检索结果-内蒙古大学图书馆

2024 International Conference on Frontiers of Information technology, FIT 2024

作者： Murad, Nauman Ali Mir, Abinta Mehmood Shahzadi, Nazia Faculty of Computer Science Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Topi Pakistan

ISBN: (纸本)9798331510503

Glacial Lake Outburst Floods (GLOFs) pose a severe risk to populations in high-altitude areas, particularly in Pakistan's northern regions, where glacier melt has created 3,044 glacial lakes in Gilgit-Baltistan and Khyber Pakhtunkhwa [1]. The Chitral region is especially vulnerable, highlighting the need for robust monitoring and mitigation strategies. This paper focuses on using Deep Learning (DL) models for detecting and segmenting glacial lakes to mitigate GLOF risks. Using the Glacial Lakes Detection Dataset from High-Mountain Asia, covering 2080.12 km2 and including around 30,121 glacial lakes, we selected 1,200 cloud-free true-color images with ground truth masks. Our study evaluates DL models like DeepLabV3+, UNet, and YOLOv8 for lake segmentation and classification. Experimental results demonstrated model proficiency, with DeepLabV3+ (ResNet50 backbone and Dice loss function) achieving the highest IoU score of 77.2%. These findings highlight the potential of DL-based systems for enhanced GLOF monitoring and early warning. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Decoding Sentiments: A Comprehensive Exploration of Real-Time Emotion Recognition from Text Through Deep Learning 10

Decoding Sentiments: A Comprehensive Exploration of Real-Tim...

引用

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Sowmya, G. Akhilesh, R. Rohan, Aurangabadkar Rao, Garikapati Kausthub Nayak, Atul Kumar Midhilesh, Koppolu Computer Science Engineering Artificial intelligence and Machine learning Mlr Institute of Technology Hyderabad India

ISBN: (纸本)9798350384369

Emotional state of a person can be found out through various modalities such as using facial expressions, voice of the person, text and so on. Our study is solely based on the emotion extracted through the text. Past research focused on categorizing texts into sentiments like positive, negative, or neutral, our novel approach shifts to predicting specific emotional states like angry, sad or happy. Our study covers the previous researches done in this field which are ranging from deep learning models, natural language processing, and machine learning models. Recurrent neural networks and its variants are mainly studied for recognizing the emotion in text. The integration of emotion detection in the customer feedback enhances organizational insights, enabling proactive measures to elevate customer satisfaction. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Personal Finance Management and Prediction using ML Algorithms 8

Personal Finance Management and Prediction using ML Algorith...

引用

8th IEEE International Conference on Computational System and Information technology for Sustainable Solutions, CSITSS 2024

作者： Kaushik, Sujay G. Kashyap, Sumukha S. Surabhi, B.V. Chaitra, M. Reddy, Santhosh Anitha, N. Bnm Institute of Technology Affiliated to Vtu Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331505462

Effective personal finance management is essential for achieving financial stability and long-term financial health. This paper presents a comprehensive approach to summarizing, analyzing, and show monthly expenses using machine learning models. By collecting user inputs such as age, place of stay, number of dependents, monthly expenses on transport, education, subscriptions, savings, medical expenses, and more, the system uses linear regression, decision trees and random forest algorithms to predict financial values. The system provides detailed information of expenses, savings, and overall financial health, along with personal health analysis based on dietary habits. Users have access to a wide range of financial and lifestyle information, allowing the system to provide personalized recommendations to increase financial security and achieve financial goals. The model also evaluates the impact of recurring expenses and notable investments, helping users understand their spending patterns and make informed financial decisions. The results demonstrate the system's capability to deliver accurate predictions and actionable advice, enable users to better manage their finances. This approach has led to significant advances in personal financial management by integrating machine learning techniques to provide insight into people's financial health. © 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

Fine-tuning Llama-2-7b Model for Conversation Summarization 15

Fine-tuning Llama-2-7b Model for Conversation Summarization

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Nivethitha, V. Verma, Nirvik Bokadia, Ronit Jaju, Ronith Vellore Institute of Technology Chennai School of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350370249

In this research paper, we explore the optimization for conversation summarization of the Llama 2.7 b model by quantization-aware fine-tuning, specifically exploiting QLORA quantization techniques. In natural language processing (NLP), large language models (LLMs) have become powerful tools for various text-processing tasks including dialogue summarization in a rapidly evolving landscape. Still, the computational needs of these model's present obstacles to their practical implementation in conversational interfaces and live applications. Quantization observance fine-tuning is an optimistic way of compressing model parameters while still enhancing performance. This analysis demonstrates through rigorous experimentation that the QLORA quantization is effective on fine tuning the Llama 2.7b model for conversation summarization. Fine-tuning the model on a well-rounded dataset with conversational data derived from different sources such as social media, chat logs, and customer interactions makes it more adaptable to any sort of dialog that takes place. The incorporation of QLORA quantization's also improves the attention mechanism of the model enabling it to obtain relevant information such as generating concise summaries. The latest version of Llama is 2.7. It is called Llama 2.7b and provides several practical advantages for summarizing dialogues such as improved computational efficiency, better user experience in conversational interfaces, and capturing key insights from long conversations. Its outputs are in line with the current research on LLM-based conversation summarization and exhibit the viability of optimization techniques like quantization-aware fine-tuning to maximize the performance of large language models for particular natural language processing tasks (NLP). © 2024 IEEE.

