Tengda Li, Gang Wang, Qiang Fu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2559-2586, 2024, DOI:10.32604/cmes.2024.052039

Abstract Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation (DTA) and high-dimensional decision space with single agent, this paper combines the deep reinforcement learning (DRL) theory and an improved Multi-Agent Deep Deterministic Policy Gradient (MADDPG-D2) algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA. The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, and considers the introduction of a double noise mechanism to increase the action exploration… More >

Abdul Momin¹, Amana Khatoon^1,*, Wajahat Khan¹, Dilsat Bozdoğan Konuşkan², Muhammad Mudasar Aslam³, Muhammad Jamil⁴, Shafiq Ur Rehman⁵, Baber Ali⁶, Alevcan Kaplan⁷, Sana Wahab⁸, Muhammad Nauman Khan^9,*, Sezai Ercisli^10,11, Mohammad Khalid Al-Sadoon¹²

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1117-1128, 2024, DOI:10.32604/phyton.2024.048994

Abstract Sprouts are ready-to-eat and are recognized worldwide as functional components of the human diet. Recent advances in innovative agricultural techniques could enable an increase in the production of healthy food. The use of light-emitting diode (LED) in indoor agricultural production could alter the biological feedback loop, increasing the functional benefits of plant foods such as wheat and lentil sprouts and promoting the bioavailability of nutrients. The effects of white (W), red (R), and blue (B) light were investigated on the growth parameters and nutritional value of wheat and lentil sprouts. In the laboratory, seeds were… More >

Ibraheem Abu Falahah¹, Osama Al-Baik², Saleh Alomari³, Gulnara Bektemyssova⁴, Saikat Gochhait^5,6, Irina Leonova⁷, Om Parkash Malik⁸, Frank Werner^9,*, Mohammad Dehghani¹⁰

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3631-3678, 2024, DOI:10.32604/cmc.2024.053189

Abstract This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization (FLO), which emulates the unique hunting behavior of frilled lizards in their natural habitat. FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards. The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases: (i) an exploration phase, which mimics the lizard’s sudden attack on its prey, and (ii) an exploitation phase, which simulates the lizard’s retreat to the treetops after feeding. To assess FLO’s efficacy in addressing optimization problems, its performance is rigorously tested on fifty-two… More >

Hao Chen^#, Runfeng Xie^#, Xiangyang Cui, Zhou Yan, Xin Wang, Zhanwei Xuan^*, Kai Zhang^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4283-4296, 2024, DOI:10.32604/cmc.2024.049129

Abstract Accurately recommending candidate news to users is a basic challenge of personalized news recommendation systems. Traditional methods are usually difficult to learn and acquire complex semantic information in news texts, resulting in unsatisfactory recommendation results. Besides, these traditional methods are more friendly to active users with rich historical behaviors. However, they can not effectively solve the long tail problem of inactive users. To address these issues, this research presents a novel general framework that combines Large Language Models (LLM) and Knowledge Graphs (KG) into traditional methods. To learn the contextual information of news text, we… More >

Nidhika Chauhan¹, Navneet Kaur², Kamaljit Singh Saini³, Sahil Verma³, Kavita³, Ruba Abu Khurma^4,5, Pedro A. Castillo^6,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3757-3782, 2024, DOI:10.32604/cmc.2024.046516

Abstract Cloud computing is a dynamic and rapidly evolving field, where the demand for resources fluctuates continuously. This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments. The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently. By adhering to the proposed resource allocation method, we aim to achieve a substantial reduction in energy consumption. This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most, aligning with the broader goal of… More >

Maie Aboghazalah^1,*, Passent El-kafrawy², Abdelmoty M. Ahmed³, Rasha Elnemr⁵, Belgacem Bouallegue³, Ayman El-sayed⁴

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3855-3875, 2024, DOI:10.32604/cmc.2023.039936

Abstract Heart monitoring improves life quality. Electrocardiograms (ECGs or EKGs) detect heart irregularities. Machine learning algorithms can create a few ECG diagnosis processing methods. The first method uses raw ECG and time-series data. The second method classifies the ECG by patient experience. The third technique translates ECG impulses into Q waves, R waves and S waves (QRS) features using richer information. Because ECG signals vary naturally between humans and activities, we will combine the three feature selection methods to improve classification accuracy and diagnosis. Classifications using all three approaches have not been examined till now. Several More >

Quan Zhou^*, Haiyang Li

Energy Engineering, Vol.121, No.7, pp. 1781-1803, 2024, DOI:10.32604/ee.2024.049387

Abstract Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive, and their use would release pollutants. Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy. Hybrid renewable energy systems (HRES) are viable for remote areas operating in standalone mode. This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades. More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace… More >

Youssef Maaloufa^1,2,3,*, Soumia Mounir^1,2,3, Sara Ibnelhaj², Fatima Zohra El Wardi⁶, Asma Souidi³, Yakubu Aminu Dodo^4,5, Malika Atigui³, Mina Amazal³, Abelhamid Khabbazi², Hassan Demrati³, Ahmed Aharoune³

Journal of Renewable Materials, Vol.12, No.4, pp. 843-867, 2024, DOI:10.32604/jrm.2024.049942

Abstract The development of bio-sourced materials is essential to ensuring sustainable construction; it is considered a locomotive of the green economy. Furthermore, it is an abundant material in our country, to which very little attention is being given. This work aims to valorize the waste of the trunks of banana trees to be used in construction. Firstly, the physicochemical properties of the fiber, such as the percentage of crystallization and its morphology, have been determined by X-ray diffraction tests and scanning electron microscopy to confirm the potential and the impact of the mode of drying on… More >

Lei Wang¹, Ziran Ma^1,*, Chunlin Zhao¹, Jiali Zhou¹, Hongyan Wang¹, Ge Li¹, Ningling Zhou²

Journal of Renewable Materials, Vol.12, No.4, pp. 799-814, 2024, DOI:10.32604/jrm.2024.047343

Abstract This study explores the corrosion issues arising from the coupled combustion of coal and biomass and proposes potential solutions. Biomass, as a renewable energy source, offers advantages in energy-saving and carbon reduction. However, the corrosive effects of alkali metal compounds, sulfur (S) and chlorine (Cl) elements in the ash after combustion cannot be underestimated due to the high volatile content of biomass fuels. We investigate the corrosion mechanisms, as well as the transfer of Cl and alkali metal elements during this process. Comparative corrosion analyses are conducted among coal-fired boilers, pure biomass boilers and boilers… More >

Qingran Meng^1,2, Wenwen Xu², Zuobing Xiao², Qinfei Ke^1,2,*, Xingran Kou^1,2,*

Journal of Renewable Materials, Vol.12, No.4, pp. 629-641, 2024, DOI:10.32604/jrm.2023.029182

Abstract Bio-based cyclodextrins (CDs) are a common research object in supramolecular chemistry. The special cavity structure of CDs can form supramolecular self-assemblies such as vesicles and microcrystals through weak interaction with guest molecules. The different forms of supramolecular self-assemblies can be transformed into each other under certain conditions. The regulation of supramolecular self-assembly is not only helpful to understand the self-assembly principle, but also beneficial to its application. In the present study, the self-assembly behavior of epoxy-β-cyclodextrin (EP-β-CD) and mixed anionic and cationic surfactant system (sodium dodecyl sulfate/dodecyltrimethylammonium bromide, SDS/DTAB) in aqueous solution was studied. Morphological… More > Graphic Abstract