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Emerging Research in Computational science (ICERCS), International Conference on

作者： Revathy Ganapathy Lingeshwaran D P. SuthanthiraDevi Harish Kumar M V Department of Computer Science and Engineering Vels Insitute of Science Technology and Advanced Studies Chennai India Department of Data Science and Business Systems SRM Institute of Science and Technology Chennai India

Offline Signature Authentication is a critical task in the field of document authentication, and its accuracy is essential for ensuring security while transactions. This research proposes two approaches: Initially Pre-trained CNN models are used to extract features from signature images, which are then combined with handcrafted features such as HOG and some other geometric features of signature. Such combined features are passed to bidirectional LSTM model in which drop out layer undergoes classification which differentiate real and forgery signature. The proposed system has potential applications in document authentication and security, subsequently combination of CNN models and additional features provides more comprehensive representation of signature images resulting in improved accuracy. Three signature datasets are utilized namely GDPS, CEDAR, and BHSig-Bengali each with varying signature styles and image quality. Our experimental outcomes reveal that Bidirectional Convolutional LSTM along with handcraft features attained maximum accuracy in offline signature verification system.

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A Study of Feature-Based and Pixel-Level Image Fusion Techniques 1

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3rd International Conference on Information Technology, InCITe 2023

作者： Kumar, Vivek Khanduja, Manisha Anandaram, Harishchander Joshi, Kapil Gupta, Ashulekha Diwakar, Manoj Department of Computer Science Uttaranchal Institute of Technology Uttaranchal University Dehradun India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun India Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Tamil Nadu Coimbatore India Department of Management Studies Uttarakhand Dehradun India Uttarakhand Dehradun India

ISBN: (数字)9789819959976

ISBN: (纸本)9789819959969

In order to offer a single, more precise representation of the display than any one of the original origin photographs, image fusion attempts to combine the original images of the same scenario. Symbol, feature, pixel and signal levels are only a few of the levels at which image fusion can be applied. The starting point for more image fusion approaches to the range of IF is pixel-level and feature based, and multi-scale decomposition multi-resolution image fusion is a significant area of image processing. In the research, we investigate different image fusion methods for the standard enhancement and performance evaluation of the merge image and get some relevant results. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Discrete wavelet transforms

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Efficiently Verifiable Quantum Advantage on Near-Term Analog Quantum Simulators

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PRX Quantum 2025年第1期6卷 010341-010341页

作者： Zhenning Liu Dhruv Devulapalli Dominik Hangleiter Yi-Kai Liu Alicia J. Kollár Alexey V. Gorshkov Andrew M. Childs Joint Center for Quantum Information and Computer Science NIST/University of Maryland College Park Maryland 20742 USA Joint Quantum Institute NIST/University of Maryland College Park Maryland 20742 USA Department of Computer Science University of Maryland College Park Maryland 20742 USA Simons Institute for the Theory of Computing University of California at Berkeley California 94720 USA Applied and Computational Mathematics Division National Institute of Standards and Technology (NIST) Gaithersburg Maryland 20899 USA Department of Physics University of Maryland College Park Maryland 20742 USA Institute for Advanced Computer Studies University of Maryland College Park Maryland 20742 USA

Existing schemes for demonstrating quantum computational advantage are subject to various practical restrictions, including the hardness of verification and challenges in experimental implementation. Meanwhile, analog quantum simulators have been realized in many experiments to study novel physics. In this work, we propose a quantum advantage protocol based on single-step Feynman-Kitaev verification of an analog quantum simulation, in which the verifier need only run an O(λ2)-time classical computation, and the prover need only prepare O(1) samples of a history state and perform O(λ2) single-qubit measurements, for a security parameter λ. We also propose a near-term feasible strategy for honest provers and discuss potential experimental realizations.

关键词： Quantum computers

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Embodied Visuomotor Representation

arXiv

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arXiv 2024年

作者： Burner, Levi Fermüller, Cornelia Aloimonos, Yiannis Department of Electrical and Computer Engineering University of Maryland College Park United States Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science University of Maryland College Park United States

