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Recognition of mortar pumpability via computer vision and deep learning

Journal of Electronic science and Technology 2023年第3期21卷 73-81页

作者： Hao-Zhe Feng Hong-Yang Yu Wen-Yong Wang Wen-Xuan Wang Ming-Qian Du Research Institute Electronic Science and Technology University of Electronic Science and Technology of ChinaChengdu611731China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China The Second Research Institute of Civil Aviation Administration of China Chengdu610041China

The mortar pumpability is essential in the construction industry,which requires much labor to estimate manually and always causes material *** paper proposes an effective method by combining a 3-dimensional convolutional neural network(3D CNN)with a 2-dimensional convolutional long short-term memory network(ConvLSTM2D)to automatically classify the mortar *** results show that the proposed model has an accuracy rate of 100%with a fast convergence speed,based on the dataset organized by collecting the corresponding mortar image *** work demonstrates the feasibility of using computer vision and deep learning for mortar pumpability classification.

关键词： Classification computer vision Deep learning Pumpability 2-dimensional convolutional long short-term memory network (ConvLSTM2D) 3-dimensional convolutional neural network(3D CNN)

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Human Affect Recognition Using Deep Learning Approaches

Human Affect Recognition Using Deep Learning Approaches

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

作者： Seshaiah, M. Bhargavi, D.S. Hema, H. Mallikashree, N. Manuja, C.R. S J C Institute of Technology Department of Computer Science and Engineering Chickballapur India

ISBN: (纸本)9798350359688

An important advance towards more characteristic human-computer interaction is the automatic detection of human impact. Present-day developments entail the integration of physiological and audiovisual sensors to identify emotions in real-world situations, posing a challenge to standard machine learning algorithms. A thorough assessment of creative writing on human affect recognition from 2010 to 2017 is done in this research, with a centre on deep neural network-based approaches. A distinct trend toward the promotion of deep learning (DL) methods is visible in the classification of 950 studies based on whether they used shallow or deep learning architectures. An extensive assessment of deep neural network appeal in this sector is possible through a more concentrated investigation of a subset consisting of 233 papers that use them. The development of spatial, temporal, and joint feature representations for multi- modal sensor data requires DL. To demonstrate the significant advancements made in this area, the study presents estimable state-of-the-art architectures. For academics working on similar applications, the outcome is identified, and the significance of frameworks in the field of human affect is recognized. © 2024 IEEE.

关键词： Adversarial machine learning

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Mood -Enhancing Music Recommendation System based on Audio Signals and Emotions 6

Mood -Enhancing Music Recommendation System based on Audio S...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Mounika, V. Charitha, Y. Dept.Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798350398496

The identity of emotional speech is a significant topic within the discipline of interactions between humans and computers. Many strategies of figuring out emotions in human speech had been introduced and installed through diverse researchers. To identify noises in audio documents is the purpose of one of these versions. Together with gender recognition and YouTube video will be played depending on mood, this suggested computer also features speech emotion detection, which listens for sentiments like happiness, rage, and sadness in audio cues. This output is sent as input to YouTube, which plays song within the user's mind, resulting in the person's temper to stabilize fast. Using the CNN characteristic extraction approach, the function sizes vector become processed with NumPy, and the audio class became carried out in MFCC. This research study mainly uses two programs: RAVDESS and SAVEE. Using the acquired datasets, a new version of the look was produced in-depth. The device area is the platform where the Google Colab is used to perform code execution. © 2023 IEEE.

关键词： Emotion Recognition

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A Robust Approach to Cloud Data Securityusing an Amalgamation of AES and Code-Based Cryptography

A Robust Approach to Cloud Data Securityusing an Amalgamatio...

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2024 International Conference on science, Technology, engineering and Management, ICSTEM 2024

作者： Muthulakshmi, Mahesh R. Anithaashri, T.P. Institute of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Médical and Technical Sciences Thandalam Tamilnadu Chennai India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350376913

Data security in cloud environments is a critical concern that increases dependence on cloud services and the persistent threat. The purpose of this paper is to present a new approach that uses the McEliece cryptosystem a form of code-based cryptography, with Advanced Encryption Standard (AES) to provide data security in the ***-based cryptography is to establish secure communication channels, while Advanced Encryption Standard is employed for efficient data encryption. Using hybrid cryptography techniques, this approach addresses the emerging need for quantum-resistant security measures and strong data protection in cloud environments. A comparative study is conducted to assess the effectiveness of this approach, examining the performance of a combination of codee-based and Advance Encryption *** findings suggest promising results in addressing the growing challenges of data security in cloud-based systems, paving the way for flexible and secure cloud infrastructure. © 2024 IEEE.

