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Exploiting the sequential nature of genomic data for improved analysis and identification

Computers in Biology and Medicine 2024年 183卷 109307-109307页

作者： Nawaz, M. Saqib Nawaz, M. Zohaib Junyi, Zhang Fournier-Viger, Philippe Qu, Jun-Feng College of Computer Science and Software Engineering Shenzhen University China Faculty of Computing and Information Technology Department of Computer Science University of Sargodha Pakistan School of Computer Engineering Hubei University of Arts and Science Hubei Xiangyang China

Genomic data is growing exponentially, posing new challenges for sequence analysis and classification, particularly for managing and understanding harmful new viruses that may later cause pandemics. Recent genome sequence classification models yield promising performance. However, the majority of them do not consider the sequential arrangement of nucleotides and amino acids, a critical aspect for uncovering their inherent structure and function. To overcome this, we introduce GenoAnaCla, a novel approach for analyzing and classifying genome sequences, based on sequential pattern mining (SPM). The proposed approach first constructs and preprocesses datasets comprising RNA virus genome sequences in three formats: nucleotide, coding region, and protein. Then, to capture sequential features for the analysis and classification of viruses, GenoAnaCla extracts frequent sequential patterns and rules in three forms and in codons. Eight classifiers are utilized, and their effectiveness is assessed by employing a variety of evaluation metrics. A performance comparison demonstrates that the suggested approach surpasses the current state-of-the-art genome sequence classification and detection techniques with a 3.18% performance increase in accuracy on average. © 2024 Elsevier Ltd

关键词： Genome

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Integration of Artificial Intelligence and Wearable Internet of Things for Mental Health Detection

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 307-315页

作者： Wang, Wei Chen, Jian Hu, Yuzhu Liu, Han Chen, Junxin Gadekallu, Thippa Reddy Garg, Lalit Guizani, Mohsen Hu, Xiping Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China School of Medical Technology Beijing Institute of Technology Beijing100081 China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518000 China School of Software Dalian University of Technology Dalian116621 China Division of Research and Development Lovely Professional University Phagwara India Center of Research Impact and Outcome Chitkara University Punjab India Faculty of Information and Communication Technology University of Malta Msida Malta United Arab Emirates

The integration of Artificial Intelligence (AI) and Wearable Internet of Things (WIoT) for mental health detection is a promising area of research with the potential to revolutionize mental health monitoring and diagnosis. Since early detection of mental diseases, i.e., depression, is of great importance for diagnosis and treatment, a fast and convenient way is urgently needed. Traditional diagnostic methods are time-consuming, laborious, over-subjective, and easily lead to misdiagnosis. The advance in information techniques and wearable devices brings innovation to mental disease detection. Therefore, this article first compares intelligent depression detection methods and traditional methods to illustrate the significance and then analyzes the opportunities of the wearable device. Then we provide specific psychophysiological data measured by wearable devices and introduce relevant datasets for depression detection. An illustrative example of depression detection with sleep data is presented and discussed and our proposed ensemble method has improved nearly 10% to baselines. Analytical results demonstrate the great potential of using wearable device-measured psychophysiological data to detect depression intelligently. © 2024 The Authors

关键词： Internet of things

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Assessing Cybersecurity Awareness among The Hashemite University Students In Terms Of Computer Usage

Assessing Cybersecurity Awareness among The Hashemite Univer...

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Ashraf H. Aljammal Ahmad Qawasmeh Salah Taamneh Fadi Wedyan Mamoon Obiedat Hani Bani Salameh Department of Computer Science and Applications Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan Department of Engineering Computing and Mathematical Sciences Lewis University Romeoville Illinois USA Department of Information Technology Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan Department of Software Engineering Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

Internet usage among information technology users has expanded substantially, as have cybercrimes with potentially disastrous repercussions. Therefore, internet users have to employ the available security measures and policies during internet usage. Nowadays, University students make up a sizable portion of internet users. This study assesses the cybersecurity awareness among The Hashemite University students In terms of Computer Usage. A questionnaire survey is used to assess students’ cybersecurity knowledge while using their PCs and connecting to the internet, concentrating on their behaviors and use of security measures.

