17746198
Large—scale parallel numerical integration
We present and analyze strategies which can be used for the parallel computation of large numbers of integrals which may be of different levels of difficulty. Parallelization on the integral level, which is generally used for large numbers of integrals, is combined with parallelization on the subregion level, which enables handling local integration difficulties within individual problems. This results in a new, hierarchical algorithm which incorporates load balancing on the integral level and on the subregion level. We report test results of the software and show that the hierarchical approach leads to a scalable integration algorithm.
155165
Multivariate Integration on Hypercubic and Mesh Networks
Abstract We analyze a class of adaptive algorithms for integration over N-dimensional hyper-rectangular or simplical regions, on distributed systems. An adaptive algorithm attempts to achieve the requested accuracy by refining the subdivision of the integration region, thus allowing for a concentration of subdivisions near singularities. At the subdivision of a region, the error behaves according to a prescribed model, relating the error of the parent region to that of its children. The analysis can also be applied to problems in other areas, as long as the task selection is based on a priority function which behaves according to a suitable model. Using an efficient management of the subregions, we show that an O (p/ log p) speedup can be achieved on a p-processor hypercubic network, such as shuffle exchange, butterfly and hypercube. Furthermore, a speedup of O ( p ) can be achieved on a p × p mesh network. We also show that our algorithms compare favorably with well-known dynamic load balancing strategies.
19327594
Mobility-Pattern-Based Anomaly Detection Algorithm in Mobile Networks
Numerous approaches have been proposed for intrusion detection in immobile networks. However, little research work has been done in actually implementing them, especially for anomaly detection, in mobile networks. In this paper, we present an efficient mobility-pattern-based (MPB) anomaly detection algorithm. It can effectively identify abnormal mobility patterns of the nodes in mobile networks. In the proposed algorithm, the normal mobility profile of a specific node is characterized by a multi-leaf tree structure in which each node corresponds to a possible destination cluster. A normal mobility profile is generated during the training process through data mining and fuzzy logic techniques. More specifically, data mining techniques are used for cluster classifications, and fuzzy logic techniques are used to integrate the 'similar'' pattern strings after the corresponding cluster generation. These two techniques are also used during the testing process for distinguishing abnormal mobility patterns of the node from those of the normal in mobile networks. Simulation results demonstrate that our proposed MPB anomaly detection algorithm can achieve good performance in terms of detection rate and false alarm rate for nodes with regular movement behaviors by fine tuning the design parameter - threshold, that can be chosen efficiently.
321445
Detection of Masquerade Attacks on Wireless Sensor Networks
We propose two lightweight techniques to detect masquerade attacks on wireless sensor networks (WSN). Our solutions take into consideration, important WSN properties like coverage, connectivity, data aggregation and specific communication patterns. The two proposed techniques complement each other when used concurrently. The mutual guarding (MG) technique does not work when nodes are not completely covered by their neighbors or when adversary has shorter transmission range than the sensor nodes. It also does not protect nodes near the boundary. The SRP technique does not have these drawbacks. In this paper, we present our proposed techniques and analyze their performance in terms of successful masquerade detection rate and traffic and computational overhead.
626014
The use of hybrid models to recover cardiac wall motion in tagged MR images
We present a new algorithm for the automatic recovery of tag grid-line intersections in Tagged MR images of the left ventricle of the heart. Our method uses an active spring mesh to capture local properties of the motion and a global motion model to capture the global coherence of the motion. We recover the global component of the motion using robust estimation. Different motion models have been developed for short and long axis views of the heart. The algorithm has been tested on healthy and pathological data.
