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Analyzing Bloom's Taxonomy to Interactions in Virtual Reality Application for Education

Analyzing Bloom's Taxonomy to Interactions in Virtual Realit...

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International Electronics Symposium (IES)

作者： Hestiasari Rante Muhammad Agus Zainuddin Zacky Maulana Achmad Khairunnisa’ Sekar Ramadhanti Cahyo Arissabarno Dept. of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9798350391992

ISBN: (纸本)9798350392005

Virtual Reality (VR) technology enables users to engage with a three-dimensional, computer-simulated environment that mimics the real world. This immersive technology allows users to fully interact with 3D content as if they were present in that environment. VR has the potential for development in numerous areas, including medical education. Integrating VR into education, particularly in the medical field, can align with Bloom's Taxonomy to create more effective and meaningful interactions. Consequently, interaction design in VR applications for medical education can be optimized to improve student learning outcomes according to Bloom's Taxonomy principles. This research leverages an immersive interactive experience that enables users to actively engage in simulations and practical tasks. By incorporating the principles of Bloom's Taxonomy, the system enhances learning engagement and motivation, ensuring users can recall, apply, analyze, and evaluate information in depth. The purpose of analyzing VR interactions is to evaluate whether the interactions used in the VR Childbirth Surgery application have been implemented correctly through the lens of Bloom's Taxonomy. The interactions analyzed are Grab, Touch, and Click in the VR Childbirth Surgery application, based on journals, applications, and demo videos reviewed. The Click interaction is straightforward and user-friendly, the Grab interaction enhances realism and engagement but requires precise implementation and advanced hardware, and the Touch interaction provides high immersion but is dependent on the capabilities of the VR hardware.

关键词： Solid modeling Three-dimensional displays Taxonomy Education MIMICs Surgery Hardware

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QoS Under Attack: A Simulation Study on the Impact of Class Hijacking in Wireless LANs

QoS Under Attack: A Simulation Study on the Impact of Class ...

引用

International Conference on computer Theory and Applications (ICCTA)

作者： Christos K. Christodoulou Anastasios C. Politis Constantinos S. Hilas Dept. of Computer Informatics and Telecommunications Engineering International Hellenic University Serres Greece

ISBN: (数字)9798331529680

ISBN: (纸本)9798331529697

User satisfaction in Wireless Networks (WLANs) heavily rely on the efficient provision of Quality of Service (QoS). Nevertheless, misbehaving acts by malicious users have the potential to disrupt the QoS provisioning and impair its overall efficiency. One such abusive behavior is called Class Hijacking (CH) and has the ability to deteriorate the QoS-levels received by the well-behaving users in the network. CH is a hard to detect, yet easy to perform attack, targeting the QoS mechanism in differentiated services networks such as WLANs. This article attempts to illustrate the negative impact of CH actions on the network performance of an infrstructure-based WLAN where stealing network resources is an attractive choice for nefarious users. This is achieved through extensive simulations using the ns-3 network simulator. Applying a gradual increase in the number of deceitful users, we observe how these attacks noticeably deteriorate network performance.

关键词： Wireless LAN Diffserv networks Computational modeling Wireless networks Quality of service

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Anomaly Detection With Quantified Explanations for Multivariate Time Series Networking Data

Anomaly Detection With Quantified Explanations for Multivari...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Marantis, Panagiotis Ramantas, Kostas Verikoukis, Christos Iquadrat Informatica S.L Barcelona Spain University of Patras Dept. of Computer Engineering and Informatics Patras Greece Athena Research Center Athens Greece Industrial Systems Institute Patras Greece

