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3rd international conference on Advancements in Smart computing and Information Security, ASCIS 2024

ISBN: (纸本)9783031862892

The proceedings contain 28 papers. The special focus in this conference is on Advancements in Smart computing and Information Security. The topics include: Prediction of Anti-Cholinesterase Inhibitor for Alzheimer Disease Using Machine Learning Techniques;scrutinize Search Engine Optimization Strategies with artificial intelligence to Rank a Website;a Study on Machine Learning algorithms: Forecasting Crop Prices;improving Student Stress Analysis: Novel Methods for Collecting, Preprocessing, and Fusing Features;extraction of Normal and Abnormal Region in Colposcopy Image to Support Cervical Cancer Clinical Decision;optimizing Pricing Strategies: A Comprehensive Framework Using Bayesian Inference and Game Theory;hybrid Ensemble Gradient Boosting Algorithm to Predict Diabetes Health Care Analytics;a Review on Machine Learning algorithms for Real-Time Traffic Management;hyperparameter-Tuned Intention Mining for Mental Health Diagnosis Using Logistic Regression;machine Learning for Accessible and Precise Assessment in Smart Monitoring Systems;an Efficient Model for Academic Performance Prediction of the University Students;comprehensive Comparative Study on Data Mining and Machine Learning Approaches for Fraud Detection in Financial Services;prediction of Stock Price and Detection of Stock Market Trends Using Adaptive Learning Techniques;asthma Prediction Using Fuzzification and Machine Learning Based Ensemble Classifier;detection and Analysis of Features of Optic Nerve Head Using Retinal Fundus Images of an Eye for a Priori Prediction of Glaucoma;a Hybrid Deep Learning Framework for Uncertain Supply Chains: An Optimization Approach;a Comprehensive Review of Machine Learning Techniques in Recommender System for E-Commerce Platform;Ethics of AI in the Educational Sector - Navigating the Moral Landscape;international Law and AI Interface.

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Fossa Optimization Algorithm with Convolution Neural Network Based Brain Tumor Segmentation and Classification in MRI Images

Fossa Optimization Algorithm with Convolution Neural Network...

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Integrated Circuits and Communication Systems (ICICACS), IEEE international conference on

作者： Veeresh Shivaprakash Ramy Read Hossain Aruna T M Tatiraju.V.Rajani Kanth Sir M Visvesvaraya College of Engineering Raichur India Affiliated to Visvesvaraya Technological University Belagavi India Government Engineering College Raichur India Visvesvaraya Technological University Belagavi India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Artificial Intelligence and Machine Learning Nitte Meenakshi Institute of Technology Bengaluru India TVR Consulting Services Private Limited Gajularamaram Hyderabad India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Magnetic Resonance Image (MRI) brain tumor segmentation is critical and significant in a clinical field that assist in diagnosis, complete growth prediction and tumor mass rates required for patients. The complexity in segmenting brain tumors are challenging due to the various structures, shapes, locations, visual characteristics, frequency, texture and contrast. To overcome this issue, this research proposes a Fossa Optimization Algorithm (FOA) with Convolution Neural Network (CNN) for brain tumor classification. The Geodesic Active Contour (GAC) is used for segmentation which identifies tumor boundaries precisely in noisy and intricate data. FOA utilizes dynamic search strategy by its hunting behavior, balancing exploration and exploitation effectively. Its adaptive step size enables better convergence when avoiding local optima. Furthermore, its ability to capture edges and patterns makes it effective for classification. CNN are better to diverse in scale, noise and rotation because of its shared weights and local connectivity reduce the complexity thereby leading to higher accuracy and quick processing in classification. The FOA-CNN obtains 99.92% accuracy, 99.20% f1-score, 99.07% sensitivity and 99.34% precision for BRATS2020 dataset which is superior than Spatial Transformer Network and Non-local Attention Mechanism (STN-NAM).

关键词： Image segmentation Accuracy Sensitivity Convolution Brain tumors Search problems Classification algorithms Complexity theory Optimization Biological neural networks

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3rd international conference on Advancements in Smart computing and Information Security, ASCIS 2024

3rd International Conference on Advancements in Smart Comput...

