检索结果-内蒙古大学图书馆

Electrical Power engineering, Communication and computing Technology(ODICON), Odisha International Conference on

作者： A Padmavathi Laxmi Maurya Gauri Santhosh G Charan Reddy Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798350354379

ISBN: (纸本)9798350354386

The agriculture sector of our country has been an important part of economic activity for a long time. Rather than the increasing demand shown by population growth, profitability remains difficult. This paper introduces an approach aimed at fixing agricultural marketing networks through the integration of blockchain technology. The proposed method uses blockchain to virtualize products and carbon offset certificates, providing a way for agricultural producers to mitigate carbon emissions and point out environmental concerns. With the help of the blockchain in this context, carbon offset credits can be securely tracked, traded, and utilized to promote sustainability practices. This innovative and new integration promises to revolutionize current agricultural product marketing methods, along with promoting environmental sustainability and empowering consumers with comprehensive information about the environmental footprint of their purchases.

关键词： computers Visualization Power engineering Profitability Green products Carbon dioxide Agricultural products Blockchains Sustainable development Carbon

来源：评论

学校读者我要写书评

暂无评论

Wearable Security-Authentication using Smartwatches

Wearable Security-Authentication using Smartwatches

引用

Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Sanyam Bhardwaj R Dhaksana Katari Amrutha Varshini N Harini Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9798350371314

ISBN: (纸本)9798350371321

Multi-factor authentication has become a widely employed method for verifying users and safeguarding sensitive information. This approach typically combines a password with an additional authentication factor, such as something the user knows, possesses, or uniquely possesses (e.g., fingerprint or iris recognition). This paper introduces a novel method to augment user authentication by integrating smart- watches/fitness bands, categorizing it under the category of the user possessions within multi-factor authentication (MFA). A noteworthy aspect of this approach is its ability to enhance the authentication process without the additional need of finances. The results from the prototype and survey revealed that most of the users find this type of scheme to be comfortable and reliable. The challenges from the user and the service provider perspective have been thoroughly reviewed for the proposed method and found to be usable while still enhancing security.

关键词： Surveys Multi-factor authentication Costs Prototypes Passwords Fingerprint recognition Reliability

来源：评论

学校读者我要写书评

暂无评论

Deep Emotion Analysis: “Enhancing Emotion classification with Transformer Model”

Deep Emotion Analysis: “Enhancing Emotion classification wi...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： P Mokshit P Syam Prasad N Sumanth Reddy Tripty Singh Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In the era of digital technology, it becomes very critical to perceive human emotions in textual data from the point of view of many applications - sentiment analysis, mental health monitoring and user experience optimization. The investigation is on the incorporation of transformer-based models and ML techniques in order to enhance the accuracy for emotion classification. This work employs a variant of Bidirectional Encoder Representations from Transformers (BERT) that is able to preserve complex linguistic constructs and contexts. Along with this, logistic regression, decision tree, support vector machine (SVM), random forest, and gradient boosting algorithms are utilized to classify emotional aspects which are then compared for their accuracy in expressing subtleties present in text data. Fundamentally, eXplainable AI (XAI) tools such as ELI5 for random forest and LIME for BERT are employed to improve the interpretability and transparency of the emotion categorization process. These XAI tools enable users to see the feature importance and decision-making process of the model which helps in improving their understanding of the critical features that influence emotion classification. This work proposes the integration of transformer models and traditional machine learning algorithms with explanation of sentiments (XAI) to boost text-based emotion analysis.

关键词： Support vector machines Analytical models Logistic regression Accuracy Bidirectional control Transformers Encoding Data models Decision trees Random forests

来源：评论

学校读者我要写书评

暂无评论

Advancing Climate Change Forecasting: LSTM-based Earth Surface Temperature Prediction Across 88 Global Cities

Advancing Climate Change Forecasting: LSTM-based Earth Surfa...

