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25th International Arab Conference on Information Technology, ACIT 2024

作者： Sabbah, Thabit Ashraf, Mahmoud Abrar, Mohammad Dhofar University Collage of Arts and Applied Sciences P.O.Box:2509 Salalah211 Oman University of Jeddah College of Computer Science and Engineering Department of Computer Science and Artificial Intelligence Jeddah Saudi Arabia Arab Open University Faculty of Computer Studies Muscat122 Oman

ISBN: (纸本)9798331540012

Class distribution imbalance in the dataset is a critical factor in machine learning based classification performance. Many oversampling techniques were used to overcome the effect of this problem and retrieve the balance state for effective modelling. This paper presents an enhanced technique based on the Support Vectors for oversampling the minority class by generating synthetic data for better performance. The proposed method is tested on machine-generated datasets for binary classification problems. Experiments show an average improvement of approximately 15% in the classification recall and AUC performance measures on both datasets using the proposed method over the leading of the studied oversampling techniques. The proposed method can benefit the real-life machine learning classification problems where the positive class forms the minority of the training dataset like fraud-detection, medical diagnosis, and other problems, by expanding the positive class samples with more discriminative and evenly distributed related synthetic samples. © 2024 IEEE.

关键词： Adversarial machine learning

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Experiences with Low-to-Medium-Effort Hybrid Teaching 14

Experiences with Low-to-Medium-Effort Hybrid Teaching

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14th IEEE Global Engineering Education Conference, EDUCON 2023

作者： Böttcher, Axel Hochschule München University of Applied Sciences Faculty of Computer Science and Mathematics Lothstraße 64 MunichD-80335 Germany

ISBN: (纸本)9798350399431

The pandemic forced our institution from classroom teaching to complete online remote teaching. After the pandemic we are faced with questions of how we will continue with remote and especially with hybrid teaching formats. This includes the development of effective setups for hybrid and remote teaching scenarios - and to determine which setup is to be preferred in which context. Furthermore we have to find didactic formats to use in remote and hybrid teaching settings. In this paper we present our experiences with the evolution of a hybrid teaching setup as it grew while we detected and incorporated more and more requirements. Our main goal was to overcome several issues related to technical handling during the hybrid lectures, and to simultaneously create a motivating environment for students. The setups considered demand for different effort in terms of technical investment and operations. The most important idea was to separate presentation and video conferencing to different computers, thus tremendously simplifying the handling. One setting is then evaluated for a cohort of the module Software Development during summer term 2022. Evaluation results are very promising. We further coin several didactic issues for hybrid teaching scenarios. © 2023 IEEE.

关键词： Video conferencing

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Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

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computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

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A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment

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Personal and Ubiquitous Computing 2023年第3期27卷 697-713页

作者： Akhbarifar, Samira Javadi, Hamid Haj Seyyed Rahmani, Amir Masoud Hosseinzadeh, Mehdi Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Mathematics and Computer Science Shahed University Tehran Iran Institute of Research and Development Duy Tan University Da Nang550000 Viet Nam Mental Health Research Center Psychosocial Health Research Institue Iran University of Medical Sciences Tehran Iran

Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients’ health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients’ health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients’ health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients’ sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms. © 2020, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Data mining

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The Students' Performance of Digital Sustainable Development Education in Gaining Competitive Advantage in ASEAN's Business Competition in the Post-Pandemic Era 23

The Students' Performance of Digital Sustainable Development...

