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检索条件"任意字段=3rd International Informatics and Software Engineering Conference, IISEC 2022"

共 2097 条记录，以下是51-60 订阅

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A Novel Countermeasure for Selective Forwarding Attacks in IoT Networks 3

A Novel Countermeasure for Selective Forwarding Attacks in I...

引用

3rd international informatics and software engineering conference, iisec 2022

作者： Yaman, Okan Sokat, Baris Ayav, Tolga Erten, Yusuf Murat Izmir Institute of Technology Department of Computer Engineering Izmir Turkey Independent Researcher Innovia Technology Izmir Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

As the Internet of Things (IoT) devices become more widespread there are rising public concerns about whether or not IoT devices and their services are secure. One of the major threats they face is selective forwarding attacks performed by malicious nodes. Although packets can be lost inherently due to network conditions, malicious nodes, such as those performing blackhole attacks, may deliberately drop some, but not all of them. Therefore, distinguishing these nodes from legitimate ones is not so easy. This study has proposed a lightweight countermeasure to deal with this kind of attack in IoT networks, using the standard IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). The mechanism is based on Mobile Trusted Nodes (MTNs). For the given threat model, we showed that our model has robust detection accuracy and brings no additional overhead to the network. © 2022 IEEE.

关键词： Internet of things

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Is there any Correlation between Users' Star Ratings and Usability? 3

Is there any Correlation between Users' Star Ratings and Usa...

引用

3rd international informatics and software engineering conference, iisec 2022

作者： Al-Jeri, Sara K. Albesher, Abdulmohsen S. King Faisal University Department of Infromation Systems Alahssa Saudi Arabia

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Millions of users rely on star ratings to decide which app is the best. However, it is not clear if there is a correlation between star ratings and how usable the apps are. In other words, there is a need to study if a better star rating means a better level of usability. The current study conducted an experimental study with 30 participants who were given three different apps with different star ratings (low-medium and high). Three sessions were recorded for every participant. In every session, an array of three tasks was performed. During each session of the usability experiment, quantitative data about the time taken to complete each task, task success, and the number of errors was collected to evaluate the factors: efficiency and effectiveness. After each session, the participant evaluated the app by answering a System Usability Scale (SUS) survey to evaluate the satisfaction factor. The results showed no correlation between user star rating and the usability of the tested apps. Additionally, the results showed no correlation between user star rating and any of the tested factors taken separately. © 2022 IEEE.

关键词： Usability engineering

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Vision Transformers-based Hand Gesture Classification 3

Vision Transformers-based Hand Gesture Classification

引用

3rd international informatics and software engineering conference, iisec 2022

作者： Al-Zebari, Adel Omar, Naaman Sengur, Abdulkadir Duhok Polytechnic University Department of Information Technology Duhok Iraq Firat University Department of Electrical-Electronics Engineering Elazig Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Hand gesture recognition (HGR) is a hot topic in machine learning and image processing communities. HGR is also vital for some Human-Computer Interaction (HCI) applications. Up to now, traditional machine learning approaches and deep convolutional neural networks (CNN) have been applied to HGR. Although these methods perform well enough on HGR, in this paper, we used a recent model namely vision transformer (ViT) on HGR. ViT is developed for improving the performance of CNN. ViT has a similar architecture to CNN but it has also different layers for the classification task. We used the ViT in a transfer learning fashion and applied it to the NTU hand gesture dataset. A holdout cross-validation test approach is considered in experiments and classification accuracy is used as a performance measure. The experimental works produce a 96.4% accuracy score and a comparative study with CNN models is carried out. Results show that the proposed model has potential in HGR. © 2022 IEEE.

关键词： Convolutional neural networks

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Twitter Sentiment Analysis using Naive Bayes Algorithm 3

Twitter Sentiment Analysis using Naive Bayes Algorithm

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3rd international informatics and software engineering conference, iisec 2022

作者： Mishra, Prashantkumar Patil, Sanjeev Anant Shehroj, Usama Aniyeri, Parvathi Khan, Talha Ali University of Europe for Applied Science Department of Tech & Software Potsdam Germany

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Sentiment analysis mines social media networks like Twitter for views, attitudes, and sentiments. It is presently a popular study subject. The traditional sentiment analysis approach emphasises textual data the most. Twitter is the most well-known microblogging social networking service, where users transmit updates on numerous topics as tweets. This research uses a publicly available labelled dataset on Kaggle. A comprehensive series of data cleaning and preparation techniques are organised to progressively make the tweets more comprehensible to typical language handling algorithms. Because each dataset sample consists of a pair of tweets and a sentiment, the Supervised machine learning concept was used in this work. Additionally, Nave Bayes-based sentiment analysis model is presented. The primary purpose is to discover tweet analysis more efficiently. Twitter sentiment analysis divides tweets into positive and negative attitudes. Using training data, machine learning algorithms correctly categorise the tweets. As a result, this strategy eliminates the requirement for a word database, making machine-learning approaches more effective and faster for sentiment analysis. © 2022 IEEE.

