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International Symposium on Distributed Computing and Applications to Business, engineering and Science (DCABES)

作者： Qianying Zhang Jin Hang Boxuan Zhang Mengzhong Wei Quanyin Zhu Xiang Li Faculty of Computer & Software Engineering Huaiyin Institute of Technology Huai'an China

ISBN: (纸本)9781665428903

In view of the safety hazards existing on campus, a campus safety detection system based on deep learning behavior recognition, license plate recognition and speed detection is proposed and designed. The design divides the campus safety monitoring system into three functional modules: hazard behavior identification, license plate tracking and vehicle speed measurement, and on this basis, designs the database of storage information and the warning system of speed too fast to realize the monitoring function of campus safety.

关键词： Deep learning Databases Licenses Alarm systems Hazards Velocity measurement Optical character recognition software

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Explainable Artificial Intelligence Solution for Online Retail

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computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan Department of Computer Science University of South AsiaLahore54000Pakistan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the *** permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

关键词： Explainable artificial intelligence online retail neural network random forest regression

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An Efficient Distributed Framework for Secured Multimedia Content Using Cloud Storage

An Efficient Distributed Framework for Secured Multimedia Co...

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computer Technologies (ICCTech), International Conference on

作者： Yunus Parvej Faniband Iskandar Ishak Fatimah Sidi Marzanah A. Jabar Deloria Shaniska Razin C. H. Yap Center for Communication & IT Research Research Institute King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Computer Science Faculty of Computer Science and Information Technology Universiti Putra Malaysia UPM Serdang Selangor Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Putra Malaysia UPM Serdang Selangor Malaysia

Applications that support multimedia data such as medical pictures and videos, video broadcasting, and secure video conferencing consume vast quantities of information that require large numbers of servers to provide services for the many client users who access them. Cloud-based sensitive data becomes increasingly important for the respective users to be kept confidential without infringing confidentiality, integrity, and availability. We propose a framework based on the OpenStack cloud-computing platform for multimedia data security. A prototype framework with a helper tool EncSwift is implemented, which allows stringent data access control and applying the data-at-rest Over-Encryption approach. The implementation is evaluated for computation of cryptography operations, cost of communications, and update policy consequences for the framework. With OpenStack Swift's open source and modular design, our multimedia data management and management framework is well suited to protecting and managing clouds' multimedia with low computational costs as shown in the experimental results.

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The 5G Wireless Technology and a Significant Economic Growth and Sustainable Development

The 5G Wireless Technology and a Significant Economic Growth...

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Smart Computing and Application (ICSCA), International Conference on

作者： Abdulsalam Alkholidi Naif A. Alsharabi Habib Hamam Talal Sarheed Alshammari Canadian Institute of Technology Tirana Albania Faculty of Engineering Sana'a university Sana'a Yemen Comuter Engineering College of Computer Scinece and Engineering Univerity of Ha'il Ha'il KSA College of Engineering and IT Amran University Yemen Faculty of Engineering Université de Moncton Moncton NB College Department of Software Engineering Canadian Institute of Technology Tirana Canada Moncton Canada

5G technology can create millions of new jobs in many economic and industry sectors. It needs an in-depth study between the engineering sector, business, moneymen, and economists to introduce new ideas and develop a road map to benefit from this technology. Also, learn from the experiences of pioneers in this sector. Mobile phone networks are no longer a means of social media, entertainment, narrow commerce, and commercial correspondence. They have become a new pillar in economic growth if they are optimally exploited. This paper aims at highlighting 5G mobile networks and economic growth by studying and analyzing prestigious research and technical and commercial related reports and raising important recommendations to the decision-makers to take advantage of it and adapt this modern technology to develop the economic sector and create new opportunities for young people and those interested. The most important recommendation of this study is the need to support a new generation of young people, especially in the least developed countries in the formation of their minor economic projects, taking advantage of the huge potential of 5G technology, as well as the localization of this technique in many medium and giant projects. One of the key recommendations of this study is to encourage young people to involve in this promising field and help them set up small businesses.

关键词： Economics Location awareness 5G mobile communication Social networking (online) Wireless networks Roads Entertainment industry

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N-Gram-Based Machine Learning Approach for Bot or Human Detection from Text Messages 22

N-Gram-Based Machine Learning Approach for Bot or Human Dete...

