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Rock Mechanics Bulletin 2025年第1期4卷 29-52页

作者： Yewuhalashet Fissha Prashanth Ragam Hajime Ikeda N.Kushal Kumar Tsuyoshi Adachi P.S.Paul Youhei Kawamura Department of Geosciences Geotechnologyand Materials Engineering for ResourcesGraduate School of International Resource SciencesAkita UniversityAkita010-8502Japan Department of Mining Engineering Aksum UniversityAksum7080TigrayEthiopia School of Computer Science and Engineering VIT-AP UniversityAmaravatiAndhra PradeshIndia Department of Systems Controland Information EngineeringNational Institute of TechnologyAsahikawa College2-2-1-6 Syunkodai Asahikawa city Hokkaido071-8142Japan Department of Mining Engineering Indian Institute of Technology(Indian School of Mines)Dhanbad826004India Faculty of Engineering Hokkaido UniversityKita 8Nishi 5Kita-KuSapporo0608628Japan

The vibrations generated by rock blasting are a serious and hazardous outcome of these activities,causing harmful effects on the surrounding environment as well as the nearby *** the local ecology and human communities suffer from the consequences of these *** the severity of blasting vibrations necessitates a thorough evaluation of Peak Particle Velocity(PPV)and frequency,which are essential parameters for measuring vibration *** prediction of vibration occurrence is critically ***,this study employs five machine learning models for predicting the PPV and frequency resulting from quarry *** work compares five machine learning models(XGBoost,Catboost,Bagging,Gradient Boosting,and Random Forest Regression)to choose the most efficient performance *** performance evaluation of each five machine learning models demonstrates each model achieved a performance of more than 0.90 during the testing phase,there was a strong correlation observed between the actual and the predicted *** analysis of performance metrics shows Catboost regression model demonstrate better performance prediction comparing with the other models with R^(2)=0.983,MSE=0.000078,RMSE=0.008,NRMSE=0.019,MAD=0.004,MAPE=35.197 in the PPV prediction,and R^(2)=0.975,MSE=0.000243,RMSE=0.015,NRMSE=0.031,MAD=0.008,MAPE=37.281 for the frequency *** study will help mining engineers and blasting experts to select the best machine learning model and its hyperparameters in estimating ground vibration,and *** the context of the mining and civil industry,the application of this study offers significant potential for enhancing safety protocols and optimizing operational *** employing machine learning models,this research aims to accurately predict and assess ground vibrations with frequency resulting from rock blasting.

关键词： PPV Frequency Machine learning Blasting Regression Catboost XGboost

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A Communication-Induced Checkpointing Algorithm for Consistent-Transaction in Distributed Database systems 1

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8th International Symposium on Security in Computing and Communications, SSCC 2020

作者： Mansouri, Houssem Pathan, Al-Sakib Khan Laboratory of Networks and Distributed Systems Computer Science Department Faculty of Sciences Ferhat Abbas Setif University 1 Setif Algeria Department of Computer Science and Engineering Independent University Dhaka Bangladesh

ISBN: (数字)9789811604225

ISBN: (纸本)9789811604218

For better protection of distributed systems, two well-known techniques are: checkpointing and rollback recovery. While failure protection is often considered a separate issue, it is crucial for establishing better secure distributed systems. This article is dedicated to the proposal of a new checkpointing algorithm for saving a consistent-transaction state in distributed databases ensuring that database management systems are able, after a failure, to recover the state of the database. The proposed communication-induced algorithm does not hamper the normal transaction processing and saves a global consistent-transaction state that records only the fully completed transactions. Analysis and experimental results of our proposal show that the proposed scheme saves a minimum number of forced checkpoints and has some performance gains compared to the alternative approaches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Distributed database systems

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Intelligent Energy Management Energy Storage systems Using Machine Learning

Intelligent Energy Management Energy Storage Systems Using M...

