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  • Open Access


    Deep Learning-Based Classification of Rotten Fruits and Identification of Shelf Life

    S. Sofana Reka1, Ankita Bagelikar2, Prakash Venugopal2,*, V. Ravi2, Harimurugan Devarajan3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 781-794, 2024, DOI:10.32604/cmc.2023.043369

    Abstract The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality, flavor and nutritional value. The primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to consumers. The impact of rotten fruits can foster harmful bacteria, molds and other microorganisms that can cause food poisoning and other illnesses to the consumers. The overall purpose of the study is to classify rotten fruits, which can affect the taste, texture, and appearance of other fresh fruits, thereby reducing their shelf life. The agriculture and food industries… More >

  • Open Access


    Fault Diagnosis Method of Rolling Bearing Based on ESGMD-CC and AFSA-ELM

    Jiajie He1,2, Fuzheng Liu3, Xiangyi Geng3, Xifeng Liang1, Faye Zhang3,*, Mingshun Jiang3

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 37-54, 2024, DOI:10.32604/sdhm.2023.029428

    Abstract Incomplete fault signal characteristics and ease of noise contamination are issues with the current rolling bearing early fault diagnostic methods, making it challenging to ensure the fault diagnosis accuracy and reliability. A novel approach integrating enhanced Symplectic geometry mode decomposition with cosine difference limitation and calculus operator (ESGMD-CC) and artificial fish swarm algorithm (AFSA) optimized extreme learning machine (ELM) is proposed in this paper to enhance the extraction capability of fault features and thus improve the accuracy of fault diagnosis. Firstly, SGMD decomposes the raw vibration signal into multiple Symplectic geometry components (SGCs). Secondly, the iterations are reset by the… More >

  • Open Access


    Optimized Deep Learning Approach for Efficient Diabetic Retinopathy Classification Combining VGG16-CNN

    Heba M. El-Hoseny1,*, Heba F. Elsepae2, Wael A. Mohamed2, Ayman S. Selmy2

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1855-1872, 2023, DOI:10.32604/cmc.2023.042107

    Abstract Diabetic retinopathy is a critical eye condition that, if not treated, can lead to vision loss. Traditional methods of diagnosing and treating the disease are time-consuming and expensive. However, machine learning and deep transfer learning (DTL) techniques have shown promise in medical applications, including detecting, classifying, and segmenting diabetic retinopathy. These advanced techniques offer higher accuracy and performance. Computer-Aided Diagnosis (CAD) is crucial in speeding up classification and providing accurate disease diagnoses. Overall, these technological advancements hold great potential for improving the management of diabetic retinopathy. The study’s objective was to differentiate between different classes of diabetes and verify the… More >

  • Open Access


    Optimization of Blade Geometry of Savonius Hydrokinetic Turbine Based on Genetic Algorithm

    Jiahao Lu1, Fangfang Zhang1, Weilong Guang1, Yanzhao Wu1, Ran Tao1,2,*, Xiaoqin Li1,2, Ruofu Xiao1,2

    Energy Engineering, Vol.120, No.12, pp. 2819-2837, 2023, DOI:10.32604/ee.2023.042287

    Abstract Savonius hydrokinetic turbine is a kind of turbine set which is suitable for low-velocity conditions. Unlike conventional turbines, Savonius turbines employ S-shaped blades and have simple internal structures. Therefore, there is a large space for optimizing the blade geometry. In this study, computational fluid dynamics (CFD) numerical simulation and genetic algorithm (GA) were used for the optimal design. The optimization strategies and methods were determined by comparing the results calculated by CFD with the experimental results. The weighted objective function was constructed with the maximum power coefficient Cp and the high-power coefficient range R under multiple working conditions. GA helps… More >

  • Open Access



    Srinath Ekkada,*, Je-Chin Hanb

    Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-14, 2015, DOI:10.5098/hmt.6.8

