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High-Speed Secure Vanity Address Generator for User Convenience in Blockchain Networks 5

High-Speed Secure Vanity Address Generator for User Convenie...

引用

5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Islam, Md. Mainul Islam, Md. Kamrul Hammoudeh, Mohammad Texas A&M University Dept. of Computer Science and Engineering College Station United States Shahjalal University of Science and Technology Dept. of Electrical and Electronic Engineering Sylhet Bangladesh King Fahd University of Petroleum and Minerals Dept. of Information and Computer Science Dhahran Saudi Arabia

ISBN: (纸本)9798350339239

Generating a vanity address (VA) for user convenience in blockchain networks is a memoryless brute-force exercise that involves testing millions of probable private keys. It requires a high-speed processor to compute millions of public keys and corresponding addresses in a short time. In this paper, we propose a novel split-key-multiplicative online VA generator for crypto wallet that provides faster VA generation compared with the existing vanity pools. The proposed approach is capable of improving the speed (in keys per second) of conventional VA generation by 2-7 times without reconfiguring the processor. We also propose a high-speed offline VA generator that offers blockchain users the ability to create a VA with a random vanity word using a low-performance processor without reliance on a vanity pool. To the best of our knowledge, this is the first research paper on VA generation in blockchain networks. © 2023 IEEE.

关键词： Blockchain

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Power Quality Problems that Occur at a Company Producing Electrical Equipment

Power Quality Problems that Occur at a Company Producing Ele...

引用

2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Petre-Marian Nicolae, Ileana-Diana Nicolae, Marian-Stefan University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania University of Craiova Computer Science and Information Technology Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper presents the problems that arise when supplying a company producing electrical equipment from the electricity network. The distorting regimes that appear affect the operation of the electric power network, inducing new problems of functional nature. For their study, the authors designed and implemented a data acquisition system in order to acquire, record and transmit data on electrical quantities (three-phase voltages and currents) from the secondary winding of the transformer that supplies the company. Data were transferred to a PC running original software developed by authors, implementing analysis modules based on Fast Fourier Transform and Wavelet Packet Transform. Small differences were revealed between power quality indices computed with both methods. The performed analysis revealed significant distortions of the currents absorbed by the analyzed plant. The total current harmonic distortion and weights of the 5-th harmonic exceeded the limits stated by IEEE Std 519-2022 whilst the value of the power factor was lower than the neutral value, being associated to additional consumptions of power / reactive energy, with effect on the penalties to be paid by the company. © 2023 IEEE.

关键词： Fast Fourier transforms

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Advancing Low Resource Natural Language Processing: Techniques, Applications, and Future Directions 2

Advancing Low Resource Natural Language Processing: Techniqu...

引用

2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Middha, Parth Agarwal, Harshit Rajput, Vaibhav Thakur, Ayush Singh, Sofia Saraswat, Shipra Amity University Dept. of Computer Science & Engineering Noida India Amity Institute of Information Technology Amity University Noida India Amity University Dept. of Artificial Intelligence Noida India

ISBN: (纸本)9798331519056

This paper explores the development and application of low resource Natural Language Processing (NLP) modules, addressing the challenges of processing underrepresented languages and domains with limited linguistic resources. It discusses key methodologies such as transfer learning, unsupervised and semi-supervised learning, and data augmentation techniques that enable effective NLP in resource-constrained environments. The paper presents case studies in machine translation, named entity recognition, and sentiment analysis, demonstrating the practical impact of these approaches. Additionally, it outlines persistent challenges in the field and proposes future research directions, emphasizing the importance of enhancing data acces-sibility, model robustness, computational efficiency, and ethical considerations in advancing low resource NLP. © 2024 IEEE.

关键词： Self-supervised learning

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About Measurement System in Stations and Substations using Original Data Acquisition Systems

About Measurement System in Stations and Substations using O...

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2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Ileana-Diana Nicolae, Petre n Marian Nicolae, Marian-Stefan University of Craiova Computer Science and Information Technology Dept. Craiova Romania University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper deals with a method and measurement system designed for the simultaneous monitoring and recording of time variations of electric quantities with no inter-correlation requirements. The method and measurement system were obtained by realizing a multi-unit data acquisition system (MUDAS), relying on at most 3 independent data acquisition systems which operate jointly, in a synchronous way, by means of a synchronizer. Because each of the individual data acquisition system can acquire data for at most 8 electrical quantities (4 voltages and 4 currents), the maximum total number of electrical quantities to be monitored, acquired, and transferred simultaneously to a central control unit is equal to 24. The sampling rate allows for the determination of power quality parameters according to existing standards. MUDAS can also be used in a structure with only 2 individual data acquisition system, in order to simultaneously acquire and display at most 16 electrical quantities. Two examples of utilization of MUDAS are presented. © 2023 IEEE.

