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Metro Cities House Price Prediction Using Ml

Metro Cities House Price Prediction Using ML

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Self Sustainable Artificial Intelligence Systems (ICSSAS), International Conference on

作者： Sonal Naik Aarti Puthran Computer Engineering Shree L.R.Tiwari College of Engineering Mumbai India Computer Engineering Vidyavardhini's College of Engineering Mumbai India

due to changes in local infrastructure as well as real estate values, home prices fluctuate every single year. Customers can figure out the value of the house with the aid of a centralized system that predicts house prices and has infrastructure. It aids the consumer in making decisions on where and when to buy a home. When forecasting a property's value, several factors are taken into account, such as location, neighborhood, size, etc. The intention of this study is to predicate house prices for individuals depending on financial situation. This study matched the outcomes of many machine learning methods including linear, XGB, decision tree, lasso regression and random forest regression, due to its outstanding accuracy. House value forecast on a data set will be performed by utilizing all of aforementioned methodologies and selecting the best among them. This study establishes the application of machine learning algorithms in the prediction of house values using datasets collected from Kaggle. This study can construct a regression model that can precisely estimate the cost of a property created on its characteristics.

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TeenSenti - A novel approach for sentiment analysis of short words and slangs

TeenSenti - A novel approach for sentiment analysis of short...

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Advances in Modern Age Technologies for Health and engineering Science (AMATHE), International Conference on

作者： Sahil Kamath Vaishnavi Padiya Sonia d'Silva Nilesh Patil Meera Narvekar Dept. of Computer Engineering D.J. Sanghvi College of Engineering Mumbai India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

The present prevalence of online platforms and the internet has seen a substantial increase in the utilization of Generation Z slang, abbreviated expressions, and short words. These lexical subtleties have become a vital part of a person's daily interactions, and therefore evident in reviews, product comments, and throughout the internet. Resultantly, there exists a need to integrate these Informal expressions such as abbrevi-ations, slang, and short words into natural language processing (NlP) systems. The Informal expressions naturally contain some contextual relevance and therefore can be used to improvise sentiment analysis, as these expressions contribute significantly to the overall context and sentiment of sentences. However, traditional NlP techniques often fall short in recognizing and incorporating these informal expressions, resulting in an atten-uated accuracy of sentiment analysis. To address this issue, this study ventures to provide a comprehensive slang dictionary, encompassing short words, abbreviated expressions, and slang along with the sentiment and sentences of each. This curated slang dictionary is effectively integrated into NlP systems using FastText Embeddings. Through extensive testing across multi-ple machine learning (Ml) and deep learning (dl) models, this approach significantly enhances the accuracy of sentiment analysis when compared to conventional methodologies. This research emphasizes the importance of accommodating informal expression in NlP systems thus opening the possibility of future research.

关键词： deep learning Sentiment analysis dictionaries Accuracy Reviews Navigation Oral communication

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Video Surveillance-Based Intrusion detection System in Edge Cloud Environment 3rd

Video Surveillance-Based Intrusion Detection System in Edge ...

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3rd International Conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2023

作者： Sharma, Annu devasenapathy, deepa Raja, M. Shadrach, Finney daniel Shirgire, Anil Arun, R. Yau, Thomas Moh Shan Department of Computer Science and Applications Rajarajeshwari College of Engineering Karnataka Bengaluru560074 India Instructor-II/Computing and Software Engineering U.A. Whitaker College of Engineering Florida Gulf Coast University Fort Myers United States Department of Computer Science and Engineering CMR Institute of Technology Karnataka Bengaluru560037 India Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Tamil Nadu Coimbatore641407 India Department of Civil Engineering Dr. D Y Patil Institute of Technology Maharashtra Pimpri Pune411018 India Department of Computer Science and Engineering Hindusthan Institute of Technology Coimbatore India Director of Centre of University Courses and Innovative Learning University of Technology Sarawak Jalan Universiti Sibu Sarawak96000 Malaysia

