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Detecting Intrusions and anomalies is becoming much more challenging with new attacks popping out over a period of time. Achieving better accuracies by applying benchmark classifier algorithms used for identifying intrusions and anomalies have several hidden data mining challenges. Although neglected by many research findings, one of the most important and biggest challenges is the similarity or membership computation. Another challenge that cannot be simply neglected is the number of features that attributes to dimensionality. This research aims to come up with a new membership function to carry similarity computation that can be helpful for addressing feature dimensionality issues. In principle, this work is aimed at introducing a novel membership function that can help to achieve better classification accuracies and eventually lead to better intrusion and anomaly detection. Experiments are performed on KDD dataset with 41 attributes and also KDD dataset with 19 attributes. Recent approaches CANN and CLAPP have showed new approaches for intrusion detection. The proposed classifier is named as UTTAMA. UTTAMA performed better to both CANN and CLAPP approaches w.r.t overall classifier accuracy. Another promising outcome achieved using UTTAMA is the U2R and R2L attack accuracies. The importance of proposed approach is that the accuracy achieved using proposed approach outperforms CLAPP, CANN, SVM, KNN and other existing classifiers., Author(s): Arun Nagaraja [sup.1], B. Uma [sup.2], Rajesh kumar Gunupudi [sup.3] Author Affiliations: (1) grid.449351.e, 0000 0004 1769 1282, Department of Information Science and Engineering, Jain University, , Bangalore, India [...]

Since its inception, the method of capillary electrophoresis has developed into a powerful analytical tool for the analysis of food and environmental samples, forensic and bioanalytical analysis. The review considers the main trends in the development of the electrophoretic method: the use of nanomaterials as a fundamentally new approach to the electrophoretic separation of analytes; search and implementation of effective options for on-line and in-line preconcentration; a combination of a capillary electrophoresis system with a mass spectrometric detector for targeted and nontargeted metabolic profiling., Author(s): L. A. Kartsova [sup.1], D. V. Makeeva [sup.1], E. A. Bessonova [sup.1] Author Affiliations: (1) grid.15447.33, 0000 0001 2289 6897, Institute of Chemistry, St. Petersburg State University, , 198504, [...]

Due to the lack of wide availability of parking assisting applications, vehicles tend to cruise more than necessary to find an empty parking space. This problem is evident globally and the intensity of the problem varies based on the demand of parking spaces. It is a well-known hypothesis that the amount of cruising by a vehicle is dependent on the availability of parking spaces. However, the amount of cruising that takes place in search of parking spaces within a parking lot is not researched. This lack of research can be due to privacy and illumination concerns with suitable sensors like visual cameras. The use of thermal cameras offers an alternative to avoid privacy and illumination problems. Therefore, this paper aims to develop and demonstrate a methodology to detect and track the cruising patterns of multiple moving vehicles in an open parking lot. The vehicle is detected using Yolov3, modified Yolo, and custom Yolo deep learning architectures. The detected vehicles are tracked using Kalman filter and the trajectory of multiple vehicles is calculated on an image. The accuracy of modified Yolo achieved a positive detection rate of 91% while custom Yolo and Yolov3 achieved 83% and 75%, respectively. The performance of Kalman filter is dependent on the efficiency of the detector and the utilized Kalman filter facilitates maintaining data association during moving, stationary, and missed detection. Therefore, the use of deep learning algorithms and Kalman filter facilitates detecting and tracking multiple vehicles in an open parking lot., Author(s): Vijay Paidi (corresponding author) [1]; Hasan Fleyeh [1]; Johan Håkansson [1]; Roger G. Nyberg [1] 1. Introduction Congestion and pollution from traffic are major problems in many urban areas. [...]

