检索结果-内蒙古大学图书馆

Intelligent Control, Computing and Communications (IC3), International Conference on

作者： Unni Krishnn A Amit Dutt Jay Singh Munugapati Bhavana Swathi Baswaraju Baydaa Fathil Mohammed Akila Venkatraman Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Lovely Professional University Phagwara India Dept. of EEE GL Bajaj Institute of Technology and Management Gr. Noida U.P. India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Department of Computer Science-Data Science New Horizon College of Engineering Bangalore India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of Information Technology GRIET Bachupally Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

The fast expansion of population worldwide and urbanisation had been estimated to have 80 % of the population in urban areas in the upcoming 50 years leads to an exponential rise in demand of food. These needs provide an urgent call for developing novel approaches to achieve global food demands amid sustainability problems. Urban Vertical Farming (UVF) offers an attractive solution for growing crops in the vertical dimension of structures, the urban skyscrapers, where land use is limited. However, it is fairly limited research which applies the current state of art in cutting edge technologies such as the Internet of Things, to try to automate and monitor farm processing. Thus, in this review paper, gaps in existing research, the potential for IoT enabled vertical farming, as well as challenges such as energy use, economic feasibility and urban policy integration are examined. Vertical farming can be enhanced through resource efficiency, scalability and level of sustainability through the use of IoT systems and AI driven data analytics which will also help promote urban food security. The research gives a summary of the current state, technological capabilities, and potential way forward in the process of successful vertical farming implementation in urban sets.

关键词： Temperature sensors Food manufacturing Urban areas Urban policy Food security Sustainable development Artificial intelligence Monitoring Water resources Farming

来源：评论

学校读者我要写书评

暂无评论

RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using Weighted and Majority Voted Fine-Tuned Transformers 1

RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using ...

引用

1st Workshop on Bangla Language Processing, BLP 2023

作者： Seth, Pratinav Goel, Rashi Mathur, Komal Vemulapalli, Swetha Dept. of Data Science & Computer Applications Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Dept. of Computer Science & Engineering Dept. of Information and Communication Technology

ISBN: (纸本)9798891760585

This paper describes our approach to submissions made at Shared Task 2 at BLP Workshop - Sentiment Analysis of Bangla Social Media Posts(Hasan et al., 2023a;Islam et al., 2021;Hasan et al., 2023b). Sentiment Analysis is an action research area in the digital age. With the rapid and constant growth of online social media sites and services and the increasing amount of textual data, the application of automatic Sentiment Analysis is on the rise. However, most of the research in this domain is based on the English language. Despite being the world’s sixth most widely spoken language, little work has been done in Bangla. This task aims to promote work on Bangla Sentiment Analysis while identifying the polarity of social media content by determining whether the sentiment expressed in the text is Positive, Negative, or Neutral. Our approach consists of experimenting and finetuning various multilingual and pre-trained BERT-based models on our downstream tasks and using a Majority Voting and Weighted ensemble model that outperforms individual baseline model scores. Our system scored 0.711 for the multiclass classification task and scored 10th place among the participants on the leaderboard for the shared task. Our code is available at https://***/ptnv-s/RSM-NLP-BLP-Task2. © 2023 Association for Computational Linguistics.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

HGP-NLP at BioLaySumm: Leveraging LoRA for Lay Summarization of Biomedical Research Articles using Seq2Seq Transformers 23

HGP-NLP at BioLaySumm: Leveraging LoRA for Lay Summarization...

引用

23rd Meeting of the ACL Special Interest Group on Biomedical Natural Language Processing, BioNLP 2024

作者： Malik, Hemang Pradeep, Gaurav Seth, Pratinav Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Dept. of Data Science & Computer Applications India Dept. of Computer Science & Engineering India

ISBN: (纸本)9798891761308

Lay summarization aims to generate summaries of technical articles for non-experts, enabling easy comprehension for a general audience. The technical language used in research often hinders effective communication of scientific knowledge, making it difficult for non-experts to understand. Automatic lay summarization can enhance access to scientific literature, promoting interdisciplinary knowledge sharing and public understanding. This has become especially important for biomedical articles, given the current global need for clear medical information. Large Language Models (LLMs) (Yao et al., 2024), with their remarkable language understanding capabilities, are ideal for abstractive summarization, helping to make complex information accessible to the public. This paper details our submissions to the BioLaySumm 2024 Shared Task: Lay Summarization of Biomedical Research Articles (Goldsack et al., 2024). We fine-tune and evaluate sequence-to-sequence models like T5 across various training dataset settings and optimization methods such as LoRA (Hu et al., 2021b) for lay summarization. Our submission achieved the 53rd position overall.. ©2024 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

