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An Efficacy analysis of data using Fuzzy Logic and Fractal Encryption Techniques for Cloud Platform data Security

An Efficacy Analysis of Data using Fuzzy Logic and Fractal E...

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Knowledge Engineering and Communication Systems (ICKECS), International conference on

作者： P Dineshkumar v Jeeva C Nithiesh P J Arun K Sathish Kumar Department of Information Technology K. S. Rangasamy College of Technology Tiruchengode India Computer Science and Business Systems Sri Sai Ram Engineering College Chennai India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

In the realm of cloud computing, safeguarding data confidentiality is paramount. This paper introduces a novel approach to data security in cloud platforms, merging fuzzy logic and fractal encryption techniques. Fuzzy logic accommodates uncertain data, enabling adaptable encryption strategies tailored to cloud dynamics. Fractal encryption harnesses self-similarity in fractals to create intricate encryption keys, fortifying data protection. Together, they propose a robust solution to mitigate unauthorized access, data breaches, and cyber threats. Through theoretical exploration and practical testing, the efficacy of this approach is demonstrated, highlighting its potential to address cloud security challenges. The scalability and versatility of these methods make them applicable across diverse cloud infrastructures, ensuring comprehensive data protection. This paper advocates for the adoption of fuzzy logic and fractal encryption as proactive measures to enhance cloud platform security, fostering trust among users and stakeholders.

关键词： Fuzzy logic Knowledge engineering Cloud computing Scalability Merging data protection Fractals

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Method of Coding video Images Based on Meta-Determination of Segments

Method of Coding Video Images Based on Meta-Determination of...

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IEEE lnternational conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2024

作者： Barannik, vladimir Barannik, valeriy Babenko, Yurii Kolesnyk, vitalii Zeleny, Pavlo Pasynchuk, Kirill Ushan, vladyslav Yermachenkov, Andrii Savchuk, Maksym V. N. Karazin Kharkiv National University Kharkiv Ukraine Kharkov National University of Radio Electronics Kharkiv Ukraine Taras Shevchenko National University of Kyiv Kyiv Ukraine State Research Institute of Armament and Military Equipment Testing and Certification Kyiv Ukraine National University of Civil Defense of Ukraine Kharkiv Ukraine Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine Heroes of Kruty Military Institute of Telecommunications and Informatization Kyiv Ukraine

ISBN: (纸本)9783031612206

The given chapter is devoted to the scientific problem of the increasing video availability level while ensuring its integrity. To solve the formulated problem, a direction related to the coding methods is used. Such methods enable reducing the video traffic intensity. various standardized platforms for encoding video data analysis are carried out. Thus, a conclusion is made regarding the need to modify the standardized coding process. The following requirements are substantiated. The first is the use of the mechanism for establishing the segments’ informative load regarding their integrity preservation. The direction is implemented based on the segments’ meta-determination technology using components’ intellectual analysis. The second is the creation of methods for segment-differentiated processing depending on their informative load level. A method for segment-differentiated coding based on structural-statistical (SS) saturation is developed. video frame segment differential processing is carried out considering their preliminary typification, depending on the significance of the video information resource (vIR) semantic integrity (SI) preservation position. This is achieved through the syntactic description correction technologies used according to the visual perception model. The main creating model stages for assessing the vIR bit volume reduction level in ensuring its availability process have been described. The created method main differences are: redundancies and their types eliminating process is selected depending on the microsegment’s presence with different SS levels;spectral component areas’ (ASC) permissible correction chains (CPC) codegrams properties regarding the bits excess number presence are considered;the bits excess number filling in the ASC CPC codegrams is carried out depending on the segments influence importance on the vIR SI preservation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Redundancy

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Space exploration Using Sensors Based on Island Nanostructures

Space Exploration Using Sensors Based on Island Nanostructur...

