ACM Journal on Computing and Sustainable Societies最新文献

What's Up On The Roof: Tracking Cool Roofs in India with Satellite Imaging 屋顶上有什么？利用卫星图像追踪印度的凉爽屋顶

ACM Journal on Computing and Sustainable Societies Pub Date : 2024-08-10 DOI: 10.1145/3685696

Varchita Lalwani, Anupam Sobti, Vishal Garg

{"title":"What's Up On The Roof: Tracking Cool Roofs in India with Satellite Imaging","authors":"Varchita Lalwani, Anupam Sobti, Vishal Garg","doi":"10.1145/3685696","DOIUrl":"https://doi.org/10.1145/3685696","url":null,"abstract":"With rapid pace of urbanization, the increase in built up area is leading to urban heat islands which absorb a lot of the heat received through solar radiation. To reduce this effect, reflective coatings on top of building roofs, known as cool roofs are installed. Cool roofs reflect light back through the atmosphere to minimize the heat radiation within the urban space. In this paper, we introduce a cool roof tracker. The tracker provides building level information of whether a roof is cool or not, thus indicating if an urban heat island is likely to develop in a region. This information helps policymakers identify the vulnerable regions in a city and track the progress of cool roof implementation in all areas.\u0000 There are three key components of the system: building polygon extraction, reflectance features extraction from roof images; and classification into cool vs non cool buildings. There are a number of satellites operational today which offer different strengths - high resolution, high revisit time, multiple spectral bands, etc. In this work, we do a mix of quantitative and qualitative evaluation of the efficacy of different satellite modalities for each of the system components, build robust models with extensive experimentation on color space, augmentations, and generalization achieving an F1-score of 97% on our test set. We also develop a prototype dashboard as a demonstration for supporting data-driven decision making for state level heat mitigation plans as well as regulatory and compliance tool for measuring roof reflectance.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"3 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experiences from Running a Voice-Based Education Platform for Children and Teachers with Visual Impairments 视障儿童和教师语音教育平台的运行经验

ACM Journal on Computing and Sustainable Societies Pub Date : 2024-08-08 DOI: 10.1145/3677323

Roshni Poddar, Tarini Naik, Manikanteswar Punnam, Kavyansh Chourasia, Rajeswari Pandurangan, Rajesh S Paali, Nagarathna R Bhat, Bhagyashree Biradar, Venkatesh Deshpande, Devidatta Ghosh, Sudipta Ray Chaudhuri, Dipanjan Chakraborty, Amit Prakash, Manohar Swaminathan

{"title":"Experiences from Running a Voice-Based Education Platform for Children and Teachers with Visual Impairments","authors":"Roshni Poddar, Tarini Naik, Manikanteswar Punnam, Kavyansh Chourasia, Rajeswari Pandurangan, Rajesh S Paali, Nagarathna R Bhat, Bhagyashree Biradar, Venkatesh Deshpande, Devidatta Ghosh, Sudipta Ray Chaudhuri, Dipanjan Chakraborty, Amit Prakash, Manohar Swaminathan","doi":"10.1145/3677323","DOIUrl":"https://doi.org/10.1145/3677323","url":null,"abstract":"\u0000 India has the world’s largest population of children with vision impairments (CVIs), a group facing significant educational barriers including inadequate accessible resources, limited school access, and a shortage of trained teachers. The authors from four different organizations including a non-profit dedicated to enhancing STEM education for CVIs through interactive, play-based learning and teacher training have collaborated to create SEEDS, Scalable Educational Experiences with Digital Scaffolding. This is a voice-based platform for educational experiences delivery, featuring an Android Teacher App, an Interactive Voice Response (IVR) system, and a comprehensive website for content management. The Teacher app facilitates educational experiences via group calls with students, while the IVR system offers students independent access to educational content using feature phones. To assess effectiveness and usability of SEEDS among students and teachers, we conducted a mixed-methods study involving 29 visually impaired students across five schools and five facilitators (3 sighted and 2 visually impaired) from\u0000 Vision Empower Trust\u0000 . Despite challenges like internet connectivity issues causing call drops, the study highlighted strong student engagement and a collaborative environment among facilitators. By open-sourcing the SEEDS codebase, we aim to improve the platform and increase its adoption among teachers in schools for CVIs across India and beyond.\u0000","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Examining Factors Influencing Technology Integration in Indian Classrooms: A Teachers' Perspective 研究影响印度课堂技术整合的因素：教师的视角

