2022 IEEE Global Humanitarian Technology Conference (GHTC)最新文献

Accelerating Mini-grid Feasibility Assessments with Rapid Engineering and Business Model Evaluation 用快速工程和商业模式评估加速微电网可行性评估

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9910609

Tam Kemabonta, E. V. Hove, N. Johnson, Abdulrahman Alsanad

引用次数: 0

Empowering Middle-Aged Women to Bolster Food Security in their Communities 赋予中年妇女权力，加强社区粮食安全

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9911023

Maya Neumann, Ella Varano, S. Chawla, Naakesh Gomanie, Khanjan Mehta

{"title":"Empowering Middle-Aged Women to Bolster Food Security in their Communities","authors":"Maya Neumann, Ella Varano, S. Chawla, Naakesh Gomanie, Khanjan Mehta","doi":"10.1109/GHTC55712.2022.9911023","DOIUrl":"https://doi.org/10.1109/GHTC55712.2022.9911023","url":null,"abstract":"Much of the world exists in a state of hunger crisis. There is an absence of public infrastructure, economic resources, and opportunities for communities struggling against poverty to find assistance. In the Philippines, there is a considerable divide between urban resources and those of their rural counterparts. Gender-based discrimination leads to a shortage of aid in the agricultural and business sectors Organizations are working towards effectively identifying women without economic power and engaging them in careers that simultaneously grow natural resources for health and economic stability. However, many localities are still trapped in poverty despite the existing ecosystem of aid. A team of researchers at Lehigh University has created the Zero Hunger College, based in the Philippines, to address the challenges of malnutrition and lack of community outreach. It is a residential school that aims to address malnutrition and community economic growth from the ground up. This initiative allows middle-aged women to travel to metropolitan Manila and work alongside fellow students and knowledgeable professionals to combine Indigenous knowledge in agriculture and modern agri-technology. Upon attending this four-month program, these women can return to their communities with the ability to lead their community members out of poverty and into lives of greater food security with fewer problems caused by malnutrition.","PeriodicalId":370986,"journal":{"name":"2022 IEEE Global Humanitarian Technology Conference (GHTC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129285042","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: 1

Humanitarian Technology Due Diligence, Part II, United Nations SDGs 5 (gender equity) and 8 and 10 (economic equality) 人道主义技术尽职调查，第二部分，联合国可持续发展目标5(性别平等)、8和10(经济平等)

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/ghtc55712.2022.9911029

引用次数: 0

Blockchain-based Data Access Environment for Disaster Risk Reduction1 基于区块链的减少灾害风险的数据访问环境

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9910985

N. H. Wasserman

引用次数: 0

Design, Fabrication, and Aerodynamic Testing of a Vertical Axis Wind Turbine (VAWT) for Berekuso, Ghana 加纳Berekuso垂直轴风力涡轮机(VAWT)的设计、制造和气动测试

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9911030

Trish A. Maduche, H. Beem

引用次数: 1

Detection and Low-Latency Notification of Improper Backpack Posture using Deep Learning 使用深度学习的不正确背包姿势的检测和低延迟通知

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9910981

Hsin-Ya Hung, Garrett Millaway, Saif Mustafa, Haonan Peng, Avi Geiger, J. Raiti

引用次数: 0

A sociotechnical analysis of interventions to promote safer working conditions in informal e-waste recycling settings 促进非正式电子废物回收环境中更安全工作条件的干预措施的社会技术分析

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9910976

Sofia L. Schlezak, Juan Lucena, Alina Handorean, Luciana Antolini, R. Neitzel, Ó. R. Baena

{"title":"A sociotechnical analysis of interventions to promote safer working conditions in informal e-waste recycling settings","authors":"Sofia L. Schlezak, Juan Lucena, Alina Handorean, Luciana Antolini, R. Neitzel, Ó. R. Baena","doi":"10.1109/GHTC55712.2022.9910976","DOIUrl":"https://doi.org/10.1109/GHTC55712.2022.9910976","url":null,"abstract":"Informal recycling of electrical and electronic waste is a significant source of income for some families in the Global South. When workers implement unsafe practices, they are potentially exposed to hazardous chemicals that can negatively impact the environment and their health. Although this is a problem that has been studied for years, technological interventions that aim to reduce risks in informal contexts are rarely analyzed in light of social criteria. In this paper we evaluate intervention strategies through a model built on the Engineering and Sustainable Community Development (ESCD) criteria. We find that, in general the interventions lack a thorough process of workers’ participation since the early stages of design, which could inform projects, minimize harm within the communities, and promote long-term sustainability of interventions. In light of these findings, we recommend that future technological interventions implemented in informal e-waste recycling settings be designed based on the model presented.","PeriodicalId":370986,"journal":{"name":"2022 IEEE Global Humanitarian Technology Conference (GHTC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133435142","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: 1

