The government of greater Germany. By James K. Pollock. New York City, D. Van Nostrand Company, Inc., 1938. xiii, 213 pp. $1.25

1939 ◽  
Vol 28 (6) ◽  
pp. 485-485
Author(s):  
Kurt Wilk
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
The Government

scholarly journals EXPLORING DRIVING FACTORS OF HIGHER PAID TAXI TRIPS USING ORIGIN–DESTINATION GPS DATA (CASE STUDY: GREEN TAXIS OF NEW YORK CITY)

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 745-748
Author(s):  
P. Mojtabaee ◽  
M. Molavi ◽  
M. Taleai
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Driving Forces ◽  
Influential Factors ◽  
Driving Factors ◽  
Population Number ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
The Government

Abstract. Investigating the influential factors of the areas where people use taxis is a crucial step in understanding the taxi demand dynamics. In this study, we intend to analyze higher-paying taxi trips by putting forward an approach to explore a dataset of green taxi trips in New York City in January 2015 together with some demographic, housing, social and economic data. The final goal is to find out whether the chosen factors are statistically significant to be considered as potential driving forces of demand location for trips with a higher-paid fare. Since airports are major attracting sources for taxi travels, all the steps are taken separately for three scenarios that the trip drop-offs are in 1) LaGuardia Airport, 2) John F Kennedy Airport or 3) other areas. First, the spatial pick-up distribution of these higher-paying trips is mapped to enable visual comparison of the urban movement patterns. Then, taking into account the pick-up density as the response variable, the densities of: foreign-born’s population, number of houses with no vehicles, the private wage and salary workers’ population, the government workers’ population and the self-employed workers’ population in own not incorporate business were considered as the explanatory variables. These variables were examined to find important factors affecting the demand in each neighborhood and different results in each of the three scenarios were discussed. This study gives a better insight into discovering driving factors of higher-paid taxi trips when considering airports as destinations which attract travels with potentially different characteristics.

scholarly journals Can the Government Deter Discrimination? Evidence from a Randomized Intervention in New York City

2019 ◽  
Vol 81 (1) ◽  
pp. 127-141 ◽  
Author(s):  
Albert H. Fang ◽  
Andrew M. Guess ◽  
Macartan Humphreys
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Randomized Intervention ◽  
The Government

scholarly journals Predict new cases of the Coronavirus 19; in Michigan, U.S.A. or other countries using Crow-AMSAA Method (Preprint)

2020 ◽  
Author(s):  
Yanshuo Wang
Keyword(s):  
New York ◽  
New York City ◽  
Social Distance ◽  
York City ◽  
Death Rate ◽  
Transmission Rate ◽  
Complex Problem ◽  
Mitigation Strategies ◽  
Summary Table ◽  
The Government

BACKGROUND Statistical predictions are useful to predict events based on statistical models. The data is useful to determine outcomes based on inputs and calculations. The Crow-AMSAA method will be explored to predict new cases of Coronavirus 19 (COVID19). This method is currently used within engineering reliability design to predict failures and evaluate the reliability growth. The author intents to use this model to predict the COVID19 cases by using daily reported data from Michigan, New York City, U.S.A and other countries. The piece wise Crow-AMSAA (CA) model fits the data very well for the infected cases and deaths at different phases during the start of the COVID19 outbreak. The slope β of the Crow-AMSAA line indicates the speed of the transmission or death rate. The traditional epidemiological model is based on the exponential distribution, but the Crow-AMSAA is the Non Homogeneous Poisson Process (NHPP) which can be used to modeling the complex problem like COVID19, especially when the various mitigation strategies such as social distance, isolation and locking down were implemented by the government at different places. OBJECTIVE This paper is to use piece wise Crow-AMSAA method to fit the COVID19 confirmed cases in Michigan, New York City, U.S.A and other countries. METHODS piece wise Crow-AMSAA method to fit the COVID19 confirmed cases RESULTS From the Crow-AMSAA analysis above, at the beginning of the COVID 19, the infectious cases did not follow the Crow-AMSAA prediction line, but during the outbreak start, the confirmed cases does follow the CA line, the slope β value indicates the pace of the transmission rate or death rate in each case. The piece wise Crow-AMSAA describes the different phases of spreading. This indicates the speed of the transmission rate could change according to the government interference, social distance order or other factors. Comparing the piece wise CA β slopes (β: 1.683-- 0.834--0.092) in China and in U.S.A (β:5.138--10.48--5.259), the speed of infectious rate in U.S.A is much higher than the infectious rate in China. From the piece wise CA plots and summary table 1 of the CA slope βs, the COVID19 spreading has the different behavior at different places and countries where the government implemented the different policy to slow down the spreading. CONCLUSIONS From the analysis of data and conclusions from confirmed cases and deaths of COVID 19 in Michigan, New York city, U.S.A, China and other countries, the piece wise Crow-AMSAA method can be used to modeling the spreading of COVID19.

Guyanese remittance motivations: altruistic?

