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Ancient Character Recognition: A Novel Image Dataset of Shui Manuscript Characters and Classification Model

Chinese Journal of Electronics 2023年第1期32卷 64-75页

作者： TANG Minli XIE Shaomin LIU Xiangrong Department of Computer Science and Technology School of Informatics Xiamen University School of Big Data Engineering KaiLi University Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University

Shui manuscripts are part of the national intangible cultural heritage of China. Owing to the particularity of text reading, the level of informatization and intelligence in the protection of Shui manuscript culture is not adequate. To address this issue, this study created Shuishu＿C, the largest image dataset of Shui manuscript characters that has been reported. Furthermore, after extensive experimental validation, we proposed ShuiNet-A,a lightweight artificial neural network model based on the attention mechanism, which combines channel and spatial dimensions to extract key features and finally recognize Shui manuscript characters. The effectiveness and stability of ShuiNet-A were verified through multiple sets of experiments. Our results showed that, on the Shui manuscript dataset with 113 categories, the accuracy of ShuiN et-A was 99.8%, which is 1.5% higher than those of similar studies. The proposed model could contribute to the classification accuracy and protection of ancient Shui manuscript characters.

关键词： Training Speech recognition Artificial neural networks Feature extraction Stability analysis Character recognition Machine translation

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Comparing Sweep Rate Effects for Different Perovskite Technologies 3

Comparing Sweep Rate Effects for Different Perovskite Techno...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Peraticos, Elias Paraskeva, Vasiliki Norton, Matthew Hadipour, Afshin Krishna, Anurag Aguirre, Aranzazu Aernouts, Tom Hadjipanayi, Maria Georghiou, George E. University of Cyprus PV Technology Lab Department of Electrical and Computer Engineering Nicosia1678 Cyprus for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Kuwait University Department of Physics Condensed Matter Physics Group Kuwait Hasselt University Imo-Imomec Hasselt3500 Belgium Imec Imo-Imomec Thin Film PV Technology Genk3600 Belgium Energyville Imo-Imomec Genk3600 Belgium

ISBN: (纸本)9798350375923

Perovskite solar cell devices - although thought to be possible candidates for substituting conventional silicon photovoltaics - display inherent instabilities that complicate the application of traditional characterisation approaches. Hence, conducting measurements for different technologies under varying conditions can help in characterising them as well as contributing to the advancement of their stability needed for commercial success. This work aims to contribute to the growing body of indoor tests aimed at enhancing the understanding and characterisation of this novel technology. Four different types of perovskite technology mini-modules have been tested with different sweep rates to study its impact on the hysteresis effect noticed during full scan current-voltage (I-V) traces. Measurements revealed that the MAPbI3 perovskite-based devices are more sensitive to sweep rate than the CsFAPbIBr perovskites. The changes noticed in the I-V traces at different sweep rates is thought to be due to different ion migration effects in the perovskite, so finding the appropriate sweep rate for each technology will lead to a better characterisation of these samples. © 2024 IEEE.

关键词： Perovskite

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Designing an Advanced Situational Awareness Platform Using Intelligent Multi-Drones for Smart Farming Towards Agriculture 5.0 11

Designing an Advanced Situational Awareness Platform Using I...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Hermanus, Davy Ronald Supangkat, Suhono Harso Hidayat, Fadhil Bina Nusantara University Research Interest Group in Educational Technology Computer Science Department Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9798350389654

With regard to Agriculture 5.0, the goal of this research is to create an intelligent platform for multi-drone collaboration that will improve situational awareness. This study examines the crucial phases in the Sensing, Understanding, and Action processes by fusing cutting-edge drone technology with creative coordination methods. Creating the architecture and foundation for drone collaboration, utilizing artificial intelligence for real-time data processing, and creating user interfaces that work are all part of the study technique. Area coverage, data quality, processing speed, and decision-making effectiveness are some of the performance evaluation measures. The goal of the research is to identify strategies for enhancing large-scale farming methods' resource management and operational effectiveness. The results will greatly enhance Agriculture 5.0 technologies and create avenues for the deployment of multi-drone collaboration platforms in a variety of high-situational awareness businesses. © 2024 IEEE.