A Comparative Analysis of Regression Algorithms with Genetic Algorithm In The Prediction of Breast Cancer Tumors 回归算法与遗传算法在乳腺癌肿瘤预测中的比较分析

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9911033

Joyce A. Ayoola, T. Ogunfunmi

{"title":"A Comparative Analysis of Regression Algorithms with Genetic Algorithm In The Prediction of Breast Cancer Tumors","authors":"Joyce A. Ayoola, T. Ogunfunmi","doi":"10.1109/GHTC55712.2022.9911033","DOIUrl":"https://doi.org/10.1109/GHTC55712.2022.9911033","url":null,"abstract":"Over the last few decades, breast cancer has become a major health concern worldwide, particularly in the women community, as its root cause is not always known and most times it is diagnosed in advanced stages which leads to high death rate. In more recent times, machine learning techniques have been employed as computer-aided diagnosis tools for breast cancer prediction These machine learning techniques have the capacity to classify and predict this cancer into benign or malignant. The main contribution of this study is to find a model which is most suitable for predicting this kind of tumor cell. Genetic Algorithm is applied as Feature Selection method to the Wisconsin Breast Cancer dataset to select the subsets of input features that are most relevant to the target variable. We compared five machine learning regression classifiers were considered, Linear regression, Logistic regression, Random Forest, Decision Tree and Support Vector Regression. The Random Forest classifier obtained the best precision and performance accuracy. This study contributes towards the enhancement of medical technology for prediction of breast cancer, which will not only improve the well-being and health of the female community but also reduce mortality rate related to breast cancer.","PeriodicalId":370986,"journal":{"name":"2022 IEEE Global Humanitarian Technology Conference (GHTC)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131303239","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: 1

A Smart Prevention Management in Gestational Diabetes Mellitus 妊娠期糖尿病的智能预防管理

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9911041

Nattacha Palawat, S. Kiattisin, T. Mayakul

引用次数: 0

Smallholder farmer-centric integration of IoT and Chatbot for early Maize diseases detection and management in pre-visual symptoms phase 以小农为中心的物联网和聊天机器人的集成，用于玉米疾病早期检测和视觉症状前阶段的管理

2022 IEEE Global Humanitarian Technology Conference (GHTC) Pub Date : 2022-09-08 DOI: 10.1109/GHTC55712.2022.9911047

T. Maginga, Jimmy Nsenga, Pierre Bakunzibake, Emmanuel Masabo

{"title":"Smallholder farmer-centric integration of IoT and Chatbot for early Maize diseases detection and management in pre-visual symptoms phase","authors":"T. Maginga, Jimmy Nsenga, Pierre Bakunzibake, Emmanuel Masabo","doi":"10.1109/GHTC55712.2022.9911047","DOIUrl":"https://doi.org/10.1109/GHTC55712.2022.9911047","url":null,"abstract":"Crop diseases are responsible for more than 50% of worldwide yield loss. Therefore, detecting crop diseases as soon as possible is important to limit both yield loss and costs involved in interrupting the disease cycles. Traditional disease detection sensors such as farmer eyes or crop imaging devices backed by Deep Neural Networks (DNN) models rely on visual symptoms which appear after the disease cycle has already undergone several asymptomatic phasing events such as inoculation, penetration, and so on. Recently, Internet of Things (IoT) sensors have been used to monitor other pre-visual abdominal signs generated by infected plants, like for instance emission of Volatile Organic Compound (VOC) or changes in soil nutrition consumption patterns. Considering the limited availability of extension officers to timely support farmers in early disease management, in this paper we propose an integrated framework that converges IoT sensing asymptomatic signs with natural language processing (NLP) chatbots to enable low literacy smallholder farmers of Maize crops in East-Africa to be completely autonomous in identifying and understanding their potential crop diseases prior to the apparition of visual symptoms.","PeriodicalId":370986,"journal":{"name":"2022 IEEE Global Humanitarian Technology Conference (GHTC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129993444","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: 1