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15th International Conference on Soft computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Uma Maheswari, V. Aluvalu, Rajanikanth Guduri, Manisha Kantipudi, M. V. V. Prasad Department of Computer Science and Engineering Chaitanya Bharati Institute of Technology Telangana Hyderabad India Pune India School of Computing and Informatics University of Louisiana at Lafayette LafayetteLA70503 United States University Pune412115 India

ISBN: (纸本)9783031810794

The COVID - 19 disease is a extremely contagious viral infection with significant global health insinuations. COVID has a negative impact on the world economy. If positive patients are identified early, the proliferation of this pandemic infection can be slackened. COVID-19 disease prophecy is useful for finding the people with health issues who are at risk of COVID. The Deep Learning and machine learning approaches for COVID prediction using X-ray images have the possibility to be tremendously helpful in addressing the shortage of clinicians and doctors in rural areas. This research presents a deep layered Convolutional Neural Network (CNN) for recognizing the COVID-19 patients by training the system with the datasets of around 6000 chest X-ray images collected from various sources. We are categorized them as normal or COVID - impacted. Our model trained the X-ray images of chest to find these patients. And it also predicted well with the help of image analysis and deep learning by showcasing the better results comparing with the state-of-the-art methods in terms of the average accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： COVID-19

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Swa Bhasha 2.0: Addressing Ambiguities in Romanized Sinhala to Native Sinhala Transliteration Using Neural Machine Translation

Swa Bhasha 2.0: Addressing Ambiguities in Romanized Sinhala ...

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Advanced Research in computing (ICARC), International Conference on

作者： Sachithya Dharmasiri T.G.D.K. Sumanathilaka School of Computing Informatics Institute of Technology Colombo Sri Lanka Department of Computer Science Swansea University Swansea Wales United Kingdom

With the growing popularity of social media and instantaneous messaging, it is more important than ever to interact online in your native language. In Sinhala, both Romanized and native Sinhala are widely used. Due to the informal textual abbreviation known as “Singlish” however, attempts to translate Romanized Sinhala into native Sinhala via machine transliteration may result in errors. Rule-based transliteration systems may not be compatible with the ad hoc transliterations used in Singlish. To translate Romanized Sinhala back precisely and consistently into Native Sinhala, a novel NMT approach has been proposed. To address the complexities of casual Romanized Sinhala, a hybrid strategy combining rule-based and neural machine translation has been proposed. This strategy aims to eliminate word selection ambiguity by selecting the best word suggestions from a pool of predicted words using a suggestion algorithm. Combining the advantages of Suggestion algorithms and neural machine translation, the proposed transliterator has the potential to considerably enhance reverse transliteration and improve communication in native Sinhala by combining the strengths of both approaches. After completing the GRU model, the performance of the machine translation models on the BLEU test improved to 0.8, indicating high word-level translation accuracy. Significant potential exists for the proposed transliterator to enhance reverse transliteration and improve communication in Sinhala. While preliminary test results are promising, additional testing and refinement are required to improve the overall efficacy of machine translation models.

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Exploring Computational Linguistics Techniques for Enhanced Outing Planning: A Comprehensive Review

Exploring Computational Linguistics Techniques for Enhanced ...

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Advanced Research in computing (ICARC), International Conference on

作者： Faizan Muthaliff T.G.D.K. Sumanathilaka School of Computing Informatics Institute of Technology Colombo Sri Lanka Department of Computer Science Swansea University Swansea Wales United Kingdom

In this day and age where convenience is king a new competitor in the form of chat-bots has appeared which requires users to only have prior knowledge on the language the chat-bot converses in. When it comes to planning outings there are a multitude of criteria to be wary of to determine the ideal solution. This review paper will address the common issues with extracting meaningful information from the user utilizing modern NLP techniques, the required criteria in addition to the user input such as, real time weather information and communicable diseases pertaining to the outing location, to determine an ideal suggestion and finally the method in which said ideal suggestion is determined after prioritizing criteria. The conclusion underscores that while NLP applications might not entirely replace existing menu-based systems for outing planning, they excel in certain scenarios. Notably, NLP's innate capacity to comprehend user preferences and context allows it to offer tailored outing suggestions. Furthermore, the application's unique feature of dynamically adapting to user requests without necessitating a return to the home page adds a distinctive advantage to its usability.

