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  • Open Access

    ARTICLE

    Analysis of the Efficiency-Energy with Regression and Classification in Household Using K-NN

    Qi Liu1,2, Zhiyun Yang1, Xiaodong Liu3, Scholas Mbonihankuye4,*

    Journal of New Media, Vol.1, No.2, pp. 101-113, 2019, DOI:10.32604/jnm.2019.06958

    Abstract This paper aims to study energy consumption in a house. Home energy man-agement system (HEMS) has become very important, because energy consumption of a residential sector accounts for a significant amount of total energy consumption. However, a conventional HEMS has some architectural limitations among dimensional variables reusability and interoperability. Furthermore, the cost of implementation in HEMS is very expensive, which leads to the disturbance of the spread of a HEMS. Therefore, this study proposes an Internet of Things (IoT) based HEMS with lightweight photovoltaic (PV) system over dynamic home area networks (DHANs), which enables the More >

  • Open Access

    ARTICLE

    A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

    Weijin Tan1,*, Yunqing Wu1, Peng Wu1, Beijing Chen1,2

    Journal of New Media, Vol.1, No.1, pp. 11-25, 2019, DOI:10.32604/jnm.2019.06219

    Abstract Digital images can be tampered easily with simple image editing software tools. Therefore, image forensic investigation on the authenticity of digital images’ content is increasingly important. Copy-move is one of the most common types of image forgeries. Thus, an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this paper. These methods are classified into three types: block-based methods, keypoint-based methods, and deep learning-based methods. In addition, the strengths and weaknesses of these methods are compared and analyzed in robustness and computational cost. Finally, further research directions More >

  • Open Access

    ARTICLE

    Anti-Noise Quantum Network Coding Protocol Based on Bell States and Butterfly Network Model

    Zhexi Zhang1, Zhiguo Qu1,2,*

    Journal of Quantum Computing, Vol.1, No.2, pp. 89-109, 2019, DOI:10.32604/jqc.2019.07415

    Abstract How to establish a secure and efficient quantum network coding algorithm is one of important research topics of quantum secure communications. Based on the butterfly network model and the characteristics of easy preparation of Bell states, a novel anti-noise quantum network coding protocol is proposed in this paper. The new protocol encodes and transmits classical information by virtue of Bell states. It can guarantee the transparency of the intermediate nodes during information, so that the eavesdropper Eve disables to get any information even if he intercepts the transmitted quantum states. In view of the inevitability More >

  • Open Access

    ARTICLE

    Quantum Multi-User Detection Based on Coherent State Signals

    Wenbin Yu1, 2, 3, 4, *, Yinsong Xu1, 2, 3, Wenjie Liu1, 2, 3, Alex Xiangyang Liu4, Baoyu Zheng5

    Journal of Quantum Computing, Vol.1, No.2, pp. 81-88, 2019, DOI:10.32604/jqc.2019.07324

    Abstract Multi-user detection is one of the important technical problems for modern communications. In the field of quantum communication, the multi-access channel on which we apply the technology of quantum information processing is still an open question. In this work, we investigate the multi-user detection problem based on the binary coherent-state signals whose communication way is supposed to be seen as a quantum channel. A binary phase shift keying model of this multi-access channel is studied and a novel method of quantum detection proposed according to the conclusion of the quantum measurement theory. As a result, More >

  • Open Access

    ARTICLE

    Crack Detection and Localization on Wind Turbine Blade Using Machine Learning Algorithms: A Data Mining Approach

    A. Joshuva1, V. Sugumaran2

    Structural Durability & Health Monitoring, Vol.13, No.2, pp. 181-203, 2019, DOI:10.32604/sdhm.2019.00287

    Abstract Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however, blade get damaged due to wind gusts, bad weather conditions, unpredictable aerodynamic forces, lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade. It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine. In this paper, a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades. The More >

  • Open Access

    ARTICLE

    Mechanical Behaviors and Deformation Properties of Retaining Wall Formed by Grouting Mould-Bag Pile

