Development Engineering最新文献

{"title":"Data Classification for Secure Mobile Health Data Collection Systems","authors":"Marriette Katarahweire ,&nbsp;Engineer Bainomugisha ,&nbsp;Khalid A. Mughal","doi":"10.1016/j.deveng.2020.100054","DOIUrl":"10.1016/j.deveng.2020.100054","url":null,"abstract":"<div><p>Data collected in Mobile Health Data Collections Systems (MHDCS) are diverse, both in terms of type and value. This calls for different data protection measures to meet security goals of confidentiality, integrity, and availability. The majority of commonly used open-source MHDCS track and monitor individuals over a while. It is therefore important to have sensitive data defined and proper security measures identified. We propose a data classification model as a basis for secure design and implementation. Our method combines interviews with case studies. The case studies focused on three of the widely used MHDCS platforms in low-resource settings; that is Muzima, Open Data Kit (ODK), and District Health Information Software (DHIS) 2 Tracker Capture. Interviews with domain experts helped define the sensitivity of data in MHDCS. The proposed data classification model provides for three sensitivity levels: public, confidential, and critical. The model uses context information and multiple parameters as inputs to a classification scheme that maps data to sensitivity levels. The generated data classifications are intended to guide developers and users to build security into MHDCS starting from the early stages of the software development life cycle.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"5 ","pages":"Article 100054"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2020.100054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54239038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enabling models of Internet eXchange Points for developing contexts","authors":"Diarmuid Ó Briain ,&nbsp;David Denieffe ,&nbsp;Dorothy Okello ,&nbsp;Yvonne Kavanagh","doi":"10.1016/j.deveng.2020.100057","DOIUrl":"10.1016/j.deveng.2020.100057","url":null,"abstract":"<div><p>In 2009, fibre-optic cables landed on the East coast of Africa, the last major area of the world to be connected to the Internet triggering a decade of Internet development (Graham et al., 2015). During the same period, there has been a general transformation of the Internet from static content to video streaming. Technologies such as Software Defined Networking (SDN) and Network Functions Virtualisation (NFV) are about to reshape the Internet once again. Globally Internet eXchange Points (IXP) have been a key node on the Internet and a central location for Content Delivery Networks (CDN), though in East Africa they have generally been confined to large cities. There is an understanding that if technology hubs are to develop in other cities, the Internet ecosystem, including IXPs, must extend outwards.</p><p>This research uses a Proof of Concept (PoC) system design methodology to investigate solutions that containerise IXP functions and develops affordable models for IXPs of various sizes and configurations based on both traditional and software-defined switching paradigms as well as automate the IXP build function. The research argues that it is necessary to develop a national IXP ecosystem by supplementing the national IXP with local IXPs to support economic development outside of the major economic cities of the region. The technology solutions must be used in conjunction with research on the political economy landscape plus optimum deployment to ensure success. This research demonstrates that systems can be designed which are achievable and affordable by exploiting the most suitable model and switching technology for each site. It also determines that software-defined models offer the potential for application development across the IXP.</p><p>This research concludes that with a combination of function containerisation and astute model selection it is possible to build an affordable set of IXPs to support multiple technology hubs across a national Internet ecosystem. Proposed systems are discussed in the context of East Africa and testbed results discussed in relation to the optimum system design which can be deployed in any IXP setting.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"5 ","pages":"Article 100057"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2020.100057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43523619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toilet alarms: A novel application of latrine sensors and machine learning for optimizing sanitation services in informal settlements","authors":"Nick Turman-Bryant ,&nbsp;Taylor Sharpe ,&nbsp;Corey Nagel ,&nbsp;Lauren Stover ,&nbsp;Evan A. Thomas","doi":"10.1016/j.deveng.2020.100052","DOIUrl":"10.1016/j.deveng.2020.100052","url":null,"abstract":"<div><p>The cost-effectiveness and reliability of waste collection services in informal settlements can be difficult to optimize given the geospatial and temporal variability of latrine use. Daily servicing to avoid overflow events is inefficient, but dynamic scheduling of latrine servicing could reduce costs by providing just-in-time servicing for latrines. This study used cellular-connected motion sensors and machine learning to dynamically predict when daily latrine servicing could be skipped with a low risk of overflow. Sensors monitored daily latrine activity, and enumerators collected solid and liquid waste weight data. Given the complex relationship between latrine use and the need for servicing, an ensemble machine learning algorithm (Super Learner) was used to estimate waste weights and predict overflow events to facilitate dynamic scheduling. Accuracy of waste weight predictions based on sensor and historical weight data was adequate for estimating latrine fill levels (mean error of 20% and 22% for solid and liquid wastes), but there was greater accuracy in predicting overflow events (area under the receiver operating characteristic curve of 0.90). Although our simulations indicate that dynamic scheduling could substantially reduce costs for lower use latrines, we found that cost reduction was more modest for higher use latrines and that there was a significant gap between the simulated and implemented results.