关键词： Sentiment analysis

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NOMA-enabled Cognitive Communication based on Hybrid Narrowband/Wideband SDR Waveform 3

NOMA-enabled Cognitive Communication based on Hybrid Narrowb...

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3rd international informatics and software engineering conference, iisec 2022

作者： Zeeshan, Muhammad Shahzad, Kashif Farooq, Muhammad Umar Walton Institute for Information & Communication Systems Science South East Technological University Waterford Ireland National University of Sciences and Technology College of e & Me Islamabad Pakistan

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

software defined radio (SDR) networks are required to achieve endurance, reliability, efficient data transmission, and adaptability to various operating requirements. Their immediate deployment in perilous ventures without the use of any permanent infrastructure has made them an inevitable choice for ad hoc tactical scenarios. The design of SDR waveforms face various challenges due to the rising requirements of cognition and reconfigurability. It is not possible to fulfill these heterogeneous and diverse requirements of quality-of-service (QoS) and range using either of the wideband or narrowband waveforms. This paper proposes an adaptive communication framework for the hybrid narrowband/wideband (NBWB) waveform to meet these requirements. We perform an experimental validation as a proof of concept for the reception of multiple signals by a radio configured in wideband mode. In addition, we develop a hybrid cognitive module (HCM) that is capable of selecting appropriate waveform with suitable system parameters. Owing to the advantages of higher spectral efficiency and user fairness, we propose to leverage non-orthogonal multiple access (NOMA) for parallel transmission from the narrowband waveform users within a single time slot. The numerical results and experimental validation demonstrates the effectiveness of the developed technology in SDR networks. © 2022 IEEE.

关键词： software radio

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Efficient Arabic Text Classification Using Feature Selection Techniques and Genetic Algorithm 3

Efficient Arabic Text Classification Using Feature Selection...

引用

3rd international informatics and software engineering conference, iisec 2022

作者： Al-Dulaimi, Ahmed Okkalioglu, Murat Institute of Graduate Studies Yalova University Department of Computer Engineering Yalova77200 Turkey Yalova University Faculty of Engineering Department of Computer Engineering Yalova77200 Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

The rapid growth of the Internet in recent years has been accompanied by a huge increase in the number of data being shared at every moment, especially text data. This huge amount of text data requires finding new techniques to be able to deal with the data. One form of these texts is the Arabic texts which poses a big challenge to researchers due to the highly derivative nature of Arabic texts. In this study, we first aim to create an effective classification model for Arabic texts, where we will start by creating a huge high-quality dataset consisting of different versions collected by web scraping techniques. Then, we apply term weighting (TW) and feature selection (FS) procedures to be able to classify our collected Arabic dataset and propose an approach that is based on genetic algorithm (GA) to ensure that the best subset of features is selected with high quality. The results prove that our proposed approach can select up to 1% of the original feature size with high efficiency. The results provide detailed information about the result of each classification technique and TW schemes, and runtime needed to obtain the best results to aid in future research aimed at developing Arabic text classification techniques. © 2022 IEEE.

关键词： Genetic algorithms

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Computational and Predictive Trust Game Model for Switching Process in fMRI 3

Computational and Predictive Trust Game Model for Switching ...

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3rd international informatics and software engineering conference, iisec 2022

作者： Candemir, Cemre Demir, Aslihan Gonul, Ali Saffet International Computer Institute Ege University Izmir Turkey Ege University Medical Faculty Dept. of Psychiatry Izmir Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Game theory paradigms allow analyzing experimentally through simulating the cognitive processes required for social cognition, such as perception, learning and decision-making, and actions. In this paper, the trust game paradigm, which is an extensively used task, is studied for measuring the trust. First, the trust game is designed as an fMRI task and then the trust data is acquired by running the task with n=80 subjects. Additionally, a computational mathematical model is proposed to model the subject-specific decision-making behavior by learning the previous game trials and then computing the difference between the actual and predicted gain, i.e., the prediction error (PE). The model is evaluated on two groups: depressed participants and healthy controls. The performance of the model is evaluated with the root mean square errors (RMSE) metric. The evaluation results show that even if the decision behavior of the participants exhibits different patterns, the proposed model can converge the actual gain fairly well with a low RMSE value. © 2022 IEEE.

