Abstract

Sexism, an injustice that subjects women and girls to enormous suffering, manifests in blatant as well as subtle ways. In the wake of growing documentation of experiences of sexism on the web, the automatic categorization of accounts of sexism has the potential to assist social scientists and policy makers in utilizing such data to study and counter sexism better. The existing work on sexism classification, which is different from sexism detection, has certain limitations in terms of the categories of sexism used and/or whether they can co-occur. To the best of our knowledge, this is the first work on the multi-label classification of sexism of any kind(s), and we contribute the largest dataset for sexism categorization. We develop a neural solution for this multilabel classification that can combine sentence representations obtained using models such as BERT with distributional and linguistic word embeddings using a flexible, hierarchical architecture involving recurrent components and optional convolutional ones. Further, we leverage unlabeled accounts of sexism to infuse domain-specific elements into our framework. The best proposed method outperforms several deep learning as well as traditional machine learning baselines by an appreciable margin.

Abstract

Analysis of high variability of inter-state land use land cover change using remote sensing and GIS techniques primarily agriculture in Krishna river basin, India.

Abstract

By 2050 most parts of India will be water stressed zones as most of the water resources are under heavy stress due to increasing nutrient contamination in their waters. In this scenario, studying the changes occurring in the freshwater nutrient contamination levels over a temporal scale is extremely important. This study focuses on monitoring the changes occurring in the nutrient contamination levels over a decade in a large reservoir known as Nagarjuna Sagar (NS) using remote sensing data. In this study, Landsat (5 & 8) data for the year 2005, 2009, 2015 and Sentinel (2A and 2B) data for the years 2016 and 2018 is used to study nutrient contamination in NS. The spatial spread of chlorophyll-a (chl-a) area is used as a proxy to estimate the extent of nutrient contamination in NS. In this study, only October images of NS are used as they exhibit the maximum spatial spread of Chl-a and hence help assess the contamination levels over the period 2005-2018. The analysis shows that during this period, chl-a spatial spread area has increased from 21 Km2 to 205 Km2, indicating a decrease in water quality in the reservoir. The study shows that this is accompanied by an increase in the agricultural land use area by 1000 Km2 in addition to a steep increase in the use of agricultural inputs, primarily fertilisers like urea, P and K. Thus, while the combined effect of excessive usage of fertilizers with agricultural intensification has increased crop yields, it has also contributed to damaging the freshwater resources.

Abstract

Geospatial data capture and handling of indoor spaces is increasing over the years and has had a varied history of data sources ranging from architectural and building drawings to indoor data acquisition approaches. While these have been more data format and information driven primarily for the physical representation of spaces, it is important to note that many applications look for the semantic information to be made available. This paper proposes a space classification model leading to an ontology for indoor spaces that accounts for both the semantic and geometric characteristics of the spaces. Further, a Space semantic model is defined, based on this ontology, which can then be used appropriately in multiple applications. To demonstrate the utility of the model, we also present an extension to the IndoorGML data standard with a set of proposed classes that can help capture both the syntactic and semantic components of the model. It is expected that these proposed classes can be appropriately harnessed for use in diverse applications ranging from indoor data visualization to more user customised building evacuation path planning with a semantic overtone. View Full-Text

Abstract

River water bodies serve as prominent water sources for various purposes ranging from drinking water, waste load allocation, irrigation, hydropower generation and ecosystem services. Human activities and natural processes require a balanced water supply and demand, while population growth, land use and climate change are the external forces which try to change the stream and river water quan-tity and quality. Water temperature is an inherent property of its quality and a con-trolling factor of health of freshwater environments. It is often considered as a driver of metabolic activity in water bodies, which influence the biological and chemical processes affecting the metabolic responses from organisms to ecosystems. The present work aims to explore sources of predictability of river water temperature (RWT) as a keen driver of hydrological and ecological processes at multiple scales. Increasing RWT in response to climate change and local-to-regional anthropogenic activities result in decreasing dissolved oxygen (DO) levels and anaerobic condi-tions in the aquatic system, thereby affecting marine life and the consequent avail-ability of food, reproduction and migration. An assessment of integrated RWT and streamflow fluctuations is proposed to evidence biological activity, chemical specia-tion, oxygen solubility and self-purification capacity of a river system and fluctua-tions of flows responsive to hydro-climate pulses. The independent and integrated contributions of air temperatures and flow fluctuations to RWT in the Missouri River near Nebraska City, USA, represent the stream responses to global raising temperatures. To quantify the contributions of multiple variations of predictor vari-ables in the air-water interfaces to RWT variability, we use a multiple regression. The performance of the model was tested along Missouri River near Nebraska City, USA, using historical series of daily river water temperature, air temperature and river discharges for the 1947–2014 period. A sensitivity analysis on river water temperature is performed, under air temperature increase of +2 °C, +4 °C and + 6 °C with a decrease of discharge of ±20%. Overall, the increase of RWT for the Missouri River is observed as about 2.76 °C under various air temperature and discharge changes when compared with the observed conditions at mean annual scale. The study results provide a comprehensive analysis of the impacts of river discharge and air temperature changes under climate change over RWT.

