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2nd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2023

作者： Mohapatra, Srikanta Kumar Singh, Kamakhya Narayan Sarangi, Prakash Kumar Sahu, Premananda Mohanty, Jayashree Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School Of Computer Application KIIT Deemed University Odisha India Hyderabad India School of Computer science and Engineering Lovely professional University Punjab India Chandigarh University Dept.of AIT-CSE Punjab Chandigarh Mohali India

ISBN: (纸本)9798350333763

The population is increasing in a rapid manner and the number of vehicles is increasing in the same ratio. Also, crude oils are very useful towards the energy needs in the industries. As a result, a day will come when we face the issue of feeling the vehicles with the petrol to run the vehicle and to run the industries. So, the solution is to find out the period up to which we can use the crude oil which is currently present in the world. To get a conclusion the most populated countries India and China is taken as reference. For simulation purpose time series based Artificial Neural Network application along with Facebook Prophet is used. Facebook Prophet is used to predict future situations in time series data related to oil production and consumption in two top countries by population, China, and India, over a period of 32 years. NeuralProphet is used for modelling time-series based on neural networks forecasting the near-term oil crisis. The dataset used in this study contains three characteristics, namely population, oil production, and consumption, and is obtained from different government sources. The best part of this model is that it can predict multi step ahead of given current data as required. The method based on NeuralProphet is best suit for the time series prediction for short period or long period. It can be used in multistep ahead prediction methods. It is predicted that by 2050 the scarcity of the petroleum is most. So, the solution is either to reduce the uses of vehicles, control the population or simply go for an alternate fuel like hydrogen could be considered a suitable substitute for oil. This prediction highlights the need for sustainable energy sources to meet the energy demand in the future. In conclusion, this paper presents NeuralProphet approach for forecasting future oil consumption and production trends combining the Facebook Prophet and NeuralProphet method. © 2023 IEEE.

关键词： Time series

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Land Use and Land Cover Classification Using Recurrent Neural Networks with Shared Layered Architecture 12

Land Use and Land Cover Classification Using Recurrent Neura...

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12th International Conference on computer Communication and Informatics, ICCCI 2022

作者： Vignesh, T. Kanimozhi, K.V. Sathish, R. Kumar, R. Prasanna Jeyavathana, R. Beaulah Ezhumalai, P. Srm Institute of Science and Technology Department of Master of Computer Application Chennai Ramapuram India Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Saveetha School of Engineering Chennai India J.N.N Institute of Engineering Department of Computer Science and Engineering Chennai India Department of Computer Science and Engineering Amrita School of Engineering Amritha Vishwa Vidyapeetham Chennai India Srm Institute of Science and Technology Department of Computer Science and Engineering Chennai Kattankulathur India R.M.D Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665480352

In the computerized world the uniqueness of information security is fundamental. Biometric frameworks utilizing individual physiological or conduct ascribes which are turning out to be ordinarily normal in giving IT insurance and getting to powerless places, for example, air terminals, organizations, medical care, the military, and so forth A multimodal biometric framework that offers an individual personality base on different physical or interior attributes is liked to permit a biometric framework to work effectively in assorted applications and conditions. To additionally further develop security, multi-modular biometric confirmation could be utilized by defeating the requirements looked by unimodal biometric validation frameworks. The proposed work clarifies facial, unique finger impression and iris-based calculations, particularly in multimodal biometrics. In this first work a coded multi-work acknowledgment of the face under unusual lighting conditions has been executed. Face picture is taken as a contribution to this proposed work. Strategies dependent on normalization or enlightenment is proposed to accomplish great outcomes under lighting changes. The Gabor highlights, LBP elements and step similarity qualities are then gotten from pre-handled facial pictures. The removed attributes are combined with Z score level combination and primary handling. The facial pictures are perceived by the ANFIS classifier as indicated by the combined keys. The trial discoveries show that the proposed technique is showing improvement over the current framework. It doesn't, in any case, yield compelling shading face picture acknowledgment execution. Therefore, the determined attributes are consolidated at the level of the match to make the multi-biometric design and perform keyage utilizing a combination subject to thickness. LVQ is in this way used to coordinate with the example. The discoveries closed, comparative with current K -Closest Neighbor calculations (KNN), Support

