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2nd International Conference on data Science and Information System, ICdSIS 2024

作者： Monica, K.M. Parameswaran, T. Swapna, J. Prabu, S. Kaliappan, S. Vit University School Of Computer Science And Engineering Chennai India Cmr University Lakeside Campus School Of Engineering And Technology Department Of Computer Science And Engineering Bangalore India Veltech Rangarajan Dr.Sagunthala R&d Institute Of Science And Technology Department Of Computer Science And Engineering Tamilnadu Chennai India Mahendra Institute Of Technology Department Of Ece Namakkal India Lovely Professional University Division Of Research And Development Punjab Phagwara India

ISBN: (纸本)9798350381665

Cloud computing has fundamentally transformed the accessibility and payment models of services within distributed system environments. In response to heightened security concerns, cloud service providers offer diverse resources spanning Infrastructure, Software, Platform, and database services, supported by security measures such as Service Level Agreements (SLAs), access control rules, and cryptographic methods. This paper introduces a novel data encryption technique, termed data Security in Cloud Computing using Maritime Search and rescue Algorithm (dSCC-MSrA). By integrating an enhanced cypher block chaining algorithm with logical substitution and the Maritime Search and rescue Algorithm (MSrA) for key generation, this method provides a unique approach to encryption. Through rigorous optimization and analysis, it has undergone significant refinement, with comparisons against industry-standard algorithms showcasing its efficacy. The primary objective is to elevate encryption procedures and introduce complexity to cryptanalysis, ultimately enhancing data security in cloud computing. © 2024 IEEE.

关键词： Cryptography

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Influence of the design of Ti (C, N)-based cermets with alternative binders on their performance and wear in milling

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Wear 2025年

作者： Premkumar, Vikas B.K. Chalkiadakis, Evangelos M'Saoubi, rachid Bushlya, Volodymyr Production and Materials Engineering Lund University Ole Römers Väg 1F Box 118 Lund221 00 Sweden R&D Materials and Technology Development Seco Tools AB FagerstaSE-73782 Sweden

Ti (C, N) based cermet materials are predominantly used in continuous finishing applications of metal cutting due to their high hardness, excellent resistance to oxidation and high chemical stability. However, their application in interrupted cutting like milling are limited due to their brittle-like failure due to low fracture toughness. In this work, alternative binder systems such as Co-Ni and Ni are investigated to study their influence on the material properties followed by evaluating their performance in face milling of quench and tempered 42CrMo4 steels having a hardness of 35 HrC. The results show that as the concentration of Ni in the binder increases, the hardness (HV) decreases and the Palmqvist fracture toughness (K1C) increases. This trend is more pronounced in the binder containing pure Ni. Thus, Ni helps in transforming the nature of a brittle-like cermet with Co binder to a tougher cermet with Co-Ni and pure Ni binder. Up-milling tests with coolant revealed that as-sintered cermet with pure Co and Co-Ni binder performed similarly while pure Ni binder showed premature failure. CVd coated cermet in as-deposited state shows a substantial improvement in performance of the Co-Ni binder compared to pure Co binder while Ni binder show rapid flaking of coating causing premature failure. Formation of comb cracks and parallel cracks networks followed by adhesion and impaction of steel in the cracks is observed as the main wear mechanism that causes rapid block isolation of the geometry leading to tool catastrophic failure. However, CVd coated Co-Ni binder system showed less adhesion in the crack networks which is speculated to be the reason for its improved performance. © 2025 The Authors

关键词： Cracks

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Optimal design of WET Etching Bath for 3d Flash Memories Using Multi-Objective Bayesian Optimization

Optimal Design of WET Etching Bath for 3D Flash Memories Usi...

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Joint e-Manufacturing and design Collaboration Symposium (eMdC) & International Symposium on Semiconductor Manufacturing (ISSM)

作者： Miyuki Kouda Yumi Mori Tomohiko Sugita Youyang Ng AI & System Research Center Frontier Technology R&D Institute KIOXIA Corporation Yokkaichi-shi Japan AI & System Research Center Frontier Technology R&D Institute KIOXIA Corporation Yokohama-shi Japan Advanced Memory Process Development Center Memory Division KIOXIA Corporation Yokkaichi-shi Japan

ISBN: (数字)9798331510589

ISBN: (纸本)9798331510596

In recent years, the complexity of semiconductor manufacturing processes has increased, leading to a growing need for the high-precision optimization of device structures. For example, in batch-type wet etching devices, the flow of chemical liquids within the process bath can vary depending on the device structure, causing variations in the etching state of the wafer. This issue is addressed using a feedback mechanism that iteratively adjusts the device structure based on the results of an etching experiment, thereby achieving more uniform etching conditions. However, this approach requires a large number of trial experiments. In the fabrication process of 3d flash memories, word-line formation in the silicon substrate requires precise control of the silicon concentration in the etching solution. However, this concentration can fluctuate due to the dissolution of the SiN film during the etching process. This fluctuation may cause various problems. This study introduces an innovative method utilizing multi-objective Bayesian optimization to derive optimal wet etching bath design parameters; this method is informed by image and physical-quantity data from fluid dynamics simulations [1]. This approach is validated through simulation experiments, whose results are used to identify the best possible wet etching bath designs effectively.