A central feature of quantum mechanics is that a measurement result is intrinsically probabilistic. Consequently, continuously monitoring a quantum system will randomly perturb its natural unitary evolution. The ability to control a quantum system in the presence of these fluctuations is of increasing importance in quantum information processing and finds application in fields ranging from nuclear magnetic resonance (1) to chemical synthesis (2). A detailed understanding of this stochastic evolution is essential for the development of optimized control methods. Here we reconstruct the individual quantum trajectories (3-5) of a superconducting circuit that evolves under the competing influences of continuous weak measurement and Rabi drive. By tracking individual trajectories that evolve between any chosen initial and final states, we can deduce the most probable path through quantum state space. These pre- and post-selected quantum trajectories also reveal the optimal detector signal in the form of a smooth, time-continuous function that connects the desired boundary conditions. Our investigation reveals the rich interplay between measurement dynamics, typically associated with wavefunction collapse, and unitary evolution of the quantum state as described by the Schrodinger equation. These results and the underlying theory (6), based on a principle of least action, reveal the optimal route from initial to final states, and may inform new quantum control methods for state steering and information processing., Our experiment focuses on the dynamics of two quantum levels of a superconducting circuit (a quantum bit, or qubit), which can be continuously measured and excited by microwave pulses. To [...]

The image-based incident detection system is capable of not only replacing the loop detector, which has limited management and operation functions, but can also record the sequential conditions before and after a traffic accident. Thus, it is possible to analyze its mechanisms objectively using this data. In this study, the researchers developed a reliable video image based accident detection system with a high detection rate and low error rates. The proposed accident detection algorithm in this study provides the preliminary judgment of potential accident by detecting stopped objects using the Gaussian Mixture Model. Afterwards, it measures the traces of vehicles, the speed variance, and the occupancy per detecting area to propose an algorithm that makes the final accident decision. The proposed algorithm performs accident detection by extracting the stopped objects based on the video image, the trajectory movement of the trailing vehicle, and the variance of speed and traffic volume in the detection area. Thus, it can minimize false detections and maximize the detection rate, making it possible to accurately interpret an accident site and the circumstances surrounding it. Moreover, it is advantageous that the detection rate does not decline under bad weather conditions such as cloudy, rainy, foggy, or snowy. Key words: traffic control, transport, incident detection, Gaussian. Un systeme de detection d'accidents base sur des images peut non seulement remplacer le detecteur a boucle d'induction, lequel a des fonctions de gestion et d'operation limitees, mais peut egalement enregistrer les conditions sequentielles avant et apres un accident de la circulation. Il est donc possible d'analyser ses mecanismes de maniere objective en utilisant ces donnees. Les chercheurs de la presente etude ont developpe un systeme de detection des accidents fiable, base sur les images video, et presentant un taux eleve de detection et de faibles taux d'erreur. L'algorithme de detection des accidents propose dans cette etude fourni une evaluation preliminaire des accidents potentiels en detectant les objets arretes par l'utilisation du modele de melange gaussien. Puis, il mesure les traces des vehicules, la variation de la vitesse et l'occupation de la zone de detection afin de proposer un algorithme qui rend la decision finale d'accident. L'algorithme propose detecte les accidents en extrayant les objets arretes selon l'image video, la trajectoire du vehicule arriere, ainsi que la variation de la vitesse et le volume de circulation dans la zone de detection. Il peut donc minimiser les fausses detections et maximiser le taux de detection, rendant possible l'interpretation precise d'un site d'accident et les circonstances associees. De plus, il est avantageux que le taux de detection ne s'amenuise pas sous des conditions climatiques defavorables, telles que nuages, pluie, brouillard ou neige. Mots-cles : controle de la circulation, transport, detection des incidents, Gaussian. [Traduit par la Redaction], 1. Introduction Traffic problems, such as traffic congestion and accidents, are becoming more and more serious. Traffic congestion is caused by a variety of factors such as a lack of [...]

Prevalence of carbon monoxide (CO) alarm usage in localities where they are not required is poorly defined and the reasons for failing to have a home CO alarm have never been described. In this study, the authors conducted a computer-based survey among employees of similar major medical centers in Seattle, Washington, and Salt Lake City, Utah. Questions were asked about the prevalence of use of residential smoke and CO alarms with regard to home style and structure, ownership status, and energy use. Respondents not using home CO detectors were asked the reasons. Among 1,351 individuals participating in the survey, 98% reported residential use of smoke alarms, while only 51% used CO alarms. CO alarm use was more common among residents of Utah than Washington, among home owners than renters, and among those with single family homes rather than other styles. Reasons for failure to use CO alarms related largely to lack of knowledge about the devices and motivation., Introduction Carbon monoxide (CO) poisoning is responsible for an estimated 500 unintentional non-fire-related deaths in the U.S. annually (Centers for Disease Control and Prevention [CDC], 2005), along with 15,000-50,000 emergency [...]

