Natural History

without treatment

Location, location, location

How important is access to markets as a driver of economic prosperity? In new research, Stephen Redding and Daniel Sturm address this question by analysing the post-war division of Germany and its impact on the border cities in the West suddenly cut off from their nearby trading partners

Location, location, location.

How important is access to markets as a driver of economic prosperity? In new research, Stephen Redding and Daniel Sturm address this question by analysing the post-war division of Germany and its impact on the border cities in the West suddenly cut off from their nearby trading partners.

Location, Location, Location: Entrepreneurial Finance Meets Economic Geography

Economic Geography maintains that economic activities are not randomly distributed across space. This paper examines the impact of industrial and regional characteristics on venture capital activities in the United States from 1995 until 2009. The unique database allows for stratifications into seventeen industries within nineteen regions of the United States. This study affirms the significance of both Location and industry in venture capital investment. Both statistical and graphical methods are employed in order to better ascertain the dynamic nature of the data.Venture Capital; Economic Geography; Location; Biotechnology; Business Products and Services; Computers and Peripherals; Consumer Products and Services; Electronics and Instrumentation; Financial Services; Healthcare Services; Industrial and Energy; Information Technology Services; Media and Entertainment; Medical Devices and Equipment; Networking and Equipment; Retailing and Distribution; Semiconductors; Software; Telecommunications.

Location spoofing

The ability to blur and lie about our location does deserve consideration and should not be treated as entirely malevolent. It will be up to designers to allow the user to have full responsibility and freedom over the access control of their location information, rather than force adherence to uncomfortable regimes of dictated access control

Location prediction based on a sector snapshot for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique

Particle impact location detector

Detector includes delay lines connected to each detector surface strip. When several particles strike different strips simultaneously, pulses generated by each strip are time delayed by certain intervals. Delay time for each strip is known. By observing time delay in pulse, it is possible to locate strip that is struck by particle

Location Dependent Dirichlet Processes

Dirichlet processes (DP) are widely applied in Bayesian nonparametric modeling. However, in their basic form they do not directly integrate dependency information among data arising from space and time. In this paper, we propose location dependent Dirichlet processes (LDDP) which incorporate nonparametric Gaussian processes in the DP modeling framework to model such dependencies. We develop the LDDP in the context of mixture modeling, and develop a mean field variational inference algorithm for this mixture model. The effectiveness of the proposed modeling framework is shown on an image segmentation task

Automatic vehicle location system

An automatic vehicle detection system is disclosed, in which each vehicle whose location is to be detected carries active means which interact with passive elements at each location to be identified. The passive elements comprise a plurality of passive loops arranged in a sequence along the travel direction. Each of the loops is tuned to a chosen frequency so that the sequence of the frequencies defines the location code. As the vehicle traverses the sequence of the loops as it passes over each loop, signals only at the frequency of the loop being passed over are coupled from a vehicle transmitter to a vehicle receiver. The frequencies of the received signals in the receiver produce outputs which together represent a code of the traversed location. The code location is defined by a painted pattern which reflects light to a vehicle carried detector whose output is used to derive the code defined by the pattern