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Emotion Recognition from Video Frame Sequence using Face Mesh and Pre-Trained Models of Convolutional Neural Network 24

Emotion Recognition from Video Frame Sequence using Face Mes...

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24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023

作者： Adi, Derry Pramono Yuniarno, Eko Mulyanto Wulandari, Diah Puspito Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Dept. of Electrical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Dept. of Electrical Engineering Dept. of Computer Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Dept. of Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350313956

Emotions are a collection of subjective cognitive experiences and psychological and physiological characteristics that express a wide range of feelings, thoughts, and behaviors in human interaction. Emotions can be represented through several means, such as facial expressions, tone of voice, and behavior. Deep Learning (DL) research has focused on incorporating facial expressions. Images with facial expressions are commonly used as data input for the DL model. Unfortunately, most DL models in Facial Emotion Recognition (FER) use static images. This method does not take into consideration all conceivable facial expressions. The static image of facial expressions is insufficient for recognizing emotions, but a sequential image from a video is required. In this study, we extract MediaPipe's face mesh feature, the state-of-the-art multidimensional expression key points embedded in the video image sequence. Furthermore, we feed sequence image data into the pre-trained Convolutional Neural Network (CNN) model. The data we used is from The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) with the emotion classes of 'Anger,' 'Fearful,' 'Happy,' and 'Sad.' For this specific FER task, we found that the best pre-trained CNN model achieved 92.8% accuracy (using the VGG-19 model), with the fastest runtime of ∼2.3 seconds (achieved using the SqueezeNet model). © 2023 IEEE.

关键词： Emotion Recognition

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From Manual to Machine: How AI is Redefining Web Scraping for Superior Efficiency: A Literature Review 3

From Manual to Machine: How AI is Redefining Web Scraping fo...

引用

3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Ayuso, Enrique Dumfeh Brogya, Maame Serwah Kumar Ahlawat, Vinay Sain, Mangal Dongseo University Dept. of Computer Engineering Busan Korea Republic of Gla University Dept. of Electronics & Communication Mathura India

ISBN: (纸本)9798331528201

Web Scraping involves the use of bots for the purpose of extracting data from the online web. To extract such data, the web scraper must conduct at least 3 different steps, i.e., collect the necessary links from the web, extract data using the provided links, and save the information in a neatly organized CSV file or database. However, traditional methods to accomplish these steps have faced many difficulties, such as anti-scraping measures and website changes. To tackle these difficulties and to accomplish the steps in a more rapid yet advanced way, Artificial Intelligence (AI) can be utilized. As of mid-2024, the rapid development and improvement of AI has resulted in its integration into many businesses and educational institutions. The current state of AI is remarkably advanced that it can be integrated in about any field and sector available. In this paper, the researcher defined the term Web Scraping, Artificial Intelligence, Natural Language Processing, and Machine Learning, explained the use of AI in Web Scraping including its importance and potential, and the understanding of ethical web scraping practices. This literature review indicated that the integrated use of AI improves the performance of Web Scraping compared to traditional methods. © 2024 IEEE.

关键词： Adversarial machine learning

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BloodBond: Optimising Blood Bank System through a Comprehensive Smart Management System 8

BloodBond: Optimising Blood Bank System through a Comprehens...

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Sharma, Chirag Shah, Vidhi Singh, Vedantika Tank, Kevin Gupta, Sudha Hakim, Ayesha Vidyavihar University K.J. Somaiya College of Engineering Somaiya Dept. Computer Engineering India Vidyavihar University K.J. Somaiya College of Engineering Somaiya Dept. Electronics Engineering India

ISBN: (纸本)9798350391770

In densely populated areas like Mumbai, the challenge of efficiently managing blood donations is critical. The gap between available donors and the urgent need for various blood types, especially in emergencies and for chronic conditions, necessitates a robust solution. Online Blood Bank Management System innovatively addresses this need, revolutionizing the blood donation and distribution process. The system enhances accessibility with a locality search feature, allowing donors to easily find and participate in nearby blood drives. It simplifies donor registration and donation management and includes educational resources. Hospitals and blood banks benefit from a dashboard for organizing donation events, monitoring blood stock, and managing blood group requests. The key contribution of this research paper is the Emergency Blood Request Donor Notification system, which allows hospitals to quickly alert potential donors in urgent situations. Furthermore, the integration of the Donor Retention Model, a machine learning tool, predicts the likelihood of donors becoming long-term, dedicated contributors. This model has demonstrated an impressive 78.30 % accuracy in identifying potential dedicated donors, crucial for patients requiring consistent blood supplies. © 2024 IEEE.

