检索结果-内蒙古大学图书馆

2nd International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Dighe, Akshada Garg, Bindu Department of Computer Engineering BVDUCOE Pune India Department of Computer Science and Business System BVDUCOE Pune India

ISBN: (纸本)9798331541217

Intellectual disability (ID), a developmental condition often stemming from prenatal or postnatal factors, exerts a profound influence on individuals' lives and necessitates timely intervention. Conventional screening methods are resource-intensive and demand specialized medical expertise. This study introduces a novel, non-invasive approach to ID screening by meticulously analyzing facial features and vocal characteristics extracted from interview *** the extraction of facial measurements and speech patterns, we devised a Craniofacial Variability Index (CVI) to assess the likelihood of ID. Furthermore, advanced machine learning techniques were strategically employed to augment the predictive accuracy of this index. Our empirical findings unequivocally demonstrate promising results, with an accuracy rate reaching up to 80% when synergizing CVI scores and phonetic features. This research underscores the potential of a non-invasive, AI-powered screening instrument for ID, offering a more accessible and efficient alternative to prevailing practices. Future investigations will concentrate on refining the model and validating its efficacy across diverse populations. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Optimization of process parameters in 3D printing of polycarbonate for high heat applications

引用

Interactions 2024年第1期245卷 1-21页

作者： Srinivas, Bathula Satishkumar, P. Saminathan, Rajasekaran Srikanth, Barre Andhra Pradesh Odalarevu533210 India Department of Mechanical Engineering Rathinam Technical Campus Coimbatore Tamil Nadu Coimbatore India Department of Mechanical Engineering College of Engineering and computer science Jazan University Jizan Saudi Arabia

This experimentation conducts for the optimization of Polycarbonate(PC) material 3D printing factors. The printing is done on the Flash Forge Guider 2 FDM equipment, employing the Taguchi methodology. The factors considered for optimization include infill rate (60%, 80%, 100%), film height (0.18 mm, 0.24 mm, 0.30 mm), and printing speed (40 mm/s, 60 mm/s, 80 mm/s). Tensile, compressive, and flexural experiments were performed to examine the mechanical properties of the printed objects. The experimental results revealed the highest tensile strength (39.106 MPa) at an infill rate of 100%, printing speed of 40 mm/s, and film thickness of 0.30 mm. As well as, the greatest compressive toughness (76.421 MPa) was produced at a fill density of 100%, printing rate of 60 mm/s, and layer thickness of 0.18 mm. The flexural toughness carried its peak (253.1 MPa) at an infill rate of 100%, printing rate of 40 mm/s, and film thickness of 0.30 mm. Using Signal-Noise (S/N) ratio charts, the maximum factors for improving tensile toughness were resolved as infill rate 100%, printing speed 40 mm/s, and film height 0.24 mm. For compressive toughness development, the maximum factors were detected as infill rate 100%, printing speed 60 mm/s, along with film height 0.18 mm. Flexural toughness optimization showed the infill rate 100%, printing speed 80 mm/s, along with film height 0.30 mm. Analysis of Variance (ANOVA) recommended the important contributions of every factor to the mechanical props. For tensile toughness, infill rate provides 93.37%, printing speed 0.121%, along with film height 4.17%. Compressive toughness development was provided to infill rate (87.48%), printing speed (3.81%), along with film height (2.38%). In the case of flexural toughness, infill rate provides 47.36%, printing speed 0.96%, along with film height 50%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Tensile strength

来源：评论

学校读者我要写书评

暂无评论

Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms

引用

Environmental Monitoring and Assessment 2025年第3期197卷 1-36页

作者： RajasundrapandiyanLeebanon, T. Murugan, N. S. Sakthivel Kumaresan, K. Jeyabose, Andrew Department of Electrical and Electronics Engineering TamilNadu College of Engineering Tamil Nadu Coimbatore India Department of Mechanical Engineering Park College of Engineering & Technology TamilNadu Coimbatore India Department of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India

Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystems, making it a key factor in environmental sustainability among various renewable energy sources. This study integrates two advanced signal processing techniques—empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD)—with machine learning (ML) algorithms, including multilayer perceptron (MLP), random forest regression (RFR), support vector regression (SVR), and ridge regression, to forecast long-term solar radiation. Meteorological data spanning 13 years (2000–2012) from seven locations across India (Bhubaneswar, Chennai, Delhi, Hyderabad, Nagpur, Patna, and Trivandrum) were used for training and testing. The optimal model was identified based on performance metrics, including the highest linear correlation coefficient (R), and the lowest mean absolute error (MAE) and root mean square error (RMSE). The results indicate that EEMD integrated with ML algorithms consistently outperformed EMD-based approaches. Among the ML models evaluated, EEMD integrated with MLP achieved the best performance across all locations, with RMSE = 0.332, MAE = 0.26, and R2 = 0.99. Furthermore, a comparative analysis with previous studies demonstrated that the proposed approach provides superior accuracy, underscoring its efficacy in solar radiation forecasting. © The Author(s) 2025.

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Soft-GNN:towards robust graph neural networks via self-adaptive data utilization

引用

Frontiers of computer science 2025年第4期19卷 1-12页

作者： Yao WU Hong HUANG Yu SONG Hai JIN National Engineering Research Center for Big Data Technology and System Service Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China College of Information and Communication National University of Defense TechnologyWuhan 430019China Department of Computer Science and Operations Research Universitéde MontréalMontreal H3C 3J7Canada

Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.

关键词： graph neural networks node classification label noise robustness

来源：评论

学校读者我要写书评

暂无评论

Enhancement of mechanical properties in AA5083 aluminum metal matrix composites through alumina and titanium carbide reinforcement

引用

Interactions 2024年第1期245卷 1-12页

作者： Vadivel, M. S., Seenivasan P., Satishkumar S., Gomkale R., Saminathan Department of Civil Engineering Nehru Institute of Technology Tamilnadu Coimbatore India Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore India Applied Chemistry Yeshwantrao Chavan College of Engineering Maharashtra Nagpur India Department of Mechanical Engineering College of Engineering and Computer Science Jazan University Jazan Saudi Arabia

As a result of its remarkable resistance to corrosion, strong wear resistance, high strength, and low weight, aluminum metal matrix composites (AMMC’s) have garnered tremendous widespread recognition for structural and aeronautical applications. Several mechanical properties of aluminum alloy (AA5083) are examined in this experimental study, which focuses on the impact of reinforcing particles (alumina and titanium carbide). The stir casting method was used to manufacture AMMC. Fabrication was carried out using the less difficult ex-situ approach. Reinforcement particle weight percentages ranging from 4 to 12% were used in the MMC preparation process. Machine operations were performed on the ingots following manufacturing in order to prepare test samples. To investigate the mechanical and tribological properties and effects of different reinforcement weight percentages, tests were conducted including tensile, compression, impact, hardness and wear tests. Adding alumina and titanium carbide resulted in a gradual rise of the tensile and compression strengths. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Aluminum corrosion

来源：评论

学校读者我要写书评

暂无评论

Sentirec - A Sentiment Analysis with Recommendation system 8

Sentirec - A Sentiment Analysis with Recommendation System

引用

8th International Conference on Communication and Electronics systems, ICCES 2023

作者： Oswalt Manoj, S. Catherine Chandralekha, T. Dharshini, R.M. Hemadharsini, P. Sri Krishna College of Engineering and Technology Department of Computer Science and Business System Coimbatore India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350396638