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6th International Conference on Software Engineering and Information Management, ICSIM 2023

作者： Pane, Murty Magda Siregar, Christian Character Building Development Center School of Computer Science Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Character Building Development Center Mass Communication Program Communication Department Faculty of Digital Communication and Hotel and Tourism Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450398237

This study is a preliminary one aims to find out the performance of the attitudes and behaviors of Binus University students towards sustainable development to gain the competitive advantages in ASEAN business competition in the post-pandemic era. It was taken using the convenience sampling technique to 225 students from varied semester and departments. It used the quantitative method (corrected item total correlations for both variables are 0.433 and 0.419 (>0.3), α for both are 0.750 and 0.773 (> 0.5)) with Likert scale to measure the performance of agree and disagree for managing and interpreting the data. The respondents are 250 students from varied semesters and departments. The performance of the most chosen variable of attitudes are: scale 4 is chosen by 44.44% and scale 5 is chosen by 35.56% of respondents. Whilst the performance of the most chosen variable of behaviors is: scale 4 is chosen by 39.56% and scale 5 is chosen by 27.56% of respondents. These results indicated that the sustainable development awareness of Bina Nusantara students tends to the level of moderate to high. © 2023 ACM.

关键词： Students

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Study of a nonlinear Schrodinger equation with truncated M proportional derivative

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Optik 2023年第1期290卷

作者： Abdel-Gawad, Hamdy I. Sulaiman, Tukur Abdulkadir Ismael, Hajar Farhan Mathematics Department Faculty of Science Cairo University Cairo Egypt Department of Computer Engineering Biruni University Istanbul34010 Turkey Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Mathematics Faculty of Science University of Zakho Zakho42002 Iraq Department of Computer Science College of Science Knowledge University Erbil44001 Iraq

In this work, we introduce a novel truncated M proportional (T-MP) derivative and consider a T-MP perturbed derivative nonlinear Schrodinger equation (PDNLSE). The PDNLSE is a nonlinear model which arises in nano optical fibers (photonic nanowires). While the DNLSE exhibits self-steepening (SS), the PDNLSE exhibits self-phase modulation (SPM) and Raman scattering (RS) effects, Here, the exact solutions of the PDENLSE are derived, here, by implementing the unified method. These solutions are displayed in graphs. It is found that a sufficient condition for a hyper-chaotic solution to hold is that an elliptic function solution exists. Non elliptic solutions may be, also, hyper-chaotic. It is worth mentioning that hyper chaotic may occur in economic and financial mathematics. Nonchaotic solutions exhibit many geometric structures, chirped solitons, and rhombus-shaped and M-shaped solitons. It is found that modulation instability triggers when the coefficient of the third-order dispersion exceeds a critical value. Further, the global bifurcation is investigated via phase portrait by constructing the Hamiltonian function. © 2023 Elsevier GmbH

关键词： Solitons

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A Distributed Automatic Domain-Specific Multi-Word Term Recognition Architecture using Spark Ecosystem 22

A Distributed Automatic Domain-Specific Multi-Word Term Reco...

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22nd International Symposium on Parallel and Distributed Computing, ISPDC 2023

作者： Truica, Ciprian-Octavian Istrate, Neculai-Ovidiu Apostol, Elena-Simona University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (纸本)9798350341270

Automatic Term Recognition is used to extract domain-specific terms that belong to a given domain. In order to be accurate, these corpus and language-dependent methods require large volumes of textual data that need to be processed to extract candidate terms that are afterward scored according to a given metric. To improve text preprocessing and candidate terms extraction and scoring, we propose a distributed Spark-based architecture to automatically extract domain-specific terms. The main contributions are as follows: (1) propose a novel distributed automatic domain-specific multi-word term recognition architecture built on top of the Spark ecosystem;(2) perform an in-depth analysis of our architecture in terms of accuracy and scalability;(3) design an easy-to-integrate Python implementation that enables the use of Big Data processing in fields such as Computational Linguistics and Natural Language Processing. We prove empirically the feasibility of our architecture by performing experiments on two real-world datasets. © 2023 IEEE.

关键词： Ecosystems

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Lightweight security Mechanism for IoT Applications using Substitution-Box 4

Lightweight security Mechanism for IoT Applications using Su...

