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Challenge-Response Emotion Authentication Algorithm Using Modified Horizontal Deep Learning

Intelligent Automation & Soft Computing 2023年第3期35卷 3659-3675页

作者： Mohamed Ezz Ayman Mohamed Mostafa Ayman Elshenawy College of Computer and Information Sciences Jouf UniversitySakaka72314Saudi Arabia Systems and Computers Engineering DEPT Faculty of EngineeringAl-Azhar UniversityCairo11651Egypt Software Engineering&Information Technology Faculty of Engineering&TechnologyEgyptian Chinese UniversityEgypt

Face authentication is an important biometric authentication method commonly used in security *** is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social media to perform spooﬁng attacks and dynamic movements for penetrating secur-ity *** paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble *** proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a speciﬁc response for every authentication trial with a different sequence of *** proposed model is applied to the KDEF dataset using 10-fold *** improvements are made to the proposed ***,the VGG16 model is applied to the seven common ***,the system usability is enhanced by analyzing and selecting only the four common and easy-to-use ***,the horizontal ensemble technique is applied to enhance the emotion recognition accuracy and minimize the error during authen-tication ***,the Horizontal Ensemble Best N-Losses(HEBNL)is applied using challenge-response emotion to improve the authentication efﬁ-ciency and minimize the computational *** successive improvements implemented on the proposed model led to an improvement in the accuracy from 92.1%to 99.27%.

关键词： Face authentication challenge-response authentication transfer learning and horizontal ensemble technique

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IT/OT Convergence Protocols: DNP3, Ethernet/IP, and Modbus

IT/OT Convergence Protocols: DNP3, Ethernet/IP, and Modbus

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Zahran, Bassam Abu Zahra, Fuad University of Wisconsin Platteville Dept of Computer Science and Software Engineering WI United States University of Wisconsin Milwaukee Dept of Engineering and Applied Sciences WI United States

ISBN: (纸本)9798350327595

The convergence of Information Technology (IT) and Operational Technology (OT) systems is becoming a ne-cessity. In the context of IT/OT convergence, various protocols are widely employed to enable smooth communication and data exchange between IT and OT systems. It is crucial to gain a comprehensive understanding of the networking and data flow between these systems in order to effectively identify and address potential security risks. This study aims to explore several common protocols utilized in IT/OT convergence and examine their strengths and weaknesses. This initial exploration will serve as a foundation for further investigation into potential security breaches and the development of appropriate countermeasures in the context of IT/OT convergence. © 2023 IEEE.

关键词： cybersecurity IIOT IT/OT risk management

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IT/OT Convergence Protocols: MQTT, OPC, and REST

IT/OT Convergence Protocols: MQTT, OPC, and REST

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Zahran, Bassam Abu Zahra, Fuad University of Wisconsin Dept of Computer Science and Software Engineering PlattevilleWI United States University of Wisconsin Dept of Engineering and Applied Sciences MilwaukeeWI United States

ISBN: (纸本)9798350327595

Information Technology and Operational Technology convergence refers to the integration and merge of IT and OT systems within an organization. Several protocols are commonly used in IT/OT convergence to facilitate communication and data exchange between IT and OT systems. It is imperative to understand how both systems are linking and exchanging data to be able to examine potential security breaches. In this study, we will discuss some of the common protocols used to achieve this convergence. We will include the known strengths and weaknesses of each. This will be considered an initial foundation to study potential security breaches and countermeasures for IT/OT convergence. © 2023 IEEE.

关键词： cybersecurity IIOT IT/OT risk management

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Medicinal Plants Recognition Using Deep Learning

Medicinal Plants Recognition Using Deep Learning

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2023 International Conference on Multimedia Computing, Networking and Applications, MCNA 2023

作者： Sharrab, Yousef Al-Fraihat, Dimah Tarawneh, Monther Sharieh, Ahmad Isra University Dept. of Computer Science Amman Jordan Isra University Dept. of Software Engineering Amman Jordan The University of Jordan Dept. of Computer Science Amman Jordan

ISBN: (纸本)9798350339277

The use of medicinal plants has been a longstanding practice in traditional medicine worldwide. Accurately identifying medicinal plants is crucial for determining their medicinal properties and potential applications. However, it can be a challenging task due to the complexity of their appearance. Variations in growth stage, lighting, and imaging conditions can make classification challenging, which limits the application of traditional methods for plant identification. This paper proposes a deep learning-based approach that uses a convolutional neural network (CNN) based on the VGG-16 model. With a dataset of 25,686 images, the CNN is capable of learning and representing complex features in images, enabling it to recognize and classify medicinal plants with high accuracy. The proposed approach can efficiently classify plants with different growth stages, lighting conditions, and imaging settings, providing a reliable tool for plant identification. We achieved an impressive recognition rate of 98%, demonstrating the feasibility of using deep learning techniques for accurate plant classification. The proposed approach has enormous potential for providing healthcare professionals and herbal medicine researchers with a reliable tool for identifying herbal plants. the study represents an essential advancement in the use of deep learning techniques for medicinal plant recognition, overcoming the challenges posed by their complex appearance. The proposed approach has farreaching implications and can significantly impact the field of herbal medicine research, enabling researchers and healthcare professionals to identify and classify medicinal plants more accurately © 2023 IEEE.