关键词： Surveys Malware Internet Computer security information technology Computer crime Artificial intelligence

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Customers' sentiment on food delivery services: An Arabic text mining approach

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International Journal of information Management Data Insights 2024年第2期4卷

作者： Mustafa, Dheya Khabour, Safaa M. Shatnawi, Ahmed S. Department of Computer Engineering Faculty of Engineering The Hashemite University Zarqa 13133 Jordan Department of Information Systems Faculty of Information Technology and Computer Sciences Yarmouk University Irbid 21163 Jordan Department of Software Engineering Jordan University of Science & Technology Irbid 21110 Jordan

The Covid-19 pandemic has accelerated the shift in organizations' strategies toward innovative online services. Customer reviews on platforms for online ordering and delivery are a vital source of information about how well a business is performing. Businesses that provide food delivery services (FDS) seek to leverage consumer input to locate areas where customer satisfaction could be raised. Sentiment analysis (SA) has been the subject of an enormous amount of English-language research. Despite Arabic's increasing popularity as a writing language on the Internet, not much study has been conducted on sentiment analysis of Arabic up to this point, with a limited number of publicly available resources for Arabic SA such as datasets and lexicons. The present study collects FDS-related reviews in Arabic to conduct extensive emotion mining, taking advantage of Natural Language Processing, feature selection, and Machine Learning techniques to elicit personal judgments, identify polarity, and recognize customers’ feelings in the FDS domain. To demonstrate that the proposed approach is suitable for analyzing human perceptions of FDS, we designed and carried out excessive experiments that assess the utility of each phase. Our highest categorization accuracy was 90 % using Mutual information with the SVM classifier. The study's findings provide various managerial insights for improving their plans and service delivery, as well as revealing the main reasons for consumer complaints. It also demonstrates how future academics might harness the power of online business reviews in Arabic using a variety of text-mining approaches. © 2024 The Author(s)

关键词： Arabic dialects Arabic sentiments resources Consumer sentiment Features selection Food delivery services Machine learning

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Deepfake Detection using EfficientNet: Working Towards Dense Sampling and Frames Selection

Deepfake Detection using EfficientNet: Working Towards Dense...

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2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022

作者： To, Tuan-An Luong, Hoang-Chau Nguyen, Nham-Tan Nguyen, Trong-Tin Tran, Minh-Triet Do, Trong-Le University of Science Vnuhcm Faculty of Information Technology and Software Engineering Laboratory Ho Chi Minh City Viet Nam Viet Nam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9781665461665

Deepfake is a controversial technology that allows the automatic generation of video content through generative adversarial networks. The emergence of Deepfake technology is problematic and sophisticated, making it more difficult to detect. In our paper, we contribute a deep-learning method to resolve that problem. We use the MTCNN face detector to extract facial images and apply data augmentation and EfficientNet for real-fake classification. We apply frame selection with the raw label prediction to tackle the fault cases and receive the final label. With the approach above applied, we utilize training and evaluation datasets from FaceForensics++ and achieve an accuracy of 62.5%. © 2022 IEEE.

关键词： Generative adversarial networks

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A New Chaotic Based Cryptographically Secure Pseudo Random Number Generator

A New Chaotic Based Cryptographically Secure Pseudo Random N...

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International Conference on Wavelet Active Media technology and information Processing (ICWAMTIP)

作者： Sarra Senouci Sid Ali Madoune Mohammed Raouf Senouci Abdelkader Senouci Tang Zhangchuan School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Engineering and Environment Northumbria University Newcastle United Kingdom

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

This paper introduces a novel chaotic-based pseudo-random number generator (PRNG) architecture utilizing the Lorenz system. We examine an enhanced model, employing techniques such as Euler integration, bifurcation analysis, and autocorrelation functions. Our enhanced model, featuring a feedback mechanism, demonstrates superior output distribution, complexity, and randomness, confirmed through successful testing using the NIST SP800-22 suite. Based on these results, we regard this improved model as a cryptographically secure pseudo-random number generator (CSPRNG).

关键词： NIST Bifurcation White noise Media Generators Autocorrelation Reliability Random number generation Testing Random sequences

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Suggestion Mining from Opinionated Text of Big Social Media Data

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Computers, Materials & Continua 2021年第9期68卷 3323-3338页

作者： Youseef Alotaibi Muhammad Noman Malik Huma Hayat Khan Anab Batool Saif ul Islam Abdulmajeed Alsufyani Saleh Alghamdi Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Department of Computer Science Faculty of Engineering and Computer SciencesNational University of Modern LanguagesIslamabadPakistan Department of Software Engineering Faculty of Engineering and Computer SciencesNational University of Modern LanguagesIslamabadPakistan Department of Computer Sciences Institute of Space TechnologyIslamabadPakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and *** increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making *** overcome this challenge,extracting suggestions from opinionated text is a possible *** this study,the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’reviews.A classification using a word-embedding approach is used via the XGBoost *** two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews.F1,precision,recall,and accuracy scores are *** results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%.Moreover,the results revealed that suggestion keywords and phrases are the predominant features for suggestion ***,this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews.

