On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

A Genre-Aware Approach to Focused Crawling

Focused crawlers have as their main goal to crawl Web pages that are relevant to a specific topic or user interest, playing an important role for a great variety of applications. In general, they work by trying to find and crawl all kinds of pages deemed as related to an implicitly declared topic. However, users are often not simply interested in any document about a topic, but instead they may want only documents of a given type or genre on that topic to be retrieved. In this article, we describe an approach to focused crawling that exploits not only content-related information but also genre information present in Web pages to guide the crawling process. This approach has been designed to address situations in which the specific topic of interest can be expressed by specifying two sets of terms, the first describing genre aspects of the desired pages and the second related to the subject or content of these pages, thus requiring no training or any kind of preprocessing. The effectiveness, efficiency and scalability of the proposed approach are demonstrated by a set of experiments involving the crawling of pages related to syllabi of computer science courses, job offers in the computer science field and sale offers of computer equipments. These experiments show that focused crawlers constructed according to our genre-aware approach achieve levels of F1 superior to 88%, requiring the analysis of no more than 65% of the visited pages in order to find 90% of the relevant pages. In addition, we experimentally analyze the impact of term selection on our approach and evaluate a proposed strategy for semi-automatic generation of such terms. This analysis shows that a small set of terms selected by an expert or a set of terms specified by a typical user familiar with the topic is usually enough to produce good results and that such a semi-automatic strategy is very effective in supporting the task of selecting the sets of terms required to guide a crawling process.     

Temporal intensity noise characteristics and discrete numeric accuracy of analog liquid-crystal-based spatial light modulators

We investigate the temporal intensity noise characteristics of analog liquid-crystal-based spatial light modulators and how they affect the device's achievable discrete numeric accuracies in an optical computing system. First we present an analytical development that defines the concept of precision in analog computing systems, then we define a noise metric and a precision-optimal quantizer for determining the discrete numeric characteristics of the devices. Second we present an experimental discussion in which a low-noise test facility constructed for this investigation is described, and the noise characteristics of three commercially available liquid-crystal-based modulators are measured and analyzed. The accuracy implications of this measured noise are then discussed within the context of the analytical model for each modulator.     

Design Optimization of Composite Prosthetic Tubes Using GA-ANN Algorithm Considering Tsai-Wu Failure Criteria

The investigation of possible failures in composite materials is a matter of very great importance, and the Tsai-Wu criterion is an effective criterion for analyzing those flaws in anisotropic materials and defining whether the material at a given load will or will not suffer structural failure. In this study, an optimization procedure is proposed to minimize the maximum value of Tsai-Wu of laminated composite tubes subject to axial loading. Artificial neural networks and genetic algorithms are chosen as optimization tools. The results of this study show that the developed algorithm converges faster. Then, the maximum Tsai-Wu value is used as the objective function and the fiber orientations are the constraints in the optimization process. The results yielded by them are compared and discussed. Optimal results are compared with respect to the usual initial design. The design approach is recommended for structures where composites are the key load-carrying members such as orthopedic prosthesis.     

Improving the yield of NoC-based systems through fault diagnosis and adaptive routing

We propose an effective and low cost method to increase the yield and the lifetime of torus NoCs. The method consists in detecting and diagnosing NoC interconnect faults using BIST structures and activating alternative paths for the faulty links. Alternative paths use the inherent redundancy of the torus topology, thus leading to minimal performance, area, and power overhead. We assume an extended interconnect fault model comprising stuck-at and pairwise shorts within a single link or between any two links in the network. Experimental results for a 3×3 NoC show that the proposed approach can correctly diagnose 93% of all possible interconnect faults and can mitigate 42% of those faults (representing 94.4% of the solvable faults) with a worst case performance penalty of 8% and 1% of area overhead. We also demonstrate the scalability of the method by presenting its application to larger NoCs.     

