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Stock Market Trading Based on Market Sentiments and Reinforcement Learning

computers, Materials & Continua 2022年第1期70卷 935-950页

作者： K.M.Ameen Suhail Syam Sankar Ashok S.Kumar Tsafack Nestor Naglaa F.Soliman Abeer D.Algarni Walid El-Shafai Fathi E.Abd El-Samie Department of Computer Science&Engineering NSS College of EngineeringPalakkad678008KeralaIndia Department of Electronics and Communication Engineering NSS College of EngineeringPalakkad678008KeralaIndia Unitéde Recherche de Matière Condensée D’Electronique et de Traitement du Signal(URAMACETS)Department of PhysicsUniversity of DschangP.O.Box 67DschangCameroon Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Stock market is a place,where shares of different companies are *** is a collection of buyers’and sellers’*** this digital era,analysis and prediction in the stock market have gained an essential role in shaping today’s *** market analysis can be either fundamental or *** analysis can be performed either with technical indicators or through machine learning *** this paper,we report a system that uses a Reinforcement Learning(RL)network and market sentiments to make decisions about stock market *** system uses sentiment analysis on daily market news to spot trends in stock *** sentiment analysis module generates a unified score as a measure of the daily news about *** score is then fed into the RL module as one of its *** RL section gives decisions in the form of three actions:buy,sell,or *** objective is to maximize long-term future *** have used stock data of Apple from 2006 to 2016 to interpret how sentiments affect *** stock price of any company rises,when significant positive news become available in the public *** results reveal the influence of market sentiments on forecasting of stock prices.

关键词： Deep learning machine learning daily market news reinforcement learning stock market

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A Novel approach for Data mining Classification using J48DT Classifier for Intrusion Detection system 11

A Novel approach for Data mining Classification using J48DT ...

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11th IEEE International Conference on communication systems and Network Technologies, CSNT 2022

作者： Manimegalai, T. Ravishankar, T. Nadana Kannagi, L. Kannan, K. Anitha, G. School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Data Science and Business System Srm Institute of Science and Technology Chennai Kattankulathur India Department of Computer and Communication Engineering Sri Sairam Institute of Technology Chennai India Department of Ece R.M.K. College of Engineering and Technology Puduvoyal Chennai India Department of Ece Saveetha School of Engineering Simats Chennai India

ISBN: (纸本)9781665480383

Because of the growing quantity of network traffic that is being transmitted across the network in today's modern era, network attack detection has become a necessity. The technique of data mining is extremely important in the hunt for network assaults and anomalies. These strategies aid in the selection and refinement of meaningful and relevant knowledge from enormous data sets, which is beneficial in many situations. The process of data mining aids in the categorisation of important information for Intrusion Detection systems (IDS). The IDS provides warnings for the network traffic informing it of any foreign intrusions into the network. We show how different data mining methods may be used for intrusion detection to offer a safe network environment in the research article. The J48DT Classifier is utilised for classification in this case. Comparisons based on characteristics such as data accuracy, the discovery of valuable patterns, and the extraction of useful information between approaches are made. © 2022 IEEE.

关键词： Intrusion detection

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Analysis Intention to Use of Smart Tourism Application with Model Extended UTAUT 2 Approach 8

Analysis Intention to Use of Smart Tourism Application with ...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Fernando, Erick Ikhsan, Ridho Bramulya Parlindungan, Davis Roganda Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Information System Tangerang Indonesia Binus Online Learning Bina Nusantara University Management Department Jakarta11480 Indonesia Institut Teknologi Dan Bisnis Kalbis Communication Science Jakarta13210 Indonesia

ISBN: (纸本)9798350326093

The development of information technology currently provides great opportunities for tourism and tourist businesses. All developments provide useful application effectiveness for tourists. Therefore, it is important and useful to explore the factors that influence the intention to use tourism applications among tourists. This study aims to understand the basic factors that influence user intentions to adopt and use smart tourism applications among college students. This study uses 61 indicators with nine constructs to form the proposed research model on the basis of the Extended UTAUT2 model. This study used an online survey using Google Forms with the results of 278 valid and appropriate respondents. Analysis was performed with 278 data using SMART PLS 4.0. The analysis of testing the fit model shows that the results are good, namely R2 of 0.743. Also, found that of the eight hypotheses designed six hypotheses were not supported, namely Performance Expectancy, Hedonic Motivation, Effort Expectancy, Social Influence, Facilitating Conditions, and habit, which had no effect on tourist Behavior Intention. Two hypotheses were supported, namely, that deal proneness and pricing value have a crucial impact in raising tourist intention to utilize the application. The application provides easy transaction services with various payment methods, fast payments, high security for transaction convenience, provides promotional offers, and rewards. So, the tourist industry in developing tourism applications can fulfill users' wishes. © 2023 IEEE.

关键词： Tourism

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Study of Smart City Compatible Monolithic Quantum Well Photodetector 3rd

Study of Smart City Compatible Monolithic Quantum Well Photo...

