40603353
3D GIS for Geo-coding Human Activity in Micro-scale Urban Environments
The study of human activity and movement in space and time has been an important research area in the social sciences. However, the difficulty in collecting and analyzing the space-time activity (STA) data using current 3D location positioning techniques has limits in applying the time-geographic and activity theory to transportation and urban research and analyses. This paper develops a “3D Indoor Geo-Coding” technique to identify 3D indoor locational data for analyzing human activities. For implementing 3D positioning methods, this paper presents (1) to model micro-scale urban environments to be a frame of reference (reference data) to identify distance and direction, in order to obtain locational data, and (2) to develop a 3D indoor geo-coding method to identify locational data on individual activities based on the reference data. Finally, this paper describes the output from implementing the 3D indoor geo-coding technique to demonstrate the potential benefits of the 3D indoor geo-coding technique for improving the speed of emergency response using GIS data of the study area at Minnesota State University-Mankato, MN (USA).
12138219
Emergency response after 9/11: the potential of real-time 3D GIS for quick emergency response in micro-spatial environments
Terrorist attacks at the World Trade Center (WTC) in New York City and the Pentagon on September 11, 2001, not only affected multi-level structures in urban areas but also impacted upon their immediate environment at the street level in ways that considerably reduced the speed of emergency response. In this paper, we examine the potential of using real-time 3D GIS for the development and implementation of GIS-based intelligent emergency response systems (GIERS) that aim at facilitating quick emergency response to terrorist attacks on multi-level structures (e.g. multi-story office buildings). We outline a system architecture and a network data model that integrates the ground transportation system with the internal conduits within multi-level structures into a navigable 3D GIS. We examine important implementation issues of GIERS, especially the need for wireless and mobile deployment. Important decision support functionalities of GIERS are also explored with particular reference to the application of network-based shortest path algorithms. Finally, we present the results of an experimental implementation of an integrated 3D network data model using a GIS database of Franklin County, Ohio (USA). Our study shows that response delay within multi-level structures can be much longer than delays incurred on the ground transportation system, and GIERS have the potential for considerably reducing these delays.
35344991
Spatial Analysis of Linguistic Data with GIS Functions
Abstract During the 1980s techniques for analysis of geographical patterns have been refined to the point that they may be applied to data from many fields. Quantitative spatial analysis and existing functions available in geographical information systems (GIS) enable computerized implementations of these spatial analysis methods. This paper describes the application of quantitative spatial analysis and GIS functions to analysis of language data, using the extensive files of the Linguistic Atlas of the Middle and South Atlantic States (LAMSAS). A brief review of recent development of using quantitative and statistical methods for analysing linguistic data is also included.
207320410
On fast supervised learning for normal mixture models with missing information
It is an important research issue to deal with mixture models when missing values occur in the data. In this paper, computational strategies using auxiliary indicator matrices are introduced for efficiently handling mixtures of multivariate normal distributions when the data are missing at random and have an arbitrary missing data pattern, meaning that missing data can occur anywhere. We develop a novel EM algorithm that can dramatically save computation time and be exploited in many applications, such as density estimation, supervised clustering and prediction of missing values. In the aspect of multiple imputations for missing data, we also offer a data augmentation scheme using the Gibbs sampler. Our proposed methodologies are illustrated through some real data sets with varying proportions of missing values.
7043785
A new family of authentication protocols
We present a related family of authentication and digital signature protocols based on symmetric cryptographic primitives which perform substantially better than previous constructions. Previously, one-time digital signatures based on hash functions involved hundreds of hash function computations for each signature; we show that given online access to a timestamping service, we can sign messages using only two computations of a hash function. Previously, techniques to sign infinite streams involved one such one-time signature for each message block; we show that in many realistic scenarios a small number of hash function computations is sufficient. Previously, the Diffie Hellman protocol enabled two principals to create a confidentiality key from scratch: we provide an equivalent protocol for integrity, which enables two people who do not share a secret to set up a securely serialised channel into which attackers cannot subsequently intrude. In addition to being of potential use in real applications, our constructions also raise interesting questions about the definition of a digital signature, and the relationship between integrity and authenticity.
2979889
An effective customization procedure with configurable standard models
In electronic catalogs, commodities such as computers and electronic equipment are specified as standard models although a variety of possible alternative specifications can exist as a combination of selected options; therefore, customized configurations are essential to support various customers with individual needs. Thus, the problem here is the selection of a standard model and reconfiguration with this selected model. An issue is that requirements may be fulfilled by more than one standard model. To develop an algorithm that can find the near minimum price without causing unacceptable computation effort, we devised the Standard Model Selection and Modification (SMSM) Algorithm. To establish the SMSM Algorithm, we propose the Concurrent Local Propagation procedure complemented with pruning capability owing to the nature of standard models. The effective strategies for selection of seed variables and stopping rules are devised through comparative experiments.For the experiment, we use Dell's personal computer (PC) products consisting of 42 standard models with 25 specification variables. The SMSM Algorithm is tested with 75 experimental cases, and we found that the most similar standard models could discover the minimum price only in 24 out of 75 cases and that the SMSM procedure could reduce the price by 6.04% from the one offered by the most similar standard models.
1805893
Secure Localization and Location Verification in Sensor Networks
Evolving networks of wireless sensing nodes have many attractive applications. Localization, that is to determine the locations of sensor nodes, is a key enabler for many applications of sensor networks. As sensor networks move closer to extensive deployments, security becomes a major concern, resulting in a new demand for secure localization and location proving systems. In this paper, we propose a secure localization system based on a secure hop algorithm. A location verification system that allows the base station to verify the locations of sensor nodes is also presented. It prevents a node from falsifying reported location information. The evaluation of the secure localization system shows that the proposed scheme performs well under a range of scenarios tested and is resilient against an attacker creating incorrect location information in other nodes.