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A Systematic Literature Review: Virtual Reality for Hearing Impaired 9th

A Systematic Literature Review: Virtual Reality for Hearing ...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Mokhtar, Ermiera Shafika Aziz, Nurulnadwan Ahmad, Siti Zulaiha Hamzah, Siti Salbiah Omar, Azizah Che Supli, Ahmad Affandi Univ Teknol MARA Dungun Terengganu Malaysia Univ Teknol MARA Arau Perlis Malaysia Univ Teknol MARA Kuala Terengganu Terengganu Malaysia Univ Utara Malaysia Changlun Kedah Malaysia Xiamen Univ Sepang Selangor Malaysia

ISBN: (纸本)9789819750344;9789819750351

The Internet of things (IoT) and 5G technologies have recently advanced, making it possible to connect different sensors and processors in industrial and commercial applications using modern wireless network approaches. Virtual reality (VR) is one of the most cutting-edge wearable and wireless technologies that is expanding quickly. Various VR technologies are now available, and they are made to meet the demands of users, including people with disabilities (PWDs). Nevertheless, it was discovered that the VR technology created for users who are hearing impaired (HI) has been woefully inadequate, and specific design principles were discovered when developing VR technology for them. The results of a systematic review and critical evaluation of publications from the Scopus and Web of Science databases using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) technique are presented in this paper. The process is divided into four phases: developing the research questions, determining the resources, specifying the inclusion and exclusion standards, and assessing the findings. Five articles were chosen based on the criteria at the end of the process. Then, along with the VR applications that have been made accessible during the last 3 years (2021-2023), three themes relating to the principles of building VR technology were covered: assistive technology (AT), visual interaction (VI), and empathy. The findings of this study can be used as a guideline for future developers to ensure the future designs of VR models for the HI individuals could be improved.

关键词： Virtual reality Hearing impaired Assistive technology Empathy Visual interaction

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Applications of Big Data Analytics and Artificial Intelligence in Medical Domain: A Survey 9th

Applications of Big Data Analytics and Artificial Intelligen...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Azeroual, Amal Nsiri, Benayad Thami, Rachid Oulad Haj Benaji, Brahim Mohammed V Univ Rabat Natl Grad Sch Arts & Crafts Rabat ENSAM Dept Res Ctr STIS M2CSBiomed Engn Rabat Morocco Mohammed V Univ Rabat Natl Sch Comp Sci & Syst Anal ENSIAS Rabat Morocco

ISBN: (纸本)9789819750344;9789819750351

Big Data and Artificial Intelligence (AI) in the medical field are versatile tools applicable in various sectors such as commercial, academic, government, and public. They encompass diverse data types, including biological, biometric, and electronic health records. Biological data may involve information stored in biobanks, while biometric data can include personal wellness data gathered from devices. Electronic health data primarily consists of patient medical records, along with demographic information and medical imaging. This article aims to extensively explore the advantages, challenges, and implications of employing Big Data and AI in the medical domain, with a specific focus on improving diagnostics, clinical decision-making, and health care. Additionally, it considers essential ethical and regulatory issues related to the integration of these technologies. The paper particularly emphasizes the positive impact of combining Big Data with AI, resulting in enhanced precision of predictive models for disease outbreaks and patient health risks, ultimately improving strategies for preventive care.

关键词： Big Data Artificial Intelligence Medical Big Data

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Evaluating the Performance of YOLOP for Lane Detection with Challenging Road Conditions 9th

Evaluating the Performance of YOLOP for Lane Detection with ...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Shehada, Dina Bouridane, Ahmed Univ Sharjah Dept Elect Engn Sharjah U Arab Emirates Univ Dubai Coll Engn & Informat Technol Dubai U Arab Emirates Univ Sharjah Ctr Data Analyt & Cybersecur Sharjah U Arab Emirates

ISBN: (纸本)9789819750344;9789819750351

Lane detection is a critical component of many autonomous and advanced driver assistance systems. In this paper, the performance of "You Only Look Once for Panoptic" driving perception (YOLOP) deep learning model is evaluated on challenging conditions targeting road lane detection. YOLOP is evaluated on two publicly available datasets, including the BDD100K dataset and the KITTI dataset. Moreover, a third test dataset, which was created by the authors containing road images in Dubai city, was also utilized in the evaluation. The performance of YOLOP model was demonstrated on detecting lanes in challenging conditions such as curved roads, occluded markings, presence of shadow, and on rainy and foggy weather conditions. Results suggest that YOLOP achieves high Pixel Accuracy (PA) and low Mean Square Error (MSE) on all test sets. However, the Intersection over Union (IoU) metric was only 12.45%, 16.70%, and 26.79%, for BDD100K, KITTI, and the created test set, respectively. Overall, the results show that YOLOP provides a robust and efficient solution for lane detection that can be easily integrated into existing autonomous driving systems though its performance degrades in challenging conditions, particularly in the presence of shadows.