A Multi-Layered Quantum-Resistant Algorithms Based Approach to Mitigate Emerging Threats in ISP Cybersecurity 3

A Multi-Layered Quantum-Resistant Algorithms Based Approach ...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Alagh, Arjun Wason, Ritika Arora, Parul Dept. of Computer Science and Applications Delhi India

ISBN: (纸本)9798331518592

The Internet Service Providers (ISP), and their structures are at high risk with the growing quantity and complexity of cyber threats. The growth of quantum computing further elevates the risks and challenges especially for the conventional cryptographic standards. This manuscript proposes a multi-layered suite of quantum-resistant cryptographic algorithms that can be proficiently integrated into ISP networks to secure against conventional cyber threats as well as prevent the impending quantum-enabled cyberattacks. This work emphasizes the importance of transitioning to quantum-resistant cryptography to ensure the longevity of ISP cybersecurity measures in the face of emerging quantum threats. © 2024 IEEE.

关键词： Encryption algorithms

来源：评论

学校读者我要写书评

暂无评论

TEST-Web: An Automated Web Application Testing Tool for Enhanced Efficiency and Consistency 3

TEST-Web: An Automated Web Application Testing Tool for Enha...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Verma, Ishaan Wason, Ritika Arora, Parul Dept. of Computer Science and Applications Delhi India

ISBN: (纸本)9798331518592

This manuscript specifies the development of TEST-Web an automated testing tool projected to evolve the efficacy and reliability of web application testing process. Using the Selenium WebDriver and the TestNG framework, TEST-Web restructures the testing process by automating repetitive and comprehensive testing in large organizations. The tool generates detailed reports, providing valued visions into application performance and functionality. TEST-Web development follows an iterative approach, beginning with prototype development and then expanding functionality through user feedback. This work aims to achieve a user-friendly and robust solution for enhancing the accuracy, speed, and reliability of web application testing processes. © 2024 IEEE.

关键词： Automated Testing Tool Software Testing TestNG Web Application Testing

来源：评论

学校读者我要写书评

暂无评论

Performance Evaluation of Multi-Disease Classification and Recommendation Models 3

Performance Evaluation of Multi-Disease Classification and R...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Singh, Lakhvinder Dalip Dept. of Computer Science & Applications Ambala India

ISBN: (纸本)9798331518592

This paper aims to review the current advances in healthcare uses of machine learning (ML) for the diagnosis of numerous diseases using different classification models. It proposes an efficient mechanism for multi-disease diagnosis by implementing the Bee-Featured Convolutional Neural Network (BFCNN), coupled with a Hybrid Statistical Fuzzy (Hybrid S-Fuzzy) scheme, to improve classification efficiency. The primary goal is to develop an accurate diagnostic system for heart, kidney, and liver diseases at early stages. The methodology presented compares several common ML models-Naive Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT), and Fast Condition Mutual Information (FCMIM-SVM)-using datasets from various sources with the BFCNN model. According to the simulated results, the proposed BFCNN model achieved a 96.7% accuracy rate and outperformed existing models in terms of sensitivity and specificity. This study suggests that using the BFCNN together with the Hybrid S-Fuzzy model enhances diagnosis for multiple diseases, offering higher accuracy and earlier identification compared to individual models, with up to 78% potential benefits in healthcare. Further studies on this model may lead to the application of deeper methods to increase diagnostic accuracy and improve treatment recommendations. © 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

Enhancing Quantum Operations: Random Forests for Anomaly Detection and Alert Generation 7

Enhancing Quantum Operations: Random Forests for Anomaly Det...

引用

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

作者： Anoop, M. Nithya, B. SRM Institute of Science and Technology Dept. of Computer Science and Applications Chennai India Hindustan Institute of Technology and Science Dept. of Computer Applications Chennai India

ISBN: (纸本)9798350372816

A promising approach for enhancing the dependability and security of quantum processes is the integration of Random Forests, a traditional machine learning technique, with quantum anomaly detection and alert production. This approach involves training Random Forest models to inspect quantum data and spot abnormalities such as variations in quantum states, entanglement patterns, and the results of quantum processes. When anomalies are found, alarms are activated, categorized by severity, and sent out via several notification channels. Operators of quantum systems can act quickly by applying techniques for adaptive control, error correction, or system reinitialization. The rigorous preservation of historical data makes post-incident study and ongoing system improvement possible. This novel strategy strengthens security while simultaneously improving the performance of quantum systems, particularly in situations involving quantum communication. To guarantee its efficiency in the continually changing quantum landscape, careful design and ongoing monitoring are essential. © 2024 IEEE.