ISBN: (纸本)9789819986453

Video surveillance is mostly used for monitoring distant videos and the cloud memory in the system provides more secure to the data. But, in the existing methodologies poor intrusion detection accuracy as well as poor performance rate is considered as the main demerits. So, to overcome the above-mentioned demerits, a novel video surveillance-based Intrusion detection System (IdS) (VS-IdS) in the edge cloud environment via deep learning method has been developed in this research. different algorithms are used for object detection and intrusion detection. Subsequently, the proposed model can be implemented and verified in NVIdIA Jetson TX2 platform. The proposed model attains better rate of performance than the existing models. The Performance of the proposed model can be validated with accuracy, precision, recall, MSE and F-measure. Higher performance rate indicates that the system can detect intrusion more accurately than the existing mechanisms. 99% of detection accuracy can be attained through the proposed model. © The Author(s), under exclusive license to Springer Nature Singapore Pte ltd. 2024.

关键词： Intrusion detection

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Artificial Intelligence based Ensemble learning Approach for Brain Tumour Classification Using MRI Images 7

Artificial Intelligence based Ensemble Learning Approach for...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Oza, Bhavesh A. Khan, Ihtiram Raza Kanulla, Naga Sathya lakshman Kumar Hasan, Shakh Md Shakib davuluri, Sandeep Kumar Pothakamuri, lakshmi Narayana L D College of Engineering Computer Engineering Department Gujarat Ahmedabad India Jamia Hamdard University Computer Science Department New Delhi India Bausch + Lomb. Department of Information Technology 2701 Indian Clover Trl LeanderTX78641 United States Westcliff University IrvineCA United States University of Cumberlands Department of Information Technology WilliamsburgKY United States

ISBN: (纸本)9798350350067

Brain tumours, produced by malignant alterations in brain tissues, are high-risk disorders that require early identification for treatment and prognosis. Current network models perform differently in categorization, and a single model often fails across various evaluation measures. TreerNet, an ensemble learning-based AI classification model, is proposed in this research. It combines TransFG, ResNet50, EfficientNetB4, EfficientNetB7, and ResNeXt101 using ensemble learning weighted averaging. The binary, tertiary, and quaternary brain tumour MRI image classification algorithm is trained using public datasets. Test results reveal that the Treer-Net model has 99.15% accuracy, 99.16% precision, 99.15% recall, and 99.87% AUC on the brain tumour three-class dataset. Comparative analysis shows that the suggested Artificial intelligence-based Ensemble learning method is accurate and efficient, making it ideal for brain tumour identification. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Multi-Band Antenna Arrays for Seamless Connectivity in Internet of Things (IoT) Applications 7

Multi-Band Antenna Arrays for Seamless Connectivity in Inter...

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7th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2023

作者： Asha, S. Jackson, Beulah Sivaraman, K. dayana, R. Hemavathy, N. Saveetha Engineering College Thandalam Department of Electronics and Communication Engineering Tamilnadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamilnadu Chennai India Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Tamilnadu Chennai India Jeppiaar Institute of Technology Department of Computer Science and Engineering Tamilnadu Chennai India Velammal Engineering College Department of Electronics and Communication Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350340600

The Internet of Things has dramatically increased the number of interconnected objects, all of which require constant and reliable communication channels. This article investigates using multi-band antenna arrays in Internet of Things installations to address connectivity issues. This study investigates such applications and proposes a novel approach to antenna design well-suited to the Internet of Things. Extensive simulations and testing are conducted to evaluate and appraise the proposed antenna array's gain, bandwidth, and radiation pattern. Compared to conventional, single-band antennas, the benefits of the multi-band approach are quite evident. The results demonstrate the capability of the multiband antenna array to reduce interference, sustain connections reliably, and support a wide variety of Internet of Things communication protocols. This study contributes significantly to the development of next-generation IoT communication systems by emphasizing the capacity of multi-band antenna arrays to improve the connectivity and dependability of IoT devices. © 2023 IEEE.