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International Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Svetlana v. Sidorova Sergey v. Kiryanov Sofia A. Aksenova Electronic Technologies in Mechanical Engineering Department Bauman Moscow State Technical University Moscow Russian Federation Space-rocket Launch Complex Department Bauman Moscow State Technical University Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

In this paper the relevance of using weak magnetic field sensors for space research is shown. The analysis of the potential integration of spin-tunnel magnetoresistive (STMR) sensors with island nanostructures into various spacecraft systems has been conducted. A possible application of the sensor in inertial navigation systems of spacecraft for long-duration missions was considered, specifically for calibrating data in regions with low Earth's magnetic field intensity. The feasibility of using the sensor in space missions to investigate remanent magnetization and measure the magnetic field of Mars at various distances from the planetary surface was explored. Through multiphysics modeling, the configuration and geometric parameters of the functional layer consisting of island nanostructures were determined for their use in designing components for spacecraft and navigation systems.

关键词： Space vehicles Mars Sensitivity Magnetic sensors Magnetization Sensor systems Nanostructures Magnetic fields Magnetoresistance Magnetosphere

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An exploration of Machine Learning Methods for Gait analysis of Potential Guide Dogs 23

An Exploration of Machine Learning Methods for Gait Analysis...

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Proceedings of the Tenth International conference on Animal-Computer Interaction

作者： Yifan Wu Colt Nichols Marc Foster Devon Martin James Dieffenderfer Masataka Enomoto B. Duncan X. Lascelles Jane Russenberger Gerald Brenninkmeyer Alper Bozkurt David L. Roberts Dept of Electrical and Computer Engineering North Carolina State University USA College of Veterinary Medicine North Carolina State University USA International Working Dog Registry USA Guiding Eyes for the Blind USA Dept of Computer Science North Carolina State University USA

ISBN: (纸本)9798400716560

Gait analysis is important for guide dog organizations, as ideal guide dogs have a smooth and efficient gait, where they can also easily shift between and maintain various gaits. Gait quality and natural traveling speed are two of the multiple factors important in matching a guide dog to its visually impaired handler. Gait evaluation typically includes subjective visual observation of the dog or objective assessments obtained from special-designed equipment. Guide dog organizations need a method to easily collect and analyze objective data of gait information. In this work, we explored how various machine learning models could learn and analyze gait patterns from inertial measurements data that were collected during two different data collection experiments using a wearable sensor device. We also evaluated how well each machine learning model could generalize behavior patterns from various dogs under different environments. Additionally, we compared how sensor placement locations could affect gait prediction performance by attaching the sensor device to the dog’s neck and back area respectively. The tested machine learning models were able to classify different gaits in the range of 42% to 91% in terms of accuracy, and predict various gait parameters with an error rate ranging from 14% to 29% depending on the setup. Furthermore, we also observed that using behavior data collected from the neck region contains more movement information than the back area. By performing a cross-dataset generalization test on the machine learning models, we found that even with performance drop, the models were able to learn gait-specific behavior patterns that are generalizable for different dogs. Although the results were preliminary, the proposed gait analysis exploration still showed promising potential for studying behavior patterns of candidate guide dogs.

关键词： Canine Behavior analysis Canine Gait analysis Guide Dog IMU Machine Learning

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COvID-19 (COv-19) Spreading Diagnoses by Feature Representation Method Through visual Learning (FvisL-Cov19) 3rd

COVID-19 (COV-19) Spreading Diagnoses by Feature Representat...

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3rd International conference on Information Technology, InCITe 2023

作者： Kakulapati, v. Jayanthiladevi, A. Srinivas University Karnataka Mangaluru India Institute of Computer Science and Information Science Srinivas University Karnataka Mangaluru India

