Geopolymer concrete is the sustainable building material that can be used as an alternative for cement concrete. There are several factors that affect the property of geopolymer concrete such as type ...of binder material used, molarity of activator solution and curing condition. The frailty of practical application of geopolymer concrete lies in its brittle nature. The main objective of this work focuses towards the synthesis of high impact strength fiber reinforced geopolymer concrete by optimizing various factors that affect its strength and reduce its brittleness. The novelty of the work lies in the approach of augmentation of high modulus glass fibers over the optimized Geopolymer concrete. In the current investigation, extensive experimental works were conducted to optimize the molarity of alkaline solution, utilization of Ground Granulated Blast Furnace Slag and glass fiber in geopolymer concrete under different curing condition. Further Microstructural investigation through Scanning Electron Microscopic analysis and Energy Dispersive Spectroscopy analysis was carried over to understand the microstructure of the geopolymer matrix. An exhaustive and meticulous discussion part is included to elaborate the influence of molarity, curing condition, Ground Granulated Blast Furnace Slag utilization and incorporation of fibers in to the geopolymer matrix. Analytical Investigation though Artificial Neural Network has been performed to predict the compressive strength of the fiber reinforced geopolymer concrete based on three different input conditions. This study reported the optimum molarity of sodium hydroxide as 13M and optimum utilization of GGBS slag as 100 percent under ambient curing and 20 percent under heat curing. Further the work reported significant increase of about ten times in the energy absorption capacity and considerable decrease over the brittleness of the geopolymer concrete with the utilization of glass fiber. This research work could pave way for the development of high performance sustainable geopolymer concrete under ambient curing condition enabling the application of application of geopolymer concrete in industry that demand high impact strength materials such as machine foundations, pile caps, spill ways. This concrete could pave way for replacing conventional concrete in all its existing applications.
Display omitted
•Al–O–Si bond formation in flyash based Geopolymer Concrete.•C–S–H bond formation in steel slag based Geopolymer Concrete.•Incorporation of high modulus fibers in optimized Geopolymer Concrete.•Production of Sustainable High performance Geopolymer Concrete.•Prediction of compressive strength through Artificial Neural Network.
World-class trend set was focusing on finding an alternative for cement which is a major pollutant to the environment by releasing greenhouse gas emission. Meanwhile, disposal of waste by generating ...a suitable method for its effective utilization is a major role of researchers in global. Geopolymer is one of the most suitable alternatives for the utilization of all industrial wastes with aluminosilicate source material in which has a disadvantage of requirement of high alkaline solution and exposed temperature curing. In this study, alternative for cement in the view of low calcium based geopolymer was introduced to reduce the aforementioned problem in GPC. Meanwhile, GPC has a problem on less brittle, less energy absorption and impact resistance. Rubber tire is a huge available waste material which is most harmful to the environment if it burnt. Waste rubber tire has a property of high elasticity and it has an abundant way to use in the concrete. In order to counteract the aforementioned problems, waste rubber as a fiber was added at a variation of 0.5, 1, 1.5 and 2% of volume fractions. The addition of fibre up to 1 percent improved the setting properties and mechanical behaviors in all ages of curing. At the age of 90 days, the compressive strength, split tensile strength, flexural strength and modulus of elasticity of low calcium geopolymer mix was increased by 4.36%, 6.25%, 3.64% and 10.62% respectively. Further, addition of waste rubber fibre beyond 1 percent results in decreasing of all strength parameters.
•Production of sustainable high performance low calcium based geopolymer concrete.•Na–S–H bond formation in low calcium based Geopolymer Concrete.•Incorporation of waste tyre rubber as a fiber in optimized Geopolymer Concrete.•Effective way of disposing the waste wood ash and tyre rubber fibre.•Prediction of mechanical characterization of rubberized low calcium based geopolymer concrete.
