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2nd International Conference on Physics and Applied sciences, ICPAS 2021

作者： Gadicha, Ajay B. Gadicha, Vijay B. Obaid, Ahmed J. India Department of Computer Science and Engineering G H Raisoni University Amravati India Faculty of Computer Science and Mathematics University of Kufa Iraq

Currently huge amount of data used to stored, extracted and transacted via various stand alone and internet based applications. These applications are extended towards the verticals like huge databases, data warehouses, cloud computing services and various client-server applications. In all these applications important data used to float day in day out. Therefore preserving user authentication & access control is extremely important aspect of information security. Here an attempt is made to generate an implicit authentication system using multi-share visual key cryptography which will generate strong password keys by using images. Initially various images will be fused to form a resultant image than on this fused visual key cryptography will be performed which will provide multiple shares, out of these one of the share is selected to generate strong password strings/keys to accomplish the task of access control or user authentications. © Published under licence by IOP Publishing Ltd.

关键词： Cryptography

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An efficient computational procedure to solve the biological nonlinear Leptospirosis model using the genetic algorithms

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Soft Computing 2024年第1期28卷 607-625页

作者： Sabir, Zulqurnain Ali, Mohamed R. Raja, Muhammad Asif Zahoor Sadat, R. Department of Mathematics and Statistics Hazara University Mansehra Pakistan Faculty of Engineering and Technology Future University in Egypt New Cairo11835 Egypt Basic Engineering Science Department Benha Faculty of Engineering Benha University Banha Egypt Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Mathematics Zagazig Faculty of Engineering Zagazig University Zagazig Egypt Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon

The purpose of this work is to present the numerical solutions of the nonlinear mathematical Leptospirosis disease (LD) model using the computational performances of the artificial neural networks (ANNs) along with the optimization procedures based on the global search genetic algorithm (GA) and local search active-set algorithm (ASA) scheme, i.e., ANNs-GA-ASA. LD is a zoonotic disease that is occurring in the whole world, obtained by rodents that become the reason of death in the people. The LD model based on the susceptible-infected-recovered, i.e., SIR, is used to solve the mechanisms of disease spread. The optimization of an error-based fitness function, which is constructed through the differential mathematical system using the hybrid computing proficiencies of the ANNs-GA-ASA for solving the LD model. The stochastic ANNs-GA-ASA procedures are applied to the LD model to authenticate the precision, exactness, reliability and competence of the ANNs-GA-ASA. The obtained results using the ANNs-GA-ASA of the LD model will be compared using the Runge–Kutta scheme, which authenticate the importance of the ANNs-GA-ASA. Furthermore, statistical analysis through different actions for the LD model approve the convergence and precision of the ANNs-GA-ASA. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Neural networks

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Detecting Pneumonia Lung Infection from X-Ray Images with Deep Learning 1

Detecting Pneumonia Lung Infection from X-Ray Images with De...

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1st International Conference on Mechatronics and Artificial Intelligence, ICMAI 2021

作者： Raheja, K. Goel, A. Mahajan, M. Department of Computer Science and Engineering SGT University Gurugram India School of Computing Science and Engineering Galgotias University India Faculty of Engineering and Technology SGT University Gurugram India

Pneumonia is one of the most prominent basis of premature death globally, according to some of the major health institutions like WHO more than 1 billion people around the world get infected and more than 4 million people die prematurely due to pneumonia lung infection. Detection of pneumonia infection requires a lot of medical tests, which can be expensive and time consuming. Deep Learning, the technology which gives computer systems the ability to learn and adapt through unstructured data in order to complex solve real world problems has the potential to make the detection of pneumonia easier, cost effective and less time consuming. The motivation behind this paper is to grasp the criticalness and utilizations of deep computational learning and Convolutional Neural Network (CNN) by executing it so as to recognize Pneumonia by examining a patient's chest x-beam pictures. © Published under licence by IOP Publishing Ltd.