关键词： Machine learning

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Implementation of a Secure Cellular Stream Cipher System for Multimedia Encryption 100

Implementation of a Secure Cellular Stream Cipher System for...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Peri, Priyanka Dutta, Jayati Malkuchi, Rohith Indian Institute of Technology Dept. of Electrical Engineering Hyderabad India Virginia Polytechnic Institute and State University Dept. of Electronics and Computer Engineering Blacksburg United States

ISBN: (纸本)9798331517786

In this paper, we explore the implementation and performance of cellular stream cipher algorithms for multimedia encryption, marking the first comprehensive assessment within the cellular standards. We evaluate these algorithms across the formats like text, audio, images, and video, using key metrics to gauge their efficiency and suitability for secure communication. This work addresses a significant gap in the literature on secure multimedia transmission over cellular networks. © 2024 IEEE.

关键词： Ciphertext

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A New S-Box Design Approach for SNOW 3G Using the POS of Power Functions 16

A New S-Box Design Approach for SNOW 3G Using the POS of Pow...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

ISBN: (纸本)9798350383119

In this paper, we propose 'S-POS', an 8× 8 S-box as a more secure alternative to Snow 3G's existing S2 S-box. By leveraging the product of the sum (POS) of power functions in GF28), S-POS demonstrates superior performance in key metrics such as differential uniformity (DU), non-linearity (NL), and algebraic immunity (AI) compared to the traditional S2-box. Additionally, differential and linear cryptanalysis reveals that S-POS enhances the keystream's randomness, supporting its potential as a replacement for the current S2-box in the Snow 3G stream cipher. © 2024 IEEE.

关键词： Cryptosystem POS of power functions Stream cipher Substitution box

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Effect of the Shielding for Opened Windows of the Reusable Vehicle Test for 5.8-GHz-Band Microwave Power Transmission 35

Effect of the Shielding for Opened Windows of the Reusable V...

引用

35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023

作者： Yoshida, Satoshi Nishikawa, Kenjiro Ryukoku Univ. Dept. of Electronics and Informatics Shiga Japan Kagoshima Univ. Dept. of Electrical and Electronics Engineering Japan

ISBN: (纸本)9789463968096

This paper summarized the effect of the shielding for opened windows of the Reusable Vehicle Test (RVT) for 5.8-GHz-band microwave power transmission (MPT). The MPT system was equipped to power the 2.4-GHz-band ZigBee wireless data communication system. Experimental evaluations were performed using the RVT. The measurement result showed that output DC power from the rectifier increased under the condition of closing all windows while no affect for data communication was observed. It is concluded that the shielding window is effective to get large DC power. © 2023 International Union of Radio Science.

关键词： Plasma jets

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Dependable Wireless Powering for the Wireless Sensor Station by Using Combination of Solar Cell and Rectenna

Dependable Wireless Powering for the Wireless Sensor Station...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Yoshida, Satoshi Nishikawa, Kenjiro Ryukoku Univ. Dept. of Electronics and Informatics Shiga Japan Kagoshima Univ. Dept. of Electrical and Electronics Engineering Japan

ISBN: (纸本)9781665442282

This paper proposes an experimental evaluation result of the combination of solar cell and rectenna for wireless sensor network to realize the dependable wireless powering. 100 W class microwave power transmission (MPT) and 3000 Ix illuminance photovoltaic power generation are combined to the system. The measurement results of the output DC power were 325 mW and 160 mW for the configuration of combination of MPT and 3000 Ix photovoltaic power generation and the configuration of MPT only, respectively. The combination of the MPT and photovoltaic power generation is effective to get large DC power. © 2023 IEEE.

关键词： Solar energy

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Reference-based Burst Super-resolution 24

Reference-based Burst Super-resolution

引用

32nd ACM International Conference on Multimedia, MM 2024

作者： Ko, Seonggwan Koh, Yeong Jun Cho, Donghyeon Dept. of Electronics Engineering Chungnam National University Daejeon Korea Republic of Dept. of Computer Science & Engineering Chungnam National University Daejeon Korea Republic of Dept. of Computer Science Hanyang University Seoul Korea Republic of

