Engineering Commons^™

Administrative Law In The Automated State, Cary Coglianese

All Faculty Scholarship

In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …

Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …

Big Data Investment And Knowledge Integration In Academic Libraries, Saher Manaseer, Afnan R. Alawneh, Dua Asoudi

Copyright, Fair Use, Scholarly Communication, etc.

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges.

One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage …

Transparency And Algorithmic Governance, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are improving and automating important functions in medicine, transportation, and business. Government officials have also started to take notice of the accuracy and speed that such algorithms provide, increasingly relying on them to aid with consequential public-sector functions, including tax administration, regulatory oversight, and benefits administration. Despite machine-learning algorithms’ superior predictive power over conventional analytic tools, algorithmic forecasts are difficult to understand and explain. Machine learning’s “black-box” nature has thus raised concern: Can algorithmic governance be squared with legal principles of governmental transparency? We analyze this question and conclude that machine-learning algorithms’ relative inscrutability does not pose a …

Defining A Smart Nation: The Case Of Singapore, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

Purpose - The purpose of this paper is to identify the key characteristics and propose a working definition of a smart nation.Design/methodology/approach - A case study of Singapore through an analysis of the key speeches made by senior Singapore leaders, publicly available government documents and news reports since the launch of the smart nation initiative in December 2014 was carried out.Findings - Just like smart cities, the idea of a smart nation is an evolving concept. However, there are some emerging characteristics that define a smart nation.Research limitations/implications - The paper provides an initial understanding of the key characteristics and …

Autonomous Indoor Localization For Fire Safety And Resource Location Via Field Mapping Techniques, Jaeyoung Kim, Kartik Ariyur, Yan Cui, Benjamin D. Branch, Joshua Ebung Umo

Libraries Faculty and Staff Presentations

An overall result of this collaboration between the Mechanical Engineering Dept. and the Purdue University Libraries (PUL) should result in building a big data framework that make have knowledge transfer for similar large scale geospatial data implementations. Such may promote best practices of data management where the library skill sets may aid faculty research and student learning. Here, the PUL is concerned with advancing the Mechanical Engineering‘s STEM pipeline capacity with this type of research, collaboration and data management engagement.

Autonomous Indoor Localization For Fire Safety And Resource Location Via Field Mapping Techniques (Android Version), Joshua Ebung Umo, Yan Cui, Kartik Ariyur, Benjamin D. Branch, Jaeyoung Kim

Libraries Faculty and Staff Presentations

An overall result of this collaboration between the Mechanical Engineering Dept. and the Purdue University Libraries (PUL) should result in building a big data framework that make have knowledge transfer for similar large scale geospatial data implementations. Such may promote best practices of data management where the library skill sets may aid faculty research and student learning. Here, the PUL is concerned with advancing the Mechanical Engineering‘s STEM pipeline capacity with this type of research, collaboration and data management engagement.

Autonomous Indoor Localization Via Field Mapping Techniques, With Agricultural Big Data Application, Yan Cui, Kartik Ariyur, Benjamin D. Branch

Libraries Faculty and Staff Presentations

This joint collaboration between the library, the Mechanical Engineering department shows the current research of localizing an Android smartphone using big data collection and sensor fusion techniques. The original work is Autonomous Indoor Localization via Field Mapping Techniques which primarily designed as indoor fire and safety aid.

For Agricultural Big Data Use, the Android smartphone is being applied to in indoor greenhouse fire, safety and data knowledge design. Such may aid big data tool value to greenhouse fire and safety design and any data that may be important fieldwork considerations.

The indoor agricultural mapping application may be application to greenhouses …

A Cris Data Science Investigation Of Scientific Workflows Of Agriculture Big Data And Its Data Curation Elements, Benjamin D. Branch, Peter N. Baker, Jai Xu, Elisa Bertino

Libraries Faculty and Staff Presentations

This joint collaboration between the Purdue Libraries and Cyber Center demonstrates the next generation of computational platforms supporting interdisciplinary collaborative research. Such platforms are necessary for rapid advancements of technology, industry demand and scholarly congruence towards open data, open access, big data and cyber-infrastructure data science training. Our approach will utilize a Discovery Undergraduate Research Investigation effort as a preliminary research means to further joint library and computer science data curation research, tool development and refinement.