关键词： Data privacy

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Unifying Application and Adaptative Patterns for Confused student EEG Signals Classification 14

Unifying Application and Adaptative Patterns for Confused st...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Menaka, S. Aishwarya, S. Singh, Ritwik Sameer, Shaik Srm Institute of Science and Technology Ramapuram Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350335095

During COVID-19 pandemic, online education has become a crucial educational tool. While it offers numerous benefits, it does not have face-to-face interactions, making it challenging to assess students' comprehension levels and detect confusion. This research utilizes electroencephalogram (EEG) data to identify confusion in students using the MOOC platform. Current ways to detect confusion primarily concentrate on optimizing models, and the study of feature engineering is relatively limited. Brain fog, or confusion, is a significant cause of low performance in learning and other cognitive tasks. The ability to detect confusion in world time is a complex and essential matter that has numerous applications, including online education and driver fatigue detection. The paper employsBidirectional LSTM Recurrent Neural Networks to acknowledge a student's difficulties and confusion while watching course videos on the internet, using EEG data. The study reveals to us that the Bidirectional LSTM model outperforms other machine learning methods anddemonstrates remarkable stability in cross-validation. The study achieves an accuracy rate of % in predicting student confusion. Additionally, the research highlights that the wave (gamma) of the EEG signal is the most critical feature in detecting brain confusion. These findings underscore the potential of machine learning to model and comprehend brain function. © 2023 IEEE.

关键词： Electroencephalography

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PALCT: vehicle-to-vehicle communication based on pseudonym assignment and encryption scheme using delay minimisation cover tree algorithm

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International Journal of Vehicle Information and Communication Systems 2025年第2期10卷 132-147页

作者： Tandon, Righa Gupta, P.K. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Jaypee University of Information Technology HP Solan173 234 India Department of Data Science School of Computing Mohan Babu University AP Tirupati517 102 India

Vehicle-to-vehicle communication is one of the new paradigms of networking, which should be secure, fast, and efficient. In this paper, we propose a framework that implements the pseudonym-based authentication scheme in which communication among vehicles is encrypted by using a matrix array symmetric key (MASK), digital signature algorithm (DSA), and intelligent water drop (IWD). The proposed security scheme also ensures the handling of many security attacks like key-guessing, non-repudiation, replay, and modification. In the proposed scheme, to preserve the identity of the vehicle, we have provided the different pseudonyms for each vehicle in the network that ensure secure communication among vehicles. Furthermore, the proposed delay minimisation cover tree algorithm ensures the issue of timed delay during vehicle-to-vehicle communication. In this algorithm, we have used Dijkstra’s algorithm for finding the optimal shortest path during vehicular communication. The results obtained show that the proposed scheme is effective and efficient, as it reduces the time delay by 4% for 140 vehicle nodes and 28.4% for 1000 vehicle nodes. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Encryption algorithms

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IntelliFarmAssist – A Novel Machine Learning integrated Genetic Algorithm Based Optimal Crop Recommendation System 1

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Mala, D. Jeya Basak, Swetaswa Reynold, A. Pradeep School of Computer Science and Engineering Vellore Institute of Technology Chennai India ASET College of Science and Technology Chennai India

ISBN: (数字)9783031648502

ISBN: (纸本)9783031648496

Crop recommendation is a critical task for agricultural productivity, and weather and soil conditions play a significant role in determining the suitable crop to grow. In this research, an intelligence assisted approach is used to develop a crop recommendation system that takes into account the weather and soil content of a particular region. The system uses weather and soil data to create objects that represent the conditions, and then applies a set of rules used as the fitness criteria in the proposed Genetic Algorithm to determine the optimal crop for the given conditions. The approach allows for flexible and modular design, making it easy to modify and extend the system. The results demonstrate the effectiveness of the proposed system in providing accurate and timely crop recommendations, which can help farmers to make informed decisions and improve their yield. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Smart city