The standard language is assessed, and the feelings transmitted by the individual are brought up. The purpose of sentiment analysis is to determine the polarity of a person's textual opinion. Most of the people use social media to market ourselves and share all knowledge, thoughts, ideas, and experiences with the rest of the world. Sentiment analysis has been studied by several internet companies that offer materials based on human emotions expressed through social media. Many people use social media to post and share their thoughts and feelings. The sentiment analysis standard assorts a sentence with all forms of emotions, each of which has an intensity. This study includes a sentiment analysis of diverse perspectives on social topics that are trending on social media, along with a recommendation system. This method recommends related content to viewers based on their current statement or issue. The algorithm also suggests customized video sets to users based on their social media activity, such as diverse perspectives on a particular social problem about which they actively express their thoughts on social media. NLP algorithms are utilized for sentiment analysis and recommendation systems. © 2023 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Optimizing mechanical strength and thermal stability of sisal fiber-plastic composites by high-temperature treatment

引用

Interactions 2025年第1期246卷 1-15页

作者： Mungle, Nischal P. Jadhav, Varsha D. Kulkarni, Sumant Khanderao D.S.Vijayan Saminathan, Rajasekaran Satishkumar, P. Department of Mechanical Engineering Yeshawantrao Chavan College of Engineering Maharashtra Wanadongari Nagpur India Department of Artificial Intelligence and Data Science Vishwakarma Institute of Technology Maharashtra Pune India School of Civil Engineering REVA University Rukmini Knowledge Park Karnataka Kattigenahalli Bengaluru India Tamilnadu Chennai India Department of Mechanical Engineering College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore India

In this experiment, high-temperature polyethylene terephthalate (PT) was mixed with epoxy resin (ER) that had been thinned with acetone. Sisal fibers were coated with the resulting product. Composites of Coated treated sisal fibre-reinforced PT (CTSF-PT) were made using a constant fiber loading of 10 wt% and processing temperatures of 230, 250, and 270ºC. The fibers were treated with NaOH. These composites were then characterized for thermal, mechanical and morphological performances. When comparing findings obtained at 250 and 270ºC, the optimal processing temperature was found to be 230ºC. This temperature resulted in the best thermal and mechanical properties, and excellent interfacial adhesion among the coated fibers and the PT. In comparison to the uncoated SF, the coated composites showed a 9.5% reduction in degradation onset temperature and a 13% improvement in decomposition temperature following resin coating, according to thermogravimetric analysis. The CSF-PT composites surpassed the uncoated composites by 2.18% and 2.8% in terms of glass transition (Tg) and melting temperature (Tm) measured by differential scanning calorimetry (DSC), with peak values at 122.2 °C and 265.1 °C, respectively. Coated Sisal-reinforced PT (CSF-PT) and coated-treated PT (CTSF-PT) composites outperformed raw Sisal (SF-PT) composites in terms of overall qualities and morphological properties, regardless of processing temperature. Applying resin to natural fibers enhances their heat resistance and the bond between the coated fibers and the plastic matrix, making them better suited for engineering plastic composites. Applications involving high temperatures, such as construction and automotive industries are well-suited to the resulting composites. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Automotive industry

来源：评论

学校读者我要写书评

暂无评论

Blockchain Interoperability for A Reputation-Based Drug Supply Chain Management 6

Blockchain Interoperability for A Reputation-Based Drug Supp...

引用

6th International Conference on Information systems and computer Networks, ISCON 2023

作者： Tanvir, Deluwar Hussen Amin, Ruhul Islam, Ashraful Islam, Mohammad Shamsul Rashid, Muhammed Mamunur Sylhet Engineering College Department of Computer Science and Engineering Sylhet Bangladesh Faridpur Engineering College Department of Computer Science and Engineering Faridpur Bangladesh System Analyst Investment Corporation of Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798350346961

