检索结果-内蒙古大学图书馆

5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Surya, M. Manohar, S. Srm Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385649

An entire country's economy, population security, nutrition, and health all depend on its agricultural productivity. In an effort to increase agricultural output, farmers have been adopting new technologies like blockchain and the Internet of Things in recent years. Blockchain has been used to address issues in a variety of industries. Blockchain is being used in agriculture to speed up transaction times and improve food safety. The complex mechanism that keeps agricultural products moving throughout the market is called an agricultural supply chain. Agricultural commercial resources play a crucial role in meeting the demand for agricultural products and preserving their quality and safety as they transport agricultural items across the market. Many existing methods have explored the use of blockchains in the supply chain, although they are unable to enhance the process's overall efficiency. An efficient crop yield prediction and demand prediction system is proposed with secure block chain technology. The proposed system has the following three phases: 1) crop yield prediction system;2) supply chain process with blockchain;and 3) demand prediction system. The first phase consists of the following steps: dataset collection, preprocessing, feature extraction, feature selection, and training. In the second phase, farmers, distributors, retailers, and consumers are involved. Finally, for demand prediction, pre-processing, feature extraction, feature reduction, and prediction are carried out. All three phases are linked to a blockchain and securely stored in the cloud. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Magnesium-incorporated biocomposite scaffolds:A novel frontier in bone tissue engineering

引用

Journal of Magnesium and Alloys 2024年第6期12卷 2231-2248页

作者： Abinaya Shanmugavadivu Sundaravadhanan Lekhavadhani Sushma Babu Nivetha Suresh Nagarajan Selvamurugan Department of Biotechnology School of BioengineeringCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia

Nonunion represents a crucial challenge in orthopedic medicine,demanding innovative solutions beyond the scope of traditional bone grafting *** the various strategies available,magnesium(Mg)implants have been recognized for their biocompatibility and ***,their susceptibility to rapid corrosion and degradation has garnered notable research interest in bone tissue engineering(BTE),particularly in the development of Mg-incorporated biocomposite *** scaffolds gradually release Mg2+,which enhances immunomodulation,osteogenesis,and angiogenesis,thus facilitating effective bone *** review presents myriad fabrication techniques used to create Mg-incorporated biocomposite scaffolds,including electrospinning,three-dimensional printing,and sol-gel *** these advancements,the application of Mg-incorporated biocomposite scaffolds faces challenges such as controlling the degradation rate of Mg and ensuring mechanical *** limitations highlight the necessity for ongoing research aimed at refining fabrication techniques to better regulate the physicochemical and osteogenic properties of *** review provides insights into the potential of Mg-incorporated biocomposite scaffolds for BTE and the challenges that need to be addressed for their successful translation into clinical applications.

关键词： Magnesium Bone tissue engineering Immunomodulation Osteogenesis Angiogenesis

来源：评论

学校读者我要写书评

暂无评论

Alzheimer's Disease Prediction using an Artificial Butterfly Optimizer with a Two-Layer CNN Approach 4

Alzheimer's Disease Prediction using an Artificial Butterfly...

引用

4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Jevin, J.A. Umamageswari, A. Srm Institute of Science & Technology Department of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350352931

Alzheimer's disease, the most common dementia, involves brain damage. Alzheimer's starts with mild symptoms and worsens over time, making it difficult to treat. Early detection can prevent disease progression or reduce symptoms before major impairment. This study uses multiple stages to detect Alzheimer's early. Model training, feature selection, and thorough data preprocessing are system essentials. Data scaling, missing value imputation, and outlier treatment prepared the clinical dataset. Information gain, correlation coefficient, and chi-square were used to choose Alzheimer's disease predictors. The model was trained on hundreds of clinical samples. The ABO-2layer CNN architecture achieved a maximum prediction accuracy of 94.56%, indicating that preprocessing and feature selection improve model performance. The high anticipated accuracy showed the significance of Alzheimer's disease early detection methods. This study improves feature selection and uses advanced CNN architectures to create tools that may help diagnose Alzheimer's early, one way to battle neurodegenerative diseases. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Effect of MHD on Porous Circular Stepped Plate Lubricated With Micropolar Fluid

引用

IAENG International Journal of Applied Mathematics 2024年第9期54卷 1847-1854页

作者： Johny, A. Sujatha, E. Sree, M. Geetha Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India

An analysis is made on the effect of magneto hydrodynamics on poro-circular stepped plates lubricated with micropolar fluid. The modified Reynold’s equation leads to the development of a closed form expression for pressure, load sustaining capacity, and squeezing time. The impact of porosity is analyzed using the modified Darcy’s equation, and the outcomes are compared with the cases of the presence and absence of porosity on the same circular stepped plate. The external magnetic field influences the bearing’s efficiency by increasing the pressure, load sustaining capacity, and squeezing time performance. In the presence of porosity, the pressure, load sustaining capacity and squeezing time decrease compared to the absence of porosity, and the comparisons are shown in the tables. The variation of the highly influenced parameter of the bearing system is represented graphically. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Porosity

来源：评论

学校读者我要写书评

暂无评论

DDoS and Botnet Attacks: A Survey of Detection and Prevention Techniques

DDoS and Botnet Attacks: A Survey of Detection and Preventio...

