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Dairy Cow Behavior Recognition Using computer Vision Techniques and CNN Networks

Dairy Cow Behavior Recognition Using Computer Vision Techniq...

引用

2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022

作者： Avanzato, Roberta Beritelli, Francesco Puglisi, Valerio Francesco University of Catania Dept. of Electrical Electronic and Computer Engineering Catania Italy University of Catania Dept. of Mathematics and Computer Science Catania Italy

ISBN: (数字)9798350396454

ISBN: (纸本)9798350396454

The application of automated monitoring systems for precision breeding has seen a great increase in recent years. In particular, several studies have addressed the possibility of recognizing cow behavior using computer vision, as well as the opportunity of uniquely identifying and locating individual cows within the barn. In this study, the authors propose a system for recognizing cow behavior within the barn, using a particular type of Convolutional Neural Network (CNN), YOLOv5, and estimation of cattle position via Multi-object recognition. The recordings are obtained from multiple cameras placed inside the barn, a mixed and vast dataset containing several 'Cow' objects was obtained and then labeled in two classes 'Cow_Standing' and 'Cow_Lying.' After the training phase, testing of the network was carried out. The results obtained using this Deep Learning (DL) model, show 94% accuracy, 96% precision and 92% recall in the training phase. In the inference phase, accuracy and recall of 88% and 91% were obtained, respectively. © 2022 IEEE.

关键词： Object recognition

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Enhancing the Security of Virtualized Infrastructure through Big Data Analytics in Cloud Computing 1

Enhancing the Security of Virtualized Infrastructure through...

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Bisen, Anand Singh Kumar, Ravi Hema, B. Jenasamanta, Abhinash Shakya, Lalit Mohan Shanthi, R. Vikrant University Dept. of CSE and IT Gwalior India ITM Skill University Dept of CSE Mumbai India Dhanalakshmi Srinivasan College of Engineering Dept. of Electronics and Communication Engineering Coimbatore India Usha Martin University Dept. of CSE Jharkhand India Science J.S. University Dept. of Computer Shikohabad India Meenakshi A.H.E.R Dept. of Mathematics Chennai India

ISBN: (纸本)9798350356816

This research paper presents a novel approach to enhancing the security of virtualized environments through big data analytics in cloud computing. While virtualization and cloud computing provide flexibility and cost-efficiency, they also pose unique security challenges. Traditional security mechanisms often struggle to detect and mitigate advanced persistent threats (APTs) and sophisticated cyberattacks. To overcome these challenges, the proposed method leverages big data analytics to analyze extensive and complex datasets, identifying patterns, anomalies, and potential threats. The paper includes a comprehensive literature review on big data analytics for cloud and virtualized security, alongside a framework for threat detection and prevention utilizing machine learning algorithms, data mining, and predictive analytics. The study evaluates the benefits and limitations of this method and highlights directions for future research. This approach is designed to strengthen the security of virtualized environments and provide robust protection against emerging and advanced cyber threats. © 2024 IEEE.

关键词： Cloud security

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Securing Sensitive Data: How Blockchain Transforms Privacy in Healthcare, Law, and Education

Securing Sensitive Data: How Blockchain Transforms Privacy i...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Bale, Ajay Sudhir Arulananth, T.S. Saranya, S. Gadag, Tejashwini Sathiamoorthy, J. Ponnuru, Sudhakiran New Horizon College of Engineering Dept. of Ece Karnataka Bengaluru India Mlr Institute of Technology Department of Electronics and communication Engineering Telangana Hyderabad500043 India Bms Institute of Technology & Management Dept. of Mathematics Bengaluru India School of Computer Science Engineering Reva University Bengaluru India Rmk Engineering college Department of Computer science and Design Kavarapettai India

ISBN: (纸本)9798331543617

In the field of healthcare, law, and education, Blockchain technology (BT) is emerging as a transformative force. This paper helps to explore the usage of BT to enhance the privacy and security in the above said domains. In healthcare industry, blockchain offers privacy and secure management of the vital electronic health records (EHR) and patient health records (PHR), boosting the data integrity and access control. In the law sector, blockchain-enabled smart contracts are providing new possibilities for the transactions automation, transparency, and security of the transactions, thoroughly facing the challenges in terms of jurisdiction and compliance with regulations like GDPR. In the field of education, blockchain technology is improvising the record-keeping, degree verification, and collaborative learning environments. The paper helps to examine the features like the effectiveness, efficiency, and security aspects of blockchain implementations in these sectors, focusing on both the potential benefits and the challenges imposed that need to be addressed for the widespread adoption in real time. © 2024 IEEE.

