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2019 International Conference on Advances in Computing and Communication engineering, ICACCE 2019

作者： Sathesh Kumar, K. Arun Kumar, R. Praveen Kumar, V. Bannari Amman Institute of Technology Dept. of Information Technology Sathyamangalam Erode Tamilnadu India MAM College of Engineering and Technology Dept. of Information Technology Siruganour Tirchy Tamilnadu India

ISBN: (纸本)9781728132501

The yield estimation in agricultural field plays a vital role for the better utilization of resources and to enhance total yield per unit area within the time. The yield estimation of fruit is currently computed manually which leads to labour extensive and also expensive. It also takes much time for yield estimation. This manual sampling may also results in imprecise yield calculation. This makes the demand in machine vision based systems to address the above mentioned problem in detecting the yield estimation and thus reduces the error in counting the number of fruits on each tree. The multilayer CNN proposed here is used to classify the fruit from the tree image and also gives better result even in case of diminished images. Overlapped fruits also counted separately to give better result. © 2019 IEEE.

关键词： Fruits

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A Symmetric Encryption Scheme With Multi User Searchable Options in the Cloud Based Applications

A Symmetric Encryption Scheme With Multi User Searchable Opt...

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International Conference on Emerging Research in Electronics, Computer Science and technology (ICERECT)

作者： Abhishek Dubey Vijay Kumar Priyank Singhal Savyasachi Atowar ul Islam R Kuppuchamy Department of CSE Chandigarh Engineering College Jhanjeri India Department of CSE JAIN University Bangalore India Department of Computing Sciences & IT Mahaveer University Moradabad India Department of information technology Lalit Narayan Mishra College of Business Management Muzaffarpur Bihar Dept. of Computer Science and Electronics University of Science and Technology Techno City Meghalaya Department of Computer Applications PSNA College of Engineering and Technology Dindigul India

Scientists in academia and business have thoroughly studied Encryption Scheme (SE). Whereas many scientific SE methods provide verifiable confidentiality, in order to attain high performance, they typically reveal certain “trans (such as search and access patterns). Yet, a number of infer methods have taken advantage of this leaking, for instance, a query recovering attack that uses foreknowledge to convert transparent question passageways to their matching keywords. But at the other hand, several more pro - posed SE schemes require substantial modification applications, that also tends to make them less convenient, weak in user experience, and complicated to deploy. In this research, we offer IDCrypt, a safe and useful Is the Enclosure (SSE) scheme with demonstrable security power for azure. IDCrypt uses cryptographic techniques to increase SE's security level and search efficiency. We also highlight the key difficulties in safely sharing decrypted data across different individuals and search across several indexes. We suggest a coin search strategy to maintain the search features across several indexes or a key sharing system that combines Personality Crypto (IBE) with Community Encrypted data to solve the aforementioned problems (PKE). Our empirical findings demonstrate that the number of key agreement's expense is rather modest.

关键词： Computer science Protocols Art Benchmark testing Search problems User experience Encryption

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A New realization of Multidimensional Fornasini-Marchesini II State-space Model for MIMO Radar

A New realization of Multidimensional Fornasini-Marchesini I...

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Chinese control and Decision Conference, CCDC

作者： Liu Chang Cheng Hua Zhongyong Cao Dept. of Information Science and Engineering Wuhan University of Science and Technology Wuhan

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In this paper, a new algorithm of solving the system realization matrix is proposed for the target detection of multi-input and multi-output radar. The algorithm is based on one-dimensional array with F-M II model to solve the implementation problem of system state space model. By setting a one-dimensional array, the array is substituted into the transfer function which is obtained by the state space model. This method is used to make the complexity of the implementation process of the system lower, and is beneficial to the analysis and design of the system. Compared with the existing image algorithms, the middle chart transformation link is omitted, the calculation step is simplified, and the realization of multi-dimensional F-M II model is more convenient and efficient. The application of this algorithm to the MIMO radar system can improve the analysis efficiency of the system.

