8614779
AITVS: Advanced Interactive Traffic Visualization System
Transportation and the highway network form the backbone of the total public infrastructure system. As such, planning and monitoring for an effective transportation system is crucial in the building and maintenance of a region’s economy and safety. However, demand for road travel continues to expand as population increases (particularly in the metropolitan areas) while new constructions have not kept pace. According to the Federal Highway Administration, it is forecasted that the volume of freight movement alone is to nearly double by 2020 [1]. Congestion and looming gridlock crises seriously threaten any region’s mobility, safety and economic vitality. A crucial component in addressing these concerns is the development of specific technologies to monitor, model, and optimize traffic flow.
14730448
Detecting spatial outliers with multiple attributes
A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. Previous work in spatial outlier detection focuses on detecting spatial outliers with a single attribute. In the paper, we propose two approaches to discover spatial outliers with multiple attributes. We formulate the multi-attribute spatial outlier detection problem in a general way, provide two effective detection algorithms, and analyze their computation complexity. In addition, using a real-world census data, we demonstrate that our approaches can effectively identify local abnormality in large spatial data sets.
9704136
Detecting region outliers in meteorological data
Spatial outliers are the spatial objects with distinct features from their surrounding neighbors. Detection of spatial outliers helps reveal important and valuable information from large spatial data sets. In the field of meteorology, for example, spatial outliers can be associated with disastrous natural events such as tornadoes, hurricane, and forest fires. Previous study of spatial outlier mainly focuses on point data. However, in the meteorological data or other applications, spatial outliers are frequently represented in region, i.e., a group of points, with two dimensions or even three dimensions, and the previous point-based approaches may not be appropriate to be used. As region outliers are commonly multi-scale objects, wavelet analysis is an effective tool to study them. In this paper, we propose a wavelet analysis based approach to detect region outliers. We discuss the region outlier detection problem and design a suite of algorithms to effectively discover them. The algorithms were implemented and evaluated with a real-world meteorological data set.
17196005
Analysis of payment transaction security in mobile commerce
Mobile payment is the process of two parties exchanging financial value using a mobile device in return for goods or services. This paper is an analysis of the security issues in mobile payment for m-commerce. We introduce m-commerce and mobile payment, discuss the public key infrastructure as a basis for secure mobile technologies, and study the features for different security technologies employed in current m-commerce market, including WAP, SIM application toolkit and J2M. In addition, we compare the effectiveness of these security technologies in supporting a secure mobile payment, and discuss research issues to enhance the security of mobile payment for large scale deployment of m-commerce.
3228880
Wavelet fuzzy classification for detecting and tracking region outliers in meteorological data
In this paper, a wavelet fuzzy classification approach is proposed to detect and track region outliers in meteorological data. First wavelet transform is applied to meteorological data to bring up distinct patterns that might be hidden within the original data. Then a powerful image processing technique, edge detection with competitive fuzzy classifier, is extended to identify the boundary of region outlier. After that, to determine the center of the region outlier, the fuzzy-weighted average of the longitudes and latitudes of the boundary locations is computed. By linking the centers of the outlier regions within consecutive frames, the movement of a region outlier can be captured and traced. Experimental evaluation was conducted on a real-world meteorological data to examine the effectiveness of the proposed approach. This work will help discover interesting and implicit information for large volume of meteorological data.
1895171
Data mining for selective visualization of large spatial datasets
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for pattern and trend analysis, and it is a common method of browsing spatial datasets to look for patterns. However the growing volume of spatial datasets make it difficult for humans to browse such datasets in their entirety, and data mining algorithms are needed to filter out large uninteresting parts of spatial datasets. We construct a web-based visualization software package for observing the summarization of spatial patterns and temporal trends. We also present data mining algorithms for filtering out vast parts of datasets for spatial outlier patterns. The algorithms were implemented and tested with a real-world set of Minneapolis-St. Paul (Twin Cities) traffic data.
