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Sign language mobile apps: a systematic review of current app evaluation progress and solution framework

Evolving Systems 2024年第2期15卷 669-686页

作者： David, Dianes Alamoodi, A.H. Albahri, O.S. Garfan, Salem Albahri, A.S. Zaidan, B.B. Chen, Juliana Perak Malaysia Baghdad Iraq Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunrlin Douliou64002 Taiwan Discipline of Nutrition and Dietetics Susan Wakil School of Nursing and Midwifery Faculty of Medicine and Health The University of Sydney CamperdownNSW2006 Australia Department of Computer Science and Information Technology La Trobe University MelbourneVIC Australia Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Charles Perkins Centre The University of Sydney CamperdownNSW2006 Australia

Mobile apps for sign language are a fascinating area of research that merits a lot of attention. These apps are widely used due to their affordability and usability. Nevertheless, the quality of these apps needs to be evaluated if they are to have a significant influence. The outcomes of app quality assessment can also stimulate app development efforts and improvements to their functionality and accuracy. Therefore, to gain more in depth understanding, four academic databases (Science Direct, IEEE, Association for Computing Machinery, and Web of Science) were searched as part of a systematic literature review. The review highlighted that sign language apps require further development to support users in achieving the greatest possible usage and learning experience. We present a solution framework based on a quality assessment criterion for sign language mobile apps that could be adopted by academics and developers. Alternative identification, criteria, and development are the three primary aspects of the framework. The results demonstrate that the new assessment approach can establish a detailed set of criteria for sign language mobile app development. Future academics could gain a thorough understanding of mobile app development criteria from this study. The results are advantageous and open up a new field where researchers and developers could collaborate on sign language mobile app development. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Audition

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An Efficient and Secure Post-Quantum Multi-Authority Ciphertext-Policy Attribute-Based Encryption Method Using Lattice

An Efficient and Secure Post-Quantum Multi-Authority Ciphert...

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2023 IEEE INFOCOM Conference on computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Bagchi, Prithwi Bera, Basudeb Maheshwari, Raj Das, Ashok Kumar Yau, David K. Y. Sikdar, Biplab International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Singapore University of Technology and Design Information Systems Technology and Design Singapore487372 Singapore National University of Singapore Department of Electrical and Computer Engineering Singapore117583 Singapore

ISBN: (纸本)9781665494274

This article deals with designing an efficient post-quantum lattice based encryption scheme that relies on the multi-authority Ciphertext-Policy Attribute-Based Encryption (CP-ABE). The security of the proposed scheme is based on the hardness of the ring learning with errors (RLWE) problem. The construction of the proposed scheme is done using the Shamir's threshold secret sharing along with the Lagrange interpolation during the key generation and decryption processes in order to achieve the segmentation and restoration of private keys. A comparative study with the existing state of art schemes has been performed to show the feasibility and efficiency of the proposed scheme. Furthermore, experiments on the proposed scheme have been conducted to illustrate the computational time required during the key generation, encryption and decryption processes. © 2023 IEEE.

关键词： Quantum cryptography

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Prediction of Climatic and Water Quality in Urban Cooum River of Chennai Using Machine Learning Approaches 4th

Prediction of Climatic and Water Quality in Urban Cooum Rive...

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4th Doctoral Symposium on Computational Intelligence, DoSCI 2023

作者： Obaid, Ahmed J. Rajest, S. Suman Priscila, S. Silvia Shynu, T. Alkhafaji, Mohammed Ayad Mohsen, Karrar Shareef Faculty of Computer Science and Mathematics University of Kufa Kufa Iraq Bharath Institute of Higher Education and Research Tamil Nadu Chennai India Department of Biomedical Engineering Agni College of Technology Tamil Nadu Chennai India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Thi-Qar Iraq

ISBN: (纸本)9789819937158

Due to a large amount of plastic production, the river and river water are polluted. Most plastics wastages are not degradable. The river is polluted by macroplastics and microplastics. The manufacturing industries put their chemical waste into the river. The river water animals consume non-degradable plastics and industrial waste. It is very dangerous for river water animals to survive in such conditions. For the past 50 years, river water temperature and pH values have been calculated by using various machines like drifting buoys, ships, and the deepness of the river. This paper proposed a new machine learning approach that is used to calculate river surface temperature and pH level of the water and identify the types of litter in the river water. For our research, we have used a dataset obtained from the Cooum River, which has been running in the heart city of Chennai, located in India. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Rivers

