32876579
Medical image segmentation and retrieval via deformable models
A new method based on deformable shape models for medical image segmentation is described. Experiments for blood cell micrographs have been conducted to verify the accuracy of the shape model-based segmentation and object shape description method. The cell segmentation method does not require user input for initialization. Coherence information between cells is utilized via a globally consistent cost function. The proposed segmentation method can be used in automated analysis for images of stained blood smear and segmentation of other medical structures. A method for shape population-based retrieval is also described. Results of population-based image queries for a database of blood cell micrographs are shown.
45704904
Automatic Deformable Shape Segmentation for Image Database Search Applications
A method for shape based image database indexing is described. Deformable shape templates are used to group color image regions into globally consistent configurations. A statistical shape model is used to enforce the prior probabilities on global, parametric deformations for each object class. The segmentation is determined in part by the minimum description length (MDL) principle. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with adjacent objects or shadows. The formulation can be used to group image regions based on any image homogeneity predicate; e.g., texture, color, or motion. Preliminary experiments in color segmentation and shape-based retrieval are reported.
17203041
Tight upper bounds for cell loss probabilities in ATM multiplexers and required bandwidth estimation
Estimating the cell loss probability in an ATM multiplexer is a key issue in network management and traffic control such as call admission control and bandwidth allocation. In this paper, we derive a new approximation to estimate the total and individual cell loss probabilities in an ATM multiplexer fed by a superposition of heterogeneous on-off sources with exponentially distributed on and off periods. Based on this approximation, a simple and accurate method is proposed to estimate the aggregate required bandwidth by a given mix of traffic to guarantee a given cell loss probability.
1650170
Efficiently clustering transactional data with weighted coverage density
It is widely recognized that developing efficient and fully automated algorithms for clustering large transactional datasets is a challenging problem. In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the concept of Weighted Coverage Density as a categorical similarity measure for efficient clustering of transactional datasets. The concept of weighted coverage density is intuitive and allows the weight of each item in a cluster to be changed dynamically according to the occurrences of items. Second, we develop two transactional data clustering specific evaluation metrics based on the concept of large transactional items and the coverage density respectively. Third, we implement the weighted coverage density clustering algorithm and the two clustering validation metrics using a fully automated transactional clustering framework, called SCALE (Sampling, Clustering structure Assessment, cLustering and domain-specific Evaluation). The SCALE framework is designed to combine the weighted coverage density measure for clustering over a sample dataset with self-configuring methods that can automatically tune the two important parameters of the clustering algorithms: (1) the candidates of the best number K of clusters; and (2) the application of two domain-specific cluster validity measures to find the best result from the set of clustering results. We have conducted experimental evaluation using both synthetic and real datasets and our results show that the weighted coverage density approach powered by the SCALE framework can efficiently generate high quality clustering results in a fully automated manner.
7311513
Polygonal Shape Blending with Topological Evolutions
This paper presents a new general approach to blend 2D shapes with different topologies. All possible topological evolutions are classified into three types by attaching three different topological cells. This formalism is resulted from Morse theory on the behavior of the 3D surface around a non-degenerate critical point. Also we incorporate degenerate topological evolutions into our framework which produce more attractive morphing effects. The user controls the morph by specifying the types of topological evolutions as well as the feature correspondences between the source and target shapes. Some techniques are also provided to control the vertex path during the morphing process. The amount of user input required to produce a morph is directly proportional to the amount of control the user wishes to impose on the process. The user may allow the system to automatically generate the morph as well. Our approaches are totally geometric based and are easy and fast enough in fully interactive time. Many experimental results show the applicability and flexibility of our approaches.
464743
Specifying and analyzing early requirements in Tropos
We present a framework that supports the formal verification of early requirements specifications. The framework is based on Formal Tropos, a specification language that adopts primitive concepts for modeling early requirements (such as actor, goal, and strategic dependency), along with a rich temporal specification language. We show how existing formal analysis techniques, and in particular model checking, can be adapted for the automatic verification of Formal Tropos specifications. These techniques have been implemented in a tool, called the T-Tool, that maps Formal Tropos specifications into a language that can be handled by the NuSMV model checker. Finally, we evaluate our methodology on a course-exam management case study. Our experiments show that formal analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tools.
9477274
Privacy Analysis for Data Sharing in *nix Systems
Linux and its various flavors (together called *nix) are growing in mainstream popularity and many enterprise infrastructures now are based on *nix platforms. An important component of these systems is the ingrained multi-user support that lets users share data with each other. In this paper, we analyze *nix systems and identify an urgent need for better privacy support in their data sharing mechanisms. In one of our studies it was possible to access over 84 GB of private data at one organization of 836 users, including over 300,000 emails and 579 passwords to financial and other private services websites. The most surprising aspect was the extremely low level of sophistication of the attack. The attack uses no technical vulnerabilities, rather inadequacies of *nix access control combined with user/application's privacy-indifferent behavior.