关键词： Support vector machines

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Icon-to-Icon Translation using Pixel-Level Weight Adversarial Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第1期7卷 147-160页

作者： Pan, Yao-Ming Lin, Kai-Biao Chen, Chin-Ling School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Engineering Research Center of Big Data Application in Private Health Medicine Fujian Provincial University Putian351100 China School of Information Engineering Changchun Sci-Tech University Changchun130600 China Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung41349 Taiwan

We investigate image-to-image translation as a solution to icon-to-icon translation problems. Icon-to-icon translation aims to translate the input icon to appear like the target domain’s icons and simultaneously preserve the original icon’s information (e.g., application logo, text and background color). We present a novel approach to trans-lating icons to the version with the target style intelligently. By observing many icons with various styles, we propose a pixel-level weight matrix to calculating the weighted losses. These losses guide the generator to focus on the critical regions of the icon. People can clearly get the original icon’s information from the proposed method’s results, while the existing state-of-the-art image-to-image translation methods may fail to do this. © 2022, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Pixels

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Wireless LAN Security 6

Wireless LAN Security

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6th International Conference on Signal and Image Processing, ICSIP 2021

作者： Al-Shebami, Taha Abdullah Ali Al-Shamiri, Abdulkawi Yahya Radman Department of Computer Application Technology School of Computer Science and Information Engineering Hefei China School of Computer Science and Engineering Hodeidah University Department of Computer Science Al-Hodeidah Yemen

ISBN: (纸本)9780738133737

The proliferation of wireless networks has increased the risks and threats to the security and privacy of its users in assault of privacy, penetration, and piracy of information and data. Due to their consideration as an open communication environment and data is available in space, where radio waves are used to exchange information;that is making them vulnerable to eavesdropping and active attack. Therefore, wireless security is very important to reduce these attacks and threats, and to reduce the risks and attacks caused by security vulnerabilities that threaten wireless networks, it is necessary to find security solutions to prevent attacks and threats on these networks. This paper presents ways to achieve security in wireless networks, to know the types of attacks and threats on these wireless networks, to identify ways, which used to manage and secure wireless networks, and then access to protect these networks against violations and interventions, and how to prevent or minimize these risks with a set of recommendations and proposals. © 2021 IEEE.

关键词： Network security

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A Hybrid Remora Optimization Algorithm with Variable Neighborhood Search for the Flexible Job Shop Scheduling Problem 7

A Hybrid Remora Optimization Algorithm with Variable Neighbo...

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7th International Conference on Advanced Algorithms and Control engineering, ICAACE 2024

作者： Yang, Zheng Liang, Xiaodan Li, Yajing Wang, Haoyue School Of Computer Science And Technology Tiangong University Tianjin China Engineering Research Center Of Integration And Application Of Digital Learning Technology Ministry Of Education The Open University Of China Beijing China College Of Artificial Intelligence Tianjin University Of Science And Technology Beijing China

ISBN: (纸本)9798350361445

Reducing the production makespan of modern small-batch, multi-variety jobs can be abstracted into a flexible job shop scheduling problem (FJSP). The organization can greatly improve production efficiency by scheduling according to the optimal solution of FJSP. However, due to the high computational complexity of FJSP, it is often difficult to achieve higher performance in actual production. To optimize the makespan of the FJSP, a hybrid remora optimization algorithm with variable neighborhood search (HROA-VNS) is proposed in this work. A hybrid initialization method based on machine load balancing is utilized to improve the quality of the initial population. To solve discrete FJSP, a conversion method for individual positions and scheduling solutions is proposed, and a host switching mechanism (HSM) is designed to enhance the development and exploration capabilities of the algorithm. Furthermore, for enhancing the accuracy and effectiveness of the optimal solution, a variable neighborhood search (VNS) strategy which contains multiple structures is designed for local search. According to the experimental data, compared with the basic algorithm, the HROA-VNS reduced the makespan by an average of 33.02% and 14.40% on the two benchmark test sets respectively, and it shows better performance than related algorithms. © 2024 IEEE.

