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Articles 1 - 25 of 25
Full-Text Articles in Physical Sciences and Mathematics
Spatial Data Management For Green Mobility, Christophe Claramunt, Christine Bassem, Demetrios Zeinalipour-Yazti, Baihua Zheng, Goce Trajcevski, Kristian Torp
Spatial Data Management For Green Mobility, Christophe Claramunt, Christine Bassem, Demetrios Zeinalipour-Yazti, Baihua Zheng, Goce Trajcevski, Kristian Torp
Research Collection School Of Computing and Information Systems
While many countries are developing appropriate actions towards a greener future and moving towards adopting sustainable mobility activities, the real-time management and planning of innovative transportation facilities and services in urban environments still require the development of advanced mobile data management infrastructures. Novel green mobility solutions, such as electric, hybrid, solar and hydrogen vehicles, as well as public and gig-based transportation resources are very likely to reduce the carbon footprint. However, their successful implementation still needs efficient spatio-temporal data management resources and applications to provide a clear picture and demonstrate their effectiveness. This paper discusses the major data management challenges, …
On Predicting Esg Ratings Using Dynamic Company Networks, Gary Ang, Zhiling Guo, Ee-Peng Lim
On Predicting Esg Ratings Using Dynamic Company Networks, Gary Ang, Zhiling Guo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Environmental, social and governance (ESG) considerations play an increasingly important role due to the growing focus on sustainability globally. Entities, such as banks and investors, utilize ESG ratings of companies issued by specialized rating agencies to evaluate ESG risks of companies. The process of assigning ESG ratings by human analysts is however laborious and time intensive. Developing methods to predict ESG ratings could alleviate such challenges, allow ESG ratings to be generated in a more timely manner, cover more companies, and be more accessible. Most works study the effects of ESG ratings on target variables such as stock prices or …
The Analysis Of Extended Producer Responsibility (Epr) For E-Waste Management Policy Drivers And Challenges In Singapore, Aldy Gunawan, Tasaporn Visawameteekul, Aidan Marc Wong, Linh C. Tran
The Analysis Of Extended Producer Responsibility (Epr) For E-Waste Management Policy Drivers And Challenges In Singapore, Aldy Gunawan, Tasaporn Visawameteekul, Aidan Marc Wong, Linh C. Tran
Research Collection School Of Computing and Information Systems
This work examines the role of the Extended Producer Responsibility (EPR) scheme in managing electronic waste (e-waste) logistics in Singapore. The study investigates the challenges and policy drivers of e-waste management, using an online survey to explore the attitudes and behaviors of young consumers, with a particular focus on young people. We use the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) frameworks to develop a model that investigates the relationship among attitudes, perceived norms, awareness, and perceived convenience towards EPR awareness and stance. The findings highlight the needs for customized policies for different groups based on …
Scanet: Self-Paced Semi-Curricular Attention Network For Non-Homogeneous Image Dehazing, Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu, Jingxiang Qu, Shengfeng He, Ren Wenqi
Scanet: Self-Paced Semi-Curricular Attention Network For Non-Homogeneous Image Dehazing, Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu, Jingxiang Qu, Shengfeng He, Ren Wenqi
Research Collection School Of Computing and Information Systems
The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details. Existing homogeneous dehazing methods struggle to handle the non-uniform distribution of haze in a robust manner. The crucial challenge of non-homogeneous dehazing is to effectively extract the non-uniform distribution features and reconstruct the details of hazy areas with high quality. In this paper, we propose a novel self-paced semi-curricular attention network, called SCANet, for non-homogeneous image dehazing that focuses on enhancing haze-occluded regions. Our approach consists of an attention generator network and a scene re-construction network. We use the luminance …
Quantifying Stranded Assets Of The Coal-Fired Power In China Under The Paris Agreement Target, Weirong Zhang, Yiou Zhou, Zhen Gong, Junjie Kang, Changhong Zhao, Zhixu Meng, Jian Zhang, Tao Zhang, Jiahai Yuan
