintain the sharpness of the cutting edge as much as possible to obtain excellent drilling ***,shear thickening polishing is a promising method for cutting edge preparation of *** research and optimization can lead to additional improvements in microdrill performance and contribute to the conti

关键词： microdrill shear thickening polishing cutting edge preparation electronic printed circuit boards hole quality

来源：评论

学校读者我要写书评

暂无评论

Experimental investigation of high carbon steel MMC for crown pinion gear

Experimental investigation of high carbon steel MMC for crow...

引用

作者： Charles Godwin, R. Dhanasekaran, C. Department of Mechanical Engineering Vels Institute of Science Technology & Advanced Studies Tamilnadu Chennai600117 India

The implementation of high carbon steel composite is growing continuously in the field of automotive and manufacturing industries because of their superior physical, mechanical and tribological properties as compared to normal steel. In automobiles, the differential plays major role to power transmission from engine to wheel. However, failure of crown pinion observed that the gear teeth have been sheared off by heat failure and edge of pinion gear is worn down caused by lubricant failure. So, this high carbon steel composite (high carbon steel + silicon carbide) could be proposed for crown pinion gear to control material wear and fracture. In this paper, the various proportions of high carbon steel composites were investigated and evaluated the characteristics of material hardness, compressive strength and material wear. The material proportions were 100–0 %, 99–1 % and 97.5–2.5 % of high carbon steel with silicon carbide. By observing experimental results, the high carbon steel with 2 % of silicon carbide have better material characteristics than other proportions and this also suggested to crown pinion gear production. © 2022

关键词： Powder metallurgy

来源：评论

学校读者我要写书评

暂无评论

CNN-LSTM: Development of Offline Signature Authentication 1

CNN-LSTM: Development of Offline Signature Authentication

引用

1st IEEE International Conference on Emerging Research in Computational Science, ICERCS 2023

作者： Ganapathy, Revathy Lingeshwaran, D. Suthanthiradevi, P. Harish Kumar, M.V. Vels Insitute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai India

ISBN: (纸本)9798350359756

Offline Signature Authentication is a critical task in the field of document authentication, and its accuracy is essential for ensuring security while transactions. This research proposes two approaches: Initially Pre-trained CNN models are used to extract features from signature images, which are then combined with handcrafted features such as HOG and some other geometric features of signature. Such combined features are passed to bidirectional LSTM model in which drop out layer undergoes classification which differentiate real and forgery signature. The proposed system has potential applications in document authentication and security, subsequently combination of CNN models and additional features provides more comprehensive representation of signature images resulting in improved accuracy. Three signature datasets are utilized namely GDPS, CEDAR, and BHSig-Bengali each with varying signature styles and image quality. Our experimental outcomes reveal that Bidirectional Convolutional LSTM along with handcraft features attained maximum accuracy in offline signature verification system. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Sensing of Surface Texture using Smart Glove for Post Stroke Rehabilitation

Sensing of Surface Texture using Smart Glove for Post Stroke...

引用

Trends in Material Science and Inventive Materials (ICTMIM), International Conference on

作者： S Priya P Sherin Heera Rj Hemalatha Department of Biomedical Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Post-stroke patients need to be rehabilitated in order to gain partly or fully some of the motor facilities that seem to have ceased to function effectively. According to the research, post-stroke deficits in the human ability to palpate and comprehend surface features is the major difficulty a stroke survivor may experience; often they cause harm or accidentally destroy objects due to an incorrect manner of holding them. This research offers a new strategy with the aid of wearable haptic interface in the form of a smart glove that employs an ESP32 microcontroller and force sensors to identify surface texture. Using pattern recognition, we can effectively distinguish between a rough and a smooth surface to adapt to the pressure required to hold any object. This innovation apart from improving safety also gives the patient feedback in the process of rehabilitation. The use of machine learning in particular proves to be more preferable when it comes to texture recognition preventing shortcomings observed in other senor-based approaches.

关键词： Wireless sensor networks Machine learning Stroke (medical condition) Motors Surface roughness Surface texture Rough surfaces Haptic interfaces Force sensors Surface treatment

来源：评论

学校读者我要写书评

暂无评论

Recognition of Deep Fake Voice Acoustic using Ensemble Bagging Model

Recognition of Deep Fake Voice Acoustic using Ensemble Baggi...

引用

Electronics and Sustainable Communication Systems (ICESC), 2020 International Conference on

作者： Shaik Abdul Yunus Basha K.Ulaga Priya Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

As artificial speech generates technological evolution; fake voice information has become an increasingly prevalent avenue for fraud. Numerous investigations have been carried out into machine learning techniques, signal processing techniques, and the Automatic Speaker Verification System to address such issues. Since there are increasing methods to create fake information, techniques must be developed to determine when audio recordings employed as electronic proof are corrupted. Such recordings contain the potential to be manipulated. Hence, this research work identified the data regarding audio systems as either fake or real by i) extracting features from audio file metadata using oversampling techniques and ii) Developing an Ensemble Bagging Model appropriate for analyzing input audio signal followed by classification of fake (fraudulent) and real (authentic) audio. Our experimental results reveal that the ensemble bagging model attained an accuracy of 99.5%, precision of 99%, 99.6% recall, and 99.9% Fl-measure in the prediction of the audio system compared with traditional approaches.

关键词： Deepfakes Accuracy Audio systems Speech recognition Metadata Feature extraction Audio recording Real-time systems Fraud Bagging

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：