关键词： Lane detection YOLOP Evaluation Machine learning

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Multisensing IIoT Platform Enabled by Custom BAP RFID TAG 9th

Multisensing IIoT Platform Enabled by Custom BAP RFID TAG

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9th International Congress on Information and Communication Technology (ICICT)

作者： Ria, Andrea Cecchi, Glauco Motroni, Andrea Univ Pisa Dept Informat Engn I-56122 Pisa Italy

ISBN: (纸本)9789819750344;9789819750351

In this work, we introduce the design of a Battery-Assisted Passive (BAP) Radio Frequency IDentification (RFID) tag incorporating sensing capabilities. The tag operates at the Ultra High Frequency (UHF) band to allow remote detection and data exchange. Designed for environmental monitoring in both industrial indoor facilities and outdoor environments, the tag is characterized by a general purpose microcontroller facilitating the data transmission between the RFID interface and the sensors. Particularly, the RFID chip integrated in the proposed system is configured as bridge for SPI communications, whereas the RFID reader acts as master node. Up on reader requests, the microcontroller triggers the required sensor to perform a measurement which result is stored in the RFID chip memory, easily accessible by the reader throughout standard RFID protocol operations. The tag encapsulates temperature, relative humidity, pressure, and 3D acceleration sensors. After the tag antenna design, fabrication, and system integration, the whole proposed system is verified experimentally in operating conditions to show its reliability.

关键词： RFID Sensing Sensor interface Remote monitoring Industrial environment

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An Analysis of Different Text Representation Schemes for an Immune Clustering Algorithm 21st

An Analysis of Different Text Representation Schemes for an ...

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21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Ferraria, Matheus A. Balbi, Pedro P. de Castro, Leandro N. Univ Presbiteriana Mackenzie FCI PPGEEC Programa Pos Grad Engn Eletrica & Comp Sao Paulo SP Brazil State Univ Campinas Unicamp Sch Technol Grad Program Technol Sao Paulo SP Brazil Florida Gulf Coast Univ Human Ctr Artificial Intelligence & Nat Comp Res Ft Myers FL 33965 USA

ISBN: (纸本)9783031820724;9783031820731

This research investigates the challenges and effectiveness of various text representation methods (standard vector, grammar-based, and distributed), when applied to clustering short texts. The study explores Bag-of-Words for standard vector, Linguistic Inquiry and Word Count (LIWC), Part-of-Speech Tagging (POS-Tagging), and the Medical Research Council Psycholinguistic Database (MRC) for grammar-based, and Word2Vec, fastText, Doc2Vec, and SentenceBERT for distributed representations. Utilizing the aiNet bio-inspired clustering algorithm, the results reveal surprising findings, with grammar-based representations demonstrating competitive performance despite their simplicity, while standard vectors exhibit known challenges like high dimensionality. The study contributes insights into the properties of different text representations, providing a foundation for optimizing their application in clustering tasks with short and informal texts.

关键词： Clustering Information retrieval Natural Computing NLP Text Mining

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AWeighted Matrix-Based Reversible Data Hiding Scheme with Dual-Image by Exploiting BWT Encoding Technique 3rd

AWeighted Matrix-Based Reversible Data Hiding Scheme with Du...

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3rd International Conference on Network Security and Blockchain Technology

作者： Datta, Kankana Jana, Biswapati Dalui, Mamata Haldia Inst Technol Haldia W Bengal India Vidyasagar Univ Midnapore W Bengal India Natl Inst Technol Durgapur W Bengal India

ISBN: (纸本)9789819780501;9789819780518

Data protection and security of confidential data transmission through social media is one of the biggest challenges in this present era. To meet this challenge, many researchers introduce different data hiding schemes based on different parameters such as security, visual quality, reversibility, embedding capacity and robustness. But, the existing schemes are not able to meet satisfactory results considering all the parameters. In view of this, a reversible, secured, dual-image-based data hiding scheme exploiting weighted matrix utilizing Burrows-Wheeler Transform (BWT) lossless encoding technique has been proposed which provides better results considering all necessary parameters. The confidential data has been concealed by BWT encoding method while preserving a trade-off between embedding capacity and PSNR (dB) values in the proposed strategy. The use of dual-image enhances the embedding capacity as well as security of the scheme. The proposed scheme is also robust against different malicious attacks. The proposed scheme outperforms the state-of-the-art schemes in terms of the crucial parameter, thereby offering greater benefits to protect important information from unauthorized multimedia users and cyber attacks.

