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2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023

作者： Kingsly Stephen, R. Faritha Banu, J. College of Engineering and Technology Srm Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350380880

Alzheimer's disease is becoming more common over time. It is a long-term brain disease that gradually impairs people's memory, thinking skills, and finally their ability to perform even the most basic tasks. Early detection can help reduce the progression of this condition because it grows severe before any obvious symptoms show up and produces a brain problem that cannot be treated with drugs or other treatments. This paper proposes a Particle Swarm Optimization Algorithm based U-Net model for image segmentation in Alzheimer's disease classification. The proposed framework uses the Kaggle Alzheimer's image dataset database for training, testing, and validation and shows improved results of 88% Dice Coefficient, 83% Jaccard Index, and 90% F1 Score when compared with Threshold-based-segmentation, Region-Based-segmentation and Clustering-based-segmentation methodologies. © 2023 IEEE.

关键词： Image segmentation

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Android based Food Rescue System 2

Android based Food Rescue System

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： More, Priyanka Shete, Rushikesh Bhaladhare, Pooja Gujarkar, Kirti Sakure, Megha Amol Khan, Sana Yeshwantrao Chavan College of Engineering Department of Computer Science and Engineering Nagpur India St.Vincent Pallotti College of Engineering Department of Computer Science and Engineering Nagpur India Datta Meghe Medical College Department of Medical Surgical Nagpur India Datta Meghe Medical College Department of Anesthesia Nagpur India Nagpur College of Pharmacy Nagpur India

ISBN: (纸本)9798331528713

Food wastage is serious issue in our society from many decades and it affects both poor and rich countries. Similarly, food waste has a strong impact on the environment which mainly includes greenhouse gas emission. To resolve this problem, some existing solutions are available but these systems are unable to cater the wastage of foods which is consider to be the extra food available at donor side with minimum or maximum quantity. Due to lack of time and existing available facility, food-donor unable to connect the needy people. The proposed system is creating a social awareness to avoid food wastage and rescue their waste food to poor or needy peoples. The system maintained the list of food donors and receivers and donor can provide the information regards food quality and its quantity. The social benefit of proposed system is to reduce food wastage and greenhouse gas effect. © 2024 IEEE.

关键词： Greenhouse gas emissions

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A Novel Structure to Mine High Utility Items Based on Transactional Weights 1

A Novel Structure to Mine High Utility Items Based on Transa...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Vimaladevi, M. Deebika, R. Russia, S. Kongu Engineering College Department of Artificial Intelligence Perundurai India K S R Institute for Engineering and Technology Department of Computer Science and Engineering Tiruchengode India Velalar College of Engineering and Technology Department Computer Science and Engineering Erode India

ISBN: (纸本)9798350342796

Association Rule Mining finds the frequent pattern rules in a dataset but association rule mining does not gives any information about the profit of the item. High utility itemset mining finds the high utility itemsets from the dataset, the high itemset discovers the profitable and useful patterns. Mining high utility itemset is challenging compared to mining association rule mining algorithm since the downward closure property is not satisfied in high utility itemset mining. Various state-of-the algorithms have been proposed to mine high utility itemset. In this paper a novel tree based data structure to mine high utility itemset is proposed and different pruning strategies is employed to effectively mine high utility itemset. The proposed idea is evaluated on 4 real time datasets. The result shows that the proposed algorithm performs better than the state-of -the-art algorithms in terms of memory and execution time. © 2023 IEEE.

关键词： Frequent Pattern High Utility Itemset Pattern Growth Utility Item

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Modified microstrip fed of pentagon shape aperture coupling with RDRA for 5G wireless application

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Materials Today: Proceedings 2022年 60卷 1665-1669页

作者： Manikandan, B. Muneeshwari, P. Sathya Sofia, A. Karthikeyan, G. Athilingam, R. Department of Electronics and Communication Engineering Nadar Saraswathi College of Engineering and Technology Theni India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering PSNA College of Engineering and Technology Dindigul India Department of Electronics and Instrumentation Engineering Dr. Mahalingam College of Engineering and Technology Pollachi India

In this paper, a rectangular dielectric resonator antenna (RDRA) with modified microstrip feed is proposed. A pentagon-shaped aperture coupling with a bifurcated modified microstrip-line (MSTL) was used to excite the DRA element on the FR4 substrate's backside, resulting in a 3.8 GHz band. Optimizing the design parameters yields a 10% increase in impedance bandwidth, covering frequencies between 3.08 and 3.8 GHz. Maximum gain and radiation efficiency are shown to be 4.85 dB and 90%, respectively, in the operational band using the proposed DRA. As a result, the proposed antenna may be appropriate for use in 5G NR band systems. © 2021 Elsevier Ltd