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"5 ","pages":"Article 100052"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2020.100052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54239015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using sensors to measure technology adoption in the social sciences","authors":"Adina Rom ,&nbsp;Isabel Günther ,&nbsp;Yael Borofsky","doi":"10.1016/j.deveng.2020.100056","DOIUrl":"10.1016/j.deveng.2020.100056","url":null,"abstract":"<div><p>Empirical social sciences rely heavily on surveys to measure human behavior. Previous studies show that such data are prone to random errors and systematic biases caused by social desirability, recall challenges, and the Hawthorne effect. Moreover, collecting high frequency survey data is often impossible, which is important for outcomes that fluctuate. Innovation in sensor technology might address these challenges. In this study, we use sensors to describe solar light adoption in Kenya and analyze the extent to which survey data are limited by systematic and random error. Sensor data reveal that households used lights for about 4 h per day. Frequent surveyor visits for a random sub-sample increased light use in the short term, but had no long-term effects. Despite large measurement errors in survey data, self-reported use does not differ from sensor measurements on average and differences are not correlated with household characteristics. However, mean-reverting measurement error stands out: households that used the light a lot tend to underreport, while households that used it little tend to overreport use. Last, general usage questions provide more accurate information than asking about each hour of the day. Sensor data can serve as a benchmark to test survey questions and seem especially useful for small-sample analyses.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"5 ","pages":"Article 100056"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2020.100056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54239050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-economic comparison of the FUEL sensor and Kitchen Performance Test to quantify household fuel consumption with multiple cookstoves and fuels","authors":"Jennifer Ventrella ,&nbsp;Olivier Lefebvre ,&nbsp;Nordica MacCarty","doi":"10.1016/j.deveng.2020.100047","DOIUrl":"10.1016/j.deveng.2020.100047","url":null,"abstract":"<div><p>Quantifying the impact of improved stoves and fuels designed to combat the health and environmental burdens of traditional cooking is necessary to ensure sustainable outcomes but remains challenging for practitioners. The current standard method to determine household fuel consumption, the Kitchen Performance Test, is costly, time intensive, and subject to error. To address these challenges, the Fuel Use Electronic Logger (FUEL), a sensor-based system that monitors fuel consumption in households was developed. In this study, the accuracy, granularity, and cost of FUEL were compared to that of the standard Kitchen Performance Test through simultaneous testing. Monitoring was conducted over four and five consecutive days in 10 households in Burkina Faso that were each stacking LPG, charcoal, and wood stoves; and in 20 households in Uganda stacking multiple wood stoves, respectively. Results show good agreement between the two methods on an aggregate level, with an overall R² value of 0.81, and more varied agreement when comparing fuel consumption on a day-to-day basis. The sample variation was found to generally decrease with increasing monitoring length, pointing to value in monitoring over longer durations afforded by the FUEL. There was no systematic over- or under-prediction of fuel consumption between FUEL and the KPT, suggesting that the FUEL method does not have significant bias relative to the KPT, but the accuracy of the methods relative to the true, “ground truth” household fuel consumption value was not known. There was no agreement between either method with self-reported survey data, further illustrating the unreliability of quantitative survey data. Moisture content and Standard Adult Equivalence measurements were found to be similar whether measurements were taken only on the first and last days of the study period as compared to each day, although this should be evaluated over a longer time period for future studies. Potential errors in each method are discussed and resulting suggestions for developing an effective study with the FUEL system are presented. An economic analysis shows that the FUEL system becomes increasingly economical as monitoring duration increases or new studies are conducted, with a breakeven point at 40 days in this case. Overall, these results point to the viability of the FUEL system to quantify long-term, in-situ fuel consumption with similar accuracy to current methods and the capability for more granular data over longer time periods with less intrusion into households.