Suppose you are at your desk looking at some objects on it. You don't know the precise distance from your eye to any particular object in meters. However, you can immediately reach out and touch any of them. Instead of the meter, your knowledge of distance is encoded in unknown but embodied units of action. In contrast, standard approaches in robotics assume calibration to the meter, so that separated vision and control processes can be interfaced. Consequently, robots are precisely manufactured and calibrated, resulting in expensive systems available in only a few configurations. In response, we propose Embodied Visuomotor Representation, a framework that allows distance to be measured by a robot's own actions and thus minimizes dependence on calibrated 3D sensors and physical models. Using it, we demonstrate that a robot without knowledge of its size, environmental scale, or its own strength can become capable of touching and clearing obstacles after several seconds of operation. Similarly, we demonstrate in simulation that an agent, without knowledge of its mass or strength, can jump a gap of unknown size after performing a few test oscillations. These experiments parallel bee and gerbil behavior, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Robots

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Preventing Order Inversion within Function-as-a-Service for Sensor Networks

Preventing Order Inversion within Function-as-a-Service for ...

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International Symposium on Object-Oriented Real-Time Distributed computing

作者： Takashi Ikegami Ichiro Satoh Tatsuo Nakajima SOKENDAI / National Institute of Informatics The Graduate University for Advanced Studies Tokyo Japan National Institute of Informatics Tokyo Japan Department of Computer Science and Engineering Waseda University Tokyo Japan

ISBN: (数字)9798350371284

ISBN: (纸本)9798350371291

Server-less architectures, specifically Function-as-a-Service (FaaS), are sometimes used for data processing in sensor networks. However, due to fluctuations in the start and completion times of FaaS tasks, the order can get reversed even when tasks are required to execute in sequence. As long as the start and end times of FaaS tasks are treated as delay fluctuated, it is not feasible to execute data processing as FaaS tasks. Therefore, this paper aims to clarify and formalize the conditions under which the execution order of periodic tasks by FaaS is maintained, assuming that fluctuations in the start and completion times of FaaS tasks can be predicted within a certain range. Furthermore, it presents a method to minimize the impact on data analysis when the completion of FaaS tasks is delayed beyond that predicted range. It is the first challenge that can provide the direction for future research on addressing the fluctuations.

关键词： Fluctuations Data analysis computer architecture Dynamic scheduling Real-time systems Delays Resource management

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Predicting the Soil Suitability using Machine Learning Techniques

Predicting the Soil Suitability using Machine Learning Techn...

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2021 IEEE International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications, CENTCON 2021

作者： Jayaraman, Vaishnavi Sridevi, S. Monica, K.M. Lakshminarayanan, Arun Raj B. S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vels Institute of Science Technology Advanced Studies Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665400176

Agriculture is a detracting sector in the global providence, which is defined as the practice of cultivating crops. Precision agriculture using machine learning algorithms is one of the fast-growing methodologies. It explores the usage of modern technologies to increase the crop yield rate by decreasing the utilization of fertilizers. The main aim of this study is to predict the soil suitability by utilizing the sensors and machine learning techniques. The temperature, humidity, pH and soil moisture were the main sources for plant growth. The nature of the soil would be identified, by measuring the above said entities. This paper analyses the soil suitability using diversified machine learning techniques such as KNN, Support Vector Machine, Random Forest, Naive Bayes, and Extreme Learning Machine. ELM model predicts the soil suitability with 99% of accuracy. © 2021 IEEE.

关键词： Precision agriculture

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Blockchain Based Digital Twins for Authorization and Remote Resource Sharing

Blockchain Based Digital Twins for Authorization and Remote ...

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International Conference on computing for Sustainable Global Development (INDIACom)

作者： V. Divya S. Arunarani U. Hemamalini A. Bharathi Department of Information Technology (BCA/IT) VELS Institute of Science Technology and Advanced Studies (VISTAS) Pallavaram Chennai Department of Computer Applications SRMIST Kattankullathur

Emerging trends namely big data, data science, block chain, digital twins, Internet of Things, Artificial Intelligence, Machine learning and Deep learning plays a significant role in all the domains. A digital twin is a computer program which uses the real data in order to predict or make decision about the performance of a process by creating simulations. Digital twins in block chain ensures transparency, decentralized storage, secure traceability, scalability and peer to peer communication in industry. Interoperability, authentication, distributed machine learning, decentralized decision making and robustness are few challenges in digital twins. Block chain technology is used for providing security and data history transparency. Therefore Digital twin's technologies are combined with block chain to transmit the data securely as well as to secure the interconnection among several devices. Recently, the significance of digital twin with the block chain technology is growing vastly. This technical combination provides supplementary competencies and enterprise use cases.

