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3rd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Deepa, R. Das, Manisha Thilakavathy, P. Bennet Prabhu, A. Surendran, R. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Andhrapradesh Rajam India Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Computer Science and Engineering Chennai India Kone Elevator India Technology & Engineering Centre Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350369083

This paper introduces Agricultural Advancement using NLP (AA-NLP) techniques as a strategy to overcome the limitations of traditional agricultural management information systems. There is a lot of unstructured data available but this situation makes agricultural research inefficient because of its knowledge extraction and usage failure. This problem is addressed by combining an ontology framework developed for agricultural information management with Natural Language Processing (NLP) methods. The solution, AA-NLP, utilizes modern NLP algorithms which extract, classify and evaluate agricultural information from many textual sources that include research papers, reports and online repositories. AA-NLP achieves effective information retrieval and exploitation through named entity identification, sentiment analysis and semantic similarity as well as other techniques to convert unstructured input into structured ontological representations. Applying AA-NLP has several benefits such as increased discoverability of relevant agricultural information, automatic classification of scientific findings, and generation of actionable insights for decision making in farming practices, crop management and formulation of agricultural policies. The effectiveness of AA-NLP was analyzed in this paper by measuring the precision associated with knowledge extraction and ontology creation through various performance metrics including accuracy, sustainability farming practices, agricultural productivity and precision. © 2024 IEEE.

关键词： Semantics

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Guardians of Truth: Exploring Techniques for Veracity Identification in social media during an Infodemic 3

Guardians of Truth: Exploring Techniques for Veracity Identi...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Suthanthiradevi, P. Revathy, G. Sathish Kumar, P. Karthikeyan, B. Muthu, Lakshmi.V SRM institute of Science and Technology Data Science and Business Systems School of Computing India Vels Institute of science Technology and Advanced studies Department of Computer science and engineering India Rajalakshmi institute of technology Computer and Communication Engineering India SASTRA Deemed University School of Computing India St. Joseph's Institute of Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350372120

With the recent advent of technology, social networks are accessible 24/7 using mobile devices. During covid-19 pandemic the propagation of misinformation are mostly related to the disease, its cures and prevention. With Twitter as the medium this information was spreaded to millions of people who lack domain specific knowledge. This can lead to bloster fear and direct damage to the people. This research focuses on identifying the veracity of the Twitter posts behind pandemic situation. The authors have proposed a Transformer Model using Bat Algorithm for identifying the fake news. This model is trained and evaluated using infodemic metadata. Our experimental results shows by which proposed model accurately detected the fake news and achieved 96.5% of f1-score. © 2024 IEEE.

关键词： Social networking (online)

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Safe Spaces Analysis for Mental Health 12th

Safe Spaces Analysis for Mental Health

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12th International Conference on Recent Trends in computing, ICRTC 2024

作者： Kelawala, Harsh Shah, Zeal Selvaraj, P. Department of Computing Technologies College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur 603203 India

ISBN: (纸本)9789819789450

Mental health is a paramount concern in contemporary urban environments, necessitating comprehensive approaches to understanding its determinants and formulating effective interventions. This research project adopts a multifaceted methodology to explore the factors influencing mental well-being in urban areas, specifically focusing on cities within Gujarat. By integrating Geographic Information Systems (GIS) technology and predictive modeling techniques, we analyze various socio-environmental factors spanning air quality, noise pollution, green space availability, educational attainment, population density, income levels, and employability. At the same time, the GIS approach encompasses all major cities across India, the Random Forest algorithm is tailored specifically to the cities of Gujarat, reflecting the unique socio-geographical context of the region. Through rigorous data analysis and visualization, we identify spatial patterns and correlations, enabling the identification of areas most vulnerable to mental health challenges and prioritizing targeted interventions. This work presents our research's methodology, findings, and implications, offering valuable insights for policymakers and stakeholders striving to cultivate safe and supportive urban environments conducive to optimal mental health outcomes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Object Detection Using Deep Learning for Blind People with Voice Feedback

Object Detection Using Deep Learning for Blind People with V...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Pongiannan, R.K. Franklin, J. Richard Pravin, A. Maria, Marissa Mishra, Sarvottam Kumar Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India Srm Institute of Science and Technology Department of Electrical and Electronics Engineering Kattankulathur India Computer Science Engineering Srm Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798331510022

BlindSpace is an innovative application aimed at improving the lives of visually challenged individuals. Leveraging cutting-edge image captioning and object detection technologies, the app allows users to capture images using their smartphone's camera, providing detailed scene descriptions and audibly identifying objects within those images. This not only enhances users' understanding of their environment but also fosters independence and confidence. With voice commands and text-to-speech technology, the application offers a user-friendly experience and can be customized to individual preferences. Operating efficiently offline, BlindSpace stands as a significant leap in accessibility technology, bridging the gap between the visual and non-visual worlds for visually challenged individuals and promoting inclusivity and autonomy. © 2024 IEEE.