14792710
Enabling analysts in managed services for CRM analytics
Data analytics tools and frameworks abound, yet rapid deployment of analytics solutions that deliver actionable insights from business data remains a challenge. The primary reason is that on-field practitioners are required to be both technically proficient and knowledgeable about the business. The recent abundance of unstructured business data has thrown up new opportunities for analytics, but has also multiplied the deployment challenge, since interpretation of concepts derived from textual sources require a deep understanding of the business. In such a scenario, a managed service for analytics comes up as the best alternative. A managed analytics service is centered around a business analyst who acts as a liaison between the business and the technology. This calls for new tools that assist the analyst to be efficient in the tasks that she needs to execute. Also, the analytics needs to be repeatable, in that the delivered insights should not depend heavily on the expertise of specific analysts. These factors lead us to identify new areas that open up for KDD research in terms of 'time-to-insight' and repeatability for these analysts. We present our analytics framework in the form of a managed service offering for CRM analytics. We describe different analyst-centric tools using a case study from real-life engagements and demonstrate their effectiveness.
14870566
An information fusion framework for robust shape tracking
Existing methods for incorporating subspace model constraints in shape tracking use only partial information from the measurements and model distribution. We propose a unified framework for robust shape tracking, optimally fusing heteroscedastic uncertainties or noise from measurement, system dynamics, and a subspace model. The resulting nonorthogonal subspace projection and fusion are natural extensions of the traditional model constraint using orthogonal projection. We present two motion measurement algorithms and introduce alternative solutions for measurement uncertainty estimation. We build shape models offline from training data and exploit information from the ground truth initialization online through a strong model adaptation. Our framework is applied for tracking in echocardiograms where the motion estimation errors are heteroscedastic in nature, each heart has a distinct shape, and the relative motions of epicardial and endocardial borders reveal crucial diagnostic features. The proposed method significantly outperforms the existing shape-space-constrained tracking algorithm. Due to the complete treatment of heteroscedastic uncertainties, the strong model adaptation, and the coupled tracking of double-contours, robust performance is observed even on the most challenging cases.
9910171
Semantics and CBIR: a medical imaging perspective
Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes. On the other hand, semantics in the medical domain is much better defined and there is a vast accumulation of formal knowledge representations that could be exploited to support semantic search for any specialty areas in medicine.
 In this paper, however, we will not dwell on any one particular specialty area, but rather address the question of how to support scalable semantic search across the whole of medical CBIR field: what are the advantages to take and gaps to fill, what are the key enabling technologies, and the critical success factor from an industrial point of view.
 In terms of enabling technologies, we discuss three aspects: 1. anatomical, disease, and contextual semantics, and their representations using ontologies; 2. scalable image analysis and tagging algorithms; and 3. ontological reasoning and its role in guiding and improving image analysis and retrieval.
 More specifically, for ontological representation of medical imaging semantics, we discuss the potential use of FMA, RadLex, ICD, and AIM. For scalable image analysis we present a learning-based anatomy detection and segmentation framework using distribution-free priors. It is easily adaptable to different anatomies and different imaging modalities.
17420676
A workstation's communication performance benchmark
In this paper we propose a communication benchmark suite: BTU(Bits To the User). In the BTU benchmarking process, the vendor supplies a workstation running a UNIX* operating system, we install our benchmark program and connect the workstation to a testbed which emulates a LAN/WAN environment. The benchmark run will submit the workstation to a carefully designed combination of tests. The result is a predictor of what the user, at the application level, can expect in terms of bits sent to or received from a remote host. Our benchmark takes into account concurrent activities such as CPU and I/O activities which compete for resources on the test machine. The combination of these activities and concurrent activities on the network will interfere with the test machine’s communication performance. The automated BTU benchmark test suite produces results at various levels of abstractions ranging from a single number, characterizing average performance in the style of SPEC92, to a TCP time sequence chart for abnormal behaviors. We intend to serve the user of a workstation by providing information which should enable the users to make a reasonable judgment when acquiring a workstation with a specific configuration within certain cost constraints. Our results when used along with existing benchmarks will make a powerful combination for predicting overall performance. Neither price nor SPECmarks are as good a predictor of communication performance as that measured by BTUs. We conclude this paper with a discussion of extensions to faster networks and our plans for having the community accept this proposal as a communication benchmark.