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Hybridization of AES and RSA Algorithm in File Encryption Using Parallel computing 1st

Hybridization of AES and RSA Algorithm in File Encryption Us...

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1st international conference on Advanced Communication and Intelligent Systems, ICACIS 2022

作者： Parikh, Sakshi Jhanwar, Raghav Singh, Apoorv School of Information Technology and Engineering VIT Vellore India School of Electronic Science and Engineering VIT Vellore India

ISBN: (纸本)9783031250873

As technology advances there is an increase in the amount of data transmitted over the network. One of the biggest challenges facing is safety. Cryptography is the study of computational methods related to information security, including privacy, integrity of data, business validation, and source verification, which provides security. In this chapter, we propose a hybrid cryptographic solution using the AES and RSA algorithm as well as the OpenMP shared memory method for memory. The proposed hybrid algorithms aim at better security and efficiency of data. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cryptography

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Research on the Construction and Application of New Smart City Based on Big data Platform

Research on the Construction and Application of New Smart Ci...

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international conference on data science and Business Analytics (ICDSBA)

作者： Gan Jianxiong Guo Tianqi Yang Shaoli Beijing Branch State Grid Information & Telecommunication Group Co. Ltd. Beijing

Under the background of the continuous development of high-tech information technology and the continuous improvement of science and technology level, cities should constantly improve their intelligence and informatization level, and integrate them into a complete system, as they undertake the functions of promoting economic development and developing society. In December 2018, the State Council released the 13th Five-Year National Informatization Plan, and deployed a new smart city construction campaign. As far as smart cities are concerned, the Internet of Things and cloud computing are the core technologies of construction, and their own advantages make them the inevitable outcome of the future development. Therefore, this paper mainly describes the application research based on the key technologies of smart city construction, and mainly makes a more in-depth analysis of each core technology in the construction process, so as to provide reference for relevant personnel. The article analyzes the important value of big data in the construction of smart cities, and puts forward suggestions for the construction of smart cities in the context of big data, with a view to providing a strong reference for China's urban development and smart city construction.

关键词： Economics Cloud computing Smart cities Information services Big data data science Internet of Things

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Pipeline Parallelism in Distributed Deep Learning for Diabetic Retinopathy Classification 4th

Pipeline Parallelism in Distributed Deep Learning for Diabet...

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4th international conference on Innovative data Communication technologies and Application, ICIDCA 2022

作者： Patil, Shashank Anand Patil, Mahesh S. Giraddi, Shantala Chickerur, Satyadhyan Boormane, Vinayak M. Gamanagatti, Ganesh School of Computer Science and Engineering K L e Technological University Karnataka Hubballi580031 India Center for High Performance Computing K L e Technological University Karnataka Hubballi580031 India

Deep learning (DL) has been used widely and successfully in a variety of industries. It is challenging for researchers to carry out their experiments to find the optimal learning model because training the deep learning model is a time-consuming operation. Distributed deep learning offers a technique for rapid training of DL models (DDL). It is difficult to create and implement DDL, nevertheless, so it is important to report on the performance analysis of different DDL algorithms for the benefit of the research community. The authors of this proposed study use two GPUs to design, construct, and analyse a pipeline parallelism in DDL and then present an analysis of its performance. As a case study for DDL implementation, the authors employ diabetic retinopathy classification. 0.834 is obtained as the validation F1 score. The performance of DDL is reported and examined by the authors, and it is demonstrated to improve training effectiveness in terms of both time and speed. © 2023 The Authors. Published by Elsevier B.V.

关键词： Graphics processing unit

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On the Impossibility of Key Agreements from Quantum Random Oracles 1

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42nd Annual international Cryptology conference (CRYPTO)

作者： Austrin, Per Chung, Hao Chung, Kai-Min Fu, Shiuan Lin, Yao-Ting Mahmoody, Mohammad KTH Royal Inst Technol Stockholm Sweden Carnegie Mellon Univ Pittsburgh PA USA Acad Sinica Taipei Taiwan Univ Virginia Charlottesville VA USA

ISBN: (数字)9783031159794

ISBN: (纸本)9783031159787;9783031159794

We study the following question, first publicly posed by Hosoyamada and Yamakawa in 2018. Can parties A, B with quantum computing power and classical communication rely only on a random oracle (that can be queried in quantum superposition) to agree on a key that is private from eavesdroppers? We make the first progress on the question above and prove the following. - When only one of the parties A is classical and the other party B is quantum powered, as long as they ask a total of d oracle queries and agree on a key with probability 1, then there is always a way to break the key agreement by asking O(d(2)) number of classical oracle queries. - When both parties can make quantum queries to the random oracle, we introduce a natural conjecture, which if true would imply attacks with poly(d) classical queries to the random oracle. Our conjecture, roughly speaking, states that the multiplication of any two degree-d real-valued polynomials over the Boolean hypercube of influence at most delta = 1/poly (d) is nonzero. We then prove our conjecture for exponentially small influences, which leads to an (unconditional) classical 2(O(md))-query attack on any such key agreement protocol, where m is the oracle's output length. - Since our attacks are classical, we then ask whether it is always possible to find classical attacks on key agreements with imperfect completeness in the quantum random oracle model. We prove a barrier for this approach, by showing that if the folklore "Simulation Conjecture" (first formally stated by Aaronson and Ambainis in 2009) about the possibility of simulating efficient-query quantum algorithms using efficient-query classical algorithms is false, then there is in fact such a secure key agreement in the quantum random oracle model that cannot be broken classically.