关键词： Quantum communication

来源：评论

学校读者我要写书评

暂无评论

Stuxnet Unveiled: The Blueprint for Modern Cyber Conflict 3

Stuxnet Unveiled: The Blueprint for Modern Cyber Conflict

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Rai, Preeti Nain, Vishal Dept. of Computer Science and Applications New Delhi India

ISBN: (纸本)9798331518592

The 2010 discovery of the Stuxnet malware signaled a sea change in the field of cyberwarfare, and the 21st century has seen an unparalleled spread of digital technology and their incorporation into vital infrastructure systems. Given this, Stuxnet is a sobering reminder of the weaknesses present in our globalized society. This paper aims to investigate the intricacies of the Stuxnet attack, including its origins, development, objectives, and significant implications for cybersecurity and international relations. By carefully analyzing this sophisticated cyberweapon, this study sheds light on how cyberthreats are evolving in the twenty-first century. © 2024 IEEE.

关键词： Critical infrastructures

来源：评论

学校读者我要写书评

暂无评论

Feature Extraction Techniques and Their Role in Alzheimer's Disease Diagnosis: A Comprehensive Review 3

Feature Extraction Techniques and Their Role in Alzheimer's ...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Rai, Preeti Ambooj Kukkar, Sania Dept. of Computer Science and Applications New Delhi India

ISBN: (纸本)9798331518592

Feature extraction is essential for breaking down complicated datasets into more digestible and useful formats, particularly in medical imaging. Accurate and timely diagnosis is critical in the context of Alzheimer's disease (AD), and MRI scan feature extraction algorithms have demonstrated significant potential. This study looks at a number of feature extraction methods, their applications across several fields, and their specific use in Alzheimer's disease diagnosis. By examining MRI-based research, we highlight important advancements and contributions in the field, emphasizing the techniques' potential to improve diagnostic accuracy. Despite these developments, there are still things that can be done to optimize feature extraction processes, such as reducing computational costs, enhancing model generalization, and refining feature selection for improved clinical outcomes. The paper continues by discussing the challenges of applying these methods in real-world clinical settings, including differences in patient demographics and imaging procedures. In conclusion, advanced feature extraction methods-particularly those that enable early detection, lower computing requirements, and provide more precise interpretations of MRI data-that employ deep learning and machine learning algorithms-have the potential to revolutionize Alzheimer's disease detection. The paper also makes recommendations for future research directions to get beyond current limitations and maximize the usage of feature extraction techniques for Alzheimer's disease diagnosis. © 2024 IEEE.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects

引用

computer Methods and Programs in Biomedicine Update 2025年 7卷

作者： Lofù, Domenico Sorino, Paolo Colafiglio, Tommaso Bonfiglio, Caterina Donghia, Rossella Giannelli, Gianluigi Lombardi, Angela Di Noia, Tommaso Di Sciascio, Eugenio Narducci, Fedelucio Dept. of Electrical and Information Engineering (DEI) Politecnico di Bari BA Bari 70125 Italy Dept. of Computer Automatic and Management Engineering (DIAG) Sapienza Università di Roma RM Roma 00185 Italy Unit of Data Science National Institute of Gastroenterology ”Saverio de Bellis” IRCCS Hospital BA Castellana Grotte 70013 Italy Scientific Direction National Institute of Gastroenterology ”Saverio de Bellis” IRCCS Hospital BA Castellana Grotte 70013 Italy

Metabolic dysfunction-associated fatty liver disease (MAFLD) introduces new diagnostic criteria for fatty liver disease that are independent of alcohol consumption and viral hepatitis infection. Therefore, investigating how biochemical and anthropometric factors influence mortality in MAFLD subjects is of significant interest. In this work, we propose MORIX, an Artificial Intelligence-based framework capable of predicting fatal mortality outcomes in subjects with MAFLD. MORIX utilizes data from epidemiological datasets containing carefully selected anthropometric and biochemical information. This selection is achieved through Recursive Feature Elimination (RFE) using a Random Forest (RF) to train Machine Learning (ML) algorithms and provide a mortality risk (Yes/No) output. To provide physicians with a valuable tool, MORIX was trained and tested on a dataset of MAFLD subjects, comparing five different models: Random Forest (RF), eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Light Gradient Boosting Model (LGBM) in a 5-fold cross-validation training strategy. Experimental results identified the RF as the best model, achieving a high accuracy for both mortality risks predicted. Additionally, an eXplainable Artificial Intelligence (XAI) analysis was conducted to clarify the diagnostic logic of the RF model and to assess the impact of each feature to the prediction. Moreover, a web application was developed to predict mortality risk and provide explanations of how the input features influenced the final prediction. In conclusion, the MORIX framework is easy to apply, and the required parameters are readily available in healthcare datasets, making it a practical tool for medical professionals. © 2025 The Authors

关键词： Epidemiology Interpretability Machine learning techniques MAFLD Mortality

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：