    Shengcai Li1,*, Jun Tang1,2, Lin Guo3

    Structural Durability & Health Monitoring, Vol.13, No.1, pp. 61-84, 2019, DOI:10.32604/sdhm.2019.06058

    Abstract The simplified mechanical model and finite element model are established on the basis of the measured results and analysis of the grouting pile deformation monitoring, surface horizontal displacement and vertical displacement monitoring, deep horizontal displacement (inclinometer) monitoring, soil pressure monitoring and seepage pressure monitoring in the lower reaches of Wuan River regulation project in Shishi, Fujian Province. The mechanical behavior and deformation performance of mould-bag pile retaining wall formed after controlled cement grouting in the silty stratum of the test section are analyzed and compared. The results show that the use of controlled cement grouting… More >

  • Open Access

    REVIEW

    Systems Neuroprotective Mechanisms in Ischemic Stroke

    Shu Q. Liu*

    Molecular & Cellular Biomechanics, Vol.16, No.2, pp. 75-85, 2019, DOI:10.32604/mcb.2019.06920

    Abstract Ischemic stroke, although causing brain infarction and neurological deficits, can activate innate neuroprotective mechanisms, including regional mechanisms within the ischemic brain and distant mechanisms from non-ischemic organs such as the liver, spleen, and pancreas, supporting neuronal survival, confining brain infarction, and alleviating neurological deficits. Both regional and distant mechanisms are defined as systems neuroprotective mechanisms. The regional neuroprotective mechanisms involve release and activation of neuroprotective factors such as adenosine and bradykinin, inflammatory responses, expression of growth factors such as nerve growth factors and neurotrophins, and activation and differentiation of resident neural stem cells to neurons… More >

  • Open Access

    ARTICLE

    Experimental Study of Aqueous Humor Flow in a Transparent Anterior Segment Phantom by Using PIV Technique

    Wenjia Wang1, 2, Xiuqing Qian1, 2, Qi Li1, 2, Gong Zhang1, 2, Huangxuan Zhao1, 2, Tan Li1, 2, Yang Yu1, 2, Hongfang Song1, 2, *, Zhicheng Liu1, 2, *

    Molecular & Cellular Biomechanics, Vol.16, No.1, pp. 59-74, 2019, DOI:10.32604/mcb.2019.06393

    Abstract Pupillary block is considered as an important cause of primary angle-closure glaucoma (PACG). In order to investigate the effect of pupillary block on the hydrodynamics of aqueous humor (AH) in anterior chamber (AC) and potential risks, a 3D printed eye model was developed to mimic the AH flow driven by fluid generation, the differential pressure between AC and posterior chambers (PC) and pupillary block. Particle image velocimetry technology was applied to visualize flow distribution. The results demonstrated obvious differences in AH flow with and without pupillary block. Under the normal condition (without pupillary block), the… More >

  • Open Access

    ARTICLE

    A Review on Deep Learning Approaches to Image Classification and Object Segmentation

    Hao Wu1, Qi Liu2, 3, *, Xiaodong Liu4

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595

    Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed More >

  • Open Access

    RETRACTION

    RETRACTED: Automatic Arrhythmia Detection Based on Convolutional Neural Networks

    Zhong Liu1,2, Xinan Wang1,*, Kuntao Lu1, David Su3

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 497-509, 2019, DOI:10.32604/cmc.2019.04882

    Abstract ECG signal is of great importance in the clinical diagnosis of various heart diseases. The abnormal origin or conduction of excitation is the electrophysiological mechanism leading to arrhythmia, but the type and frequency of arrhythmia is an important indicator reflecting the stability of cardiac electrical activity. In clinical practice, arrhythmic signals can be classified according to the origin of excitation, the frequency of excitation, or the transmission of excitation. Traditional heart disease diagnosis depends on doctors, and it is influenced by doctors' professional skills and the department's specialty. ECG signal has the characteristics of weak More >

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