关键词： Wet etching Three-dimensional displays Fluid dynamics Semiconductor device manufacture Silicon Bayes methods Flash memories Optimization Silicon dioxide Substrates

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Physiological and molecular mechanisms of insect appendage regeneration

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Cell regeneration 2023年第1期12卷 351-362页

作者： Jiru Zhong Andi Jing Shaojuan Zheng Sheng Li Xiaoshuai Zhang Chonghua ren Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology Guangzhou Key Laboratory of Insect Development Regulation and Application ResearchInstitute of Insect Science and TechnologySchool of Life SciencesSouth China Normal UniversityGuangzhou 510631China Guangmeiyuan R&D Center Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied TechnologySouth China Normal UniversityMeizhou 514779China

regeneration,as a fascinating scientific field,refers to the ability of animals replacing lost tissue or body *** metazoan organisms have been reported with the regeneration phenomena,but showing evolutionarily variable *** the most diverse metazoan taxon,hundreds of insects show strong appendage regeneration *** regeneration process and ability are dependent on many factors,including macroscopic physiological conditions and microscopic molecular *** article reviews research progress on the physiological conditions and internal underlying mechanisms controlling appendage regeneration in insects.

关键词： Appendage regeneration Physiological condition Molecular mechanism Signaling pathways Epigenetics Insects

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Gain Penalty for Stability-Guaranteed reinforcement Learning via Small Gain Theorem

Gain Penalty for Stability-Guaranteed Reinforcement Learning...

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SICE Annual Conference

作者： Nobuyuki Yoshikawa ryoichi Takase Information Technology R&D Lab. Mitsubishi Electric Kanagawa Japan Research & Development Group Hitachi Ltd Tokyo Japan

The gain penalty method is investigated to ensure the stability of the closed-loop system consisting of a neural network controller and a target plant. The gain penalty is defined to constrain the L 2 gain of the closed-loop system in order to satisfy the small-gain theorem. To apply the gain penalty method for the target plant which do not have finite L 2 gain, the imaginary feedback gain is introduced to be the plant that has a finite L 2 gain. Numerical experiments are performed on two types of linear time-invariant (LTI) systems to investigate the property of the proposed methods in terms of learning efficiency.

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Gas anomaly data detection based on hybrid neural network 7

Gas anomaly data detection based on hybrid neural network

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2022 7th International Conference on Electronic technology and Information Science, ICETIS 2022

作者： Li, Xiaolong Xu, Junwu Liao, Jiayin Wang, Chaoqun Chen, Xiaohui Li, Fang School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Product Development Department Shanghai Academy of Spaceflight Technology Shanghai China Gas Intelligent Application Technology R&D Center Shanghai Aerospace Energy Co. Ltd Shanghai China

ISBN: (纸本)9783800757794

The accurate measurement of gas flow is directly related to the economic benefits and social interests of gas enterprises. Moreover, as a kind of time-series data, there is a serious imbalance in the distribution of positive and negative samples in the data, which leads to low accuracy and difficulty in detecting gas anomaly data. To address these problems, a cost-sensitive hybrid network model is proposed in this paper. The model combines the stronger local feature learning ability of CNN network and the better sequence feature learning ability of GrU network, and then introduces a cost-sensitive loss function to solve the problem of inaccurate classification accuracy due to skewed data distribution. The experimental results show that using this model can find the outliers in the measurement data more accurately, which has some reference significance for the accurate measurement of traffic. © VdE VErLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Flow of gases

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Implementation of Precision Education System Based on Machine Learning Model 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Shanmugasundar, G. Chohan, Jasgurpreet Singh Kalita, Kanak Department of Mechanical Engineering Sri Sai Ram Institute of Technology Chennai600044 India Department of Mechanical Engineering and University Center for Research & Development Chandigarh University Mohali140413 India Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi600062 India Jadara University Research Center Jadara University Irbid21110 Jordan

ISBN: (数字)9783031733185

ISBN: (纸本)9783031733178

Precision Education (PE) is an approach that emphasizes the use of various forms of technology to personalize students’ educational opportunities according to their unique requirements. In order to facilitate effective learning that is suited to the needs of each individual, it is necessary to have complete information about the learning process. PE describes a personalized approach to classroom instruction. We propose dignified reinforcement Learning (drL) which includes all the essential elements required for PE, in order to determine the impact of developing multimodal innovations on individualized learning. The system aims to address issues with the standard model of education analysis, such as insufficient internal validity, predictive validity, timeliness, comparability, and understandability, in order to provide more precise instruction. Networking sites, the digital classroom, the intelligent agent, and the panel are the four fundamental aspects of an rL-based technology. Through model-based rL, the head attribute of the continuous educational environment gathers and processes a multimodal flow of student records from the various modules to create laws of appropriate behaviors that optimize the long-term benefits for both the individual and the computer. To demonstrate the usefulness of the proposed model, experimental evidence was presented using a subset of multimodal data. Practical and theoretical implications for future digital learning approaches and investigations may be drawn from rL systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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development of Python-Based Applications for Virtual Instrument Control Using PyQt5, PyVISA, and SCPI Protocol

Development of Python-Based Applications for Virtual Instrum...

