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Android security: State of art and challenges

AIP Conference Proceedings 2021年第1期2387卷

作者： R. Thamilselvan K. Tamil Selvi C. Mahalakshmi N. Sanjeev Yogesh Bala 1Professor Department of Master of Computer Application Kongu Engineering College Erode Tamil Nadu India - 638060 2Assistant Professor Department of Computer Science and Engineering Kongu Engineering College Erode Tamil Nadu India - 638060 3PG Scholar Department of Master of Computer Application Kongu Engineering College Erode Tamil Nadu India - 638060

Now-a-days Android devices are rapidly increasing as per user's need and very helpful to fulfil personal and professional need. Also, these devices are quickly turning into a genuine danger because of the various malwares and security issues and threats present in them. In this paper, different proposals of security mechanisms and techniques are reviewed, which are used to ensure the security of these devices along with the latest state of art. It also discovers different kinds of security mechanisms that include authorization related issues, which are a continuous wonder in Android applications. Consent related issues that can often times wait inside an application for an all-inclusive timeframe, which can be as high as quite a while, prior to being fixed. With the collected information, security mechanisms are evaluated to find the effectiveness of methods for forestalling and identifying portable malwares and threats. Also analyzed, the motivating forces that cause benign android hobbyists to distribute root exploits and overviewed the accuracy and accessibility measures of those techniques.

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Estimation of Temporal R-factor Based on Monthly Precipitation Data

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Journal of Physics: Conference Series 2021年第1期2070卷

作者： Narendra Kumar Maurya Prakash Singh Tanwar Research Scholar Department of Civil Engineering Madhav University Pindwara (Sirohi) India Associate Professor Department of Computer Science & Engineering Lovely Professional University Phagwara Jalandhar Punjab India

This study assesses temporal variation in rainfall erosivity of Gurushikhar, Rajasthan, (India) on a monthly precipitation basis in the form of the USLE/RUSLE R-factor. The objective of the paper is to theoretically calculate rainfall erosivity when the unavailability of high temporal resolution pluviographic rainfall data such as Indian condition. In the study, the rainfall erosivity has been calculated using the Modified Fourier Index. The results show that the annual rainfall erosivity factor (R) value highest in the year 2017 and lowest in 1974. Conferring to an examination through NASA, earth's global superficial temperatures in 2017 ranked as second warmest since 1880. Therefore, the rainfall amount was more in 2017 compared to past years, and also rainfall erosivity value suddenly increased in 2017, achieved the highest value. They concluded that the heavy precipitation events in the year are lead to an increase in rainfall erosivity value and risk of soil erosion.

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Kannada word sense disambiguation using semantic relations

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Journal of Physics: Conference Series 2021年第1期1767卷

作者： B.H. Manjunatha Kumar M Siddappa Assistant Professor Department of Computer Science and Engineering Sri Siddhartha Institute of Technology Tumakuru Karnataka India Dean (Academics) Sri Siddhartha Academy of Higher Education Tumakuru Karnataka India

In this paper, a method is proposed to use the semantic relations of words to solve Word Sense Disambiguation (WSD) for the Kannada language. Semantic relationships like hypernymy and hyponymy are used in finding the overlaps between two concepts. Integrating the idea proposed in this paper with original Lesk's technique improves the accuracy of the Lesk's algorithm. Indo-WordNet is used as the lexical resource to gain the knowledge about the semantic relations of words and this knowledge is exploited to disambiguate the target word of the Kannada language. Since the approach used in this paper is unsupervised, so it can be scalable to other languages also.

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Modified linear congruential generator to secure random number generation

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AIP Conference Proceedings 2021年第1期2387卷

作者： Sathya K. Premalatha J. Vani Rajasekar Madhan Kumar M. Deepak M. Manoj S. R. 1Assistant Professor Department of Computer Science Engineering Kongu Engineering College Perundurai India 2Professor Department of Information Technology Kongu Engineering College Perundurai India 3UG Scholar Dept of CT-UG Kongu Engineering College Perundurai India