关键词： Antenna arrays

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Human Illegal Activity Recognition Based on deep learning Techniques

Human Illegal Activity Recognition Based on Deep Learning Te...

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2023 IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2023

作者： Shivaprasad Yadav, S.G. Itagi, Sumangala Krishna Suresh, B.V.N.V. Hemalatha, K.l. Ramachandra, A.C. Ramaiah Institute of Technology Department of Electronics and Telecommunication Engineering Bangalore India H. K. E. Society's S. L. N. College of Engineering Department of Computer Science & Engineering Raichur India K L University Vadeeshwaram Department of Computer Science & Engineering Vijayawada India Sri Krishna Institute of Technology Department of Information Science and Engineering Bangalore India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350398465

Human activity assertion in video is perhaps the most overall applied subjects in the field of picture and video arranging, with different applications in perception (security, sports, and so on), movement Id, video-content-based seeing, man-machine correspondence, and flourishing/handicap care. Homes and public locations such as hospitals, shopping malls, railway stations, airports, and so on all have surveillance cameras placed to safeguard the public's well-being and the safety of their personal items. About seven out of ten of the homicides that have been investigated and solved by professionals over the last several decades have benefited from the use of surveillance film in this capacity. In several instances of criminal investigation, the person of interest was located by comparing their picture to others of the same species that were taken by various cameras in various locations. Person Re-Identification is the process of discovering matches for a person or suspect across several cameras. This method is also known as Person Matching. The Person Re-Identification system, or PId, is a tool that helps keep track of human entries that are captured on video by a variety of cameras in a variety of settings. As a reaction to an image of the person obtained by a camera, the PRId system retrieves relevant pictures of the same person collected by multiple cameras in various places and at various times. This is done as a result of the input image of the person (called a probe image). By comparing images of the same person captured by different cameras, it is able to carry out the process of automating the search for a person or target that has been followed but been lost in a different camera view.. In this assessment, we propose a novel human development insistence methodology utilizing convolutional neural networks (CNN) and perceive the activity performed on that outline annals. Properly, this examination paper will give the required inspiration to seeing human acti

关键词： Cameras

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Analysis the impact of digital trends and IoT procedural scheme on traditional banking system

Analysis the impact of digital trends and IoT procedural sch...

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2022 IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2022

作者： Sharmila, V. Manisha, G. Subhashini, M. Sudha, B. R.M.D. Engineering College Department of Computer Science and Engineering India RMD Engineering College Department of Electronics and Instrumentation Engineering India Saveetha College of Liberal Arts and Sciences SIMATS Department of BCA Chennai India

ISBN: (纸本)9781665495295

The next stage of the digital revolution is here, and it's going to have a significant impact on consumers' daily lives: The Internet of things. Things and locations may be linked to the Internet, even though the Internet is often confined to electronic devices. Financial institutions are increasingly using IoT in a wide range of ways. Still, this essay aims to show how these technologies affect conventional banking procedures and how they may be used in the future. It would be fascinating to compile all the digital advancements that have a comparable influence on bank procedures. We will use these new approaches to carry out the digital transition as we have done before. © 2022 IEEE.

关键词： Technological innovation Systematics Computational modeling digital transformation Banking Market research Internet of Things

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design of Proficient Fused MAC Unit for PId Controllers 3

Design of Proficient Fused MAC Unit for PID Controllers

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

作者： Abinaya, A. Maheswari, M. Haridoss, G. Sherin Shibi, C. Babitha lincy, R. Jency Rubia, J. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India K.Ramakrishnan College of Engineering Department of Ece Tiruchirappalli India M.A.M College of Engineering and Technology Department of Ece Trichy India Srm Institute of Science and Technology Department of Computational Intelligence Tamilnadu Kattankulathur India Sir Eshwar College of Engineering Department of Computer and Communication Engineering Coimbatore India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369083

The implementation of PId controllers in ASICs demands a strong grasp of system and hardware design. despite the straightforward control structure and efficiency of industrial components regulated by PId controllers, they still incur significant power consumption. These control systems incorporate VlSI components like adders, multipliers, and accumulators to operate effectively. In this study, the integration of a fused MAC (Multiply-Accumulate) unit is employed for designing PId controllers, aiming to enhance efficiency across power consumption, path delay, and the utilization of lUTs. © 2024 IEEE.