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3rd EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2022

作者： Pareek, Prakash Maurya, Naveen Kumar Singh, Lokendra Gupta, Nishu Reis, Manuel J. Cabral S. Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram534202 India Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522002 India Department of Electronic System Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Gjøvik2815 Norway Engineering Department UTAD/IEETA Vila Real5001-801 Portugal

ISBN: (纸本)9783031289743

This work is focused on the exploration of the potential of Group IV alloy based nanostructured photodetector which can perform well in smart city environment. The theoretical model for multiple quantum well detector based on Germanium Tin (GeSn) alloy working in short wave infrared range (SWIR) is proposed after considering various design aspects. In this work, detectivity is estimated for SiGeSn/GeSn based interband multiple quantum well infrared photodetector. Detectivity is calculated by using responsivity and dark current, assuming appropriate conditions. After calculation, it is studied under variation of some important parameters. The result reveals the enhancement of detectivity with number of wells. It also indicates that the low biasing range is quite sufficient to make the proposed device work efficiently. Moreover, peak detectivity in the tune of 109 cm Hz1/2 W−1 is attained. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Tin alloys

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Initial Study of Oil Palm Crop Condition Detection Through Drone Imagery: A YOLO Approach

Initial Study of Oil Palm Crop Condition Detection Through D...

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International Conference on Informatics, Multimedia, Cyber and Information system (ICIMCIS)

作者： Winata Nugraha Ermatita Deris Stiawan Faculty of Computer Science Doctoral Program Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Department of Information System Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Oil palm plantations in Indonesia still have many challenges, especially in terms of monitoring and mapping technology. One of the important aspects in the monitoring stage of oil palm plantations is monitoring the productivity of oil palm plants. To identify the oil palm plants, many previous studies have utilized image analysis to solve the problem. The problem is that poor image conditions can affect the architecture model to be built.[1] So in this research we do tune mapping on the image to produce a quality image. Each image data that has been improved will be feature extracted using ResNet and VGG to produce the best model. Furthermore, the classification model development process is carried out using CNN architecture as the model architecture. We also provide innovation by using object detection technology. Which uses artificial neural networks. Here we train the model using aerial video datasets of oil palm plants obtained from drones. Furthermore, to evaluate the performance of the above technique, it is proposed to use the mapping model, precision and accuracy evaluation obtained in the test phase[2]

关键词： YOLO Productivity Technological innovation Oils Multimedia systems Plantations Feature extraction Informatics Monitoring Drones

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Towards Real Time Traffic Analysis with Reduced Image Quality

Towards Real Time Traffic Analysis with Reduced Image Qualit...

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IEEE India Conference (INDICON)

作者： Rohit Mohanraj Erunika Oshani Dayaratna Department of Electronics and Communication Engineering National Institute of Technology Warangal Warangal India Department of Statistics and Computer Science Faculty or science University of peradeniya SriLanka

ISBN: (数字)9798350391282

ISBN: (纸本)9798350391299

This paper presents a detailed study of two computationally efficient object recognition models-YOLOv5 and Fast R-CNN with a MobileNet backbone-focusing on their performance under different degrees of image / video qualities. Blurring is a common problem in autonomous driving due to motion, weather conditions, and other factors, which can greatly reduce picture quality and, consequently, the accuracy of object recognition. Also, the low-quality images produced by on-car devices suffer when trying to utilize them for advanced detection applications. Utilizing the Zenseact Open Dataset (ZOD), images are generated by varying kernel sizes of Gaussian blur to examine how each model's recognition accuracy is affected by picture degradation. Our study shows key differences in the stability of these models, showing the trade-offs between processing speed and recognition confidence in poor visual settings. The results provide helpful guidance for choosing object recognition systems that keep performance in difficult situations, crucial for the safety and efficiency of driverless cars.

关键词： YOLO Performance evaluation Degradation Training Adaptation models Visualization Accuracy Real-time systems Object recognition Video recording

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Design and Implementation of Flutter Based Multi-Platform Docker Controller App

Design and Implementation of Flutter Based Multi-Platform Do...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Saxena, Adarsh Singh, Sudhakar Prakash, Shiv Yadav, Nand Lal Yang, Tiansheng Rathore, Raikumar Singh Singh, Shreya University of Allahabad Department of Electronics and Communication Prayagraj India University of South Wales Faculty of Business and Creative Industries Pontypridd United Kingdom Cardiff School of Technologies Cardiff Metropolitan University Cardiff United Kingdom Institute of Engineering and Technology Department of Computer Science & Engineering Dr. A.P.J. Abdul Kalam Technical University Lucknow India

ISBN: (纸本)9798350369106

This paper focuses on developing a Flutter application for controlling Docker resources remotely. The application provides a user-friendly interface for executing various Docker-related commands on the server where the Docker engine is installed. The application uses the SSH protocol to establish a secure connection with the server and execute the commands. Further, an alternative approach is also explored, which involves connecting the application with the Docker engine using HTTP. This proposed Docker controller application provides a significant advantage for managing Docker resources remotely, which is highly beneficial in DevOps fields. It provides a user-friendly interface to manage containers, making it easy to create, start, stop, restart, and remove containers. It abstracts away the complexities of working with Docker commands, allowing users to interact with containers more intuitively. It can be used to manage a number of docker engines from one place making it easy to control and monitor all the docker resources. Its performance, security, and scalability are evaluated using various testing techniques, and the results are found satisfactory. Further improvements may include enhancing the application's features, optimizing the performance, and exploring other possible approaches for establishing the connection between the application and the Docker engine. © 2024 IEEE.