The effect of bacterial and fiber combination to enhance the properties of GGBS based geopolymer concrete to be used as paver block is investigated in this study. In this study, Bacterial ...combinations such as Bacillus Subtillis and Bacillus Sphaericus and high modulus glass fibers and low modulus polypropylene fibers were incorporated to produce hybrid fiber reinforced bacterial geopolymer concrete with increased energy absorption characteristics and better post cracking behavior under heavy loads. Combined and the discrete performance of bacteria and fiber over the mechanical properties of the geopolymer concrete were investigated. The influence of bacterial strain combination over self-healing of concrete is also studied by inducing artificial cracks of 1mm over concrete. The self-healed products were subjected to microstructural investigation such as SEM analysis and XRD analysis to understand the microstructure of precipitated products and the bio- remedial action exhibited by the bacteria. Finally, the paver blocks were produced for the optimum specimens of geopolymer concrete along with fiber and bacteria and its performance over compressive, split tensile, flexural and water absorption characteristics were assessed to determine its adaptability to sustain loading under heavy and very heavy traffic conditions as per Indian Standard 15658 (2006). This research work lays a path for the sustainable development of production of eco-friendly self-healing high strength paver blocks.
Assessing the value of property is important in the real estate activity. Important factor to assess the property value is the location of the property. In India, value of a property is mainly ...evaluated by the guideline value and the market value. This paper addresses the effect of different parameters that affect the market value in Madurai Corporation area. It also addresses the implementation of urban valuation on a Geographic Information System for better decision-making. The valuation of the land depends upon the popularity and also the facilities around in that area. The spatial data constitutes the location information of the assets and the attributes that contain the details of the assets. Quantum GIS software is used for the storage and analysis of the data. The effective use of GIS along with reliable data and predictive tools can provide a robust and near realistic solution in predicting real estate trends. It is found that, for land assets, the Geographic Information System approach is effective. In this paper, we have used the statistical methods in order to find the market value and modelled value using Voronoi Polygon Method.
The significant environmental pollution caused by synthetic fibers drew researchers' attention to the development of eco-friendly reinforcement for composite products. This study seeks to identify an ...alternative novel natural fiber from the Cryptostegia Grandiflora (CG) plant as a reinforcement material for bio composites. The fiber chemical compositions, X-ray diffraction, Fourier Transform Infrared spectroscopy (FTIR), Scanning Electron Microscopy, Thermo Gravimetric Analysis, and tensile test for single fiber are all examined. The fiber had a cellulose content of 79.20% and a crystallinity index of 62%. Thermo Gravimetric Analysis confirms that Cryptostegia Grandiflora fiber (CGF) can withstand temperatures as high as 230°C. It has a density of 1.02 g/cc and a tensile strength of 791 MPa on average. This novel Cryptostegia Grandiflora fiber will undoubtedly be used as reinforcement material in bio-composite materials.
Nowadays, social media networks like Facebook, Twitter, Snapchat, Instagram, LinkedIn, and WhatsApp provide communication and connection on a huge scale. The revolution of social media networking has ...shared information and improved the digital world. Though these platforms are improved in creating new things, they have a dark side that leads in the wrong direction. The main dark side of this media is spreading false news against the people. The fake spreading has both advantages and disadvantages toward people. In particular, during the pandemic of COVID-19, the false news made people believe and misguided people into unexpected situations. Therefore, it is necessary to restrict false news to not reach a huge audience. A novel approach lightweight convolutional random forest-based honey badger (LCRF-HB) is proposed for the detection of fake news via three stages, namely the pre-processing of data, selecting features, and classifying features. Stop-word deletion, stemming, and tokenization are applied to pre-process input data during the pre-processing stage. Then, the features are minimized and the accuracy is enhanced in the selection stage via the honey badger (HB) optimization algorithm. The selected features are then provided to the classification phase where the lightweight convolutional random forest (LCRF) algorithm is used for classifying whether the news is fake or not. The performance metrics attain an accuracy of 98.7%, precision of 98.3%, specificity of 95.4%, and recall of 97.6%, respectively. The comparative analysis and performance evaluation are performed and enable a good performance rate as compared to other fake detection methods.
Land use land cover mapping practices over period in Madurai district varies due to increase of urban and rural migration. Valuation of land in urban areas is very important tool towards economic ...impact on human communities. Madurai is a temple city located on Vagai river bank which attract most tourists and also increase the urban areas due to various factors such as rural migration, Population increase. With the evidence from Government Land Register (GLR) and Present Market Rate (PMR )Values the Population is directly proportional to the value of land. Population increase last 12 years and built-up areas also increased. This paper studies the urban sprawl using land use land cover changes over the period of 2007 to 2019 between GLR and PMR values as per real estate practices in India. Using GIS techniques the analysis of urban sprawl of the city as well GLR, PMR values relationship by interpolation method to assess the land valuation practices which followed by Government of India.