引用

BIT Conference (BITCON), International

作者： Rekha R Nair Ebin P M Tina Babu Department of Computer Science and Engineering Alliance School of Advanced Computing Alliance University Bengaluru India

ISBN: (数字)9798331518394

ISBN: (纸本)9798331518400

Global climate change, manifested through increasing wild fires, rising sea levels, and species extinction, primarily stems from rising global temperatures. Hence proposed a study on predicting Earth surface temperatures using Long Short-Term Memory (LSTM) networks. The proposed model provided a powerful tool for temperature forecasting, crucial for potentially saving lives and preserving vegetation. The LSTM model demonstrated superior predictive capabilities for temperature forecasting when compared to the Decision Tree Regression approach. This study contributes significantly to climate modeling knowledge, providing a valuable resource for scientists and policymakers. The global warming doesn’t manifest uniformly, the proposed research utilizes a comprehensive dataset spanning 25 years (1995-2020) across 88 global cities. According to the suggested LSTM, there was 99 percent of validity which can be interpreted from these precautions taken in the stock analysis. 18% accuracy with low error rates (RMSE: 3. 76 K, Mean Absolute Error: 2. 971 K, Mean Absolute Percentage Error: 5. 676. The proposed work helps to improve climate predictions and, thus, aids decision-making of mitigation and adaptation to climate change.

关键词： Earth Sea surface Wildfires Urban areas Predictive models Forecasting Ocean temperature Long short term memory Regression tree analysis Meteorology Surface treatment Regression analysis Climate change

来源：评论

学校读者我要写书评

暂无评论

Secure ML Based Image Encryption Framework with Recursive Splitting and Linear Feedback Shift Register

Secure ML Based Image Encryption Framework with Recursive Sp...

引用

International Conference on Circuits, Communication, Control and computing

作者： Bandaru Rohan Satya Balaji Alluri Jayanth Varma K Ashwini Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amrita School of Computing Chennai India

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528546

With the development of advanced communication ensuring the secure transmission of images has become more and more important. This research suggests a novel approach for digital image encryption and decryption that combines Linear Feedback Shift Register (LFSR) encryption, recursive image splitting and shuffling in order to increase security. Test image is divided into blocks and each block is encrypted using a different LFSR key. The encrypted blocks are then joined to create a single encrypted image that is ready to be sent. The receiver uses a machine learning model that has been pre-trained to identify the specific LFSR key used for each block after breaking the image back up into its component blocks. This allows for precise decryption. The viability of the encryption process is assessed using entropy analysis, histogram comparison and pixel relationship etc. The results show that the encrypted images have a notable disruption of spatial relationships, a high degree of unpredictability, and significant interference with spatial relations. Furthermore, evaluation is done on the performance of multiple Support Vector Machine (SVM) models with different kernel functions. The results indicate that the SVM with a radial basis function (RBF) kernel performs best in terms of key identification accuracy. This thorough analysis demonstrates the suggested encryption method's resilience and its potential for safe image transfer across a range of applications.

关键词： Support vector machines Histograms Linear feedback shift registers Receivers Machine learning Interference Entropy Encryption Kernel Resilience

来源：评论

学校读者我要写书评

暂无评论

Tri-Model Synergy: Redefining Depression Detection through the Convergence of ANN, CNN, and SVM

Tri-Model Synergy: Redefining Depression Detection through t...

引用

Smart Electronics and Communication (ICOSEC), International Conference on

作者： Angelina George Achal Baniya Alphonsa Jose K Dinesh Kumar Department of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Depression being a universal mental health challenge that affects millions globally, necessitating reliable detection methods in order to aid in timely intervention. Like physical health, mental health is not to be ignored. This study presents a novel hybrid model that combines Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Support Vector Machines (SVM) to analyze and detect depression in individuals. The hybrid model achieved a training accuracy of $\mathbf{9 5 . 6 \%}$ and a test accuracy of $\mathbf{9 1 . 2 \%}$, demonstrating its robustness and reliability. The total training time was recorded at 3.01 seconds, with ANN contributing 1.11 seconds and CNN contributing 1.9 seconds. Furthermore, the model’s performance metrics included an F1-Score of 0.91 and 0.91 for detecting the classes of absence and presence of depression respectively, highlighting its effectiveness in correctly identifying depressive states. This hybrid approach provides a comprehensive analysis by leveraging the strengths of each individual model, paving the way for more reliable and scalable mental health assessment tools.

