Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (142)
  • Open Access

    ARTICLE

    A Novel Multi-Stage Bispectral Deep Learning Method for Protein Family Classification

    Amjed Al Fahoum*, Ala’a Zyout, Hiam Alquran, Isam Abu-Qasmieh

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1173-1193, 2023, DOI:10.32604/cmc.2023.038304

    Abstract Complex proteins are needed for many biological activities. Folding amino acid chains reveals their properties and functions. They support healthy tissue structure, physiology, and homeostasis. Precision medicine and treatments require quantitative protein identification and function. Despite technical advances and protein sequence data exploration, bioinformatics’ “basic structure” problem—the automatic deduction of a protein’s properties from its amino acid sequence—remains unsolved. Protein function inference from amino acid sequences is the main biological data challenge. This study analyzes whether raw sequencing can characterize biological facts. A massive corpus of protein sequences and the Globin-like superfamily’s related protein families generate a solid vector representation.… More >

  • Open Access

    ARTICLE

    Automatic Diagnosis of Polycystic Ovarian Syndrome Using Wrapper Methodology with Deep Learning Techniques

    Mohamed Abouhawwash1,2, S. Sridevi3, Suma Christal Mary Sundararajan4, Rohit Pachlor5, Faten Khalid Karim6, Doaa Sami Khafaga6,*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 239-253, 2023, DOI:10.32604/csse.2023.037812

    Abstract One of the significant health issues affecting women that impacts their fertility and results in serious health concerns is Polycystic ovarian syndrome (PCOS). Consequently, timely screening of polycystic ovarian syndrome can help in the process of recovery. Finding a method to aid doctors in this procedure was crucial due to the difficulties in detecting this condition. This research aimed to determine whether it is possible to optimize the detection of PCOS utilizing Deep Learning algorithms and methodologies. Additionally, feature selection methods that produce the most important subset of features can speed up calculation and enhance the effectiveness of classifiers. In… More >

  • Open Access

    ARTICLE

    SIMULATION AND OPTIMIZATION OF MULTISTAGE COMPRESSED DMR NATURAL GAS LIQUEFACTION PROCESS

    Rongge Xiaoa,*, Yanwei Zhanga , Xu Gaob , Hongping Yuc , Wangying Weia

    Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-8, 2020, DOI:10.5098/hmt.15.22

    Abstract In order to improve DMR (double mixed refrigerant) liquefaction process and reduce operation cost of natural gas liquefaction plant, a four-stage DMR process optimization simulation calculation model was established through Aspen Hysys v8.4 and the purpose of the optimization model is achieved by using the segmented compression process in this paper. The minimum energy consumption and the highest exergy efficiency were used as the objective functions. By using the optimizer in HYSYS, the process parameters and ingredient proportion of the mixed refrigerant in the fourstage DMR process was optimized, and the best process parameters and ingredient proportion of the mixed… More >

  • Open Access

    ARTICLE

    Detection Algorithm of Knee Osteoarthritis Based on Magnetic Resonance Images

    Xin Wang*, Shuang Liu, Chang-Cai Zhou

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 221-234, 2023, DOI:10.32604/iasc.2023.036766

    Abstract Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Currently, studies on the detection of knee OA mainly focus on X-ray images, but X-ray images are insensitive to the changes in knee OA in the early stage. Since magnetic resonance (MR) imaging can observe the early features of knee OA, the knee OA detection algorithm based on MR image is innovatively proposed to judge whether knee OA is suffered. Firstly, the knee MR images are preprocessed before training, including a region of interest clipping, slice selection, and data augmentation. Then the data set was divided… More >

  • Open Access

    ARTICLE

    A Progressive Approach to Generic Object Detection: A Two-Stage Framework for Image Recognition

    Muhammad Aamir1, Ziaur Rahman1,*, Waheed Ahmed Abro2, Uzair Aslam Bhatti3, Zaheer Ahmed Dayo1, Muhammad Ishfaq1

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6351-6373, 2023, DOI:10.32604/cmc.2023.038173

    Abstract Object detection in images has been identified as a critical area of research in computer vision image processing. Research has developed several novel methods for determining an object’s location and category from an image. However, there is still room for improvement in terms of detection efficiency. This study aims to develop a technique for detecting objects in images. To enhance overall detection performance, we considered object detection a two-fold problem, including localization and classification. The proposed method generates class-independent, high-quality, and precise proposals using an agglomerative clustering technique. We then combine these proposals with the relevant input image to train… More >

