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Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： R. Sarasu V. Nandagopal N V Shibu Suresh Lakshminarayanan T Saju Raj M. Rajmohan Department of Spatial Informatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Electrical and Electronics Engineering School of Engineering Mohan Babu University Tirupathi India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Engineering & Electronics University of Technology and Applied Sciences South Al Batina Oman Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Chennai India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

This paper introduces a new method for managing fire hydrants that uses a monitoring system based on the Internet of Things (IoT) and a Naive Bayes Classifier (NBC) for predictive maintenance. Water pressure, flow rate, and the physical state of fire hydrants are among the essential factors for the proposed system continually collecting data using an IoT sensor network. The system analyzes real-time data using NBC. These predictive capabilities reduce the potential of hydrant breakdowns during emergencies through preventive maintenance potential. It introduces a reliable IoT infrastructure for fire hydrant monitoring, improving the acquired data's granularity and timeliness. NBC provides a powerful instrument for early problem detection, significantly improving maintenance effectiveness. Since the technology is compatible with existing fire department procedures, it can easily integrate into current operational processes. Better public safety, more efficient use of resources, and more dependable fire hydrants are potential outcomes of responsive and proactive data-driven maintenance techniques. The findings improve overall fire safety and operational efficiency, with a 25% decrease in maintenance expenditures and a 40% increase in issue detection accuracy.

关键词： Accuracy Scalability Urban areas Real-time systems Maintenance Naive Bayes methods Internet of Things Stakeholders Predictive maintenance Risk mitigation

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Role assignment for spatially-correlated data aggregation using multi-sink internet of underwater things

Role assignment for spatially-correlated data aggregation us...

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作者： Al-Habob, Ahmed A. Dobre, Octavia A. Poor, H. Vincent Faculty of Engineering and Applied Science Memorial University St. John'sNLA1B 3X5 Canada Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

In this paper, we consider a multi-sink underwater data aggregation network, in which a set of Internet-of-Underwater-Things devices survey an underwater area of interest and upload their data to a set of data gathering stations. A device-role assignment framework is provided, which captures the network topology and allows multi-hop data aggregation. In this framework, an optimization problem is formulated with the objective of maximizing the uncorrelated data at the gathering stations with minimal energy consumption. The optimization problem is constrained over binary coupled role assignment, inter-device, and device-station association decision variables. An ant colony optimization (ACO) algorithm is developed to tackle the complexity of the optimization problem and find optimized solutions. Simulation results illustrate that the proposed ACO algorithm provides performance close to the optimal solution, which is obtained through exhaustive search. Results also show that the proposed framework aggregates more uncorrelated data and preserves more energy compared to a baseline approach, where the devices transmit raw data to the stations directly. © 2017 IEEE.

关键词： Ant colony optimization

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Active photonic molecules based on ring quantum cascade lasers

Active photonic molecules based on ring quantum cascade lase...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Theodore P. Letsou Dmitry Kazakov Nikola Opačak Maximilian Beiser Sandro Dal Cin Benedikt Schwarz Federico Capasso Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Institute of Solid State Electronics TU Wien Vienna Austria

Photonic molecules are the optical analog of chemical molecules: two or more strongly coupled optical resonators. Here, we present a new class of active photonic molecules based on ring quantum cascade lasers.

ISBN: (纸本)9781957171258

关键词： Coupled resonators Laser sources Molecules Q factor Quantum cascade semiconductor lasers Ring resonators

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Application of Neural Networks and Genetic Algorithms in Establishing Logical Rules for Evaluating the Edibility of Mushroom Data 2nd

Application of Neural Networks and Genetic Algorithms in ...

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2nd International Conference on Advanced Communication and Intelligent Systems, ICACIS 2023

作者： Johri, Ishita Nallakaruppan, Musiri Kailasanathan Balusamy, Balamurugan V, Geetha Grover, Veena School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Noida India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Management Noida Institute of Engineering and Technology Greater Noida India

ISBN: (纸本)9783031451201

The cultivation of mushrooms for commercial purposes has had a notable impact on the global economy, as evident from recent agricultural data. The mushroom industry is rapidly becoming one of the most lucrative industries in India and around the globe. This has led to a rise in popularity of mushroom farms and cultivation. The objective of this study is to determine the logical rules for edibility of mushrooms based on 22 biological characteristics. To achieve this goal, two different approaches were utilized. The first approach involved using Back Propagation Neural Networks that were constructed using data mining techniques. This method is distinct from a simple Decision Tree as it doesn’t require listing rules one by one. The cost function of the neural networks is based on the standard MSE (mean square error) plus a convergence controller. The Neural Network can be perceived as a tree-like logical graph, with a weight of 1 representing a strong positive correlation, −1 indicating a strong negative correlation, and 0 signifying no correlation. As a result, the top 4 logical rules account for every possible outcome based on most coverage. In the second approach, a Decision Tree is combined with a Genetic Algorithm (GA) for feature selection. The accuracy of the decision tree, which is constructed from the GA’s feature selections, feeds back into the GA’s fitness function. This method provides an alternative way of identifying edible mushrooms based on their biological characteristics. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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THE SECOND-ORDER ZERO DIFFERENTIAL SPECTRA OF SOME FUNCTIONS OVER FINITE FIELDS

arXiv

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arXiv 2023年

作者： Garg, Kirpa Hasan, Sartaj Ul Riera, Constanza Stănică, Pantelimon Department of Mathematics Indian Institute of Technology Jammu Jammu 181221 India Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen5020 Norway Applied Mathematics Department Naval Postgraduate School MontereyCA93943 United States

