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International Conference on Advanced science and Engineering (ICOASE)

作者： Nagham Tharwat Saeed Hasan Maher Ahmed Dept. of Computer Science College of Education for Pure Science University of Mosul Mosul Iraq Software dept College of Computer Science and Math. University of Mosul Mosul Iraq

The spread of the Corona Virus pandemic on a global scale had a great impact on the trend towards e-learning. In the virtual exams the student can take his exams online without any papers, in addition to the correction and electronic monitoring of the exams. Tests are supervised and controlled by a camera and proven cheat-checking tools. This technology has opened the doors of academic institutions for distance learning to be wide spread without any problems at all. In this paper, a proposed model was built by linking a computer network using a server/client model because it is a system that distributes tasks between the two. The main computer that acts as a server (exam observer) is connected to a group of sub-computers (students) who are being tested and these devices are considered the set of clients. The proposed student face recognition system is run on each computer (client) in order to identify and verify the identity of the student. When another face is detected, the program sends a warning signal to the server. Thus, the concerned student is alerted. This mechanism helps examinees reduce cheating cases in early time. The results obtained from the face recognition showed high accuracy despite the large number of students' faces. The performance speed was in line with the test performance requirements, handling 1,081 real photos and adding 960 photos.

关键词： Training Performance evaluation Pandemics Face recognition Digital images Computational modeling Real-time systems

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Neutrosophic Fuzzy Pairwise Local Function and Its Application

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Neutrosophic Sets and Systems 2022年 49卷 19-31页

作者： Salama, A.A. Khaled, Huda E. Elagamy, H.A. Dept. of Math and Computer Sci. Faculty of Science Port Said Univ. Egypt Telafer University The Administration Assistant for the President of the Telafer University Telafer Iraq Dept. of Mathematics and Basic sciences Ministry of Higher Education Higher Future institute of Engineering and Technology Mansour Egypt

In this paper we introduce the notion of neutrosophic fuzzy bitopological ideals. The concept of neutrosophic fuzzy pairwise local function is also introduced here by utilizing the neutrosophic quasi-coincident neighbourhood (i.e. Nq — nbd) structure in a neutrosophic fuzzy topological space. As well as, the concepts of neutrosophic fuzzy bitopologies and several relations between different neutrosophic fuzzy bitopological ideals have been explored. © 2022. All Rights Reserved.

关键词： Fuzzy sets

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Bayesian Decision-Theoretic Prediction with Ensemble of Meta-Trees for Classification Problems

Bayesian Decision-Theoretic Prediction with Ensemble of Meta...

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International Symposium on Information Theory and Its Applications, ISITA

作者： Naoki Ichijo Ryota Maniwa Yuta Nakahara Koshi Shimada Toshiyasu Matsushima Dept. of Pure and Applied Math. Waseda University Tokyo Japan KDDI Corporation Tokyo Japan Center for Data Science Waseda University Tokyo Japan

ISBN: (数字)9784885523519

ISBN: (纸本)9798331533335

Decision tree algorithms are one of the most popular methods in machine learning. However, most decision tree algorithms do not assume a stochastic model behind data. On the other hand, a meta-tree was recently proposed as a stochastic model with a tree structure. The prediction under the assumption of the meta-tree is decided using Bayesian decision theory. Although the optimal prediction can be calculated with an assumption of a known meta-tree, an approximation is necessary to obtain a prediction under the problem setting of an unknown meta-tree because of the marginalization of all possible meta-trees. In this paper, we propose an approximation method, where a subset of meta-trees is sequentially constructed, and the prediction is made by weighting the meta-trees. For the approximation, we clarify the approaches of constructing the subset and making predictions with weighted meta-trees. We also examine the effectiveness of the approaches in an experiment using synthetic data. In addition, we conduct an experiment on benchmark data to confirm the performance of the proposal.

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Reinforcement Learning for a Raspberry Pi Smart Car for Lane Detection Using OpenCV

Reinforcement Learning for a Raspberry Pi Smart Car for Lane...

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IEEE Annual Computing and Communication Workshop and Conference (CCWC)

作者： Minh Nguyen Tauheed Khan Mohd Dept. of Math and Computer Science Augustana College Rock Island Illinois United States Dept of Math and Computer Science Augustana College Rock Island Illinois

The paper aims to represent an autonomous car prototype using the Raspberry Pi as a processing chip. The pi-camera module provides necessary data from the real world to the car, which then passes the data on to the raspberry-pi. The car can follow a given path safely and intelligently, thus avoiding the risk of human errors by responding to the real-time curve.

