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Continuous Monitoring of Web Server Assaults Using Machine Learning

Continuous Monitoring of Web Server Assaults Using Machine L...

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Emerging Trends in Information Technology and engineering (ic-ETITE), Conference on

作者： Vishali M Mirudhula A Priya A M Iswarya Kavitha Subramanian M.E Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India Dept of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India

Because of the widespread accessibility of the weband its ease of use, every organisation nowadays uses web apps to expand its company. With the growth of Due to growing online usage, attack riskhas grown as well. An effective monitoring tools that can recognise these threats Timely is necessary. Java script, PHP, and HTML are utilisedfor website development and database use of SQL management in depth. most typical web server assaults include XSS, DOS (Denial of Service), and SQL injection Cascading Style Sheets. IDS with rules work with keywords and patterns but fail to recognise unidentified assaults. In this article, ML based model is used for leveraging web server logsto identify intrusions. It identifies the sort of assault as well as if a given log is normal or malicious. By establishing a private network with the aid of an Apache WAMP server, web server logs are produced and gathered.

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BoneSegNet: Enhanced 2D-TransUnet Model for Multiclass Semantic Segmentation of X-Ray Images of Human Hand Bone

BoneSegNet: Enhanced 2D-TransUnet Model for Multiclass Seman...

引用

North Karnataka Subsection Flagship International Conference (NKCon), IEEE

作者： Venkatesh Nagaraju Y Darshan D Sahanashree K J Nagamani P N Satish B Basapur Dept. of Computer Science and Engineering College of Engineering University of Visvesvaraya Bengaluru India

ISBN: (数字)9798350364569

ISBN: (纸本)9798350364576

Multiclass segmentation of hand bones in X-ray images is crucial for various medical applications, including diagnostic assistance and surgical planning. This study presents BoneSegNet, a deep learning-based segmentation model designed to classify hand bones into seven distinct anatomical classes: Distal phalanges, Intermediate phalanges, Proximal phalanges, Metacarpals, Carpals, Ulna, and Radius. Our model, BoneSegNet leverages the strengths of both convolutional neural networks (CNNs) and transformer encoders incorporating the UNet architecture. Our model architecture begins with patch and positional embeddings of the input image, followed by a series of transformer encoder layers to capture long-range dependencies and contextual information. The transformer encoder is equipped with multi-head attention mechanisms and multi-layer perceptron’s (MLPs) with GELU activation and dropout for regularization. Skip connections at specific layers are stored and later utilized in the decoder. The decoding path consists of a series of deconvolution and convolution blocks designed to progressively upscale the feature maps while incorporating skip connections from the encoder. This hierarchical structure ensures detailed spatial information is preserved and enhanced. The final output layer employs a 1x1 convolution with a sigmoid activation function to produce the multiclass segmentation map. The model is trained and evaluated on a dataset of hand X-ray images. It achieves an average accuracy of 99.25%, an average Dice score of 0.81, an average mIoU score of 0.70, sensitivity of 0.79, and specificity of 0.997. These results demonstrate the model’s effectiveness in accurately segmenting and classifying hand bones, making it a valuable tool for medical professionals.

关键词： Image segmentation Accuracy Surgery Medical services Bones Transformers Planning Decoding X-ray imaging Medical diagnostic imaging

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Optimization of Quality Power Distribution System using Artificial Intelligence 5

Optimization of Quality Power Distribution System using Arti...

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Awasthi, Satya Prakash Singh, Sanjay Pilania, Urmila Kumar, Manoj Sindhu, A.S. Sarika, A.S. Poornima University Faculty of Computer Engineering Ramchandraoura Jaipur India Manav Rachna University Dept. of Computer Science and Technology Faridabad India Rajas Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu India Amrita College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu India

ISBN: (纸本)9781665474672

A maximum power point tracker is used in this study to determine incremental conductance (INC) (MPPT). Artificial Intelligence (AD based analysis and simulation of a solar photovoltaic module and associated electric circuit is presented, along with an examination of the effects of various environmental conditions on the behavior of the PV module. To fully appreciate the operating parameters of a PV module, basic PV cell attributes are addressed. A block diagram model of a PV module was made in Simulink and used to illustrate the curves. The results of simulations using a solar module demonstrate that the suggested method is quick and precise. This model is effectively used utilizing steady conductance in light of most maximum power point tracking methodologies for testing the behavior of the suggested system and forestall this output in the simulation via MATLAB. Controller can be implemented using a number of different techniques and algorithms. Power Point is liked here and is likewise reasonable for business purposes due to the minimal oscillations while establishing the Maximum. © 2023 IEEE.