It was shown by Boukerrou et al. [IACR Trans. Symmetric Cryptol. 1 (2020), 331–362] that the F -boomerang uniformity (which is the same as the second-order zero differential uniformity in even characteristic) of perfect nonlinear functions is 0 on Fpn (p prime) and the one of almost perfect nonlinear functions on F2n is 0. It is natural to inquire what happens with APN or other low differential uniform functions in even and odd characteristics. Here, we explicitly determine the second-order zero differential spectra of several maps with low differential uniformity. In particular, we compute the second-order zero differential spectra for some almost perfect nonlinear (APN) functions over finite fields of odd characteristic, pushing further the study started in Boukerrou et al. and continued in Li et al. [Cryptogr. Commun. 14.3 (2022), 653–662], and it turns out that our considered functions also have low second-order zero differential uniformity. Moreover, we study the second-order zero differential spectra of certain functions with low differential uniformity over finite fields of even characteristic. We connect this new concept to the sum-freedom and vanishing flats concepts and find some counts for the number of vanishing flats via our methods. We provide detailed analyses on several equations over finite fields that may have an interest outside of the scope of our *** Codes 12E20, 11T06, 94A60 Copyright © 2023, The Authors. All rights reserved.

关键词： Nonlinear simulations

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Multi-Instance Task in Swarm Robotics: Sorting Groups of Robots or Objects into Clusters with Minimalist Controllers

Multi-Instance Task in Swarm Robotics: Sorting Groups of Rob...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Adilson Krischanski Yuri K. Lopes Andre B. Leal Ricardo F. Martins Roberto S.U. Rosso Department of Computer Science Santa Catarina State University (UDESC) Joinville Brazil Graduate Program in Applied Computing (PPGCAP) UDESC Brazil Department of Electrical Engineering Santa Catarina State University (UDESC) Joinville Brazil

Relying only on behaviors that emerge from simple responsive controllers; swarms of robots have been shown capable of autonomously aggregate themselves or objects into clusters without any form of communication. We push these controllers to the limit, requiring robots to sort themselves or objects into different clusters. Based on a responsive controller that maps the current reading of a line-of-sight sensor to a pair of speeds for the robots' differential wheels, we demonstrate how multiple tasks instances can be accomplished by a robotic swarm. Using the dividing rectangles approach and physics simulation, a training step optimizes the parameters of the controller guided by a fitness function. We conducted a series of systematic trials in physics-based simulation and evaluate the performance in terms of dispersion and the ratio of clustered robots/objects. Across 20 trials where 30 robots cluster themselves into 3 groups, an average of 99.83% of them were correctly clustered into their group after 300 s. Across 50 trials where 15 robots cluster 30 objects into 3 groups, an average of 61.20%, 82.87%, and 97.73% of objects were correctly clustered into their group after 600 s, 900 s, and 1800 s, respectively. The object cluster behavior scales well while the aggregation does not, the latter due to the requirement of control tuning based on the number of robots.

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BAG2 Assisted Hierarchical Analog Layout Synthesis for Planar Technologies

BAG2 Assisted Hierarchical Analog Layout Synthesis for Plana...

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Austrian Workshop on Microelectronics (Austrochip)

作者： Matthew Bio Wolfgang Scherr A. S. Agbemenu Santiago Martin Sondón Johannes Sturm Vinayak Hande Josef Ressel Centre for System-on-Chip Design Automation Carinthia Institute for Microelectronics Carinthia University of Applied Sciences Department of Computer Engineering Kwame Nkrumah University of Science and Technology Kumasi Ghana Department of Integrated Systems and Circuit Design Carinthia University of Applied Sciences Villach Austria

Analog circuit design automation remains an intense area of attention and has seen both new and existing tools continued to be developed targeting different phases of the analog design flow to reduce development time and cost. One of the promising tools is the Berkeley analog generator (BAG2) framework which is an open-source analog layout generator for automating and verifying circuit layouts. It promises a process-independent flow as well as encourages design re-use due to using parameterized generators which can be scaled as required and this reduces the layout-development time compared to manual hand-made layouts. This work describes the effort and results of evaluating the BAG2 framework for the TSMC 65nm and Cadence GPDK 45nm processes. A case study is made with a number of circuits to discuss the problems in setting up and using BAG2 for the above technologies as well as the limitations and solutions required to utilize the framework effectively.