关键词： computer vision

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Mining general fuzzy sequences based on fuzzy ontology

Mining general fuzzy sequences based on fuzzy ontology

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International Conference on Advances in Intelligent control and Innovative Computing

作者： Gholizadeh, Mehdi Pedram, Mir Mohsen Shanbezadeh, Jamshid Computer Engineering Department Islamic Azad University Science and Research Branch Tehran Iran Computer Engineering Department Faculty of Engineering Tarbiat Moallem University Karaj/Tehran Iran

ISBN: (纸本)9781461416944

Sequence mining, a branch of data mining, is recently an important research area, which recognizes subsequences repeated in a temporal database. Fuzzy sequence mining can express the problem as quality form that leads to more desirable results. Sequence mining algorithms focus on the items with support higher than a specified threshold. Considering items with similar mental concepts lead to general and more compact sequences in database which might be indistinguishable in situations where the support of individual items are less than threshold. This paper proposes an algorithm to find sequences with more general concepts by considering mental similarity between items by the use of fuzzy ontology. © 2012 Springer science+Business Media, LLC.

关键词： Data mining

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Differentially Private Online Federated Learning with Correlated Noise 63

Differentially Private Online Federated Learning with Correl...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Zhang, Jiaojiao Zhu, Linglingzhi Johansson, Mikael Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-100 44 Sweden Chinese University of Hong Kong Department of Systems Engineering and Engineering Management Hong Kong

ISBN: (纸本)9798350316339

We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challenges posed by DP noise and local updates with streaming non-iid data, we develop a perturbed iterate analysis to control the impact of the DP noise on the utility. Moreover, we demonstrate how the drift errors from local updates can be effectively managed under a quasi-strong convexity condition. Subject to an (, δ) DP budget, we establish a dynamic regret bound over the entire time horizon, quantifying the impact of key parameters and the intensity of changes in dynamic environments. Numerical experiments confirm the efficacy of the proposed algorithm. © 2024 IEEE.

关键词： Federated learning

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Chaotic Harris Hawks Optimization for Unconstrained Function Optimization 16

Chaotic Harris Hawks Optimization for Unconstrained Function...

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16th International computer engineering Conference, ICENCO 2020

作者： Ibrahim, Abdelhameed Ali, Hesham Arafat Eid, Marwa M. El-Kenawy, El-Sayed M. Mansoura University Faculty of Engineering Computer Engineering and Control Systems Department Mansoura35516 Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura35111 Egypt

ISBN: (纸本)9781728163925

Swarm-based techniques, a form of meta-heuristic techniques, are derived from the swarm system's social conduct in nature. A newly brought optimization algorithm is Harris Hawks Optimization (HHO) that is stimulated through looking conduct of Harris Hawks (agents) of finding food (optimal solution). Balancing between exploitative and exploratory processes of the original HHO algorithm is desirable for achieving better performance to many optimization problems. An algorithm, Chaotic Harris Hawks Optimization (CHHO), is proposed in this work for the unconstrained function optimization. The CHHO algorithm is presented based on adjusting the exploration mechanism of the original HHO algorithm. Ten chaotic maps are used to control this mechanism instead of random adjusting. The unimodal, multimodal, and multimodal based fixed-dimension benchmark functions are used to compare the CHHO algorithm with the HHO algorithm. Visibility of the CHHO algorithm for optimizing the unconstrained benchmark function, with the intelligible effect of the Gauss and Logistic chaotic maps over other maps, is shown in the experiments. © 2020 IEEE.

关键词： Optimization

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Packet parsing problem solving on mobile low energy client of Biotelemetry system

Packet parsing problem solving on mobile low energy client o...

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2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

作者： Janckulik, Dalibor Motalova, Leona Krejcar, Ondrej Cernohorsky, Jindrich Dept. of Measurement and Control Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Ostrava Czech Republic

ISBN: (纸本)9781424470006

The most important parts of our Biotelemetry system is a hardware platform. If we could develop visualization, we must have to measure real data. They are two main choices to solve this part of system. We can use commercial devices, such as embedded PCs, PDAs and wireless ECG unit Blue ECG communicating via Bluetooth. Suggests major problems and disadvantages of their use and offers possible solutions in the form of construction of our own purpose-built equipment. Whether in the form of small auxiliary hardware and design options ECG units optimized for low power consumption and collaboration with mobile devices with limited computing capabilities. We also describe here the real-time response time of packet parsing problem. © 2011 IEEE.

