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2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Pawan Dhiman, Rohtash Saini, Jasbir Singh Saxena, Ankur Sharma, Vikas Meerut Institute Of Engineering Technology Department Of Computer Science And Engineering Uttar Pradesh Meerut India Deenbandhu Chhotu Ram University Of Science And Technology Department Of Electrical Engineering Haryana Murthal India Panipat Institute Of Engineering And Technology Panipat Institute Of Engineering And Technology Haryana Samalkha India Delhi Technological University Department Of Information Technology Delhi India

ISBN: (纸本)9798350306446

Feature selection is a significant process in brain-computer interfaces (BCIs) that has the potential to significantly enhance system performance, especially if a large number of features are present. Feature selection can help decrease noisy data, overtraining effects, storage needs, and computational complexity thereby enhancing classifier performance. The various feature selection strategies have been reported to attain these objectives. In this work, a hybrid feature selection technique is suggested. It uses a wavelet packet decomposition technique to extract features and grey wolf optimization (GWO) technique to obtain the best subset of features. It is then evaluated with support vector machine (SVM) classifier and obtains maximum classification accuracy of 82.88% for the approximate entropy feature. Experimental findings reveal that the suggested approach outperforms the contemporary MI-BCI systems even with relatively small training data sets. © 2024 IEEE.

关键词： Support vector machines

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GNSS/IμUWB-Based Train Integrity Monitoring Using Fuzzy Reasoning 4

GNSS/IμUWB-Based Train Integrity Monitoring Using Fuzzy Rea...

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4th IEEE International Conference on Power, Electronics and computer Applications, ICPECA 2024

作者： Zhong, Tianyu Liu, Jiang Cai, Baigen Wang, Jian School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer Science and Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350359589

Integrity of a train is a significant characteristic parameter towards a railway train control system in order to guarantee the railway operational safety. The decoupling event between a locomotive and a carriage or two adjacent carriages has become a serious threat for the following train operating along the same track. Conventional train integrity monitoring solutions based on state detection with specific sensors, like the Global Navigation Satellite System (GNSS) receiver and tail wind pressure unit, may not perform effectively and safely under constrained or difficult operation environments. This paper presents a Train Integrity Monitoring System (TIMS) architecture with integration of GNSS, Inertial Measurement Unit (IMU) and Ultra-wide Band (UWB) ranging technique. To realize the effective determination of the train integrity state with multiple detection channels, the fuzzy reasoning theory is adopted for decision-making. By using the simulated Head-of-Train (HoT) and End-of-Train (EoT) platforms, both the normal and decoupling scenarios are investigated through experiments. With the practically collected sensor datasets, the different single-sensor-based methods are compared with the presented fuzzy reasoning-based solution. The comparison results illustrate the advanced performance level under the given experimental conditions, which indicate great potentials of the presented solution in novel train control systems. © 2024 IEEE.

关键词： fuzzy reasoning Global Navigation Satellite System (GNSS) railway transportation sensor integration train integrity monitoring Ultra-wide Band

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Single-to-Multi Music Track Composition Using Interactive Chaotic Evolution 13th

Single-to-Multi Music Track Composition Using Interactive Ch...

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13th International Conference on Frontier Computing, FC 2023

作者： Hung, Ying Kai Pei, Yan Li, Jianqiang Graduate School of Computer Science and Engineering University of Aizu Fukushima Aizuwakamatsu965-8580 Japan Faculty of Information Technology Beijing University of Technology Beijing100124 China

ISBN: (纸本)9789819993413

This research presents a new music generation model and a novel MIDI data format for MIDI music generation. This innovative data format allows us to process MIDI music in a manner analogous to video analysis. Initially, the model employs Convolutional Neural Networks (CNN) as an encoder to effectively capture local and global features within the musical data. Subsequently, we utilize a Transformer as a decoder, leveraging its self-attention mechanism to handle the long-term dependencies present in music data. In the training process, an interactive chaotic algorithm is introduced to update the model’s weights, assisting the model in avoiding entrapment in local optima. This enhances the learning efficiency of the model and improves the quality of the generated output, enabling the model to generate music, including accompaniment, that aligns with human aesthetics from any given melody. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Music

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Leveraging AI for Enhanced Botnet Detection - A Review of Machine Learning Approach for Cybersecurity 3

Leveraging AI for Enhanced Botnet Detection - A Review of Ma...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Sonune, Harsha Kulkarni, Nilima Mksss's Cummins College of Engineering for Women Department of Information Technology Pune India Mitadt University Mitsoe Department of Computer Science and Engineering Maharashtra Pune India