关键词： computing power

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Building an international Entrepreneurship Index using the PSR framework

Building an International Entrepreneurship Index using the P...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Hitaishi Shivaram Kritika Dutta Shine Raju Kappil Department of Data Science CHRIST (Deemed to be University) Bangalore India

This paper builds an international Index for Entrepreneurship (IIE) for the year 2018, by using a conceptual framework named PSR (Pressures-State-Response) to encapsulate the contextual aspect of entrepreneurship globally. In the past, the indices have used a methodological framework of composite indices. This paper uses the PSR framework to show how these indicators fall into the categories of pressure, state, and response, and concentrates on how these subsystems are interrelated. The study considers 41 countries for the construction of the index. We also check the correlation between the IIE and other growth indicators such as the corruption perception index, the economic freedom summary index, GDP per capita, and trade openness using suitable statistical *** correlation analysis demonstrates that the IIE and the Economic Freedom Summary Index have a positive association.

关键词： Correlation Economic indicators Force Buildings Entrepreneurship Indexes Sustainable development

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Sentiment Analysis on Amazon Alexa Reviews Using NLP & Classification

Sentiment Analysis on Amazon Alexa Reviews Using NLP & Class...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Sanjay Kumar Sahil Kanshal Vishnu Sharma Rajneesh Talwar Department of Computer Science Engineering Chandigarh Group of Colleges Jhanjeri Mohali India Department of Information Technology JIMS Delhi India Department of Computer Science Engineering Galgotia’s College of Engineering and Technology Greater Noida India Department of Electronic & Communication Engineering Chandigarh Group of Colleges Jhanjeri Mohali India

many firms and manufacturers, knowledge on public opinion is critical. They frequently want to know what consumers and the general public think of their products and services in real time. However, personally reading every post on the website and extracting important viewpoint information is not feasible. The frequency of data is very high to do it manually. Sentiment analysis enables for efficient and cost-effective data processing on a wide scale. We investigated the application of sentiment analysis in business to better understand its strengths and limits in order to learn more about it. Using Python and Machine Learning Algorithms, this project created a representation to forecast the response of a remark given the observation declaration using a dataset of Amazon Alexa reviews.

关键词： Sentiment analysis Machine learning algorithms Text recognition Virtual assistants Process control Prediction algorithms Tag clouds

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Rapid-Prototyping of Integrated Edge/Fog and DLT/Blockchain Systems with Fogbed

Rapid-Prototyping of Integrated Edge/Fog and DLT/Blockchain ...

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IEEE international conference on Communications (ICC)

作者： Antonio Coutinho Uellington da C. Damasceno Esaú da S. Mascarenhas Allan C. de S. Santos João E. B. T. da Silva Fabíola Greve Department of Technology State University of Feira de Santana Computer Science Department Federal University of Bahia

Edge and fog computing are models to develop internet of things (IoT) solutions with mobility, location awareness, low latency and that allow the processing of large amount of data. Distributed ledger technologies (DLT), such as blockchain, improve IoT system interoperability by enabling a more secure and decentralized way to share data. Recent research has pointed out that integrating current paradigms such as edge/fog and DLT/blockchain allows the development of responsive and secure IoT solutions. Despite recent advances in edge/fog platforms, the current modeling tools are adapted to evaluate edge/fog solutions in limited environments with no DLT/blockchain support. This paper presents an extensible toolset integration to enable edge/fog-based DLT testbeds in virtualized environments. The proposed architecture extends Fogbed to allow the deployment and testing of real-world Edge/Fog-DLT solutions in a scalable way. A case study to demonstrate the emulation and benefits of Edge/Fog-DLT systems is presented. Furthermore, future developments and research directions are discussed.

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IoT-Enabled Smart System for Personalized Health Management with Semantic technologies

IoT-Enabled Smart System for Personalized Health Management ...

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Intelligent Control, computing and Communications (IC3), international conference on

作者： Arelli Madhavi Ammar Hameed Shnain Keerthana S Marimuthu B. Gayathri Vinoth Kumar V Department of AIML Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad Telangana India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq General Surgery Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Information Technology Sethu Institute of Technology Kariapatti Tamil Nadu India Department of CSE CMR College of Engineering & Technology Hyderabad Telangana India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

