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AI Financial Adviser Performance and Monitoring of AI Derived Stocks

AI Financial Adviser Performance and Monitoring of AI Derive...

引用

2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： McGuire, Dean Jenkins, Paul Cardiff Metropolitan Univ Llandaff CampusWestern Ave Cardiff CF5 2YB Wales

ISBN: (纸本)9783031744426;9783031744433

With the recent release of Chat GPT in November 2022, AI has been a prevalent topic in the mind of the public, as they are concerned about a range of different factors from, it is replacing work of the population, or indeed their lives. This paper investigates how AI has impacted the financial markets and it compares current and past financial advisers. It explains the strengths and weaknesses of having AI within financial markets, suggesting solutions for current and future problems that AI will pose in these markets. The paper reviews a range of current financial advisers and their websites establishing how they utilize AI. In addition, the paper examines the construction of a monitoring website for financial markets. The paper is organized as follows: Sect. 1: Introduction, Sect. 2: Related Work;Sect. 3: Evaluation of AI vs Human Adviser;Sect. 4: Monitoring Website;Sect. 5: Conclusions and further work.

关键词： FinTech AIEQ SP&500 Web Development Widgets Chatbots

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Machine Learning-Based systems for Intrusion Detection in VANETs

Machine Learning-Based Systems for Intrusion Detection in VA...

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Intelligent systems Conference

作者： Idris, Hala Eldaw Hosni, Ines Jouf Univ Collage Comp & Informat Sci Sakaka Al Jouf Saudi Arabia

ISBN: (纸本)9783031664304;9783031664311

It is critical to identify attacks in Vehicle Ad-hoc networks (VANETs) in order to provide more dependable and safe communication amongst all of the system's cars. One of the most important parts of the Internet-connected VANETs is the Intrusion Detection System (IDS), which requires dependable and secure communication between all of the system's vehicles. In this study, vehicle network attacks that significantly compromise system availability, such as spoofing, flooding, denial-of-service (DoS), replaying attacks, benign packets, and evil twins are anticipated and identified using a VANET IDS. Influencing artificial intelligence is a superb method for developing network intrusion detection (Deep Learning). Influencing artificial intelligence is a superb method for developing network intrusion detection (Deep Learning). This is due to the algorithms' ability to pick up on complex VANET activities, which they then apply to recognize and block threats to the vehicle network. In order to recognize intrusions and attacks in car networks, we have used a DNN deep method in this study to develop an auto encoder. Regarding the attack types in the dataset that involve flooding, impersonation, and injection, the suggested VIDS demonstrates an accuracy of 99%, yielding remarkably good results.

关键词： VANET Deep learning Vehicles intrusion detection system Attack detection

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RAG-Based Question-Answering systems for Closed-Domains: Development of a Prototype for the Pollution Domain

RAG-Based Question-Answering Systems for Closed-Domains: Dev...

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Intelligent systems Conference

作者： Soto-Jimenez, Fabian Martinez-Velasquez, Mateo Chicaiza, Janneth Vinueza-Naranjo, Paola Bouayad-Agha, Nadjet Univ Tecn Particular Loja Loja Ecuador Univ Nacl Chimborazo Riobamba Canton Ecuador Univ Oberta Catalunya Barcelona Spain

ISBN: (纸本)9783031663284;9783031663291

In recent years, question-answering (Q&A) systems have become essential tools for combating misinformation and providing specific information to answer users' questions. In this paper, we introduce the design of a Q&A system based on a retrieval augmented generation approach. This approach combines the power of semantic retrieval models to find relevant information from large textual corpora and the ability of pre-trained language models to process natural language and generate new answers. The workflow connects retrieved documents from an updated database containing domain-specific information and provides them to the generative module to produce reliable answers for users based on the context. The design of the proposal is notable for its adaptability to different domains, as the system dataset can be iteratively created from updated content based on Wikipedia pages. To test the proposal, we developed a Q&A prototype focused on the pollution domain. Through an iterative approach, the prototype was developed over three iterations, successfully addressing and overcoming key challenges and making significant progress in operational efficiency and answer quality. Based on the preliminary results obtained, the performance of the RAG-based prototype is satisfactory. After evaluating a small subset of questions, only 10% of the answers were not very coherent with the context provided.