Statement of RetractionWe, the Editor and Publisher of the journal European Journal of Remote Sensing, have retracted the following articles that were published in the Special Issue titled “Remote ...Sensing in Water Management and Hydrology”:Marimuthu Karuppiah, Xiong Li & Shehzad Ashraf Chaudhry (2021) Guest editorial of the special issue “remote sensing in water management and hydrology”, European Journal of Remote Sensing, 54:sup2, 1-5, DOI: 10.1080/22797254.2021.1892335Jian Sheng, Shiyi Jiang, Cunzhu Li, Quanfeng Liu & Hongyan Zhang (2021) Fluid-induced high seismicity in Songliao Basin of China, European Journal of Remote Sensing, 54:sup2, 6-10, DOI: 10.1080/22797254.2020.1720525Guohua Wang, Jun Tan & Lingui Wang (2021) Numerical simulation of temperature field and temperature stress of thermal jet for water measurement, European Journal of Remote Sensing, 54:sup2, 11-20, DOI: 10.1080/22797254.2020.1743956Le Wang, Guancheng Jiang & Xianmin Zhang (2021) Modeling and molecular simulation of natural gas hydrate stabilizers, European Journal of Remote Sensing, 54:sup2, 21-32, DOI: 10.1080/22797254.2020.1738901Tianyi Chen, Lu Bao, Liu Bao Zhu, Yu Tian, Qing Xu & Yuandong Hu (2021) The diversity of birds in typical urban lake-wetlands and its response to the landscape heterogeneity in the buffer zone based on GIS and field investigation in Daqing, China, European Journal of Remote Sensing, 54:sup2, 33-41, DOI: 10.1080/22797254.2020.1738902Zhiyong Wang (2021) Research on desert water management and desert control, European Journal of Remote Sensing, 54:sup2, 42-54, DOI: 10.1080/22797254.2020.1736953Ji-Tao Li & Yong-Quan Liang (2021) Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale, European Journal of Remote Sensing, 54:sup2, 55-64, DOI: 10.1080/22797254.2020.1740894Wei Wang, R. Dinesh Jackson Samuel & Ching-Hsien Hsu (2021) Prediction architecture of deep learning assisted short long term neural network for advanced traffic critical prediction system using remote sensing data, European Journal of Remote Sensing, 54:sup2, 65-76, DOI: 10.1080/22797254.2020.1755998Yan Chen, Ming Tan, Jiahua Wan, Thomas Weise & Zhize Wu (2021) Effectiveness evaluation of the coupled LIDs from the watershed scale based on remote sensing image processing and SWMM simulation, European Journal of Remote Sensing, 54:sup2, 77-91, DOI: 10.1080/22797254.2020.1758962Ke Deng & Ming Chen (2021) Blasting excavation and stability control technology for ultra-high steep rock slope of hydropower engineering in China: a review, European Journal of Remote Sensing, 54:sup2, 92-106, DOI: 10.1080/22797254.2020.1752811Yufa He, Xiaoqiang Guo, Jun Liu, Hongliang Zhao, Guorong Wang & Zhao Shu (2021) Dynamic boundary of floating platform and its influence on the deepwater testing tube, European Journal of Remote Sensing, 54:sup2, 107-116, DOI: 10.1080/22797254.2020.1762246Kai Peng, Yunfeng Zhang, Wenfeng Gao & Zhen Lu (2021) Evaluation of human activity intensity in geological environment problems of Ji’nan City, European Journal of Remote Sensing, 54:sup2, 117-121, DOI: 10.1080/22797254.2020.1771214Wei Zhu, XiaoSi Su & Qiang Liu (2021) Analysis of the relationships between the thermophysical properties of rocks in the Dandong Area of China, European Journal of Remote Sensing, 54:sup2, 122-131, DOI: 10.1080/22797254.2020.1763205Yu Liu, Wen Hu, Shanwei Wang & Lingyun Sun (2021) Eco-environmental effects of urban expansion in Xinjiang and the corresponding mechanisms, European Journal of Remote Sensing, 54:sup2, 132-144, DOI: 10.1080/22797254.2020.1803768Peng Qin & Zhihui Zhang (2021) Evolution of wetland landscape disturbance in Jiaozhou Gulf between 1973 and 2018 based on remote sensing, European Journal of Remote Sensing, 54:sup2, 145-154, DOI: 10.1080/22797254.2020.1758963Mingyi Jin & Hongyan Zhang (2021) Investigating urban land dynamic