关键词： Decision making

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A Comprehensive Big Data Framework for Energy Markets: Oil and Gas Demand Forecasting 3

A Comprehensive Big Data Framework for Energy Markets: Oil a...

引用

3rd international informatics and software engineering conference, iisec 2022

作者： Bayar, Alp Koc, Burcu Gokalp, Mert Onuralp Ozden, Baran Yeldan, Yigit Erhan Eren, P. Kocyigit, Altan Informatics Institute Middle East Technical University Ankara Turkey Data Analytics Center Tüpraş Ankara Turkey

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Demand forecasting in the energy sector is essential for both countries and companies to plan their supply and demand. Agents in the highly volatile oil markets have to act fast and data-driven. In the literature, studies on oil or gasoline demand forecasting are carried out using traditional econometric and AI-based models, using static data for long periods. In this paper, short-term gasoline demand forecasting literature has been investigated. We focus on short-term demand prediction based on big data analytics and investigate potential data sources and architectures to collect data. To this end, several iterative meetings were conducted between the Data Science department, the Oil Trading department of an Oil & Gas company, and researchers within an industry-academia cooperation project. Traditional data sources used for the problem are presented, and the applicability of real-time data to the problem is discussed. A big data architecture is proposed that can be used to predict the demand for petroleum products, mainly for gasoline in the U.S., for the transparency, amplitude, and availability of open data. © 2022 IEEE.

关键词： Forecasting

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Web-based Brief Screening Test for Identifying Twenty Common Psychological Disorders 3

Web-based Brief Screening Test for Identifying Twenty Common...

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3rd international informatics and software engineering conference, iisec 2022

作者： Ahmed, Iftekhar Farrok, Omar Fuad, Abu M. Brac University Dept. of Computer Science & Engineering Dhaka Bangladesh Ahsanullah University of Science & Technology Dept. of Electrical & Electronics Engineering Dhaka Bangladesh

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

As developing countries are facing psychologist and psychiatrist crises, screening tools can save time in consultancy. Although several screening tools are available, they are so time-consuming and none of them determines most of the common psychological disorders in a single test. To solve the problem and increase the treatment capability of psychologists or psychiatrists, a new psychological screening web application named 'MindSee' is proposed in this paper. It can detect 20 common psychological disorders within 10 minutes. It provides doctors with a brief map of the patient's overall information from food habit to mood swing without asking any questions manually. MindSee uses conditional logic and algorithm to cut-off redundant or repetitive questions according to the responder's answer choices to keep the duration of test within 10 minutes. With privacy, anyone can monitor one's progress of mental health from time to time taking MindSee screening test. MindSee is proposed as a psychological screening testing tool to support psychologists and psychiatrists. © 2022 IEEE.

关键词： Web services

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Algorithmically Navigating Complex Tabular Structures in Images for Information Extraction 3

Algorithmically Navigating Complex Tabular Structures in Ima...

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3rd international informatics and software engineering conference, iisec 2022

作者： Nugawela, Methmi Abeywardena, Kavinga Yapa Mahaadikara, Hansika Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

Computer vision has been in the forefront of automating workflows to replace manual repetitive tasks with convenience and accuracy. Recognizing text from images of commercial documents through optical character recognition (OCR) form the initial step of most such workflows where majority of their information are in the form of complex data structures such as tables and nested tables. Although OCR technology has evolved to effectively capture text from images, there is still room for improvement in recognizing complex data structures and extracting tabular data from images. This paper proposes an algorithmic approach based on keyword detection and the position of words relative to each other in order to recognize nested structures and successfully extract tabular data into a program and human readable format, which aims to take a different approach as opposed to using machine learning models or pre-defined templates for layout recognition. Furthermore, this approach is shown to yield successful results in correctly comprehending the layout and data of nested table structures in multiple rows in a table. © 2022 IEEE.

关键词： Optical character recognition

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