    Abstract Improved film cooling hole geometries and effect of coolant density on film cooling have been a focus since the 1970s. One of the first studies on modifying hole exit to improve film cooling effectiveness and quantifying coolant density effect was from Prof. Goldstein’s group. This paper provides an overview of the development and implementation of hole exit geometries as well as coolant density study over the past few decades and the impact on future studies of advanced hole geometries under realistic engine-like coolant-to-mainstream density ratio conditions. This work is not intended to be a comprehensive review of the literature. More >

  • Open Access


    Solving Algebraic Problems with Geometry Diagrams Using Syntax-Semantics Diagram Understanding

    Litian Huang, Xinguo Yu, Lei Niu*, Zihan Feng

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 517-539, 2023, DOI:10.32604/cmc.2023.041206

    Abstract Solving Algebraic Problems with Geometry Diagrams (APGDs) poses a significant challenge in artificial intelligence due to the complex and diverse geometric relations among geometric objects. Problems typically involve both textual descriptions and geometry diagrams, requiring a joint understanding of these modalities. Although considerable progress has been made in solving math word problems, research on solving APGDs still cannot discover implicit geometry knowledge for solving APGDs, which limits their ability to effectively solve problems. In this study, a systematic and modular three-phase scheme is proposed to design an algorithm for solving APGDs that involve textual and diagrammatic information. The three-phase scheme… More >

  • Open Access


    Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone: A Stochastic Geometry Approach

    Yulei Wang1, Li Feng1,*, Shumin Yao1,2, Hong Liang1, Haoxu Shi1, Yuqiang Chen3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 639-661, 2024, DOI:10.32604/cmes.2023.029565

    Abstract Interference management is one of the most important issues in the device-to-device (D2D)-enabled heterogeneous cellular networks (HetCNets) due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular spectrum. To alleviate the interference, an efficient interference management way is to set exclusion zones around the cellular receivers. In this paper, we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled HetCNets. The main difficulties contain three aspects: 1) how to model the location randomness of base stations, cellular and D2D users in practical networks; 2)… More >

  • Open Access


    Gas Transport Through Nanochannels: Surface Effect and Molecular Geometry Effect

    JianHao Qian1, HengAn Wu1, FengChao Wang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.09144

    Abstract Gas transport through nanochannels is ubiquitous in nature and also plays an important role in industry. The gas flow in this regime can be described by the Knudsen theory, which assumes that molecules diffusely reflect on the confining walls [1]. However, with the emergence of low dimensional carbon-based materials such as graphene and carbon nanotubes, it has been evidenced that this assumption might not hold for some atomically smooth surfaces, resulting in an anomalous enhancement of gas flux [2]. Moreover, in Knudsen theory, gas molecules are usually treated as mass points and distinguished solely by molecular weight, which cannot interpret… More >

  • Open Access



    R. Rajaramana , L. Anna Gowsalyab,*, R. Velrajc

    Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-8, 2018, DOI:10.5098/hmt.11.23

    Abstract To get accurate results in casting simulations, prediction of interfacial heat transfer coefficient (IHTC) is imperative. In this paper an attempt has been made for estimating IHTC during solidification process of a rectangular aluminium alloy casting in a sand mould. The cast temperature and mould temperature are measured during the experimental process at different time intervals during the process of solidification. Two different inverse methods, namely control volume and Beck’s approach are used to estimate the heat flux and temperature at the mould surface by using the experimentally measured temperatures. In the case of control volume technique, the partial derivative… More >

  • Open Access


    New Quantum Color Codes Based on Hyperbolic Geometry

    Avaz Naghipour1,*, Duc Manh Nguyen2

    Journal of Quantum Computing, Vol.4, No.2, pp. 113-120, 2022, DOI:10.32604/jqc.2022.033712

    Abstract In this paper, hyperbolic geometry is used to constructing new quantum color codes. We use hyperbolic tessellations and hyperbolic polygons to obtain them by pairing the edges on compact surfaces. These codes have minimum distance of at least and the encoding rate near to which are not mentioned in other literature. Finally, a comparison table with quantum codes recently proposed by the authors is provided. More >

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