关键词： Electronic health record

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A data-driven approach for context definition in situation-aware wearable computing systems

A data-driven approach for context definition in situation-a...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Giuseppe D’Aniello Giancarlo Fortino Matteo Gaeta Zia Ur Rehman Dept. Information and Electrical Engineering and Applied Mathematics University of Salerno Fisciano Italy Dept. Computer Engineering Modeling Electronics and Systems University of Calabria Rende Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

A situation-aware wearable computing system is defined as a wearable device with the capability to perceive, comprehend, and project the situations occurring in the environment in order to adapt its behavior accordingly. For this kind of devices, the identification of complex situations related to the activities performed by users in various contexts is of great interest. This requires the capability to identify context states. A well-known technique for this task is the Context Space Theory (CST), which provides a multidimensional space representing contexts. Although powerful and lightweight, this technique has the drawback of requiring manual definition of such a space, a time-consuming process that involves domain experts. To address this issue, this work proposes a data-driven approach for defining context spaces in CST using kernel density estimation. This approach is compared with a state-of-theart expert-based CST technique and a fuzzy inference system for context representation, demonstrating superior performance on the Extrasensory dataset.

关键词： Performance evaluation Fuzzy logic computer aided software engineering Estimation Manuals computer architecture Feature extraction Object recognition Wearable devices Kernel

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CDP: Selective Influential Nodes Based on Cliques in the Diffusion Process in Social Networks 9

CDP: Selective Influential Nodes Based on Cliques in the Dif...

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9th International Conference on Web Research, ICWR 2023

作者： Yazdanifar, Fatemeh Beni, Hamid Ahmadi Salimi, Nikoo Bouyer, Asgarali Amirkabir University of Technology Dept. of Mathematics and Computer Science Tehran Iran Madani University Dept. Software Engineering Azarbijan Shahid Tabriz Iran University of Genoa Dept. of the Elec. Electronics Electronics and Telecommunication Eng. and Naval Architecture Genoa Italy Azarbaijan Shahid Madani University Dept. of Computer Engineering Tabriz Iran

ISBN: (纸本)9798350399691

Influence maximization techniques emphasize selecting a set of influential nodes in order to maximize influence. Because the algorithms presented in this field ignore the topology of cliques for diffusion, there are two major challenges in influence maximization algorithms: optimal diffusion and computational overhead reduction. As a result, the CDP algorithm is presented in this article to address these issues. This algorithm first selects suitable cliques for diffusion based on their position and strategy in social networks. Furthermore, for each clique, a score is calculated based on the topological criteria of the clique, and suitable cliques are selected for diffusion by applying a threshold limit. The seed nodes are chosen from the cliques in the second step. To avoid the rich club phenomenon, only a few nodes from each clique are chosen as seed candidate nodes. Finally, the seed nodes are chosen based on the node's topology and the strength of the node's level one neighbor. In the experiment section, the CDP algorithm significantly outperforms the best algorithms presented in recent years in terms of influence spread rate and execution time. © 2023 IEEE.

关键词： Diffusion

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Web User Profiling using Fuzzy Signatures and Browser Fingerprinting

Web User Profiling using Fuzzy Signatures and Browser Finger...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Aliberti, Luca Apicella, Francesco D'Aniello, Giuseppe Flammini, Francesco Gaeta, Matteo Salzano, Simone University of Salerno Dept. Information and Electrical Engineering and Applied Mathematics SA Fisciano Italy Evolution Adv Rome Italy Idsia USI-SUPSI University of Applied Sciences and Arts of Southern Switzerland School of Innovation Design and Engineering Mälardalen University Sweden

ISBN: (纸本)9781665410205

Accurately identifying and profiling users is one of the primary challenges of many modern web applications. This paper presents an approach for user profiling that utilizes Fuzzy User Signatures combined with browser fingerprinting techniques. Our approach analyzes users' web domain visit frequencies and categories to determine their preferences and behaviors. Fuzzy User Signatures provide a condensed representation of user activities, enabling a framework for assessing user similarity. This method can significantly improve web navigation experiences by allowing for personalized content and product recommendations. The approach has been evaluated on a dataset comprising users' web activities combined with browser fingerprints, achieving overall good performances. © 2024 IEEE.

关键词： User profile

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Gradient-free decoder inversion in latent diffusion models 24

Gradient-free decoder inversion in latent diffusion models

引用

Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Seongmin Hong Suh Yoon Jeon Kyeonghyun Lee Ernest K. Ryu Se Young Chun Dept. of Electrical and Computer Engineering INMC & IPAI Seoul National University Dept. of Electrical and Computer Engineering and Dept. of Mathematics University of California Los Angeles