关键词： llama 2 LLM Natural Language Processing QLORA Quantization

来源：评论

学校读者我要写书评

暂无评论

Emotion Classification to Augment the Emotional Intelligence of Autistic Individuals 5

Emotion Classification to Augment the Emotional Intelligence...

引用

5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Guruvammal, S. Kesavamoorthy, R. Anju, M.I. Chellatamilan, T. Jegatha Deborah, L. Jain University Dept. of Cse Kanakapura India Cmr Institute of Technology Dept. of Cse Bengaluru India Srm Institute of Science and Technology Dept. of Ece Chennai India Vellore Institute of Technology School of Computer Science and Engineering Vellore India University College of Engineering Computer Science and Engineering Tindivanam India

ISBN: (数字)9798350379884

ISBN: (纸本)9798350379884

The collaboration of machine learning (ML) algorithms and cognitive psychological frameworks supports the enhancement of emotional intelligence. In light of Plutchik's emotional wheel, this study investigates how to identify human emotions. By utilizing 24 different emotions, 8 high-intensive (secondary) emotions are identified. We employed 9 different classification algorithms K-nearest neighbors (KNN), decision trees (DT), naïve bayes (NB), support vector machine (SVM), Logistic regression, random forest (RF), artificial neural network (ANN), gradient boosting machines (GBM), and bagging classifier (BC) to identify the emotions accurately and the performance of them are compared. This research uses the labelled dataset consisting of 11 columns as similar word 1, similar word 2, typical sensation 1, typical sensation 2, opposite intensity low, opposite intensity medium, opposite intensity high, tells, helps, emotion and cluster. © 2024 IEEE.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

Development of Energy Efficient Routing Protocol using Genetic Algorithm for IoMT 3

Development of Energy Efficient Routing Protocol using Genet...

引用

3rd International Conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Jha, Rishabh Ranjan Singh, Manvendra Ansari, Md. Sarfaraj Alam Pal, Kunwar Govil, Mahesh Chandra National Institute of Technology Department of Computer Science and Engineering Sikkim India Dr B R Ambedkar National Institute of Technology Department of Computer Science and Engineering Jalandhar India

ISBN: (纸本)9798350300710

The Internet of Medical Things (IoMT) has evolved as a promising healthcare monitoring and management solution. However, the efficient management of IoMT sensor nodes' energy consumption, fault tolerance, and optimal routing of data packets are still challenging issues. We developed an Energy Efficient Routing Protocol using Genetic Algorithm (GA) with Dual Cluster Heads to address these challenges. IoMT sensor Nodes' energy factor and node-sink distance are considered as fitness parameters. The recommended protocol includes a dual cluster head mechanism that allocates two cluster heads to each cluster in order to ensure fault tolerance and load balancing. Additionally, the proposed GA-based optimisation method is used to improve the choice of cluster heads (CHs) based on the residual energy of the nodes and the distance to their sinks. The experimental simulation outcome is presented in the form of energy efficiency and network lifespan, and the suggested methodology outperforms the existing routing based methods. © 2023 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Developing a Smart Drip Infusion System to Elevate Precision in Healthcare 4

Developing a Smart Drip Infusion System to Elevate Precision...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Molefinyane, Sefemo Yahya, Abid Hamsadhwani, V. Rohini, R. Samikannu, Ravi Begam, K.Maruliya Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode India Saveetha School of Engineering Saveetha Institute of Medical and Technology Science Department of Computer Science and Communications Engineering Tiruchengode India

ISBN: (纸本)9798331529635

Intravenous (IV) therapy is a critical component of modern healthcare, yet traditional IV systems are prone to human errors, manual adjustments, and limited monitoring capabilities, which can jeopardize patient safety and hinder healthcare efficiency. This paper presents the development of the Smartdrip IV Infusion System, a sophisticated and automated solution that integrates advanced sensors, control algorithms, and intuitive user interfaces to address these limitations. The Smartdrip system minimizes human intervention, provides real-time monitoring, and automates fluid administration with enhanced precision and safety features. The system demonstrates high reliability through simulation and prototype testing in detecting anomalies, issuing alerts, and ensuring accurate infusion rates, thereby improving patient outcomes and reducing healthcare provider workload. The results validate the Smartdrip system as a transformative approach to optimizing IV therapy in diverse clinical settings. © 2024 IEEE.