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Intelligent systems for Cybersecurity (ISCS), International Conference on

作者： Chinnaraj Govindasamy T.R Nisha Dayana Siddhika Dilip Adkar D. Shyam Prakash A. Shilpa Gupta Sanjeev Kumar Trivedi Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu India Department of Computer Science Vels Institute of Science Technology and Advance Studies Chennai School of Computer Science Engineering and Applications D Y Patil International University Akurdi Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Department of Electrical and Electronics Engineering Aurora's Technological Research Institute Uppal Hyderabad Department of Electronics Faculty of Engineering and Technology Khwaja Moinuddin chishti Language University Lucknow

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

A nevertheless-emerging generation called cloud computing permits customers to pay for services on a usage-based foundation. Internet-primarily based IT offerings are supplied through cloud computing, at the same time as virtualization enables the availability of PC sources. The muse of cloud computing is the information center, which is made up of networked computers, cables, electricity components, and different components that host and shop corporate records. With cloud facts centers, high overall performance has continually been the most critical concern, yet it compromises strength utilization. The key hassle is to lessen power consumption at the same time as preserving provider nice and performance a good way to stability device performance and strength intake. A detailed grasp of strength use styles within the cloud environment is needed for our suggested technique. We look at power consumption tendencies and reveal how, through the use of the right optimization standards based on our strength intake models, we can keep more strength in cloud records facilities. All through the prediction section, tablet optimization, which has a 97 percent accuracy rate, permits this era to provide extra correct future price forecasts.

关键词： Performance evaluation Cloud computing Power demand Electricity Stability criteria Machine learning Load management

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Human-Aware Navigation in Crowded Environments Using Adaptive Proxemic Area and Group Detection

Human-Aware Navigation in Crowded Environments Using Adaptiv...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Carlos Medina-Sánchez Simon Janzon Matteo Zella Jesús Capitán Pedro J. Marrón Faculty of Business Administration and Economics Institute for Computer Science and Business Information Systems (ICB) University of Duisburg-Essen Essen Germany Faculty of Electrical Engineering and Computer Science University of Applied Sciences Niederrhein Krefeld Germany Department of System Engineering and Automation University of Seville Seville Spain

Navigation is an essential task for social robots. However, certain rules must be followed to allow them to move without causing distraction or discomfort to people. Considering that the context surrounding robots and persons affects the expected behavior, this work defines a social area around a person that adapts to the real situation. In addition, the social context of a person is extended to identify groups of people, which the robot should take into account while navigating. With this understanding of the surrounding of the robot together with the ability to predict the trajectory of individuals as well as groups, the proposed solution not only effectively addresses collision avoidance while promoting socially acceptable behavior but also outperforms the majority of recent works in terms of accuracy. Furthermore, a dedicated policy is introduced to react to social navigation conflicts. The evaluation performed in a simulated environment shows that the computation of our proposed solution is at least 8 times faster than the best state-of-the-art approach while preserving comparable social conduct. Also, the results of realistic experiments performed using Gazebo and a real robot are reported.

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The Effect of Data Augmentation on the Accuracy of Fish Species Classification Using Deep Learning

The Effect of Data Augmentation on the Accuracy of Fish Spec...

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International Conference on Informatics and Computing (ICIC)

作者： Ellya Helmud Catur Edi Widodo Oky Dwi Nurhayati Doctor Information System Postgraduate Diponegoro University Semarang Indonesia Faculty of Information Technology Information Systems Study Program Atma Luhur Institute of Science and Business Pangkalpinang Indonesia Physics Department Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Computer Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Fish image classification presents an intriguing challenge in the field of computer vision. This research aims to develop an accurate classification model to differentiate between four different fish species using a convolutional neural network. The dataset used consists of $\mathbf{3 0 1 0}$ fish images, divided into training, validation, and testing sets. The convolutional neural network model was trained both with and without data augmentation. Evaluation results show that the model trained with data augmentation achieved an accuracy of $95 \%$ with a loss value of 0.0983, slightly better than the model without augmentation which achieved an accuracy of $94.56 \%$ with a loss value of $\mathbf{0. 1 7 9 4}$. This indicates that data augmentation techniques are effective in improving model performance, likely because augmentation helps the model generalize better to variations in fish image data. The results of this research demonstrate the significant potential of convolutional neural network for fish image classification tasks. The developed model can serve as a foundation for the development of computer vision-based applications such as automatic fish species identification in fisheries or educational applications. Further research can be conducted by exploring different convolutional neural network architectures, more advanced data augmentation techniques, and larger datasets to improve model performance.