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Image Fusion for Single-Trait Multimodal Biometrics: A Brief Review 20

Image Fusion for Single-Trait Multimodal Biometrics: A Brief...

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20th IEEE Student Conference on Research and Development, SCOReD 2022

作者： Ariffin, Syed Mohd Zahid Syed Zainal Jamil, Nursuriati Kasinathan, Vinothini Centre of Foundation Studies Universiti Teknologi MARA Dengkil Malaysia College of Computing Informatics and Media Universiti Teknologi MARA Shah Alam Malaysia School of Computing Asia Pacific University of Technology and Innovation Kuala Lumpur Malaysia

ISBN: (数字)9781665474887

ISBN: (纸本)9781665474887

Biometrics is a process of determining an individual's identity based on their personal traits. Most of the available biometrics applications are based on physical traits, such as fingerprint, face and ear. All biometrics traits have their own drawbacks, such as occlusion, illumination, and pose variation. To overcome these issues, image fusion approach has been proposed in several studies to improve the performance of biometrics applications. Image fusion may happen at three levels (i.e. pixel, feature, and score). Implementation of image fusion approach in biometrics is generally called multimodal biometrics. In multimodal biometrics, source images to be fused can be taken from a single trait (same biometrics trait, e.g., thermal and visible face images) or multiple traits (different biometrics traits, e.g., fusion of ear and fingerprint). In addition, multimodal biometrics also can be done based on a single trait, such as fusion of thermal and visible face image or fusion of features extracted from one trait (e.g., LBP and HOG features of the ear). This paper describes and discusses image fusion implementation at the mentioned three levels, using a single biometrics trait. © 2022 IEEE.

关键词： Biometrics

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Advancing Color Perception: An IoT-driven Pedagogical System for Visually Impaired Children

Advancing Color Perception: An IoT-driven Pedagogical System...

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Advances in Signal Processing, Power, Communication, and computing (ASPCC), IEEE International Conference on

作者： Prasandika Balage Nuwan Jayawardene School of Computer Science and Engineering University of Westminster London United Kingdom Department of Computing Informatics Institute of Technology Colombo Sri Lanka

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

Visual impairment is characterized by the loss of vision, encompassing both complete blindness and partial vision loss. Studies reveal a notable prevalence of visual impairment among school-aged children. The significance of colors in acquiring and discerning visual information is crucial, aiding children in effectively perceiving and comprehending their surroundings. This study presents an Internet of Things (IoT) system designed for teaching colors to visually impaired children. The system achieved an accuracy rate surpassing 77.8%, and it is operated effectively regardless of surrounding lighting conditions. Given that the target users of the system are visually impaired children, this research was conducted in close alignment with Human-Computer Interaction (HCI) principles.

关键词： Human computer interaction Visualization Accuracy Visual impairment Education Lighting Color Blindness Signal processing Internet of Things

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Supply Chain Optimization: Bibliometric Analysis of Mathematical Models Emphasizing Sustainability and Global Trends

Supply Chain Optimization: Bibliometric Analysis of Mathemat...