关键词： Radiation efficiency

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Emergency Vehicle Detection Using Deep ConvNet2D and computer Vision 2

Emergency Vehicle Detection Using Deep ConvNet2D and Compute...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Poongavanam, Elumalaivasan Prathik, A. Munirathinam, T. Kayalvizhi, V. Rajesh, R. Mahavishnu, C. Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai Kattankulathur India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Sona College of Technology Department of Information Technology Salem India School of Computer Science and Engineering and Information Science Presidency University Bangalore India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Shreenivasa Engineering College Department of Computer Science and Engineering Dharmapuri India

ISBN: (纸本)9798350328202

A surveillance system detects emergency vehicles stuck in traffic. This system helps manage traffic because the number of vehicles on the road has been increasing daily for years, causing congestion. This project implements Deep ConvNet2D (Convolutional Network 2D) and computer Vision emergency vehicle recognition. We propose a CNN-based real-time image processing model for emergency vehicle detection. The signal control unit can be set to terminate the round robin sequence when an emergency vehicle is detected. A CNN trained on Indian ambulance images solves the problem. Tensor Flow, a Python library, was used for training. Our method detects and classifies emergency cars well. Existing systems use ANN algorithm, which is inaccurate and inefficient. The system uses Deep ConvNet2D Algorithm. The proposed real-time system is accurate. The proposed system loads and executes faster than the existing system. The system is efficient, scalable, and enhanced for complex use cases. © 2024 IEEE.

关键词： Real time systems

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Automatic Text Summarization using Text Rank Algorithm 3

Automatic Text Summarization using Text Rank Algorithm

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3rd International Conference for Advancement in Technology, ICONAT 2024

作者： Dumne, Rakhi Gavankar, Nitin L. Bokare, Madhav M. Waghmare, Vivek N. Walchand College of Engineering Department of Comp. Science and Engineering Sangli India Institute of Technology and Management Department of Computer Nanded India PVG' College of Engineering S.S. Dhamankar Institute of Management Department of Computer Engineering Nashik India

ISBN: (纸本)9798350354171

Automatic text summarization has been emerged as a valuable tool for quickly locating the significant information in vast text with minimal effort. The practice of constructing a summarized form of a text document that retains significant information and also withstand the overall meaning of the source text is known as text summarization. This study mainly concentrates on the extractive text summarization technique wherein the text summarization is carried out on single document as well as on multi document text. Further, the application is extended by implementing document summarization and URL summarization. Here, the sentence extraction method from the input text forms the basis of proposed text summarization technique. During sentence extraction, the weights are assigned to sentences which act as rank of these sentences, using page rank algorithm. In this study, extraction technique has been implemented to extract sentences having higher rank from the given input text. The study mainly focuses on obtaining high rank sentences from the given document in order to generate a high-quality summary of the input text. © 2024 IEEE.

关键词： Text mining

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A Comprehensive Survey of Cybercrime and Cybersecurity 5

A Comprehensive Survey of Cybercrime and Cybersecurity

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5th IEEE International Conference on Advances in Electronics, computers and Communications, ICAECC 2023

作者： Shindagi, Kunaal Shirish Koppad, Khushi Vikram Jayakkanavar, Abhilasha Gorabal, S.V. Jain College of Engineering and Research Department of Computer Science and Engineering Belagavi India Jain College of Engineering and Research Department of Mechanical and Engineering Belagavi India

ISBN: (纸本)9798350305449

In the futuristic context, 'cybercrime' has become more hazardous to the nation's youth because felons and cybercrime victims are reported worldwide with false geographic information. any person in any area with a region is susceptible to a cyber threat, according to the futuristic scenario because protecting data has become one of the largest concerns in the modern world, cybersecurity is essential in the field of information technology. Cyber security is crucial to protect businesses and individuals from spammers and cyber culprits because one security branch Can make the private information of millions of people available. These branches can lead to a loss of client trust and have a single financial impact on the business. Cybercrime is expanding daily and it is the first thing that comes to mind when we think of cybersecurity. It is crucial to be aware of the threat that information technology (IT) poses and how to defend against it. Knowing what cyber security is and being able to use it effectively are essential in the modern world, which is run almost entirely by information technology. Cyber security seeks to shield users from harm, secure their safety, and safeguard personal information while they browse the internet. This research aims the acknowledge the extent of awareness among youth about cybercrime and cybersecurity. © 2023 IEEE.

