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Record Framework Utilization for the Collection of Wireless Device Static Users

Record Framework Utilization for the Collection of Wireless ...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Maganti Syamala Annaji Kuthe V. Selvakumar Alankrita Joshi K. Baranidharan Joshuva Arockia Dhanraj Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Computer Science and Engineering K. D. K. College of Engineering Nagpur Maharashtra India Department of Master of Business Administration Sri Sai Ram Institute of Technology Chennai Tamil Nadu India Department of Electronics & Communication Engineering Graphic Era Deemed to be University Dehradun Uttarakhand Department of Master of Business Administration Sri Sairam Institute of Technology Chennai Tamil Nadu India Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Chennai Tamil Nadu India

The cell of today is a typical instrument. It has become a significant "social item," as opposed to only a minor "specialized object," in the regular daily existences of its users. In this article, we look at a few ongoing improvements in the examination of mobile phone data. With the developing openness of enormous, anonymised datasets, this field of concentrate previously seemed decade prior and has since formed into an independent subject. The estimating investigation of record framework utilization for a gathering of mobile gadget users in different spots is introduced in this work. The purpose of this research is to refute the notion that mobile system behaviour can be modelled as being uniform across different environments. The research demonstrates that when participants travel between places, they obtain statistically substantially diverse sets of data. These findings call into question how mobile computing systems are normally evaluated, which often models a user's behaviour as being comparable to her behaviour at a single place over a longer length of time.

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An Analysis of the Impact of DNS-Based Authentication on Wireless Network Security

An Analysis of the Impact of DNS-Based Authentication on Wir...

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

作者： Piyush P. Gawali Neeraj Das A Rajesh Anupam Shukla Jagmeet Sohal R. Jayadurga Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Master of Business Administration Prince Shri Venkateshwara Padmavathy Engineering College Chennai

This paper investigates the effect of DNS-primarily based authentication on wireless network safety. DNS-primarily based authentication is used to authenticate consumer credentials on Wi-Fi networks, generally primarily based upon the Dynamic Host Configuration Protocol (DHCP). The research specializes in checking out the authentication system via numerous simulations, reading the performance and security of the authentication manner. Effects from such studies monitor that the usage of DNS-based total authentication can improve the safety of a Wi-Fi community, specifically in mitigating man-in-the-center assaults. In addition, analysis shows that DNS-based authentication concurrently improves network overall performance using reducing the fee of authentication, decreasing latency, and increasing the scalability of the authentication process. This research suggests that universal, DNS-based authentication is a precious tool to enhance the security of Wi-Fi networks.

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Resilience test case automation for LTE femtocell networks 5

Resilience test case automation for LTE femtocell networks

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5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021

作者： Sudarsanam, P. Anand, R. Banerjee, Sumanta Hemanth, R. BMS Institute of Technology and Management Bangalore Department of Master of Computer Applications Bengaluru India CMR Institute of Technology Bengaluru Department of Information Science and Engineering Bengaluru India Nokia Solutions and Network SQUAD LEAD Bengaluru India BMS Institute of Technology and Management Bangalore Department of MCA Bengaluru India

ISBN: (纸本)9781665412728

The automated test case generation includes the manual test cases, which are converted to automated test cases through executable test scripts. It is more essential to bring out an effective resilience testing for network gateways. The automation testing plays a major role in performing time constrained and skillful work. Moreover, the network gateways will not take part in onetime investment, even when the technology or environment evolves, the test scripts are continuously patched based on the market demands. Thus, the automation testing is remaining as a challenging task to define and test automatically in a cost-effective mode. The developed device is called as femtocell, which helps to effectively densify the network and deliver a great customer experience in small indoor environments. It is checked to meet the real world scenarios under resilience test cases. It is performed by various manual test cases. Moreover, this project automates the manual test cases. © 2021 IEEE.

关键词： Automation

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Vision-Based Locomotion Control for Humanoid Robots: A Study on Vision-Guided Walking Strategies

Vision-Based Locomotion Control for Humanoid Robots: A Study...

