Savaş Takan^1,*, Duygu Ergün^2,*, Gökmen Katipoğlu³

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6059-6082, 2023, DOI:10.32604/cmc.2023.039505

Abstract As digital data circulation increases, information pollution and manipulation in journalism have become more prevalent. In this study, a new digital journalism model is designed to contribute to the solution of the main current problems, such as information pollution, manipulation, and accountability in digital journalism. The model uses blockchain technology due to its transparency, immutability, and traceability. However, it is tough to provide the mechanisms necessary for journalism, such as updating one piece of information, instantly updating all other information affected by the updated information, establishing logical relationships between news, making quick comparisons, sorting and indexing news, and keeping the… More >

Jiaxin Chen^1,#, Jiawei Guo^1,#, Zhixin Yang¹, Jiqing Yang^2,*, Hengwen Dong³, Huiyun Wang³, Yalei Wang³, Fangdong Zhan^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.2, pp. 471-485, 2023, DOI:10.32604/phyton.2022.023660

Abstract Heavy metal-polluted soil was collected from the Pulang copper mine in Shangri-La City, Yunnan Province, Southwest China. The effects of fertilizer (organic and inorganic) and arbuscular mycorrhizal fungi (AMF) on ryegrass (Lolium multiflorum L.) growth, root morphology, mineral nutrition and cadmium (Cd) and lead (Pb) contents were investigated by pot experiments. The results showed that both fertilizer and AMF significantly ameliorated the root morphology and mineral nutrition, reduced the Cd and Pb contents, and promoted the growth of ryegrass. Among all treatments, the combined application of organic–inorganic compound fertilizer with AMF had the highest effect, resulting in increases in root… More >

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 >

Jiusong Chen^1,*, Dejun Miao¹, Yizong Dai¹, Mojtaba Ghadamyari^2,*

Energy Engineering, Vol.119, No.5, pp. 1985-2003, 2022, DOI:10.32604/ee.2022.021142

Abstract Electric vehicles (EVs) have received special consideration from modern society over the past several years. Although EVs are a fine example of environmentally friendly technology and have many advantages, they relatively increase the electricity demand upon a power grid as well. Therefore, their negative impact on busvoltage and line losses should be analyzed. In this study, the effect of EV loads and their penetration on bus voltage and line losses of an IEEE-33 bussystem has been examined via two scenarios. It is important to mention that the effect of EVs on the rate of air pollution, produced by fossil fuel… More >

Nithya Rekha Sivakumar^*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2383-2398, 2023, DOI:10.32604/iasc.2023.028574

Abstract Internet of things (IoT) has brought a greater transformation in healthcare sector thereby improving patient care, minimizing treatment costs. The present method employs classical mechanisms for extracting features and a regression model for prediction. These methods have failed to consider the pollution aspects involved during COVID 19 prediction. Utilizing Ensemble Deep Learning and Framingham Feature Extraction (FFE) techniques, a smart healthcare system is introduced for COVID-19 pandemic disease diagnosis. The Collected feature or data via predictive mechanisms to form pollution maps. Those maps are used to implement real-time countermeasures, such as storing the extracted data or feature in a Cloud… More >

Manar Ahmed Hamza^1,*, Hadil Shaiba², Radwa Marzouk³, Ahmad Alhindi⁴, Mashael M. Asiri⁵, Ishfaq Yaseen¹, Abdelwahed Motwakel¹, Mohammed Rizwanullah¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3235-3250, 2022, DOI:10.32604/cmc.2022.029604

Abstract Environmental sustainability is the rate of renewable resource harvesting, pollution control, and non-renewable resource exhaustion. Air pollution is a significant issue confronted by the environment particularly by highly populated countries like India. Due to increased population, the number of vehicles also continues to increase. Each vehicle has its individual emission rate; however, the issue arises when the emission rate crosses the standard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop prediction approaches to monitor and control pollution using real time data. With the development of… More >

Xiaoxuan Zhu¹, Xueyan Wang², Li Lei^1,*, Yuting Zhao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 661-679, 2022, DOI:10.32604/cmes.2022.020427

Abstract In this study, numerical simulations were used to explore the effects of roadside green belt, urban street spatial layout, and wind speed on vehicle exhaust emission diffusion in street canyon. The diffusion of different sized particles in the street canyon and the influence of wind speed were investigated. The individual daily average pollutant intake was used to evaluate the exposure level in a street canyon microenvironment. The central and leeward green belts of the road were the most conducive to the diffusion of pollutants, while the positioning of the green belts both sides of a road was least conducive to… More >

Narendran Sobanapuram Muruganandam, Umamakeswari Arumugam^*

Computer Systems Science and Engineering, Vol.44, No.2, pp. 979-989, 2023, DOI:10.32604/csse.2023.024943

Abstract In forecasting real time environmental factors, large data is needed to analyse the pattern behind the data values. Air pollution is a major threat towards developing countries and it is proliferating every year. Many methods in time series prediction and deep learning models to estimate the severity of air pollution. Each independent variable contributing towards pollution is necessary to analyse the trend behind the air pollution in that particular locality. This approach selects multivariate time series and coalesce a real time updatable autoregressive model to forecast Particulate matter (PM) PM2.5. To perform experimental analysis the data from the Central Pollution… More >

Shun Wang¹, Lin Qiao², Wei Fang³, Guodong Jing⁴, Victor S. Sheng⁵, Yong Zhang^1,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 673-687, 2022, DOI:10.32604/cmc.2022.028411

Abstract PM2.5 concentration prediction is of great significance to environmental protection and human health. Achieving accurate prediction of PM2.5 concentration has become an important research task. However, PM2.5 pollutants can spread in the earth’s atmosphere, causing mutual influence between different cities. To effectively capture the air pollution relationship between cities, this paper proposes a novel spatiotemporal model combining graph attention neural network (GAT) and gated recurrent unit (GRU), named GAT-GRU for PM2.5 concentration prediction. Specifically, GAT is used to learn the spatial dependence of PM2.5 concentration data in different cities, and GRU is to extract the temporal dependence of the long-term… More >

R. Saravana Ram¹, K. Venkatachalam², Mehedi Masud³, Mohamed Abouhawwash^4,5,*

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1639-1652, 2022, DOI:10.32604/iasc.2022.023962

Abstract In current scenario, Wireless Sensor Networks (WSNs) has been applied on variety of applications such as targets tracking, natural resources investigation, monitoring on unapproachable place and so on. Through the sensor nodes, the information for the applications is gathered and transferred. The physical coordination of these sensor nodes is determined, and it is called as localization. The WSN localization methods are studied widely for recent research with the study of small proportion of the sensor node called anchor nodes and their positions are determined through the GPS devices. Sometimes sensor nodes can be a IoT device in the network. With… More >