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Image Segmentation of underwater side-scan Sonar under Long-Tail Distribution 8

Image Segmentation of underwater side-scan Sonar under Long-...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Liu, Rui Luo, Xiaonan Guilin University of Electronic Technology School of Computer Science and Information Security Guilin China Guilin University of Electronic Technology Guilin Huigu Institute of Artificial Intelligence Industrial Technology National Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin China

ISBN: (纸本)9798350302455

This paper discusses the critical role of autonomous underwater vehicles (AUVs) in marine resource exploration and protection, focusing on the importance of side-scan sonar images for acquiring important ocean information. We propose a novel input-output balancing framework to accurately segment the target regions in side-scan sonar images, which consists of an enhanced framework at the input level and a multi-headed combined output balancing module at the output level. The proposed method has been experimentally validated on a dataset and shows good generalization capability. These modules can be applied to different networks and datasets, making them a plug- and-play tool. The method has fewer computational parameters, making it easy to deploy in underwater mobile detection devices in the future. © 2023 IEEE.

关键词： Image enhancement

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AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis of the Femoral Head Detection 37

AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis o...

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Chen, Haoyang Liu, Shuai Lu, Feng Li, Wei Sheng, Bin Li, Mi Jin, Hai Zomaya, Albert Y. National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Department of Computer Science and Engineering Shanghai Jiao Tong University China Tongji Hospital Tongji Medical College Huazhong University of Science and Technology China

ISBN: (纸本)9781577358800

Early diagnosis of osteonecrosis of the femoral head (ONFH) can inhibit the progression and improve femoral head preservation. The radiograph difference between early ONFH and healthy ones is not apparent to the naked eye. It is also hard to produce a large dataset to train the classification model. In this paper, we propose Asymmetric-Sensitive Transformer (AsT) to capture the uneven development of the bilateral femoral head to enable robust ONFH detection. Our ONFH detection is realized using the self-attention mechanism to femoral head regions while conferring sensitivity to the uneven development by the attention-shared transformer. The real-world experiment studies show that AsT achieves the best performance of AUC 0.9313 in the early diagnosis of ONFH and can find out misdiagnosis cases firmly. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Large dataset

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Intelligent Data Transmission Through Stability-Oriented Multi-agent Clustering in VANETs 11th

Intelligent Data Transmission Through Stability-Oriented Mul...

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11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Alsalamy, Ali Al-Tahai, Mustafa Qader, Aryan Abdlwhab Kadeem, Sahar R. Abdul Alani, Sameer Mahmood, Sarmad Nozad Department of Computer Technical Engineering College of Information Technology Imam Ja‘afar Al-Sadiq University Al-Muthanna Samawah66002 Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Department of Computer Technical Engineering Bilad Alrafidain University College Diyala Baqubah32001 Iraq College of Engineering Technology Department of Medical Device Industry Engineering National University of Science and Technology Dhi Qar Nasiriyah Iraq University of Mashreq Research Center Baghdad Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Kirkuk Iraq

ISBN: (纸本)9789819967018

Vehicular Ad hoc Networks (VANETs) are one of the intelligent data transmission technologies which captured the attention of maximum of the applications of Intelligent Transport Systems. Due to the high mobility nature of VANETs, the consumption of energy is increased during the process of communication between the vehicles which leads to an increase in the end-to-end delay of the network. To overcome the network from this drawback Stability-Oriented Multi-agent Clustering (SOMAC)-based effective CH selection is performed in VANETs to improve the effectiveness of the communication. The parameters which are considered for the process of CH selection are distance, speed, connectivity, average acceleration and velocity, and residual energy. According to the parameters, the weight factor of the vehicle is measured and the vehicle with the highest weight factor is chosen as a CH. Two types of vehicles are present in the network which is a smart vehicles and ordinary vehicles. Smart vehicles can able to communicate directly with the RSU, but it is fewer in number. The ordinary vehicle is huge in numbers, and it transmits the data to the RSU using the CH. Effective CH selection provides a better communication platform for ordinary vehicles where it can reduce the energy consumption and delay of the network. The proposed SOMAC approach is simulated by using NS2 and evaluates the performance by focusing on the four performance metrics which are end-to-end delay (E2E), packet delivery ratio (PDR), throughput (TP), and energy efficiency (EE). Also, it compares with the earlier research on DGCM and ECRDP. From the simulation outcome, it is proven that the proposed SOMAC approach produced better PDR, TP, and EE as well as lower end-to-end delay when compared with the earlier works. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Vehicular ad hoc networks

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A Preliminary Study on the Development of Drones Network Remote Identification Mechanism in Taiwan 6

A Preliminary Study on the Development of Drones Network Rem...