关键词： MIMO radar Mathematical model Object detection Radar detection Transfer functions Multidimensional systems

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Enabling Conditions for the Deployment of Integrated Local Energy Communities in Europe

Enabling Conditions for the Deployment of Integrated Local E...

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Blockchain for Renewables Integration (BLORIN), Workshop on

作者： Martina Caliano Amedeo Buonanno Marialaura Di Somma Giorgio Graditi Christina Papadimitriou Chrysanthos Charalambous Przemysław Dopierała Leszek Bronk Dept. of Energy Technologies and Renewable Energy Sources ENEA Portici NA Italy Electrical Engineering dpt. Eindhoven University of Technology (TU/e) Eindhoven The Netherlands Department of Electrical and Computer Engineering University of Cyprus FOSS Research Centre for Sustainable Energy Nicosia Cyprus Department of Control Information and Communications Instytut Energetyki - Instytut Badawczy Gdansk Poland Department of Strategy and System Development Instytut Energetyki - Instytut Badawczy Gdansk Poland

ISBN: (纸本)9781665472500

The main goal of eNeuron H2020 project (Nov 2020-Oct. 2024, ID: 957779) is to develop innovative tools for the optimal design and operation of local energy communities, integrating distributed energy resources and multiple energy carriers at different scales. This paper presents a review study of the enabling conditions for the deployment of integrated local energy communities (ILECs) in Europe, performed within the project. The enabling conditions are addressed by defining the key actors and their interests in the implementation of an energy community at local level and through a detailed mapping of the enabling and emerging energy and information and communication technologies at both household and community levels. Special focus is also on mapping of the demand-side flexibility technologies to understand the benefits of local flexibility and impacts on the larger systems. In such analysis, the key issues for implementation and adaptation of this new energy paradigm are investigated through covering technological, socio-economic, environmental, and regulatory aspects.

关键词： Renewable energy sources Conferences Europe information and communication technology Distributed power generation Blockchains

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Correlating the Effect of Covid-19 Lockdown with Mobility Impacts: A Time Series Study Using Noise Sensors Data

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Transportation Research Procedia 2022年 62卷 115-122页

作者： Antonio Pascale Simona Mancini Pedro M. d’Orey Claudio Guarnaccia Margarida C. Coelho Centre for Mechanical Technology and Automation Dept. of Mechanical Engineering University of Aveiro Campus Universitário de Santiago 3801-193 Aveiro Portugal Department of Information and Electric Engineering and Applied Mathematics University of Salerno Via Giovanni Paolo II 132 I-84084 Fisciano Italy Real-Time and Embedded Computing Systems Research Centre (CISTER) ISEP IPP Rua Dr. António Bernardino de Almeida 431 4200-072 Porto Portugal Dept. of Civil Engineering University of Salerno Via Giovanni Paolo II 132 I-84084 Fisciano Italy

The Covid-19 crisis forced governments around the world to rapidly enact several restrictions to face the associated health emergency. The Portuguese government was no exception and, following the example of other countries, established various limitations to flat the contagions curve. This led to inevitable repercussions on mobility and environmental indicators including noise. This research aims to assess the impact of the lockdown due to Covid-19 disease on the noise levels recorded in the city of Porto, Portugal. Data from four noise sensors located in strategic spots of the city were used to calibrate and validate Time Series Models, allowing to impute the missing values in the datasets and rebuild them. The trend and the cyclic information were extracted from the reconstructed datasets using decomposition techniques. Finally, a Spearman correlation analysis between noise levels values and traffic volumes (extracted from five inductive loop detectors, located nearby the noise sensors) was performed. Results show that the noise levels series present a daily seasonal pattern and the trends values decreased from 6.7 to 7.5 dBA during the first lockdown period (March-May 2020). Moreover, the noise levels tend to gradually rise after the removal of restrictions. Finally, there is a monotonic relationship between noise levels and traffic volumes values, as confirmed by the positive moderate-to-high correlation coefficients found, and the sharp drop of the former during March-May 2020 can be attributed to the strong reduction of road traffic flows in the city.