关键词： Deep learning Training Accuracy Computational modeling computer architecture Fish Data augmentation Data models Convolutional neural networks Image classification

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Distributed formation control of end-effector of mixed planar fully- and under-actuated manipulators

arXiv

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arXiv 2023年

作者： Peng, Zhiyu Jayawardhana, Bayu Xin, Xin School of Automation Southeast University Nanjing210096 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Faculty of Computer Science and Systems Engineering Okayama Prefectural University Okayama719-1197 Japan

This paper addresses the problem of end-effector formation control for a mixed group of two-link manipulators moving in a horizontal plane that comprises of fully-actuated manipulators and underactuated manipulators with only the second joint being actuated (referred to as the passive-active (PA) manipulators). The problem is solved by extending the distributed end-effector formation controller for the fully-actuated manipulator to the PA manipulator moving in a horizontal plane by using its integrability. This paper presents stability analysis of the closed-loop systems under a given necessary condition, and we prove that the manipulators’ end-effector converge to the desired formation shape. The proposed method is validated by simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： End effectors

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Implementation and Evaluation of 0.6 µm CMOS Complex RCPF for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2025年第1期145卷 25-37页

作者： Sato, Lina Fukagawa, Kanta Shouno, Kazuhiro Tanimoto, Hiroshi Muto, Cosy Moriyama, Seijiro Takahashi, Chikau Yoshino, Michitaka Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan Anagix Corporation 3-22-27 Numama Kanagawa Zushi249-0004 Japan Takamori Corporation Japan Research Center for Micro-Nano Technology Hosei University 3-11-15 Midori-cho Koganei Tokyo184-0003 Japan

This paper describes the implementation and evaluation of an RC polyphase filter (RCPF) and circuitry for measuring its frequency characteristics. The integrated circuit is fabricated on a 0.6 µm CMOS process and its supply voltage is 5 V. The integrated circuit includes a filter under test (FUT), a four-phase square wave generator, several analog switches and differential amplifiers to amplify the high-impedance signals of the RCPF. This FUT is a third-order complex RCPF whose passband is 8 − 40 MHz. This paper describes the design of these circuits in detail. This integrated circuit can select two measurement methods by means of external control signals. The first method uses a four-phase square wave. The frequency characteristics are measured by using an on-chip four-phase square wave generator driven by an external clock generator and by a spectrum analyzer tuned to the fundamental frequency. The second method uses an external network analyzer. Furthermore, this integrated circuit is equipped with a calibration circuit to measure the frequency characteristics of the circuitry except FUT by passing through the input / output signals of the FUT. As a result, the frequency characteristics of the FUT itself can be accurately measured. The effectiveness is confirmed through evaluation of the fabricated integrated circuit. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Differential amplifiers

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Development of a New Opto-Electrochemical Cell for Sensing Applications

Development of a New Opto-Electrochemical Cell for Sensing A...

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IEEE Sensors Applications Symposium, SAS

作者： João P. Mendes Luís C. C. Coelho José A. Ribeiro Centre for Applied Photonics INESCTEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Chemistry and Biochemistry CIQUP/IMS Faculty of Sciences of University of Porto Porto Portugal