关键词： Data acquisition

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Computing and Analysing PQ Indices for a Consumer with Various Sources of Harmonics and Non-symmetries

Computing and Analysing PQ Indices for a Consumer with Vario...

引用

2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Ileana - Diana Nicolae, Petre - Marian Cirstea, Daniel-Nicolae University of Craiova Computer Science and Information Technology Dept. Craiova Romania University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper presents a detailed analysis of certain operating regimes that appear for a consumer with various sources of harmonics and non-symmetries. The analyzed waveforms were acquired with a portable dedicated data acquisition system and transferred to a laptop for processing with Fast Fourier Transform (FFT) and Wavelet Packed Transform (WPT). Small differences (FFT vs WPT) were noticed between the computed values of the power quality indices, due to the non-sinusoidal and sometimes non-symmetric nature of the studied regimes and discrete nature of the processed data respectively. The FFT analysis revealed significant non-symmetrical regimes, as great weights for harmonic orders multiple of 3 were found in the three-phase currents waveforms. Reversed flow of active and reactive powers were noticed. A comparative study of the energies produced by current harmonics was made and discussed. A non-symmetry of the consumer as a whole was detected as well. © 2023 IEEE.

关键词： Fast Fourier transforms

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Development and Realization of Software Application for Syntax Checking of Karakalpak Language Text 3

Development and Realization of Software Application for Synt...

引用

3rd IEEE International Conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Saidov, Bobur R. Barakhnin, Vladimir B. Sharipov, Elbek J. Maksetbaev, Akilbek B. Ruzimov, Javokhir O. Abdullayev, Ruslan M. Novosibirsk State University Dept. of Mechanics and mathematics Novosibirsk Russia Novosibirsk State University It Department Novosibirsk Russia Federal Research Center for Information and Computational Technologies Novosibirsk Russia University of Information Technologies in Tashkent Dept. of Computer Engineering Tashkent Uzbekistan

ISBN: (纸本)9798331516321

This scientific work focuses on developing a software application to check the syntax of texts in the Karakalpak language. With the growing accessibility of the Internet in Karakalpakstan, this tool serves native speakers and learners alike, benefiting various fields. The study aims to design and implement a syntactic analysis application, centering on the parsing of Karakalpak texts. A comprehensive database of 31,243 words from the modern Karakalpak literary language was created to support this analysis. The application can evaluate both simple and complex sentences across genres, including scientific, newspaper, and fiction texts. Utilizing Python, a script for syntactic analysis was developed, and a website was created to facilitate user access. A simple and easy-to-use interface has been developed for users. Additionally, a comparative analysis of Turkic languages was conducted, with results presented in a table format. The algorithm developed is versatile and can also be adapted for use with Uzbek, Kazakh, and Tatar languages. © 2024 IEEE.

关键词： Application programs

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Energy Efficient Coverage Optimization in Mobile Wireless Sensor Network Using Grey Wolf Algorithm 14

Energy Efficient Coverage Optimization in Mobile Wireless Se...

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

作者： Gupta, Ankit Mamatha, K.M. Kiran, M. National Institute of Technology Karnataka Dept. of Information Technology Surathkal India Viseveshvaraya Technological University Dept. of Computer Science and Engineering Belgaum India

ISBN: (纸本)9798350335095

The issue of decreased coverage rate in Mobile Wireless Sensor Networks (MWSNs), caused by mobile sensor nodes being randomly placed inside a monitoring area. Additionally, it becomes extremely important to utilise a sensor node's energy very effectively due to the finite energy of sensor nodes. Hence, to provide optimised positions for the sensor nodes while using the energy of sensor nodes adept.y authors propose an energy efficient coverage algorithm. Initially, article focus on optimal placement of the sensor nodes within a area to achieve the maximum coverage and later authors have focused on improvising the network lifetime. Article presents a combination of Grey Wolf Optimization and Virtual Force algorithm for optimization of coverage in MWSN. Further, to improve the network lifetime, a GWO-based clustering algorithm is presented using distance and energy as a parameter. The algorithms are implemented and simulated on Matlab. The efficiency of the presented algorithm is observed comparing with other Swarm Intelligence (SI) based optimization algorithms, like GWO, VFA, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant-lion Optimization (ALO) and the results of the GWO-based clustering is compared with the traditional LEACH algorithm and energy-balanced clustering based on PSO. Simulation results demonstrate that the presented algorithms outperform the considered algorithms. © 2023 IEEE.