关键词： Question-answering systems Close-domain corpus Pre-trained language models Pollution

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LIDia: A Serious Game for Type 1 Diabetes Education 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Amengual-Alcover, Esperanca Mascaro-Oliver, Miquel Caimari-Jaume, Maria Univ Illes Balears Ctra ValldemossaKm 7-5 Palma De Mallorca 07122 Spain Hosp Univ Son Espases Ctra Valldemossa 79 Palma De Mallorca 07120 Spain

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

In this paper an ongoing work whose goal is to develop an educational serious game for type 1 diabetes (T1D) is introduced. A serious game is a video game that has been designed with a main purpose that goes beyond entertainment. The ultimate goal of a serious game is to help users to reach their objective in a playful way through the game. Initially, the target audience is children and/or adolescents with T1D. The first version of the game represents a hypoglycemia situation. The objective is to offer players a tool so that they can learn in an entertaining way to manage the different scenarios that can take place in a situation of hypoglycemia. The goodness of this first version will be validated with patients. It is intended to evolve the video game in future versions that will expand the functionality of the game with new aspects related to diabetes education. The ultimate goal is to cover as many scenarios as possible to offer patients an educational tool that helps them to better control diabetes and improve their quality of life.

关键词： type 1 diabetes mellitus serious games diabetes self-management

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A Comprehensive Study on Security and Privacy of E-Health Cloud-Based System 1

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13th Computer Science Online Conference

作者： Ali, Sadaquat Univ Warwick WMG Cyber Secur Ctr Coventry W Midlands England

ISBN: (数字)9783031703003

ISBN: (纸本)9783031702990;9783031703003

Today, a growing number of individuals and organisations are considering distributing resources in this manner, considering recent technological developments involving "the cloud". Due to the sensitive and critical nature of patient information, IT and networks have not been widely used in healthcare systems for a long period. E-health systems have recently benefited from the high levels of accessibility, ease of access, durability, efficiency, usefulness, and automation of the various cloud models. E-health refers to health services and information provided or improved on the Internet and other techniques. Health information and communication technology (HIT) can improve the delivery locally, regionally, and globally. In this paper, we review different studies based on the security and privacy concerns of electronic health records (EHRs). We also identified different security challenges for data storage in the cloud. Furthermore, in the end of the paper open challenges are discussed with the future predictions of an EHR system. #CSOC1120

关键词： E-health Security Challenges Cloud Computing Health Information and Communication Technologies (HIT)

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Algorithmic Foundations of Reinforcement Learning 1

引用

15th International Conference on Autonomous systems

作者： Pareigis, Stephan Hamburg Univ Appl Sci Dept Informat Berliner Tor 7 D-20099 Hamburg Germany

ISBN: (数字)9783031614187

ISBN: (纸本)9783031614170;9783031614187

A comprehensive algorithmic introduction to reinforcement learning is given, laying the foundational concepts and methodologies. Fundamentals of Markov Decision Processes (MDPs) and dynamic programming are covered, describing the principles and techniques for addressing model-based problems within MDP frameworks. The most significant model-free reinforcement learning algorithms, including Q-learning and actor-critic methods are explained in detail. A comprehensive overview of each algorithm's mechanisms is provided, forming a robust algorithmic and mathematical understanding of current practices in reinforcement learning.

关键词： reinforcement learning MDP markov-decision process dynamic programming deep reinforcement learning SARSA Q-learning DQN REINFORCE A2C PPO DDPG SAC policy gradient methods exploration vs exploitation sparse rewards robotics offline reinforcement learning

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Social Media and Marketing Worldwide 10th

Social Media and Marketing Worldwide

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Dudic, Branislav Mittelman, Alexandra Vojtechovsky, Jaroslav Comenius Univ Fac Management Bratislava 82005 Slovakia Univ Business Acad Fac Econ & Engn Management Novi Sad 21000 Serbia

ISBN: (纸本)9783031662706;9783031662713

Social networks are one of the most used medium of the internet marketing communication, by means of which companies influence the decision making in consumer behaviour of the big group of people around the world. Social neworks have become by gradual technological progress very important medium in the field of marketing communication of companies operating in all sectors of economy. Social networks are able to influence big amount of people in short time and new product that is introduced will be come world wide known. The expression digital marketing is connected to the newest information technologies as following: computer and mobile communication. Facebook, Youtube, WhatsApp, Instagram etc. Belong among the most used social networks.