关键词： Suggestion mining word embedding Naïve Bayes random forest XGBoost dataset

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Smart Photo Editor for Differently-abled People using Assistive technology 6

Smart Photo Editor for Differently-abled People using Assist...

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6th International Conference on information technology Research, ICITR 2021

作者： Buddhika, A.S. Wijesekera, P.K. Kavindu, D. G. Hasintha Dinusha, Dilshan S Arachchillage, Udara Srimath S. Samaratunge Kuruppu, Thilmi Anuththara Faculty of Computing Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665420006

Differently-abled people are significant minority groups, have many limitations to live everyday life, are starved of services, and are mostly ignored by society due to many types of disabilities. This problem may lead to massive frustrations and disappointments among themselves. Assistive technology may easily fill this gap with the enhanced different aiding applications. It helped in various ways, such as helping them to interact, communicate with people and allow people to do basic daily tasks by themselves. Nevertheless, there were fewer applications developed to entertain their leisure time. Therefore, the proposed solution provides a Smart Photo Editor, a hand-free mobile application with attractive photo editing features. This application focused on people having hand motor disabilities. Users can interact with the application using simple head gestures, eye gaze, and eye blinks. Head gestures and eye blinks are used as commands for application operations, while eye gaze is used for cursor enabling, which is helpful for navigation on application screens. Machine Learning (ML) and image processing techniques are used for real-time gesture recognition and eye gaze detection, using the input video frames captured by the inbuilt front-facing camera of the mobile phone. Moreover, in addition to the image processing techniques, Mask Recurrent-Convolutional Neural Network (R-CNN) is used to develop enhanced image adjusting features and customization of backgrounds based on object detection. © 2021 IEEE.

关键词： Image enhancement

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Utilizing Organizational Patterns to Build High-Performing Remote Teams 23

Utilizing Organizational Patterns to Build High-Performing R...

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Proceedings of the 28th European Conference on Pattern Languages of Programs

作者： Kristián Toldy Waheedullah Sulaiman Khail Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia Helmholtz-Zentrum Berlin für Materialien und Energie Gmbh Germany

ISBN: (纸本)9798400700408

In recent years, remote work has become a more popular option for companies across various industries. While remote work provides numerous benefits, such as flexibility and increased work-life balance, it also presents unique challenges that can hinder team collaboration, productivity, and overall success. In order to overcome these obstacles, it is essential to adopt effective organizational patterns that can help build high-performing remote teams. Building a high-performing remote team requires a set of strategies with some key focus points to be kept in mind such as communication, trust, goals, collaboration, and performance. For all of these, there have been an extensive research and publication of observed patterns to which we have also contributed with a new set of these four patterns: Use Common Language, Discuss Publicly, Lights, Camera, Action!, and Praise in Public, Correct in Private.

关键词： agile communication distributed teams meeting organizational patterns remote work

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Stakeholder Identification Overview and Challenges in Requirements engineering Prospective 2

Stakeholder Identification Overview and Challenges in Requir...

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2nd International Conference on Computing and information technology, ICCIT 2022

作者： Elneel, Duha Awad Fakharudin, Abdul Sahli Ahmed, Elsadig Musa Kahtan, Hasan Abdullateef, Mansoor Universiti Malaysia Pahang Faculty of Computing Kuantan26300 Malaysia Multimedia University Faculty of Business Melaka Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur50603 Malaysia Knowbis Solutions Consultancy Selangor Malaysia

ISBN: (纸本)9781665436052

Stakeholder identification (SI) illustrates a critical part of the requirements elicitation activity. It helps software analysts gather accurate system requirements to ensure high quality and avoid system failure. Stakeholder identification considered one of the earliest stages of project development. The main problem related to project success and failure is identifying the real stakeholders and selecting the right one. The lack of stakeholder identification methodologies and the shortage of previous research in identifying the stakeholders for different systems, encourage the research to propose a guideline framework, assist analysts in building the convenient methodology for identifying real stakeholders. Stakeholders are defined based on different projects and the various services they provide. This difference leads to the fact that a particular and systematic technique must be used to identify stakeholders based on the project's types. The exploration of stakeholder identification matters and the guideline framework is a baseline for future research in requirements engineering. © 2022 IEEE.

关键词： Requirements engineering

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