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Computational Intelligence and Sustainable Engineering Solutions (CISES), International Conference on

作者： Saroj Kumar Pandey Lalan Kumar Gaurav Kumar Ankit Kumar Kamred Udham Singh Teekam Singh Department of Computer Engineering & Applications GLA University Mathura UP India Department of Master of Computer Application GL Bajaj Institute of Technology and Management India School of Computing Graphic Era Hill University Dehradun India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun

Recently, there has been a lot of research on using vision to direct humanoid robots as they walk. Focusing on the major methodologies, difficulties, and prospects, this review article presents an overview of the current state of study in the vision-guided walking of humanoid robots. In the first part of the study, we introduce vision-guided walking and go through the several methods that have been developed to execute it, such as visual serving, visual odometer, and visual simultaneous localization and mapping. The difficulties of vision-guided walking are then discussed; these include, but are not limited to, the necessity for accurate and strong computer vision algorithms, the robot's need to have a solid awareness of its own body and how it moves, and the need to maintain balance while walking. This paper provides a detailed review of the research on humanoid robots that use vision to direct their gait. Deep learning for vision-guided walking, tactile and proprioceptive sensing combined with vision, and reinforcement learning for adaptive walking are only a few of the issues covered in this overview. Future directions in vision-guided walking research are discussed in this paper. These include the development of more advanced and reliable computer vision algorithms, the incorporation of other modalities like tactile and auditory sensing, and the investigation of new applications for vision-guided walking in fields like healthcare and rehabilitation.

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Predictive Design for Quality Assessment Employing Cloud Computing And Machine Learning

Predictive Design for Quality Assessment Employing Cloud Com...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International Conference on

作者： Gaurav Jindal Vidhika Tiwari Riyaz Mahomad Anita Gehlot Mimoh Jindal Dibyhash Bordoloi Department of Master of Computer Applications G L Bajaj College of Technology and Management Gr. Noida Mechanical Engineering Department DPGITM Gurugram School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Uttaranchal Institute of Technology Uttaranchal University India National Informatics Centre Delhi India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

In this work, we investigate a unique effective framework for projected design inspections in industrial manufacturing combining machine learning methodologies and edges cloud computing technologies. We recommend a thorough approach that involves targeted data gathering and broadcast, forecasting and supplying appropriate, as well as innovation with the current IT plant infrastructure, in contrary to state-of-the-art contributions. To highlight the steps and advantages of the suggested solution, a genuine business use case in the manufacture of SMT is described. The outcomes demonstrate that the proposed strategy can dramatically reduce inspection volumes, leading to economic gains. A key achievement basis for the drawn-out presentation of assembling ventures is the creation of imperfection-free, top-notch items. Indeed, even with the intricacy and assortment of items and the requirement for savvy production, an exhaustive and dependable quality investigation is habitually required. Along these lines, high examination volumes cause producing bottlenecks in the review processes. Thus, the purpose of this paper is to develop a predictive design for quality assessment regarding employing cloud computing and machine learning. Concerning this particular research, a descriptive research design has been used by depending on secondary data due to its reliability and validity. Moreover, it has been found that both cloud computing and machine learning contribute effectively for employing quality assessment because of their innovative features and infrastructure.

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A Study and Analysis on Various Types of Agricultural Drones and its Applications 5

A Study and Analysis on Various Types of Agricultural Drones...

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5th International Conference on Research in Computational Intelligence and Communication Networks, ICRCICN 2020

作者： Dileep, M.R. Navaneeth, A.V. Ullagaddi, Savita Danti, Ajit Nitte Meenakshi Institute of Technology Department of Master of Computer Applications Bengaluru India Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781728188188