The pharmaceutical drug industry faces considerable challenges in supply chain management, particularly in regard to tracking and tracing medications. Counterfeit drugs pose a significant global threat, and existing supply chain management practices often prove insufficient to prevent adulteration. Blockchain technology offers a potential solution to these issues by establishing a decentralized and distributed ecosystem where stakeholders can foster a trustworthy relationship. To address these limitations, we propose a blockchain-based system for tracking drugs in the supply chain, incorporating a reputation mechanism to ensure transparency and accountability among entities. To mitigate the interoperability challenges between blockchain networks, we implement inter-blockchain communication using the burn-to-claim protocol. Hyperledger Fabric is used as the primary blockchain because it ensures confidentiality between multiple organizations, and Quorum is the other blockchain. Our solution prioritizes trust, traceability, transparency, and accountability to deliver safe, authentic medication to consumers.. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

KENKO - an AI system to hold health records and assist individuals across cross domains 6

KENKO - an AI system to hold health records and assist indiv...

引用

6th International Conference on Recent Trends in Advance Computing, ICRTAC 2023

作者： Ignisha Rajathi, G. Sneharajalakshmi, P. Midhun Kumar, V.N. Vikash Kumar, S. Sri Krishna College of Engineering and Technology Department of Computer Science and Business System Coimbatore India

ISBN: (纸本)9798350394702

According to HCPro, an unfinished medical record signifies that the provided care was not comprehensive, showing gaps that indicate subpar clinical care and a failure to adhere to organizational policies. In addition, such incomplete records can be utilized as evidence to substantiate claims of negligence and allegations of fraudulent practices. In the fast-growing world of technology and great development of health sciences, we as common people have no independence to our health history. Imagine using regular insulin without realizing it might lead to heart complications due to sudden blood sugar spikes. Consider a scenario where you're involved in an accident, and the ER doctors are unaware of your penicillin allergy because your medical history is inaccessible. Picture a situation where your dermatologist prescribes new medications, but you're unaware of the potential risk of developing skin cancer. Envision the possibility of receiving urgent painkillers, only to discover that the dosage is actually excessive for your body. This is precisely where Kenkō steps in as a comprehensive solution for all your medical assistance requirements. © 2023 IEEE.

关键词： Image processing

来源：评论

学校读者我要写书评

暂无评论

A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

引用

computers, Materials & Continua 2023年第12期77卷 3969-3992页

作者： Naeem Ullah Javed Ali Khan Sultan Almakdi Mohammed S.Alshehri Mimonah Al Qathrady Eman Abdullah Aldakheel Doaa Sami Khafaga Department of Software Engineering University of Engineering and TechnologyTaxila4400Pakistan Department of Computer Science Faculty of PhysicsEngineeringand Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Departments of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tomato leaf diseases significantly impact crop production,necessitating early detection for sustainable *** Learning(DL)has recently shown excellent results in identifying and classifying tomato leaf ***,current DL methods often require substantial computational resources,hindering their application on resource-constrained *** propose the Deep Tomato Detection Network(DTomatoDNet),a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome *** Convn kernels used in the proposed(DTomatoDNet)framework is 1×1,which reduces the number of parameters and helps in more detailed and descriptive feature extraction for *** proposed DTomatoDNet model is trained from scratch to determine the classification success rate.10,000 tomato leaf images(1000 images per class)from the publicly accessible dataset,covering one healthy category and nine disease categories,are utilized in training the proposed DTomatoDNet *** specifically,we classified tomato leaf images into Target Spot(TS),Early Blight(EB),Late Blight(LB),Bacterial Spot(BS),Leaf Mold(LM),Tomato Yellow Leaf Curl Virus(YLCV),Septoria Leaf Spot(SLS),Spider Mites(SM),Tomato Mosaic Virus(MV),and Tomato Healthy(H).The proposed DTomatoDNet approach obtains a classification accuracy of 99.34%,demonstrating excellent accuracy in differentiating between tomato *** model could be used on mobile platforms because it is lightweight and designed with fewer *** farmers can utilize the proposed DTomatoDNet methodology to detect disease more quickly and easily once it has been integrated into mobile platforms by developing a mobile application.

关键词： CNN deep learning DTomatoDNet tomato leaf disease classification smart agriculture

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：