关键词： HTTP

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Colour Image Cryptography using Chaotic Pixel Shuffling and 3D Logistic Diffusion 4

Colour Image Cryptography using Chaotic Pixel Shuffling and ...

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4th International Conference on Information Management and Machine Intelligence, ICIMMI 2022

作者： Ravi, Renjith V Goyal, S.B. Singla, Sanjay Department of Electronics and Communication Engineering M.E.A Engineering College Kerala Malappuram India Faculty of Information Technology City University Petaling Jaya Malaysia Department of Computer Science and Engineering Uie Chandigarh University Punjab Mohali India

ISBN: (纸本)9781450399937

All types of multimedia data, including digital images, audio, text, and video, are now easily accessible on the internet due to the phenomenal growth of internet services and wireless telecommunication systems, including mobile and computer systems, in order to achieve a specific degree of security, integrity, and secrecy as well as to prevent malicious access to the information. In contrast, for data storage and transmission, cryptographic procedures are necessary. This study presents brand-new, very effective colour image encryption and decryption algorithms that use diffusion and pixel scrambling. At first Zig-Zag permutation was used to scramble the data. Then, by concealing the statistical makeup of the pixels, the two-dimensional Lozi map is used to distort further the connection between neighbouring pixels in the original image. Furthermore, the diffusion in three colour channels is accomplished using a 3D logistic map. During the decryption process, the image pixels are again moved back to their original positions. The chaotic mapping technique encrypts images to reduce the correlation between encrypted and unencrypted versions. As described in this study, the tested and examined encryption algorithm on certain colour photos showed substantial security and authenticity to resist statistical and differential cyber attacks. © 2022 ACM.

关键词： Pixels

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Diagnosis Expert system on Breast Cancer Using Fuzzy Logic and Clustering Technique 5th

Diagnosis Expert System on Breast Cancer Using Fuzzy Logic a...

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5th International Conference on Information systems and Management science, ISMS 2022

作者： Awotunde, Joseph Bamidele Sisodia, Dilip Singh Ayodele, Peace Ayomide Ogundokun, Roseline Oluwaseun Chouhan, Virendra Singh Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria National Institute of Technology Raipur Raipur India Department of Multimedia Engineering Kaunas University of Technology Kaunas44249 Lithuania Manipal University Jaipur India

ISBN: (纸本)9783031311529

The disease of breast cancer is now widespread throughout the world. Expert systems are useful tools that have been effective in the diagnosis of various diseases. Therefore, this paper develops an expert system for diagnosis and detection of breast cancer using fuzzy logic enabled with clustering classifier. The fuzzy logic provides a bridge in improving the classification and detection accuracy of breast cancer disease. To balance out the dataset and avoid the costly overhead of collecting and labeling a large set of training tuples or patterns, clustering was utilized for data segmentation. The classifier can then make use of data of each group in terms of how similar they are. These tools have been developed to improve and alter the current expert systems, increasing their usefulness for the reasons for which they were designed. The fuzzy rule-based method includes expert knowledge to address the patient's ailment and render a reliable judgment in accordance with established rules. The proposed model can be applied as a clinical decision support tool to help healthcare professionals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Diseases

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Design of IoT based physical protection system for nuclear facility 2

Design of IoT based physical protection system for nuclear f...

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2nd IEEE International Conference on Electronic engineering, ICEEM 2021

作者： Ateya, Muhammad Z. El-Din Hemdan, Ezz El-Samie, Fathi E. Abd Egypt Menoufia University Faculty of Electronic Engineering Department of Computer Science and Engineering Egypt Menoufia University Faculty of Electronic Engineering Department of Electronics and Communication Engineering Egypt

ISBN: (纸本)9781665418423

Radioactive materials are an attractive target for terrorist or criminal groups, because they can be used throughout the world in applications including agriculture, industry, medicine, scientific research, transport, and water desalination. Criminals can build dirty bombs by using these radioactive materials. The dirty bomb has harmful consequences on humanity. Keeping radioactive materials from any malevolent human attack is a must. Therefore, this work aims to strengthen the Physical Protection system (PPS) in nuclear facilities against criminal activities. This system works to provide the detection function of adversary actions through integrating various components. These components include Internet-of-Things (IoT) controller, magnetic sensors, vibration sensors, and Passive Infra-Red (PIR) motion detection sensors with cloud-based IoT platform and mobile application for monitoring and auditing purposes, remotely. The proposed work is intended for securing nuclear facility that contains radioactive materials through detection using various sensors and IoT controllers. A controller detects trigger signals from any sensor, an alarm and warning signs are sent to the dashboard and smartphone over the Internet. © 2021 IEEE.

关键词： Internet of things

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