Socially responsible pay for priority traffic control system for e-commerce delivery vehicles
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Gavric, Slavica↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Earth Science Goes E-Commerce
Software packages commercially marketed by Agri ImaGIS allow customers to analyze farm fields. Agri ImaGIS provides satellite images of farmland and agricultural views to US clients. The company approached NASA-MSU TechLink for access to technology that would improve the company's capabilities to deliver satellite images over the Internet. TechLink found that software with the desired functions had already been developed through NASA's Remote Sensing Database Program. Agri ImaGIS formed a partnership with the University of Minnesota group that allows the company to further develop the software to meet its Internet commerce needs.
Source record↗
Giving E-Commerce a Boost
A former Ames employee, Monte Zweben, founded a new company, Blue Martini Software, that provides software to companies seeking to personalize their products to individual customers. This customer targeting approach is accomplished through the use of artificial intelligence concepts Zweben worked on while at Ames. The Ames AI research has found applications in clickstream mining and purchasing behavior data collection.
Source record↗
A consumer-centric approach to quantify efficiency of receiving goods purchased via online
Virtual participation in shopping activities has increased exponentially in the past four years compared to the last couple of decades. E-tailing or online shopping offers the convenience of goods reaching a consumer instead of a consumer traveling to a store, but it has downsides like geographical service variability and negative social externalities such as increased energy consumption and emissions. This study proposes a novel approach to quantify e-tailing efficiency from the consumers’ viewpoint. The methodology is innovative in its integration of accessibility theory with energy and cost impedance factors and consideration of delivering and picking up goods purchased via online. The methodology is implemented for the San Francisco Bay Area and is subject to scenarios that see enhancements to various facets of online shopping delivery. Results demonstrate that increasing the frequency of e-commerce deliveries helps improve e-tailing efficiency in rural locations, while improvements in energy and cost aspects of delivery modes are seen to improve e-tailing efficiencies in the central parts of the region. The approach proposed can provide valuable insights on where people have limited benefits from online shopping and how emerging delivery mechanisms can change the quality of the e-commerce experience within a city. This research offers a replicable framework for assessing e-commerce systems in diverse geographic contexts, contributing to the development of equitable and environmentally sustainable urban freight systems.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
BEAM CORE: A Flexible Ecosystem for Freight, Demographics, and Vehicle Analysis
The Behavior, Energy, Autonomy, and Mobility Comprehensive Regional Evaluator (BEAM CORE) is an open-source, modular ecosystem of highly refined, agent-based modeling tools developed by Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies. Organizations such as metropolitan planning organizations, agencies, and companies can use BEAM CORE to analyze freight movement and optimize logistics solutions, assess the impacts of emerging freight technologies or e-commerce trends, model dynamic population growth and evolution, and understand the drivers and impacts of electric vehicle adoption across households in a given region. Users can choose from a flexible suite of modeling modules according to their needs and priorities. The modules integrate with travel demand models to support enhanced analysis of diverse scenarios involving freight movement, vehicle technologies, and other key factors relevant to regional planning.
33 ADVANCED PROPULSION SYSTEMS↗
An open retail boundary dataset for South Korea using open data and computer vision technique
Although delineating retail boundaries is important to explore and comprehend the dynamics of the retail sector, it is hard to find studies specifically addressing it in the South Korean context. This study fills this gap by proposing new retail boundaries across South Korea. To achieve this goal, we employed a variety of retailers and building datasets and proposed a unique computer vision-based framework with a deep ensemble voting technique. As a result, we delineated 6,636 distinct retail boundaries that were validated against existing reference retail boundaries. These newly delineated retail boundaries provide valuable insights for researchers, governments, and other relevant stakeholders by enhancing their understanding of retail geography. This dataset can be used as a foundational resource for analyses on topics such as pandemic recovery, retail gentrification, and the resilience of retail spaces in response to e-commerce growth, ultimately contributing to more robust retail sector research in South Korea.
97 MATHEMATICS AND COMPUTING↗
FRISM (FReight Integrated Simulation Model) [SWR-24-40]
FRISM simulates day-to-day freight activities including end-consumer shopping, distribution channel, and carrier operation with e-commerce dynamics between passenger and freight travel. It outputs an assignment of different shipments to carriers and tour plans of the carriers' vehicles to transport shipments from their origins to their destinations.