As an active remote sensor technology, the terrestrial laser scanner is widely used for direct generation of a three-dimensional (3D) image of an object in the fields of geodesy, surveying, and photogrammetry. In this article, a new laser scanner using array avalanche photodiodes, as designed by the Shanghai Institute of Technical Physics of the Chinese Academy of Sciences, is introduced for rapid collection of 3D data. The system structure of the new laser scanner is first presented, and a mathematical model is further derived to transform the original data to the 3D coordinates of the object in a user-defined coordinate system. The performance of the new laser scanner is tested through a comprehensive experiment. The result shows that the new laser scanner can scan a scene with a field view of 30[degrees] x 30[degrees] in 0.2 s and that, with respect to the point clouds obtained on the wall and ground floor surfaces, the root mean square errors for fitting the two planes are 0.21 and 0.01 cm, respectively. The primary advantages of the developed laser scanner include: (i) with a line scanning mode, the new scanner achieves simultaneously the 3D coordinates of 24 points per single laser pulse, which enables it to scan faster than traditional scanners with a point scanning mode and (ii) the new scanner makes use of two galvanometric mirrors to deflect the laser beam in both the horizontal and the vertical directions. This capability makes the instrument smaller and lighter, which is more acceptable for users. [c] 2010 Optical Society of America OCIS codes: 140.0140, 280.0280, 040.0040.

Advancements in transportation coupled with the growth and movement of human populations enable efficient transport of infectious diseases almost anywhere in the world within 24 hours (1). This recognition has [...]

A challenge in the detection of explosives is the differentiation between explosives and contaminants. Synthetic musk-containing perfumes can cause false alarms, as these perfumes are nitroaromatic compounds, which can be mistaken for trinitro toluene (TNT) by some detectors. We present a detection principle based on surface-enhanced Raman scattering (SERS). A stream of the airborne compounds is focused and resublimated on a cooled nanostructured gold surface. We recorded high-resolution SERS spectra of TNT, musk xylene, and musk ketone. The nitroaromatic compounds can be identified unambiguously by their SERS spectra. Even the dominant bands containing nitro-group scissoring and symmetric stretching modes are significantly shifted by the difference in molecular structure. OCIS codes: 240.6695, 300.6450.

We report detection and identification of trace quantities of explosives at standoff distances up to 150 m with high sensitivity (signal-to-noise ratio of ~70) and high selectivity. The technique involves illuminating the target object with laser radiation at a wavelength that is strongly absorbed by the target. The resulting temperature rise is observed by remotely monitoring the increased blackbody radiation from the sample. An unambiguous determination of the target, TNT, in soil samples collected from an explosives test site in China Lake Naval Air Weapons Station is achieved through the use of a tunable C[O.sub.2] laser that scans over the absorption fingerprint of the target explosives. The theoretical analysis supports the observation and indicates that, with optimized detectors and data processing algorithms, the measurement capability can be improved significantly, permitting rapid standoff detection of explosives at distances approaching 1 km. The detection sensitivity varies as [R.sup.-2] and, thus, with the availability of high power, room-temperature, tunable mid-wave infrared and long-wave infrared quantum cascade lasers, this technology may play an important role in screening personnel and their belongings at short distances, such as in airports, for detecting and identifying explosives material residue on persons. [c] 2010 Optical Society of America OCIS codes: 140.0140, 250.0250, 010.0280, 010.3640, 010.5630.