ISBN: (纸本)9798350351255

Next-generation telecommunication networks provide vast amounts of Multivariate Time Series monitoring data during their operation. Using these data to automatically detect anomalous system behavior is of critical importance to operators and Internet Service Providers, in order to analyze the network state and take mitigating actions to resolve possible faults. For the output of this Anomaly Detection process to be trusted, comprehensive and accurate explanations must be provided. These explanations are essential to make critical decisions that affect the network state. In this paper, we present a framework that utilizes reconstruction-based Deep Neural Network models to perform the anomaly detection task, while also using an explainability module that provides explanations of the results. The quality of the explanations is quantified through the use of interpretation labels. In addition, we provide a comparative analysis, performing Anomaly Detection on three different open-source datasets from the mobile networking domain, while testing multiple Deep Learning models and comparing their performance. The presented results show that our framework accurately detects various types of anomalies that can be present in mobile networks, while offering the flexibility to identify and select the model that offers the best performance for each dataset, in both the Anomaly Detection and explainability tasks. © 2024 IEEE.

关键词： DNNs Explainable Anomaly Detection Machine Learning Multivariate Time Series Next-Generation Networks Reconstruction-based Models

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Auto-Adaptive Stator Ground Fault Protection for Synchronous Generators in Diesel-Electric Locomotives 14

Auto-Adaptive Stator Ground Fault Protection for Synchronous...

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14th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023

作者： Mahtani, Kumar Guerrero, Jose M. Beites, Luis F. Platero, Carlos A. Universidad Politécnica de Madrid Automation Electrical and Electronic Engineering and Industrial Informatics Dept. Madrid Spain Mondragon Unibertsitatea Electronics and Computer Science Dept. Arrasate-Mondragon Spain Universidad Politécnica de Madrid Automation Electrical and Electronic Engineering and Industrial Informatics Department Madrid Spain

ISBN: (纸本)9798350320770

Diesel-electric locomotives are equipped with one or more synchronous generators driven by diesel engines, that provide the necessary electrical energy for their operation. These generators are usually provided with some protection relays, depending on their rated power and their type of service. Standard stator-ground fault protection has a setting for rated conditions. In case of variable speed and voltage operation, the protection does not cover all the operation range of the machine. In addition, unwanted tripping may occur due to incorrect filtering of the third harmonic. In this paper, an auto-adaptative stator ground protection function is presented, for the operation of synchronous machines at variable voltage and frequency. A specific case study is tackled, focused on the main generators of a diesel-electric locomotive. Numerous simulations are carried out to verify the proposed protection method. The obtained results are promising, and they can be used in other synchronous machines operating at variable speed. © 2023 IEEE.

关键词： Stators

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Instance-Level Safety-Aware Fidelity of Synthetic Data and its Calibration 27

Instance-Level Safety-Aware Fidelity of Synthetic Data and i...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Cheng, Chih-Hong Stockel, Paul Zhao, Xingyu Chalmers & Univ. of Gothenburg Dept. of Computer Science & Engineering Sweden University of Hildesheim Department of Informatics Germany University of Warwick WMG CV4 7AL United Kingdom

ISBN: (纸本)9798331505929

Modeling and calibrating the fidelity of synthetic data is paramount in shaping the future of safe and reliable self-driving technology by offering a cost-effective and scalable alternative to real-world data collection. We focus on its role in safety-critical applications, introducing four types of instance-level fidelity that go beyond mere visual input characteristics. The aim is to ensure that applying testing on synthetic data can reveal real-world safety issues, and the absence of safety-critical issues when testing under synthetic data can provide a strong safety guarantee in real-world behavior. We suggest an optimization method to refine the synthetic data generator, reducing fidelity gaps identified by deep learning components. Experiments show this tuning enhances the correlation between safety-critical errors in synthetic and real data. © 2024 IEEE.

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Designing and Simulating a Smart Water Harvesting System Using PLC Techniques

Designing and Simulating a Smart Water Harvesting System Usi...