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6th International Conference on Intelligent Systems, Metaheuristics and Swarm Intelligence, ISMSI 2022

作者： Kavadi, Durga Prasad Sanaboina, Chandra Sekhar Patan, Rizwan Gandomi, Amir Department Of Information Technology B V Raju Institute Of Technology Narsapur Telangana India Department Of Computer Science And Engineering University College Of Engineering Kakinada Jawaharlal Nehru Technological University Kakinada India Decentralized Science Lab College Of Computing And Software Engineering Kennesaw State University MariettaGA30060 United States Faculty Of Engineering And Information Systems University Of Technology Sydney UltimoNSW Australia

ISBN: (纸本)9781450396288

Social bots are computer programs created for automating general human activities like the generation of messages. The rise of bots in social network platforms has led to malicious activities such as content pollution like spammers or malware dissemination of misinformation. Most of the researchers focused on detecting bot accounts in social media platforms to avoid the damages done to the opinions of users. In this work, n-gram based approach is proposed for a bot or human detection. The content-based features of character n-grams and word n-grams are used. The character and word n-grams are successfully proved in various authorship analysis tasks to improve accuracy. A huge number of n-grams is identified after applying different pre-processing techniques. The high dimensionality of features is reduced by using a feature selection technique of the Relevant Discrimination Criterion. The text is represented as vectors by using a reduced set of features. Different term weight measures are used in the experiment to compute the weight of n-grams features in the document vector representation. Two classification algorithms, Support Vector Machine, and Random Forest are used to train the model using document vectors. The proposed approach was applied to the dataset provided in PAN 2019 competition bot detection task. The Random Forest classifier obtained the best accuracy of 0.9456 for bot/human detection. © 2022 ACM.

关键词： Feature Selection

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Accessibility Metadata: A Proposal for the OER's Evaluation Considering Quality Models 5

Accessibility Metadata: A Proposal for the OER's Evaluation ...

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5th IEEE Ecuador Technical Chapters Meeting, ETCM 2021

作者： Chimbo, Bryan Ingavélez-Guerra, Paola Otón-Tortosa, Salvador Salesian Polytechnic University Research Group on Artificial Intelligence and Assistive Technologies Cuenca Ecuador University of Alcalá Faculty of Computer Science Information Technology Department of Software Engineering Madrid Spain

ISBN: (纸本)9781665441414

The collaborative approach which are born OER (Open Educational Resource) is the joint search for pedagogical and technological challenges to achieve improved quality reconstruction. It is necessary to demonstrate defined metrics that support processes and provide guidelines or instructions related to design for all. The open feature of the OERs must demonstrate accessibility, guaranteeing their interoperability. The incorporation of intelligent systems based on the efficient publication of accessibility information, contributes to the evaluation of accessible resources, knowledge modeling and future trends based on the feedback of profiles, and personalization from the user experience through. This paper presents the proposal for an expert system based on the ISO 40500, ISO 24751 and UDL standards. © 2021 IEEE.

关键词： Metadata

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Semi-definite optimization of the measured relative entropies of quantum states and channels

arXiv

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arXiv 2024年

作者： Huang, Zixin Wilde, Mark M. School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia School of Electrical and Computer Engineering Cornell University IthacaNY14850 United States

The measured relative entropies of quantum states and channels find operational significance in quantum information theory as achievable error rates in hypothesis testing tasks. They are of interest in the near term, as they correspond to hybrid quantum-classical strategies with technological requirements far less challenging to implement than required by the most general strategies allowed by quantum mechanics. In this paper, we prove that these measured relative entropies can be calculated efficiently by means of semi-definite programming, by making use of variational formulas for the measured relative entropies of states and semi-definite representations of the weighted geometric mean and the operator connection of the logarithm. Not only do the semi-definite programs output the optimal values of the measured relative entropies of states and channels, but they also provide numerical characterizations of optimal strategies for achieving them, which is of significant practical interest for designing hypothesis testing protocols. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimal systems

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Automated Model-Based Test Case Generation Using Uml Activity Diagram: A Review 9th

Automated Model-Based Test Case Generation Using Uml Activit...