关键词： Performance evaluation Deep learning Lane detection Prototypes Reinforcement learning Real-time systems Nanoscale devices

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Graph Fourier MMD for Signals on Graphs

Graph Fourier MMD for Signals on Graphs

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2023 International Conference on Sampling Theory and Applications, SampTA 2023

作者： Leone, Samuel Venkat, Aarthi Huguet, Guillaume Tong, Alexander Wolf, Guy Krishnaswamy, Smita Applied Math Program New HavenCT United States Yale University Computational Biology & Bioinformatics Program New HavenCT United States Université de Montréal Mila - Quebec Ai Institute Dept. of Math. & Stat Montreal Canada Université de Montréal Mila-Quebec Ai Institute Dept. of Comp. Sci. & Oper. Res. Montreal Canada Yale University Department of Computer Science Department of Genetics New HavenCT United States

ISBN: (纸本)9798350328851

While numerous methods have been proposed for computing distances between probability distributions in Euclidean space, relatively little attention has been given to computing such distances for distributions on graphs. However, there has been a marked increase in data that either lies on graph (such as protein interaction networks) or can be modeled as a graph (single cell data), particularly in the biomedical sciences. Thus, it becomes important to find ways to compare signals defined on such graphs. Here, we propose Graph Fourier MMD (GFMMD), a novel distance between distributions and signals on graphs. GFMMD is defined via an optimal witness function that is both smooth on the graph and maximizes the difference in expectation between the pair of distributions on the graph. We find an analytical solution to this optimization problem as well as an embedding of distributions that results from this method. We also prove several properties of this method including scale invariance and applicability to disconnected graphs. We showcase it on graph benchmark datasets as well on single cell RNA-sequencing data analysis. In the latter, we use the GFMMD-based gene embeddings to find meaningful gene clusters. We also propose a novel type of score for gene selection called gene localization score which helps select genes for cellular state space characterization. © 2023 IEEE.

关键词： Genes

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Securing Internet of Vehicles Protocols using ASCON and GIFT-COFB

Securing Internet of Vehicles Protocols using ASCON and GIFT...

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IEEE Conference on Vehicular Technology (VTC)

作者： Wissal BenMassaoud Darshan M Rutvij H. Jhaveri Gautam Srivastava Dept. of Computer Science Lakehead University Thunder Bay ON Canada Dept. of Computer Science and Engineering School of Technology Pandit Deendayal Energy University India Dept. of Math and Computer Science Brandon University Brandon MB Canada

The Internet of Vehicles (IoV) is a network of vehicles that are connected through the Internet using communication protocols. However, this raises concerns about security and privacy. The vulnerability of object networks has been highlighted in recent reports on cybernetics, and attacks on these networks could pose significant dangers to data integrity. To avoid this, security measures such as resistance to attacks, data authenticity, access control, and privacy must be integrated. The limited capabilities of IoT objects in terms of processing power, memory, bandwidth, and energy have led to the creation and redesign of protocols and architectures that meet the specific needs of these networks. One such protocol is the Message Queue Telemetry Transport (MQTT), which uses a Publish/Subscribe methodology and small amounts of bandwidth. To address security concerns, the paper proposes using the lightweight cryptographic techniques ASCON and GIFT-COFB, which could be useful in securing communication and data exchange in IoV sensor networks.

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Is Gamification a Practical Solution for Increasing Repurchase Intention of Online Customers?

Is Gamification a Practical Solution for Increasing Repurcha...

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2023 Congress in computer science, computer Engineering, and Applied Computing, CSCE 2023

作者： Safari, Khalil Safari, Zohreh Keshavarzi, Fatemeh Payam Noor University Dept. of Business Management and Information Technology Tehran Iran Elizabeth City State University Dept. Computer Science Math Engineering Technology Elizabeth City United States Qazvin Islamic Azad University Dept.Information Technology Engineering Qazvin Iran

ISBN: (纸本)9798350327595

With the growth of online shopping, organizations should update their portals and websites in response to changing conditions and competitors' actions. To attract and retain online customers, various tools such as reputation building, trust en-hancement, and gamification are utilized and reinforced. This study has investigated 243 users of DigiKala company through paper and electronic questionnaires. Due to the non-normality of the data, non-parametric statistical methods using SPSS and Smart-PLS3.0 software were employed to analyze structural relationships. Additionally, machine learning tools were utilized to optimize the analysis of customer behavior and identify patterns for effective customer retention strategies. The results show that contrary to the research background, the use of gamification on DigiKala's website has not had a positive and significant impact on customers using this company's website and their repurchase intention. Thus, it seems that DigiKala should focus on context and infrastructures, while simultaneously strengthening and revamping gamification dimensions. © 2023 IEEE.

