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arXiv 2021年

作者： Borrielli, Antonio Bonaldi, Michele Serra, Enrico Sarro, Pasqualina Maria Morana, Bruno Institute of Materials for Electronics and Magnetism IMEM-CNR Trento unit c/o Fondazione Bruno Kessler Via alla Cascata 56/C Povo TrentoIT-38123 Italy Dept. of Microelectronics and Computer Engineering ECTM DIMES Delft University of Technology Feldmanweg 17 Delft2628 CT Netherlands Trento Institute for Fundamental Physics and Application Povo Trento38123 Italy

Feedback-based control techniques are useful tools in precision measurements as they allow to actively shape the mechanical response of high quality factor oscillators used in force detection measurements. In this paper we implement a feedback technique on a high-stress low-loss SiN membrane resonator, exploiting the charges trapped on the dielectric membrane. A properly delayed feedback force (dissipative feedback) enables the narrowing of the thermomechanical displacement variance in a similar manner to the cooling of the normal mechanical mode down to an effective temperature Te f f. In the experiment here reported we started from room temperature and gradually increasing the feedback gain we were able to cool down the first normal mode of the resonator to a minimum temperature of about 124mK. This limit is imposed by our experimental set-up and in particular by the the injection of the read-out noise into the feedback. We discuss the implementation details and possible improvements to the technique. Copyright © 2021, The Authors. All rights reserved.

关键词： Resonators

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A Glimpse on Key applications of Smart City under M2M Communication

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IOP Conference Series: Materials Science and engineering 2021年第1期1022卷

作者： Sonam Kaushik Gaurav Aggarwal Sanjay Tejasvee Asst. Professor/Research Scholar Dept. of Engineering & Technology Gurugram Univ. Gurugram -122001-India Professor Dept. of Computer Science JIMS Bahadurgarh-124507-India Asst. Professor Computer Application Dept. Govt. Engineering College Bikaner 334004-India

In India, It is very necessary to make normal cities as smart cities near future. So, Develop a smart city is one of the most recent fields in today's digital era to researches. Machine to Machine (M2M ) communication is the latest innovative-fangled type of communiqué that enables full automation with the help of integrated applications to make a normal city to a smart city. Many devices are connected in a smart city to monitoring many tasks and it is a very challenging task to integrate and manage these connected devices. Interconnection of several devices and machines using the internet to form an M2M Area Network (M2MAN) provides controlling and monitoring smart applications like smart-metering, weather, environment, home, air quality, water supply with quality management, power supply with bill monitoring, traffic, and healthcare, etc. under M2M communication and integrated single level umbrella structured applications. Out of several M2M monitoring and controlling applications towards smart cities, few key applications are presented in this paper with their basic approach, workflow, and concerning issues and used technologies for the implementation with the brief growth analysis.

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Machine Learning Based Prediction of Long-Term Energy Consumption and Overheating Under Climate Change Impacts Using Urban Building Energy Modeling

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Sustainable Cities and Society 2025年

作者： Ilkim Canli Eren Gökberk Halacli Sevval Ucar Orcun Koral Iseri Feyza Yavuz Dilara Guney Fatma Ece Gursoy Ayca Duran Cagla Meral Akgul Sinan Kalkan Ipek Gursel Dino Dept. of Architecture Middle East Technical University Universiteler Mah Dumlupinar Bulvari No:1 06800 Ankara Turkiye Center for Solar Energy Research and Applications (METU-GÜNAM) Universiteler Mah Dumlupinar Bulvari No:1 06800 Ankara Turkiye Dept. of Computer Engineering Middle East Technical University Universiteler Mah Dumlupinar Bulvari No:1 06800 Ankara Turkiye Dept. of Civil Engineering Middle East Technical University Universiteler Mah Dumlupinar Bulvari No:1 06800 Ankara Turkiye Center for Robotics and Artificial Intelligence (METU-ROMER) Universiteler Mah Dumlupinar Bulvari No:1 06800 Ankara Turkiye Climate Change and Sustainable Development Application and Research Center (METU-CLIMATE) Universiteler Mah. Dumlupinar Bulvari No:1 06800 Ankara Turkiye

In cities, well-informed decisions targeting improved building energy performance under climate change impacts require tools that can make long-term projections and devise effective strategies. Physics-based Urban Building Energy Models (UBEM) can calculate building performance for future years; however, this process is challenging as (i) future weather files are generated only for discrete years, and (ii) physics-based simulations are computationally demanding, hindering the evaluation of a high number of buildings for all future years. Alternatively, machine learning (ML) approaches can offer high-precision estimations at a lower computational cost. In this paper, a UBEM-assisted ML-based approach that predicts residential buildings’ heating energy use and indoor overheating for the current and future years is proposed. A UBEM of a residential district is developed, and simulations are performed using weather files of the current year, 2050, and 2080 to develop training/testing datasets. Multi-layer perceptrons are trained to a very high predictive performance (with an R 2 score of 0.98 and 0.96 for the two output features), with a remarkable speed advantage (∼430 times faster than simulations). Finally, the results of the long-term analysis of three urban-scale retrofit scenarios are presented, which offers insights into the potential use of the proposed ML models.