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A Heuristic Approach to Identify Influential Node in Complex Social Networks 14

A Heuristic Approach to Identify Influential Node in Complex...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Dutta, Sangita Chakraborty, Susanta Indian Institute of Engineering Science and Technology Department of Computer Science and Technology Howrah India

ISBN: (纸本)9798350335095

Multiple features of the complex network are exhibited among the nodes in time-varying social networks. Community detection has numerous approaches, but the majority of methods are restricted to disjoint community situations. Solutions to disjoint community situations do not reflect well on real-world social networks. An innovative heuristic method has been proposed to recognize community structure in real-world networks and to identify the most influential node within each community. The proposed concept on a recognized community network has been tested in order to validate it. This work introduced one new network metric, the Dependency factor which computes the influence of a node. Our results are compared with other existing approaches using real-life datasets. We have compared the dependency factor with other network centralities. The computational case study is done over a well-known Bengali novel, namely Chaar Adhyay written by Nobel laureate Rabindranath Tagore. The analytical results are more accurate than the state-of-the-art approaches. © 2023 IEEE.

关键词： Heuristic methods

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Novelty Encouraged Beam Clustering Search for Multi-Objective De Novo Diverse Drug Design

Novelty Encouraged Beam Clustering Search for Multi-Objectiv...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhao, Dengwei Tu, Shikui Xu, Lei Shanghai Jiao Tong University Department of Computer Science and Engineering China Guangdong Institute of Intelligence Science and Technology China

ISBN: (纸本)9798350386226

The generation of drug-like, high-quality molecules from scratch within the expansive chemical space is a significant challenge in drug discovery. In previous research, value-based reinforcement learning algorithms have been utilized to optimize multiple desired properties simultaneously. Randomness is injected into the decision-making process through ϵ-Greedy or stochastic sampling to enable the generation of a diverse ensemble of molecules, which usually encounters a trade-off between the optimality and diversity of these generated molecules. Moreover, novelty has not been explicitly addressed as an optimization objective, and the distinctiveness of generated molecules from the reference molecules is not guaranteed. In this paper, novelty-encouraged beam clustering (NeBC) search algorithm is proposed for de novo drug design. A clustering strategy is integrated with heuristic value-guided beam search to strike a balance between the optimality and diversity of the generated molecules. An intrinsic reward, which is measured by the disagreement of a group of experts trained on reference molecules, is proposed to encourage novelty explicitly. Experimental results demonstrate that NeBC search not only achieves a balanced trade-off between optimality and diversity but also effectively enhances the novelty of the generated molecules. The source code is publicly accessible on https://***/CMACH508/NeBC. © 2024 IEEE.

关键词： Drug discovery

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Enhancing Mobility with Next-Generation Partial Hand Prosthesis Using Arduino Uno and Flex Sensors 2

Enhancing Mobility with Next-Generation Partial Hand Prosthe...

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2nd International Conference on Cyber Physical Systems, Power Electronics and Electric Vehicles, ICPEEV 2024

作者： Matury, Sai Sathwik Sam Stewart, X. Ra, Nawin Kumba, Krishna School of Computer Science & Engineering Vellore Institute of Technology Chennai India School of Electrical Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350388664

The proposed work delves into the comprehensive design, development, and evaluation process of a 3D printed prosthetic arm, employing servo motors controlled by an Arduino Uno microcontroller to enable gesture mimicry through flex sensors integrated into a wearable glove. The primary objective is to provide an affordable and accessible solution for individuals with upper limb disabilities. The paper outlines the intricacies of the design process, system architecture, programming nuances, and rigorous testing procedures, showcasing promising results in terms of gesture accuracy, adaptability, and user-friendliness. The prosthetic arm demonstrates high precision in replicating various hand gestures. Future work will focus on enhancing the durability and responsiveness of the system to further improve its practical application. User feedback has been overwhelmingly positive, indicating significant potential for real-world adoption. © 2024 IEEE.

关键词： Servomotors

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