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3rd international conference on Advancements in Smart computing and Information Security, ASCIS 2024

ISBN: (纸本)9783031862922

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Overview on Quantum computing and its Applications in artificial intelligence 3

Overview on Quantum Computing and its Applications in Artifi...

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3rd IEEE international conference on artificial intelligence and Knowledge Engineering AIKE 2020

作者： Abdelgaber, Nahed Nikolopoulos, Chris Bradley Univ Comp Sci & Informat Syst Peoria IL 61625 USA

ISBN: (纸本)9781728187082

This paper will review the basic building blocks of quantum computing and discuss the main applications in artificial intelligence that can be addressed more efficiently using the quantum computers of today. artificial intelligence and quantum computing have many features in common. Quantum computing can provide artificial intelligence and machine learning algorithms with speed of training and computational power in less price. artificial intelligence on the other hand can provide quantum computers with the necessary error correction algorithms. Some of the algorithms in AI that have been successfully implemented on a quantum computer, that we will present in this paper, are both unsupervised learning algorithms (clustering and Principal component analysis) and also supervised learning classification, such as support vector machines.

关键词： Machine Learning PCA Quantum computing SVM

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Puzzles, art, and magic with algorithms

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THEORY OF computing SYSTEMS 2006年第3期39卷 473-481页

作者： Demaine, ED Demaine, ML MIT Comp Sci & Artificial Intelligence Lab 77 Massachusetts Ave Cambridge MA 02139 USA

Solving and designing puzzles, creating sculpture and architecture, and inventing magic tricks all lead to fun and interesting algorithmic problems. This paper describes some of our explorations into these areas.

关键词： algorithms LOGARITHMS GAMES in mathematics education LOGIC puzzles MAGIC tricks in mathematics education MATHEMATICAL analysis

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Providing Cyber Security using artificial intelligence - A survey 3

Providing Cyber Security using Artificial Intelligence - A s...

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3rd international conference on computing Methodologies and Communication (ICCMC)

作者： Sagar, B. S. Niranjan, S. Kashyap, Nithin Sachin, D. N. Vidyavardhaka Coll Engn Dept Comp Sci & Engn Mysore Karnataka India

ISBN: (纸本)9781538678084

artificial intelligence is really a kind of computerized version of human intelligence. The way artificial intelligence works is like learning iteratively again and again, just like humans. In this generation, the threat of landscape is unquestionably evolving. The cyber attackers are entirely focused on financial rewards. But the department has found a new way to prevent attacks before they occur, as the old traditional way can no longer be relied upon. This paper introduces the need for the development of cybersecurity skills and how artificial intelligence can be implied to improve skills through the use of artificial neural networks and machine learning algorithms.

关键词： artificial intelligence Cybercrime Cyber-attacks Cyber Security

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A Survey on artificial intelligence Models for Endometrial Tumor Detection, Classification and Diagnosis

A Survey on Artificial Intelligence Models for Endometrial T...

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3rd international conference on Advancements in Smart computing and Information Security, ASCIS 2024

作者： Karthick, N. Nithya, P. Department of Computer Applications Sri Krishna Arts and Science Tamil Nadu Coimbatore641041 India Department of Networking and Mobile Application PSG College of Arts and Science Tamil Nadu Coimbatore641041 India