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2023 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2023

作者： Thabet, Hassaan Th. H. Al-Hilali, Aqeel A. Qasim, Haitham B. Thabit, Thabit H. Mahmood, Firas M. Al-Hadba University College Techniques Engineering Dept. of Medical Instruments Mosul Iraq Al-Farahidi University Dept. of Medical Instruments Engineering Techniques Baghdad Iraq Al-Esraa University College Dept. of Computer Science Baghdad Iraq Ninevah University Dept. of Computer Engineering and Information Mosul Iraq Cihan University-Erbil Dept. of Informatics and Software Engineering Iraq

ISBN: (纸本)9798350307771

The presence of water in human life is crucial, and God has blessed humans much with its availability. This paper tries to reduce the amount of water that people use for washing in all aspects of daily life and instead utilize it to irrigate gardens and maintain hygienic facilities. The importance of water as a fundamental ingredient and the range of social and age groups that regularly take advantage of the washing process made it an ideal location for water waste during the washing process. This is why the authors choose this region to conduct their research. The monitoring and management of water usage during the washing process are simulated using PLC techniques. © 2023 IEEE.

关键词： Washing

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Design and Simulation of an Affordable Vehicle Speed Detection System

Design and Simulation of an Affordable Vehicle Speed Detecti...

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2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Thabet, Hassaan Th. H. Al-Hilali, Aqeel A. Al-Safi, Mohammed G. S. Thabit, Thabit H. Mahmood, Firas M. Al-Hadba University College Dept. of Computer Technology Engineering Mosul Iraq Al-Farahidi University Dept. of Medical Instruments Engineering Techniques Baghdad Iraq Al-Esraa University College Dept. of Accounting Baghdad Iraq Ninevah University Dept. of Computer Engineering and Information Mosul Iraq Cihan University-Erbil Dept. of Informatics and Software Engineering Kurdistan Region Iraq

ISBN: (纸本)9798350369359

The objective of this paper is to detect the over speed of vehicles on the roads. Although maximum speed limit signs exist on the roads, many accidents keep on because of high-speed driving. It is necessary to solve these problems through automation techniques. This paper describes a speed detection system for vehicles, the traffic police can easily check the speed of vehicles by using this system. This system consists of a PLC (Programmable Logic Controller) LOGO! V8.3, two Laser sensors, an HMI (Human Machine Interface), a speed camera, and a LOGO! CMR (Communication Module Radio). The detected speed is displayed on the HMI display, moreover, if a vehicle crosses the limited speed, this system displays the over-speed on HMI, and the speed camera is activated to capture an image of that vehicle. Also, an SMS (Short Messages Service) will be sent by the CMR to the traffic authority informing them about the violation to take the necessary legal actions. The system can also store the collected data for documentation purposes. The authors describe a simple, affordable technique for monitoring vehicles' speeds in this paper. © 2023 IEEE.

关键词： Vehicles

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Examining The Risk Factors of Liver Disease: A Machine Learning Approach 7

Examining The Risk Factors of Liver Disease: A Machine Learn...

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7th International Conference on Communication and Electronics Systems, ICCES 2022

作者： Hossen, Md. Sagar Haque, Imdadul Sarkar, Puza Rani Islam, Md. Ashiqul Fahim, Wasik Ahmmed Khatun, Tania Institut Teknologi Sepuluh Nopember Dept. of Informatics Engineering Surabaya Indonesia Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Nowadays, Liver Disease (LD) is a very common clinical problem for human health and is related to morbidity and mortality. Nevertheless, an earlier prognosis of LD patients gets a scope to avoid, prior diagnosis and subsequent treatment. This research work attempts to implement a high qualified performer machine learning design to predict LD, the most wanted and unwanted risk factor of LD which could help physicians in classifying risky patients and create an analysis to restrict and control LD. The proposed research study has included all patients, who were identified as having liver diseases. Totally, 6 (six) machine learning algorithms such as Decision Tree(DT), Logistic Regression(LR), Multilayer Perceptron(MLP), Artificial Neural Network(ANN), Random Forest(RF), K Nearest Neighbor classifier(KNN) are selected to predict LD. The location underneath had been utilized to evaluate the accuracy among the six applied models. An overall total of 583 instances had been included in this scholarly research;of the 416 patients are affected by liver illness. The location which defines the receiver operating characteristic (AU ROC) of Logistic Regression, Decision Tree, Multilayer Perceptron, Random Forest, Artificial Neural Network, and K-Nearest Neighbor classifier with 10-fold-cross validation was performed. Furthermore, the reliability of LR, DT, MLP, RF, ANN and KNN with accuracy 72.89%, 81.32%, 60.24%, 86.14%, 75.61%, and 65.52%. The utilization of woodland which is certainly arbitrary within the medical setting may help doctors to detect and classify liver patients for major avoidance, surveillance, quick treatment, and management. LR, DT, MLP, RF, ANN, and KNN formulas are acclimatized to forecast and after analyzing the data set, an increased price of accuracy is achieved. © 2022 IEEE.