引用

2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Pranav, S.A. Sathya Priya, S. HariHaran, B. Srm Institute Of Science And Technology Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

The Internet of Things (IoT) heralds a innovative generation in communication via enabling regular gadgets to supply, receive, and percentage records easily. IoT applications, which prioritise venture automation, aim to present inanimate items autonomy;they promise increased consolation, productivity, and automation. However, strong safety, privateness, authentication, and recuperation methods are required to understand this goal. In order to assemble give up-to-quit secure IoT environments, this newsletter meticulously evaluations the security troubles and risks inherent to IoT applications. It emphasises the vital necessity for architectural *** paper starts by conducting an examination of security worries before exploring emerging and advanced technologies aimed at nurturing a sense of trust, in Internet of Things (IoT) applications. The primary focus of the discussion revolves around how these technologies aid in overcoming security challenges and fostering an ecosystem for IoT. © 2024 IEEE.

关键词： Botnet

来源：评论

学校读者我要写书评

暂无评论

Generative AI: A Transformative Force in Business Intelligence 2

Generative AI: A Transformative Force in Business Intelligen...

引用

2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Thiruneelakandan, A. Umamageswari, A. SRM Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350327533

In an era where data is the cornerstone of strategic decision-making, Generative Artificial Intelligence (Gen AI) is revolutionizing the Business Intelligence (BI) landscape. This study investigates the multifaceted role of Generative AI in BI, encompassing data generation and augmentation, predictive analytics, reporting automation, product and service innovation, and personalization of customer experiences. The work employs a combination of synthetic data generated by Generative Adversarial Networks (GANs) and Seasonal Autoregressive Integrated Moving Average (SARIMA) predictive modeling techniques to demonstrate the potent capabilities of Generative AI in enhancing data-driven insights. The findings reveal that Generative AI not only significantly improves the accuracy of predictive models, especially in scenarios with limited historical data but also streamlines reporting processes and catalyzes innovation by uncovering latent customer needs. The research underscores the transformative impact of Generative AI in BI, while also addressing the attendant ethical considerations and the necessity for rigorous data governance. Through this exploration, the study provides a roadmap for businesses to harness the power of Generative AI, paving the way for smarter, more agile, and more personalized business strategies. © 2024 IEEE.

关键词： Data Augmentation Ethical Artificial Intelligence Generative Adversarial Networks Generative Artificial Intelligence Reporting Automation

来源：评论

学校读者我要写书评

暂无评论

Detecting Mental Stress Using K-NN Classifier and IoT Devices 11th

Detecting Mental Stress Using K-NN Classifier and IoT Device...

引用

11th International Conference on Intelligent Computing and Applications, ICRTC 2023

作者： Prabu Shankar, K.C. Hema, M. Computer Science and Engineering SRM Institute of Science & Technology Kattankulathur Chennai India

ISBN: (纸本)9789819717231

Mental tension has become a constant in the fast-paced world of today. It is a problem that keeps getting worse and, if left unchecked, could have serious health effects. Consequently, it is of highest importance to detect stress in individuals to prevent any detrimental results. With its sophisticated algorithms and skills, machine learning can be essential in solving this problem. In this study, a theoretical framework for stress detection using wearable technology with machine learning algorithms and other cutting-edge features is proposed. Heart rate variability (HRV) and speech emotion recognition (SER), two crucial modules that help identify stress in people, are implemented in the proposed system. The SER module detects the emotions in speech, whereas the HRV module examines fluctuations in heart rate. It is anticipated that the suggested system will offer a precise and trustworthy stress detection method, opening the door to better health results. HRV for short is a method to help identifying stress. Many machine learning classification techniques, including logistic regression, k-nearest neighbors, random forest classifier, decision tree classifier, and neural network classifier (NNC), are used to create this particular module. The k-NN model outperformed the other algorithms, scoring a 99.7% accuracy rate. The Python programming language was chosen because of its abundance of libraries and header files to make implementation easier. Streamlit, an open-source app framework used in the domains of machine learning and data science for developing apps connected to ML modules, was used to deploy the HRV module locally. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Node Deployment Strategies and Challenges in Underwater Wireless Sensor Network 5

Node Deployment Strategies and Challenges in Underwater Wire...