Abstract

This study aimed to estimate water quality–based minimum environmental flow (Eflow) of a river under the impact of different plausible scenarios. The water quality model QUAL2K was deployed to simulate levels of dissolved oxygen (DO) and biochemical oxygendemand (BOD) in a river during the dry season. Hypothetical scenarios of pollution were generated by varying BOD in contributing drains,and climate change scenarios were generated by altering air temperature over the study region. DO and BOD levels were simulated under theimpact of various scenarios. Corresponding to each scenario, minimum Eflow throughout the river stretch—that is, the headwaters flow(quantity and quality) meeting desirable river water quality standards (as proposed by the Indian Central Pollution Control Board)—was explored. Water quality charts were developed for direct and user-friendly estimation of Eflows. The proposed approach was applied to the Yamuna and Bhadra rivers in India. The results reveal the inefficiency of existing river flow conditions in maintaining permissible water quality standards. Adverse effects of pollution load, upstream diversions, and climate change are highlighted.

Abstract

Validation of precipitation data is important for hydrological modeling. Though there are many models available, rainfall prediction is difficult due to various uncertainties. This study is an attempt to compare and assess the Coordinated Regional Climate Downscaling Experiment (CORDEX) model data and India Meteorological Department (IMD) observed gridded data over Malaprabha river basin, Karnataka state, India. Both gridded data sets were downscaled at 0.25× 0.25 resolution and then processed into a 12× 115 matrix form by using QGIS (2.18. 24) and MATLAB (R2003a). These two products were compared over the period 1961-2015 to evaluate their behavior in terms of fitness by using statistical parameters such as NSE, D, R, MAE, MBE and RMSE values. Results showed that out of 16 grid points, fourteen grid points showed medium correlation ranging between 0.30 and 0.49.

Abstract

In the present study an attempt has been made to propose the application of rice husk ash (RHA), by strengthening it using quarry waste (QW) as additive material in varying percentages of weight. Geotechnical properties of RHA and its combinations with quarry waste (RQ10, RQ20, RQ30, RQ40, RQ50 and RQ60) have been studied by performing grain size analysis, specific gravity, compaction, permeability and triaxial tests. The maximum increase in density, shear strength of RHA upon the addition of quarry waste was observed to be about 45.6% and 39%, respectively. The permeability of RHA, RQ mixes was found to be in fine sand range and hence their application as shell material in earth dam was proposed. The combination RQ50, with equal amounts of RHA and QW was found to exhibit maximum shear strength and was thus considered as the optimum mix. To assess the suitability of RQ50 as shell material in earth dam, numerical analysis of dam system was performed under seismic loading using FEM software Plaxis2D. The seismic behavior of dam system under the application of Nepal input motion was found satisfactory showing high shear resistance and safety against liquefaction. From the outcomes of laboratory and numerical investigations, RHA-QW mixture has been considered as a promising material to be used in earth dam enabling the bulk utilization of both the waste materials.

Abstract

Afghanistan is the most vulnerable to climate extremes related hazards, including droughts and floods that have caused huge impact on the socio-economic development of the country. The present study analysed the observed precipitation and temperature trends for seven agro-climatic zones of Afghanistan over the period 1951 to 2006 with Asian Precipitation-Highly-Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE). The trend analysis was performed on daily data to test the increasing or decreasing rainfall and temperature trends using Mann-Kendall trend test for each agro-climatic zone of Afghanistan. The annual total precipitation has shown an increasing trend for the zones of South, South-West, East and Central, whereas, a decreasing trend has been observed for North, North-East and West zones of Afghanistan. The trend analysis of the precipitation with gridded data sets reveals for most parts of the Afghanistan, the rainfall has been observed to be decreasing. Whereas, an increasing trend of temperatures were observed for all seven agro-climatic zones of Afghanistan.

Abstract

In the present investigation, an attempt has been made to propose a lightweight back fill material using industrial wastes, namely quarry waste and granulated rubber. Granulated rubber was added in varying percentages (5%, 10%, 15%, 20%, 25%, and 30%) to quarry wastefor obtaining lightweight material. Laboratory investigation has been performed in the present study to examine the physical, chemical, andgeotechnical properties of quarry waste and the geotechnical behavior of quarry waste–granulated rubber (QWGR) mixes. Using granulatedrubber as additive, the unit weight of quarry waste material was found to reduce from 21.8 to14.1kN=m3for QWGR30 mix. The friction angleof quarry waste was obtained to be 51.2°, which increased by about 14° with rubber addition for the QWGR30 mix. The permeability of quarrywaste was found to improve from fine sand to coarse sand range with the granulated rubber inclusion, making it an efficient backfill material.QWGR30 mix was found to be an efficient lightweight backfill material with reduced lateral pressure by about 73% and 85% comparedto quarry waste and conventional sand, respectively. The economic savings of the project on backfill material by using QWGR30 over conven-tional sand would be around 8.35%. DOI:10.1061/(ASCE)HZ.2153-5515.0000455.© 2019 American Society of Civil Engineers.