关键词： Multilayer neural networks

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Unconventional Computing based on Four Wave Mixing in Highly Nonlinear Media

Unconventional Computing based on Four Wave Mixing in Highly...

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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Sozos, Kostas Deligiannidis, Stavros Mesaritakis, Charis Bogris, Adonis University of West Attica Dept. of Informatics and Computer Engineering. Aghiou Spiridonos Egaleo Athens12243 Greece University of the Aegean Dept. of Information and Communication Systems Engineering Palama 2 Karlovassi Samos83200 Greece

ISBN: (纸本)9798350345995

Nowadays, photonic analog computing in the form of neuromorphic photonics or photonic neural networks has resulted in powerful hardware platforms that accelerate difficult tasks with marginal power consumption. Although linear transformations are efficiently carried out in the optical domain, nonlinear transformations are also of paramount importance. Here, we propose four wave mixing (FWM) process as an elegant solution for the generation of diverse nonlinear higher order products of an original signal. On one hand, these products can act as activation functions in different types of neural networks, either recurrent neural networks (RNNs) and reservoir computers or in any other type of brain-inspired frameworks. On the other hand, the same products can form the basis for polynomial regression which is a very powerful technique used in machine learning in different tasks i.e. for the prediction of COVID-19 transmission [1]. © 2023 IEEE.

关键词： Recurrent neural networks

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Exploring the Semantic Complexity of Adjective-Noun Collocations between Uzbek and English for Improved Machine Translation 9

Exploring the Semantic Complexity of Adjective-Noun Collocat...

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9th International Conference on computer Science and engineering, UBMK 2024

作者： Abdurakhmonova, Nilufar Shamieva, Nargiza Adali, Eşref National University of Uzbekistan Dept. of Computational and applied linguistics Tashkent Uzbekistan National Univ. of Uzbekistan Dept. of Foreign language and Literature Tashkent Uzbekistan Istanbul Technical University Computer Engineering and Informatics Faculty Istanbul Turkey

ISBN: (纸本)9798350365887

The bilingual thesaurus of Uzbek-English adjectives is a field that has not been studied well explored yet for machine translation. Several websites and electronic dictionaries created nearby show that not enough semantically close adjectives are included in them. Despite extensive research on the meaning the adjectives in both languages, there remains a lack of understanding about the relationship between the adjective itself and the noun, which has an absolutely new connotation in collaboration. Our result shows that a recent bilingual thesaurus demonstrates how one adjective could acquire numerous new synonyms while combining with different nouns. The meanings of words, in both languages have been extensively studied, Little is understood about the dynamic connection between these words and the nouns they describe. The complexity of how adjectives pair with nouns is evident in how this relationship leads to meanings and connotations. Our study aims to bridge this gap by demonstrating how a bilingual thesaurus can capture the meanings and variations of adjectives when combined with nouns. The findings indicate that depending on the noun it accompanies a contemporary bilingual thesaurus can generate synonyms, for a single adjective. © 2024 IEEE.

关键词： Machine translation

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