关键词： Smartphones

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Multi Head Graph Attention for Drug Response Predicton 3

Multi Head Graph Attention for Drug Response Predicton

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3rd International Conference on Smart Data Intelligence, ICSMDI 2023

作者： Selvi Rajendran, P. Sivannarayna, M. Computer Science and Engineering School of Computing Hindustan Institute of Technology and Science Chennai India

ISBN: (纸本)9781665464871

Precision medicine is based on curing diseases based on a patient's genetic profile, lifestyle, and environmental factors. This method improves clinical trial success rates and speed up drug regulatory approval. Predicting tumour vulnerability to specific anti-cancer therapy is critical for the successful implementation of precision medicine. Drug combinations have been shown to be very effective in cancer treatment to lower the drug resistance and improve the therapeutic effectiveness. The experiments carried out in all these therapeutic combinations have become expensive and time-consuming as a result of the increasing number of anti-cancer drugs. Large-scale drug response testing on cancer cell lines might help to understand the way drugs react with cancer cells. This study proposes a multi head graph attention network to perform drug response prediction. © 2023 IEEE.

关键词： Diseases

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A Hierarchical Hybrid Deep-Net Framework for Water Demand Forecasting Using OPHO Optimization and Deep Learning Techniques

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Iranian Journal of science and Technology - Transactions of Civil engineering 2025年 1-17页

作者： Jeyavelu, Subha Mohan, Kowsigan Department of Computing Technologies College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chengalpattu 603203 India

Intelligent water supply relies heavily on water demand forecasting. Due to nonlinear changes in the water consumption process, traditional prediction models have significant limitations regarding precision and consistency. Water wastage is monitored and the water distribution system is wirelessly monitored via the Internet of Things (IoT) technology. This study introduces a Hierarchical Hybrid Deep-Net Framework for water demand forecasting, combining advanced deep learning architectures and the Osprey-Pelican Hybrid Optimization (OPHO) algorithm to enhance prediction accuracy and efficiency. The framework integrates RNN-LSTM to capture temporal patterns, Caps Net to understand hierarchical relationships, and MobileNetV2 for efficient data processing. The methodology begins with comprehensive data preprocessing, including data cleaning to handle inconsistencies, Min–Max normalization for feature scaling, and feature extraction through statistical measures such as mean, median, standard deviation, and skewness and correlation-based features like Spearman rank correlation. High-level abstract features are extracted using Inception V3, a pre-trained deep learning model. Feature selection is performed using the OPHO algorithm, which combines the precision of Osprey optimization and the local search capabilities of Pelican optimization to identify the most informative features while reducing dimensionality. The framework is validated on a real-world dataset sourced from United Utilities, a water and wastewater management firm in the North West of England, obtained from Kaggle. The proposed model is evaluated for both 70% and 80% of training data for the metrics MAE of 0.0300, 0.0100, MAPE of 0.0119, 0.0223. Also, the MSE, NMSE, RMSE, and IoA have superior performance when compared to the other existing methods. © The Author(s), under exclusive licence to Shiraz University 2025.

关键词： Hierarchical hybrid deep net Inception V3 Min–max normalization Osprey-Pelican hybrid optimization Water demand forecasting

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Advanced Weather Monitoring and Disaster Mitigation System with Interactive Weather Visualizations, Flood Zone Detection, Unplanned Drainage Identification, and Emergency Shelter Mapping including Optional Drought Intensity Prediction Capabilities 7

Advanced Weather Monitoring and Disaster Mitigation System w...

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

作者： Ranjani, M. Devaraju, Perada Sreeharshitha, Yengalasetty Viswesh, Mekala Dubey, Siddhanth SRM Institute of Science and Technology Faculty of Engineering and Technology Chennai India SRM Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798350372816

The Advanced Weather Monitoring and Disaster Mitigation System is an essential resource for enhanced preparedness and response to unexpected events. It applies modern methods to show us dynamic weather images, detect regions susceptible to flooding, and present us with interactive weather maps. It is able of forecasting the intensity of an impending drought. These stupendous pictures and weather forecasts can assist everyone, including the public and authorities, make educated decisions and get ready for bad weather. In the case of flooding, the technology can detect high-risk areas, allowing officials to prepare ahead of time and safely evacuate citizens. It also looks for drainage problems before they cause disastrous flooding. By providing up-to-date information on local shelters, the system helps people find safe havens throughout emergencies. The alternative drought forecast may help farmers and water managers plan more effectively during dry spells. All of these components work together to protect us and lowered the effects of natural disasters. © 2024 IEEE.