关键词： marketing socialmedia consumerbehaviour digital marketing communication

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Robustness of Named Entity Recognition Models 19th

Robustness of Named Entity Recognition Models

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19th International Conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Walkowiak, Pawel Wroclaw Univ Sci & Technol Wroclaw Poland

ISBN: (纸本)9783031618567;9783031618574

Transformer based models are gaining popularity on most of the Natural Language Processing (NLP) including sequence labeling task such like Named Entity Recognition (NER). The previous (pre-transformers) state of the art approaches for NER task where models based on Conditional Random Fields (CRF). Adversarial attacks, which involve trying to deceive the model by creating adversarial examples with subtle, almost imperceptible changes, are increasingly posing a threat to all NLP models, including those which solve sequence labeling tasks. When deciding which architecture to use for NER model, robustness of approach could be one of the deciding factors. We are going to examine named entity recognition trained models resilience, focusing on differences between CRF and Transformer based approaches.

关键词： Adversarial Attacks NER Transformer CRF Polish

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Human Activity Recognition Using Convolutional Neural networks 2nd

Human Activity Recognition Using Convolutional Neural Networ...

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2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Awad, Omer Fawzi Ahmed, Saadaldeen Rashid Shaker, Atheel Sabih Majeed, Duaa A. Hussain, Abadal-Salam T. Taha, Taha A. Tikrit Univ Coll Med Dept Surg Tikrit Salahalden Iraq Alayan Univ Coll Engn Artificial Intelligence Engn Dept Nasiriyah Iraq Bayan Univ Comp Sci Dept Erbil Kurdistan Iraq Baghdad Coll Econ Sci Univ Comp Engn Tech Baghdad Iraq Baghdad Univ Aeronaut Engn Dept Baghdad Iraq Al Kitab Univ Tech Engn Coll Dept Med Instrumentat Tech Engn Altun Kupri Kirkuk Iraq Northern Tech Univ Unit Renewable Energy Kirkuk Iraq

ISBN: (纸本)9783031628702;9783031628719

This research addresses human activity recognition (HAR) using a deep learning framework. Particularly convolutional neural networks (CNNs) to identify and categorize human actions using sensor data. Employing a complete dataset containing numerous actions. It features reclining, sitting, standing, and different walking modes. The study applies CNN models to attain the best precision and accuracy. The models' strong performance in these CNN. Constraints in dataset diversity and size could impact real-world applicability. This article asks for more investigation and design. It combines additional sensors and concentrates emphasis on real-time HAR systems. The paper illustrates the potential of deep learning models in HAR.

关键词： CNN Classification Real-time Resnet101 HAR

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Comprehensive Analysis of Feature Extraction Methods for Emotion Recognition on Motor Imagery from Multichannel EEG Recordings 12th

Comprehensive Analysis of Feature Extraction Methods for Emo...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Mohamed, Amr F. Jusas, Vacius Kaunas Univ Technol Studentu 50 LT-51390 Kaunas Lithuania

ISBN: (纸本)9783031602177;9783031602184

Electroencephalogram (EEG) related analyses have a vast extent of enquiries, preliminary from Brain-Computer Interfaces (BCI) on motor imagery tasks, neurotechnology, human-computer interaction, clinical and medical applications, sleep research, as well as the neural basis of emotional recognition and behavioural responses. This study purposely investigates the application of feature extraction methods from the emotion recognition arena against the motor imagery arena, using the electroencephalogram (EEG) data from the BCI Competition IV. As the same methods are used in both fields, binary classification has been embraced, emotion recognition's valence and arousal, using its equivalent motor imageries of left and right classes. Essentially, six EEG feature extraction methods were used in the classification accuracy process, including statistical features, wavelet analysis, higher-order spectra (HOS), Hjorth, fractal dimension (Katz, Higuchi, Petrosian) and three-dimensional combination of fractal, wavelet and Hjorth. Further, the classifier performance methods were the Gaussian radial basis function RBF SVM (GSVM) and the regression tree (CART). Remarkably, the statistical method has better accuracy than the other feature sets, precisely the fractal dimension, which was the highest considering the emotion recognition span. Also, GSVM generally has better accuracy on the BCI IV dataset than CART. By contemplating the novel outcome notices, we can deduce that in the methods used in emotion recognition when applied to motor imagery, unique results are obtained, feature-wise and classifier-wise.

关键词： Electroencephalogram Emotion Recognition Motor Imagery EEG Feature Extraction Brain-Computer Interface

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