Characterizing permeability of the endothelium that lines blood vessels and heart valves provides fundamental physiological information and is required to evaluate uptake of drugs and other biomalecules. However, current techniques used to measure permeability, such as Transwell insert assays, do not account for the recognized effects of fluid flow-induced shear stress on endothelial permeability or are inherently low-throughput. Here we report a novel on-chip technique in a two-layer membrane-based microfluidic platform to measure real-time permeability of endothelial cell monolayers on porous membrsnes. Bovine serum albumin (a model protein) conjugated with fluoreseein isothiocyanate was delivered to an upper microchannel by pressure-driven flow and was forced to permeate a poly(ethylene terephthalate) membrane into a lower microchannel, where it was detected by laser-induced fluorescence. The concentration of the permeate at the point of detection varied with channel flow rates in agreement to less than 1% with theoretical analyses using a pore flow model. On the basis of the model, a sequential flow rate stepping scheme was developed and applied to obtain the permeability of cell-free and cell-bound membrane layers. This technique is a highly sensitive, novel microfluidic approach for measuring endothelial permeability in vitro, and the use of micrometer-sized channels offers the potential for parallelization and increased throughput compared to conventional shear-based permeability measurement methods. 10.1012/ac901560w

Buckmlnsterfullerene ([C.sub.60) as a primary ion for secondary ion mass spectrometry (SIMS) has shown many benefits over classical SIMS sources in the analysis of large organic molecules including many of biological significance. One constraint has been the limited focusing capabilities of the [C.sub.60] beam. Although this could be circumvented by using beam size limiting apertures at the cost of beam current, high-resolution imaging using conventional time-of-flight (TOF) instruments has been challenging and time-consuming. We present a method in which we combine the use of an unfocused [C.sub.60.sup.+] beam with an ion optical microscope. A delay line detector is used to obtain fully resolved hyperspectral data sets that contain both the full mass spectral and the localization information. The obtained image resolving power is 4[micro]m at a pixel size of 250 nm. Microscope mode [C.sub.60.sup.+] imaging was shown to resolve micrometer-scale features in a combined polymer-tissue sample. Our new approach demonstrates high-quality SIMS imaging using the full [C.sub.60.sup.+] beam current. This results in equal or better resolving power at reduced acquisition speed. 10.1021/ac902587g

No single biomarker can accurately predict disease. An ideal biodetection technology should be capable of the quantitative, reproducible, and sensitive detection of a limited suite of such molecules. To this end, we have developed a multiplex biomarker assay for protective antigen and lethal factor of the Bacillus anthracis lethal toxin using semiconductor quantum dots as the fluorescence reporters on our waveguide-based biosensor platform. The platform is extendable to a wide array of biomarkers, facilitating rapid, quantitative, sensitive, and multiplex detection, better than achievable by conventional immunoassay. Our assay allows for the sensitive (limit of detection 1 pM each), specific (minimal nonspecific binding), and rapid (15 min) detection of these biomarkers in complex biological samples (e.g., serum). To address the issue of reproducibility in measurement and to increase our sample throughput, we have incorporated multichannel waveguides capable of simultaneous multiplex detection of biomarkers in three samples in quadruplicate. In this paper, we present the design, fabrication, and development of multichannel waveguides for the simultaneous detection of lethal factor and protective antigen in serum. Evaluation of the multichannel waveguide shows an excellent concordance with single-channel data and effective, simultaneous, and reproducible measurement of lethal toxins in three samples. 10.1021/ac901497g

This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared. Keywords--Filtering, Minmax Detector Based (MDB), noise, centre weighted mean filter, PSNR, restoration., I. INTRODUCTION IMAGE processing algorithms are designed to handle different problem domains. Some of the broad area includes (i) Image Representation and Modeling Image Transforms, (ii) Image Enhancement Image Restoration, [...]

The ability to measure or estimate accurate speed data are of great importance to a large number of transportation system operations applications. Estimating speeds from the widely used single inductive loop sensor has been a difficult, yet important challenge for transportation engineers. Based on empirical evidence observed from sensor data collected in two metropolitan regions in Virginia and California, this research developed a Kalman filter model to perform speed estimation for congested traffic. Taking advantage of the coexistence of dual loop and single loop stations in many freeway management systems, a calibration procedure was developed to seed and initiate the algorithm. Finally, the paper presents an evaluation that illustrates that the proposed algorithm can produce acceptable speed estimates under congested traffic conditions, consistently outperfoming the conventional g-factor approach. DOI: 10.1061/(ASCE)TE.1943-5436.0000071 CE Database subject headings: Traffic speed: Estimation; Kalman filters; Traffic management; Intelligent transportation systems; Traffic congestion.