关键词： Drought

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Securing Cloud-based Data Sharing with Accountable Proxy Re-Encryption 4

Securing Cloud-based Data Sharing with Accountable Proxy Re-...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Mahalakshmi, E. Vaidhegi, A. Jayakumar, D. Ramkumar, M.O. Rajmohan, R. Department of Computer Science and Engineering Villupuram India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350349900

Cloud computing has been a considerable way to store and share data among different communities in the past few decades. However, it has always been a challenge to ensure that the data is secured during cloud data transfer. The proposed paper resolves the major challenges being faced in cloud data sharing with the new approach of Accountable Proxy-ReEncryption (APRE). The proposed paper deals with protocols and anticipates cryptography measures, namely homomorphic encryption, by ensuring two things: confidentiality and integrity. Both work on the shared data of the cloud. The major aspect of homomorphic encryption is that it has an inbuilt feature of function execution over the encrypted data without decryption. So, it communicates the data confidentially by maintenance. Thus, re-encryption of the proxy used in this research would also allow for safe delegation to the proxy servers. The APRE protocol brings about different accountability mechanisms. In this case, it deals with the aspect of transparency and data supervision in communication. The homomorphic signatures in the paper enable the data owner to monitor and audit the proxy functions. It strictly enforces the decryption policies and minimizes the rate of mishandling of shared information. In so doing, this layer boosts the trust of cloud data sharing, especially in terms of provision of confidentiality, preservation of privacy, and the allowance of the robustness of behaviour in verifying and tracking data access. Finally, this proposed system uses a comprehensive assessment framework to check the effectiveness and efficiency of the APRE protocol. It can, therefore, be inferred that from the outcome obtained from the results, this proposed system outperforms the other existing systems in security, performance, and effectiveness. © 2024 IEEE.

关键词： Cloud platforms

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Deep Neural Decision Forests for Accurate ESD Prediction: A Novel Approach 2

Deep Neural Decision Forests for Accurate ESD Prediction: A ...

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2nd International Conference on Automation, computing and Renewable Systems, ICACRS 2023

作者： Desai, Dhyani Dhaval Mittapalli, Jishnu Saurav Tyagi, Karmanya School of Computing Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350340235

S kin is one of the most versatile and is one of the largest organs in the body. It has many important functions, it regulates the temperature of the body and at the same time also protects our internal organs from external damage. This outer layer shields the body from outside particles including harmful UV rays, bacteria, and chemicals, and other substances. Without proper care and maintenance, the skin can become dry, irritated, and more susceptible to infection and disease. S imilar to other bodily organs, the skin needs care and maintenance for its healthy functi oning. WHO says that the world's most widespread health issues are mainly skin conditions, ranking as the third most frequent cause of health issues. Additionally, they are one of the leading causes of disability and are among the most common reasons for visits to outpatient clinics. The World Health Organization has reported a noticeable increase of skin cancer in the last few years, it also identified UV radiation as a leading cause. present a multi-filter deep neural decision forest-based method determining which category the ES D disease belongs to. Data used in this project includes both histopathological and also the clinical attributes of various patients suffering from EDS . The proposed multi-filter feature selection method identifies the most optimal features and attributes contributing to disease detection and improves its performance. After generating the feature set a deep neural decision forest is utilized for determining the category of the disease. To evaluate more on this particular method, various criteria were taken and checked with other conventional classification approaches. © 2023 IEEE.

关键词： ESD prediction Modern technologies Skin issues

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Key Logger for Recording the Keystroke of the Targeted Machine 1

Key Logger for Recording the Keystroke of the Targeted Machi...

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1st IEEE International Conference on computing and Data science, ICCDS 2024

作者： Gnanavel, S. Sreekrishna, M. Shivaramakrishnan, P. Yaswanth, R. Gopika, G.S. Supriya, S. SRM Institute of Science and Technology Faculty of Engineering and Technology Dept of Computing Technologies Kattankulathur603203 India Sathyabama Institute of Science and Technology Dept of Computer Science Engineering Chennai600119 India

ISBN: (纸本)9798350365337

In the recent digital era security has become more challenging. There is a plethora of ways to find solution to ensure monitor the system and provide required security. Key logger is one of the cyber attacks which record the key strokes of the targeted systems or devices from the host person. In other words, the program retrieves vital information such as login credentials, passwords and other sensitive information. There are many types of key logger, software key loggers is one of the key logger type which use software applications to collect the information from the targeted machine to host machine. It is indeed difficult to trace the software key logger because it runs in background without any noticeable signs. However, there are some signs like network traffic and unexpected activity. This paper concentrates on the implementation of key logger and its observation using python file, JavaScript file and etc. © 2024 IEEE.

关键词： Network security

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