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6th International Symposium on computer, Consumer and Control, IS3C 2023

作者： Kao, Ya-Ling Peng, Gin-Der Hong, Jai-Tsung Lin, I-Ching Lin, Yu-Da National Penghu University of Science Technology Department of Marketing and Logistics Management Penghu Taiwan Chien Hsin University of Science and Technology Department of International Business Taoyuan Taiwan Yulin-Chiayi-Tainan Regional Transportation Development Research Center Tainan Taiwan Central Regional Transportation Development Research Center Taichung Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798350301953

While the number of remote-controlled drones in Taiwan continues to grow, it is necessary to set up a proper regulatory mechanism for public safety and interests. Although Taiwan has the first law in Asia to regulate remote-controlled drones, if a proper regulatory mechanism is not designed, not only will the relevant laws and regulations become a formality and fail to achieve the goal of protecting public interests, but it will even slow down the potential development of more remote-controlled drones. In this study, we have conducted a preliminary introduction and comparison of the documents related to network-based remote identification (remote ID) mechanisms proposed by the FAA and EASA and other advanced national aviation authorities and found that Europe, the United States, and other countries have set the goal of developing network-based remote ID. However, considering the current status of infrastructure and telecommunication services, most countries have set broadcast remote ID as the first target and have gradually developed a clear mechanism to follow. Although Taiwan currently has preliminary regulations in the relevant areas, the details have not been fully released. Therefore, this study will start from the legal and regulatory level and use literature analysis and comparative research to make a preliminary judgment on the relevant regulations as a reference for the future planning and development of the Radio Frequency Identification mechanism in Taiwan. © 2023 IEEE.

关键词： Drones

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Time-series satellite remote sensing reveals gradually increasing war damage in the Gaza Strip

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national Science Review 2024年第9期11卷 181-191页

作者： Shimaa Holail Tamer Saleh Xiongwu Xiao Jing Xiao Gui-Song Xia Zhenfeng Shao Mi Wang Jianya Gong Deren Li State Key Laboratoryof Information Engineering in Surveying Mapping and Remote SensingWuhan University Geomatics Engineering Department Faculty of Engineering at Shoubra Benha University School of Computer Science Wuhan University Collaborative Innovation Center of Geospatial Technology National Engineering Research Center for Multi-media Software Institute of Artificial IntelligenceWuhan University

War-related urban destruction is a significant global concern, impacting national security, social stability,people's survival and economic development. The effects of urban geomorphology and complex geological contexts during conflicts, characterized by different levels of structural damage, are not yet fully understood globally. Here we report how integrating deep learning with data from the independently developed Luo Jia3-01 satellite enables near real-time detection of explosions and assessment of different building damage levels in the Israel–Palestine conflict. We found that the damage continually increased from 17 October 2023 to 2 March 2024. We found 3747 missile craters with precision positions and sizes, and timing on vital infrastructure across five governorates in the Gaza Strip on 2 March 2024, providing accurate estimates of potential unexploded ordnance locations and assisting in demining and chemical decontamination. Our findings reveal a significant increase in damage to residential and educational structures, accounting for 58.4% of the total—15.4% destroyed, 18.7% severely damaged, 11.8% moderately damaged and 12.5% slightly damaged—which exacerbates the housing crisis and potential population displacement. Additionally, there is a 34.1% decline in the cultivated area of agricultural land, posing a risk to food security. The Luo Jia3-01 satellite data are crucial for impartial conflict monitoring, and our innovative methodology offers a cost-effective, scalable approach to assess future conflicts in various global *** first-time findings highlight the urgent need for an immediate ceasefire to prevent further damage and support the release of hostages and subsequent reconstruction efforts.

