Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (22,098)
  • Open Access

    ARTICLE

    Research on Public Opinion Propagation Model in Social Network Based on Blockchain

    Gengxin Sun1,*, Sheng Bin1, Meng Jiang2, Ning Cao3, Zhiyong Zheng4, Hongyan Zhao5, Dongbo Wang6, Lina Xu7

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1015-1027, 2019, DOI:10.32604/cmc.2019.05644

    Abstract With the emergence and development of blockchain technology, a new type of social networks based on blockchain had emerged. In these social networks high quality content creators, filters and propagators can all be reasonably motivated. Due to the transparency and traceability brought by blockchain technology, the public opinion propagation in such social networks presents new characteristics and laws. Based on the theory of network propagation and blockchain, a new public opinion propagation model for this kind of social network based on blockchain technology is proposed in this paper. The model considers the effect of incentive mechanism produced by reasonably quantifying… More >

  • Open Access

    ARTICLE

    A Recommendation System Based on Fusing Boosting Model and DNN Model

    Aziguli Wulam1,2, Yingshuai Wang1,2, Dezheng Zhang1,2,*, Jingyue Sang3, Alan Yang4

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1003-1013, 2019, DOI:10.32604/cmc.2019.07704

    Abstract In recent years, the models combining traditional machine learning with the deep learning are applied in many commodity recommendation practices. It has been proved better performance by the means of the neural network. Feature engineering has been the key to the success of many click rate estimation model. As we know, neural networks are able to extract high-order features automatically, and traditional linear models are able to extract low-order features. However, they are not necessarily efficient in learning all types of features. In traditional machine learning, gradient boosting decision tree is a typical representative of the tree model, which can… More >

  • Open Access

    ARTICLE

    Research on Sensor Network Coverage Enhancement Based on Non-Cooperative Games

    Chaofan Duan1, Jing Feng1,*, Haotian Chang1, Jianping Pan2, Liming Duan1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 989-1002, 2019, DOI:10.32604/cmc.2019.06033

    Abstract Coverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an exact potential game in which… More >

  • Open Access

    ARTICLE

    GaiaWorld: A Novel Blockchain System Based on Competitive PoS Consensus Mechanism

    Rui Song1, Yubo Song1,*, Ziming Liu2, Min Tang2, Kan Zhou3

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 973-987, 2019, DOI:10.32604/cmc.2019.06035

    Abstract The birth of blockchain has promoted the development of electronic currencies such as Bitcoin and Ethereum. Blockchain builds a financial system based on cryptology instead of credit, which allows parties to complete the transaction on their own without the need for credible third-party intermediaries. So far, the application scenario of blockchain is mainly confined to the peer-to-peer electronic financial system, which obviously does not fully utilize the potential of blockchain.
    In this paper, we introduce GaiaWorld, a new system for decentralized application. To solve the problem of resource waste and mismatch between nodes and computing power in traditional PoW… More >

  • Open Access

    ARTICLE

    An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles

    Belghachi Mohammed1,*, Debab Naouel1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 959-972, 2019, DOI:10.32604/cmc.2019.07580

    Abstract A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with… More >

  • Open Access

    ARTICLE

    High Precision SAR ADC Using CNTFET for Internet of Things

    V. Gowrishankar1,*, K. Venkatachalam1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 947-957, 2019, DOI:10.32604/cmc.2019.07749

    Abstract A high precision 10-bit successive approximation register analog to digital converter (ADC) designed and implemented in 32nm CNTFET process technology at the supply of 0.6V, with 73.24 dB SNDR at a sampling rate of 640 MS/s with the average power consumption of 120.2 μW for the Internet of things node. The key components in CNTFET SAR ADCs are binary scaled charge redistribution digital to analog converter using MOS capacitors, CNTFET based dynamic latch comparator and simple SAR digital code error correction logic. These techniques are used to increase the sampling rate and precision while ensuring the linearity, power consumption and… More >

  • Open Access

    ARTICLE

    Failure Prediction, Lead Time Estimation and Health Degree Assessment for Hard Disk Drives Using Voting Based Decision Trees

    Kamaljit Kaur1, *, Kuljit Kaur2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 913-946, 2019, DOI:10.32604/cmc.2019.07675

    Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the gradual change/deterioration of HDDs; they… More >

  • Open Access

    ARTICLE

    Localization Based Evolutionary Routing (LOBER) for Efficient Aggregation in Wireless Multimedia Sensor Networks

    Ashwinth Janarthanan1,*, Dhananjay Kumar1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 895-912, 2019, DOI:10.32604/cmc.2019.06805

    Abstract Efficient aggregation in wireless sensor nodes helps reduce network traffic and reduce energy consumption. The objective of this work Localization Based Evolutionary Routing (LOBER) is to achieve global optimization for aggregation and WMSN lifetime. Improved localization is achieved by a novel Centroid Based Octant Localization (CBOL) technique considering an arbitrary hexagonal region. Geometric principles of hexagon are used to locate the unknown nodes in the centroid positions of partitioned regions. Flower pollination algorithm, a meta heuristic evolutionary algorithm that is extensively applied in solving real life, complex and nonlinear optimization problems in engineering and industry is modified as Enhanced Flower… More >

  • Open Access

    ARTICLE

    Dynamic Analysis of a Horizontal Oscillatory Cutting Brush

    Libardo V. Vanegas-Useche1,4, Magd M. Abdel-Wahab2,3,*, Graham A. Parker5

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 871-893, 2019, DOI:10.32604/cmc.2019.06480

    Abstract Street sweeping is an important public service, as it has an impact on aesthetics and public health. Typically, sweeping vehicles have a gutter brush that sweeps the debris that lies in the road gutter. As most of the debris is located in the gutter, the effective operation of the gutter brush is important. The aim of this work is to study the performance of a type of gutter brush, the cutting brush, through a 3D dynamic (transient), large deflection finite element model developed by the authors. In this brush model, the brush mounting board is modelled as fixed, and, consequently,… More >

  • Open Access

    ARTICLE

    Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

    B. V. Santhosh Krishna1, *, T. Gnanasekaran2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 855-869, 2019, DOI:10.32604/cmc.2019.07585

    Abstract An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction… More >

Displaying 21511-21520 on page 2152 of 22098. Per Page