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2022 applied Informatics International Conference, AiIC 2022

作者： Al Maashri, Issaa Mohamed Hassan Ghosh, Shounak Bukar, Umar Ali University of Technology and Applied Sciences Academic Electronic Systems Center Muscat Oman School of Computing and Technology Malaysia Universiti Putra Malaysia Faculty of Computer Science and Information Technology Malaysia

ISBN: (数字)9781728184289

ISBN: (纸本)9781728184289

As a consequence of the Covid-19 outbreak, students are required to stay at home to prevent the virus from spreading. This has resulted in a quick acceptance of online learning, as students and faculty cannot participate in in-class activities. This study examines the determinants affecting E-Learning uptake in Oman during the Covid-19 outbreak, using 223 student responses and structural equation modeling (SEM). Four hypotheses were supported, while two were rejected. Specifically, perceived ease of use, perceived usefulness, and institutional support affect behavioral intention to adopt E-Learning. However, infrastructure support and privacy risk, on the other hand, were not. Thus, this research serves as a springboard for higher education officials to increase the use of E-Learning and adjust to student hurdles for students to comprehend and effectively use the system. © 2022 IEEE.

关键词： E-learning

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Does Human Factor Contribute to Mining Accidents? A Systematic Literature Review Approach

Does Human Factor Contribute to Mining Accidents? A Systemat...

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Human Engineering Symposium, HUMENS 2021

作者： Ismail, Siti Noraishah Ramli, Azizan Faculty of Industrial Sciences and Technology College of Computing and Applied Sciences Universiti Malaysia Pahang Kuantan Pahang Malaysia Faculty of Chemical and Process Engineering Technology College of Engineering Technology Universiti Malaysia Pahang Kuantan Pahang Malaysia

ISBN: (纸本)9789811641145

Human factor always has been debated as the key factor contributes to industrial accidents such as manufacturing, construction and many more. However, there are lack of studies globally within this research to review and prove the human factor is a primary cause of accidents at mining industry. The objective of this systematic literature review (SLR) study is to investigate the dominant factor contributes to mining accidents by applying a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. Three main themes and fifteen subthemes have been developed based on 25 selected articles from Scopus database. The findings showed the organizational factor is the most dominant contributor to mining accidents (53%) followed by human factor (27%) and situational factor (20%). In conclusion, this finding hopefully could facilitate mine owners to improve organizational safety concern and provide a healthy safety culture in reducing mining accidents in future. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mining accidents Mining industry Organizational factor Preferred reporting items for systematic reviews and meta-analyses Systematic literature review

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Architecture optimization model for the probabilistic self-organizing maps

Architecture optimization model for the probabilistic self-o...

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International Conference on Big Data, Cloud and Applications, BDCA 2015

作者： En-Naimani, Zakariae Lazaar, Mohamed Ettaouil, Mohamed Modeling and Scientific Computing Laboratory Faculty of Science and Technology Fez Morocco National School of Applied Sciences Abdelmalek Essaadi University Tetouan Morocco

The PRobabilistic Self-Organizing Maps (PRSOM) become more and more interesting in many fields such as: pattern recognition, clustering, classification, speech recognition, data compression, medical diagnosis, etc. The PRSOM give an estimation of the density probability function of the data, which depends on the parameters of the PRSOM, such as the architecture of the network. When we take a random PRSOM architecture choice (the number of neurons or components), we could have degenerated solutions, called also singular solutions. Associated with a given problem, it is one of the most important research problems in the neural network research. In the present paper we describe a recent approach of probabilistic self-organizing maps (PRSOM) trying to propose a solution to this problem. We propose a speech compression technique based on vector quantization. The main innovation is the use of an optimal probabilistic self-organizing map to determine the optimal codebook, unlike in classical PRSOM. Also, we give an implementation and an evaluation of the proposed method;the numerical results are powerful and show the practical interest of our approach.

关键词： Self organizing maps

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Legacy Moderization: A Cloud Migration Strategy with Serverless Microservice Architecture

Legacy Moderization: A Cloud Migration Strategy with Serverl...

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2023 International Conference on Intelligent computing and Control, IC and C 2023

作者： Ang, Qi Zhi Yau, Peter Chunyu Sum, Chin Sean Cao, Qi Wong, Dennis University of Glasgow School of Computing Science United Kingdom Singapore Institute of Technology Singapore Macao Polytechnic University Faculty of Applied Sciences China

ISBN: (纸本)9781665457095

This paper provides an overview, presents the work-in-progress study of how software architecture can be modernized using the latest technologies. We will discuss the reasons why software modernization is required, how to choose an optimal solution from the architecture perspective, related migration strategy and the related points to note. The paper will also discuss some of the common issues faced while reviewing the architecture. These issues would provide some insights to some frequently faced problems in development and deployment. Finally, a discussion on how containerization technology and load balancer could help in resolving some of the common issues faced. In this paper, we have evaluated our proposed approach in a realistic case study involving an actual organization, which was anonymized for identity protection A certain organization would be used to provide the corresponding review mentioned. © 2023 IEEE.