关键词： Maximum power point trackers

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QGen: Automated Question Paper Generator

QGen: Automated Question Paper Generator

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Innovative Trends in Information Technology (ICITIIT), International Conference on

作者： Rohan Jose Paul Sangeetha Jamal Sebin Bejoy Ronit John Daniel Nevin Aju Dept. of Computer Science and Engineering Rajagiri School of Engineering and Technology Kochi India

ISBN: (数字)9798350386813

ISBN: (纸本)9798350386820

Traditional methods of creating question papers manually by educators takes a significant amount of time and are also susceptible to mistakes made by humans. To overcome these challenges, the concept of an automatic Question Paper Generator has emerged as a valuable tool for automating the process of generating assessment materials. The objective of this AI enabled Question Paper Generator is to establish an automated system that can efficiently set a question paper in seconds. This project is a web application that utilizes a fine tuned T5 transformer model to generate questions from the given input text. Of all the questions generated, 70% were relevant to the context.

关键词： Natural languages Transformers Market research Generators Information technology Artificial intelligence

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Unravel News: An Efficient Summarization Approach

Unravel News: An Efficient Summarization Approach

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Computing, Applications and Systems (COMPAS), IEEE International Conference on

作者： Ankan Saha Abdullah Al Shafi Dept. Computer Science and Engineering Khulna University of Engineering & Technology Khulna Bangladesh

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

The process of automatically creating a concise and informative summary of a news piece is known as news summarizing. This can be a useful tool for people who want to quickly get the gist of a news story without having to read the entire article. Extractive and abstractive summarization are the two basic methods used to summarize news. The process of extractive summarization entails locating and separating the key phrases from the source text. In this paper, sentence weighting is used for extractive summarization. The words in the headlines are given ten times more emphasis than the other words in the news article. The final summarization is done by rearranging the sentences as per the sequence in the main news article. The paper concludes by discussing the future of news summarization, which is an active area of research.

关键词： Analytical models Computational modeling Text summarization Information retrieval Natural language processing Computational efficiency Complexity theory Data mining

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Nirnayaak: Revolutionizing Legal Research

Nirnayaak: Revolutionizing Legal Research

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International Conference on computer, Communication, Control and Information Technology (C3IT)

作者： Soumyajit Datta Arya Chakraborty Saptarshi Bhattacharya Amit Samui Anurag Chakraborty Kousik Dasgupta Dept. of Computer Science and Engineering Kalyani Government Engineering College Kalyani India

ISBN: (数字)9798350389128

ISBN: (纸本)9798350389135

Nirnayaak is a novel and advanced legal software application, that is meticulously designed to expedite the retrieval of crucial legal information in an Indian Context, addressing the challenges posed by a growing caseload and inaccuracies in the legal system. Employing a groundbreaking architectural framework, it leverages OCR, Smart Text preprocessing, keyword extraction, a sophisticated LLM-based summarization and information retrieval and a feedback-based keyword ranking technique. This amalgamation of techniques enhances the accuracy and accessibility of legal data, enabling legal professionals, scholars, and the public to access pertinent information seamlessly just using natural language queries. We conducted benchmarks on popular keyword extraction techniques, demonstrating that our preprocessing techniques enhance their performance. Additionally, we evaluated LLMs to ascertain their proficiency in understanding contextual nuances.

关键词： Accuracy Law Optical character recognition Natural languages Benchmark testing Information retrieval Data mining Information technology

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Efficient Hyperspectral Data Compression using 3D Convolutional Autoencoder

Efficient Hyperspectral Data Compression using 3D Convolutio...

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International Conference on Advancement in Electrical and Electronic engineering (ICAEEE)

作者： Afsana Afrin Md. Al Mamun Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798350388282

ISBN: (纸本)9798350388299

Hyperspectral image has large size due to abundance of spectral bands preventing efficient storage and transmission in real-time applications. This paper introduces a 3dimensional convolutional autoencoder (CAE) for hyperspectral data compression, utilizing CAE for both compression and subsequent decompression. Our method achieves improved Compression Ratio (CR) values of 982 and 960 on the KSC and Botswana datasets, along with better Peak Signal-to-Noise Ratio (PSNR) results of 55.29 and 52.64, surpassing existing 2D convolutional autoencoder-based HSI compression. Our approach also shows negligible differences in classification accuracy between original image and the reconstructed version of the compressed image, confirming its effectiveness in real-world applications.