关键词： Data quality

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Integration of Large Language Models into Higher Education: A Perspective from Learners 25

Integration of Large Language Models into Higher Education: ...

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25th International Symposium on computers in Education, SIIE 2023

作者： Zdravkova, Katerina Dalipi, Fisnik Ahlgren, Fredrik Ss. Cyril and Methodius University Faculty of Computer Science and Engineering Skopje Macedonia Linnaeus University Faculty of Technology Department of Informatics Kalmar Sweden Linnaeus University Faculty of Technology Department of Computer Science and Media Technology Kalmar Sweden

ISBN: (纸本)9798350329315

Large language models (LLMs) are being criticized for copyright infringement, inadvertent bias in training data, a danger to human innovation, the possibility of distributing incorrect or misleading information, and prejudice. Due to their popularity among students, the introduction of many comparable apps, and the inability to resist unfair and fraudulent student usage, their educational use needs to be adapted and harmonized. The incorporation of LLMs should be defined not only by pedagogues and educational institutions, but also by students who will actively utilize them to learn and prepare assignments. In order to find out what students from two universities think and suggest about LLMs use in education, they were asked to give their contribution by answering the survey that was conducted at the beginning of the spring semester of academic 2022/23. Their feedback was quantitatively and qualitatively analyzed, showing in a better light what students think about LLMs and how and why they would use them. Based on the analysis, the authors propose an original strategy for integrating LLMs into education. The proposed approach is also adapted for those students who are not interested in using LLMs and for those who prefer the hybrid mode by combining their own research with LLMs generated recommendations. The authors expect that by implementing the proposed strategy, schools will benefit from a better education in which research, creativity, academic honesty, recognition of false information, and the ability to improve knowledge will prevail. © 2023 IEEE.

关键词： Students

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KDTL: knowledge-distilled transfer learning framework for diagnosing mental disorders using EEG spectrograms

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Neural Computing and Applications 2024年第30期36卷 18919-18934页

作者： Singh, Shreyash Jadli, Harshit Padma Priya, R. Surya Prasath, V.B. Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore India Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Computer Science University of Cincinnati CincinnatiOH45221 United States

Electroencephalography (EEG) is a well-known modality in neuroscience and is widely used in identifying and classifying neurological disorders. This paper investigates how EEG data can be used along with knowledge distillation-based deep learning models to detect mental disorders like epilepsy and sleep disorders. The EEG signals are converted into time–frequency plots using short-time Fourier transforms. Further, we propose a novel methodology for using knowledge distillation-based transfer learning (KDTL). Knowledge distillation is becoming quite prevalent in the machine learning field and is associated with various applications in our work;we propose its use in the detection of mental disorders from EEG spectrograms. We convert the EEGs using short-term Fourier transform to obtain time–frequency representation and apply teacher-student by first training a large teacher model and use knowledge distillation to train a student model. In our experiments, we found that ConvNext teacher and MobileNet student combination obtained better results. Our proposed KDTL approach is tested on two datasets with multiple cases, namely the Bonn and ISRUC datasets and obtain 98% and 95% accuracies, respectively. Further experimental results show that the overall KDTL methodology can obtain high classification accuracy across both datasets in binary and multiclass classifications and proves to be better than multiple prior works. Further, our KDTL approach provides a way to train lightweight models which have a smaller number of trainable parameters and thereby constitute lower training time overall. Our proposed KDTL-based approach obtained accurate results in diagnosing mental disorders from EEG spectrograms. Compared to other related methods, KDTL outperformed across tasks with obtained good results in both binary and multiclass classifications. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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A vision-based fall detection framework for the elderly in a room environment using motion features and DAG-SVM

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International Journal of computers and Applications 2022年第7期44卷 678-686页

