scholarly journals Designing Zoning Systems for Freight Transportation Planning: A GIS-based approach for Automated Zone Design using Public Data Sources

2020 ◽  
Vol 48 ◽  
pp. 605-619
Author(s):  
Aithichya Chandra ◽  
Agnivesh Pani ◽  
Prasanta K Sahu
Keyword(s):  
Transportation Planning ◽  
Freight Transportation ◽  
Data Sources ◽  
Public Data ◽  
Zoning Systems

The Changing Landscape of Asian Entrepreneurship, Minority Banks, and Community Development

2011 ◽  
Vol 9 (1-2) ◽  
pp. 78-90
Author(s):  
Tarry Hum
Keyword(s):  
New York ◽  
New York City ◽  
Data Collection ◽  
Community Development ◽  
Real Estate ◽  
York City ◽  
Commercial Real Estate ◽  
Data Sources ◽  
Real Estate Development ◽  
Public Data

This policy brief examines minority banks and their lending practices in New York City. By synthesizing various public data sources, this policy brief finds that Asian banks now make up a majority of minority banks, and their loans are concentrated in commercial real estate development. This brief underscores the need for improved data collection and access to research minority banks and the need to improve their contributions to equitable community development and sustainability.

Freight Travel Demand Modeling: Synthesis of Approaches and Development of a Framework

2000 ◽  
Vol 1725 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Ram M. Pendyala ◽  
Venky N. Shankar ◽  
Robert G. McCullough
Keyword(s):  
Decision Making ◽  
Transportation Planning ◽  
Travel Demand ◽  
Freight Transportation ◽  
The Body ◽  
Travel Demand Modeling ◽  
Demand Modeling ◽  
Transportation Sector ◽  
Planning Framework ◽  
Freight Data Needs

It is increasingly being recognized at all levels of decision making that freight transportation and economic development are inextricably linked. As a result, many urban entities and states are embarking upon comprehensive freight transportation planning efforts aimed at ensuring safe, efficient, and smooth movement of freight along multimodal and intermodal networks. Over the past few decades there has been considerable published research on (1) freight transportation factors, (2) freight travel demand modeling methods, (3) freight transportation planning issues, and (4) freight data needs, deficiencies, and collection methods. A synthesis of the body of knowledge in these four areas is provided with a view to developing a comprehensive statewide freight transportation planning framework. The proposed framework consists of two interrelated components that facilitate demand estimation and decision making in the freight transportation sector.

scholarly journals Review: Application and Prospective Discussion of Machine Learning for the Management of Dairy Farms

Animals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1690 ◽  
Author(s):  
Marianne Cockburn
Keyword(s):  
Machine Learning ◽  
Dairy Farm ◽  
Poor Performance ◽  
Dairy Farming ◽  
Training Data ◽  
Data Sources ◽  
Full Potential ◽  
Promising Tool ◽  
Public Data ◽  
Dairy Research

Dairy farmers use herd management systems, behavioral sensors, feeding lists, breeding schedules, and health records to document herd characteristics. Consequently, large amounts of dairy data are becoming available. However, a lack of data integration makes it difficult for farmers to analyze the data on their dairy farm, which indicates that these data are currently not being used to their full potential. Hence, multiple issues in dairy farming such as low longevity, poor performance, and health issues remain. We aimed to evaluate whether machine learning (ML) methods can solve some of these existing issues in dairy farming. This review summarizes peer-reviewed ML papers published in the dairy sector between 2015 and 2020. Ultimately, 97 papers from the subdomains of management, physiology, reproduction, behavior analysis, and feeding were considered in this review. The results confirm that ML algorithms have become common tools in most areas of dairy research, particularly to predict data. Despite the quantity of research available, most tested algorithms have not performed sufficiently for a reliable implementation in practice. This may be due to poor training data. The availability of data resources from multiple farms covering longer periods would be useful to improve prediction accuracies. In conclusion, ML is a promising tool in dairy research, which could be used to develop and improve decision support for farmers. As the cow is a multifactorial system, ML algorithms could analyze integrated data sources that describe and ultimately allow managing cows according to all relevant influencing factors. However, both the integration of multiple data sources and the obtainability of public data currently remain challenging.

scholarly journals PAGER-CoV: a comprehensive collection of pathways, annotated gene-lists and gene signatures for coronavirus disease studies