Random numbers are important tools for generating secret keys, encrypting messages, or masking the content of certain protocols with a random sequence that can be deterministically generated. The nonattendance of demand about the self-decisive numbers conveyed can make genuine harm cryptographic shows, impelling weaknesses to be mishandled by the aggressors. In this paper, another pseudo - optional number generator calculating that utilizes dynamic design clock changed over to Epoch Timestamp as PRNG seed was made. The figuring utilizes a Linear Congruential Generator (LCG) tally that makes a get-together of pseudo - randomized numbers that performs numerical tasks to change numbers that has all the stores of being disconnected to the Seed. Multiplication result shows that the new PRNG calculation doesn’t convey emphasized self-emphatic numbers subject to the rehash of highlight, a decent pointer that the key for flighty numbers is guaranteed about. Mathematical evaluation utilizing NIST Test Suite results focused to optional movements made flighty numbers has a completely conventional of 0.342 P-Value. For a P-Value≥0.001, a social event would be viewed as abstract with an affirmation of 99.9%. This shows that strength and weirdness were developed. Accordingly, It is astoundingly deterministic in nature and has a benevolence of Pseudo-Random Numbers. It is hence a pleasant wellspring of a social event key age for encryption, equal in the assertion plans and other cryptographic assessment restricts that improve and secure information from a security assault.

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An Experimental Performance Analysis on Robotics Process Automation (RPA) With Open Source OCR Engines: Microsoft Ocr And Google Tesseract OCR

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IOP Conference Series: Materials science and engineering 2021年第1期1059卷

作者： T Malathi D Selvamuthukumaran C S Diwaan Chandar V Niranjan A K Swashthika Assistant Professor Department of Computer Science & Engineering Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401 Assistant Professor Department of Mechanical Engineering Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401 Second Year Department of Information Science & Engineering Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401 Second Year Department of Computer Technology Bannari Amman Institute of Technology Sathyamangalam Erode Tamilnadu - 638401

Robotic Process Automation (RPA) plays an important role in the solution for automating human digital interaction in various software domains like IT, Business Strategy and so on. Optical Character Recognition(OCR) superimposes subtitled characters on an *** we use two Open source OCR engines, Google Tesseract OCR - It literally makes use of the open source Tesseract OCR Engine[1]. Microsoft OCR - This is another open source OCR engine accessible in the Robotics Process Automation tool, UiPath[1]. The technique of optical character recognition (OCR) has been used to transform printed text into editable text. In various applications, OCR is a very useful and common technique. OCR precision can be dependent on algorithms for text preprocessing and segmentation. Often because of different scale, design, orientation, complex picture context, etc., it is difficult to retrieve text from the image. We begin this paper with an introduction to the Optical Character Recognition (OCR) process, in this paper, we propose a research analysis to estimate the accuracy of two open source OCR engines with Robotics Process Automation(RPA). These RPA processes are created using the UiPath tool and our results compare the OCR engines performance during the execution with the workflow and save the results to our local storage or on cloud storage if cloud support enabled and here we used local storage for purpose, and the result analysis and error analysis was evaluated by manual process which also included excel formulas to calculate the accuracy of the extracted string with the original string.

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Preface

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Journal of computer science & Technology 2020年第3期35卷 491-492页

作者： Shi-Min Hu Ying He Belen Masia Professor Department of Computer Science and TechnologyTsinghua UniversityBeijing Associate Professor School of Computer Science and EngineeringNanyang Technological University Singapore Assistant Professor Department of Computer ScienceUniversity of ZaragozaZaragoza

The Computational Visual Media(CVM)conference series is intended to provide a major international forum for exchanging novel research ideas and significant computational methods that either underpin or apply visual *** primary goal is to promote cross-disciplinary research to amalgamate aspects of computer graphics,computer vision,machine learning,image and video processing,visualization and geometric *** main topics of interest to CVM include classification,composition,retrieval,synthesis,cognition and understanding of visual media(e.g.,images,videos,3D geometry).

关键词： computer graphics visual

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Smart Villages: IoT Technology Based Transformation

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Journal of Physics: Conference Series 2021年第1期2070卷

作者： Pankaj Mudholkar Megha Mudholkar B S Puneeth Kumar V Dankan Gowda S. Srinivasulu Raju Assistant Professor Department of Master of Computer Applications. Thakur Institute of Management Studies Career Development and Research Mumbai Maharashtra (State) INDIA Assistant Professor Department of Computer Science. St. Joseph's College (Autonomous) Bangalore Karnataka (State) INDIA Assistant Professor Department of Electronics and Communication Engineering. B.M.S. Institute of Technology and Management Bangalore Karnataka (State) INDIA Department of Electronics and Instrumentation Engineering. Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada Andhra Pradesh(State) INDIA