Ugirumurera, Juliette↗
Exploring Class 8 Long-Haul Truck Electrification: Key Technology Evaluation and Potential Challenges
The phenomena of global warming and climate change are encouraging more and more countries, local communities, and companies to establish carbon neutrality targets, which has very significant implications for the US trucking industry. Truck electrification helps fleets to achieve zero tailpipe emissions and macro-scale decarbonization while allowing continued business growth in response to the rapid expansion of e-commerce and shipping related to increased globalization. Here, this paper presents an analysis of Class 8 long-haul truck electrification using a commercial vehicle electrification evaluation tool and Fleet DNA drive data. The study provides new insight into the impacts of streamlined chassis, battery energy density, and superfast charging on battery capacity needs as well as implications for payload, energy consumption, and greenhouse gas emissions for electric long-haul trucks. The study also identifies a pathway for achieving optimal long-haul truck electrification. The results show that no single technology can simultaneously achieve significant improvements in all these key areas and that a cost-effective approach requires a deliberate combination of all of these technologies. Moreover, the analysis highlights the strong evolution of vehicle and battery technologies and the excellent potential for long-haul truck electrification to achieve 100% year-round service coverage with continued technology advancement.
33 ADVANCED PROPULSION SYSTEMS↗
Developing Distributed Collaboration Systems at NASA: A Report from the Field
Web-based collaborative systems have assumed a pivotal role in the information systems development arena. While business to customers (B-to-C) and business to business (B-to-B) electronic commerce systems, search engines, and chat sites are the focus of attention, web-based systems span the gamut of information systems that were traditionally confined to internal organizational client server networks. For example, the Domino Application Server allows Lotus Notes (trademarked) uses to build collaborative intranet applications and mySAP.com (trademarked) enables web portals and e-commerce applications for SAP users. This paper presents the experiences in the development of one such system: Postdoc, a government off-the-shelf web-based collaborative environment. Issues related to the design of web-based collaborative information systems, including lessons learned from the development and deployment of the system as well as measured performance, are presented in this paper. Finally, the limitations of the implementation approach as well as future plans are presented as well.
Becerra-Fernandez, Irma↗
Next Space Race is in IT
The next Space Race will be in the economic applications from space and science technology. As NASA science and technology has global application; IT is global, economics is global; surely there are great untapped potentials in finding the IT links of commonality among these three. The Economics of IT will continue to depend upon solution providers creating new methods that capitalize on linking information and information centers with the applications community for business and economic functions.. New and innovative IT vendors whose increased efforts to apply evolving technologies and principles that power the e-business revolution are now seeing the business of government being transformed in a similar fashion. NASA will be a prime example of IT transformation. Potential benefits of e-government are identical to the benefits of e-commerce, which start from value derived from capabilities and assets. The capability and asset wealth of NASA technology and data mass scattered through hundreds of archives will one day provide incredible economic benefit across international and corporate boundaries. Yet the ability to economically benefit from bridging the gap between capability to billable service has yet to find it's first major market. Ultimately the role of government, science, and technology linking to the business world will find greater dependence from this increasingly common ground of IT solutions and technologies. Therefore the future role of the IT industry may be as much administrative as technical, ultimately of critical importance furthering the role of science into application.
Alger, George↗
A Survey of Complex Object Technologies for Digital Libraries
Many early web-based digital libraries (DLs) had implicit assumptions reflected in their architecture that the unit of focus in the DL (frequently "reports" or "e-prints") would only be manifested in a single, or at most a few, common file formats such as PDF or PostScript. DLs have now matured to the point where their contents are commonly no longer simple files. Complex objects in DLs have emerged from in response to various requirements, including: simple aggregation of formats and supporting files, bundling additional information to aid digital preservation, creating opaque digital objects for e-commerce applications, and the incorporation of dynamic services with the traditional data files. We examine a representative (but not necessarily exhaustive) number of current and recent historical web-based complex object technologies and projects that are applicable to DLs: Aurora, Buckets, ComMentor, Cryptolopes, Digibox, Document Management Alliance, FEDORA, Kahn-Wilensky Framework Digital Objects, Metadata Encoding & Transmission Standard, Multivalent Documents, Open eBooks, VERS Encapsulated Objects, and the Warwick Framework.
