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  • Open Access

    ARTICLE

    Health Risks Assessment of Heavy Metal Pollution in the Soil-Crop System from an E-Waste Dismantling Area

    Shengting Rao#, Jia Fang#, Keli Zhao*

    Phyton-International Journal of Experimental Botany, Vol.91, No.12, pp. 2669-2685, 2022, DOI:10.32604/phyton.2022.022416

    Abstract

    Soil is an essential resource for agricultural production. In order to investigate the pollution situation of heavy metals in the soil-crop system in the e-waste dismantling area, the crop and soil samples (226 pairs, including leaf vegetables, solanaceous vegetables, root vegetables, and fruits) around the e-waste dismantling area in southeastern Zhejiang Province were collected. The concentrations of Cd, Cu, Pb, and Cr were determined. The average concentrations of Cd, Cu, Pb, and Cr in soils were 0.94, 107.79, 80.28, and 78.14 mg kg-1, respectively, and their corresponding concentrations in crops were 0.024, 0.7, 0.041, and 0.06 mg kg-1, respectively. The… More >

  • Open Access

    ARTICLE

    Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

    Thavavel Vaiyapuri1, K. Priyadarshini2, A. Hemlathadhevi3, M. Dhamodaran4, Ashit Kumar Dutta5, Irina V. Pustokhina6,*, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2429-2444, 2022, DOI:10.32604/cmc.2022.026204

    Abstract Due to global financial crisis, risk management has received significant attention to avoid loss and maximize profit in any business. Since the financial crisis prediction (FCP) process is mainly based on data driven decision making and intelligent models, artificial intelligence (AI) and machine learning (ML) models are widely utilized. This article introduces an intelligent feature selection with deep learning based financial risk assessment model (IFSDL-FRA). The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise. In addition, the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection (WSOA-FS) manner to… More >

  • Open Access

    ARTICLE

    A Lightning Disaster Risk Assessment Model Based on SVM

    Jianqiao Sheng1, Mengzhu Xu2, Jin Han3,*, Xingyan Deng2

    Journal on Big Data, Vol.3, No.4, pp. 183-190, 2021, DOI:10.32604/jbd.2021.024892

    Abstract Lightning disaster risk assessment, as an intuitive method to reflect the risk of regional lightning disasters, has aroused the research interest of many researchers. Nowadays, there are many schemes for lightning disaster risk assessment, but there are also some shortcomings, such as the resolution of the assessment is not clear enough, the accuracy rate cannot be verified, and the weight distribution has a strong subjective trend. This paper is guided by lightning disaster data and combines lightning data, population data and GDP data. Through support vector machine (SVM), it explores a way to combine artificial intelligence algorithms with lightning disaster… More >

  • Open Access

    ARTICLE

    Estimation of Aleatory Randomness by Sa(T1)-Based Intensity Measures in Fragility Analysis of Reinforced Concrete Frame Structures

    Yantai Zhang1,*, Yongan Shi2, Baoyin Sun3, Zheng Wang4

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 73-96, 2022, DOI:10.32604/cmes.2022.016857

    Abstract Based on the multiple stripes analysis method, an investigation of the estimation of aleatory randomness by Sa(T1)-based intensity measures (IMs) in the fragility analysis is carried out for two typical low- and medium-rise reinforced concrete (RC) frame structures with 4 and 8 stories, respectively. The sensitivity of the aleatory randomness estimated in fragility curves to various Sa(T1)-based IMs is analyzed at three damage limit states, i.e., immediate occupancy, life safety, and collapse prevention. In addition, the effect of characterization methods of bidirectional ground motion intensity on the record-to-record variability is investigated. It is found that the damage limit state of… More >

  • Open Access

    ARTICLE

    Analyzing the Implications of COVID-19 Pandemic through an Intelligent-Computing Technique

    Abhishek Kumar Pandey1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Rajeev Kumar4,*, Raees Ahmad Khan1

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 959-974, 2022, DOI:10.32604/csse.2022.021443

    Abstract The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a decision making based methodology of… More >