关键词： Electrocardiograms

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Finite-time chaotic control of unified hyperchaotic systems with multiple parameters

International Journal of Control and Automation

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International Journal of control and Automation 2015年第8期8卷 57-66页

作者： Chen, Chang-Zhong He, Ping Fan, Tao Jing, Chun-Guo School of Automation and Electronic Information Sichuan University of Science and Engineering Zigong China Department of Electromechanical Engineering Faculty of Science and Technology E11 University of Macau Avenida da Universidade Taipa China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and Engineering Zigong China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China

This paper is concerned with finite-time chaos control of unified hyperchaotic systems with multiple parameters. Based on the finite-time stability theory in the cascade-connected systems, a nonlinear control law is presented to achieve finite-time chaos control. The controller is simple and easy to be constructed. Simulation results for Lorenz hyperchaotic system, Lü hyperchaotic system, Chen hyperchaotic system are provided to illustrate the effectiveness of the proposed scheme. © 2015 SERSC.

关键词： Chaotic systems

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A Hybrid approach on Tracking Criminal Investigation and Suspect Prediction

A Hybrid approach on Tracking Criminal Investigation and Sus...

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2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022

作者： Wadhwa, Mridul Jha, Tushar Prasad, Bishal Kumar Bajaj, Abhishek Nagpal, Lakshya Bura, Deepa Manav Rachna International Institute of Research and Studies Faculty of Engineering & Technology Department of Computer Science & Engineering Faridabad India

ISBN: (数字)9781665496025

ISBN: (纸本)9781665496025

Criminal investigation is a machinery that involves examining of evidence in order to discover, detect and authenticate occurrence of crime. Application of number of sophisticated scientific systems, together known as forensic science, is a necessity in a modern investigation. Criminal Investigation Tracker with Suspect Prediction is a revolutionary step towards digital world and controlling the growing rate of crime. It can be used during crime investigation by an agency to assist in their work. The research is designed with UI/UX elements similar to a CRM, that help manage cases and evidence along with client-server architecture to ensure all the necessary documentation as well information is centrally available in place with deployed Access control System, to promote remote working. The research packages certain Free and Open-Source tools for analysis of evidence to best of abilities of the development team to further aid the investigation officers in their work by sharing the workload between dedicated forensics teams with much better tools at their disposal as well as the investigating officers if they want to quickly analyze some piece of evidence. The research paper focuses on how modern technology can be used to reduce the hectic work and making investigation easier for the investigating officers. This also brings a doorway for getting a faster rate of justice inside the system and quick actions to any crime. Furthermore, improvising on existing investigation assistant software in use. This is a leap in investigation methods used by various agencies. © 2022 IEEE.

关键词： Crime

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Extracting Motion Patterns of Greeting Gestures Using GNG with Spiking Neuron Model 13

Extracting Motion Patterns of Greeting Gestures Using GNG wi...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Obo, Takenori Wibowo, Angga Wahyu Sato-Shimokawara, Eri Shibata, Hiroki Ho, Yihsin Kobayashi, Ichiro Tokyo Metropolitan University Department of Mechanical Systems Engineering Tokyo Japan Tokyo Metropolitan University Department of Computer Science Tokyo Japan Takushoku University Department of Electronics and Computer Systems Tokyo Japan Takushoku University Faculty of Engineering Tokyo Japan

ISBN: (纸本)9798350373332

This study focuses on behavior patterns, which are characteristic actions common to groups or communities, to promote intercultural understanding. Understanding greeting gestures is crucial for comprehending social relationships, but these vary across cultures and regions. Recent advancements in sensing technology and artificial intelligence, such as RGB-D cameras and markerless motion capture systems, have made it easier to capture motion data in diverse formats. Therefore, it is important to extract relevant motion patterns and apply appropriate structuring for effective long-term archiving. We propose a method for extracting motion patterns using a Growing Neural Gas (GNG) algorithm with a Spiking Neuron Model. Additionally, this paper presents an experimental example of extracting a gesture pattern in Indonesian style. © 2024 IEEE.

关键词： Economic and social effects

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