ACM Journal on Computing and Sustainable Societies Pub Date : 2024-08-08 DOI: 10.1145/3677325

Tarini Naik, Meena Elapulli Shankaranarayanan, Manohar Swaminathan, Kalika Bali, Mohit Jain

引用次数: 0

Shadow Program Committee: Designing for Diversity and Equity within Academic Communities 影子计划委员会：设计学术社区内的多样性和公平性

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-10-28 DOI: 10.1145/3630743

Delvin Varghese, Hafeni Mthoko, Jessica Watterson, P. Kulkarni, Dan Richardson, Shaimaa Y. Lazem, Patrick Olivier

{"title":"Shadow Program Committee: Designing for Diversity and Equity within Academic Communities","authors":"Delvin Varghese, Hafeni Mthoko, Jessica Watterson, P. Kulkarni, Dan Richardson, Shaimaa Y. Lazem, Patrick Olivier","doi":"10.1145/3630743","DOIUrl":"https://doi.org/10.1145/3630743","url":null,"abstract":"The development of early career researchers (ECRs) and their induction into academia has traditionally been a process that is at best obscure, and at worst, cronyism laden. Arguably this is especially true for cross-disciplinary fields like HCI, where relatively fragmented specialisms co-exist. With COVID-19 and its negative impacts on ECRs as the backdrop, we explored the design of a five-month virtual training program for ECRs worldwide (with particular emphasis on Global South). Through an action research approach, the program was executed in collaboration with the organizers of a cross-disciplinary conference. 81 participants from 26 countries took part. The program created a collaborative learning experience for attendees and provided opportunities for networking and learning the nuances of the peer-review process. This paper details our experiences and provides reflections on design opportunities to (1) develop professional development spaces for underserved researchers, and (2) leverage ECRs’ unique capacity for contributing to inclusive conference spaces.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139311998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flamingo: Environmental Impact Factor Matching for Life Cycle Assessment with Zero-Shot Machine Learning 火烈鸟:零射击机器学习生命周期评估的环境影响因子匹配

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-09-08 DOI: 10.1145/3616385

Bharathan Balaji, Venkata Sai Gargeya Vunnava, Nina Domingo, Shikhar Gupta, Harsh Gupta, G. Guest, Aravind Srinivasan

{"title":"Flamingo: Environmental Impact Factor Matching for Life Cycle Assessment with Zero-Shot Machine Learning","authors":"Bharathan Balaji, Venkata Sai Gargeya Vunnava, Nina Domingo, Shikhar Gupta, Harsh Gupta, G. Guest, Aravind Srinivasan","doi":"10.1145/3616385","DOIUrl":"https://doi.org/10.1145/3616385","url":null,"abstract":"Consumer products contribute to more than 75% of global greenhouse gas (GHG) emissions, primarily through indirect contributions from the supply chain. Measurement of GHG emissions associated with products is a crucial step toward quantifying the impact of GHG emission abatement actions. Life cycle assessment (LCA), the scientific discipline for measuring GHG emissions, estimates the environmental impact associated with each stage of a product from raw material extraction to its disposal. Scaling LCA to millions of products is challenging as it requires extensive manual analysis by domain experts. To avoid repetitive analysis, environmental impact factors (EIF) of common materials and products are published for use by LCA experts. However, finding appropriate EIFs for even a single product under study can require hundreds of hours of manual work, especially for complex products. We present Flamingo, an algorithm that leverages natural language machine learning (ML) models to automatically identify an appropriate EIF given a text description. A key challenge in automation is that EIF databases are incomplete. Flamingo uses industry sector classification as an intermediate layer to identify when there are no good matches in the database. On a dataset of 664 products, our method achieves an EIF matching precision of 75%.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123368245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beyond Digital Financial Services: Exploring Mobile Money Agents in Tanzania as General ICT Intermediaries 超越数字金融服务:探索坦桑尼亚移动货币代理作为一般ICT中介