关键词： Traffic Noise Time Series Models Covid-19 Inductive Loops

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Small Area Fingerprint Verification using Deep Convolutional Neural Network

Small Area Fingerprint Verification using Deep Convolutional...

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Intelligent engineering and Management (ICIEM), International Conference on

作者： Nabilah Shabrina Dongju Li Tsuyoshi Isshiki Dept. of Information and Communications Engineering Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9781728140971

ISBN: (纸本)9781728140988

This paper presents a solution for a small area (partial-to-partial) fingerprint verification, which is suitable for mobile devices with small fingerprint sensors. Since images captured from the fingerprint sensor contain very limited minutiae features and less image overlapping areas between the input image and the template image, the minutiae-based method is hardly used. We propose a new approach that consists of two steps:(l) fingerprint alignment using band-limited phase-only correlation (BLPOC) and (2) fingerprint matching using deep convolutional neural network (DCNN). To handle the large displacement between two fingerprints, we added both preprocessing and post-processing steps to make the fingerprint alignment process more robust. The experiment results show that the proposed method achieves better performances compared to other methods.

关键词： DH-HEMTs

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InfiniWolf: Energy Efficient Smart Bracelet for Edge Computing with Dual Source Energy Harvesting

InfiniWolf: Energy Efficient Smart Bracelet for Edge Computi...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Michele Magno Xiaying Wang Manuel Eggimann Lukas Cavigelli Luca Benini Dept. of Information Technology and Electrical Engineering ETH Zürich Switzerland

ISBN: (数字)9783981926347

ISBN: (纸本)9781728144689

This work presents InfiniWolf, a novel multi-sensor smartwatch that can achieve self-sustainability exploiting thermal and solar energy harvesting, performing computationally high demanding tasks. The smartwatch embeds both a System-on-Chip (SoC) with an ARM Cortex-M processor and Bluetooth Low Energy (BLE) and Mr. Wolf, an open-hardware RISC-V based parallel ultra-low-power processor that boosts the processing capabilities on board by more than one order of magnitude, while also increasing energy efficiency. We demonstrate its functionality based on a sample application scenario performing stress detection with multi-layer artificial neural networks on a wearable multi-sensor bracelet. Experimental results show the benefits in terms of energy efficiency and latency of Mr. Wolf over an ARM Cortex-M4F micro-controllers and the possibility, under specific assumptions, to be self-sustainable using thermal and solar energy harvesting while performing up to 24 stress classifications per minute in indoor conditions.

关键词： Wearable computers Stress Sensors Feature extraction Neurons Task analysis Batteries

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Intelligent Monitoring Systems for Transportation of Perishable Products based Internet of Things (IoT) technology

Intelligent Monitoring Systems for Transportation of Perisha...

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： M.Hossein Ahmadzadegan M.Saeed Mohammadzadeh Ghazaleh Eftekharnejad Hamidreza Ghorbani Dept. Electrical Engineering and Information Technology Azad University of Tehran Iran

ISBN: (数字)9781728149769

ISBN: (纸本)9781728149776

For the past decade, one of the most important challenges for human societies has been the impact of food on human health. European countries, and in particular the European Union, have established laws and standards to address this challenge by allowing them to track and monitor foodstuffs in during the production chain until consumption. By enforcing these rules, the European Union has obliged food and feed operators to set up tracking and monitoring systems for their products. One of the most important parts of these systems is the transportation chain. The transportation of food from origin of production to consumption destination is very important. And must provide traceability for food quality control and health. One of the new technologies that has enabled human societies to make food products traceable to humans is the Internet of Things (IoT). That has brought together manufacturers, transport systems, retailers and consumers of food. In this paper, we propose a cost effective way to enable real-time food tracking and monitoring.