Drones are considered to be the greatest invention of mankind. Drones can be used in many areas widely. Drones can also be used in agriculture and it is called as unnamed aerial vehicles (UAV). In the traditional agriculture methods land vehicles are used to monitor various activities of the agriculture, this was consuming lot of human effort and time. Using drones in agriculture is more beneficial than using traditional methods for the activities. Usage of drones in agriculture provides a huge benefit in terms of economy and time due to their most astonishing features. In recent years many surveys have proved that drones can cover almost 10 to 15 times of the area which can be covered with traditional land based techniques. Drones can be controlled by computers according to their capacities, that is drones can be automated over some range of area, locating remote area, and even can be semi-automated. Drones can be efficiently used in agriculture for performing certain activities such as, studying weather conditions and variations, infection for the crops, land fertility and many more. Because of the efficiency of the drones they can be used in various activities of agriculture. In this paper, a detailed study has been made on various types of agricultural drones based on the feature, capacity, range as well as cost and the area of agriculture where they suit the most, and a statistical analysis about the usage of the drones in the field of agriculture. © 2020 IEEE.

关键词： Drones

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A Diversity Inventory Monitoring System of Riparian Vegetation

A Diversity Inventory Monitoring System of Riparian Vegetati...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Dian Pratama Putra Nanda Satya Nugraha Teddy Suparyanto Alam Ahmad Hidayat Digdo Sudigyo Bens Pardamean Faculty of Agricultural Technology STIPER Agricultural Institute Yogyakarta Indonesia Faculty of Agricultural Technology Faculty of Forestry STIPER Agricultural Institute Yogyakarta Yogyakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

To strengthen conservation efforts for preserving biodiversity in a conservation area, forest inventory is important to understand the natural succession process in the area and to establish a monitoring strategy. Further, tree inventory aims to monitor the output yielded in the area. More specifically, the tree inventory in the watershed area plays a key role to achieve Sustainable Development Goals (SDG), especially in riparian zones which are also vital parts of green zones in forests. However, the traditional inventory approach is time-consuming and laborious therefore the development of an expert system to assist in inventory monitoring is required. In this study, we develop a monitoring system via a mobile application to collect, analyze and visualize tree inventory data. The application includes algorithms required to compute tree biodiversity, distribution, and richness for the given input of the data of all tree species in a conservation area. For the model validation stage, we compare the traditional inventory approach with our proposed application-based approach to compute diversity inventory in two riparian locations: Klaten Conservation Park and Wonosobo Conservation Park. After the three-day data collection in the areas, we obtain that the accuracy of reading data of our proposed system can achieve more than 90% in comparison with the manual approach. This demonstrates that the system can assist forestry workers to perform more efficient tree inventories in different locations.

关键词： Vegetation Manuals Forestry Soil Mobile applications Biodiversity Expert systems

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Probabilistic Modeling and Uncertainty Quantification of Harmonic Distortions in Grid-Integrated Inverters Through Bayesian Neural Networks

Probabilistic Modeling and Uncertainty Quantification of Har...

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Intelligent Control, Computing and Communications (IC3), International Conference on

作者： Srinivasa Rao Neeta Awasthy V. Asha Ginni Nijhawan Gurmeet Singh Ali Albawi E. Annapoorna Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Department of Computer Science and Engineering GL Bajaj Group of Institutions Mathura U.P. India Master of Computer Application New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of AIMLE GRIET Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Harmonic distortion in grid connected inverters Thus, impacts on power quality and system stability are high, and more especially for systems that use renewable energy sources. This research presents a new stochastic predictive modelling approach based on Bayesian Neural Networks for forecasting of harmonic distortions with prediction uncertainty. The proposed methodology uses data from the National Renewable Energy Laboratory (NREL) database that consists of detailed grid voltage, current under various REMs. Harmonics components derived via sophisticated signal processing algorithms then yields the desired data base for training and testing. The uncertainty of grid conditions can be modelled by means of probabilities due to the utilization of BNNs for improving the reliability of predictions. The combination of stochastic modelling and harmonic analysis in this work creates a complex approach to enhancing grid stability and power quality. As applied to renewable energy challenges, the common method enhances the proposed approach as a scalable and adaptive solution for the mitigation of harmonic impacts for future power systems.

关键词： Renewable energy sources Adaptation models Uncertainty Stochastic processes Power system harmonics Predictive models Power system stability Harmonic analysis Inverters Harmonic distortion

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An Overview of Video Tampering Detection Techniques: State-of-the-Art and Future Directions

An Overview of Video Tampering Detection Techniques: State-o...