Because of the premature failure of in-service soft-body armor containing the ballistic fiber poly[(benzo-[1,2-d: 5,4-d']-benzoxazole-2,6-diyl)-l,4-phenylene] (PBO), the Office of Law Enforcement Standards (OLES) at the National Institute of Standards and Technology (NIST) initiated a research program to investigate the reasons for this failure and to develop testing methodologies and protocols to ensure that these types of failures do not reoccur. In a report that focused on the stability of the benzoxazole ring that is characteristic of PBO fibers, Holmes, G. A.; Rice, K.; Snyder, C. R. J. Mater. Sci. 2006, 41, 4105-4116, showed that the benzoxazole ring was susceptible to hydrolytic degradation under acid conditions. Because of the processing conditions for the fibers, it is suspected by many researchers that residual phosphoric acid may cause degradation of the benzoxazole ring resulting in a reduction of ballistic performance. Prior to this work, no definitive data have indicated the presence of phosphoric acid since the residual phosphorus is not easily extracted and the processed fibers are known to incorporate phosphorus containing processing aids. Methods to efficiently extract phosphorus from PBO are described in lids article. Further, characterization determined flint the majority of the extractable phosphorus in PBO was attributed to the octyldecyl phosphate processing aid with some phosphoric acid being detected. Analysis by matrix assisted laser desorption ionization of model PBO oligomers indicates that the nonextractable phosphorus is attached to the PBO polymer chain as a monoaryl phosphate ester. The response of model aryl phosphates to NaOH exposure indicates that monoaryl phosphate ester is stable to NaOH washes used in the manufacturing process to neutralize the phosphoric acid reaction medium and to extract residual phosphorus impurities. 10.1021/ac901602x

A capillary electrophoresis coupled with electrochemiluminescent detection system (CE-ECL) was developed for the detection of polymerase chain reaction (PCR) amplicons. The ECL luminophore, tris(1,10-phenanthroline) ruthenium(II) (Ru[(phen).sub.3.sup.2+]), was labeled to the PCR primers before amplification. Ru[(phen).sub.3.sup.2+] was then introduced to PCR amplicons by PCR amplification. Eventually, the PCR amplicons were separated and detected by the homemade CE-ECL system. The detection of a typical genetically modified organism (GMO), Roundup Ready Soy (RRS), was shown as an example to demonstrate the reliability of the proposed approach. Four pairs of primers were amplified by multiple PCR (MPCR) simultaneously, three of which were targeted on the specific sequence of exogenous genes of RRS, and another was targeted on the endogenous reference gene of soybean. Both the conditions for PCR amplification and CE-ECL separation and detection were investigated in detail. Results showed that, under the optimal conditions, the proposed method can accurately identifying RRS. The corresponding limit of detection (LOD) was below 0.01% with 35 PCR cycles. 10.1021/ac901510s

Melanoma is the deadliest form of skin cancer and has the fastest growth rate of all cancer types. Proper staging of melanoma is required for clinical management. One method of staging melanoma is performed by taking a sentinel node biopsy, in which the first node in the lymphatic drainage path of the primary lesion is removed and tested for the presence of melanoma cells. Current standard of care typically involves taking fewer than ten histologic sections of the node out of the hundreds of possible sections available in the tissue. We have developed a photoacoustic method that probes the entire intact node. We acquired a lymph node from a healthy canine subject. We cultured a malignant human melanoma cell line HS 936. Approximately 1 X [10.sup.6] cells were separated and injected into the lymph node. We also had a healthy lymph node in which no melanoma cells were implanted. We used a tunable laser system set at 532 nm to irradiate the lymph nodes. Three piezoelectric acoustic detectors were positioned near the lymph node to detect photoacoustic pulses generated within the lymph nodes. We also acquired lymph nodes from pigs and repeated the experiments with increased amplification and improved sensors. We detected photoacoustic responses from a lymph node with as few as 500 melanoma cells injected into the tissue, while normal lymph nodes showed no response. Photoacoustic generation can be used to detect melanoma micrometastasis in sentinel lymph nodes. This detection can be used to guide further histologic study of the node, increasing the accuracy of the sentinel lymph node biopsy. [DOI: 10.1115/1.3169247]