17738179
Perfect edge domination and efficient edge domination in graphs
Let G = (V,E) be a finite and undirected graph without loops and multiple edges. An edge is said to dominate itself and any edge adjacent to it. A subset D of E is called a perfect edge dominating set if every edge of E \ D is dominated by exactly one edge in D and an efficient edge dominating set if every edge of E is dominated by exactly one edge in D. The perfect (efficient) edge domination problem is to find a perfect (efficient) edge dominating set of minimum size in G. Suppose that each edge e is associated with a real number w(e) as its weight. Then, the weighted perfect (efficient) edge domination problem is to calculate a perfect (efficient) edge dominating set D such that the weight w(D) of D is minimum, where w(D)=Σe∈D w(e). In this paper, we show that the perfect (efficient) edge domination problem is NP-complete on bipartite (planar bipartite) graphs. Moreover, we present linear-time algorithms to solve the weighted perfect (efficient) edge domination problem on generalized series-parallel graphs and chordal graphs.
30370540
On (d, 2)-dominating numbers of binary undirected de Bruijn graphs
Abstract In this paper, we show that: (i) For n-dimensional undirected binary de Bruijn graphs, UB(n), n⩾4, there is a vertex x=x 1 x 1 x 1 ⋯ x 1 x 1 (x1=1 or 0) such that for any other vertex t there exist at least two internally disjoint paths of length at most n−1 between x and t in UB(n), i.e., the (n−1,2)-dominating number of UB(n) is equal to one. (ii) For n⩾5, let S={100⋯01,011⋯10}. For any other vertex t there exist at least two internally disjoint paths of length at most n−2 between t and S in UB(n), i.e., the (n−2,2)-dominating number of UB(n) is no more than 2.
1071507
On greedy geographic routing algorithms in sensing-covered networks
Greedy geographic routing is attractive in wireless sensor networks due to its efficiency and scalability. However, greedy geographic routing may incur long routing paths or even fail due to routing voids on random network topologies. We study greedy geographic routing in an important class of wireless sensor networks that provide sensing coverage over a geographic area (e.g., surveillance or object tracking systems). Our geometric analysis and simulation results demonstrate that existing greedy geographic routing algorithms can successfully find short routing paths based on local states in sensing-covered networks. In particular, we derive theoretical upper bounds on the network dilation of sensing-covered networks under greedy geographic routing algorithms. Furthermore, we propose a new greedy geographic routing algorithm called Bounded Voronoi Greedy Forwarding (BVGF) that allows sensing-covered networks to achieve an asymptotic network dilation lower than 4:62 as long as the communication range is at least twice the sensing range. Our results show that simple greedy geographic routing is an effective routing scheme in many sensing-covered networks.
7786870
Construction of a hierarchical classifier schema using a combination of text-based and image-based approaches
Web document hierarchical classification approaches often rely on textual features alone even though web pages include multimedia data. We propose a new hierarchical integrated web classification approach that combines image-based and text-based approaches. Instead of using a flat classifier to combine text and image classification, we perform classification on a hierarchy differently on different levels of the tree, using text for branches and images only at leaves. The results of our experiments show that the use of the hierarchical structure improved web document classification performance significantly.
16028942
On monotone planar circuits
In this paper we show several results about monotone planar circuits. We show that monotone planar circuits of bounded width, with access to negated input variables, compute exactly the functions in non-uniform AC/sup 0/. This provides a striking contrast to the non-planar case, where exactly NC/sup 1/ is computed. We show that the circuit value problem for monotone planar circuits, with inputs on the outerface only, can be solved in LOGDCFL/spl sube/SC, improving a LOGCFL upper bound due to Dymond and Cook. We show that for monotone planar circuits, with inputs on the outerface only, excessive depth compared to width is useless; any function computed by a monotone planar circuit of width w with inputs on the outerface can be computed by a monotone planar circuit of width O(w) and depth w/sup O(1)/. Finally, we show that monotone planar read-once circuits, with inputs on the outerface only, can be efficiently learned using membership queries.