关键词： Three term control systems

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Evaluating the Influence of Text Representation techniques on diverse Machine learning Algorithms for Stress detection in Social media users

Evaluating the Influence of Text Representation techniques o...

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Advances in Modern Age Technologies for Health and engineering Science (AMATHE), International Conference on

作者： Khushali deulkar Meera Narvekar Priya Gandhi dhruv Gada Sahil Kamath Dept. of Computer Engineering D.J. Sanghvi College of Engineering Mumbai India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

Over the past few years, there has been a notable surge in social media usage like Twitter, Facebook, Instagram. due to the anonymity of the internet, people's mental health is frequently reflected in their social media activity. Through such activities, psychiatric problems are frequently discovered and can be treated in their early stages, potentially preventing the effects of untreated mental disorders like depression and anxiety. The present study aims to examine the potential consequences of utilising two commonly used methods for text representation, namely Term Frequency-Inverse document Frequency(TF-IdF) and Bag-of-Words(BoW). The specific focus of this investigation is on the application of these techniques to the task of stress detection. The aim is to comprehend how these methods influence the effectiveness of different classifiers in identifying stress patterns within textual data. By assessing the impact of TF-IdF and BoW, this research seeks to enhance our understanding of their roles in shaping the performance of various algorithms. This study encompasses various machine learning algorithms, including Support Vector Machines(SVM), Random Forest, logistic Regression, and Naive Bayes. In the case of deep learning techniques, Recurrent Neural Network(RNN), long Short Term Memory(lSTM), RoBerta, and implementation of BERT embeddings in Recurrent Neural Networks was studied. The experimentation involves extensive datasets taken from two social media platform, Reditt and Twitter to ensure the robustness and generalizability of findings. The results shed light on the varying effects of TF-IdF and BoW, offering insights into which techniques are better suited for stress detection and contributing to the optimization of future stress detection systems.

关键词： Support vector machines logistic regression Machine learning algorithms Recurrent neural networks Social networking (online) Blogs Vectors

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Revolutionizing Financial Cloud Services: AI and Blockchain-driven Resource Allocation for Maximized Transaction Speed and Security 3

Revolutionizing Financial Cloud Services: AI and Blockchain-...

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

作者： Kumar, M. lenin Amanullah, M. Krishnamurthy, Revatthy Suganthi, N. Mohana Kalaiselvan, S.A. Vignan Institute of Technology and Sciences Department of Electronics Communication and Engineering Telangana India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Chennai Tamil Nadu Avadi India

ISBN: (纸本)9798350369083

In response to the evolving challenges of real-time monitoring in financial cloud environments, we propose a comprehensive solution integrating cutting-edge technologies. Our system employs AI-driven decision-making (AddM) with a dynamic Nested Neural Network (dNN) for adaptive resource allocation. This is coupled with a Markov decision Process (MdP) for probabilistic decision-making, optimizing computational power, storage, and network resources dynamically. Blockchain technology fortifies transaction verification through a decentralized consensus mechanism and cryptographic techniques like RSA. The collaborative synergy of optimized resource allocation and Blockchain security ensures near-instantaneous processing, meeting the demands of a dynamic financial landscape. Our proposed system transforms the financial cloud environment into an adaptive and intelligent system, enhancing efficiency, security, and responsiveness for seamless and reliable real-time transaction processing. The results demonstrate accelerated transaction speeds, resource efficiency, and a robust security framework, addressing critical concerns in the realm of financial transactions. © 2024 IEEE.

关键词： decentralized finance

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