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Agrosystem Engineering, technology & Applications (AGRETA), IEEE International Conference on

作者： Najihan Awang Ali Adibah Shuib Ismail Rakibe School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Perak Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia Faculty of Plantation and Agro technology Universiti Teknologi MARA Melaka Malaysia

ISBN: (数字)9798350373660

ISBN: (纸本)9798350373677

Understanding the need for lean supply chains to reduce costs, improve efficiency, and address carbon emissions, climate change, and sustainability concerns has developed over recent years. Advanced quantitative supply chain optimization models and novel solution methods are needed to meet these challenges. This study provides comprehensive insights into supply chain optimization via mathematical models, focusing on agricultural supply chains, sustainability, and global trends. The bibliometric analysis used data from Scopus, covering the period from 1988 to August 23, 2023, totaling 1,778 papers. Microsoft Excel was used for frequency analysis due to its robust data handling capabilities, VOSviewer for data visualization, and Harzing's Publish or Perish for comprehensive citation metrics and analysis. The study examines trends and impacts of publications, identifies the most productive and influential countries, institutions, and authors, and highlights highly cited articles and prevalent themes in supply chain optimization. Findings demonstrate high average citations, indicating active scholarly debate on major supply chain optimization mathematical model issues. The top three nations demonstrating the most robust crossnational collaboration are China, the United States, and Iran, highlighting significant global engagement. VOSviewer visualizations identify areas for further research, including sustainable agriculture supply chain models integrating environmental considerations, resilient global supply chain networks, and real-time adaptive optimization models enabled by big data and AI technologies. These areas are crucial for achieving economic efficiency, food security, waste management and environmental sustainability, echoing the themes of innovation, sustainability, and global collaboration. This research contributes to the rapidly emerging literature on worldwide trends in supply chain optimization using mathematical modeling. It investigates growing issues

关键词： Adaptation models Optimization models Biological system modeling Supply chains Bibliometrics Data visualization Market research Real-time systems Sustainable development Optimization

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Enhancing Spatiotemporal Traffic Prediction through Urban Human Activity Analysis

arXiv

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arXiv 2023年

作者： Han, Sumin Park, Youngjun Lee, Minji An, Jisun Lee, Dongman School of Computing Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Luddy School of Informatics Computing and Engineering Indiana University Bloomington Bloomington United States

Traffic prediction is one of the key elements to ensure the safety and convenience of citizens. Existing traffic prediction models primarily focus on deep learning architectures to capture spatial and temporal correlation. They often overlook the underlying nature of traffic. Specifically, the sensor networks in most traffic datasets do not accurately represent the actual road network exploited by vehicles, failing to provide insights into the traffic patterns in urban activities. To overcome these limitations, we propose an improved traffic prediction method based on graph convolution deep learning algorithms. We leverage human activity frequency data from National Household Travel Survey to enhance the inference capability of a causal relationship between activity and traffic patterns. Despite making minimal modifications to the conventional graph convolutional recurrent networks and graph convolutional transformer architectures, our approach achieves state-of-the-art performance without introducing excessive computational overhead. © 2023, CC BY-NC-SA.

关键词： Convolution

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Immersive Learning Constructs for Deaf and Hard-of-Hearing Students in TVET Practical Skill

Immersive Learning Constructs for Deaf and Hard-of-Hearing S...

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Visualization, informatics and technology Conference (IVIT), International

作者： Rini Hafzah Abdul Rahim Dinna Nina Mohd Nizam Nur Faraha Mohd Naim Aslina Baharum User Experience Group Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia Computing and Information System School of Engineering and Technology Sunway University Selangor Malaysia

ISBN: (数字)9798350354447

ISBN: (纸本)9798350354454

The advent of advanced educational technologies, and immersive learning utilizing virtual reality (VR), augmented reality (AR), and mixed reality (MR) have emerged as a powerful tool to enhance learning experiences. However, traditional approaches often lack the ability to address the unique needs of Deaf and Hard of Hearing (DHH) students, particularly in practical skill development. The usage of immersive learning for the purpose of DHH students is still limited, especially in Malaysia. This study explores critical elements of immersive learning environments designed to facilitate practical skill acquisition for DHH students. Using the systematic literature review (SLR) determines immersive practical skill learning elements from selected 34 papers to help DHH students learn more effectively. 30 constructs are highlighted in the SLR results as recommendations for creating immersive learning for DHH practical skills. It is thus intended that the highlighted features would contribute to both the process of teaching and learning as well as the enhancement of student performance.