ISBN: (纸本)9798350354348

Botnets represent a substantial threat to cybersecurity, enabling malicious actors to execute large-scale attacks that compromise network integrity and data confidentiality. Current detection methods often fall short in addressing the rapidly evolving strategies employed by botnets. This study has an aim of designing and developing a sophisticated botnet detection system leveraging artificial intelligence (AI) techniques. By integrating machine learning algorithms and advanced data analysis methods, the proposed system seeks to accurately identify and mitigate botnet activities in real-time. The study will evaluate the effectiveness of various AI models in detecting botnet traffic, provide a comparative analysis of their performance, and propose an optimal framework for implementation in cybersecurity infrastructures. © 2024 IEEE.

关键词： Bot (Internet)

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Research on multimodal relation extraction method based on contrast learning 3

Research on multimodal relation extraction method based on c...

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3rd International Conference on Electronic information engineering, Big Data, and computer technology, EIBDCT 2024

作者： Zhao, Jingsheng Ni, Qihui Yan, Shuai Zhu, Qiaoming School of Information and Control Engineering Qingdao University of Technology Qingdao Shandong266000 China School of Computer Science and Technology Suzhou University Suzhou Jiangsu215006 China

ISBN: (纸本)9781510680449

Traditional relation extraction methods are usually based on single text data, and other modality information such as image and video can improve the effect of text relation extraction. Aiming at the problem of heterogeneity between multi-modal data, a multi-modal relation extraction model MRECL based on contrastive learning is constructed. Firstly, the feature representation of image and text is obtained through ViT and BERT models;secondly, contrastive learning is introduced to align image-text features to reduce modality heterogeneity in advance;then image is used as prefix guidance information, and multi-modal interaction fusion is carried out with text information through attention mechanism;finally, the probability of all relation classification is calculated through Softmax layer and the prediction relation is output. Experimental results show that the precision, recall, and F1 values of MRECL on the MNRE dataset reach 83.23%, 82.19%, and 82.70%, respectively, achieving better performance than the current SOTA model. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image enhancement

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Application of a class of density peak clustering algorithm in short-term smart grid 8

Application of a class of density peak clustering algorithm ...

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Wang, Chenyu Zhang, Zhao Zhu, Zhipeng Zhou, Hongyan School of Computer Science and Software Engineering University of Science and Technology Liaoning 185 Qianshanzhong Road Liaoning Anshan114051 China School of Electronic and Information Engineering University of Science and Technology Liaoning 185 Qianshanzhong Road Liaoning Anshan114051 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

The classification of short-term power load data by clustering algorithm can lay a good foundation for the subsequent power load forecasting work and provide a more efficient, safe and reliable direction for the operation of power system. Density peaks clustering algorithm with k-nearest neighbors and weighted similarity can reduce the negative impact of global data on local data, avoid the collateral effect of errors and improve the accuracy of the model. It has better effect on local peak power change and global power forecast. In this paper, the density peaks clustering algorithm with k-nearest neighbors and weighted similarity are compared with DPC clustering method through simulation examples, and the effectiveness of this method is verified. © 2024 SPIE.

关键词： Clustering algorithms

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Mechanical characterization of extruded sisal-polypropylene composites with optimized compounding parameters

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Interactions 2024年第1期245卷 1-17页

作者： Khawale, Vijay Ramrao Jadhav, Varsha D. Satishkumar, P. Vijayan, D.S. Saminathan, Rajasekaran Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Maharashtra Wanadongri India Department of Artificial Intelligence and Data Science Vishwakarma Institute of Information Technology Maharashtra Pune India Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore India Tamilnadu Chennai India Department of Mechanical Engineering College of Engineering and Computer Science Jazan University Jazan Saudi Arabia

This study aims to optimize the mechanical characteristics of Sisal-polypropylene composites by investigating the impact of varying the compounding factors on these qualities. These parameters include fiber feeding location, barrel temperature, and fiber content. A capillary rheometer was used to track the changes in viscosity of the mixed compounds in relation to shear rate and temperature. Blends were tested at predetermined shear rates using a Couette shear rate theory–based extruder screw speed chart. In order to determine how each processing variable affected the mechanical characteristics of the composites, an analysis of variance (ANOVA) was conducted, and experimental designs were based on Taguchi’s optimization method. The optimization study revealed that, in addition to barrel temperature, the mechanical characteristics of the specimens were highly influenced by fiber content and feeding position inside the extruder. Compounds containing 40 wt % fiber, when treated at 180 ºC and fed into the extruder’s melt zone, had an average modulus value of 7 GPa and a strength value of 48 MPa. The viscosity measurements show minimal variations at shear speeds above 1850 s− 1, making it suitable for analyzing these substances. The scanning electron micrographs (SEM) reveal that the fibers were coated uniformly with polymer, and there was some seepage through the core, resulting in twofold shear effect. The optimal screw speeds for the blends studied here ranged from 75 to 220 rpm when using the present extruder (Do/Di = 1.3 and shear rates 1850 s− 1 to 4750 s− 1). © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Polypropylenes