关键词： Legacy systems

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Child Head Gesture Classification through Transformers

Child Head Gesture Classification through Transformers

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2022 IEEE Region 10 International Conference, TENCON 2022

作者： Wedasingha, Nushara Samarasinghe, Pradeepa Singarathnam, Dharshika Papandrea, Michela Puiatti, Alessandro Seneviratne, Lasantha Sri Lanka Institute of Information Technology Faculty of Computing Sri Lanka University of Applied Sciences and Arts of Southern Switzerland Switzerland University of Applied Sciences and Arts of Southern Switzerland Switzerland

This paper proposes a transformer network for head pose classification (HPC) which outperforms the existing SoA for HPC. This robust model is then extended to overcome the limited child data challenge by applying tran... 详细信息

ISBN: (数字)9781665450959

ISBN: (纸本)9781665450959

关键词： Transfer learning

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An Abstractive Summarization Technique with Variable Length Keywords as per Document Diversity

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Computers, Materials & Continua 2021年第3期66卷 2409-2423页

作者： Muhammad Yahya Saeed Muhammad Awais Muhammad Younas Muhammad Arif Shah Atif Khan M.Irfan Uddin Marwan Mahmoud Department of Software Engineering Government College UniversityFaisalabadFaisalabad38000Pakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Department of Computer Science Islamia College PeshawarPeshawarPakistan Institute of Computing Kohat University of Science and TechnologyKohatPakistan Faculty of Applied Studies King Abdulaziz UniversityJeddahSaudi Arabia

Text Summarization is an essential area in text mining,which has procedures for text *** natural language processing,text summarization maps the documents to a representative set of descriptive ***,the objective of text extraction is to attain reduced expressive contents from the text *** summarization has two main areas such as abstractive,and extractive *** text summarization has further two approaches,in which the first approach applies the sentence score algorithm,and the second approach follows the word embedding *** such text extractions have limitations in providing the basic theme of the underlying *** this paper,we have employed text summarization by TF-IDF with PageRank keywords,sentence score algorithm,and Word2Vec word *** study compared these forms of the text summarizations with the actual text,by calculating cosine ***,TF-IDF based PageRank keywords are extracted from the other two extractive *** intersection over these three types of TD-IDF keywords to generate the more representative set of keywords for each text document is *** technique generates variable-length keywords as per document diversity instead of selecting fixedlength keywords for each *** form of abstractive summarization improves metadata similarity to the original text compared to all other forms of summarized *** also solves the issue of deciding the number of representative keywords for a specific text *** evaluate the technique,the study used a sample of more than eighteen hundred text *** abstractive summarization follows the principles of deep learning to create uniform similarity of extracted words with actual text and all other forms of text *** proposed technique provides a stable measure of similarity as compared to existing forms of text summarization.

关键词： Metadata page rank sentence score word2vec cosine similarity This

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A Deep Learning Based Approach for Janya Raga Classification in Carnatic Music 6

A Deep Learning Based Approach for Janya Raga Classification...

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6th SLAAI International Conference on Artificial Intelligence, SLAAI-ICAI-2022

作者： Kavitha, P. Charles, J. Lekamge, L.S. Sabaragamuwa University of Sri Lanka Faculty of Applied Sciences Department of Computing and Information Systems Belihuloya Sri Lanka Sabaragamuwa University of Sri Lanka Faculty of Applied Sciences Department of Physical Sciences and Technology Belihuloya Sri Lanka

ISBN: (纸本)9781665476072

Janya Ragas are Carnatic music ragas derived from the fundamental ragas called Melakarta Raga, by the permutation and combination of various ascending and descending swaras. Raga recognition is an important task, essential to research in Music Information Retrieval in Indian Classical Music. Even though the automatic raga recognition methods have been widely adopted in Carnatic music, most of the existing methods are restricted only to Melakarta Ragas. It is an important task to identify the Melakarta Raga of a Janya Raga, especially for improved music recommendation performance. In this study, we used deep learning-based approach to address this problem. Music files were collected for 65 Janya Ragas belonging to seven Melakarta Ragas. Classification-based supervised deep learning models: 1D CNN, LSTM and 1D CNN-LSTM were used in the study. The models were implemented to learn similarities from 1-20 mean values of Mel-Frequency Cepstral Coefficients (MFCCs) features of audio samples, by using TensorFlow and Keras APIs. The results revealed that the 1D CNN-LSTM model outperformed the other models with an accuracy of 82.0%. In the future, 1D CNN-LSTM based Siamese neural networks can be introduced to reduce the dependence on large amounts of labeled audio data. © 2022 IEEE.