This paper aims to provide reliable indications of driver drowsiness based on the characteristics of driver-vehicle interaction. A test bed was built under a simulated driving environment, and a total of 12 subjects participated in two experiment sessions requiring different levels of sleep (partial sleep-deprivation versus no sleep-deprivation) before the experiment. The performance of the subjects was analyzed in a series of stimulus-response and routine driving tasks, which revealed the performance differences of drivers under different sleep-deprivation levels. The experiments further demonstrated that sleep deprivation had greater effect on rule-based than on skill-based cognitive functions: when drivers were sleep-deprived, their performance of responding to unexpected disturbances degraded, while they were robust enough to continue the routine driving tasks such as lane tracking, vehicle following, and lane changing. In addition, we presented both qualitative and quantitative guidelines for designing drowsy-driver detection systems in a probabilistic framework based on the paradigm of Bayesian networks. Temporal aspects of drowsiness and individual differences of subjects were addressed in the framework. Index Terms--Bayesian networks (BNs), camouflage, drowsy driving, sleep deprivation, stimulus-response tasks, tracking tasks.

A system for drug detection using X-ray diffraction is currently being developed by the DILAX collaboration. A simulation program for modelling the response of an energy-dispersive X-ray diffraction system has been developed, with the two-fold aim of selecting possible configurations prior to experimental tests and of generating data for statistical models for prediction of drug content. Simulated data showed a good agreement with experimental results. The data showed that the main factor affecting the shape of the diffraction pattern is the thickness of the sample. Scatter angle and detector energy resolution have a smaller effect on the diffraction pattern. This suggests that cheaper, room-temperature detectors can be used for a drug detection system without any loss in sensitivity and specificity. Index Terms--Nondestructive testing, X-ray imaging, diffraction, geometric modelling.

We present a 16-channel self triggered readout chip for simultaneous time and energy measurement, suitable for a wide range of applications. All circuit elements required for detector readout are integrated on the chip. A fast, low-noise discriminator detects hits at the differential inputs. The events are time stamped with an electronic resolution of 15 ps (single channel rms). The timing range is virtually infinite by means of a coarse counter and an overflow indicator. In parallel to the time stamping of the discriminated input signal, the analog input is integrated during a programmable time window and digitized with 8-bit integral resolution. Readout is achieved through a simple serial protocol. Several chips can be synchronized by means of a built in PLL circuit locking to a common reference dock. The 3 x 3 [mm.sup.2] chip has been fabricated in 0.18 [micro]m technology, employing a differential logic for all crucial parts. Possible applications of this ASIC are in the fields of high energy physics experiments, medical imaging, range finding, georadar and others. Index Terms--Application specific integrated circuits, front-end electronics, time to digital converters.

A detector of targets behind walls and in enclosed structures is presented. The detector is applied to through-the-wall radar images obtained by wideband delay and sum beamforming. We consider the detection problem using single- and multiple-view imaging. The statistics of noise, clutter, and target images are examined and formulated using sample scenes. The effects of wall parameter errors on the image statistics are shown. An iterative detection scheme, which adapts itself to the image statistics, is presented. The proposed detection schemes are evaluated using real data. Index Terms--Detection theory, radar imaging, through the wall (TTW).