ISBN: (纸本)9798331314385

In latent diffusion models (LDMs), denoising diffusion process efficiently takes place on latent space whose dimension is lower than that of pixel space. Decoder is typically used to transform the representation in latent space to that in pixel space. While a decoder is assumed to have an encoder as an accurate inverse, exact encoder-decoder pair rarely exists in practice even though applications often require precise inversion of decoder. In other words, encoder is not the left-inverse but the right-inverse of the decoder; decoder inversion seeks the left-inverse. Prior works for decoder inversion in LDMs employed gradient descent inspired by inversions of generative adversarial networks. However, gradient-based methods require larger GPU memory and longer computation time for larger latent space. For example, recent video LDMs can generate more than 16 frames, but GPUs with 24 GB memory can only perform gradient-based decoder inversion for 4 frames. Here, we propose an efficient gradient-free decoder inversion for LDMs, which can be applied to diverse latent models. Theoretical convergence property of our proposed inversion has been investigated not only for the forward step method, but also for the inertial Krasnoselskii-Mann (KM) iterations under mild assumption on cocoercivity that is satisfied by recent LDMs. Our proposed gradient-free method with Adam optimizer and learning rate scheduling significantly reduced computation time and memory usage over prior gradient-based methods and enabled efficient computation in applications such as noise-space watermarking and background-preserving image editing while achieving comparable error levels.

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Quantum Safe Construction of Authentication and Key Exchange Based on Module Lattices 4

Quantum Safe Construction of Authentication and Key Exchange...

引用

4th IEEE Global Conference for Advancement in Technology, GCAT 2023

作者： Banerjee, Sayan Nikhilesh, M. Sharma, Ankit Sreedevi, A.G. Rana, Saurabh Chaudhary, Dharminder Dept. of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Dept. of Mathematics Chitkara University Solan India Bennett University Noida India

ISBN: (纸本)9798350305258

An authenticated mobile key exchange is necessary for post quantum secure communication over a public channel. It allows two entities to create a secure and unique session key for every communication session. We feel a need to design two party efficient and secure authenticated key agreement. We have also observed all the protocols given above are based on learning with error assumption over a finite ring. The"Module Learning with Errors" assumption is the more appropriate choice among"Learning with Errors" and"Ring Learning with Errors" for designing practical password-authenticated key exchange protocols. With the help of"Module Learning with Errors" assumption, and by lowering the number of ring polynomials, several implementations of the protocols can be realized. Therefore, this paper contains quantum safe, efficient, and practical"Module Learning with Errors" assumption based authenticated key agreement protocol. The protocol's security analysis is presented within the framework of the random oracle model. © 2023 IEEE.

关键词： Authentication Cryptography Key Agreement Module Ring Learning with Errors Reconciliation

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Book Recommendation System using R Programming - A Comparative Study. 4

Book Recommendation System using R Programming - A Comparati...

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4th International Conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Sandhiya, B. Meera, K.N. Broumi, Said Amrita School of Engineering Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India Amrita School of Engineering Dept. of Mathematics Amrita Vishwa Vidyapeetham Bengaluru India Faculty of Science Ben m'Sik University of Hassan Ii Laboratory of Information Processing Casablanca Morocco

ISBN: (纸本)9798350307757

A Recommendation System (also known as Recommender System) is built for the purpose of recommending similar items to the user based on their interest. The item can be anything like movies, music, books, songs, etc. Many famous platforms such as Netflix and YouTube also use recommendation system. This paper focuses on comparing and studying the performance of the Recommender System for books that uses various different techniques such as k-means Clustering, PCA, Feature Selection, etc. © 2024 IEEE.

关键词： Recommender systems

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Exploring the Semantic Complexity of Adjective-Noun Collocations between Uzbek and English for Improved Machine Translation 9

Exploring the Semantic Complexity of Adjective-Noun Collocat...

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9th International Conference on computer Science and engineering, UBMK 2024

作者： Abdurakhmonova, Nilufar Shamieva, Nargiza Adali, Eşref National University of Uzbekistan Dept. of Computational and applied linguistics Tashkent Uzbekistan National Univ. of Uzbekistan Dept. of Foreign language and Literature Tashkent Uzbekistan Istanbul Technical University Computer Engineering and Informatics Faculty Istanbul Turkey

ISBN: (纸本)9798350365887

The bilingual thesaurus of Uzbek-English adjectives is a field that has not been studied well explored yet for machine translation. Several websites and electronic dictionaries created nearby show that not enough semantically close adjectives are included in them. Despite extensive research on the meaning the adjectives in both languages, there remains a lack of understanding about the relationship between the adjective itself and the noun, which has an absolutely new connotation in collaboration. Our result shows that a recent bilingual thesaurus demonstrates how one adjective could acquire numerous new synonyms while combining with different nouns. The meanings of words, in both languages have been extensively studied, Little is understood about the dynamic connection between these words and the nouns they describe. The complexity of how adjectives pair with nouns is evident in how this relationship leads to meanings and connotations. Our study aims to bridge this gap by demonstrating how a bilingual thesaurus can capture the meanings and variations of adjectives when combined with nouns. The findings indicate that depending on the noun it accompanies a contemporary bilingual thesaurus can generate synonyms, for a single adjective. © 2024 IEEE.

关键词： Machine translation

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