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"5 ","pages":"Article 100047"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2020.100047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54238971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and participatory design of scale-appropriate agricultural machinery workshops in developing countries: A case study in Bangladesh","authors":"Ellerbe Somers Gregg ,&nbsp;Jonathan Colton ,&nbsp;Md Abdul Matin ,&nbsp;Timothy J. Krupnik","doi":"10.1016/j.deveng.2019.100046","DOIUrl":"10.1016/j.deveng.2019.100046","url":null,"abstract":"<div><p>Smallholder farmers provide the foundation for food security in South Asia. However, increasing seasonal labor scarcity caused by rural out-migration has resulted in growing agricultural labor costs, presenting challenges to cash-constrained smallholder farmers that hire manual labor for land preparation, sowing, harvest and post-harvest operations. Technological innovations in small-scale agricultural machinery appropriate for the small field sizes and limited resource endowments of South Asia's farmers have been proposed as a potential solution to this problem. An increasing number of development initiatives also promote rural entrepreneurial approaches to mechanization, whereby smallholder farmers can access and use machinery in their own fields on an affordable fee-for-service basis offered by machinery owners. This approach reduces capital constraints for smallholder farmers while enabling entrepreneurs who can afford equipment to enter into business serving stallholder farmers as clients. This approach is now widely practiced in Bangladesh, where machinery entrepreneurs play a crucial role in providing access to productive technologies for smallholder farmers who could not otherwise afford direct purchase of labor- and cost-saving machinery. In order to maintain low machinery purchase costs for emerging yet capital constrained rural entrepreneurs, while also assuring high quality standards, cost-effective domestic production of agricultural machinery is increasingly championed as an important long-term national development objective. With no safety standards or guidelines for best production practices, the few manufacturing workshops that exist within Bangladesh operate inefficiently and without clear rationalization of manufacturing processes. Haphazard copying of prototypes or imported available machinery is common. This leads to inefficient production and poor product quality in an emerging but potentially highly beneficial industry. This paper addresses these problems and presents a case study to increase machinery manufacturers' capacity while improving manufacturing operations and workplace safety through equipment selection, workshop layout, and usability.</p><p>Janata Engineering (JE) is a small-scale machinery manufacturing enterprise in Bangladesh, specializing in two-wheel tractor attachments such as bed planters, local derivations of power-tiller operated seeders, and other equipment for planting, irrigating, and processing crops. JE was expanding and setting up a second factory for which the authors provided assistance on its design. Our research question was whether participatory action research (PAR) supported by empirical data could provide improved factory design in terms of functionality, safety and human interactions, when compared with conventional approaches driven by technical efficiency concerns alone. Using PAR, we developed a number of alternative process and layout recommendations for JE to increase the eff","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"5 ","pages":"Article 100046"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2019.100046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39152474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors leading to sustainable social impact on the affected communities of engineering service learning projects","authors":"Andrew Armstrong, C. Mattson, Randy S. Lewis","doi":"10.1115/detc2019-98407","DOIUrl":"https://doi.org/10.1115/detc2019-98407","url":null,"abstract":"\u0000 University engineering programs across the USA engage in service learning projects. These projects involve student teams designing and implementing products or solutions for communities in need, often in developing nations. There has been much research done relating to pedagogy and the impact of these programs on student learning. However, less research has been done on measuring the impact of these programs on the affected communities. This paper examines factors that practitioners believe are related to successfully delivering a desirable and transferable solution to affected communities. The authors identified 46 distinct factors from the literature that implicitly or explicitly are suggested to contribute to successful project outcomes. Formed as postulates in this paper, these 46 factors have been separated into 5 categories to assist understanding and implementing these factors into service learning programs. Lastly, different methods of analyzing and measuring project success and impact are discussed. Future methods for proving the viability of the 46 postulates are discussed as well.","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42268702","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}