关键词： Scalability Ultra reliable low latency communication Blockchains Digital twins Resource management Internet of Things Security

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Real-Time Cold Chain Forecasting Model for Agricultural Logistic Transportation using Feature Centric Deep Neural Classification for Seasonal Recommendation

Real-Time Cold Chain Forecasting Model for Agricultural Logi...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： S. Priyanka A. Prema Department of Computer Science Vels Institute of Science Technology and Advanced Studies (VISTAS) Chennai India

ISBN: (纸本)9781665482721

In recent days, cold chain logistic progression has been affected due to covid quarantine because real-time human resources being affected. Agriculture transportation and food safety are essential for human lives to avoid wastage of product. Analyzing the stock hold management needs more prediction accuracy in the seasonal recommendations for producing Agri-products. Increasing information and collaborative approaches in big data leads to more dimensions to analyze the prediction leads to inaccuracy for a recommendation. To improve the cold chain process, intend a Real-time Cold chain forecasting model for agricultural logistic transportation using feature centric deep neural classification for a seasonal recommendation. Initially, the preprocess was carried out to reduce the noise present in the seasonal collective and cold chain logistic dataset, which contains information about agriculture in stock detail, production, seasonal, and daily requirement ratio. The cold chain recommendation big data analytics estimate the seasonal productive margin factor (SPMF) and Stock hold production hit rate (SPHR) for feature logistic margins. Then selects the features using Intensive Agro feature successive rate (IAFSR) be grouped into clusters. Then the selected features are trained with Multi-objective Deep sub spectral neural network (MODS2NN) to categorize the needs of classes for recommendation. This cold chain process improves the prediction accuracy as well than other methods to recommendation the logistic stock hold management by right seasonal recommendation.

关键词： COVID-19 Transportation Production Predictive models Big Data Real-time systems Agriculture

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Memetic Optimization with Cryptographic Encryption for Secure Medical Data Transmission in IoT-Based Distributed Systems

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computers, Materials & Continua 2021年第2期66卷 1577-1594页

作者： Srinath Doss Jothi Paranthaman Suseendran Gopalakrishnan Akila Duraisamy Souvik Pal Balaganesh Duraisamy Chung Le Van Dac-Nhuong Le Faculty of Computing Botho UniversityGaboroneBotswana Department of Computer Science Gaborone University College of Law and Professional StudiesGaboroneBotswana Vels Institute of Science Technology&Advanced StudiesChennai600117India Global Institute of Management and Technology West Bengal741102India Faculty of Computer Science and Multimedia Lincoln University CollegeKelantan15050Malaysia Center for Visualization&Simulation Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Haiphong UniversityHaiphong180000Vietnam

In the healthcare system,the Internet of Things(IoT)based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical *** datum is sensitive,and hence security is a must in transforming the sensational *** this paper,an Evolutionary Algorithm,namely the Memetic Algorithm is used for encrypting the text *** encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 *** reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the encoded *** show its precision,equivalent to five RGB images and five Grayscale images are used to test the proposed *** results of the proposed algorithm were analyzed using statistical methods,and the proposed algorithm showed the importance of data transfer in healthcare systems in a stable *** the future,to embed the privacy-preserving of medical data,it can be extended with blockchain technology.

关键词： Internet of Things medical images cryptography memetic algorithm steganography

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Analyzing the effectiveness of a health care waste reduction education and training interventions: A step towards green healthcare 2

Analyzing the effectiveness of a health care waste reduction...

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2nd International Conference on Innovative Sustainable Computational Technologies, CISCT 2022

作者： Dwivedi, Swati Poddar, Ajay Gupta, Ashulekha Memoria, Minakshi Kumar, Rajiv Department of Management Studies Dehradun India Omsterling Global University Haryana Hissar India Graphic Era University Department of Management Studies Dehradun India Uttaranchal University Uttaranchal Institute of Technology Department of Computer Applications Dehradun India Uttaranchal University Uttaranchal School of Computing Science Uttaranchal Institute of Technology Dehradun India

ISBN: (纸本)9781665474160

A major problem in the environmental and green healthcare domains is effective waste management. Regarding this, notable recent technical advancements have greatly aided in resolving environmental problems. The goal of this investigation is to examine how successful education and training would be in meeting the demands of waste management in the healthcare sector. In order to identify and evaluate critically the success of a healthcare waste reduction education and training intervention, a thorough literature analysis is conducted. Researchers with an interest in waste management, green healthcare, and related subjects will find the results of this study to be useful. © 2022 IEEE.

关键词： Health care

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