关键词： Solid modeling Image coding Accuracy Three-dimensional displays PSNR Recurrent neural networks Convolution

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Efficient Optimization in Dispensation of Cloud applications using Novel Stochastic Gradient with Forward Back Propagation Algorithm

Efficient Optimization in Dispensation of Cloud applications...

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Pervasive Computing and Social Networking (ICPCSN), International Conference on

作者： Anithaashri T.P V. Loganathan R. Lalitha Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Dept of Computer Science and Engineering Saveetha Engineering College Chennai Tamil Nadu India Dept of Computer Science and Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India

ISBN: (数字)9798350386349

ISBN: (纸本)9798350386356

The effective use of cloud server is a major challenge in the recent days. To handle the computation speed, space complexity, network accessibility is playing vital role in achieving the efficiency of cloud server. The objective is to obtain the energy efficiency in cloud servers using a novel stochastic gradient with forward back propagation algorithm. Two sample groups with number of iterations 20 each have been tested with G-power of 80% with the total sample size of 360, divided into two groups with Group 1=180, Group 2=180 and an independent sample t-test has been done. To improve the accuracy of energy optimization, a novel stochastic gradient with forward back propagation algorithm is proposed and compared with the machine learning algorithm. The results prove that the novel stochastic gradient with forward back propagation algorithm has a high accuracy of 92.1%, which is significantly better than the other machine learning algorithms. The level of significance p=0.02 (p<0.05) shows that there is a significant difference between these two algorithms. Thus, the cloud server optimization is achieved using stochastic gradient with forward back propagation algorithm through various testbeds.

关键词： Backpropagation Pervasive computing Data centers Machine learning algorithms Accuracy Costs Social networking (online)

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Earth Pit Monitoring System for Petrol Pumps

Earth Pit Monitoring System for Petrol Pumps

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IoT Based Control Networks and Intelligent Systems (ICICNIS), International Conference on

作者： Sunitha Guruprasad Amulya Nikitha Glen Rebello Calisha Noronha Elena Madtha Dept. of Computer Science & Engineering St Joseph Engineering College Mangaluru India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

The oil industry is constantly seeking ways to monitor their facilities and equipment in a systematic way with as little human intervention as possible. Currently, monitoring of earth pits is done manually. The Hindustan Petroleum Corporation Limited (HPCL) Earth Pit Monitoring App is a mobile application that aims to enable HPCL staff to securely log in and monitor their petroleum storage sites and earthing pits. This app will make it easier to monitor all aspects of their operations, including vendors and petrol pump dealers, with timely alerts for any necessary maintenance checks. The research conducted on the modern type of earthing will be beneficial for the petroleum outlets as maintenance time and cost would be reduced due to its durability. Field research at HPCL Petroleum Outlets were conducted to observe the state of earth pits and the method of earthing used. Chemical earthing is a method of grounding electrical equipment by pouring a mixture of bentonite and graphite around a copper or iron rod driven into the ground, creating a low-resistance path for electrical charge to dissipate into the earth. It is used in areas with high soil resistance and where traditional earthing methods are not feasible. Comparison between the GI Earthing used currently, and the Chemical Earthing was drawn by comparing resistance values under different conditions.

关键词： Earth Systematics Grounding Maintenance Personnel Internet of Things Monitoring Petroleum Chemicals Immune system

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Compact Raspberry PI Server with Integrated UPS

Compact Raspberry PI Server with Integrated UPS

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Hemachandran A S Nithyabharathi S Dept. Computer Science Engineering IFET College of Engineering Villupuram Tamilnadu India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

This paper designs and implements a compact server system based on the Raspberry Pi 4B and tailored to specific low-end and budget-constrained environments, such as home offices and small businesses, through the integration of an uninterruptible power supply (UPS) in the system to ensure continuous operation during periods of power failure. Important features include VPN for secure remote access, an ad blocker to increase the efficiency of browsing, a private NAS system with data management in a secured and easily accessible manner, and video streaming capabilities to meet multimedia requirements. Real-time performance monitoring comes through with an OLED display. The paper reflects an integrated approach combining hardware and software components which stress system flexibility, low costs, and reliability. This compact server system allows an efficient, user-friendly, and flexible server infrastructure at small scale by providing a cost-effective alternative to traditional server solutions.

关键词： Streaming media Organic light emitting diodes Hardware Software Real-time systems Virtual private networks Software reliability Servers Uninterruptible power systems Stress

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