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-09-06 DOI: 10.1145/3616386

Ananditha Raghunath, Innocent Ndubuisi-Obi Jr, Hosea Mpogole, Richard Anderson

{"title":"Beyond Digital Financial Services: Exploring Mobile Money Agents in Tanzania as General ICT Intermediaries","authors":"Ananditha Raghunath, Innocent Ndubuisi-Obi Jr, Hosea Mpogole, Richard Anderson","doi":"10.1145/3616386","DOIUrl":"https://doi.org/10.1145/3616386","url":null,"abstract":"Tanzanian mobile money and telecom agents (called wakala(s) in Swahili) have played a crucial role in expanding digital financial services (DFS) to rural areas. However, wakalas are losing their ability to financially sustain themselves providing intermediation services that their communities require. This work explores the potential for the wakala network to extend intermediation services to emerging ICTs beyond the scope of commercial DFS by uncovering the social and institutional factors that currently shape wakala practices. First, we investigate how two different models of intermediation from ICTD literature can inform broader strategies for intermediation through human infrastructures. We then complement this analysis with an on-the-ground quantitative survey and focus groups with community members and wakalas in Kagera, Tanzania. Our focus groups reveal that community members face challenges with new ICTs that require sustained intermediation and that wakalas encounter mounting financial instability and are thus receptive to intermediating for other ICTs. Finally, we present three factors that influence the broadening of the wakalas’ role of general ICT intermediaries: (1) aligning incentives and addressing the limits of pro bono actions, (2) providing appropriate training and a suitable support infrastructure, and (3) fostering trust-building and reciprocity.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124113309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantifying the Quality of Parent-Child Interaction Through Machine-Learning Based Audio and Video Analysis: Towards a Vision of AI-assisted Coaching Support for Social Workers 通过基于机器学习的音频和视频分析来量化亲子互动的质量:面向社会工作者的人工智能辅助辅导支持的愿景

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-09-01 DOI: 10.1145/3617693

Atefeh Jebeli, L. Chen, Katherine Guerrerio, Sophia Papparotto, L. Berlin, Brenda Jones Harden

{"title":"Quantifying the Quality of Parent-Child Interaction Through Machine-Learning Based Audio and Video Analysis: Towards a Vision of AI-assisted Coaching Support for Social Workers","authors":"Atefeh Jebeli, L. Chen, Katherine Guerrerio, Sophia Papparotto, L. Berlin, Brenda Jones Harden","doi":"10.1145/3617693","DOIUrl":"https://doi.org/10.1145/3617693","url":null,"abstract":"Attachment is the emotional bonding between a child and a caregiver. Whether or not there is a secure attachment in early childhood has a profound life-long impact on the child. In recent years, attachment-based interventions have been developed and implemented, especially with families from low socioeconomic backgrounds. One important aspect of the program is to assess the quality of parent-child interactions through audio/video recorded at home while parent-child dyads were engaged in semi-structured interaction tasks, such as ”three-bag-assessment.” The current practice relies on human coders to rate the videos, which is a time-consuming process. Using a dataset of 220 video recordings of parent-child dyads collected at home as part of an attachment-based intervention program, we prototype a machine learning approach based on human body keypoints extracted from the posture analysis tool OpenPose and voice activity features derived from audio recordings. The results show that there are potential values in using machine learning to improve the coding efficiency of parent-child interactions. When further developed and improved, this kind of model may contribute to a new vision of AI-assisted parenting coaching support to make evidence-based interventions accessible and affordable at a large scale to children and families.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122161519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A First Look into Software Security Practices in Bangladesh 孟加拉国软件安全实践初探