ISBN: (纸本)9783031862922

An Endometrial Tumor (ET) is a common uterine disease that continues to play a significant role in the mortality linked to a tumor. Advanced ET diagnosis exhibits worse diagnostic accuracy. The medically used ET screening methods require a significant amount of time and money, and not all patients can easily access them. So, oncologists have focused huge attention on molecular modeling as it has grown quickly, which has sped up the invention of computer-aided tumor detection systems. artificial intelligence (AI) models offer possibilities for molecular diagnostics, early tumor classification, efficient diagnosis, and diagnosis modality selection. It may be especially pertinent to use AI models in ET detection, classification, and diagnosis. From this perspective, researchers have been actively developing and implementing AI models to create effective ET diagnostic systems. This article studies the background of ET characteristics and earlier diagnosis techniques to stimulate further research in this field. The review is planned to investigate AI models, such as Machine Learning (ML) and Deep Learning (DL) algorithms, for ET detection, classification, and diagnosis. After that, the positives and negatives of each classification model, such as Logistic Regression (LR), Support Vector Machine (SVM), Deep Neural Network (DNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) networks, are compared. Amongst them, a multi-modal CNN-LSTM model achieves 93% accuracy on the TCGA-UCEC dataset, compared to the other models. At last, promising prospects are emphasized to achieve greater efficiency in classifying and diagnosing ET. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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DDoS Detection and Prevention Based on artificial intelligence Techniques 3

DDoS Detection and Prevention Based on Artificial Intelligen...

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3rd IEEE international conference on Computer and Communications (ICCC)

作者： Zhang, Boyang Zhang, Tao Yu, Zhijian Beijing Univ Posts & Telecommun Int Sch Beijing Peoples R China Geely Automobile Res Inst Ningbo Zhejiang Peoples R China Beijing Univ Posts & Telecommun Sch Econ & Management Beijing Peoples R China

ISBN: (纸本)9781509063529

DDoS attacks have been the major threats for the Internet and can bring great loss to companies and governments. With the development of emerging technologies, such as cloud computing, Internet of things, artificial intelligence techniques, attackers can launch a huge volume of DDoS attacks with a lower cost, and it is much harder to detect and prevent DDoS attacks. Because DDoS traffic is similar to normal traffic. Some artificial intelligence techniques like machine learning algorithms have been used to classify DDoS attack traffic and detect DDoS attacks, such as Naive Bayes and Random forest tree. In the paper, we survey on the latest progress on the DDoS attack detection using artificial intelligence techniques and give recommendations on artificial intelligence techniques to be used in DDoS attack detection and prevention.

关键词： DDoS detection prevention artificial intelligence machine learning

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Research and Realization of Einstein Chess Game System and Autoplay Machine Automatic Game 3

Research and Realization of Einstein Chess Game System and A...

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3rd international conference on algorithms, computing and artificial intelligence, acai 2020

作者： Hao, Yiwei Cai, Dian Li, Shuqin School of Computer Beijing Information and Science Technology University Beijing100101 China Sensing and Computational Intelligence Joint Lab Beijing Information and Science and Technology University Beijing100101 China

ISBN: (纸本)9781450388115

Einstein Chess is a small game where winning chess depends on "luck". A good "luck"is supported by many complicated algorithms. One of the innovations of this article is to use TCP/IP socket technology to realize automatic computer game and provide higher efficiency for code *** second is that this article designs and implements three Einsteins game algorithms: a completely random chess strategy, a chess strategy based on a static evaluation function, and a dynamic chess strategy based on UCT. Experimental results show that the dynamic evaluation function based on UCT is better than the other two algorithms, and won the first prize in the 2020 Chinese University Student Computer Game Competition. © 2020 ACM.

关键词： Computer games

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Research on Anti-telecom Fraud Based on artificial intelligence and Edge computing 3

Research on Anti-telecom Fraud Based on Artificial Intellige...

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3rd IEEE international conference on Electrical Engineering, Big Data and algorithms, EEBDA 2024

作者： Fang, Peng Fang, Qinguo Design Institute Co. LTD. Shandong Branch of China Mobile Communication Group Jinan China

ISBN: (纸本)9798350380989

This paper studies the artificial intelligence method based on the collaboration of edge and terminal, integrates the complementary advantages of the local computing and strong computing power of the two, realizes the characteristic recognition of telecom fraud behavior, and realizes the accurate and real-time anti-telecom fraud. By constructing a telecom fraud identification and defense system based on deep learning, the whole life cycle from post-analysis to pre-warning, in-process reminder and even blocking, post-monitoring feedback is realized, and the level of anti-telecom fraud technology is improved. © 2024 IEEE.

关键词： anti-telecom fraud artificial intelligence edge computing

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