Quantifying Stranded Assets Of The Coal-Fired Power In China Under The Paris Agreement Target, Weirong Zhang, Yiou Zhou, Zhen Gong, Junjie Kang, Changhong Zhao, Zhixu Meng, Jian Zhang, Tao Zhang, Jiahai Yuan
Research Collection School Of Computing and Information Systems
Coal-fired power plays a critical role in China's compliance with the Paris Agreement. This research quantifies China's stranded coal assets under different coal capacity expansion scenarios with an integrated approach and high-precision coal-fired power database. From a top-down perspective, firstly, the pathway of China's coal-fired power capacity consistent with the global 2 degrees C scenario is outlined and then those stranded coal-fired power plants are identified with a bottom-up perspective. Stranded value is estimated based upon a cash flow algorithm. Results show that if coal capacity stabilizes during 2020-2030, China will only incur a sizeable yet manageable stranded asset loss …
Artificial Intelligence For Natural Disaster Management, Guansong Pang
Artificial Intelligence For Natural Disaster Management, Guansong Pang
Research Collection School Of Computing and Information Systems
Artificial intelligence (AI) can leverage massive amount of diverse types of data, such as geospatial data, social media data, and wireless network sensor data, to enhance our understanding of natural disasters, their forecasting and detection, and humanitarian assistance in natural disaster management (NDM). Due to this potential, different communities have been dedicating enormous efforts to the development and/or adoption of AI technologies for NDM. This article provides an overview of these efforts and discusses major challenges and opportunities in this topic.
Managing The Phaseout Of Coal Power: A Comparison Of Power Decarbonization Pathways In Jilin Province, Weirong Zhang, Zhixu Meng, Jiongjun Yang, Yan Song, Yiou Zhou, Changhong Zhao, Jiahai Yuan
Managing The Phaseout Of Coal Power: A Comparison Of Power Decarbonization Pathways In Jilin Province, Weirong Zhang, Zhixu Meng, Jiongjun Yang, Yan Song, Yiou Zhou, Changhong Zhao, Jiahai Yuan
Research Collection School Of Computing and Information Systems
With the periodic goals of reaching carbon emission peak before 2030 and achieving carbon neutrality before 2060 (“dual carbon” goals), China shows its unprecedented determination to coal power phaseout. This research takes Jilin Province to showcase possible pathways of coal power units’ phaseout on provincial level. We set up four different coal power phaseout scenarios, under which their transition cost and effectiveness would be calculated, respectively. In terms of natural resource endowment and electricity demand, Jilin Province would achieve a complete coal power phaseout by 2045 or even by 2040. However, after assessing the effectiveness of power transition under the …
Ispray: Reducing Urban Air Pollution With Intelligent Water Spraying, Yun Cheng, Zimu Zhou, Lothar Thiele
Ispray: Reducing Urban Air Pollution With Intelligent Water Spraying, Yun Cheng, Zimu Zhou, Lothar Thiele
Research Collection School Of Computing and Information Systems
Despite regulations and policies to improve city-level air quality in the long run, there lack precise control measures to protect critical urban spots from heavy air pollution. In this work, we propose iSpray, the first-of-its-kind data analytics engine for fine-grained PM2.5 and PM10 control at key urban areas via cost-effective water spraying. iSpray combines domain knowledge with machine learning to profile and model how water spraying affects PM25 and PM10 concentrations in time and space. It also utilizes predictions of pollution propagation paths to schedule a minimal number of sprayers to keep the pollution concentrations at key spots under control. …
Peer-To-Peer Trade And The Economy Of Distributed Pv In China, Peiyun Song, Yiou Zhou, Jiahai Yuan
Peer-To-Peer Trade And The Economy Of Distributed Pv In China, Peiyun Song, Yiou Zhou, Jiahai Yuan
Research Collection School Of Computing and Information Systems
With the deepening of power market reform, distributed power generation is gaining momentum. This paper tests the distributed photovoltaic (DPV) economy under different business models by taking three provinces to stand for typical resource zones. The Internal return rate (IRR) is used to measure the economy, while the improved levelized cost of electricity (LCOE) is used to model the generation cost. Three business modes, namely pure producer (all generation sold to the grid), prosumer (self-use and the rest sold to the grid), and peer-to-peer trade (P2P, all generation traded via the grid) are studied. Results show that peer-to-peer trade is …