关键词： Automated Infusion System Drip Rate Monitoring Healthcare Automation Intravenous Therapy Patient

来源：评论

学校读者我要写书评

暂无评论

A Design and Challenges in Energy Optimizing CR-Wireless Sensor Networks

引用

Recent Advances in computer science and Communications 2023年第5期16卷 82-92页

作者： Reddy, Pundru Chandra Shaker Sucharitha, Yadala School of Computing and Information Technology REVA University Karnataka Bengaluru India Department of Computer Science and Engineering CMR Institute of Technology TS Hyderabad India

Background: The progress of the Cognitive Radio-Wireless Sensor Network is being influenced by advancements in wireless sensor networks (WSNs), which significantly have unique features of cognitive radio technology (CR-WSN). Enhancing the network lifespan of any network requires better utilization of the available spectrum as well as the selection of a good routing mechanism for transmitting informational data to the base station from the sensor node without data conflict. Aims: Cognitive radio methods play a significant part in achieving this, and when paired with WSNs, the above-mentioned objectives can be met to a large extent. Methods: A unique energy-saving Distance-Based Multi-hop Clustering and Routing (DBMCR) methodology in association with spectrum allocation is proposed as a heterogeneous CR-WSN model. The supplied heterogeneous CR-wireless sensor networks are separated into areas and assigned a different spectrum depending on the distance. Information is sent over a multi-hop connection after dynamic clustering using distance computation. Results: The findings show that the suggested method achieves higher stability and ensures the energy-optimizing CR-WSN. The enhanced scalability can be seen in the First Node Death (FND). Additionally, the improved throughput helps to preserve the residual energy of the network which helps to address the issue of load balancing across nodes. Conclusion: Thus, the result acquired from the above findings shows that the proposed heterogeneous model achieves the enhanced network lifetime and ensures the energy optimizing CR-WSN. © 2023 Bentham science Publishers.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

A Novel Smartphone-Based Human Activity Recognition Using Deep Learning in Health care 3rd

A Novel Smartphone-Based Human Activity Recognition Using De...

引用

3rd International Conference on Machine Learning, Image Processing, Network Security and Data sciences, MIND 2021

作者： Soni, Vaibhav Yadav, Himanshu Semwal, Vijay Bhaskar Roy, Bholanath Choubey, Dilip Kumar Mallick, Dheeresh K. Department of Computer Science and Engineering Maulana Azad National Institute of Technology Madhya Pradesh Bhopal India Department of Computer Science and Engineering Indian Institute of Information Technology Bihar Bhagalpur India Department of Computer Science and Engineering Birla Institute of Technology Mesra Jharkhand Ranchi India

ISBN: (纸本)9789811958670

Nowadays, most smartphones feature a number of strong sensors, such as direction, network, location, and motion sensors. Motion and inertial sensors (i.e., accelerometer, gyroscope, etc.) are particularly popular in human activity recognition (HAR) for detecting human physical activity which helps in many research areas of the Internet of healthcare things (IoHT) including several patient’s diseases such as Parkinson, obesity, cardiovascular, and diabetes. Deep learning (DL) techniques have been increasingly popular over the years as a result of their significant outcomes. The use of deep learning techniques to recognize human physical activity in wearable and mobile sensor situations has also gotten a lot of attention from around the world. In this paper, a deep neural network (DNN) combining bidirectional long short-term memory (Bi-LSTM) and convolutional neural network (CNN) is proposed. The performance of the model has been evaluated on two publicly available datasets: WISDM and UCI-HAR. The model has achieved 97.96 and 97.15% accuracy for the WISDM and UCI-HAR, respectively. Moreover, the simulation results show the effectiveness of the proposed work compared to other state-of-the-art methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Skillify: Enhanced Learning Management System Using Generative AI 7

Skillify: Enhanced Learning Management System Using Generati...

引用

7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Dhairya Hrishikesh, Jeeri Sonu, Gollapalli Persis Vaishnavi, Dandla Sanapala, Srinuvasarao Pallavi, L. B V Raju Institute of Technology Department of Computer Science and Engineering Telangana Narsapur India

ISBN: (纸本)9798350372816

Traditionally, students faced challenges in acquiring knowledge from textbooks due to difficulties in access and the high cost associated with them. Online learning aims to overcome these hurdles by providing a digital alternative that is accessible to everyone. Students can overcome geographical obstacles by using online platforms, gaining access to a wealth of instructional resources. This digital paradigm shift seeks to democratize education by making it more equitable and inclusive. However, the accessibility of online learning remains a significant challenge, especially for those who are visually impaired. Additionally, the vast number of courses offered on online platforms can make it challenging for learners to select the right course that can advance their careers. Learners often struggle to identify the best courses to improve their skills. To overcome accessibility challenges for the visually impaired, our platform incorporates a text-to-speech feature, which converts written text into spoken words. To address the problem of choosing the right course, we are implementing a course recommendation system to enable learners to acquire new skills that are beneficial to their advancement. Our platform encompasses three distinct modules: user, professor, and admin. Each module serves a specific role within our system. This project exemplifies the potential of artificial intelligence in revolutionizing education through enhanced learning experiences. Our proposed model aims to improve the efficiency of existing models by implementing text-to-speech and course recommendation features. © 2024 IEEE.

关键词： Contrastive Learning

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：