429860
Spatial Weighted Outlier Detection
Spatial outliers are the spatial objects with distinct features from their surrounding neighbors. Detection of spatial outliers helps reveal valuable information from large spatial data sets. In many real applications, spatial objects can not be simply abstracted as isolated points. They have different boundary, size, volume, and location. These spatial properties affect the impact of a spatial object on its neighbors and should be taken into consideration. In this paper, we propose two spatial outlier detection methods which integrate the impact of spatial properties to the outlierness measurement. Experimental results on a real data set demonstrate the effectiveness of the proposed algorithms.
18415730
Multivariate Spatial Outlier Detection
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.
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.
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.
11606897
Malicious ICMP Tunneling: Defense against the Vulnerability
This paper presents a systematic solution to the problem of using ICMP tunneling for covert channel. ICMP is not multiplexed via port numbers and the data part of the ICMP packet provides considerable bandwidth for malicious covert channels. These factors make it an integral part of many malicious software like remote access and denial of service attack tools. These tools use ICMP to establish covert communication channels. In this paper a stateless model is proposed to prevent ICMP tunneling. A Linux kernel module was implemented to demonstrate the proposed stateless solution. The module enforces a fixed payload policy for ICMP packets and virtually eliminates ICMP tunneling which arises due to the data carrying capability of ICMP. The performance impact on end hosts and routers due to the stateless monitoring model is described.
11974123
Practical 3-D Shape Measurement Using Optimal Intensity-Modulated Projection and Intensity-Phase Analysis Techniques
In the field of 3D image measurement, a technique based on stripe pattern projection and observation image intensity analysis is expected to be able to detect several stripes by a single projection. It is necessary to increase the stripe number of the projection pattern in order to improve the measurement accuracy of depth distance. However, when the stripe number is increased, the difference of the intensity between stripes will be reduced and stripe detection will become difficult. In order to improve the detection accuracy of the stripe order and shorten the 3D measurement time, we use the optimal intensity-modulation projection (OIMP) technique, and in order to improve the depth distance measurement accuracy, we propose an intensity-phase analysis (IPA) technique. In the proposed IPA technique, the observation pattern be segmented by the intensity of the intensity-modulated stripe, and in every segmentation the depth distance of all pixels are obtained by phase analysis. By using a combination of the OIMP and IPA techniques, high-speed (single projection and double image captures) and high-accuracy (error less than 0.1%) practical 3D shape measurement can be realized
5184285
Design and Analysis of Spatiotemporal Multicast Protocols for Wireless Sensor Networks
AbstractWe propose a new multicast communication paradigm called “spatiotemporal multicast” for supporting applications which require spatiotemporal coordination in wireless sensor networks. In this paper we focus on a special class of spatiotemporal multicast called “mobicast” featuring a message delivery zone that moves at a constant velocity 
$$\vec v$$
. The key contributions of this work are: (1) the specification of mobicast and its performance metrics, (2) the introduction of four different mobicast protocols along with the analysis of their performance, (3) the introduction of two topological network compactness metrics for facilitating the design and analysis of spatiotemporal protocols, and (4) an experimental evaluation of compactness properties for random sensor networks and their effect on routing protocols.
10114388
O(1) Time Algorithm on BSR for Constructing a Binary Search Tree with Best Frequencies
Constructing a binary search tree of n nodes with best frequencies needs Ω(n log n) time on RAM, and Ω(log n) time on n-processor EREW, CREW, or CRCW PRAM. In this paper, we propose an O(1) time algorithm on n-processor BSR PRAM for the problem, which is the first constant time solution to the problem on any model of computation.
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.