2020 ◽  
Vol 49 (D1) ◽  
pp. D589-D599
Author(s):  
Zongliang Yue ◽  
Eric Zhang ◽  
Clark Xu ◽  
Sunny Khurana ◽  
Nishant Batra ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Organ Damage ◽  
Gene Set Enrichment Analysis ◽  
Data Sources ◽  
Functional Study ◽  
Data Set ◽  
Gene Signatures ◽  
Genomic Study ◽  
Study Results ◽  
Public Data

Abstract PAGER-CoV (http://discovery.informatics.uab.edu/PAGER-CoV/) is a new web-based database that can help biomedical researchers interpret coronavirus-related functional genomic study results in the context of curated knowledge of host viral infection, inflammatory response, organ damage, and tissue repair. The new database consists of 11 835 PAGs (Pathways, Annotated gene-lists, or Gene signatures) from 33 public data sources. Through the web user interface, users can search by a query gene or a query term and retrieve significantly matched PAGs with all the curated information. Users can navigate from a PAG of interest to other related PAGs through either shared PAG-to-PAG co-membership relationships or PAG-to-PAG regulatory relationships, totaling 19 996 993. Users can also retrieve enriched PAGs from an input list of COVID-19 functional study result genes, customize the search data sources, and export all results for subsequent offline data analysis. In a case study, we performed a gene set enrichment analysis (GSEA) of a COVID-19 RNA-seq data set from the Gene Expression Omnibus database. Compared with the results using the standard PAGER database, PAGER-CoV allows for more sensitive matching of known immune-related gene signatures. We expect PAGER-CoV to be invaluable for biomedical researchers to find molecular biology mechanisms and tailored therapeutics to treat COVID-19 patients.

scholarly journals Share repurchases in the South African mining sector

2014 ◽  
Vol 45 (2) ◽  
pp. 1-14
Author(s):  
V. Vermeulen
Keyword(s):  
South African ◽  
Data Sources ◽  
Annual Reports ◽  
Share Repurchases ◽  
Share Repurchase ◽  
Mining Sector ◽  
Holding Company ◽  
Monetary Value ◽  
News Service ◽  
Public Data

The purpose of this study was to obtain an overview of the share repurchase activities of companies listed in the mining sector of the JSE, and to determine the extent to which detail information of these share repurchases are available on public data sources such as SENS (Securities Exchange News Service - the office of the JSE that distributes all relevant company information electronically). The study focused on a period of 11 years, from July 1999 until the 2010 financial year-end. The annual reports of a sample of companies were analysed to determine the number of shares, as well as the monetary value of the shares that were repurchased. The SENS announcements were then scrutinised to determine the number of share repurchases recorded in the annual reports that were announced to shareholders. From a total of 55 share repurchase transactions, only 23 transactions were announced on SENS. The repurchase transactions were then further analysed in terms of the method used (general or specific repurchase), the repurchasing entity (company, subsidiary or share trust) and the subsequent sale of treasury shares from the subsidiary to the holding company. It was concluded that the majority of share repurchases are announced. However, if only companies with primary listings on the JSE areconsidered, 60% of share repurchases are not announced. The use of the general and specific methods are more or less equal for companies with primary listings on the JSE, but for companies with secondary listings on the JSE, 98% ofrepurchases are general. Of the specific share repurchases of companies with primary listings about 46% are not announced, but of the general share repurchases about 77% are not announced. Since share repurchases made bycompanies with secondary listings on the JSE were significant in terms of numbers and value, it changed the total statistics substantially from what it would be if only companies with primary listing on the JSE were considered. Even though about 85% of total share repurchases are announced, studies on share repurchases cannot rely on SENS announcements only, since this would exclude a significant portion of the repurchase activities of companies withprimary listings on the JSE (60%), and therefore lead to unreliable results.

ETHICAL CONCERNS IN USING PUBLIC DATA SOURCES: ISSUES IN ACCESS AND LINKAGE

2011 ◽  
Vol 2011 (1) ◽  
Author(s):  
Daniel Wartenberg ◽  
W. Douglas Thompson ◽  
Gerald Harris
Keyword(s):  
Data Sources ◽  
Ethical Concerns ◽  
Public Data
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