关键词： Classification (of information)

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Quantitative Trends Analysis on Russian Literature Research in Korean Academia: Insights from KCI Data 10

Quantitative Trends Analysis on Russian Literature Research ...

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10th International Conference on Platform Technology and Service, PlatCon 2024

作者： Iosifovich, Ten Alexander Yeo, Sang-Soo Jung, Young-Ae Dept. of Computer Science Sun Moon University Asan Korea Republic of Dept. of Computer Engineering Mokwon University Daejeon Korea Republic of Dept. of AI Software Technology Sun Moon University Asan Korea Republic of

ISBN: (纸本)9798350367874

This paper presents a quantitative analysis of trends in Russian literature and Korean-Russian translated literature within Korean academia from 1996 to 2024. By analyzing frequency themes and contexts, the study explores evolving research trends, revealing how sociocultural, political, and artistic exchanges between Korea and Russia have influenced each other. Future research using text mining promises to uncover more specific patterns, offering deeper insights into literary and cultural exchanges. This study contributes to understanding the role of literature in expressing and understanding sociopolitical and cultural values in both countries. © 2024 IEEE.

关键词： Korean Citation Index Korean-Russian literature Quantitative analysis Research trend analysis Text mining

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Phoneme Classification in Imagined Speech Using Explainable Machine Learning 13

Phoneme Classification in Imagined Speech Using Explainable ...

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13th International Winter Conference on Brain-computer Interface, BCI 2025

作者： Kim, Sejin Kang, Hyunwook Jeong, Ji-Hoon Lee, Minji Dept. Artificial Intelligence The Catholic University of Korea Bucheon Korea Republic of Dept. Electrical and Computer Engineering Inha University Incheon Korea Republic of Dept. Computer Science Chungbuk National University Cheongju Korea Republic of Dept. Biomedical Software Engineering The Catholic University of Korea Bucheon Korea Republic of

ISBN: (纸本)9798331521929

Imagined speech is gaining attention as a next-generation paradigm for brain-computer interfaces in terms of its intuitiveness in communication. Many studies have focused on classifying imagined words as the basis of communication, but some studies on phoneme classification based on imagined speech have begun to be conducted in terms of the fact that combinations of phonemes can further expand sound images. In addition, explainability is a major issue in classification results in machine learning, but there have been few studies that analyzed the explainability of imagined speech classification. In this study, we examined explainability using SHAP for phoneme classification based on imagined speech. FEIS dataset was used, and 16 phonemes were classified using the XGBoost classifier. In 21 subjects, the average accuracy was 40.36%, the average precision was 41.7%, the average recall was 40.34%, and the average F1-score was 40.7%. In addition, when looking at Sub 04, which had the highest performance, the SHAP values were high in AF3 and F7 channels, which correspond to Wernicke’s area related to speech. In this regard, we could observe the feature importance of this area. These results prove that Wernicke’s area actually plays an important role in classifying phoneme units in imagined speech, and can provide important insights to improve the performance of imagined speech for intuitive communication based on brain-computer interface in the future. © 2025 IEEE.

关键词： Adversarial machine learning

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Exploiting Impact of Eavesdropping Attacks on Secrecy Performance in WPT-based Secure Multi-hop Transmission 14

Exploiting Impact of Eavesdropping Attacks on Secrecy Perfor...

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14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Shim, Kyusung An, Beongku Hankyong National University School of Computer Engineering & Applied Mathematics Korea Republic of Hongik University Dept. of Software and Communications Engineering Korea Republic of

ISBN: (纸本)9798350335385

In this paper, we study the impact of various eaves-dropping attacks on the secrecy performance in wireless power transfer (WPT)-based secure multi-hop transmission. Since each node has a limited power supply, each node harvests energy from the power beacon before data transmission. After then, each node fully consumes the harvested energy for data transmission. Meanwhile, according to the nature of the wireless medium, eavesdroppers can overhear the confidential message at each hop. In order to exploit the relationship between network parameters and secrecy performance, we derive the closed-form expression for secrecy outage probability (SOP) with different eavesdropping attacks, respectively. From the numerical results, we show that the Monte-Carlo simulation and analysis results are tightly matched. Additionally, we evaluate and discuss the impact of the power beacon's transmit power, the number of eavesdroppers, and time switching ratio on the secrecy performance. © 2023 IEEE.