关键词： Cybersecurity

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Development of Weather Forecast Application Using API 1

Development of Weather Forecast Application Using API

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1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Chadha, Shikha Ahmad, Salman Khursheed Sharma, Dolly Singh, Manu Srivastavaline, Anubhava Sharda University Department of Computer Science Greater Noida India School Of Computer Science & Engineering Galgotias University Department Of Computer Science Engineering Greater Noida India Graphic Era Hill University School of Computing Department Haldwani India ABES Engineering College Department of Computer Science UP Ghaziabad India

ISBN: (纸本)9798350353648

This research paper presents the development of a weather forecasting model that incorporates real-time data through Application Programming Interfaces. This model utilises simple algorithms to analyse meteorological parameters from diverse API data sources, aiming to improve forecast accuracy compared to traditional methods. Extensive datasets are used for training and validation, demonstrating the model's effectiveness in providing more precise predictions. The study highlights the significance of API integration in advancing weather forecasting methodologies and fostering innovation in the field. The model created has yielded highly reliable results with minimal error. © 2024 IEEE.

关键词： Prediction models

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Road Accident Detection using MobileNetv2 with Gradient Boosting Algorithm 1

Road Accident Detection using MobileNetv2 with Gradient Boos...

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1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Priyanka, K. Obaid, Saif Anguraj, K. Thangam, V. Thirumani Sahana, R. Nitte Meenakshi Institute of Technology Department of Information Science and Engineering Bengaluru India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Sona College of Technology Department of Electronics and Communication Engineering Salem India New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Chennai India Vel Tech Multi Tech Dr. Rangarajan Dr.Sakunthala Engineering College Avadi Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350352931

An increased number of vehicles on the roads increases the risk of accidents and eventually resulted huge loss of lives and property. Accident detection utilizing computer vision in much consideration as of late. The existing methods for accident detection gave inaccurate detection due to the errors in sensors and cameras may not capture all angles or all areas. Therefore, this paper proposes MobileNetV2-Gradient Boosting (MNGB) for detection of road accidents which effectively gave accurate detections. Firstly, all videos are split up into smaller shots according to scene changes and then key frames are extracted from each shot based on consecutive frames. This images are augmented by using Kalman filter which reduced the noise and artifacts in images, accurately tracks the objects across frames. Then, features are extracted by using Multi-Scale Network (MSNet) where it extracts the features at various scales by capturing both local and global information. After that, these features were classified by using proposed MNGB which enables the real time processing and reduces the computational resources and gave accurate detection results. The proposed MNGB for road accident detection achieved better results in terms of accuracy 95 %, precision 9 8 %and F1-Score of 9 6 %when compared with existing YOLOv3. © 2024 IEEE.

关键词： Kalman filters

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Extended Finite State Machine based Fault Tolerance in WSN 7

Extended Finite State Machine based Fault Tolerance in WSN

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7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Lekha, D. Ahsan Shariff, M. Lakshmi, S. Venkata Anwar Basha, H. Department of Computer Science and Engineering RMK College of Engineering and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Aalim Muhammed Salegh College of Engineering Tamil Nadu Chennai India Artificial Intelligence and Data Science Sri Krishna College of Engineering and Technology Tamil Nadu Coimbatore India School of Computer Science and Engineering REVA University Karnataka Bengaluru India

ISBN: (纸本)9781665464086

Wireless Sensor Network (WSN) suffers from different malware attacks. Several traditional approaches are proposed for detecting fault nodes in WSN. It is necessary to redistribute the nodes and detect the fault nodes while modifying the WSN parameters. Faults can occur in the nodes interrupting the continuous communication process of the nodes in the WSN. The main reason for a fault is also the induction of the energy drain in a node to the maximum possible level, failure of links in communicating nodes due to bandwidth constraints, and attacks induced by the malicious nodes. To solve this problems, Extended Finite State Machine based Fault Tolerance (EFSM_FT) in the WSN is used to detect the fault sensor nodes in the WSN. In this approach, called the finite state machine (FSM), state prompted is modified while a set of situations are true. Every node can be absolutely to be faulty or not establishing on the sensor node states. Using sensor energy, drop rate, forward sensor rate, sensor obtained rate, bandwidth, and transmission delay, this method finds the node with the fault. As a result, this approach accurately detects the faulty nodes in the WSN. The simulation outcomes illustrate the proposed method has a better fault detection ratio and minimizes the false negative ratio in the WSN. © 2023 IEEE.

关键词： Finite automata

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