In recent years, large-scale urbanisation has been on the rise with cities being the hubs for growth, but rural business continues to play an important role in any country's overall development. A recent report reveals that almost 69 percent of India's population resides in their villages, accounting for almost 50 percent of the nation's GDP. This agricultural region varies from small towns with less than 500 residents to small towns. There are also similar situations in western nations. Despite their economic contribution, smaller villages seem to earn fewer in terms of infrastructural expenditure. The major problems addressed in these small towns include shortage of adequate public transit, emergency care and limited knowledge on federal subsidies for rural areas. Our vision is to expand the Smart city to Smart village by allowing use of recent technical advances and giving more attention to the problems in rural areas. The approach in this chapter is to bring IoT technology to Villages by literally showing a network of linked sensors and knowledge dissemination devices, controlling energy use and ensuring infrastructure protection. It gives a wide-ranging vision of enhancing the standard of living in villages and encourages them to meet the essential needs of domestic villagers.

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Beach Topographic Change Analysis Using Multi-temporal UAV Data

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IOP Conference Series: Earth and Environmental science 2021年第1期799卷

作者： K T Chang H M Fang S S Hsiao C S Li Associate Professor Department of Civil Engineering and Environmental Informatics Minghsin University of Science and Technology Assistant Professor Bachelor's Degree Program in Ocean Engineering and Technology National Taiwan Ocean University Professor Department of Harbor and River Engineering National Taiwan Ocean University Center of Excellence for Ocean Engineering Master Department of Harbor and River Engineering National Taiwan Ocean University

A time-serial topographic change was performed using two kinds of surveying methods, including direct measurement and indirect remote sensing technology for beach topography surveillance. Compared with reference topographic data, the root mean square error was 0.169 m. From May, 2018 to March, 2019, multi-temporal beach topographic change results indicated that the distance between baseline and shoreline varied in the range of −24.82∼9.58 meter, and weekly variates are −3.16∼0.45 m. The UAV technique can be efficiently used to detect topographic change information in the coastal area.

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Machine Learning and Data Analytics for Environmental science: A Review, Prospects and Challenges

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IOP Conference Series: Materials science and engineering 2020年第1期955卷

作者： Tharsanee Maganathan Soundariya Senthilkumar Vishnupriya Balakrishnan Assistant Professor Department of Computer Science and Engineering Bannari Amman Institute of Technology Sathyamangalam.

Innovations in Machine Learning and Data Analytics can possibly affect numerous aspects of Environmental science (ES). Data Analytics refers to a collection of data resources indicated in terms of variety, velocity, veracity and volume. Big data contributes to the ES arena in applications such as weather forecasting, energy sustainability and disaster management with the advent of techniques such as Remote Sensing, Information and Communication technologies. Though big data is used to accomplish data analysis and interpretation for ES, there are still requirements for efficient ways of data storage, processing and retrieval. Machine Learning and Deep Learning are the sub fields of artificial intelligence which deals with training the models to learn from data without being explicitly programmed. When Machine Learning and Deep Learning are combined together it is possible to unleash the supremacy of data analytics. These techniques show high prospective for process optimization, information-centric decision making and scientific discovery. Scientific developments like these will assist ES to make real time autonomous decisions by extracting useful insights from huge data. These advancements also aid in bridging the gap between the theoretical backgrounds on ES to practical implementation. The primary objective of this survey is to figure out the basic concepts of Machine Learning, Deep Learning, and Data Analytics and find the state-of-the-art applications in ES, and observe the impending benefits of information-centric investigation on ES.

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Review for the Solar Radiation Forecasting Methods Based on Machine Learning Approaches

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Journal of Physics: Conference Series 2021年第4期1964卷

作者： U Hemavathi Ann C V Medona V Dhilip Kumar R Raja Sekar Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Assistant Professor Department of Artificial Intelligence and Data Science Saveetha Engineering College Chennai Tamil Nadu India

Predictions of solar potential for these systems' production are important, whether they ensure sound activity or the perfect control of an energy discharge heading to the solar system. It is important to base the prediction on solar irradiance before predicting solar systems performance. The measurement of solar radiation elements is a very significant criterion for applications of solar energy. Several globalized solar radiation prediction modes can be done in the two major categories: cloud imagery with physical models and machine learning techniques are correlated. In this paper, the methods used to predict solar radiation are explained with machine learning algorithms.

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