The Spatial And Temporal Impact Of Agricultural Crop Residual Burning On Local Land Surface Temperature In Three Provinces Across China From 2015 To 2017, Wenting Zhang, Mengmeng Yu, Qingqing He, Tianwei Wang, Lu Lin, Kai Cao, Wei Huang, Peihong Fu, Jiaxin Chen
The Spatial And Temporal Impact Of Agricultural Crop Residual Burning On Local Land Surface Temperature In Three Provinces Across China From 2015 To 2017, Wenting Zhang, Mengmeng Yu, Qingqing He, Tianwei Wang, Lu Lin, Kai Cao, Wei Huang, Peihong Fu, Jiaxin Chen
Research Collection School Of Computing and Information Systems
China has suffered from severe crop residue burning (CRB) for a long time. As a type of biomass burning, CRB leads to a huge alteration in climate due to the emission of greenhouse gases and particulates in the atmosphere and damages to surface characteristics on land. At present, a growing body of research focuses on the impact of biomass burning (BB) (e.g., forest fire, grass fire, and CRB) on climate change from the aspect of atmospheric process. Meanwhile, a small number of research studies have started to pay attention on the damage caused by BB (e.g. forest fire) on land …
An Artificial Bee Colony-Based Hybrid Approach For Waste Collection Problem With Midway Disposal Pattern, Qu Wei, Zhaoxia Guo, Hoong Chuin Lau, Zhenggang He
An Artificial Bee Colony-Based Hybrid Approach For Waste Collection Problem With Midway Disposal Pattern, Qu Wei, Zhaoxia Guo, Hoong Chuin Lau, Zhenggang He
Research Collection School Of Computing and Information Systems
This paper investigates a waste collection problem with the consideration of midway disposal pattern. An artificial bee colony (ABC)-based hybrid approach is developed to handle this problem, in which the hybrid ABC algorithm is proposed to generate the better optimum-seeking performance while a heuristic procedure is proposed to select the disposal trip dynamically and calculate the carbon emissions in waste collection process. The effectiveness of the proposed approach is validated by numerical experiments. Experimental results show that the proposed hybrid approach can solve the investigated problem effectively. The proposed hybrid ABC algorithm exhibits a better optimum-seeking performance than four popular …
Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang
Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang
Research Collection School Of Computing and Information Systems
The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep …
Unearthing The X-Streams: Visualizing Water Contamination, Akangsha Bandalkul, Angad Srivastava, Kishan Bharadwaj Shridhar, Jason Guan Jie Ong, Yanrong Zhang
Unearthing The X-Streams: Visualizing Water Contamination, Akangsha Bandalkul, Angad Srivastava, Kishan Bharadwaj Shridhar, Jason Guan Jie Ong, Yanrong Zhang
Research Collection School Of Computing and Information Systems
The datasets released for VAST 2018 Mini Challenge 2 pertain to sensor readings capturing chemical concentrations and physical properties from water bodies in the Boonsong Lekagul wildlife preserve. This challenge is in continuation to the VAST 2017 Challenge, where the company Kasios was identified as the culprit in dumping the chemical - Methylosmoline. In the absence of actual chemical measurements in the soil, challenge participants need to visualize chemical contamination based on the proximal water bodies to identify trends of interest. A horizon plot developed helps to narrow down the complete list of 106 chemicals provided to only 7, …
Esg And Corporate Financial Performance: Empirical Evidence From China's Listed Power Generation Companies, Changhong Zhao, Yu Guo, Jiahai Yuan, Mengya Wu, Daiyu Li, Yiou Zhou, Jiangang Kang
Esg And Corporate Financial Performance: Empirical Evidence From China's Listed Power Generation Companies, Changhong Zhao, Yu Guo, Jiahai Yuan, Mengya Wu, Daiyu Li, Yiou Zhou, Jiangang Kang
Research Collection School Of Computing and Information Systems
Nowadays, listed companies around the world are shifting from short-term goals of maximizing profits to long-term sustainable environmental, social, and governance (ESG) goals. People have come to realize that ESG has become an important source of the corporate risk and may affect the company's financial performance and profitability. Recent research shows that good ESG performance could improve the financial performance in some countries. Yet, the question of how does ESG affect financial performance has not been thoroughly discussed and studied in China. In this article, we study China's listed power generation groups to explore the relationship between ESG performance and …
