Unit Roots, Level Shifts and Trend Breaks in Per Capita Output: A Robust Evaluation

Determining whether per capita output can be characterized by a stochastic trend is complicated by the fact that infrequent breaks in trend can bias standard unit root tests towards non-rejection of the unit root hypothesis. The bulk of the existing literature has focused on the application of unit root tests allowing for structural breaks in the trend function under the trend stationary alternative but not under the unit root null. These tests, however, provide little information regarding the existence and number of trend breaks. Moreover, these tests suffer from serious power and size distortions due to the asymmetric treatment of breaks under the null and alternative hypotheses. This paper estimates the number of breaks in trend employing procedures that are robust to the unit root/stationarity properties of the data. Our analysis of the per-capita GDP for OECD countries thereby permits a robust classification of countries according to the "growth shift", "level shift" and "linear trend" hypotheses. In contrast to the extant literature, unit root tests conditional on the presence or absence of breaks do not provide evidence against the unit root hypothesis.growth shift, level shift, structural change, trend breaks, unit root.

Statistically derived contributions of diverse human influences to twentieth-century temperature changes

The warming of the climate system is unequivocal as evidenced by an increase in global temperatures by 0.8 °C over the past century. However, the attribution of the observed warming to human activities remains less clear, particularly because of the apparent slow-down in warming since the late 1990s. Here we analyse radiative forcing and temperature time series with state-of-the-art statistical methods to address this question without climate model simulations. We show that long-term trends in total radiative forcing and temperatures have largely been determined by atmospheric greenhouse gas concentrations, and modulated by other radiative factors. We identify a pronounced increase in the growth rates of both temperatures and radiative forcing around 1960, which marks the onset of sustained global warming. Our analyses also reveal a contribution of human interventions to two periods when global warming slowed down. Our statistical analysis suggests that the reduction in the emissions of ozone-depleting substances under the Montreal Protocol, as well as a reduction in methane emissions, contributed to the lower rate of warming since the 1990s. Furthermore, we identify a contribution from the two world wars and the Great Depression to the documented cooling in the mid-twentieth century, through lower carbon dioxide emissions. We conclude that reductions in greenhouse gas emissions are effective in slowing the rate of warming in the short term.F.E. acknowledges financial support from the Consejo Nacional de Ciencia y Tecnologia (http://www.conacyt.gob.mx) under grant CONACYT-310026, as well as from PASPA DGAPA of the Universidad Nacional Autonoma de Mexico. (CONACYT-310026 - Consejo Nacional de Ciencia y Tecnologia; PASPA DGAPA of the Universidad Nacional Autonoma de Mexico

SSwWS: structural model of information architecture

The Web Technologies allow a representation of a domain of knowledge. This facilitates the conversion of an explicit and tacit knowledge to the possibility of adding knowledge to the Web for automatic processing by the computer. For this reason, it has been designed to be an architecture known as SSwWS (Search Semantic with Web Services) or Search Semantic Web Services, to show how to extend the functionality of the Web search and semantic raised by Berners-Lee, on the meta-references, defined in a Web ontology, so that a user on the Internet can find the answers to their questions through Web services in a simple and fast

Autonomous Flight and Real-time Tracking of Nano Unmanned Aerial Vehicle

This study describes a system in which a micro UAV (quadrotor) was coupled with a Kinect (v2), a Myo armband and an RGB camera. The quadrotor was connected to two PC clients or workstations and communicated through the Robot Operating System. The UAV moved to the marked targets in a cluttered environment without collision using the depth sensor. Recognises faces via the on-board camera based on the frame by frame basis and uses feature-based monocular simultaneous localisation and mapping (SLAM) in real-time. The SLAM tracks the pose of the quadrotor, simultaneously builds an incremental map of the surrounding environment to locate the UAV in that. The Myo armband was employed for teleoperation which commands the quadrotor to start/stop its journey or to begin a new task using hand gestures. The face recognition algorithm was developed using the Fisherface library and pre-trained database. Three missions were assigned to the UAV; to detect the marked area via Kinect's depth sensor, fly towards and hover around the marked area, send the image/video streams to the ground station and to look for the person's face in the crowded environment, match the name with the face owner and follow him/her within the distance of $2$ m. Various organisations could use the proposed system for different purposes. It could be utilised for search and rescue, environmental monitoring, surveillance or inspection. It could be used to identify a person in a collapsed building, in urban/suburban areas or to locate people with a particular need (alzheimer or dementia casualties which leads to wandering behaviour)

Emoji Extractions from Geotagged Twitter Data

We provide a filtered, pre-processed and anonymized dataset collected originally from the Twitter decahose (a random 10% sample of Twitter) over 29 days in October, 2016, to support computational social science research on how people on Twitter use emojis. The data comprises of a table with four columns and 4,057,872 rows (including a header). The fields of the table are: ID: A unique tweet ID that could also be used to ‘hydrate’ the contents of the tweet directly from Twitter. Country: The country code associated with the tweet. Language: The language metadata tag associated with the tweet. We only retain the top 30 languages (sorted by frequency of tweets) in our initial corpus. Emojis: The emojis extracted from the ‘text’ field of the tweet. The methodology that was used to extract the tweets is described in the next section. A paper that uses the data as the basis for its findings and also contains descriptive statistics: M. Kejriwal, Q. Wang, H. Li, L. Wang, An Empirical Study of Emoji Usage on Twitter in Linguistic and National Contexts. Online Social Networks and Media. In Press