  • Open Access

    ARTICLE

    Rectal Cancer Stages T2 and T3 Identification Based on Asymptotic Hybrid Feature Maps

    Shujing Sun1,3, Jiale Wu2, Jian Yao1, Yang Cheng4, Xin Zhang1, Zhihua Lu3, Pengjiang Qian1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 923-938, 2023, DOI:10.32604/cmes.2023.027356

    Abstract Many existing intelligent recognition technologies require huge datasets for model learning. However, it is not easy to collect rectal cancer images, so the performance is usually low with limited training samples. In addition, traditional rectal cancer staging is time-consuming, error-prone, and susceptible to physicians’ subjective awareness as well as professional expertise. To settle these deficiencies, we propose a novel deep-learning model to classify the rectal cancer stages of T2 and T3. First, a novel deep learning model (RectalNet) is constructed based on residual learning, which combines the squeeze-excitation with the asymptotic output layer and new cross-convolution layer links in the… More >

  • Open Access

    ARTICLE

    A Multi-Stage Security Solution for Medical Color Images in Healthcare Applications

    Walid El-Shafai1,2,*, Fatma Khallaf2,3, El-Sayed M. El-Rabaie2, Fathi E. Abd El-Samie2, Iman Almomani1,4

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3599-3618, 2023, DOI:10.32604/csse.2023.037655

    Abstract This paper presents a robust multi-stage security solution based on fusion, encryption, and watermarking processes to transmit color healthcare images, efficiently. The presented solution depends on the features of discrete cosine transform (DCT), lifting wavelet transform (LWT), and singular value decomposition (SVD). The primary objective of this proposed solution is to ensure robustness for the color medical watermarked images against transmission attacks. During watermark embedding, the host color medical image is transformed into four sub-bands by employing three stages of LWT. The resulting low-frequency sub-band is then transformed by employing three stages of DCT followed by SVD operation. Furthermore, a… More >

  • Open Access

    ARTICLE

    Proteomic Analyses of Three Inflorescence Styles of Castor (Ricinus communis L.) at Different Developmental Stages

    Xue Lei1,#, Yong Zhao2,#, Rui Luo1, Mingda Yin1, Yanpeng Wen1, Zhiyan Wang1, Xuemei Hu1, Fenglan Huang1,3,4,5,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1621-1632, 2023, DOI:10.32604/phyton.2023.027046

    Abstract Castor (Ricinus communis L.) is one of ten oil crops in the world and has complex inflorescence styles. Generally, castor has three inflorescence types: single female inflorescence (SiFF), standard female inflorescence (StFF) and bisexual inflorescence (BF). StFF is realized as a restorer line and as a maintainer line, which was applied to castor hybrid breeding. However, the developmental mechanism of the three inflorescences is not clear. Therefore, we used proteomic techniques to analyze different inflorescence styles. A total of 72 diferentially abundant protein species (DAPs) were detected. These DAPs are primarily involved in carbon and energy metabolism and carbon fixation… More >

  • Open Access

    ARTICLE

    Multi-Stage Improvement of Marine Predators Algorithm and Its Application

    Chuandong Qin, Baole Han*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3097-3119, 2023, DOI:10.32604/cmes.2023.026643

    Abstract The metaheuristic algorithms are widely used in solving the parameters of the optimization problem. The marine predators algorithm (MPA) is a novel population-based intelligent algorithm. Although MPA has shown a talented foraging strategy, it still needs a balance of exploration and exploitation. Therefore, a multi-stage improvement of marine predators algorithm (MSMPA) is proposed in this paper. The algorithm retains the advantage of multi-stage search and introduces a linear flight strategy in the middle stage to enhance the interaction between predators. Predators further away from the historical optimum are required to move, increasing the exploration capability of the algorithm. In the… More > Graphic Abstract

    Multi-Stage Improvement of Marine Predators Algorithm and Its Application

  • Open Access

    ARTICLE

    Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

    Weijun Li1, Xin Die2, Zhicheng Ma3, Jinping Zhang3, Haiying Dong1,*

    Energy Engineering, Vol.120, No.4, pp. 1001-1022, 2023, DOI:10.32604/ee.2023.024426

    Abstract Aiming at the problems of large-scale wind and solar grid connection, how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations, a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed. Firstly, the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output, obtains the optimal output value under the economic conditions of each new energy station, and then obtains the maximum consumption space of the… More > Graphic Abstract

    Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

Displaying 21-30 on page 3 of 142. Per Page