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  • Open Access

    ARTICLE

    Machine Learning and Classical Forecasting Methods Based Decision Support Systems for COVID-19

    Ramazan Ünlü1, Ersin Namlı2, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1383-1399, 2020, DOI:10.32604/cmc.2020.011335

    Abstract From late 2019 to the present day, the coronavirus outbreak tragically affected the whole world and killed tens of thousands of people. Many countries have taken very stringent measures to alleviate the effects of the coronavirus disease 2019 (COVID-19) and are still being implemented. In this study, various machine learning techniques are implemented to predict possible confirmed cases and mortality numbers for the future. According to these models, we have tried to shed light on the future in terms of possible measures to be taken or updating the current measures. Support Vector Machines (SVM), Holt-Winters, Prophet, and Long-Short Term Memory… More >

  • Open Access

    ARTICLE

    On the Detection of COVID-19 from Chest X-Ray Images Using CNN-Based Transfer Learning

    Mohammad Shorfuzzaman1, *, Mehedi Masud1

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1359-1381, 2020, DOI:10.32604/cmc.2020.011326

    Abstract Coronavirus disease (COVID-19) is an extremely infectious disease and possibly causes acute respiratory distress or in severe cases may lead to death. There has already been some research in dealing with coronavirus using machine learning algorithms, but few have presented a truly comprehensive view. In this research, we show how convolutional neural network (CNN) can be useful to detect COVID-19 using chest X-ray images. We leverage the CNN-based pre-trained models as feature extractors to substantiate transfer learning and add our own classifier in detecting COVID-19. In this regard, we evaluate performance of five different pre-trained models with fine-tuning the weights… More >

  • Open Access

    ARTICLE

    Data Driven Modelling of Coronavirus Spread in Spain

    G. N. Baltas1, *, F. A. Prieto1, M. Frantzi2, C. R. Garcia-Alonso1, P. Rodriguez1, 3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1343-1357, 2020, DOI:10.32604/cmc.2020.011243

    Abstract During the late months of last year, a novel coronavirus was detected in Hubei, China. The virus, since then, has spread all across the globe forcing Word Health Organization (WHO) to declare COVID-19 outbreak a pandemic. In Spain, the virus started infecting the country slowly until rapid growth of infected people occurred in Madrid, Barcelona and other major cities. The government in an attempt to stop the rapssid spread of the virus and ensure that health system will not reach its capacity, implement strict measures by putting the entire country in quarantine. The duration of these measures, depends on the… More >

  • Open Access

    ARTICLE

    Intelligent Forecasting Model of COVID-19 Novel Coronavirus Outbreak Empowered with Deep Extreme Learning Machine

    Muhammad Adnan Khan1, *, Sagheer Abbas2, Khalid Masood Khan1, Mohammad A. Al Ghamdi3, Abdur Rehman2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1329-1342, 2020, DOI:10.32604/cmc.2020.011155

    Abstract An epidemic is a quick and widespread disease that threatens many lives and damages the economy. The epidemic lifetime should be accurate so that timely and remedial steps are determined. These include the closing of borders schools, suspension of community and commuting services. The forecast of an outbreak effectively is a very necessary but difficult task. A predictive model that provides the best possible forecast is a great challenge for machine learning with only a few samples of training available. This work proposes and examines a prediction model based on a deep extreme learning machine (DELM). This methodology is used… More >

  • Open Access

    ARTICLE

    Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

    Yuheng Sun1, Ye Mu1, 2, 3, 4, *, Qin Feng5, Tianli Hu1, 2, 3, 4, He Gong1, 2, 3, 4, Shijun Li1, 2, 3, 4, Jing Zhou6

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1317-1328, 2020, DOI:10.32604/cmc.2020.010510

    Abstract In large-scale deer farming image analysis, K-means or maximum betweenclass variance (Otsu) algorithms can be used to distinguish the deer from the background. However, in an actual breeding environment, the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer. Also, when the target and background grey values are similar, the multiple background targets cannot be completely separated. To better identify the posture and behaviour of deer in a deer shed, we used digital image processing to separate the deer from the background. To address the problems… More >