2014 ◽  
Vol 41 (3) ◽  
pp. 201-212 ◽  
Author(s):  
Tilokie Depoo
Keyword(s):  
New York ◽  
Economic Development ◽  
New York City ◽  
York City ◽  
Positive Impact ◽  
Altruistic Motive ◽  
Content Type ◽  
The Usa ◽  
The Government ◽  
Remittance Behavior

Purpose – This paper aims to examine the remittance behavior of Guyanese immigrants living in three communities of New York City, USA to assess their remittance behavior and if these are motivated by altruism or the intent to return to live in Guyana. Over the last two decades, remittances accounted for approximately 17 percent of the GDP of the Guyanese economy and continue to grow. The bulk of these remittances are significant from its native sons and daughters residing in the USA. Design/methodology/approach – This case study uses non-experimental survey research design with survey data collected from 300 participants living in New York, with 236 selected for analysis. Findings – Guyanese living in New York City remit monies to Guyana because of a pure altruistic motive as well as believing that their contributions have a positive impact on the economic development of their nations regardless of their intention to return to Guyana. These findings support the altruistic model on remittance motivation. Research limitations/implications – The data gathered for this survey are restricted to three communities in the USA where Guyanese are significant in numbers, thus limiting generalizations and findings to other countries such as Canada, England, where there are significant enclaves of Guyanese immigrants. Practical implications – New York-based Guyanese deem their remittances as contributing to the economic development of their country. This suggest that there may room for a coordinated policy on the part of the Government of Guyana to develop a coordinated plan to engage overseas-based Guyanese to remit more to help with Guyana economic development efforts. Originality/value – This is the first study to survey Guyanese in their host countries to gather information on remittances motivation and the perceived impact of these remittances from the sender's perspective. The paper highlights the significant remittance contributions of US-based Guyanese and their net private flows to Guyana.

Fast-Day Sermon

2012 ◽  
pp. 109-122
Author(s):  
Gershom Mendes Seixas
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Full Text ◽  
War Of 1812 ◽  
Historical Significance ◽  
The Media ◽  
The Government

This chapter turns to the sermon of Gershom Mendes Seixas during the War of 1812. This sermon is the only known extant Jewish preaching text responding to any American war before 1861, delivered before the flagship Jewish congregation of the nation, expressing the ideals of loyal support for the government despite its failures and empathetic commitment to fellow citizens in their time of need. As such, it is a text of considerable historical significance. Here, the chapter shows how Seixas's sermon presents a ringing assertion of the responsibility of citizens in a democracy to support their chosen leaders, even (or perhaps especially) when things are not going well. In this context, Seixas read the full text of the resolution of the New York City Common Council declaring the day of ‘fasting, humiliation and prayer’ as it had been publicized in the media.

scholarly journals Use Crow-AMSAA Method to predict the cases of the Coronavirus 19 in Michigan and U.S.A

2020 ◽  
Author(s):  
Yanshuo Wang
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Complex Problem ◽  
Mitigation Strategies ◽  
Homogeneous Poisson Process ◽  
Ca Model ◽  
The Government ◽  
Reported Data ◽  
Non Homogeneous Poisson Process

AbstractThe Crow-AMSAA method is used in engineering reliability world to predict the failures and evaluate the reliability growth. The author intents to use this model in the prediction of the Coronavirus 19 (COVID19) cases by using the daily reported data from Michigan, New York City, U.S.A and other countries. The piece wise Crow-AMSAA (CA) model fits the data very well for the infected cases and deaths at different phases while the COVID19 outbreak starting. The slope β of the Crow-AMSAA line indicates the speed of the transmission or death rate. The traditional epidemiological model is based on the exponential distribution, but the Crow-AMSAA is the Non Homogeneous Poisson Process (NHPP) which can be used to modeling the complex problem like COVID19, especially when the various mitigation strategies such as social distance, isolation and locking down were implemented by the government at different places.SummaryThis paper is to use piece wise Crow-AMSAA method to fit the COVID19 confirmed cases in Michigan, New York City, U.S.A and other countries.

scholarly journals Quantifying the Building Energy Dynamics of Manhattan, New York City, Using an Urban Building Energy Model and Localized Weather Data

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3244
Author(s):  
Wenliang Li
Keyword(s):  
New York ◽  
New York City ◽  
Carbon Emissions ◽  
York City ◽  
Energy Use ◽  
Building Energy ◽  
Weather Data ◽  
Electricity Use ◽  
Building Energy Use ◽  
The Government

Building sectors account for major energy use and greenhouse gas emissions in the US. While urban building energy-use modeling has been widely applied in many studies, limited studies have been conducted for Manhattan, New York City (NYC). Since the release of the new “80-by-50” law, the NYC government has committed to reducing carbon emissions by 80% by 2050; indeed, the government is facing a big challenge for reducing the energy use and carbon emissions. Therefore, understanding the building energy use of NYC with a high spatial and temporal resolution is essential for the government and local citizens in managing building energy use. This study quantified the building energy use of Manhattan in NYC with consideration of the local microclimate by integrating two popular modeling platforms, the Urban Weather Generator (UWG) and Urban Building Energy Modeling (UBEM). The research results suggest that (1) the largest building energy use is in central Manhattan, which is composed of large numbers of commercial buildings; (2) a similar seasonal electricity-use pattern and significantly different seasonal gas-use patterns could be found in Manhattan, NYC, due to the varied seasonal cooling and heating demand; and (3) the hourly energy-use profiles suggest only one electricity-use peak in the summer and two gas-use peaks in the winter.

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