A Survey On Sensor Calibration In Air Pollution Monitoring Deployments, Balz Maah, Zimu Zhou, Lothar Thiele
A Survey On Sensor Calibration In Air Pollution Monitoring Deployments, Balz Maah, Zimu Zhou, Lothar Thiele
Research Collection School Of Computing and Information Systems
Air pollution is a major concern for public health and urban environments. Conventional air pollution monitoring systems install a few highly accurate, expensive stations at representative locations. Their sparse coverage and low spatial resolution are insufficient to quantify urban air pollution and its impacts on human health and environment. Advances in lowcost portable air pollution sensors have enabled air pollution monitoring deployments at scale to measure air pollution at high spatiotemporal resolution. However, it is challenging to ensure the accuracy of these low-cost sensor deployments because the sensors are more error-prone than high-end sensing infrastructures and they are often deployed …
Big Data For Climate Change Actions And The Paradox Of Citizen Informedness, Kustini Lim-Wavde, Robert J. Kauffman
Big Data For Climate Change Actions And The Paradox Of Citizen Informedness, Kustini Lim-Wavde, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
Advanced sensor technology, social media, and other information technologies have provided us with “big data” on climate change. Due to the World Meteorological Organization’s Global Climate Observing System, climate observations and records, as well as discussions on climate-related concerns such as measurement of air temperature, are widely available now. The United Nations’ Global Pulse visualises public engagement on climate change globally, with data such as the volume of climate-related tweets. Big data, data analytics, and the sharing of scientific results in the popular press have created, as a result, an unprecedented level of citizen informedness—the degree to which citizens have …
Household Informedness And Policy Analytics For The Collection And Recycling Of Household Hazardous Waste In California, Kustini Lim-Wavde, Robert J. Kauffman, Gregory S. Dawson
Household Informedness And Policy Analytics For The Collection And Recycling Of Household Hazardous Waste In California, Kustini Lim-Wavde, Robert J. Kauffman, Gregory S. Dawson
Research Collection School Of Computing and Information Systems
Collection and recycling of household hazardous waste (HHW) can vary due to differences in household incomes, demographics, material recyclability, and HHW collection programs. We evaluate the role of household informedness, the degree to which households have the necessary information to make utility-maximizing decisions about the handling of their waste. Household informedness seems to be influenced by HHW public education and environmental quality information. We assess the effects of household informedness on HHW collection and recycling using panel data, community surveys, drinking water compliance reports, and census data in California from 2004 to 2012. The results enable the calculation of …
Location Matters: Geospatial Policy Analytics Over Time For Household Hazardous Waste Collection In California, Kustini Lim-Wavde, Robert John Kauffman, Tin Seong Kam, Gregory S. Dawson
Location Matters: Geospatial Policy Analytics Over Time For Household Hazardous Waste Collection In California, Kustini Lim-Wavde, Robert John Kauffman, Tin Seong Kam, Gregory S. Dawson
Research Collection School Of Computing and Information Systems
By integrating mapping and geospatial data into a county-level datasetfor exploratory analysis, we will demonstrate how to provide useful insightsfor waste managers and local governments regarding spatial patterns ofhousehold hazardous waste (HHW) collection and how it changes over time. We usemap-based visualization to display patterns of spatial intensity and countylocations for HHW collection in California from 2004 to 2015. We use exploratory spatial data analyticsmethods to characterize the spatial distribution of HHW collected per person.When we considered the spatial relationships, we were able to develop andestimate a geographically-weighted regression to explain how different regionalfactors influence the amount of HHW collected. …
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Research Collection School Of Computing and Information Systems
To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.
Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson
Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson
Research Collection School Of Computing and Information Systems
Proper collection of Household Hazardous Waste (HHW) is an important action to support environmental sustainability. We investigate the role of household informedness, the degree to which households have the necessary information to make utility-maximizing decisions, as they relate to participation in HHW collection programs. We find two factors that influence household informedness: the provision of public education about HHW and environmental quality information. We conducted an empirical study on HHW collection in California to obtain statistical evidence on the effect of these factors on the amount of HHW collected. The findings of this policy analytics study improve our understanding of …
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah
Research Collection School Of Computing and Information Systems
The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.
Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta
Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta
Research Collection School Of Computing and Information Systems
The particle bound mercury (PBM) in urban-industrial areas is mainly of anthropogenic origin, and is derived from two principal sources: Hg bound to particulate matter directly emitted by industries and power generation plants, and adsorption of gaseous elemental mercury (GEM) and gaseous oxidized mercury (GOM) on air particulates from gas or aqueous phases. Here, we measured the Hg isotope composition of PBM in PM10 samples collected from three locations, a traffic junction, a waste incineration site and an industrial site in Kolkata, the largest metropolis in Eastern India. Sampling was carried out in winter and monsoon seasons between 2013–2015. …
A Study On Singapore Haze, Bingtian Dai, Kasthuri Jayarajah, Ee-Peng Lim, Archan Misra, Shriguru Nayak
A Study On Singapore Haze, Bingtian Dai, Kasthuri Jayarajah, Ee-Peng Lim, Archan Misra, Shriguru Nayak
Research Collection School Of Computing and Information Systems
In 2015, Singaporean have experienced one of the worse air pollution crises in history. With datasets from a well-known photo sharing social network, we analyze how this haze affects Singaporean's daily life. We will share our preliminary results in this paper.
Trace Element Composition Of Pm2.5 And Pm10 From Kolkata - A Heavily Polluted Indian Metropolis, Reshmi Das, Bahareh Khezri, Bijayen Srivastava, Subhajit Datta, Pradip Kumar Sikdar, Richard D. Webster, Xianfeng Wang
Trace Element Composition Of Pm2.5 And Pm10 From Kolkata - A Heavily Polluted Indian Metropolis, Reshmi Das, Bahareh Khezri, Bijayen Srivastava, Subhajit Datta, Pradip Kumar Sikdar, Richard D. Webster, Xianfeng Wang
Research Collection School Of Computing and Information Systems
Elemental composition of PM2.5 and PM10 was measured from 16 locations in Greater Kolkata in Eastern India. Sampling was carried out in the winter months of 2013–2014. PM2.5 and PM10 mass concentrations ranged from 83–783 μg/m3 and 167–928 μg/m3 respectively. 20 elements were measured with an Agilent 7700 series ICP–MS equipped with a 3rd generation He reaction/collision cell following closed vessel microwave digestion. In both size fractions Fe, Na, Al, K, Ca were present in high concentrations (>1 000 ng/m3), Mn, Zn and Pb demonstrated medium concentrations (>100 ng/m …
Disclosing Climate Change Patterns Using An Adaptive Markov Chain Pattern Detection Method, Zhaoxia Wang, Gary Lee, Hoong Maeng Chan, Reuben Li, Xiuju Fu, Rick Goh, Pauline A. W. Poh Kim, Martin L. Hibberd, Hoong Chor Chin
Disclosing Climate Change Patterns Using An Adaptive Markov Chain Pattern Detection Method, Zhaoxia Wang, Gary Lee, Hoong Maeng Chan, Reuben Li, Xiuju Fu, Rick Goh, Pauline A. W. Poh Kim, Martin L. Hibberd, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
This paper proposes an adaptive Markov chain pattern detection (AMCPD) method for disclosing the climate change patterns of Singapore through meteorological data mining. Meteorological variables, including daily mean temperature, mean dew point temperature, mean visibility, mean wind speed, maximum sustained wind speed, maximum temperature and minimum temperature are simultaneously considered for identifying climate change patterns in this study. The results depict various weather patterns from 1962 to 2011 in Singapore, based on the records of the Changi Meteorological Station. Different scenarios with varied cluster thresholds are employed for testing the sensitivity of the proposed method. The robustness of the proposed …