关键词： Evolutionary algorithms

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Development of China's spaceborne SAR satellite,processing strategy,and application:take Gaofen-3 series as an example

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地球空间信息科学学报（英文版） 2024年第1期27卷 221-236页

作者： Guo Zhang Shunyao Wang Zhenwei Chen Yuzhi Zheng Ruishan Zhao Taoyang Wang Yu Zhu Xinzhe Yuan Wei Wu Weitao Chen State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina School of Law Wuhan UniversityWuhanChina School of Geomatics Liaoning Technical UniversityFuxinChina School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina Institute of Spacecraft System Engineering China Academy of Space TechnologyBeijingChina National Disaster Reduction Center of China Ministry of Emergency ManagementBeijingChina School of Computer Science China University of GeosciencesWuhanChina Key Laboratory of Space Ocean Remote Sensing and Application Ministry of Natural Resources of the People's Republic of ChinaBeijingChina

After mastering the key technologies of manufacturing spaceborne Synthetic Aperture Radar(SAR),China's SAR satellites have been successfully launched into *** the only civil microwave satellite listed in the"National High-resolution Earth Observation System Major Project,"the Gaofen-3(GF-3)01 satellite is the first C-band multi-polarization SAR satellite with a resolution of 1 ***-3 series satellites stand out among civil SAR satellites worldwide because of their high resolution,wide swath,high geometric radiation quality,multiple imaging modes,and long operation *** GF-3 series satellites as an example,this study introduces the development of China's civil SAR satellites,as well as their processing strategies and *** success of the GF-3 series satellites shows that China's SAR remote sensing technology has stepped into a new era of high-quality and high-precision Earth observations.

关键词： High-resolution Synthetic Aperture Radar(SAR) GaoFen-3(GF-3)satellites earth observation

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Optimizing Drug Dosage and Medication Management for Geriatric Patients with Artificial Neural Networks 3

Optimizing Drug Dosage and Medication Management for Geriatr...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Beemkumar, N. Singh, Daljeet Pal Ahmed, Zahid Faculty of Engineering and Technology Department of Mechanical Engineering Bagalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350343274

In this paper, we utilize ANNs to investigate how medicine dosing and management might be improved for the elderly population. The suggested strategy calls for the use of patient-specific data as inputs for the ANNs, such as age, renal and hepatic function, body mass index, and preexisting prescription profiles. The neural network model dynamically changes drug doses using the combination of the Multilayer Perceptron (MLP) algorithm, Backpropagation, and the Stochastic Gradient Descent (SGD) algorithm to maximize therapeutic benefits and reduce the likelihood of adverse drug events. The research highlights the improved accuracy, sensitivity, specificity, precision, and F1 score of the suggested technique compared to numerous conventional methods. As a result, the suggested system has great potential to revolutionize medication management for the elderly population since it is more personalized, flexible, patient-safe, effective, and efficient in its use of resources. © 2023 IEEE.

关键词： Optimization

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Exploring OSINT for Modern Day Reconnaissance

Exploring OSINT for Modern Day Reconnaissance

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2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Ram, Ajay S. Thalakkat, Arya Udayan, Devika Khader, Aiby A. Hari, K. George, Vipin Government Engineering College Dept. of Computer Science and Engg. Thrissur India School of Technology and Applied Science Dept. of Cyber Forensics Kottayam India Kerala Police Academy Dept. of Computer Application Thrissur India Kerala Police Academy Police Computer Lab Thrissur India Kerala Police Academy Thrissur India

ISBN: (纸本)9798350303452

The Internet's growth has connected users globally, forming a vast network of data. As new social media platforms with diverse features emerge, individuals are drawn to sharing their personal data online. This inclination stems from a desire to display social status. However, this openness poses risks, as personal data uploaded to the internet can easily unveil one's online identity. Extracting such data is a straightforward process, as a simple correlation of evidence with an online profile can summarize a user's identity. By combining various sources of information linked to a specific individual, a comprehensive profile can be created. As the digital landscape expands, Open Source Intelligence (OSINT) has become an invaluable tool for gathering information. OSINT involves searching and accessing publicly available data to extract relevant information, analyze patterns, and draw conclusions. It encompasses activities like web scraping, data mining, social media monitoring, and online research. OSINT is crucial for understanding public sentiment, identifying potential threats, conducting background checks, investigating crimes, and performing competitive analysis. This paper investigates the impact of OSINT as a modern day reconnaissance tool. Through case studies and real-world examples, the research demonstrates the effectiveness of OSINT in enhancing situational awareness, supporting decision-making for law enforcement agencies, and using OSINT as a modern-day reconnaissance tool. © 2023 IEEE.