关键词： Support vector machines Training Measurement Analytical models Accuracy Mental health Depression Robustness Convolutional neural networks Synthetic data

来源：评论

学校读者我要写书评

暂无评论

Real-Time Object Detection using Mobile Robot Captured Images: A Deep Learning Approach

Real-Time Object Detection using Mobile Robot Captured Image...

引用

Innovation in Technology (INOCON), IEEE International Conference for

作者： Hema Srivarshini Ch N Preeti Sreekar Praneeth Marri Suja Palaniswamy Peeta Basa Pati Department of Computer Science & Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

Robots are becoming more and more prevalent in a variety of industries, such as transportation, agriculture, healthcare, and so forth. Deep learning is an area of study that is rapidly expanding and is applied in many fields including robots. For a robot to understand its environment and carry out tasks, object recognition is essential. This paper proposes a deep learning method that leverages both pre-existing data and real-time data for robotic object recognition which will enable robots to operate in challenging conditions. Using real-time data, CNN with decision tree is tested after being trained on both pre-existing and real-time data which yields 96% accuracy. A model has been created for reliable and accurate object recognition for robots.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Review and Bibliometric Analysis of the Current Studies for the 6G Networks

引用

computer Modeling in engineering & sciences 2024年第9期140卷 2165-2206页

作者： Qusay M.Salih Md.Arafatur Rahman Ahmad Firdaus Mohammed Rajih Jassim Hasan Kahtan Jasni Mohamad Zain Ahmed Hussein Ali Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)PekanPahang26600Malaysia Department of Medical Equipment Technology Engineering Al Salam University CollegeBaghdadIraq School of Mathematics and Computer Science University of WolverhamptonWolverhampton01902UK Department of Production Engineering and Metallurgy University of TechnologyBaghdadIraq Cardiff School of Technologies Cardiff Metropolitan UniversityCardiffCF52YBUK Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Kompleks Al-KhawarizmiUniversiti Teknologi MARAShah AlamSelangor40450Malaysia Department Computer Science Al-Salam University CollegeBaghdadIraq

The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already *** realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ***,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G ***,this study aims to review,examine,and summarize existing studies and research activities in *** study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and ***,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of *** study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.

关键词： 6G bibliometric wireless networks review

来源：评论

学校读者我要写书评

暂无评论

Homomorphic Encryption for Secure Data Analysis: A Hybrid Approach using PKCS1_OAEP Padding

Homomorphic Encryption for Secure Data Analysis: A Hybrid Ap...

引用

Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Shanmukha Aditya G Kruthika B Shinu M. Rajagopal C. R. Kavitha Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

In today's data-driven world, striking a balance between data utility and privacy is paramount. Homomorphic encryption, a revolutionary cryptographic technique, facilitates computations on encrypted data without decryption. This study addresses the growing demand for secure data analysis, emphasizing the seamless integration of homomorphic encryption in connecting robust data analysis with essential privacy safeguards. Serving as a vital component in this context, this cutting-edge technique proves pivotal in fostering a secure, privacy-centric approach to data analytics. The outcomes underscore its significance, representing a substantial stride towards the evolution of a conscientious and responsible data-driven ecosystem. The achieved results signal progress in harmonizing data utility and privacy, enhancing overall security and ethical data practices without compromising analytical capabilities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Homomorphic Encryption Compiler for Blood Pressure Analysis

A Homomorphic Encryption Compiler for Blood Pressure Analysi...

引用

Electrical, Electronics, Information and Communication Technologies (ICEEICT), International Conference on

作者： Varshini Balaji Srinidhi Kannan Suryamritha M Meena Belwal Department of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369090

The growing concern for data privacy, particularly in the medical domain, underscores the necessity of encrypting sensitive medical information to prevent unauthorized access and misuse. Homomorphic Encryption (HE) proposes a solution by enabling computations on encrypted data without decryption, ensuring privacy while allowing for meaningful analysis. In this paper, we propose a framework for securely calculating the mean blood pressure (MBP) and categorizing the patient’s BP level, a critical health indicator, using the Paillier cryptosystem. The framework includes components such as a lexer for tokenizing medical text, a parser for examining tokens, and the implementation of Paillier encryption for secure computation. Through encryption, computation, and subsequent decryption, the MBP and the BP levels are derived without compromising data privacy.

关键词： Data privacy Blood pressure Information and communication technology Homomorphic encryption Blood

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：