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2008.10.025 Byline: Ren C. Luo (a), Tung Y. Lin (b), Kuo L. Su (c) Abstract: Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. The most importance role of the intelligent building is the security system. We develop a multi sensor-based intelligent security robot (ISR) that is widely employed in intelligent buildings. The intelligent security robot can detect abnormal and dangerous situations and notify users. The robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. The function of the ISR contains six parts. There is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. We develop a multi sensor-based sensor system in the ISR. We use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. There is an adaptive fusion method, a rule based method, and a statistical signal method. We demonstrate the remote supervisory system to control the ISR using a direct control mode and a behavior control mode. We think that the man-machine interface in a security robot system must have mobility and convenience. Therefore, we use a touch screen to display the system state, and design a general user interface (GUI) to service the user and visitors. The user can remotely control the appliance using a cell phone through a GSM modem, too. The appliance module can feedback reaction results to the user through a cell phone. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. In intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of the detection result to the user using a GSM modem for a fire event or intruder, and transmits the detection result to a client computer through the internet. Author Affiliation: (a) Intelligent Robotic & Automation Laboratory, Department of Electrical Engineering, National Taiwan University, 1, Sec. 4, Roosevelt Road, Taipei 106, Taiwan, ROC (b) Intelligent Automation Laboratory, Department of Electrical Engineering, National Chung Cheng University, 168 University Road, Ming-Hsiung, Chia-Yi, 621, Taiwan, ROC (c) Department of Electrical Engineering, National Yunlin University of Science & Technology, 123, Sec. 3, University Road, Touliu, Yunlin, 640, Taiwan, ROC

Most existing video-based target detection systems employ state-space models to keep track of an explicit number of individual targets. We introduce a framework for enhancing target detection in video by applying probabilistic models to the soft information in correlation outputs before threshoiding. We show how to efficiently compute arrays of posterior target probabilities for every position in the scene conditioned on all current and past frames of a video sequence. These arrays can then be thresholded in the typical manner to yield more reliable target detections. Because the framework avoids the formation of explicit tracks, it is well suited for handling scenes with unknown numbers of targets at unknown positions. Simulation results on forward-looking infrared (FLIR) video sequences show that our proposed framework can significantly reduce the false-alarm rate of a bank of correlation filters while requiring only a marginal increase in computation.

This paper deals with a new synthetic aperture radar (SAR) Processor based on a subspace detector designed for man-made target (MMT) detection. As MMTs are more accurately decribed by a set of canonical elements than with isotropic points, we develop a new algorithm which aims at using new models, instead of the isotropic point model commonly used in SAR processors. A subspace detector matched to canonical elements is included in the SAR processing. The implementation and the optimization of subspace detector SAR (SDSAR) algorithm is described. Simple examples of MMT detection in simulations and real data with a target hidden in a forest show the power of our approach. The SDSAR algorithm is shown to be the first robust and tractable algorithm relying on realistic scattering assumptions about the target.

Byline: Christa E. Pereira (Center for Advanced Research in Physical Sciences, Department of Physics Fatima Mata National College, Kollam 691 001, Kerala, India); V.K. Vaidyan (Center for Advanced Research in [...]

The aim of this paper is to infer partial discharge (PD) detection limits in extruded cables as a function of the distance between PD source and detection point. The investigation is carried out for different types of detectors, from IEC 60270-compliant to ultra-wide bandwidth systems. For this purpose, a medium voltage cable has been modeled as a transmission line with frequency-dependent parameters accounting for skin effect, dielectric and semicon characteristics. Pulse propagation through the cable has been predicted for very long distances. Different filters have been used to simulate different detectors, emphasizing the behavior of these systems, particularly the features of sensitivity, noise rejection, PD source separation and PD source localization. Index Terms--Partial discharges, power cables, propagation, attenuation constant, semiconductive layers, IEC 60270, diagnostics, asset management.

The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classification. In this paper, we present novel methods for automatic object detection in high-resolution images by combining spectral information with structural information exploited by using image segmentation. The proposed segmentation algorithm uses morphological operations applied to individual spectral bands using structuring elements in increasing sizes. These operations produce a set of connected components forming a hierarchy of segments for each band. A generic algorithm is designed to select meaningful segments that maximize a measure consisting of spectral homogeneity and neighborhood connectivity. Given the observation that different structures appear more clearly at different scales in different spectral bands, we describe a new algorithm for unsupervised grouping of candidate segments belonging to multiple hierarchical segmentations to find coherent sets of segments that correspond to actual objects. The segments are modeled by using their spectral and textural content, and the grouping problem is solved by using the probabilistic latent semantic analysis algorithm that builds object models by learning the object-conditional probability distributions. The automatic labeling of a segment is done by computing the similarity of its feature distribution to the distribution of the learned object models using the Kullback--Leibler divergence. The performances of the unsupervised segmentation and object detection algorithms are evaluated qualitatively and quantitatively using three different data sets with comparative experiments, and the results show that the proposed methods are able to automatically detect, group, and label segments belonging to the same object classes. Index Terms--Hierarchical segmentation, image segmentation, mathematical morphology, object-based analysis, unsupervised object detection.