  • Open Access

    ARTICLE

    Earthquake Risk Assessment Approach Using Multiple Spatial Parameters for Shelter Demands

    Wenquan Jin1, Naeem Iqbal2, Hee-Cheal Kang3, Dohyeun Kim2,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3763-3780, 2022, DOI:10.32604/cmc.2022.020336

    Abstract The earthquake is considered one of the most devastating disasters in any area of the world due to its potentially destructive force. Based on the various earthquake-related parameters, the risk assessment is enabled in advance to prevent future earthquake disasters. In this paper, for providing the shelter space demands to reduce the damage level and prevention costs, an earthquake risk assessment approach is proposed for deriving the risk index based on multiple spatial parameters in the gridded map. The proposed assessment approach is comprised of pre-processing, methodology model, and data visualization. The risk index model derives the earthquake risk index… More >

  • Open Access

    ARTICLE

    Hesitant Fuzzy-Sets Based Decision-Making Model for Security Risk Assessment

    Ahmed S. Alfakeeh1, Abdulmohsen Almalawi2, Fawaz Jaber Alsolami2, Yoosef B. Abushark2, Asif Irshad Khan2,*, Adel Aboud S. Bahaddad1, Alka Agrawal3, Rajeev Kumar4, Raees Ahmad Khan3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2297-2317, 2022, DOI:10.32604/cmc.2022.020146

    Abstract Security is an important component in the process of developing healthcare web applications. We need to ensure security maintenance; therefore the analysis of healthcare web application's security risk is of utmost importance. Properties must be considered to minimise the security risk. Additionally, security risk management activities are revised, prepared, implemented, tracked, and regularly set up efficiently to design the security of healthcare web applications. Managing the security risk of a healthcare web application must be considered as the key component. Security is, in specific, seen as an add-on during the development process of healthcare web applications, but not as the… More >

  • Open Access

    ARTICLE

    A New Random Forest Applied to Heavy Metal Risk Assessment

    Ziyan Yu1, Cong Zhang1,*, Naixue Xiong2, Fang Chen1

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 207-221, 2022, DOI:10.32604/csse.2022.018301

    Abstract As soil heavy metal pollution is increasing year by year, the risk assessment of soil heavy metal pollution is gradually gaining attention. Soil heavy metal datasets are usually imbalanced datasets in which most of the samples are safe samples that are not contaminated with heavy metals. Random Forest (RF) has strong generalization ability and is not easy to overfit. In this paper, we improve the Bagging algorithm and simple voting method of RF. A W-RF algorithm based on adaptive Bagging and weighted voting is proposed to improve the classification performance of RF on imbalanced datasets. Adaptive Bagging enables trees in… More >

  • Open Access

    ARTICLE

    A Mortality Risk Assessment Approach on ICU Patients Clinical Medication Events Using Deep Learning

    Dejia Shi1, Hanzhong Zheng2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 161-181, 2021, DOI:10.32604/cmes.2021.014917

    Abstract ICU patients are vulnerable to medications, especially infusion medications, and the rate and dosage of infusion drugs may worsen the condition. The mortality prediction model can monitor the real-time response of patients to drug treatment, evaluate doctors’ treatment plans to avoid severe situations such as inverse Drug-Drug Interactions (DDI), and facilitate the timely intervention and adjustment of doctor’s treatment plan. The treatment process of patients usually has a time-sequence relation (which usually has the missing data problem) in patients’ treatment history. The state-of-the-art method to model such time-sequence is to use Recurrent Neural Network (RNN). However, sometimes, patients’ treatment can… More >

  • Open Access

    ARTICLE

    A Network Security Risk Assessment Method Based on a B_NAG Model

    Hui Wang1, Chuanhan Zhu1, Zihao Shen1,*, Dengwei Lin2, Kun Liu1, MengYao Zhao3

    Computer Systems Science and Engineering, Vol.38, No.1, pp. 103-117, 2021, DOI:10.32604/csse.2021.014680

    Abstract Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between nodes of the attack graph… More >

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