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Emerging Trends in Information technology and Engineering (ic-ETITE), Conference on

作者： Abhishek Singh rao deepak Sai Anita Taterao Mahajan Vaibhav Pratap Singh rahul Neiwal Haribabu Pasupuleti Sudarsan S d Internet of Things (IoT) Group Centre for Development of Advanced Computing Bangalore Bengaluru India R&D in IT Group Ministry of Electronics and Information Technology Delhi India Centre for Development of Advanced Computing Bangalore Bengaluru India

This work aims to create desktop applications to enable virtual access and control to prominent lab equipment like signal generators, oscilloscopes, spectrum analyzers, etc. The developed applications utilize PyQt5 and PyVISA Python libraries, enabling the creation of Graphical User Interfaces (GUIs) and virtual instrument communication. The applications support USB and Ethernet connection between the PC and the instruments. We demonstrate Python-enabled applications to remotely access a Vector Signal Generator, an Oscilloscope and in conjugation, also use an OEM's Spectrum Analyzer PC application to complete a framework for remote signal generation, analysis, and acquisition which can be useful in various research and testing scenarios in the modern hybrid work culture.

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Comprehensive Study on the Slat Noise of 30P30N High-Lift Airfoil Basd on High-Order Wall-resolved Large-Eddy Simulation

arXiv

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arXiv 2024年

作者： Zhang, Keli Lin, Shizhi Liu, Peiqing Liu, Shihao Liu, Kai Beihang University Beijing100191 China Rankyee Technology Beijing Beijing100097 China School of Aeronautic Science and Engineering China Solver R&D and Development Center CTO

This study presents wall-resolved large-eddy simulations (WrLES) of a high-lift airfoil, based on high-order flux reconstruction (Fr) commercial software dimaxer, which runs on consumer level GPUs. A series of independence tests are conducted, including various Ffowcs Williams-Hawkings sampling surfaces, different mesh densities, simulations at 4tℎ and 5tℎ order accuracies, and varying spanwise lengths, to establish best practice for predicting slat noise through high-order WrLES. The results show excellent agreement with experimental data while requiring significantly fewer computational resources than traditional second-order methods. An investigation on the effects of reynolds number (re) is performed by scaling the airfoil size, with reynolds numbers ranging from 8.55 × 105 to a real aircraft level of 1.71 × 107. By applying simple scaling through Strouhal number (St), spanwise correction, and distance from the receiver, the far-field noise spectra for different reynolds numbers can be coincided. Additionally, simulations are performed at four angles of attack: 3◦, 5.5◦, 9.5◦, and 14◦. The results indicate that higher angles of attack lead to a less intense feedback loop, resulting in lower tonal noise frequencies and reduced noise amplitude. The maximum noise reduction observed is over 14dB when comparing 14◦ to 3◦. Furthermore, an improved formula is proposed to enhance the prediction of slat noise tonal frequencies and to better elucidate the mechanism behind tonal noise generation. Copyright © 2024, The Authors. All rights reserved.

关键词： reynolds number

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Novel Gender and Age Prediction from real Time Facial Images using Linear regression Algorithm 8

Novel Gender and Age Prediction from Real Time Facial Images...

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8th International Conference on Electronics, Communication and Aerospace technology, ICECA 2024

作者： Nalini, N. Shahila, d. Ferlin deva rosi, A. Tamilselvi, M. Giri, Jayant Sherideh, Ala'a Al Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Saveetha University Saveetha School of Engineering Department of Ece Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University College of Information Technology Department of Cyber Security zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (纸本)9798350367904

The proposed novel algorithm utilizes linear regression in real-time facial image analysis for predicting both gender and age. By leveraging features extracted from facial data, the model aims to provide accurate and instantaneous predictions. The emergence of social media platforms has made the automatic classification of gender and age increasingly relevant. real-time frame processing is possible with OpenCV. The expected gender and age are provided as the output, and this frame is provided as the input. The capacity to autonomously ascertain age and gender from facial images because of its versatility in facial analysis applications. However, the current models are still behind the required accuracy level, which is required for these models to be used in real-world applications, because of the significant intraclass variance of face images (such as difference in lighting, position, scale, and occlusion). In this work, a deep learning framework uses an ensemble of residual and attentional convolutional networks to reliably determine the gender and age group of facial photographs. By employing an attention mechanism, this model can concentrate on the important and instructive aspects of the face, increasing its prediction accuracy to 90.15%. © 2024 IEEE.

关键词： Prediction models

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