Voice over Internet protocol (VoIP) flooding detection system (vFDS) is an online statistical anomaly detection framework for generating alerts based on abnormal variations in a selected hybrid collection of traffic flows. Findings reveal that vFDS is fast and accurate in detecting flooding attacks.

Particle impact noise detection (PIND) is a reliable screening technique specified by MIL-STD-883E. But MIL-STD-883E gives some test conditions which are not always appropriate. The test conditions of PIND are derived here based on dynamics. The upper limit frequency expression is obtained by a transforming equation. How vibration acceleration, vibration frequency, recovery coefficient, particle mass, and cavity height influence the particle's output energy is discussed. Moreover, the applicable range of test conditions of MIL-STD-883E are indicated and the best vibration frequency is derived by analyzing the relationship between the output power of vibrator and the particle's output energy. Some experiments are given.

A generalized likelihood ratio test (GLRT) is derived for adaptive detection of range and Doppler-distributed targets. The clutter is modeled as a spherically invariant random process (SIRP) and its texture component is range dependent (heterogeneous clutter). We suppose here that the speckle component covariance matrix is known or estimated thanks to a secondary data set. Thus, unknown parameters to be estimated are local texture values, the complex amplitudes and Doppler frequencies of all scattering centers. To do so, we use superresolution methods. The proposed detector assumes a priori knowledge on the spatial distribution of the target and has the precious property of having a constant false alarm rate (CFAR) with the assumption of a known speckle covariance matrix or by the use of frequency agility.

The focus of this paper is the investigation of a new dynode-timing technique optimized for PET block detectors. This method allows utilization of dynode signals from single but especially multiple photo-multiplier tubes (PMTs), operated with negative high-voltage. The technique will provide an event-timing trigger without deteriorating the anode signal. A printed circuit board has been developed and built for this investigation. Benchmark measurements have been performed, comparing timing of the anode signal with timing of the inverted last-dynode signal and timing of the dynode signal extracted via a newly developed LVPECL-logic based board. Timing measurements were performed with plastic as well as LSO scintillators. From single PMT measurements we find a 30 ps improvement with the dynode-timing method compared to the standard anode timing with two Photonis XP2020Q PMTs with LSO (10 mm x 10 mm x 10 mm). For a quad-PMT block detector, assembled of four Hamamatsu R9800 with a Hi-Rez block, the timing-resolution improves ~10%, by 43 ps compared to the standard anode timing. Index Terms--Detectors, dynode-timing, high resolution, positron emission tomography (PET), small animal, SPECT.

1. Introduction Integrating spheres (IS) have been used extensively for measuring optical properties of surfaces, films and light sources. The light from a source placed at the center of the […]

The joint successive interference cancellation technique (JSIC) is capable of jointly detecting consecutive users in an ordered set. Results suggest that the proposed JSIC is capable of achieving higher performance with an increase in complexity.

We propose a blind user identification detection (UID) scheme based on linear prediction algorithm for asynchronous direct-sequence code-division multiple-access systems over multipath fading channels. Numerical results show that both the false alarm rate and bit error rate of the proposed algorithm are better than those of the existing subspace-based UID algorithms. Index Terms--Code-division multiple access (CDMA), decorrelating detector, linear prediction (LP), multipath fading channel, user identification detection (UID).

A position sensitive detecter (PSD) has been used to determine the diameter of cylindrical pins based on the shift in a laser beam's centroid. The centroid of the light beam is defined here as the weighted average of position by the local intensity. A shift can be observed in the centroid of an otherwise axially symmetric light beam, which is partially obstructed. Additionally, the maximum shift in the centroid is a unique function of the obstructing cylinder diameter. Thus to determine the cylinder diameter, one only needs to detect this maximum shift as the cylinder is swept across the beam. OCIS codes: 120.0120, 040.5160.