change and its spatial determinants in Harbin city, China, European Journal of Remote Sensing, 54:sup2, 155-166, DOI: 10.1080/22797254.2020.1758964Balaji L. & Muthukannan M. (2021) Investigation into valuation of land using remote sensing and GIS in Madurai, Tamilnadu, India, European Journal of Remote Sensing, 54:sup2, 167-175, DOI: 10.1080/22797254.2020.1772118Xiaoyan Shi, Jianghui Song, Haijiang Wang & Xin Lv (2021) Monitoring soil salinization in Manas River Basin, Northwestern China based on multi-spectral index group, European Journal of Remote Sensing, 54:sup2, 176-188, DOI: 10.1080/22797254.2020.1762247GN Vivekananda, R Swathi & AVLN Sujith (2021) Multi-temporal image analysis for LULC classification and change detection, European Journal of Remote Sensing, 54:sup2, 189-199, DOI: 10.1080/22797254.2020.1771215Yiting Wang, Xianghui Liu & Weijie Hu (2021) The research on landscape restoration design of watercourse in mountainous city based on comprehensive management of water environment, European Journal of Remote Sensing, 54:sup2, 200-210, DOI: 10.1080/22797254.2020.1763206Bao Qian, Cong Tang, Yu Yang & Xiao Xiao (2021) Pollution characteristics and risk assessment of heavy metals in the surface sediments of Dongting Lake water system during normal water period, European Journal of Remote Sensing, 54:sup2, 211-221, DOI: 10.1080/22797254.2020.1763207Jin Zuo, Lei Meng, Chen Li, Heng Zhang, Yun Zeng & Jing Dong (2021) Construction of community life circle database based on high-resolution remote sensing technology and multi-source data fusion, European Journal of Remote Sensing, 54:sup2, 222-237, DOI: 10.1080/22797254.2020.1763208Zilong Wang, Lu Yang, Ping Cheng, Youyi Yu, Zhigang Zhang & Hong Li (2021) Adsorption, degradation and leaching migration characteristics of chlorothalonil in different soils, European Journal of Remote Sensing, 54:sup2, 238-247, DOI: 10.1080/22797254.2020.1771216R. Vijaya Geetha & S. Kalaivani (2021) A feature based change detection approach using multi-scale orientation for multi-temporal SAR images, European Journal of Remote Sensing, 54:sup2, 248-264, DOI: 10.1080/22797254.2020.1759457LianJun Chen, BalaAnand Muthu & Sivaparthipan cb (2021) Estimating snow depth Inversion Model Assisted Vector Analysis based on temperature brightness for North Xinjiang region of China, European Journal of Remote Sensing, 54:sup2, 265-274, DOI: 10.1080/22797254.2020.1771217Yajuan Zhang, Cuixia Li & Shuai Yao (2021) Spatiotemporal evolution characteristics of China’s cold chain logistics resources and agricultural product using remote sensing perspective, European Journal of Remote Sensing, 54:sup2, 275-283, DOI: 10.1080/22797254.2020.1765202Guangping Liu, Jingmei Wei, BalaAnand Muthu & R. Dinesh Jackson Samuel (2021) Chlorophyll-a concentration in the hailing bay using remote sensing assisted sparse statistical modelling, European Journal of Remote Sensing, 54:sup2, 284-295, DOI: 10.1080/22797254.2020.1771774Yishu Qiu, Zhenmin Zhu, Heping Huang & Zhenhua Bing (2021) Study on the evolution of B&Bs spatial distribution based on exploratory spatial data analysis (ESDA) and its influencing factors—with Yangtze River Delta as an example, European Journal of Remote Sensing, 54:sup2, 296-308, DOI: 10.1080/22797254.2020.1785950Liang Li & Kangning Xiong (2021) Study on peak cluster-depression rocky desertification landscape evolution and human activity-influence in South of China, European Journal of Remote Sensing, 54:sup2, 309-317, DOI: 10.1080/22797254.2020.1777588Juan Xu, Mengsheng Yang, Chaoping Hou, Ziliang Lu & Dan Liu (2021) Distribution of rural tourism development in geographical space: a case study of 323 traditional villages in Shaanxi, China, European Journal of Remote Sensing, 54:sup2, 318-333, DOI: 10.1080/22797254.2020.1788993Lin Guo, Xiaojing Guo, Binghua Wu, Po Yang, Yafei Kou, Na