ISBN: (纸本)9798400706868

Burst super-resolution (BurstSR) utilizes signal information from multiple adjacent frames successively taken to restore rich textures. However, due to hand tremors and other image degradation factors, even recent BurstSR methods struggle to reconstruct finely textured images. On the other hand, reference-based super-resolution (RefSR) leverages the high-fidelity reference (Ref) image to recover detailed contents. Nevertheless, if there is no correspondence between the Ref and the low-resolution (LR) images, the degraded output is derived. To overcome the limitations of existing BurstSR and RefSR methods, we newly introduce a reference-based burst super-resolution (RefBSR) that utilizes burst frames and a high-resolution (HR) external Ref image. The RefBSR can restore the HR image by properly fusing the benefits of burst frames and a Ref image. To this end, we propose the first RefBSR framework that consists of Ref-burst feature matching and burst feature-aware Ref texture transfer (BRTT) modules. In addition, our method adaptively integrates features with better quality between Ref and burst features using Ref-burst adaptive feature fusion (RBAF). To train and evaluate our method, we provide a new dataset of Ref-burst pairs collected by commercial smartphones. The proposed method achieves state-of-the-art performance compared to both existing RefSR and BurstSR methods, and we demonstrate its effectiveness through comprehensive experiments. The source codes and the dataset are available at https://***/SeonggwanKo/RefBSR. © 2024 ACM.

关键词： Image reconstruction

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Edge Computing Devices Authentication using Quantum Computing 15

Edge Computing Devices Authentication using Quantum Computin...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Telsang, Vinayak A. Kakkasageri, Mahabaleshwar S. Devangavi, Anil D. Dept. of Computer Science and Engineering Biluru Gurubasava Mahaswamiji Institute of Technology Mudhol India Dept. Electronics and Communication Engineering Basaveshwar Engineering College Bagalkote India Dept. of Artificial Intelligence and Machine Learning Basaveshwar Engineering College Bagalkote India

ISBN: (纸本)9798350370249

Edge computing allows different technologies such as Internet of Things (IoT), vehicle-to-vehicle communications(VV), Industrial IOT (IIOT) to connect to the cloud computing to facilitate end users. The edge networks uses low bandwidth, and enhances the processing speed. With more number of IoT devices connected in the network the privacy of data stored at the edge server also under threat. Authentication is a major challenge which is be addressed to provide security and privacy to IoT devices connected in the network. The existing works uses cryptographic algorithms to solve the authentication problems, but with increase in growth of quantum computers and quantum computing, breaking the complex cryptographic algorithm is not an issue. Hence one should adopt the quantum approach to provide authentication in edge network. The proposed work uses quantum key and context information of IoT devices to store in the edge server using blockchain, which proves to be more secure. The performance analysis shows that it is better with respect to registration, encryption, decryption and authentication of IoT devices. ©2024 IEEE.

关键词： Authentication Blockchain Cryptography Edge computing Quantum key

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IoT Based Poultry Farm Smart Management System

IoT Based Poultry Farm Smart Management System

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Krishnamurthy, K.T. Managuli, Manjunath Malipatil, Sushma Bagyalakshmi, K. Salake, Sudha V. Kadalagi, Pankaja S. Patil, Sheetal B. Bms College of Engineering Vtu Dept. of Electronics & Instrumentation Belagavi India Kls Gogte Institute of Technology Vtu Dept. of Electronics & Communication Belagavi India Amc College of Engineering Vtu Dept. of Computer Science Belagavi India Sri Ranganathar Institute of Engineering & Technology Dept. of Electrical & Electronics Coimbatore India Kls Gogte Institute of Technology Vtu Dept. of Computer Science Belagavi India Sgb Institute of Technology Vtu Dept. of Computer Science Belagavi India

ISBN: (纸本)9798350359688

One of the greatest significant and fastest-growing financial sectors of India's agriculture industry at the moment is poultry. Chicken output has been steadily rising globally due to superior manufacturing processes and uniform farming management. Automation is essential in today's environment, and the Internet of Things (IoT) is a rapidly developing idea. Traditional systems are being transformed into automated systems. The project's main goal is to automate chicken farms by utilizing Internet of Things technology to carry out several management-related tasks. This study examines how a poultry farm's environmental factors, similar to humidity, temperature, and ammonia gas, are automatically observed and managed to promote chicken growth. The water position is also controlled and covered with the help of a detector module. All detector values are acquired by connecting all the detector modules to the microcontroller, and also, using the WIFI module, they will be uploaded to the webpage. Being in the care of the loud ranch can get the inner eco-friendly condition over a PC using the internet. This system will control temperature, moisture, ammonia gas and water situation with the help of a cooling addict, exhaust addict, ventilation window and DC motor without any moral interface. Grounded on the threshold values, it'll switch on the bias. therefore, this system design provides automated flesh, reduces the pool, and increases the product of healthy cravens. © 2024 IEEE.

关键词： DC motors

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