ISBN: (数字)9798350369250

ISBN: (纸本)9798350369267

New systems with innovative design to perform measurements combining electrochemistry and surface plasmon resonance (ESPR) are currently a need to overcome the limitations of existent market solutions and expand the research possibilities of this technology. The main goal of this work was to develop a new cell to increase ESPR practical applications in several fields. To do so, a homemade SPR cell, fabricated by 3D-printing technology, was adapted for this purpose by incorporating the conventional 3-electrodes to perform the electrochemical experiments. The developed cell was fully compatible with commercial SPR substrates. After optimization of the homemade ESPR setup to perform the combined electrochemical and SPR measurements, two main applications were explored in this work. The first was the use of ESPR technology as straightforward tool to simultaneously investigate the electrical and optical properties of conducing/non-conducting polymers electrosynthetized on the SPR platforms. The conducting polymer poly(thionine) was used in this work for proof-of-concept. The second application envisaged the use of ESPR approach for simple electrodeposition ofmaterials with enhanced plasmonic properties for sensitivity enhancement of SPR biosensors. For validation of the concept, graphene oxide (GO) was electrochemically reduced on gold substrates aiming to evaluate the plasmonic properties of graphene-modified sensing surfaces.

关键词： Gold Biomedical optical imaging Sensitivity Microprocessors computer architecture Stability analysis Plastics

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Software Architecture Reconstruction for Microservice systems Using Static Analysis via GraalVM Native Image

Software Architecture Reconstruction for Microservice System...

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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Richard Hutcheson Austin Blanchard Noah Lambaria Jack Hale David Kozak Amr S. Abdelfattah Tomas Cerny Computer Science ECS Baylor University Waco United States Computer Science ECS Baylor University San Francisco California Faculty of Information Technology Brno University of Technology Brno Czech Republic Systems and Industrial Engineering University of Arizona Tucson Arizona

ISBN: (数字)9798350330663

ISBN: (纸本)9798350330670

Microservices are the mainstream architecture when designing cloud-native systems. The performance and elastic scalability of such systems are the main attraction for many vendors. Recent advancements improving microservice initialization times are related to the ahead-of-time compilation, which produces self-contained executables, significantly reducing load times. Despite recent advancements and various benefits of cloud-native systems, the evolution of such systems might be threatened by a missing system-centered view. Such a view would guide in a better contextual understanding of individual microservices and their dependencies from the holistic system perspective and aid developers in informed decisions to mitigate ripple effects. One way literature has addressed this gap is by performing Software Architecture Reconstruction (SAR), a process essential for understanding, maintaining, and evolving software systems. This paper questions whether instruments used to produce self-contained executables for microservices can be utilized for SAR, producing system-centered views. We propose a methodology for such a process, implement a proof of concept tool, MicroGraal, for the Java Platform, and assess it through a case study involving a third-party microservice system benchmark. We uncovered a system service dependency graph and a context map, comparing the approach and obtained results with source code analysis.

关键词： Software architecture Reviews Source coding Scalability Microservice architectures Static analysis Benchmark testing

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Speech-Gesture GAN: Gesture Generation for Robots and Embodied Agents

arXiv

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arXiv 2023年

作者： Liu, Carson Yu Mohammadi, Gelareh Song, Yang Johal, Wafa The Faculty of Engineering School of Computer Science and Engineering University of New South Wales SydneyNSW2052 Australia The Faculty of Engineering and Information Technology School of Computing & Information Systems University of Melbourne MelbourneVIC3010 Australia

Embodied agents, in the form of virtual agents or social robots, are rapidly becoming more widespread. In human-human interactions, humans use nonverbal behaviours to convey their attitudes, feelings, and intentions. Therefore, this capability is also required for embodied agents in order to enhance the quality and effectiveness of their interactions with humans. In this paper, we propose a novel framework that can generate sequences of joint angles from the speech text and speech audio utterances. Based on a conditional Generative Adversarial Network (GAN), our proposed neural network model learns the relationships between the co-speech gestures and both semantic and acoustic features from the speech input. In order to train our neural network model, we employ a public dataset containing co-speech gestures with corresponding speech audio utterances, which were captured from a single male native English speaker. The results from both objective and subjective evaluations demonstrate the efficacy of our gesture-generation framework for Robots and Embodied Agents. © 2023, CC BY.

关键词： Human robot interaction

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