Nelson, Michael L.↗
Finding Diamonds in the Rough
HighTower Software, Inc. has developed a commercial software application originally designed at JPL that helps users identify deviations from norms out of massive quantities of data. The commercial product is known as CyberGrid and the same software is still supporting NASA's Voyager, Galileo and Cassini missions. CyberGrid generates 3-D graphs of data and has been used in AIDS research as well as e-commerce applications.
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The D3 Middleware Architecture
DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.
Walton, Joan↗
Discrete Lattice Material Vacuum Airship
Vacuum airships fueled by renewable energy would reduce reliance on fossil fuel-based modes of transport, lessen the need for limited and non-renewable lifting gases, and can be achieved using novel manufacturing techniques for ultra-light, discrete lattice material systems.The Discrete Lattice Material Vacuum Airships (DLMVA) system combines novel material science and manufacturing technologies for new modes of mass transportation, resulting in a disruptive approach to reduce national resource consumption and emissions. Through the use of high performance building block elements, modular, scalable and extensible aircraft can be rapidly assembled into positive net-buoyancy systems utilizing a vacuum instead of a lifting gas. By using architected lattice material principles, show that lattice materials can overcome stability limitations of previous vacuum balloon designs. Additionally, we show that lattice vacuum balloons are strength limited, rather than stability limited. As a result,airborne infrastructure can be developed to support the proliferation of modern systems such as e-commerce and distributed communications, while simultaneously reducing dependence on finite, non-renewable, emission-heavy resources.
Jenett, Benjamin E.↗
Item Retrieval as Utility Estimation
Retrieval systems have greatly improved over the last half century, estimating relevance to a latent user need in a wide variety of areas. One area that has not enjoyed such advancements is searching for items by attribute values, a common activity in e-commerce and science, particularly given numeric values. Existing item retrieval systems assume the user has a firm grasp of their own desires and can formulate a good Boolean or SQL-style query to retrieve items, as one would do with a database. A contrasting approach would be to estimate how well items match the user?s latent desires and return items ranked by this estimation. Towards this end, we present a retrieval model inspired by multi-criteria decision making theory, concentrating on numeric attributes. We evaluate our novel approach, the de-facto standard of Boolean retrieval, and several models proposed in the literature, in two user studies using Amazon Mechanical Turk. We use a competitive game to motivate test subjects and compare methods based on the results of the subjects? initial query and their success in the game. In our experiments, our new method signi cantly outperformed the others, whereas the Boolean approaches had the worst performance.
operations research↗
Classification of Notices to Airmen using Natural Language Processing
This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.
Aiden C. Szeto↗
Classification of Notices to Airmen using Natural Language Processing
This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.
Aiden Szeto↗
New Norms or Old Habits: Evaluating Interlinked Trajectories of Online Shopping and Work Commute Post-Pandemic
The COVID-19 pandemic has significantly shifted travel behaviors, with major changes observed in online shopping and travel to work. Despite considerable research into pandemic-induced changes in travel behavior, it remains uncertain whether these new patterns have persisted or reverted to pre-pandemic norms. This study addresses this uncertainty by evaluating whether shifts in online shopping and work travel during the pandemic have become permanently ingrained in individuals' daily routine. Leveraging data from the 2022 National Household Travel Survey, a bivariate ordered probit model is employed to analyze changes in online shopping and work travel - whether they have increased, decreased, or remained stable compared to pre-pandemic levels across different population segments. The analysis finds that the pandemic did not significantly alter online shopping for home delivery and travel to work for the majority of society. However, a substantial portion of respondents reported increased online shopping for home delivery and reduced travel to work compared to pre-pandemic levels, with online shopping trends appearing more permanent. Segment-wise analysis and model results indicate heterogeneity in behavioral shifts with females engaging more in online shopping, while zero-vehicle households are traveling less to work, compared to pre-pandemic levels. Additionally, increase in online shopping frequency is significantly and negatively correlated with decrease in traveling to work. These findings highlight the need for improved digital infrastructure, flexible work policies, and integrated transportation solutions tailored to evolving demographic and socioeconomic needs in the post-pandemic era. Additionally, the study calls for integrating passenger and freight movement in a single framework rather than treating them in silos.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