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Investigation on agricultural land selection using hybrid fuzzy logic system ∗

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Scalable Computing 2020年第4期21卷 569-582页

作者： Sengan, Sudhakar Vijayakumar, V. Krishnamoorthy, Sujatha Gunasekaran, S. Kumar, C. Sathiya Palani, Saravanan Subramaniyaswamy, V. Department of CSE Sree Sakthi Engineering College Coimbatore641 104 India School of Computer Science and Engineering University of New South Wales Sydney Australia Department of Computer Science Wenzhou Kean University Wenzhou Zhejing China Dept. of Computer Application King College of Arts & Science Tiruchengode637 215 India Department of Computational Intelligence Vellore Institute of Technology Vellore India School of Computing SASTRA Deemed University Thanjavur India

For maintaining the horticultural generation, Land Selection Investigation (LSI) is essential. Though incorporates estimation of the criteria assortment from the soil, territory to financial, market, and foundation, and these components are considerably enigmatically characterized and described by their inherent ambiguity. Multi-criteria basic leadership systems like positioning, rating, and so on are utilized for reasonableness examination. Master learning and judgment by leaders at different levels is integrated into this process. In the field of farming sciences, the Fuzzy Logic (FL) strategy has been effectively used to take care of numerous issues. Fuzzy with AHP is a Hybrid Fuzzy Logic (HFL) methodology. The policies Analytic Hierarchy Process (AHP), Fuzzy Numbers, Fuzzy Degree Investigation, Alpha Cut, and Lambda capacity are associated with it. As expressed, the procedure of necessary leadership includes a scope of criteria and a considerable measure of master learning and decisions. The components result from impacts extraordinarily. The capacity of three methods to demonstrate the affectability of the necessary leadership procedure is researched. Alpha cut and lambda esteem give and encourage considerable affectability investigation. All techniques are actualized to examine the reasonableness of the crop in the Indian nation. Test results when performed on Various Datasets, demonstrate that the proposed procedure removes more highlights just as gives more exactness when contrasted with existing techniques. © 2020 SCPE.

关键词： Fuzzy logic

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The Complex Method of Intrusion Detection Based on Anomaly Detection and Misuse Detection

The Complex Method of Intrusion Detection Based on Anomaly D...

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IEEE International Conference on Dependable Systems, Services and Technologies (DESSERT)

作者： Tamara Radivilova Lyudmyla Kirichenko Abed Saif Alghawli Andrii Ilkov Maxim Tawalbeh Petro Zinchenko V.V. Popovskyy dept. of Infocommunication Engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Applied mathematics dept. Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Computer Science Prince Sattam Bin Abdulaziz University Aflaj Kingdom of Saudi Arabia Department of Combat Application of Radio Engineering Weapons Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

Intrusion detection is an important task on network cybersecurity. Intrusion detection systems solve this problem by using various methods. An analysis of the relevant works that offer possible solutions are presented, and a description of the proposed complex method that allows online identification of attacks is provided. The proposed complex method based on the joint application of the signature analysis method, entropy protocols analysis method, and machine learning method for behavior traffic analysis. The probability of intrusion detection used and based on the confusion matrix, the completeness, and the F-measure. There is a problem not only to detect the attacks but to identify the type of ones. Many attacks can be detected by using the proposed complex method, but also, this method allows to identify the type of attack and choose the type of defenses. The proposed complex method was compared to existing methods. Simulation results have shown that the proposed method better identifies attacks and has fewer false positives detections.

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Real-Time Vehicle Detection from Captured Images

Real-Time Vehicle Detection from Captured Images

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International Conference on Opto-Electronics and Applied Optics (IEM OPTRONIX)

作者： Soumen Santra Sanjit Roy Prosenjit Sardar Arpan Deyasi Department of Computer Application Techno International Newtown Kolkata India Dept. of Electronics and Communication Engineering RCC Institute of Information Technology Kolkata India

Objective of this paper is to primarily detect moving vehicles from real-time captured images so that we can later use them for a variety of purposes like detecting the number of vehicles that are present at a road at a certain point, understanding the motion of the vehicles, analyzing vehicle density at any traffic signal at any specified point of time; and based on our previous knowledge can make a good assumption where the vehicle will be heading towards. Signal-to-noise ratio, PSNER and mean-square-error are computed for each captured image using after detection. After establishing vehicle detection scheme, we can also make an attempt to read vehicle plate numbers further a much broader attempt to automate a traffic flow system using image recognition and probability distribution.