The current world could be a critical representation of the exceptionally speedy improvement of electronic and data innovation. Wellbeing frameworks are not exempt from the consistent changes happening within the industry. For analysts, specialists, and patients, all these modern innovations are opening up a world of unused potential and challenges. The Web of Things is one of the advances that has been brought into the healthcare industry with extraordinary guarantee. These days, a parcel of restorative contraptions and sensors are associated to the Web of Things, giving shoppers real-time control over their wellbeing and specialists the capacity to appropriately screen their patients' conditions from a separate. The failure to effectively coordinated approaching information from heterogeneous sources, share information collected viably and productively whereas keeping up its security and protection, extricate valuable data from this information utilizing proficient information examination apparatuses, and perform expressive and customized visualizations are right now hindering the effective accomplishment of tall quality in wellbeing care hone. We too present the SM-IoT stage, an cleverly, internet-of-things-based, and customized health care stage energetic to progress farther understanding observing in arrange to supply patients with easier-to-access and more successful healthcare. The objective of SM-IoT is to assemble information from different sources of data, get it from relevant sources, combine it employing a adaptable semantic web, store it within the cloud for extra analysis, visualize it utilizing user-friendly interfacing, and make sharing of the information less demanding whereas keeping protection in mind. The wellbeing care division has changed to supply more quick and individualized restorative medicines much obliged to the quick growing Web of Things innovation. This particular study presents a novel Shrewd IoT stage that employments semantic advan

关键词： Industries Technological innovation Cloud computing data visualization Medical services Real-time systems Security Protection Monitoring Semantic technology

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Quantitative Analysis Indicators and Risk Factor Assessment of HR-HPV 14th

Quantitative Analysis Indicators and Risk Factor Assessment ...

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14th international conference on Genetic and Evolutionary computing, ICGEC 2021

作者： Gong, Ling Xie, Hua Wang, Ling Zhang, Lu Li, Site Miao, Beibei Department of Nursing Beihua University Jilin City China Jilin Central General Hospital Jilin City China Department of Computer Science and Technology School of Computer Science Northeast Electric Power University Jilin City China

ISBN: (纸本)9789811684296

The purpose of this study is to explore the risk factors of HR-HPV (High-Risk Human PapillomaVirus) cervical infection, and to construct an evaluation model through quantification of indicators, so as to provide a basis for the identification of high-risk population, propose a reference for reducing and clearing HR-HPV infection of the cervix and determine a reasonable follow-up period. Computer science and technologies are widely used in the study to calculate and analyze clinical data. The outcome of the study can help to carry forward the prevention of HR-HPV infection, so as to achieve the secondary prevention of cervical cancer. Quantitative analysis indicators model can be used to identify risky people who are vulnerable to HR-HPV and improve the compliance of targeted population to participate in screening. And at the same time, the study can provide reference and basis in the decision of the interval between follow-up visits for HPV testing. Therefor the number of missing HPV screening among risky women is expected to decreased and psychological panic and unnecessary economic burden of patients caused by excessive testing could be avoided. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Risk assessment

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Comparison of One-Stage and Two-Stage Strategies of Machine Learning Model for Rock Art Object Detection 13

Comparison of One-Stage and Two-Stage Strategies of Machine ...

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13th IEEE international conference on System Engineering and Technology, ICSET 2023

作者： Suhaimi, Muhammad Safwan Zainuddin, Khairulazhar Ghazali, Mimi Diana Marzukhi, Faradina Samad, Abd Manan Majid, Zulkepli Ariff, Mohd Farid Mohd Universiti Teknologi MARA College of Built Environment Perlis Branch Arau Campus Perlis Malaysia Universiti Teknologi MARA Shah Alam Geomatics Science and Natural Resources College of Built Environment Malaysia Universiti Teknologi Malaysia Geopark Research Sattelite Laboratory Faculty of Built Environment and Surveying Johor Malaysia

ISBN: (纸本)9798350340891

Tracing rock art documentation has traditionally relied on manual identification by field specialists, which can be laborious and expensive. Integrating Artificial Intelligence (AI) and Machine Learning (ML) in archaeology has introduced new possibilities for enhancing rock art research. ML, a sub-field of AI, focuses on training models using data. At the same time, Deep Learning (DL) advances this approach with Artificial Neural Networks (ANN). Although ML methods have proven helpful for structured datasets, their application to rock art research remains largely unexplored. Object detection, a critical task in computer vision, involves predicting object locations and classes in images. State-of-the-art object detectors include two-stage detectors like Faster R-CNN and Mask R-CNN, which generate region proposals for classification and bounding-box regression, achieving high accuracy at the expense of speed. Conversely, one-stage detectors like YOLO treat object detection as a regression problem, sacrificing some accuracy for improved speed. Striking a balance between accuracy and speed poses a challenge in rock art research. In this context, a promising approach involves training a deep neural network to regress the difficulty scores produced by human annotators. An experiment was conducted using both one-stage and two-stage detectors on large-scale rock art images. The study presents the results and reflects their implications for rock art research. The findings emphasize the potential of AI, ML, and advanced computer vision techniques to revolutionize the field of rock art research, offering enhanced capabilities for analyzing, preserving, and interpreting these invaluable archaeological artifacts. Through automation of the detecting process and a decrease in the need for manual labor, these technologies can increase efficiency and accuracy in rock art studies. © 2023 IEEE.

关键词： Object detection

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