作者： Zhu, Huazheng Du, Jinglong Wang, LuLu Han, Baoru Jia, Yuanyuan College of Intelligent Technology and Engineering Chongqing University of Science and Technology Chongqing China College of Medical Informatics Chongqing Medical University Chongqing China College of Computer Science Chongqing University Chongqing China

Falls are one of the major health risks for the elderly in public health care issues, thus fall detection is particularly necessary for the seniors. In this paper, we propose a novel computer vision-based fall activity detection framework which is based on a new feature extraction method of human motion. We detect falls by analyzing the motion process of human body rather than conventional human shape analysis. Approximate ellipse is first adopted to fit human silhouette, and the areas outside the ellipse are removed to confirm human body silhouette (HBS). Then HBS is divided into three regions, and the motion features are extracted from the centroid coordinate changes of each region. A directed acyclic graph support vector machine (DAG-SVM) classifier is finally applied to detect falls from normal daily activities. The advantage of the proposed method is that it can not only effectively distinguish falls from fall-like activities but also detect the falls parallel to camera optical axis. Experimental results show that our method achieves a state-of-the-art accuracy in fall detection. This method is lightweight and thus can be integrated into embedded devices for real-time health surveillance. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： computer vision

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Research on the Design Method of Prefabricated Concrete Structure Based on BIM

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computer-Aided Design and Applications 2023年 20卷 148-164页

作者： Yang, Fan Hussain, Saddam Fadhel, Mustafa Abbas Ghafoor, Kayhan Zrar Gannan University of Science and Technology Jiangxi Ganzhou China Department of Civil and Architecture Engineering Kyushu Institute of Technology Fukuoka Kitakyushu8040015 Japan University of Al Muthanna Samawa66001 Iraq Department of Computer Science Knowledge University Erbil44001 Iraq Department of Software & Informatics Engineering Salahaddin University-Erbil Erbil44001 Iraq

With the gradual development in industrialization, the advent of computer and information technology has evolved in the field of engineering and construction industry. BIM technology has become a valuable part of prefabricated concrete engineering with the advancement of modern technology based on 3D modeling simulation. In order to realize the industrialization and automation of prefabricated concrete structures, this paper analyzes the characteristics of fabricated concrete structure and BIM, combining the two techniques. This work applies BIM to fabricated concrete design and chooses finite element analysis and calculation software ETABS to analyze the structure model. The results show that the mass participation ratio of the model studied in this paper reaches more than 90%, the interlayer displacement angle is less than 1/550, and the modal and shell internal force analysis results meet the requirements. In this paper, modal analysis, shell internal force analysis under live load and structural dynamic analysis under response spectrum load conditions were carried out on the ETABS model converted from the Revit model and the model directly established by ETABS. The ETABS model converted from the Revit model by the data interface plug-in can be used for structural analysis. © 2023, CAD Solutions, LLC. All rights reserved.

关键词： Finite element method

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Multi-Partner Project: Safe, Secure and Dependable Multi-UAV Systems for Search and Rescue Operations

Multi-Partner Project: Safe, Secure and Dependable Multi-UAV...

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2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Nikolaou, Panagiota Savva, Antonis Sorokos, Ioannis Aslansefat, Koorosh Missaoui, Sondess Naveed, Akram Mohammed Hillen, Daniel Lorenz, Marc Walker, Martin D. Papoutsakis, Manos Gerasimou, Simos Kolios, Panayiotis Papadopoulos, Yiannis Reich, Jan Ioannidis, Sotiris Michael, Maria K. University of Central Lancashire Cyprus Electrical and Computer Engineering Department University of Cyprus Cyprus Kios Research and Innovation Center of Excellence University of Cyprus Cyprus Computer Science Department University of Cyprus Cyprus Fraunhofer Iese Germany University of Hull United Kingdom University of York United Kingdom Institute of Computer Science Foundation for Research and Technology Greece

