Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (23,827)
  • Open Access

    ARTICLE

    Object Detection for Cargo Unloading System Based on Fuzzy C Means

    Sunwoo Hwang1, Jaemin Park1, Jongun Won2, Yongjang Kwon3, Youngmin Kim1,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4167-4181, 2022, DOI:10.32604/cmc.2022.023295

    Abstract With the recent increase in the utilization of logistics and courier services, it is time for research on logistics systems fused with the fourth industry sector. Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence field, but so far, algorithms suitable for automatic unloading devices that need to identify a number of unstructured cargoes require further development. In this study, the object recognition algorithm of the automatic loading device for cargo was selected as the subject of the study, and a cargo object recognition algorithm applicable to More >

  • Open Access

    ARTICLE

    Correlation Analysis of Energy Consumption of Agricultural Rotorcraft

    Lihua Zhu1,*, Zhijian Xu1, Yu Wang1, Cheire Cheng2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3179-3192, 2022, DOI:10.32604/cmc.2022.023293

    Abstract With the rapid development of unmanned aerial vehicle technology, unmanned aerial vehicles (UAVs) have been widely used in the field of agricultural plant protection. Compared with fuel-driven UAVs, electrically driven rotorcrafts have many advantages such as lower cost, simpler operation, good maneuverability and cleaner power, which them popular in the plant protection. However, electrical rotorcrafts still face battery problems in actual operation, which limits its working time and application. Aiming at this issue, this paper studied the influence of rotorcraft flight parameters on energy consumption through series of carefully designed flight experiments. First of all,… More >

  • Open Access

    ARTICLE

    Computational Algorithms for the Analysis of Cancer Virotherapy Model

    Ali Raza1,2,*, Dumitru Baleanu3,4, Muhammad Rafiq5, Syed Zaheer Abbas6, Abubakar Siddique6, Umer Javed8, Mehvish Naz7, Arooj Fatima6, Tayyba Munawar6, Hira Batool6, Zaighum Nazir6

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3621-3634, 2022, DOI:10.32604/cmc.2022.023286

    Abstract Cancer is a common term for many diseases that can affect any part of the body. In 2020, ten million people will die due to cancer. A worldwide leading cause of death is cancer by the World Health Organization (WHO) report. Interaction of cancer cells, viral therapy, and immune response are identified in this model. Mathematical and computational modeling is an effective tool to predict the dynamics of cancer virotherapy. The cell population is categorized into three parts like uninfected cells (x), infected cells (y), virus-free cells (v), and immune cells (z). The modeling of More >

  • Open Access

    ARTICLE

    Multi-Agent Deep Q-Networks for Efficient Edge Federated Learning Communications in Software-Defined IoT

    Prohim Tam1, Sa Math1, Ahyoung Lee2, Seokhoon Kim1,3,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3319-3335, 2022, DOI:10.32604/cmc.2022.023215

    Abstract Federated learning (FL) activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging processes. However, in large-scale heterogeneous Internet of Things (IoT) cellular networks, massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled significantly. This paper introduces the system model of converging software-defined networking (SDN) and network functions virtualization (NFV) to enable device/resource abstractions and provide NFV-enabled edge FL (eFL) aggregation servers for advancing automation and controllability. Multi-agent deep Q-networks (MADQNs) target to enforce a… More >

  • Open Access

    ARTICLE

    Evolution of Desertification Types on the North Shore of Qinghai Lake

    Wenzheng Yu1, Jintao Cui2, Yang Gao1, Mingxuan Zhu1, Li Shao3, Yanbo Shen4,5,*, Xiaozhao Zhang6, Chen Guo7, Hanxiaoya Zhang8

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3635-3646, 2022, DOI:10.32604/cmc.2022.023195

    Abstract Land desertification is a widely concerned ecological environment problem. Studying the evolution trend of desertification types is of great significance to prevent and control land desertification. In this study, we applied the decision tree classification method, to study the land area and temporal and spatial change law of different types of desertification in the North Bank of Qinghai Lake area from 1987 to 2014, based on the current land use situation and TM remote sensing image data of Haiyan County, Qinghai Province, The results show that the area of mild desertification land and moderate desertification… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Advertisement Banner Identification Technique for Effective Piracy Website Detection Process

    Lelisa Adeba Jilcha1, Jin Kwak2,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2883-2899, 2022, DOI:10.32604/cmc.2022.023167

    Abstract In the contemporary world, digital content that is subject to copyright is facing significant challenges against the act of copyright infringement. Billions of dollars are lost annually because of this illegal act. The current most effective trend to tackle this problem is believed to be blocking those websites, particularly through affiliated government bodies. To do so, an effective detection mechanism is a necessary first step. Some researchers have used various approaches to analyze the possible common features of suspected piracy websites. For instance, most of these websites serve online advertisement, which is considered as their… More >

  • Open Access

    ARTICLE

    The Impact of Semi-Supervised Learning on the Performance of Intelligent Chatbot System

    Sudan Prasad Uprety, Seung Ryul Jeong*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3937-3952, 2022, DOI:10.32604/cmc.2022.023127

    Abstract Artificial intelligent based dialog systems are getting attention from both business and academic communities. The key parts for such intelligent chatbot systems are domain classification, intent detection, and named entity recognition. Various supervised, unsupervised, and hybrid approaches are used to detect each field. Such intelligent systems, also called natural language understanding systems analyze user requests in sequential order: domain classification, intent, and entity recognition based on the semantic rules of the classified domain. This sequential approach propagates the downstream error; i.e., if the domain classification model fails to classify the domain, intent and entity recognition… More >

  • Open Access

    ARTICLE

    Gaining-Sharing Knowledge Based Algorithm for Solving Stochastic Programming Problems

    Prachi Agrawal1, Khalid Alnowibet2, Ali Wagdy Mohamed3,4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126

    Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are More >

  • Open Access

    ARTICLE

    Estimating Weibull Parameters Using Least Squares and Multilayer Perceptron vs. Bayes Estimation

    Walid Aydi1,3,*, Fuad S. Alduais2,4

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4033-4050, 2022, DOI:10.32604/cmc.2022.023119

    Abstract The Weibull distribution is regarded as among the finest in the family of failure distributions. One of the most commonly used parameters of the Weibull distribution (WD) is the ordinary least squares (OLS) technique, which is useful in reliability and lifetime modeling. In this study, we propose an approach based on the ordinary least squares and the multilayer perceptron (MLP) neural network called the OLSMLP that is based on the resilience of the OLS method. The MLP solves the problem of heteroscedasticity that distorts the estimation of the parameters of the WD due to the… More >

  • Open Access

    ARTICLE

    Analysis and Modeling of Propagation in Tunnel at 3.7 and 28 GHz

    Md Abdus Samad1,2, Dong-You Choi1,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3127-3143, 2022, DOI:10.32604/cmc.2022.023086

    Abstract In present-day society, train tunnels are extensively used as a means of transportation. Therefore, to ensure safety, streamlined train operations, and uninterrupted internet access inside train tunnels, reliable wave propagation modeling is required. We have experimented and measured wave propagation models in a 1674 m long straight train tunnel in South Korea. The measured path loss and the received signal strength were modeled with the Close-In (CI), Floating intercept (FI), CI model with a frequency-weighted path loss exponent (CIF), and alpha-beta-gamma (ABG) models, where the model parameters were determined using minimum mean square error (MMSE)… More >

Displaying 9941-9950 on page 995 of 23827. Per Page