Geolocation of Multiple Targets from Airborne Video Without Terrain Data

The task of geolocating targets from airborne video is required for many applications in surveillance, law enforcement, reconnaissance, etc. The usual approaches to target geolocation involve terrain data, single target tracking, gimbal control of camera heads, altimeters, etc. The main goal of this research is to eliminate those requirements and still develop an accurate, efficient, and robust vision-based method for geolocation that can be carried out for multiple targets simultaneously. In that sense, our main contributions to the state-of-the-art in geolocation are fourfold: 1) to eliminate the requirement for gimbal control of the cameras or any particular path planning control for the UAV; 2) to perform instaneous geolocation of multiple targets; 3) to eliminate the requirements for geo-referenced terrain database (elevation maps) or for an altimeter that provides the UAV’s and target’s altitudes; and 4) to use one single camera while still maintaining good overall accuracy. In order to achieve that, the only requirements for our proposed method are: that the intrinsic parameters of the camera be known; that the on board camera be equipped with global positioning system (GPS) and inertial measurement unit (IMU); and that the height of the vehicle can be calculated using feature points extracted from the ground surrounding the image of the targets. To satisfy the first two requirements, we developed and tested a robust calibration procedure that can estimate not only the intrinsic parameters of the camera, but also the IMU-camera parameters (also know in the robotic circles as the hand-eye calibration). The last requirement was addressed using a pseudo-stereo vision technique that maximizes the distance between stereo pairs (baseline) while keeping large the number of common feature points extracted by the algorithm. The result is a method that can reach approximately 25 m of accuracy for an UAV flying at 155 m away from the target. Such performance is demonstrated by computer simulation, in-scale data using a model city, and real airborne video with ground truth.     

Model-based testing approaches selection for software projects

Selecting software technologies for software projects represents a challenge to software engineers. It is known that software projects differ from each other by presenting different characteristics that can complicate the selection of such technologies. This is not different when considering model-based testing. There are many approaches with different characteristics described in the technical literature that can be used in software projects. However, there is no indication as to how they can fit a software project. Therefore, a strategy to select model-based testing approaches for software projects called Porantim is fully described in this paper. Porantim is based on a body of knowledge describing model-based testing approaches and their characterization attributes (identified by secondary and primary experimental studies), and a process to guide by adequacy and impact criteria regarding the use of this sort of software technology that can be used by software engineers to select model-based testing approaches for software projects.     

Iso-Kinematic Maps from statistical analysis of PS-InSAR data of Piemonte, NW Italy: Comparison with geological kinematic trends

SAR interferometry based on Permanent Scatterers (PS-InSAR™) is used here to study the present crustal mobility of a large area of NW Italy, in the Piemonte region.Thirty-eight satellite scenes (ERS SAR), taken from May 1992 to January 2001, were analysed for detecting more than 2 million PS on the study area. Continuous velocity surface maps (Iso-Kinematic Maps: IKM) were obtained from geo-statistical and spatial cluster techniques (Hot Spot analysis) of PS “short-period” data, to identify relative ground motions and to compare them with “long-period” tectonic mobility trends, i.e. those inferred at regional scale over geological times (some million years).The comparison was made by individuation of homogeneous kinematic areas, represented in the IKM, and characterization of the boundaries between them (Iso-Kinematic Boundaries: IKB). The IKB were used as tools to asses if the PS-InSAR data on present-day crustal mobility could fit with the distribution of real tectonic structures or field geological elements.IKM were drawn for uplifting geological sectors of Piemonte (Maritime Alps, Gran Paradiso, Langhe) where moderate to very low seismicity is recorded, and gravitational instabilities of rock mass on mountain slopes are widespread. The land sectors have been chosen in order to test the suitability of IKM in very different geo-morphological conditions.Different types of correspondence between the IKM and the geological kinematic trend were found:

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a first type in which the kinematic trend of short-period (a decade of years, i.e. the PS-InSAR detection time span) is in agreement with a long-period tectonic trend (some million years) and seem to be driven by well known faults subparallel to the IKB. These kinematic trends can be hidden by the slope movement due to gravitational instabilities;

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a second type in which the kinematic trend of short-period does not strictly correspond to the long-period trend, but can be considered as minor-order, uplifting-subsidence cycles, even if in contrast with the long-period kinematic trend. Alternatively, the short-period kinematic trends could reflect the action of deep-seated geological forces or structures, not yet known or inferable (at least with the recorded PS-InSAR velocities) on the basis of the available geological data and models.