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  • Open Access

    ARTICLE

    Ash Detection of Coal Slime Flotation Tailings Based on Chromatographic Filter Paper Sampling and Multi-Scale Residual Network

    Wenbo Zhu1, Neng Liu1, Zhengjun Zhu2,*, Haibing Li1, Weijie Fu1, Zhongbo Zhang1, Xinghao Zhang1

    Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 259-273, 2023, DOI:10.32604/iasc.2023.041860

    Abstract The detection of ash content in coal slime flotation tailings using deep learning can be hindered by various factors such as foam, impurities, and changing lighting conditions that disrupt the collection of tailings images. To address this challenge, we present a method for ash content detection in coal slime flotation tailings. This method utilizes chromatographic filter paper sampling and a multi-scale residual network, which we refer to as MRCN. Initially, tailings are sampled using chromatographic filter paper to obtain static tailings images, effectively isolating interference factors at the flotation site. Subsequently, the MRCN, consisting of a multi-scale residual network, is… More >

  • Open Access

    ARTICLE

    Developing Transparent IDS for VANETs Using LIME and SHAP: An Empirical Study

    Fayaz Hassan1,*, Jianguo Yu1, Zafi Sherhan Syed2, Arif Hussain Magsi3, Nadeem Ahmed4

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3185-3208, 2023, DOI:10.32604/cmc.2023.044650

    Abstract Vehicular Ad-hoc Networks (VANETs) are mobile ad-hoc networks that use vehicles as nodes to create a wireless network. Whereas VANETs offer many advantages over traditional transportation networks, ensuring security in VANETs remains a significant challenge due to the potential for malicious attacks. This study addresses the critical issue of security in VANETs by introducing an intelligent Intrusion Detection System (IDS) that merges Machine Learning (ML)–based attack detection with Explainable AI (XAI) explanations. This study ML pipeline involves utilizing correlation-based feature selection followed by a Random Forest (RF) classifier that achieves a classification accuracy of 100% for the binary classification task… More >

  • Open Access

    ARTICLE

    Preparation of High Activity Admixture from Steel Slag, Phosphate Slag and Limestone Powder

    Ying Ji*, Xi Liu*

    Journal of Renewable Materials, Vol.11, No.11, pp. 3977-3989, 2023, DOI:10.32604/jrm.2023.028439

    Abstract The problem of low disposal and utilization rate of bulk industrial solid waste needs to be solved. In this paper, a high-activity admixture composed of steel slag-phosphate slag-limestone powder was proposed for most of the solid waste with low activity and a negative impact on concrete workability, combining the characteristics of each solid waste. The paper demonstrates the feasibility and explains the principle of the composite system in terms of water requirement of standard consistency, setting time, workability, and mechanical properties, combined with the composition of the phases, hydration temperature, and microscopic morphology. The results showed that the steel slag:phosphate… More > Graphic Abstract

    Preparation of High Activity Admixture from Steel Slag, Phosphate Slag and Limestone Powder

  • Open Access

    ARTICLE

    Resource Allocation for IRS Assisted mmWave Wireless Powered Sensor Networks with User Cooperation

    Yonghui Lin1, Zhengyu Zhu2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 663-677, 2024, DOI:10.32604/cmes.2023.028584

    Abstract In this paper, we investigate IRS-aided user cooperation (UC) scheme in millimeter wave (mmWave) wireless-powered sensor networks (WPSN), where two single-antenna users are wireless powered in the wireless energy transfer (WET) phase first and then cooperatively transmit information to a hybrid access point (AP) in the wireless information transmission (WIT) phase, following which the IRS is deployed to enhance the system performance of the WET and WIT. We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots, power allocations, and the phase shifts of the IRS. Due to the non-convexity of the original problem, a semidefinite programming… More >

  • Open Access

    ARTICLE

    Preliminary Study on the Treatment Efficiency of Pasteurized Lime Thermal Alkaline Hydrolysis for Excess Activated Sludge and Reduction of Tetracycline Resistance Genes

    Maoxia Chen1,2,*, Qixuan Zhou1, Jiayue Zhang1, Jiaoyang Li1, Wei Zhang1, Huan Liu1

    Journal of Renewable Materials, Vol.11, No.10, pp. 3711-3723, 2023, DOI:10.32604/jrm.2023.027826

    Abstract Thermal alkaline hydrolysis is a common pretreatment method for the utilization of excess activated sludge (EAS). Owing to strict environment laws and need for better energy utilization, new methods were developed in this study to improve the efficiency of pretreatment method. Direct thermal hydrolysis (TH), pasteurized thermal hydrolysis (PTH), and alkaline pasteurized thermal hydrolysis (PTH + CaO and PTH + NaOH) methods were used to treat EAS. Each method was compared and analyzed in terms of dissolution in ammonium nitrogen (NH4 + -N) and soluble COD (SCOD) in EAS. Furthermore, the removal of tetracycline resistance genes (TRGs) and class 1… More >