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Computational Intelligence and Sustainable Engineering Solutions (CISES), International Conference on

In the realm of video processing and forensics, finding video tampering is a critical challenge. The purposeful change or manipulation of video material to conceal or falsely depict the original information is referred to as “video tampering.” A significant demand for efficient video tampering detection methods has emerged in recent years as a result of the rise in false news, cyberbullying, and other types of criminal behavior. Modern approaches for detecting video manipulation may be generally divided into two categories: passive methods and aggressive methods. Whereas active methods entail putting digital watermarks or other identifiers on the video clip to aid tampering detection, passive methods rely on evaluating the video content for inconsistencies or artifacts generated during tampering. Techniques like sensor noise analysis, splicing detection, and forgery detection based on compression artifacts are examples of passive approaches. To find any discrepancies produced by manipulation, sensor noise analysis examines the noise patterns in the video. Splicing detection entails identifying the borders between several video segments and inspecting the content of each segment for irregularities. Analyzing the compressed video stream for irregularities caused during tampering is required for detecting forgeries based on compression artifacts. Techniques like digital watermarking, digital signatures, and fingerprinting are examples of active procedures. To detect any manipulation efforts, digital watermarking entails putting a digital watermark into the video clip. To confirm the legitimacy of the video clip, a digital signature is applied to it. To do fingerprinting, special characteristics from the video footage are extracted and saved in a database. In addition to the aforementioned methods, machine learning-based systems have also demonstrated promising outcomes in the identification of video manipulation. Using these methods, any tampering attempts in fresh mov

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Automatic Scene Text Extraction and Recognition Using Steerable Convolutional Neural Network with Fennec Fox Optimization

Automatic Scene Text Extraction and Recognition Using Steera...

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Intelligent Cyber Physical Systems and Internet of Things (ICoICI), International Conference on

作者： G. Vasukidevi Gulshan Dhasmana Madhavi Kappagantula Shalini S Harshal Patil Ramya Maranan Department of Computer Science and Engineering R.M.K. Engineering College Chennai Tamil Nadu India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Head of the Department Master of Business Administration (MBA) Acharya Institute of Graduate Studies Acharya Sarvepalli Radhakrishna Road Bengaluru Karnataka India Department of Computer Science and Engineering Dayananda Sagar Academy of Technology and Management Bangalore Karnataka India School of Computer Science & Engineering IILM University Greater Noida Uttar Pradesh India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

One of the most crucial steps in developing effective indexing and retrieval systems for multimedia databases is the extraction as well as recognition of text from images. Applications including accessibility, information retrieval and travel, depend on this approach. Many methods are used in order to extract the text. However, there are numerous drawbacks to the current approaches, including a high mistake rate and poor precision. Text Extraction Using Steerable Convolutional Neural Network (TeEx-SCNN) is suggested as a high-accuracy solution to the previously mentioned issue. Data used in this input comes from the IIIT5K dataset. Discrete Wavelet Transformation with Pre-Gaussian Filtering (DWTPre-GF) is suggested as a way to lessen noise in the input data. After that, Dual Aggregation Transformer (DAT) is used to segment the pre-processed pictures. Then, Discrete Orthogonal S-Transforms (DOS-T) are used to extract features. Subsequently, Text Extraction Using Steerable Convolutional Neural Network (TeEx-SCNN) is used for classification and character recognition, while Fennec Fox optimization (FFO) is used for text extraction, which shows improved accuracy and efficiency. Utilizing the IIIT5K dataset, the effectiveness of the suggested TeEx-SCNN -FFO is examined. It achieves 99.5% accuracy, 99.4% recall, and produces superior outcomes when compared to the methods that are already in use. The suggested technique's results demonstrated that it might enhance the computerized text extraction from scene photos method's evaluation capabilities.

关键词： Accuracy Text recognition Filtering Feature extraction Transformers Robustness Discrete wavelet transforms Convolutional neural networks Character recognition Optimization

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