  • Open Access

    ARTICLE

    A Hybrid Method of Coreference Resolution in Information Security

    Yongjin Hu1, Yuanbo Guo1, Junxiu Liu2, Han Zhang3, *

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1297-1315, 2020, DOI:10.32604/cmc.2020.010855

    Abstract In the field of information security, a gap exists in the study of coreference resolution of entities. A hybrid method is proposed to solve the problem of coreference resolution in information security. The work consists of two parts: the first extracts all candidates (including noun phrases, pronouns, entities, and nested phrases) from a given document and classifies them; the second is coreference resolution of the selected candidates. In the first part, a method combining rules with a deep learning model (Dictionary BiLSTM-Attention-CRF, or DBAC) is proposed to extract all candidates in the text and classify them. In the DBAC model,… More >

  • Open Access

    ARTICLE

    Coverless Image Steganography Based on Image Segmentation

    Yuanjing Luo1, Jiaohua Qin1, *, Xuyu Xiang1, Yun Tan1, Zhibin He1, Neal N. Xiong2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1281-1295, 2020, DOI:10.32604/cmc.2020.010867

    Abstract To resist the risk of the stego-image being maliciously altered during transmission, we propose a coverless image steganography method based on image segmentation. Most existing coverless steganography methods are based on whole feature mapping, which has poor robustness when facing geometric attacks, because the contents in the image are easy to lost. To solve this problem, we use ResNet to extract semantic features, and segment the object areas from the image through Mask RCNN for information hiding. These selected object areas have ethical structural integrity and are not located in the visual center of the image, reducing the information loss… More >

  • Open Access

    ARTICLE

    PUF-Based Key Distribution in Wireless Sensor Networks

    Zheng Zhang1, Yanan Liu1, *, Qinyuan Zuo1, Lein Harn2, Shuo Qiu1, Yuan Cheng1

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1261-1280, 2020, DOI:10.32604/cmc.2020.010034

    Abstract Physical Unclonable Functions (PUFs) can be seen as kind of hardware oneway functions, who are easily fabricated but difficult to clone, duplicate or predict. Therefore, PUFs with unclonable and unpredictable properties are welcome to be applied in designing lightweight cryptography protocols. In this paper, a Basic Key Distribution Scheme (Basic-KDS) based on PUFs is firstly proposed. Then, by employing different deployment modes, a Random Deployment Key Distribution Scheme (RD-KDS) and a Grouping Deployment Key Distribution Scheme (GD-KDS) are further proposed based on the Basic-KDS for large scale wireless sensor networks. In our proposals, a sensor is not pre-distributed with any… More >

  • Open Access

    ARTICLE

    A Controlled Quantum Dialogue Protocol Based on Quantum Walks

    Jinqiao Dai1, Shibin Zhang1, *, Yan Chang1, Xueyang Li1, Tao Zheng1, Jinyue Xia2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1247-1260, 2020, DOI:10.32604/cmc.2020.010550

    Abstract In order to enable two parties to exchange their secret information equally, we propose a controlled quantum dialogue protocol based on quantum walks, which implements the equal exchange of secret information between the two parties with the help of the controller TP. The secret information is transmitted via quantum walks, by using this method, the previously required entangled particles do not need to be prepared in the initial phase, and the entangled particles can be produced spontaneously via quantum walks. Furthermore, to resist TP’s dishonest behavior, we use a hash function to verify the correctness of the secret information. The… More >

  • Open Access

    ARTICLE

    A Multi-Tenant Usage Access Model for Cloud Computing

    Zhengtao Liu1, *, Yun Yang1, Wen Gu1, Jinyue Xia2

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1233-1245, 2020, DOI:10.32604/cmc.2020.010846

    Abstract Most cloud services are built with multi-tenancy which enables data and configuration segregation upon shared infrastructures. It offers tremendous advantages for enterprises and service providers. It is anticipated that this situation will evolve to foster cross-tenant collaboration supported by Authorization as a service. To realize access control in a multi-tenant cloud computing environment, this study proposes a multi-tenant cloud computing access control model based on the traditional usage access control model by building trust relations among tenants. The model consists of three submodels, which achieve trust relationships between tenants with different granularities and satisfy the requirements of different application scenarios.… More >

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