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4th IEEE International Conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Hanif, Fozia Shams, Rehan Waheed, Urooj University of Karachi Department of Mathematics Karachi Pakistan Sir Syed University of Engineering and Technology Karachi Department of Telecommunication Pakistan DHA Suffa University Karachi Department of Computer Science Pakistan

ISBN: (纸本)9798331518882

In recent times the use of small computing devices for gathering information from the real world is increasing day by day. The devices like wireless sensors, RIFD tags, embedded devices and IoT devices are required to transmit huge amounts of confidential data for monitoring and controlling. IoT applications have now become an important factor across various industries. That is why the security of IoT device is always been an important issue, because they transmit private and sensitive data. For handling the security issue cryptography is one the way for handling the security issues of IoT devices but sometimes cryptographic algorithms are cracked and as well as very costly. Lightweight cryptography requires less memory and less computational cost. Substitution box is a very useful concept in generating the lightweight cryptographic algorithm that provide robust security in the process of encryption. This study produces lightweight cryptographic encryption and decryption algorithm with the help of substitution boxes. The provided scheme not only provides the encryption procedure but also generating a flexible key structure which enhances the security for IoT devices where lightweight image encryption is crucial. The provided technique will be beneficial for those places where confidential public data has to be secured. The aim of this paper is to recommend effective original and straightforward techniques of encryption and decryption by using the substitution box. Experimental results show the efficiency of the suggested technique in terms of execution time and throughput. © 2025 IEEE.

关键词： Encryption algorithms

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ModeLLer – Enabling End-Users to Model Systems: a Case Study in Digital Agriculture 8

ModeLLer – Enabling End-Users to Model Systems: a Case Stud...

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8th International Workshop on Cultures of Participation in the Digital Age: Differentiating and Deepening the Concept of "End User" in the Digital Age, CoPDA 2024

作者： Mannari, Chiara Anichini, Elisa Bacco, Manlio Ferrari, Alessio Turchi, Tommaso Malizia, Alessio Department of Computer Science University of Pisa Italy Institute of Information Science and Technologies "Alessandro Faedo" - ISTI CNR Pisa Italy Faculty of Logistics Molde University College Norway

Digital technologies show promising potential in the development of sustainable agriculture. For example, the combination of cloud and edge paradigms, 5G, and the Internet of Things (IoT) allows the development of sophisticated applications — e.g., for food traceability, pest detection, and automatic irrigation — with the possibility to also exploit Artificial Intelligence (AI)-powered techniques. At the same time, digitalisation in agriculture is a socio-technical process that involves several classes of stakeholders with diverse backgrounds and skills, e.g., in farming or technology. Model-driven approaches leveraging diagrammatic notations can support information exchange between different domains. In fact, the development of models can be a co-design practice involving end-users throughout all phases of creation because of their expressive power. However, current modelling platforms are typically oriented toward engineers, and there is a lack of tools accessible to end-users for designing and modelling systems. In this position paper, we present ModeLLer, a prototype of a web environment for modelling systems based on an intuitive visual language that can be exported into standard code. The aim is to increasingly involve users in modelling their digital ecosystems as a task for developing digital applications. © 2024 Copyright for this paper by its authors.

关键词： Visual languages

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Shape from Shading under changing Illumination using a CNN 38

Shape from Shading under changing Illumination using a CNN

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38th International Conference on Image and Vision Computing New Zealand, IVCNZ 2023

作者： Rate, Keetley Green, Richard University of Canterbury Department of Mathematics and Statistics New Zealand University of Canterbury Department of Computer Science and Software Engineering New Zealand

ISBN: (纸本)9798350370515

This paper presents an alternative method to the classical yet foundational problem of recovering the geometry of a 3D object from a single 2D brightness image, i.e., shape-from-shading. Drawing inspiration from traditional approaches and recent work in single-image 3D reconstruction, we employ a convolutional neural network trained on synthetic images of characteristic shapes as well as high-frequency surfaces to address the shape-from-shading problem. Although the resulting network is less accurate than non-deep learning (DL) approaches, it exhibits greater resilience to common pitfalls, such as variations in light source direction and the presence of noise in the input image. © 2023 IEEE.

关键词： Convolutional neural networks

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