ISBN: (纸本)9789819959969

The use of computer vision and AI methods in medical image assessment has shown impressive success in the analysis and monitoring of respiratory ailment deterioration. To decrease the impact on people and the global economy, the COv-19 epidemic basis on the coronavirus has highlighted the need for artificial intelligence [AI] and disease management. The COv-19 identification approach proposed in this study is completely focused on the depiction of modal functions in pictures. Using standard pre-training features and tiny pattern development during chest CT processing, this approach first extracts modal function characteristics. A regular pooling layer prevents overfitting and reduces training parameters. The representation is trained and fine-tuned;to get the trained model, a machine that learns the scoring standard is utilized. The visible learning modeling approach of Coronavirus 19 (FvisL-Cov19) is used in this study to give a novel multi-layered function feature illustrated representation that is used to examine visible demands, including feature optimum function identification. However, using visual learning of structures improves FvisL accuracy. By employing Cov19’s Chest X-ray images and scans from the reference coranavirus record, the recommended function-based total representations are assessed. For training and testing, we employed 265 (with data-fact augmentation) and 795 COv-19 images, respectively. The FvisL-Cov19 approach demonstrated improved performance overall, using all feature functions in the dataset with an accuracy of 95.22%. The studies show that the kind of technology in this suggested work can analyze the modal statistics of the COv-19 picture more effectively than the standard techniques, and it increases the anticipated impact of appropriately detecting incidents. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COvID-19

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Design and Implementation of an IOT terminal for a Q/v-band GEO satellite 27

Design and Implementation of an IOT terminal for a Q/V-band ...

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27th Ka and Broadband Communications conference and the 39th International Communications Satellite Systems conference, ICSSC 2022

作者： Ebert, Johannes Schlemmer, Harald Schmidt, Michael Cupido, Luis JOANNEUM RESEARCH Steyrergasse 17 Graz8010 Austria LCT Rua da Vila Verde 39 Eixo AveiroP3800-810 Portugal

In this paper, we describe the design of an Internet of things (IOT) terminal for geostationary satellites and a demonstrator implementation for the Q/v band transponder of the Alphasat. A sensor data communication service would normally not be implemented on Qv-band, since this band is more dedicated to feeder links. Nevertheless, this approach is also feasible on Ka-Band, where it would lead to a cost effective and scalable solution for IOT-type of network. The basic approach for the IOT service is to use a terminal with small dimensions which corresponds then also to low gain. The advantage of a low gain antenna is that the terminal is small, cheap and there is no accurate tracking necessary. On the other hand with the small gain of the antenna, we had to consider an accordingly weak link budget as well as harsh limitations by off-axis emission regulations. A second goal of the terminal development is to gain knowledge in the use of low cost, low-gain and non-tracking antenna for satellite beacon power measurements used for wave propagation science. Two terminals and the bigger hub station are in use to allow measurements at three sites, which provide site-diversity measurement/ analysis for the wave propagation science. © 2022 FGM Events LLC. All rights reserved.

关键词： Internet of things

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Hydrogeological settings and petroleum potential of the jurassic-cretaceous deposits of the West Siberian Basin Karabash Zone 23

Hydrogeological settings and petroleum potential of the jura...

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23th conference on Oil and Gas Geological exploration and Development, Geomodel 2021

作者： Plavnik, A.G. Itskovich, M.v. West-Siberian Branch IPGG SB RAS TIU

ISBN: (纸本)9789462823839

The paper presents analysis of geo-temperature, hydrodynamic and hydrogeochemical data in comparison with the complex results of geological, geophysical, paleontological, geochemical and other studies in assessment of the petroleum potential of Mesozoic sediments in the Karabash zone. The results obtained indicate a low efficiency of the traditional hydrogeological criteria application for the zone under consideration, due to the unevenness of the deposits study, small ranges of changes in hydrogeological indicators and the use of many different criteria. Under these conditions, the task of developing methods for a comprehensive analysis of all hydrogeological data becomes urgent. © Geomodel 2021 - 23th Conf. on Oil and Gas Geo. Expl. and Dev. All rights reserved.

关键词： Energy resources

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Predictive Modeling for Cardiovascular Health: Unveiling Insights, Enhancing Interpretability, and Charting Future Trajectories

Predictive Modeling for Cardiovascular Health: Unveiling Ins...

