Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (31,561)
  • Open Access

    ARTICLE

    Salicylic Acid Application Mitigates Oxidative Damage and Improves the Growth Performance of Barley under Drought Stress

    Shah Mohammad Naimul Islam1, Niloy Paul1, Md. Mezanur Rahman2, Md. Ashraful Haque1, Md. Motiar Rohman3, Mohammad Golam Mostofa4,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1513-1537, 2023, DOI:10.32604/phyton.2023.025175 - 09 March 2023

    Abstract Drought is a severe environmental constraint, causing a significant reduction in crop productivity across the world. Salicylic acid (SA) is an important plant growth regulator that helps plants cope with the adverse effects induced by various abiotic stresses. The current study investigated the potential effects of SA on drought tolerance efficacy in two barley (Hordeum vulgare) genotypes, namely BARI barley 5 and BARI barley 7. Ten-day-old barley seedlings were exposed to drought stress by maintaining 7.5% soil moisture content in the absence or presence of 0.5, 1.0 and 1.5 mM SA. Drought exposure led to severe… More >

  • Open Access

    ARTICLE

    Adaptive Time Slot Resource Allocation in SWIPT IoT Networks

    Yunong Yang1, Yuexia Zhang2,3,*, Zhihai Zhuo2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2787-2813, 2023, DOI:10.32604/cmes.2023.027351 - 09 March 2023

    Abstract The rapid advancement of Internet of Things (IoT) technology has brought convenience to people’s lives; however further development of IoT faces serious challenges, such as limited energy and shortage of network spectrum resources. To address the above challenges, this study proposes a simultaneous wireless information and power transfer IoT adaptive time slot resource allocation (SIATS) algorithm. First, an adaptive time slot consisting of periods for sensing, information transmission, and energy harvesting is designed to ensure that the minimum energy harvesting requirement is met while the maximum uplink and downlink throughputs are obtained. Second, the optimal… More >

  • Open Access

    ARTICLE

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

    Min Hu1,2,3, Zhimin Chen4, Yuan Xia4, Liping Zhang1,2,3,*, Qiuhua Tang1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2815-2840, 2023, DOI:10.32604/cmes.2023.027146 - 09 March 2023

    Abstract The multi-skill resource-constrained project scheduling problem (MS-RCPSP) is a significant management science problem that extends from the resource-constrained project scheduling problem (RCPSP) and is integrated with a real project and production environment. To solve MS-RCPSP, it is an efficient method to use dispatching rules combined with a parallel scheduling mechanism to generate a scheduling scheme. This paper proposes an improved gene expression programming (IGEP) approach to explore newly dispatching rules that can broadly solve MS-RCPSP. A new backward traversal decoding mechanism, and several neighborhood operators are applied in IGEP. The backward traversal decoding mechanism dramatically More > Graphic Abstract

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

  • Open Access

    ARTICLE

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

    Wenchao Yi, Zhilei Lin, Yong Chen, Zhi Pei*, Jiansha Lu

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2841-2860, 2023, DOI:10.32604/cmes.2023.027055 - 09 March 2023

    Abstract Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated ε-level method is proposed to avoid trapping in infeasible More > Graphic Abstract

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

  • Open Access

    ARTICLE

    Interpolation Technique for the Underwater DEM Generated by an Unmanned Surface Vessel

    Shiwei Qin, Zili Dai*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3157-3172, 2023, DOI:10.32604/cmes.2023.026874 - 09 March 2023

    Abstract High-resolution underwater digital elevation models (DEMs) are important for water and soil conservation, hydrological analysis, and river channel dredging. In this work, the underwater topography of the Panjing River in Shanghai, China, was measured by an unmanned surface vessel. Five different interpolation methods were used to generate the underwater DEM and their precision and applicability for different underwater landforms were analyzed through cross-validation. The results showed that there was a positive correlation between the interpolation error and the terrain surface roughness. The five interpolation methods were all appropriate for the survey area, but their accuracy More >

  • Open Access

    ARTICLE

    Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

    Feisha Hu1, Qi Wang1,*, Haijian Shao1,2, Shang Gao1, Hualong Yu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2405-2424, 2023, DOI:10.32604/cmes.2023.026732 - 09 March 2023

    Abstract Unmanned Aerial Vehicles (UAVs) are widely used and meet many demands in military and civilian fields. With the continuous enrichment and extensive expansion of application scenarios, the safety of UAVs is constantly being challenged. To address this challenge, we propose algorithms to detect anomalous data collected from drones to improve drone safety. We deployed a one-class kernel extreme learning machine (OCKELM) to detect anomalies in drone data. By default, OCKELM uses the radial basis (RBF) kernel function as the kernel function of the model. To improve the performance of OCKELM, we choose a Triangular Global More > Graphic Abstract

    Anomaly Detection of UAV State Data Based on Single-Class Triangular Global Alignment Kernel Extreme Learning Machine

  • Open Access

    ARTICLE

    PoQ-Consensus Based Private Electricity Consumption Forecasting via Federated Learning

    Yiqun Zhu1, Shuxian Sun1, Chunyu Liu1, Xinyi Tian1, Jingyi He2, Shuai Xiao2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3285-3297, 2023, DOI:10.32604/cmes.2023.026691 - 09 March 2023

    Abstract With the rapid development of artificial intelligence and computer technology, grid corporations have also begun to move towards comprehensive intelligence and informatization. However, data-based informatization can bring about the risk of privacy exposure of fine-grained information such as electricity consumption data. The modeling of electricity consumption data can help grid corporations to have a more thorough understanding of users’ needs and their habits, providing better services for users. Nevertheless, users’ electricity consumption data is sensitive and private. In order to achieve highly efficient analysis of massive private electricity consumption data without direct access, a blockchain-based… More >

  • Open Access

    ARTICLE

    Many-Objective Optimization-Based Task Scheduling in Hybrid Cloud Environments

    Mengkai Zhao1, Zhixia Zhang2, Tian Fan1, Wanwan Guo1, Zhihua Cui1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2425-2450, 2023, DOI:10.32604/cmes.2023.026671 - 09 March 2023

    Abstract Due to the security and scalability features of hybrid cloud architecture, it can better meet the diverse requirements of users for cloud services. And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud. However, most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling, even ignoring the conflicts between its security privacy features and other requirements. Based on the above problems, a many-objective hybrid cloud task scheduling optimization model (HCTSO) is constructed combining risk rate, resource utilization, total cost, and task completion time. Meanwhile, an opposition-based 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 - 09 March 2023

    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… More > Graphic Abstract

    Multi-Stage Improvement of Marine Predators Algorithm and Its Application

  • Open Access

    ARTICLE

    BC-PC-Share: Blockchain-Based Patient-Centric Data Sharing Scheme for PHRs in Cloud Computing

    Caihui Lan1, Haifeng Li2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2985-3010, 2023, DOI:10.32604/cmes.2023.026321 - 09 March 2023

    Abstract Sharing of personal health records (PHR) in cloud computing is an essential functionality in the healthcare system. However, how to securely, efficiently and flexibly share PHRs data of the patient in a multi-receiver setting has not been well addressed. For instance, since the trust domain of the cloud server is not identical to the data owner or data user, the semi-trust cloud service provider may intentionally destroy or tamper shared PHRs data of user or only transform partial ciphertext of the shared PHRs or even return wrong computation results to save its storage and computation… More >

Displaying 10091-10100 on page 1010 of 31561. Per Page