关键词： Visualization Prototypes Mixed reality Auditory system Educational technology Object recognition informatics Augmented reality Immersive learning

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Fusion of Infrared and Visible Images Using Fuzzy Based Siamese Convolutional Network

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Computers, Materials & Continua 2022年第3期70卷 5503-5518页

作者： Kanika Bhalla Deepika Koundal Surbhi Bhatia Mohammad Khalid Imam Rahmani Muhammad Tahir Department of Electrical Engineering National Taipei University of TechnologyTaipei10608Taiwan Department Virtualization School of Computer ScienceUniversity of Petroleum&Energy StudiesDehradunIndia College of Computer Science and Information technology King Faisal University36362Saudi Arabia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia

Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared(IR)/visible(VS)*** in various kind of features in these images are vital to preserve in the single fused ***,simultaneous preservation of both the aspects at the same time is a challenging ***,most of the existing methods utilize the manual extraction of features;and manual complicated designing of fusion rules resulted in a blurry artifact in the fused ***,this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous ***,fuzzification of two IR/VS images has been done by feeding it to the fuzzy sets to remove the uncertainty present in the background and object of interest of the ***,images have been learned by two parallel branches of the siamese convolutional neural network(CNN)to extract prominent features from the images as well as high-frequency information to produce focus maps containing source image ***,the obtained focused maps which contained the detailed integrated information are directly mapped with the source image via pixelwise strategy to result in fused *** parameters have been used to evaluate the performance of the proposed image fusion by achieving 1.008 for mutual information(MI),0.841 for entropy(EG),0.655 for edge information(EI),0.652 for human perception(HP),and 0.980 for image structural similarity(ISS).Experimental results have shown that the proposed technique has attained the best qualitative and quantitative results using 78 publically available images in comparison to the existing discrete cosine transform(DCT),anisotropic diffusion&karhunen-loeve(ADKL),guided filter(GF),random walk(RW),principal component analysis(PCA),and convolutional neural network(CNN)methods.

关键词： Convolutional neural network fuzzy sets infrared and visible image fusion deep learning

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How Private Blockchain technology Secure IoT Data Record 2

How Private Blockchain Technology Secure IoT Data Record

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2nd IEEE International Conference on AI in Cybersecurity, ICAIC 2023

作者： Anaam, Elham Hasan, Mohammad Kamrul Ghazal, Taher M. Haw, Su-Cheng Alzoubi, Haitham M. Alshurideh, Muhammad Turki Faculty of Information Science and Technology Selangor43600 Malaysia School of Information Technology Skyline University College Sharjah United Arab Emirates Multimedia University Jalan Multimedia Faculty of Computing and Informatics Cyberjaya63100 Malaysia School of Business Skyline University College Sharjah United Arab Emirates School of Business The University of Jordan Department of Marketing Amman11942 Jordan

ISBN: (纸本)9798350396966

Scalability, security, and communication delays in the Internet of Things can be resolved using blockchain technology, which is the final piece of the puzzle. Blockchain technology may provide the IoT sector with the panacea it needs. Blockchain technology can record massive amounts of access points, allowing for the recording of data and collaboration between equipment, and providing manufacturers in the IoT sector with significant cost reductions. By removing individual points of failure, this decentralized strategy would build a more robust environment for the operation of equipment. Wondering in the era of information technology. Blockchain has attracted a lot of interest in recent decades for its ability to provide decentralized, definitive, and auditable usage in the Internet of Things (IoT). The majority of Internet of Things (IoT) devices are facing significant adaptability and privacy difficulties. This study proposes an understanding of How blockchain works with IoT for security data records. © 2023 IEEE.

关键词： Internet of things

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