关键词： Data mining

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SVM-Guided Dynamic Routing for Post-Harvest Quality Preservation in Smart Warehouses with IoT 3

SVM-Guided Dynamic Routing for Post-Harvest Quality Preserva...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Umamaheswari, K. Antony Joseph Rajan, D. Ramasamy, Jayabharathi Seeni, Senthil Kumar Meenakshi, R. Thamizhamuthu, R. VR. Siddhartha Engineering College Department of Electronics and Instrumentation Engineering Andhra Pradesh Vijayawada India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Cognizant Technology Solutions Department of Mobile Application Development Buffalo GroveIL United States Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus-Chengalpattu Tamil Nadu Chennai India

ISBN: (纸本)9798350381931

This research presents a new approach to smart warehouse quality preservation after harvest by combining the Internet of Things (IoT) with Support Vector Machine (SVM)-guided dynamic routing. Preserving the quality of harvested goods during storage and transportation is of utmost importance in today's agricultural supply chain. Critical characteristics like temperature and humidity are monitored using real-time data acquired from sensors via the IoT. It uses the SVM algorithm to optimize the items' route dynamically according to the changing environmental conditions. The adaptable and efficient flow of agricultural goods throughout the warehouse is guaranteed by this dynamic routing method, which is led by SVM decision-making. A number of aspects that impact quality preservation, the method lessen the possibility of degradation during transit and storage. The effectiveness of the suggested strategy is supported by simulation findings, which demonstrate better preservation of post-harvest quality in comparison to conventional approaches. Smart warehouses may benefit greatly from the combination of SVM and the IoT, which solves many problems in the agricultural supply chain and helps improve sustainable postharvest management. © 2024 IEEE.

关键词： Sensor networks

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Recognition and evaluation of cutaneous condition through assorted artificial intelligence reliant algorithms

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International Journal of Information Technology (Singapore) 2025年 1-13页

作者： Mishra, Manmohan Yadav, Ajay Kumar Mazumdar, Bireshwar Dass Gupta, Prashant K. Panwar, Arvind Bharadwaj, Shivam Department of Computer Application United Institute of Management Prayagraj India School of Computer Science & Engineering Technology Bennett University Plot Nos 8-11 TechZone II Uttar Pradesh Greater Noida 201310 India Galgotias University Plot No. 2 Yamuna Expy opposite Buddha International Circuit Sector 17A Uttar Pradesh Prayagraj 203201 India

Our skin is the hefty organ that envelops and shields body. It prevents us from numerous fatal and non fatal diseases. It is observed that due to bacteria or other causes of infection, skin faces certain minor or life threatening diseases. The most prioritized step toward restoring health is early illness signs identification. Identifying Cutaneous Condition from clinical images is one of the foremost challenges in medical image investigation. In the presented study we will enlighten the various Artificial Intelligence techniques falling under the categories of supervised machine learning including Probabilistic classifier (Naïve Bayes), Statistical algorithm (Logistic Regression), Ensemble learning (Random Decision Trees), Data analysis technique (Convolutional Neural Network) and Kernel approach (Support Vector Machine) to identify and classify the cutaneous condition appropriately so that corrective measures of skin treatment can be endow with. The proposed approach entails collecting images as input, preprocessing, segmenting, feature extraction and lastly applying the classification algorithms to derive the Cutaneous Condition categories. Additional trials are conducted using the different approaches as indicated and it was discovered from the suggested tests that the Convolutional Neural Network strategy yields the best results overall. The proposed model is trained, tested, and evaluated using the International Skin Imaging Collaboration (ISIC) 2019 challenge dataset and Human Against Machine with 10,000 training images (HAM10000) for the detection of manifold Cutaneous Condition. © Bharati Vidyapeeth's Institute of computer applications and Management 2025.

关键词： Artificial intelligence Confusion matrix Convolutional neural networks Cutaneous condition Image processing Machine learning

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