关键词： Sensor nodes

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Generalised Active Learning With Annotation Quality Selection 33

Generalised Active Learning With Annotation Quality Selectio...

引用

33rd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2023

作者： Lindqvist, Jakob Olmin, Amanda Svensson, Lennart Lindsten, Fredrik Chalmers University of Technology Dept. of Electrical Engineering Gothenburg Sweden Linköping University Dept. of Computer and Information Science Linköping Sweden

ISBN: (纸本)9798350324112

In this paper we promote a general formulation of active learning (AL), wherein the typically binary decision to annotate a point or not is extended to selecting the qualities with which the points should be annotated. By linking the annotation quality to the cost of acquiring the label, we can trade a lower quality for a larger set of training samples, which may improve learning for the same annotation cost. To investigate this AL formulation, we introduce a concrete criterion, based on the mutual information (MI) between model parameters and noisy labels, for selecting annotation qualities for the entire dataset, before any labels are acquired. We illustrate the usefulness of our formulation with examples for both classification and regression and find that MI is a good candidate for a criterion, but its complexity limits its usefulness. © 2023 IEEE.

关键词： computer vision

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3D-CAN: A 3D Convolution Attention Network for Feature Extraction and Classification of Hyperspectral Images

3D-CAN: A 3D Convolution Attention Network for Feature Extra...

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2023 IEEE International Conference on Network, Multimedia and information Technology, NMITCON 2023

作者： Kanthi, Murali Rao, K. Venkateshwara Sekhar Reddy, L. Chandra Sarma, T. Hitendra Bhaskar, Nuthanakanti Vasundhara, Nam Telangana Hyderabad India Cmr College of Engineering and Technology Dept. of Computer Science and Engineering Telangana Hyderabad India Telangana Hyderabad India Vasavi College of Engineering Dept. of Information Technology Telangana Hyderabad India Cmr Technical Campus Dept. of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350300826

In recent years, the deep learning method has gained widespread popularity in hyperspectral image classification (HSI) tasks because of remarkable feature extraction capability. However, conventional deep learning approaches often yield suboptimal classification performance due to the limited discrimination ability of the extracted features. Moreover, the challenge of obtaining high classification performance with a limited number of samples in hyperspectral images (HSIs) has emerged as a prominent research area of interest. To address this concern, this letter provides a novel 3D convolution attention network (3D-CAN) for feature extraction and HSIs classification. The attention mechanism employed in this context enables capturing both the long-range spatial dependencies of HSIs in the horizontal and vertical directions and the varying significance levels across distinct spectral channels. The experiments are executed on both the new data sets and the publicly accessible benchmark data sets to expose the efficiency and durability of the proposed model. Empirically, it has been demonstrated that the presented model succeeds over the remaining state-of-the-art approaches in terms of classification accuracy. © 2023 IEEE.

关键词： Convolution

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Human Activity Recognition in Free Living Using a Wearable Sensor: A Two-Stage Approach 12

Human Activity Recognition in Free Living Using a Wearable S...

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12th International Conference on Awareness science and Technology, iCAST 2023

作者： Li, Tianhui Zhou, Xue Kokubun, Kota Chen, Wenxi Division of Information System The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9798350324693

A novel two-stage approach for human activity recognition (HAR) using a wearable sensor is proposed in this study. The goal is to achieve both coarse-level and fine-level recognition of activities. The study focuses on five common activities: desk-working, driving, walking, downstairs, and upstairs. Three-axis acceleration signals were collected using a wrist-worn accelerometer sensor, and the activities were annotated during the participant’s daily routines. The acceleration data were preprocessed through segmentation, feature extraction, and normalization. In the first s tage, a t raditional m achine learning model (decision tree) was used for coarse-level classification, distinguishing between activities with exercise and without exercise. In the second stage, deep learning models were employed for fine-level classification to recognize specific activities within the coarse classes. The performance of the models was evaluated using accuracy, sensitivity, and specificity. T he p roposed approach showed promising results with accuracies of 93.53%, 93.52%, 85.70%, 98.11%, and 85.91% respectively for desk-working, driving, walking, downstairs, and upstairs, demonstrating the effectiveness of the two-stage strategy for HAR. The proposed two-stage approach outperforms the one-stage method (decision tree classifier a nd d eep l earning m odel), p articularly i n imbalanced data, achieving a graceful equilibrium between sensitivity and specificity. T he s tudy h ighlights t he i mportance o f considering the complexity and variability of daily activities for accurate classification a nd r esource optimization. © 2023 IEEE.

关键词： Wearable sensors

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