引用

5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024

作者： Layolin Benisto, L.C. Sukumaran, Rajeev Agnel Shyam kumar, C. SRM Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur India

ISBN: (纸本)9798350395235

Underwater Wireless Sensor Networks (UWSNs) are gaining importance for a wide range of applications, from environmental monitoring to underwater exploration. However, the challenging underwater environment poses significant obstacles to reliable data transmission. This study focuses on the role of deployment nodes in UWSNs, addressing the need for extended communication range, signal amplification, and data reliability. The study presents an in-depth exploration of node deployment, communication protocols, and the unique challenges faced in underwater environments. By strategically placing and managing nodes, UWSNs can overcome these challenges and improve overall network performance. UWSNs integrate a number of critical deployment strategies designed for land-based sensor networks. However, because to the unique 3-D properties of UWSNs, not all of these methodologies are immediately relevant. Underwater networks function in three dimensions, posing additional issues such as sensor node mobility driven by water currents and significant communication delays. The goal of this research is to look at various node deployment methodologies in order to shed light on the difficulty of sensor node deployment. The study intends to investigate various node deployment strategies in order to shed light on the complexities of sensor node deployment in UWSNs. Furthermore, the research performs an exhaustive literature analysis on node deployment, diving into difficulties and obstacles faced during deployment, and extensively analyzing the performance of various node deployment approaches. This research provides useful insights for optimizing node deployment in UWSNs, opening the path for increased communication efficiency in the difficult underwater realm. © 2024 IEEE.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

COVID-19 Diagnosis through Chest X-Ray Images Leveraging VGG16 Architecture 1

COVID-19 Diagnosis through Chest X-Ray Images Leveraging VGG...

引用

1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Sharma, Shiwanki Singh, Abhilasha Srm Institute of Science & Technology Department of Computer Science & Engineering Ghaziabad India

ISBN: (纸本)9798350367720

The ongoing COVID-19 pandemic has demanded developing efficient and reliable diagnostic tools to combat the virus's dissemination. In this paper, we have put forward a novel approach based on deep learning for the automated recognition of COVID-19 from chest X-ray images, based on the VGG16 architecture. Utilizing a dataset containing X-ray images of the chest of people who are both COVID-19 positive as well as negative, we trained and evaluated the VGG16 model for its diagnostic performance. Through rigorous experimentation and validation, this proposed model has achieved an remarkable accuracy of 98.2%, demonstrating its worth in effectively differentiating between COVID-19 and non-COVID-19 patients. Furthermore, we conducted extensive comparative analyses with existing approaches, showcasing the superiority of our suggested model in terms of computing efficiency and accuracy. Achieved results highlight the prospective of methodologies based on deep learning, particularly the VGG16 model, as a valuable tool when combating the COVID-19 epidemic, offering rapid and reliable diagnosis to aid in effective patient management and community wellbeing interventions, and the precision, recall, and F1 score of the suggested model yield positive values of 0.98, 0.98, and 0.98. © 2024 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Enhanced Genomic Prediction for Maize Breeding Using Deep Learning and K-mer-based Sequence Encoding 5

Enhanced Genomic Prediction for Maize Breeding Using Deep Le...

引用

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Kudiyarasudevi, C. Suresh, S. SRM Institute of Science and Technology Department of Computer Science and Engineering Ramapuram India

ISBN: (纸本)9798331518097

Maize (Zea mays L.) plays a pivotal role in global food security due to its substantial economic and nutritional value. With advancements in agricultural technologies, crop yields have surged, but challenges remain in optimizing maize breeding for even higher productivity. This research explores cutting-edge approaches in maize breeding, focusing on novel genomic prediction tools that enhance crop yield. While numerous studies have demonstrated the potential of genomic prediction in accelerating maize yields, current models often suffer from suboptimal data quality and lengthy processing times due to the use of raw data for genotype prediction. To address these challenges, this study introduces a deep learning- based model that leverages polymorphism data, employs k-mer methods to shorten sequences, and applies one-hot encoding for preprocessing. This data is then processed by a convolutional neural network (CNN) to predict genotypes efficiently. The proposed model aims to achieve a 98% accuracy in genomic prediction, outperforming existing models in both speed and accuracy, thereby contributing to the generation of superior maize traits. © 2024 IEEE.

关键词： Prediction models

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：