{"title":"Geospatial data for research on economic development","authors":"Ran Goldblatt,&nbsp;Madeline Jones,&nbsp;Brad Bottoms","doi":"10.1016/j.deveng.2019.100041","DOIUrl":"10.1016/j.deveng.2019.100041","url":null,"abstract":"","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"4 ","pages":"Article 100041"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2019.100041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54238920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategies for successful field deployment in a resource-poor region: Arsenic remediation technology for drinking water","authors":"Dana Hernandez ,&nbsp;Kathryn Boden ,&nbsp;Prasenjit Paul ,&nbsp;Siva Bandaru ,&nbsp;Sreemannarayana Mypati ,&nbsp;Abhisek Roy ,&nbsp;Susan Amrose ,&nbsp;Joyashree Roy ,&nbsp;Ashok Gadgil","doi":"10.1016/j.deveng.2019.100045","DOIUrl":"10.1016/j.deveng.2019.100045","url":null,"abstract":"<div><p>Strong long-term international partnership in science, technology, finance and policy is critical for sustainable field experiments leading to successful commercial deployment of novel technology at community-scale. Although technologies already exist that can remediate arsenic in groundwater, most are too expensive or too complicated to operate on a sustained basis in resource-poor communities with the low technical skill common in rural South Asia. To address this specific problem, researchers at University of California-Berkeley (UCB) and Lawrence Berkeley National Laboratory (LBNL) invented a technology in 2006 called electrochemical arsenic remediation (ECAR). Since 2010, researchers at UCB and LBNL have collaborated with Global Change Program of Jadavpur University (GCP-JU) in West Bengal, India for its social embedding alongside a local private industry group, and with financial support from the Indo-US Technology Forum (IUSSTF) over 2012–2017. During the first 10 months of pilot plant operation (April 2016 to January 2017) a total of 540 m³ (540,000 L) of arsenic-safe water was produced, consistently and reliably reducing arsenic concentrations from initial 252 ± 29 to final 2.9 <span><math><mrow><mo>±</mo></mrow></math></span> 1 parts per billion (ppb). This paper presents the critical strategies in taking a technology from a lab in the USA to the field in India for commercialization to address the technical, socio-economic, and political aspects of the arsenic public health crisis while targeting several sustainable development goals (SDGs). The lessons learned highlight the significance of designing a technology contextually, bridging the knowledge divide, supporting local livelihoods, and complying with local regulations within a defined Critical Effort Zone period with financial support from an insightful funding source focused on maturing inventions and turning them into novel technologies for commercial scale-up. Along the way, building trust with the community through repetitive direct interactions, and communication by the scientists, proved vital for bridging the technology-society gap at a critical stage of technology deployment. The information presented here fills a knowledge gap regarding successful case studies in which the arsenic remediation technology obtains social acceptance and sustains technical performance over time, while operating with financial viability.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"4 ","pages":"Article 100045"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2019.100045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54238962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the causal impact of Chinese aid on vegetative land cover in Burundi and Rwanda under conditions of spatial imprecision","authors":"Robert Marty ,&nbsp;Seth Goodman ,&nbsp;Michael LeFew ,&nbsp;Carrie Dolan ,&nbsp;Ariel BenYishay ,&nbsp;Daniel Runfola","doi":"10.1016/j.deveng.2018.11.001","DOIUrl":"10.1016/j.deveng.2018.11.001","url":null,"abstract":"<div><p>There has been considerable debate regarding the efficacy of international aid in meeting the dual goals of human development and environmental sustainability. Many donors have sought to engage with this challenge by introducing environmental safeguard and monitoring initiatives; however, evidence on the success of these interventions is limited. Evaluating aid is a particular challenge in the case of donors that do not disclose information on the nature, geographic location, or extents of their interventions. In such cases, new methods that extract and geoparse data on the activities of opaque donors through the manual interpretation of thousands of news and other articles allow us to investigate the impacts of these activities. However, residual spatial uncertainty in these data remains a potential source of bias. In this article, we apply and discuss a Geographic Simulation and Extrapolation (GeoSIMEX) approach to mitigate the spatial imprecision inherent in geoparsed data. In conjunction with GeoSIMEX, we test and contrast multiple approaches to reducing the imprecision of aid, including high-assumption cases in which other covariates (i.e., nighttime lights) are leveraged to allocate aid. In our application, we find that methods which do not account for spatial imprecision find statistically significant relationships between Chinese aid and vegetation change; after accounting for spatial uncertainty, findings are similar for Rwanda and inconclusive for Burundi.</p></div>","PeriodicalId":37901,"journal":{"name":"Development Engineering","volume":"4 ","pages":"Article 100038"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.deveng.2018.11.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54238907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}