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Scheme Invisible Internet Protocol (I2P) using Blockchain techniques for tracking Darkweb User Activities 4

Scheme Invisible Internet Protocol (I2P) using Blockchain te...

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4th IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2021

作者： Rajawat, Anand Singh Barhanpurkar, Kanishk Mukhopadhyay, Debajyoti Ghosh, Ankush SVVV Department of CSE Indore India Sambhram Institute of Technology Department of CSE Bengaluru India Bennett University Dept of Computer Science Engineering Greater Noida India School of Engineering and Applied Sciences The Neotia University West Bengal India

ISBN: (纸本)9781728199511

The classic example of shared hidden data transformation is the Invisible Internet Protocol (I2P), which works with Tor web-net and make incognito relay confidential. The I2P offers an outstanding possibility for people seeking anonymity to circumvent authoritarian regimes. It can also be troublesome in corporate environments where I2P-routers over-use restricted web-net assets or provide a means for malware to exfiltrate information. In this research paper, the authors discussed the IDS possibility to track I2P web-net congestion and associate peers positively is done. Additionally, the authors given context details on the internal mechanisms of I2P, and showed the ways to recognize I2P routers throughout the bootstrapping process. The development and review of the new system is of the current state of the art. We intend to introduce Blockchain techniques for tracking Darkweb User Activities on a trust computational web-net to improve data protection in transparent blockchains (BC). © 2021 IEEE.

关键词： Internet protocols

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Green Leaf Disease Detection Using Raspberry Pi and Random Forest Machine Learning Algorithm: An Automated Approach for Precision Agriculture

Green Leaf Disease Detection Using Raspberry Pi and Random F...

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International Conference on Smart Computing & Communications (ICSCC)

作者： Chitra Sabapathy Ranganathan Amjath Ali Jakul Basha A Vijayalakshmi N. Mohankumar S. Sujatha C. Sasikala Mphasis Corporation Chennai Tamil Nadu India Department of Engineering Computer Engineering Electrical and Electronic Section University of Technology and Applied Sciences Ibra Sultanate of Oman Department of Computer Science and Engineering Chennai Institute of Technology Chennai Tamil Nadu India Symbiosis Institute of Technology Symbiosis International (Deemed University) Nagpur Maharashtra India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Electronics and Communication Engineering Sri Sai Ranganathan Engineering College Coimbatore Tamil Nadu India

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

Farm production and food security are affected by green leaf diseases. Modern disease detection technologies may discover plant health issues early. This work uses Raspberry Pi, a cheap and flexible single-board computer, along the advanced Random Forest machine learning technique to identify a green leaf disease. To identify crop diseases, the study uses automated, non-invasive technologies. From labeled images of good and sickly leaves, the algorithm extracts color histograms and texture, and form. It feeds a Random Forest classifier these properties for classifying data with high dimensions. Several green leaf diseased plant species were examined. This method detected plant health concerns with high precision. Movement and low cost make the Raspberry Pi ideal for remote and resource-limited agriculture, increasing farming accuracy. Helping farmers and users identify and develop green leaf diseases improves efficient farming. This methodology has the potential to improve crop management, optimize pesticide usage, and increase agricultural productivity. These results might contribute to the development of advanced automatic disease detection techniques to address green leaf diseases in modern agriculture.

关键词： Productivity Precision agriculture Machine learning algorithms Accuracy Plants (biology) Crops Real-time systems Random forests Diseases Farming

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Preparation of ultrafast ammonia sensor based on cross-linked ZnO nanorods coated with poly(3-hexylthiophene)

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Synthetic Metals 2023年第1期299卷

作者： Han, Kai-Xu Wu, Chia-Ching Hsu, Wei-Fan Chien, Wei Yang, Cheng-Fu Education Department of Guangxi Zhuang Autonomous Region Qinzhou535011 China Department of Applied Science National Taitung University Taitung95092 Taiwan Department of Chemical and Materials Engineering National University of Kaohsiung Kaohsiung811726 Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City333 Taiwan Department of Aeronautical Engineering Chaoyang University of Technology Taichung413310 Taiwan

A gas sensing device was fabricated using poly(3-hexylthiophene) (P3HT)-coated ZnO nanorods, and the ammonia (NH3) gas-sensing properties of the heterojunction device were analyzed. Hexagonal ZnO nanorods were prepared using the hydrothermal method on a ZnO seed layer. The ZnO seed layer was deposited using the sputtering method on a Ti–Pt bilayer interdigital electrode. X-ray diffraction and field emission scanning electron microscopy characterized the crystal structure and morphology of the ZnO–P3HT nanorods heterojunction devices. The gas-sensing properties of the P3HT–ZnO nanorods heterojunction sensor were examined and compared with different concentrations of NH3 gas. The response and recovery times were less than 1.5 s with a NH3 gas concentration of 1 ppm. Comparison with sensors of other materials indicated that P3HT was the reason for the short response and recovery times. Plausible mechanisms explaining the enhanced NH3 selectivity of the P3HT–ZnO nanorods heterojunction structure are discussed. © 2023

关键词： Zinc oxide

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