  • Open Access

    ARTICLE

    Explainable AI and Interpretable Model for Insurance Premium Prediction

    Umar Abdulkadir Isa*, Anil Fernando*

    Journal on Artificial Intelligence, Vol.5, pp. 31-42, 2023, DOI:10.32604/jai.2023.040213

    Abstract Traditional machine learning metrics (TMLMs) are quite useful for the current research work precision, recall, accuracy, MSE and RMSE. Not enough for a practitioner to be confident about the performance and dependability of innovative interpretable model 85%–92%. We included in the prediction process, machine learning models (MLMs) with greater than 99% accuracy with a sensitivity of 95%–98% and specifically in the database. We need to explain the model to domain specialists through the MLMs. Human-understandable explanations in addition to ML professionals must establish trust in the prediction of our model. This is achieved by creating a model-independent, locally accurate explanation… More >

  • Open Access

    ARTICLE

    Computer Modelling of Compact 28/38 GHz Dual-Band Antenna for Millimeter-Wave 5G Applications

    Amit V. Patel1, Arpan Desai1, Issa Elfergani2,3,*, Hiren Mewada4, Chemseddine Zebiri5, Keyur Mahant1, Jonathan Rodriguez2, Raed Abd-Alhameed3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2867-2879, 2023, DOI:10.32604/cmes.2023.026200

    Abstract A four-element compact dual-band patch antenna having a common ground plane operating at 28/38 GHz is proposed for millimeter-wave communication systems in this paper. The multiple-input-multiple-output (MIMO) antenna geometry consists of a slotted ellipse enclosed within a hollow circle which is orthogonally rotated with a connected partial ground at the back. The overall size of the four elements MIMO antenna is 2.24λ × 2.24λ (at 27.12 GHz). The prototype of four-element MIMO resonator is designed and printed using Rogers RT Duroid 5880 with εr = 2.2 and loss tangent = 0.0009 and having a thickness of 0.8 mm. It covers… More >

  • Open Access

    ARTICLE

    Statistical Data Mining with Slime Mould Optimization for Intelligent Rainfall Classification

    Ramya Nemani1, G. Jose Moses2, Fayadh Alenezi3, K. Vijaya Kumar4, Seifedine Kadry5,6,7,*, Jungeun Kim8, Keejun Han9

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 919-935, 2023, DOI:10.32604/csse.2023.034213

    Abstract Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance, medicine, science, engineering, and so on. Statistical data mining (SDM) is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the data. It varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other resolves. Thus, this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime Mould Optimization with Deep Learning… More >

  • Open Access

    ARTICLE

    Réflexion méthodologique et application à Lyon-Saint-Étienne

    Luc Merchez1 , Hélène Mathian2 , Julie Le Gall3

    Revue Internationale de Géomatique, Vol.30, No.1, pp. 85-104, 2020, DOI:10.3166/rig.2020.00103

    Abstract La question de l’alimentation et de la caractérisation des environnements alimentaires a déjà fait l’objet de nombreuses études et développements méthodologiques pour rendre compte des différentiels d’accessibilité. Aux Etats-Unis, essentiellement à l’aune de questions sur la santé, ces études ont conduit à identifier des « déserts alimentaires . Cette question éminemment spatiale, qui repose sur la notion d’accessibilité, est souvent approchée par des enquêtes et entretiens ou des approches quantitatives basées sur des calculs d’accessibilités géographiques. Dans la lignée de ces travaux, nous proposons d’explorer la transférabilité de cette notion de « désert à un espace métropolitain français. La démarche… More >

  • Open Access

    ARTICLE

    An Improved Elite Slime Mould Algorithm for Engineering Design

    Li Yuan1, Jianping Ji1, Xuegong Liu1, Tong Liu2, Huiling Chen3, Deng Chen4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 415-454, 2023, DOI:10.32604/cmes.2023.026098

    Abstract The Swarm intelligence algorithm is a very prevalent field in which some scholars have made outstanding achievements. As a representative, Slime mould algorithm (SMA) is widely used because of its superior initial performance. Therefore, this paper focuses on the improvement of the SMA and the mitigation of its stagnation problems. For this aim, the structure of SMA is adjusted to develop the efficiency of the original method. As a stochastic optimizer, SMA mainly stimulates the behavior of slime mold in nature. For the harmony of the exploration and exploitation of SMA, the paper proposed an enhanced algorithm of SMA called… More > Graphic Abstract

    An Improved Elite Slime Mould Algorithm for Engineering Design

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