ISBN: (纸本)9783982674100

Unmanned Aerial Vehicles (UAVs) have become essential in search and rescue operations, especially in disaster management scenarios. Their effective navigation and the integration of a plethora of sensors assist in efficient person detection, making them an essential technological tool to first responders. Multi-UAV systems extend these benefits by using coordinated strategies to cover large areas efficiently, reducing overall mission response time and enhancing its success. Despite these advantages, challenges remain in ensuring the safety, security, and dependability of (mutli-)UAV missions. Issues such as navigation risks, potential cyber threats, and hardware-/software-related reliability issues can impact the mission results. Additionally, UAVs are highly constrained devices with limited battery capacity, requiring the use of lightweight technologies. In this paper, we present part of the results of the SESAME project, an EU multi-partner project that aims to develop safe and secure multi-robot Systems. In particular, we present some of the developed SESAME Executable Digital Dependability Identities (EDDI) technologies based on Markov models, statistical distance measures, and other advanced approaches for enhancing safety, security and dependability of the UAV platform and underlying models. These EDDI technologies are seamlessly integrated using the ConSerts framework in a multi-UAV platform and tested using search and rescue scenarios. The results demonstrate significant improvements in multi-UAV safety, with an availability rate of 91% and a search and rescue algorithmic accuracy of 99.8%. Additionally, the system achieves precise detection of spoofing attacks, using collaborative localization as a mitigation technique to guide the UAV to a safe landing, even in the absence of GPS signals © 2025 EDAA.

关键词： Drones

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Assessment of the targeted energy saving potential through an energy efficiency action plan adapted to the specific needs of a SME in Romania 13

Assessment of the targeted energy saving potential through a...

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13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2022

作者： Mureșan, Claudia Farkas, Timea Șteț, Denisa Czumbil, Levente Cîrstea, Ștefan Turcu, Antoniu Polycarpou, Alexis Micu, Dan D. Energy Transition Research Center Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia Cyprus

ISBN: (纸本)9781839538445

This paper aims to contribute to overcoming the barriers that are hindering the adoption of energy efficiency measures in SMEs sector, particularly addressing informational and organizational issues, by presenting a methodology for assessment of the targeted energy saving potential in a SME that has been developed and validated in the framework of H2020 SMEmPower Efficiency project, based on a Monitoring & Targeting (M&T) tool. As a case study, the method was applied in a SME activating in the manufacturing of knitted and crocheted fabrics sector in Romania. After the company's energy profile was created, the M&T simulation generated a series of energy saving and CO2 emission reduction targets, based on which a set of specific energy efficiency (technical and organisational) measures tailored to the company's needs were proposed and assessed from both technical and financial perspectives. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Energy efficiency

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Age-of-Information and Energy Optimization in Digital Twin Edge Networks

Age-of-Information and Energy Optimization in Digital Twin E...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Guo, Yongna Fu, Yaru Zhang, Yan Quek, Tony Q. S. Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Hong Kong Metropolitan University School of Science and Technology Hong Kong University of Oslo Department of Informatics Oslo Norway Singapore University of Technology and Design Singapore

ISBN: (纸本)9798350351255

In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing the two performance metrics Age of Information (AoI) and energy efficiency. We jointly consider the problems of edge association, power allocation, and digital twin deployment. However, the inherent randomness of the problem presents a significant challenge in identifying an optimal solution. To address this, we first analyze the feasibility conditions of the optimization problem. We then examine a specific scenario involving a static channel and propose a cyclic scheduling scheme. This enables us to derive the sum AoI in closed form. As a result, the joint optimization problem of edge association and power control is solved optimally by finding a minimum weight perfect matching. Moreover, we examine the one-shot optimization problem in the contexts of both frequent digital twin migrations and fixed digital twin deployments, and propose an efficient online algorithm to address the general optimization problem. This algorithm effectively reduces system costs by balancing frequent migrations and fixed deployments. Numerical results demonstrate the effectiveness of our proposed scheme in terms of low cost and high efficiency. © 2024 IEEE.

关键词： Costs

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