关键词： war damage monitoring satellite remote sensing missile crater detection type of damaged building building damage level detection Gaza Strip

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Trust Management Scheme-Based Intelligent Communication for UAV-Assisted VANETs 11th

Trust Management Scheme-Based Intelligent Communication for ...

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11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Alani, Sameer Qader, Aryan Abdlwhab Al-Tahai, Mustafa Mansour, Hassnen Shakir AL-Hameed, Mazin R. Mahmood, Sarmad Nozad University of Mashreq Research Center Baghdad Iraq Department of Computer Technical Engineering Bilad Alrafidain University College Diyala Baqubah32001 Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Department of Computer Technical Engineering College of Information Technology Imam Ja‘afar Al-Sadiq University Al-Muthanna Samawah66002 Iraq College of Engineering Technology Department of Medical Device Industry Engineering Dhi Qar National University of Science and Technology Nasiriya Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Kirkuk Iraq

ISBN: (纸本)9789819967018

Vehicular Ad hoc Network (VANET) is serving for various applications of Intelligent Transmission System (ITS) where vehicle can easily able to communicate to other vehicles and to the infrastructure in an independent manner. Several problems are identified in VANETs due to highly dynamic mobility patterns. They are attackers which can easily able to capture in network, and huge obstacles are present in the ground level, connectivity loss, and so on. In order to save the vehicles from the ground-level obstacle, Unmanned Aerial Vehicles (UAVs) are introduced in vehicular communication that collects the data from the vehicle in air medium so that it can get escape from the obstacles in the ground level. In this paper, to secure the network from attackers, Trust Management Scheme (TMS) is proposed in UAV-Assisted VANETs (UAVs). Through this method, trust evaluation is performed in both the communication modules of VANETs such as vehicle-to-vehicle data transmission and vehicle-to-UAVs’ data transmission which greatly helps to secure the network from the external threads. The proposed TMS-UAVs’ protocol has been validated using NS2 and SUMO. The simulation is performed and the results are compared with the earlier works such as ES-UAVs and PRO-UAVs. The simulation results of the proposed TMS-UAVs’ protocol confirm encouraging performance in terms of higher packet delivery ratio, lower end-to-end delay, lower average number of hops, and lower overhead. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Vehicular ad hoc networks

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Recurrent Intra Prediction Mode for Future Video Coding

Recurrent Intra Prediction Mode for Future Video Coding

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Data Compression Conference (DCC)

作者： Jiaye Fu Xuewei Meng Siwei Ma Jiaqi Zhang Yao-Jen Chang Vadim Seregin Marta Karczewicz School of Electronic and Computer Engineering Peking University China National Engineering Research Center of Visual Technology School of Computer Science Peking University China Qualcomm Inc United States

ISBN: (数字)9798331534714

ISBN: (纸本)9798331534721

Intra prediction is a crucial component of hybrid video coding framework due to its remarkable ability to reduce spatial redundancy in video signals. Unlike the single-mode based intra prediction in HEVC and VVC, intra fusion prediction methods, that combine the results of multiple angular prediction modes, were newly adopted by Enhanced Compression Model (ECM). However, intra fusion prediction over-relies on local spatial correlations and neglects potential texture similarities in non-adjacent regions. To overcome these limitations and elevate the accuracy of luma intra prediction, a Recurrent Intra Prediction Mode (RIPM) is proposed in this paper, which is composed of two sub-modules, i.e., Recurrent Intra Merge Mode (RIMM) and Recurrent Block Vector Substitution Module (RBVSM). RIMM utilizes the recurrent spatial texture information of the adjacent and non-adjacent spaces for adaptive mode derivation and prediction within the intra fusion prediction framework. RBVSM is a sophisticated mechanism for adaptive prediction mode selection and weight assignment during intra fusion prediction, resulting in enhanced coding performance with minimal impact on computational complexity. The proposed method, implemented on top of ECM-12.0, demonstrates a 0.095% BD-rate gain for the luma component under All Intra configuration, with negligible complexity increase. Currently, RIPM is under study in Exploration Experiments (EE) for ECM in JVET.

关键词： Video coding Accuracy Correlation Redundancy Neural networks Data compression Predictive models Encoding Vectors Decoding

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