关键词： Music

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3D Semantic Deep Learning Networks for Leukemia Detection

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Computers, Materials & Continua 2021年第10期69卷 785-799页

作者： Javaria Amin Muhammad Sharif Muhammad Almas Anjum Ayesha Siddiqa Seifedine Kadry Yunyoung Nam Mudassar Raza University of Wah Wah CanttPakistan COMSATS University Islamabad Wah CampusPakistan National University of Technology(NUTECH) IJP Road IslamabadPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

White blood cells(WBCs)are a vital part of the immune system that protect the body from different types of bacteria and *** cell growth destroys the body’s immune system,and computerized methods play a vital role in detecting abnormalities at the initial *** this research,a deep learning technique is proposed for the detection of *** proposed methodology consists of three *** I uses an open neural network exchange(ONNX)and YOLOv2 to localize *** localized images are passed to Phase II,in which 3D-segmentation is performed using deeplabv3 as a base network of the pre-trained Xception *** segmented images are used in Phase III,in which features are extracted using the darknet-53 model and optimized using Bhattacharyya separately criteria to classify *** proposed methodology is validated on three publically available benchmark datasets,namely ALL-IDB1,ALL-IDB2,and LISC,in terms of different metrics,such as precision,accuracy,sensitivity,and dice *** results of the proposed method are comparable to those of recent existing methodologies,thus proving its effectiveness.

关键词： YOLOv2 darknet53 Bhattacharyya separately criteria ONNX

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Retinal Vessel Segmentation with Slime-Mould-Optimization based Multi-Scale-Matched-Filter 7

Retinal Vessel Segmentation with Slime-Mould-Optimization ba...

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7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021

作者： Kadry, Seifedine Rajinikanth, Venkatesan Damasevicius, Robertas Taniar, David Noroff University College Faculty of Applied Computing and Technology Kristiansand Norway St. Joseph's College of Engineering Department of Electronics and Instrumentation Engineering Chennai600119 India Silesian University of Technology Faculty of Applied Mathematics Gliwice44-100 Poland Monash University Faculty of Information Technology ClaytonVIC3800 Australia

ISBN: (纸本)9781665441261

Even though a number of sensory organs are existing, eye plays a necessary role in the sensory system;which converts the incident light into meaningful visual information. If any abnormality arises in eye, then the whole sensory system gets stressed. The disease in eye is due to injury, infection and ageing and the untreated eye disease will lead to vision loss. The proposed research aims to propose a Computer-Aided-Procedure (CAP) to extract the blood-vessel section from Digital-Fundus-Image (DFI). In order to accomplish this task, a Multi-Scale-Matched-Filter (MSMF) is designed using the Slime-Mould-Optimization algorithm. In this work, the necessary test images are collected from the benchmark DRIVE and CHASE_DB1 dataset. After extracting the blood-vessel using the MSMF, an examination among extracted vessel and the Ground-Truth (GT) image is executed and the Image-Performance-Values are separately computed for each database. The attained result with this CAP confirms that the attained Jaccard, Dice and Accuracy of proposed approach is better compared to similar existing approaches in the literature. © 2021 IEEE.

关键词： Matched filters

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Extraction of Abnormal Skin Lesion from Dermoscopy Image using VGG-SegNet 7

Extraction of Abnormal Skin Lesion from Dermoscopy Image usi...

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7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021

作者： Kadry, Seifedine Taniar, David Damasevicius, Robertas Rajinikanth, Venkatesan Lawal, Isah A. Noroff University College Faculty of Applied Computing and Technology Kristiansand Norway Monash University Faculty of Information Technology ClaytonVIC3800 Australia Silesian University of Technology Faculty of Applied Mathematics Gliwice44-100 Poland St. Joseph's College of Engineering Department of Electronics and Instrumentation Engineering Chennai600119 India

ISBN: (纸本)9781665441261

Skin is one of the vital and well-known sensory organs in human physiology and due to various reasons, the abnormality in skin arises. Skin Melanoma (SM) is one of the medical crisis in humans and the untreated SM will cause various abnormalities, such as skin irritation, spreading the cancerous cells through the blood stream, etc. Efficient assessment of the SM is essential to identify the severity of the disease and hence the proposed work implemented a Convolutional-Neural-Network (CNN) based approach to support the automated SM examination. This work employed the VGG-SegNet scheme to extract the SM section from the Digital-Dermoscpy-Image (DDI). After the extraction, a relative assessment between the segmented SM and the Ground-Truth (GT) is executed and the essential performance indices are then computed. The proposed scheme is tested and validated using the benchmark ISIC2016 database and the average result attained with the proposed study helped to achieve a better values of Jaccard-Index, Dice, and Accuracy for the DDI with and without the artifacts. These results confirm that, proposed technique is significant in evaluating the clinical grader DDI. © 2021 IEEE.

关键词： Extraction

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