关键词： Gamification intention to use repurchase intention Reputation Trust in vendor

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Overcoming Imbalanced Datasets and Feature Complexity in Fraud Transaction Detection Through Down-Sampling and Dimension Reduction 17

Overcoming Imbalanced Datasets and Feature Complexity in Fra...

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17th International Conference on Open Source Systems and Technologies, ICOSST 2023

作者： Shan, Chan Pei Leng, Too Ai Ahmad, Muneer Malik, Yasir Jaffar, Fehmi Universiti Malaya Dept. of Information Systems Malaysia Digby Stuart College University of Roehampton United Kingdom Bishops University Dept. of Computer Science Canada Université du Québec à Chicoutimi Département d'Informatique et de Mathématique Canada

ISBN: (纸本)9798350381320

Detecting fraudulent transactions presents two primary obstacles, the presence of imbalanced datasets and the sheer volume of feature categories. The scarcity of fraudulent instances within the dataset often results in these cases being erroneously classified as noise, consequently introducing bias towards non-fraudulent cases in the detection outcomes. Simultaneously, the extensive array of feature categories poses a formidable challenge in identifying crucial variables, thereby limiting the efficacy of detection algorithms. This research contributes to the field of fraud transaction detection by proposing a multifaceted approach that addresses the challenges of imbalanced data and feature complexity. Through down-sampling, dimension reduction, model evaluation, and precision enhancement, the study aims to improve the accuracy and efficiency of fraud detection models, with the goal of reducing false alarms and financial losses in real-world scenarios. © 2023 IEEE.

关键词： Principal component analysis

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Towards Arabic Multimodal Dataset for Sentiment Analysis 3

Towards Arabic Multimodal Dataset for Sentiment Analysis

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3rd International Conference on Intelligent Data science Technologies and Applications, IDSTA 2023

作者： Haouhat, Abdelhamid Bellaouar, Slimane Nehar, Attia Cherroun, Hadda Université Amar Telidji Lab. d'Informatique et de Mathématiques Laghouat Algeria Dept. of Mathematics and Computer Science Algeria Université Ziane Achour Djelfa Algeria Laghouat Algeria

ISBN: (纸本)9798350339253

Multimodal Sentiment Analysis (MSA) has recently become a centric research direction for many real-world applications. This proliferation is due to the fact that opinions are central to almost all human activities and are key influencers of our behaviors. In addition, the recent deployment of Deep Learning-based (DL) models has proven their high efficiency for a wide range of Western languages. In contrast, Arabic DL-based multimodal sentiment analysis (MSA) is still in its infantile stage due, mainly, to the lack of standard datasets. In this paper, our investigation is twofold. First, we design a pipeline that helps building our Arabic Multimodal dataset leveraging both state-of-the-art transformers and feature extraction tools within word alignment techniques. Thereafter, we validate our dataset using state-of-the-art transformer-based model dealing with multimodality. Despite the small size of the outcome dataset, experiments show that Arabic multimodality is very promising. © 2023 IEEE.

关键词： Sentiment analysis

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RFID and NFC authentication protocol for securing a payment transaction 4

RFID and NFC authentication protocol for securing a payment ...

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4th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2022

作者： Chabbi, Samir Araar, Chaouki University of Souk Ahras Dept. of Math and Computer Science Souk Ahras Algeria Fréres Mentouri University Electronics Department Constantine Algeria

ISBN: (数字)9781665461610

ISBN: (纸本)9781665461610

RFID (Radio Frequency Identification) is a technology that permits to identify objects with a radio frequency field for few meters distance. It is applied in several fields such as traceability, logistics, military, security, healthcare, library, etc. Its successor NFC (Near Field Communication)), on the contrary, is used to transmit messages at a short distance (less than 10 Cent.). Recently, NFC is frequently used for payment transaction using ATM and smartphone both equipped of this technology. Unfortunately, the information transferred with this technology during a payment transaction can be an objectif for threads to steale personal and privacy data that concern a user. This paper introduces a new method for payment transaction that combines RFID and NFC. This process which uses an authentication protocol is proposed in order to (1) secure the payment transaction using an Automated Teller Machine (ATM) and a smartphone both equipped with these two technologies, (2) minimize the waiting chain in front of the ATM for agents using NFC by minimizing the transaction time. To evaluate the performance of our proposal, we tested its security against few attacks. A security and performance comparison of our technique with few recent and important methods is performed and shows the effectiveness of the solution. © 2022 IEEE.

关键词： Smartphones

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