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International conference on Inventive Systems and Control (ICISC)

作者： Katakam Naga venkata Anjani Siva Sri Lasya Peram Meghana Kota Pranathi Gontla venkata Iswarya A.K. velmurugan A.Dinesh Kumar Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

ISBN: (数字)9798350386578

ISBN: (纸本)9798350386585

Heart disease is still a major global health concern, which makes the creation of reliable and treatment necessary. This research study analyzes a large dataset that includes cardiovascular risk variables by using cutting-edge technologies by considering clinical measurements, lifestyle factors, and demographic data. The study uses well-known Python tools for data preprocessing, exploratory data analysis (EDA), and predictive modeling, including NumPy, pandas, and scikit-learn. Statistical and visual techniques are used in exploratory data analysis to find patterns and relationships present in the dataset. The relationships between gender, forms of chest discomfort, and the existence is investigated by using chi-squared testing and visualization approaches. The significance of several characteristics are also analyzed in this study. To determine possible risk factors, the relationship between categorical variables is measured using the Cramer’s v statistic. Correlation matrices are also utilized to investigate the connections between numerical variables. An extensive analysis of feature importance is also included in the conclusion, highlighting the factors that have a major impact on the prognosis. Bar charts are used as visualization tools to reveal the significance of different parameters in the prediction models.

关键词： Heart visualization data analysis Predictive models Nearest neighbor methods Numerical models Trajectory

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Complexity analysis of Ocular Signal for Detection of Human Fatigue Using Small datasets

Complexity Analysis of Ocular Signal for Detection of Human ...

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2022 International conference on Machine Learning and data Engineering, ICMLDE 2022

作者： Das, Ashis Kumar Kumar, Prashant Halder, Suman Department of Electrical Engineering National Institute of Technology Durgapur713209 India Faculty of Technology Uttar Banga Krishi Viswavidyalaya Cooch Behar736165 India

The electrooculogram, often known as an EOG signal, can frequently be used to quantify the amount of drowsiness and exhaustion that a person is experiencing in their body. Electrooculogram signal analysis is primarily a process that does not include any invasive procedures and is used to evaluate the movement of the eye in both horizontal as well as in the vertical direction. The primary purpose of this research is to identify signs of exhaustion using the process of complexity analysis using non-invasive data collected from twenty people who are deemed to be in good physical and mental health. This investigation makes use of three distinct visual signals at three distinct frequencies, and it also considers three distinct time slots during the day. Based on real-time EOG signals that have been gathered in a non-invasive manner, oculo-parameters such as moving window fuzzy entropy and moving window dispersion entropy can be computed. According to the findings of the experiment, the level of complexity of both horizontal and vertical data steadily grows throughout the afternoon and evening as cue frequency steadily rises and we can ascertain the fatigue of the body. Drowsiness and exhaustion in humans may be caused by factors such as muscle stress, insufficient sleep, and a significant time gap between two different sleep cycles. © 2022 Elsevier B.v.. All rights reserved.

关键词： Muscle

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data Brain: Streamlining data Science with AI-Assisted Conversations 1st

Data Brain: Streamlining Data Science with AI-Assisted Conve...

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1st International Research conference on Computing Technologies for Sustainable Development, IRCCTSD 2024

作者： Krithik, Santhakumar S. Aditya, v. Reddy, Kurapati Praneeth Sai Gayathri, R. SRM Institute of Science and Technology Vadapalani Chennai India

ISBN: (纸本)9783031823855

The "data Brain" initiative introduces an innovative AI data Assistant, revolutionising the data science landscape by streamlining the analysis process and making it more accessible. By integrating a user-friendly web interface via stream-lit, alongside robust data manipulation through pandas and visual insights via matplotlib, "data Brain" caters to both novice and experienced data enthusiasts. OpenAI's advanced AI models and custom-built algorithms are employed to offer a conversational interface that guides users through exploratory data analysis, problem-solving, and algorithm selection, based on the analysis of uploaded CSv datasets. Furthermore, "data Brain" enhances query understanding and response accuracy through Sentence Transformers and Pinecone's vector search technology, ensuring user queries are addressed with precision. This seamless integration of AI and machine learning technologies not only democratises data science by simplifying complex analysis tasks but also fosters an environment where users can effortlessly extract actionable insights from their data. "data Brain" stands as a testament to the potential of AI in enhancing data accessibility, promoting an intuitive and interactive experience that empowers users to unlock the full value of their data. Through "data Brain," the field of data science is made approachable, allowing users to navigate and analyse data with an unprecedented level of support and efficiency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data accuracy

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