关键词： Weighted matrix Data hiding Secret message Bwt encoding Reversibility

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Towards Reliable DTMF Recognition: A TinyML Approach 1

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Yusuf, Hadiza Perkins, Mike Nkama, Chukwuemeka Carnegie Mellon Univ Africa Kigali Rwanda

ISBN: (数字)9789819754410

ISBN: (纸本)9789819754403;9789819754410

Dual-tone multi-frequency (DTMF) detection faces challenges in real-world environments due to noise, distortions, and diverse telecommunications equipment. This paper explores the application of a simple Artificial Neural Network (ANN) for robust DTMF tone classification, with subsequent deployment on an Arduino device. The proposed TinyML model achieves near-identical accuracy to the unquantized model across pure signals, signals with noise, and speech distortions. Notably, the quantized model significantly reduces file size (70%) while maintaining excellent performance. This work highlights the potential of ANNs for robust DTMF classification in real-world scenarios, particularly on low-power devices.

关键词： DTMF TinyML Artificial neural network Machine learning Quantization

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Toward Birds Conservation in Dry Forest Ecosystems Through Audio Recognition via Deep Learning 9th

Toward Birds Conservation in Dry Forest Ecosystems Through A...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Rodriguez, Tyrone Guilindro, Adriana Piedrahita, Paolo Realpe, Miguel ESPOL Polytech Univ Escuela Super Politecn Litoral FIEC Guayaquil Ecuador ESPOL Polytech Univ Escuela Super Politecn Litoral FCV Guayaquil Ecuador ESPOL Polytech Univ Escuela Super Politecn Litoral CIDIS Guayaquil Ecuador

ISBN: (纸本)9789819750344;9789819750351

This paper proposes an innovative solution for the conservation and understanding of avian biodiversity in forest ecosystems in Ecuador using deep learning techniques. Preprocessing techniques, including noise signal separation, were applied, and convolutional neural network models were used to extract significant features from Mel spectrograms using data from the forest "La Prosperina". To train the model, an average of 400 samples of bird songs were utilized for each of the six species to be classified, achieving accuracy rates of 99.93% for training dataset and 96.27% for testing dataset, demonstrating exceptional abilities to identify threatened bird species, with positive results represented in a confusion matrix. This approach not only benefits conservationists by providing them with effective and economically viable tools for monitoring bird species and behaviors but also has broader applications.

关键词： Deep learning Audio recognition La prosperina Biodiversity Birds conservation

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Junior High School Teachers' Challenges in Evaluating Students' Performance in Online Physical Education Classes 1

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9th International Congress on Information and Communication Technology (ICICT)

作者： Morenos, Lean James Cruz, Reine Joshua Baybay, Mark Christer Lucas, Karl Francis Rodriguez, Ramon L. Natl Univ Philippines NU Dasmarinas Manila Philippines

ISBN: (数字)9789819754410

ISBN: (纸本)9789819754403;9789819754410

The paper aims to understand the challenges junior high school teachers face in evaluating students' performance in physical education in online classes. The researcher collected the data via open-ended questionnaires through Google Forms. Six junior high school physical education teachers participated in the study. The data were analyzed for patterns that might offer insight into junior high school teachers' challenges in assessing students' physical education performance in online classes. The findings of this study focus primarily on the difficulties encountered by teachers in schools, such as financial reasons that result in the unavailability of equipment like smartphones, laptops, or even tablets to conduct a class. Additionally, limited strategies and approaches are utilized in an online class setup that restricts the capabilities of the teachers in applying a better learning process in which the students could maximize learning.

关键词： Evaluation student performance Challenges in assessment Online physical education

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Development and Assessment of a System to Help Students Improve Self-compassion 21st

Development and Assessment of a System to Help Students Impr...

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21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Koizumi, Masashi Ohsuga, Mieko Manuel Corchado, Juan Osaka Inst Technol Grad Sch Robot & Design Osaka Japan Osaka Inst Technol Fac Robot & Design Osaka Japan Univ Salamanca Bisite Res Grp Salamanca Spain

ISBN: (纸本)9783031820724;9783031820731

Mental health issues are becoming more prevalent among university students. The mindful self-compassion (MSC) training program, which was introduced to address this issue, has shown some efficacy. However, many people, particularly Japanese people, have difficulty recalling visual imagery or feel uncomfortable or resistant to treating themselves with compassion. This study proposes and develops a system that uses virtual space and avatars to help individuals improve their self-compassion. In the proposed system, the user first selects an avatar of a person with whom to talk (hereafter referred to as "partner"), and then talks about the problem to the avatar of his/her choice. Next, the user changes viewpoints and listens to the problem as the partner's avatar and responds with compassion. Finally, the user returns to his/her own avatar and listens to the compassionate response spoken as the partner avatar. We first conducted surveys to understand the important system components, and then developed prototypes. In light of the results of the experiments, we improved the prototype by introducing a generative AI. The first prototype used the user's spoken voice as it was, but the improved system uses the generative AI to organize and convert the voice and present it. In addition, we added a function to generate and add advice with compression. The proposed system is expected to contribute to the improvement of students' self-compassion.

关键词： Self-compassion Virtual Space Avatar Generative AI

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