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9th International Conference on IT Convergence and Security, ICITCS 2021

作者： Nor, Rozi Nor Haizan Monim, Md Abdul Jusoh, Yusmadi Yah Tajuddin, Nur Ilyana Ismarau Department of Software Engineering and Information System Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang Malaysia Tamhidi Centre Universiti Sains Islam Malaysia Nilai Malaysia

ISBN: (纸本)9789811641176

software or application testing is a process of executing a program with the goal of finding defect to make better system. In software testing phase, writing test cases is one of the important activities. Manually writing test cases approach is lengthy of time period and need more effort to accomplish the process. This paper describes test case, test case generation techniques, different types of software testing approaches and comparison of testing tool. Test cases usually writing at the beginning of testing process from the set of software requirements. Test cases are created by using two different approaches. One is manually written test cases and another is automatically generated test cases. Manually written test cases are a very lengthy process and need to give a lot of effort to make good quality test cases. On the other hand, automatically generated test cases are generated by automatically using some software tools and it saves a lot of time and effort. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： software testing

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Fault Diagnosis Model of Switching Power Supply Based on Improved DBN 16

Fault Diagnosis Model of Switching Power Supply Based on Imp...

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16th IEEE International Conference on Intelligent Systems and Knowledge engineering, ISKE 2021

作者： Zhou, Lei Yu, Cheng Liu, Hu Li, Xin Li, Fenfen Zhang, Haiyan National-Local Joint Engineering Lab of System Credibility Automatic Verification Huaiyin Institute of Technology huai'An Faculty of Computer and Software Engineering Research Center for Logic and Intelligent Computation Jiangsu China Nanjing University of Technology Nanjing College of Computer Science and Technology Jiangsu211816 China Huaiyin Institute of Technology huai'An Faculty of Chemical Engineering Jiangsu China

ISBN: (纸本)9781665405539

Switching power supply has wide application in various electrical equipment. The failure of high-voltage filter capacitors is the main cause of frequent faults, accounting for more than 60% of switching power supply failures. In order to realize the real-time detection of switching power supply failure without disassembling the power supply, a fault diagnosis model for improving the deep belief network (DTDBN) is proposed. The model uses the data acquisition device to isolate, filter, and collect data on the grid voltage of the switching power supply, judge the failure ratio of the filter capacitor according to the degree of voltage distortion of the power supply. Experimental results show that the proposed fault detection method achieves a 100% recognition rate for the filter capacitor normal state, 50% and 90% state recognition rate is 90%. The superiority of this method for the classification and early warning of power capacitor faults is proved. © 2021 IEEE.

关键词： Fault detection

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Validating IP Reputation in Cloud Firewall Systems Using Machine Learning Driven Signature Generation and Detection Techniques

Validating IP Reputation in Cloud Firewall Systems Using Mac...

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IEEE Industrial Electronics and Applications Conference (IEACon)

作者： NW Chanka Lasantha Valmik Tilwari MWP Maduranga Ruvan Abeysekara Nilotpal Chakraborty Debashree Sharma Faculty of Graduate Studies IIC University of Technology Phnom Penh Cambodia Department of Electronics & Communication Engineering Indian Institute of Information Technology Guwahati India Department of Software Engineering Sri Lanka Technology Campus Padukka Sri Lanka Department of Computer Science Engineering Indian Institute of Information Technology Guwahati India

ISBN: (数字)9798350382976

ISBN: (纸本)9798350382983

This paper offers a new approach to validation for IP address reputation (IPR) using dynamic signatures achieved through the application of machine learning (ML) to conduct an accurate detection of malicious IPs. The proposed solution connects to the Amazon Web Services (AWS) Web Application Firewall (WAF) to improve security by deploying artificial intelligence (AI) models and natural language (NL) processing for automation of information extraction from IP-related information saved in the AWS object storages. All these lead to minimization of the number of false positives, real-time feedback, and optimization of IP reputation checking. The experimental outcome proves the capability of the proposed system to mitigate the IP address of the attacker and improve the protection of web applications against cybercrimes. This new approach is much advanced and a major leap ahead of other conventional IP reputation techniques, which offer a good protection shield against spam, DDoS, and other such evils.

关键词： Radio frequency Accuracy Firewalls (computing) Web services Natural languages Real-time systems IP networks Protection computer crime Optimization

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