Li & Hui Tang (2021) Geo-environmental suitability assessment for tunnel in sub-deep layer in Zhengzhou, European Journal of Remote Sensing, 54:sup2, 334-340, DOI: 10.1080/22797254.2020.1788994Hui Zhou, Cheng Zhu, Li Wu, Chaogui Zheng, Xiaoling Sun, Qingchun Guo & Shuguang Lu (2021) Organic carbon isotope record since the Late Glacial period from peat in the North Bank of the Yangtze River, China, European Journal of Remote Sensing, 54:sup2, 341-347, DOI: 10.1080/22797254.2020.1795728Chengyuan Hao, Linlin Song & Wei Zhao (2021) HYSPLIT-based demarcation of regions affected by water vapors from the South China Sea and the Bay of Bengal, European Journal of Remote Sensing, 54:sup2, 348-355, DOI: 10.1080/22797254.2020.1795730Wei Chong, Zhang Lin-Jing, Wu Qing, Cao Lian-Hai, Zhang Lu, Yao Lun-Guang, Zhu Yun-Xian & Yang Feng (2021) Estimation of landscape pattern change on stream flow using SWAT-VRR, European Journal of Remote Sensing, 54:sup2, 356-362, DOI: 10.1080/22797254.2020.1790994Kepeng Feng & Juncang Tian (2021) Forecasting reference evapotranspiration using data mining and limited climatic data, European Journal of Remote Sensing, 54:sup2, 363-371, DOI: 10.1080/22797254.2020.1801355Kepeng Feng, Yang Hong, Juncang Tian, Xiangyu Luo, Guoqiang Tang & Guangyuan Kan (2021) Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States, European Journal of Remote Sensing, 54:sup2, 372-382, DOI: 10.1080/22797254.2020.1819169Xiaowei Xu, Yinrong Chen, Junfeng Zhang, Yu Chen, Prathik Anandhan & Adhiyaman Manickam (2021) A novel approach for scene classification from remote sensing images using deep learning methods, European Journal of Remote Sensing, 54:sup2, 383-395, DOI: 10.1080/22797254.2020.1790995Shanshan Hu, Zhaogang Fu, R. Dinesh Jackson Samuel & Prathik Anandhan (2021) Application of active remote sensing in confirmation rights and identification of mortgage supply-demand subjects of rural land in Guangdong Province, European Journal of Remote Sensing, 54:sup2, 396-404, DOI: 10.1080/22797254.2020.1790996Chen Qiwei, Xiong Kangning & Zhao Rong (2021) Assessment on erosion risk based on GIS
During the COVID‐19 pandemic, online social networks are extensively utilized, more than ever before by 8.4%, resulting in the propagation of false information related to COVID‐19. Despite the ...existence of many fake news detection models; annotation inconsistency, memory consumption, accurate and self‐trained efficient algorithms for detecting the emerging COVID‐19 misinformation tweets are still challenging. Hence, the main aim of this work is to come up with a self‐trained semi‐supervised model that accurately and automatically detects the reliability of emerging COVID‐19 tweets without delay. In this work, COVID‐19 tweet dataset is created in English Language from the period January 2020 to January 2022 as a ground truth database. Then self‐trained semi‐supervised hybrid deep learning model is proposed to train both supervised and unsupervised components simultaneously using the created dataset. The proposed model is self‐trained repeatedly and the model gets updated to predict the reliability of upcoming COVID‐19 tweets that differ from training tweets. We performed experiments multiple times by limiting the percentage amount of labelled tweets shown to the model, namely 80%, 50%, 40%, 30%, 20% and 10% labelled tweets, respectively. Experimental results show that the proposed model achieves 80.92% accuracy and 98.15% accuracy in the 10% and 80% label‐seen experiments, respectively. This shows a clear rising trend in the performance curve. Therefore, this technique will be useful for effectively classifying voluminous amounts of emerging tweets generated as part of the COVID‐19 infodemic. The proposed model may efficiently use a huge amount of unlabelled tweets and enhance the model's generalization performance.
PDF