关键词： Food monitoring Transportation Internet of Things Raspberry Pi transport Internet of things Food food monitoring Intelligent monitoring system Internets monitoring systems

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The state-of-the-art review on resource allocation problem using artificial intelligence methods on various computing paradigms

arXiv

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arXiv 2022年

作者： Joloudari, Javad Hassannataj Mojrian, Sanaz Saadatfar, Hamid Nodehi, Issa Fazl, Fatemeh Shirkharkolaie, Sahar Khanjani Alizadehsani, Roohallah Dipu Kabir, H.M. Tan, Ru-San Rajendra Acharya, U. Department of Computer Engineering Faculty of Engineering University of Birjand Birjand*** Iran Department of Information Technology Mazandaran University of Science and Technology Babol Iran Department of Computer Engineering Qom University of Technology Qom Iran Department of Electronic Engineering Faculty of Electrical and Computer Engineering University of Birjand Birjand Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia School of Science and Technology Singapore University of Social Sciences Singapore Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan

With the increasing growth of information through smart devices, increasing the quality level of human life requires various computational paradigms presentation including the Internet of Things, fog, and cloud. Between these three paradigms, the cloud computing paradigm as an emerging technology adds cloud layer services to the edge of the network so that resource allocation operations occur close to the end-user to reduce resource processing time and network traffic overhead. Hence, the resource allocation problem for its providers in terms of presenting a suitable platform, by using computational paradigms is considered a challenge. In general, resource allocation approaches are divided into two methods, including auction-based methods (goal, increase profits for service providers-increase user satisfaction and usability) and optimization-based methods (energy, cost, network exploitation, Runtime, reduction of time delay). In this paper, according to the latest scientific achievements, a comprehensive literature study (CLS) on artificial intelligence methods based on resource allocation optimization without considering auction-based methods in various computing environments are provided such as cloud computing, Vehicular Fog Computing, wireless, IoT, vehicular networks, 5G networks, vehicular cloud architecture, machine-to-machine communication (M2M), Train-to-Train(T2T) communication network, Peer-to-Peer (P2P) network. Since deep learning methods based on artificial intelligence are used as the most important methods in resource allocation problems;Therefore, in this paper, resource allocation approaches based on deep learning are also used in the mentioned computational environments such as deep reinforcement learning, Q-learning technique, reinforcement learning, online learning, and also Classical learning methods such as Bayesian learning, Cummins clustering, Markov decision process. © 2022, CC BY-SA.

关键词： Reinforcement learning

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Object-based normalized-cuts for high-resolution polsar image segmentation

Object-based normalized-cuts for high-resolution polsar imag...

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2019 SAR in Big Data Era, BIGSARDATA 2019

作者： Xu, Xiaofang Zou, Bin Zhang, Lamei Harbin Institute of Technology Dept. of Information Engineering Harbin150001 China

ISBN: (纸本)9781728126531

As more and more high-resolution PolSAR images being available, effective methods need to be studied for the processing of high-resolution PolSAR images. Since the complexity and speckle noise in high-resolution PolSAR image, traditional pixel-based image segmentation methods can result in heavy salt-and-pepper noise and the segments won't be in accord with the edge in PolSAR images. Object-based image analysis (OBIA) methods have been proven to be effective for high-resolution images. In this paper, a novel object-based image segmentation method for high-resolution PolSAR image is proposed, combining the superpixel algorithm and Normalized-Cuts segmentation (NCuts). The proposed method first generates original objects using simple local iterative clustering (SLIC) which is a new superpixel algorithm;and then Ncuts segmentation is implemented on the original objects to obtain refined object segments and reduce the computational complexity. In addition, both spatial information and polarimetric information will be introduced in the proposed method. Experiments using EMISAR image show that the proposed method can better preserve the edges and homogeneous regions on the image. © 2019 IEEE.

关键词： Image segmentation

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