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Biometric Web based Vote Cast using Blocks 3

Biometric Web based Vote Cast using Blocks

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Abinaya, M. Priya, P.Kaviya Mirza, Mohsina Anbumani, A. Sathya, R. Sethuram, M. Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India P.A College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Global College of Engineering and Technology Department of Electrical and Electronic Engineering India Paavai College of Engineering Department of Computer Science and Engineering Coimbatore India Kongunadu College of Engineering and Technology Department of Information Technology Trichy India Hindusthan College of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350343632

Web based vote casting is a form of voting in which the voter is able to cast their votes through any web portal wherever in the world. In the Biometric method, voter can cast the votes using their finger impression. In this method the voter can selects the login portal which is particularly designed for an election commission. Each person needs to register the election commission website, using the registration details substantiate themselves before the machine authorize the user to sight the ballot visible on the screen. The voter is then allowed to pick their selected candidate and then cast the votes which would be passed to the election server for the refining process. In 'E-Voting' method a voter can cast their votes through online without any difficulty. If all the entries provided by the user are precise user can login the system using the user ID and password voter can cast their votes through online wherever in the world. If an information given by the voter is not correct then the entry will be discarded and it shows the error message. This technique is mainly implemented to reduce the difficulty of the election commission and voter. It is a user-friendly approach, also it avoids the unwanted crowds during the election period. Here, this study has used immutable ledger technology that is a blockchain based application, which provides the security and also increase the efficiency of the voting process. © 2023 IEEE.

关键词： Blockchain Electronic Voting (E-Voting) Personnel computer (PC)

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Active Power Curtailment and Reactive Power Control in PV-Rich Low-Voltage Distribution Network 20

Active Power Curtailment and Reactive Power Control in PV-Ri...

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20th International Conference on the European Energy Market, EEM 2024

作者： Dubravac, Marina Topić, Danijel Fekete, Krešimir Šimić, Zvonimir Prenc, Rene Rojnić, Michele Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia University of Rijeka Faculty of Engineering Rijeka Croatia

ISBN: (纸本)9798350381740

High PV systems integration faces distribution networks (DN) with technical issues. However, PVs are inverter- based sources and with active power curtailment (APC) and reactive power control (RPC) can provide ancillary services for distribution system operators (DSOs) and participate as problem/solution principle. This paper proposes an optimal power flow (OPF)-based model for improving voltages and reducing losses by using PV inverter APC and RPC strategies. The proposed optimization model is presented as nonlinear programming (NLP). For solving this optimization problem without approximations, a co-simulation of OpenDSS power system analysis software and PyGMO package with embedded computational intelligence (CI) optimization methods is used. Several case studies are carried out over the IEEE European low-voltage test feeder (LVTF). Regardless of which strategy is applied, the obtained results show that the proposed model improves technical conditions in PV-rich DN and illustrate PV potential in providing ancillary services to DSO. © 2024 IEEE.

关键词： Power distribution networks

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Saline Infusion Monitoring and Control System Using IoT 2

Saline Infusion Monitoring and Control System Using IoT

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2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Ranjani, J. Hariharan, Shanmugasundaram Jeyashree, Anupama Aishwarya, E. Sri Sairam Engineering College Department of Information Technology Chennai India Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350347456

The use of technology in healthcare is becoming increasingly common with the growth of population and advancements in technology. The healthcare industry is integrating engineering principles to create automated systems instead of manual labor. So, we have proposed an IoT-based saline infusion monitoring system which can greatly improve patient safety by continuously monitoring the saline level using a level sensor and alerting healthcare providers if it falls below 10%. The system includes sensors to monitor the patient's blood pressure and heart rate, and a connection module for remote monitoring to send the alert notifications. The system stops the flow of saline if the level is low, ensuring that the patient's vein is not damaged. This system can significantly improve patient care and minimize the need for monitoring and management. © 2023 IEEE.

关键词： Blood pressure

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