关键词： Monte Carlo methods

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Dynamic View Synthesis of Thin Structures with Short-term Movements from Monocular Videos Using Neural Radiance Fields 25

Dynamic View Synthesis of Thin Structures with Short-term Mo...

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25th International Conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Rajapaksha, Uchitha Laga, Hamid Diepeveen, Dean Bennamoun, Mohammed Sohel, Ferdous School of Information Technology Murdoch University MurdochWA Australia The University of Western Australia Dept. of Computer Science and Software Engineering CrawleyWA Australia

ISBN: (纸本)9798350379037

Learning to generate motions of thin structures such as plant leaves in dynamic view synthesis is challenging. This is because thin structures usually undergo small but fast, non-rigid motions as they interact with air and wind. When given a set of RGB images or videos of a scene with moving thin structures as input, existing methods that map the scene to its corresponding canonical space for rendering novel views fail as the object movements are too subtle compared to the background. Disentangling the objects with thin parts from the background scene is also challenging when the parts show fast and rapid motions. To address these issues, we propose a Neural Radiance Field (NeRF)-based framework that accurately reconstructs thin structures such as leaves and captures their subtle, fast motions. The framework learns the geometry of a scene by mapping the dynamic images to a canonical scene in which the scene remains static. We propose a ray masking network to further decompose the canonical scene into foreground and background, thus enabling the network to focus more on foreground movements. We conducted experiments using a dataset containing thin structures such as leaves and petals, which include image sequences collected by us and one public image sequence. Experiments show superior results compared to existing methods. Video outputs are available at https://***/. © 2024 IEEE.

关键词： Rendering (computer graphics)

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Towards an integration management maturity 49

Towards an integration management maturity

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49th Euromicro Conference on software engineering and Advanced Applications, SEAA 2023

作者： Hyrynsalmi, Sonja M. Olsson, Helena Holmstrom Bosch, Jan Lut University Dept. Software Engineering Lahti Finland Malmö University Dept. Computer Science and Media Technology Malmö Sweden Chalmers University of Technology Dept. Computer Science and Engineering Göteborg Sweden

ISBN: (纸本)9798350342352

As industries continue to digitize at a rapid pace, the number of integrations, the connections between different digital systems, is increasing. As a consequence, integration management is becoming increasingly difficult, leading to scalability, stability, and system outage problems that directly affect company performance. For that reason the modern integration management platforms have emerged to offer efficient management of the growing number of integrations, as well as a new way to handle, enrich, and utilize data both inside and outside *** research involved interviews with 20 software vendor professionals and 20 clients who had recently undergone an integration platform project. The study identified key drivers behind integration management projects and recognized different maturity levels in integration management. The results revealed that more mature companies are utilizing modern integration platforms to support their digital transformation. The study also highlighted the growing importance of data management and utilization in integration *** address these findings, a maturity model was developed to help companies evaluate their current integration management status and find ways to progress in their integration management. © 2023 IEEE.

关键词： Integration

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Towards a Data Business Maturity Model for software-intensive Embedded System Companies 29

Towards a Data Business Maturity Model for Software-intensiv...

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29th International Conference on engineering, Technology, and Innovation, ICE 2023

作者： Hyrynsalmi, Sami Olsson, Helena Holmström Bosch, Jan Lut University Dept. Software Engineering Lahti Finland Malmö University Dept. Computer Science and Media Technology Malmö Sweden Chalmers University of Technology Dept. Computer Science and Engineering Göteborg Sweden

ISBN: (纸本)9798350315172

Data has been quickly becoming as the fuel, the new oil, of growth and prosperity of companies in the modern age. With useful data and sufficient tools, companies have the ability to enhance their current products, presents new innovations and services as well as generate new revenue streams with a secondary customer base. While there are ongoing efforts to develop machine learning and data science techniques, little attention has been paid to understanding and characterizing data-related business activities in software-intensive *** multiple-case study examines four large international embedded system companies to explore how they are utilizing data and how they have proceeded in their journey in the data business. This study identifies six distinct stages, each with unique challenges, that seems to be common for embedded system companies in their data business. As the result, this study presents an initial data business maturity model for software-intensive embedded system companies. Additionally, this research provides a foundation for future efforts to support software-intensive embedded system companies in establishing data businesses. © 2023 IEEE.

关键词： Embedded systems

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