关键词： Real-time systems Signal to noise ratio Neural networks Vehicle detection Probability distribution Object detection Image color analysis

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A Study of Authentication Protocols in Internet of Things

A Study of Authentication Protocols in Internet of Things

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International Conference on Information Technology (ICIT)

作者： Amiya Kumar Sahu Suraj Sharma Shankar Sharan Tripathi Kamakhya Narain Singh Dept. of CSE International Institute of Information Technology Bhubaneswar India Dept. of CSE Sri Shankaracharya Engineering College Bhilai India School of Computer Application KIIT Deemed to be University Bhubaneswar India

ISBN: (数字)9781728160528

ISBN: (纸本)9781728160535

Internet of Things(IoT) is a promising technology in the current era, and security is one amongst the significant challenges in its success. The resource constraints in devices make the design and implementation of counter security mechanisms more challenging. Many attacks from an eavesdropper may endanger to authentication and lunch further attack to IoT systems. Hence, there is a need for an efficient authentication mechanism to withstand all possible known attacks. This study discusses the recent research on lightweight authentication protocols and compares them on various security parameters. In addition, the study also enumerates the various research issues related to the efficiency of authentication mechanisms in IoT. The study also discusses the possible solutions for authentication.

关键词： Authentication Protocols Internet of Things Tools Encryption

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An Analytical Model for WSN-MCN Convergence Network Based on Processor Sharing Scheduling

An Analytical Model for WSN-MCN Convergence Network Based on...

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2018 International Conference on Applied Electromagnetics, Signal Processing and Communication, AESPC 2018

作者： Swain, Anita Ray, Arun Kumar Swain, Prasanta Kumar KIIT Deemed to Be University School of Electronics Engineering Bhubaneswar India North Orissa University Dept. of Computer Application Baripada India

ISBN: (纸本)9781538683330

Advancement in ubiquitous techniques and the need of wide coverage network march towards convergence of networks. Mobile cellular network (MCN) is the largest network which can be the master network for this purpose and Wireless sensor network (WSN) can converge with MCN to form a single platform. As the world is moving towards machine to machine communication possibilities where WSN plays the major role. Hence there is a need to study the performances of the MCN-WSN convergence network. In this paper we have proposed an analytical model to accept the request from both WSN and MCN part and acceptances rate use certain probability to enter into a process at mobile node using processing sharing (PS) scheduling. The service rate is reduced to half of it's original rate to satisfy the processor sharing simultaneously for both WSN and MCN part. The performance factors like utilization, throughput is calculated and the analysis is done using graphs in numerical section. © 2018 IEEE.

关键词： Wireless sensor networks

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Reservation based Resource Allocation with Dynamic Admission Probability for WSN-MCN Convergence Network

Reservation based Resource Allocation with Dynamic Admission...

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2018 International Conference on Recent Innovations in Electrical, Electronics and Communication engineering, ICRIEECE 2018

作者： Swain, Anita Ray, Arun Kumar Kumar Swain, Prasanta Kalinga Institute of Industrial Technology School of Electronics Engineering Bhubaneswar India North Orissa University Dept. of Computer Application Baripada India

ISBN: (纸本)9781538659946

This Ubiquitous application of cell phones leads to an idea of using cell phones as a carrier of sensor data, which can create a larger network. This represents an idea of heterogeneous network such as cellular network and wireless sensor network to emerge as WSN-MCN convergence network. These mutually benefit both the network but the resource allocation that shares spectrum resources between cellular users and WSN user is critically challenging. We propose a reservation based resource sharing scheme that reserves a part of the spectrum for cellular users and rest part of the spectrum is dynamically allocated to users of both the network. An analytical model has been developed to determine various performance factors of the converged network in terms of channel allocation. The proposed model is compared with existing schemes and numerical results are presented in the form of graphs. © 2018 IEEE.

关键词： Resource allocation

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Faster RCNN Detection Based OpenCV CSRT Tracker Using Drone Data

Faster RCNN Detection Based OpenCV CSRT Tracker Using Drone ...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Xurshedjon Farhodov Oh-Heum Kwon Kyung Won Kang Suk-Hwan Lee Ki-Ryong Kwon Dept. of IT Convergence and Application Engineering Pukyong National University Busan South Korea Dept.of Computer Software Engineering Dongeui University Busan South Korea Dept. of Information & Communication Engineering Tongmyong University Busan South Korea Dept.of Information Security Tongmyong University Busan South Korea

ISBN: (数字)9781728125640

ISBN: (纸本)9781728125657

Object tracking is one of the well-known topic in computer Vision sphere with challenging and problematic tasks that frames come with problems like overlapping, camera motion blur, changing object appearance, environmental variations and so on. Using OpenCV based CSRT (Channel and Spatial Reliability Tracking) tracker itself, without integration object detection part may face problems which mentioned above. To overcome that challenges we integrated deep learning based object detection with CSRT tracker and got better tracking results.

关键词： Target tracking Object detection Object tracking Training Machine learning Reliability

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