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-08-31 DOI: 10.1145/3616383

Ankit Shrestha, Tanusree Sharma, Pratyasha Saha, Syed Ishtiaque Ahmed, M. N. Al-Ameen

引用次数: 0

PollutionMapper: Identifying Global Air Pollution Sources 污染地图:识别全球空气污染源

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-08-29 DOI: 10.1145/3617129

Dhruv Agarwal, Srinivasan Iyengar, Pankaj Kumar

{"title":"PollutionMapper: Identifying Global Air Pollution Sources","authors":"Dhruv Agarwal, Srinivasan Iyengar, Pankaj Kumar","doi":"10.1145/3617129","DOIUrl":"https://doi.org/10.1145/3617129","url":null,"abstract":"Air pollution adversely impacts public health. The National Capital Region (Delhi-NCR) is among the most polluted urban areas in the world. One component of air pollution is PM2.5, which accounts for around 80% of deaths due to air pollution. Solutions for lowering PM2.5 levels in Delhi have been ineffective due to their unscientific design. In this paper, we build a mixed-methods model that captures the interplay of various factors—geographical, chemical, meteorological—that contribute to the concentration of PM2.5. Using domain knowledge and KDE sampling from NASA’s GEOS-CF dataset, we identify the major sources of each of the seven constituents of PM2.5. From the 68 sources thus selected, we run the NOAA’s HYSPLIT wind dispersion model to track the movement of released particles to the sink, i.e., Delhi. Using the concentration of pollutants at the sources and by tracking their movement, we can predict the PM2.5 levels at the sink and identify polluting sources. Our model performed significantly better than the baseline fixed-effects model and captured seasonal variations in all seven constituents of PM2.5. It also uncovered the impact of polluting sources hundreds of kilometers away on the air of Delhi. Policymakers can use such a model to design data-driven policy interventions.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122966387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of performance improvements and bias associated with the use of human mobility data in COVID-19 case prediction models 分析在COVID-19病例预测模型中使用人员流动性数据所带来的绩效改进和偏差

ACM Journal on Computing and Sustainable Societies Pub Date : 2023-08-26 DOI: 10.1145/3616380

S. Abrar, N. Awasthi, D. Smolyak, V. Frías-Martínez

{"title":"Analysis of performance improvements and bias associated with the use of human mobility data in COVID-19 case prediction models","authors":"S. Abrar, N. Awasthi, D. Smolyak, V. Frías-Martínez","doi":"10.1145/3616380","DOIUrl":"https://doi.org/10.1145/3616380","url":null,"abstract":"The COVID-19 pandemic has mainstreamed human mobility data into the public domain, with research focused on understanding the impact of mobility reduction policies as well as on regional COVID-19 case prediction models. Nevertheless, current research on COVID-19 case prediction tends to focus on performance improvements, masking relevant insights about when mobility data does not help, and more importantly, why, so that it can adequately inform local decision making. In this paper, we carry out a systematic analysis to reveal the conditions under which human mobility data provides (or not) an enhancement over individual regional COVID-19 case prediction models that do not use mobility as a source of information. Our analysis - focused on US county-based COVID-19 case prediction models - shows that (1) at most, 60% of counties improve their performance after adding mobility data; (2) that the performance improvements are modest, with median correlation improvements of approximately 0.13; (3) that improvements were lower for counties with higher Black, Hispanic, and other non-White populations as well as low-income and rural populations, pointing to potential bias in the mobility data negatively impacting predictive performance; and that (4) different mobility datasets, predictive models and training approaches bring about diverse performance improvements.","PeriodicalId":238057,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127232608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0