Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fraction of time instants of significantly mis-...
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Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fraction of time instants of significantly mis-matched sensor readings exceed the given percentage-threshold. Discovering flow anomalies (FA) is an important problem in environmental flow monitoring networks and early warning detection systems for water quality problems. However, mining FAs is computationally expensive because of the large (potentially infinite) number of time instants of measurement and potentially long delays due to stagnant (e.g. lakes) or slow moving (e.g. wetland) water bodies between consecutive sensors. Traditional outlier detection methods (e.g. t-test) are suited for detecting transient FAs (i.e., time instants of significant mis-matches across consecutive sensors) and cannot detect persistent FAs (i.e., long variable time-windows with a high fraction of time instant transient FAs) due to a lack of a pre-defined window size. In contrast, we propose a Smart Window Enumeration and Evaluation of persistence-Thresholds (SWEET) method to efficiently explore the search space of all possible window lengths. Computation overhead is brought down significantly by restricting the start and end points of a window to coincide with transient FAs, using a smart counter and efficient pruning techniques. Experimental evaluation using a real dataset shows our proposed approach outperforms Nainodotve alternatives.
In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna...
In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna. As a prototype system, a measurement stage (a circle 240mm in diameter) with 36 antennas that placed in each 10 degrees was developed. Two transmitter antennas are settled in a right angle on the stage as the target object, and the position and the rotation angle is estimated by measuring efficiency of the radio communication of each 36 antennas. The experimental result revealed that even when the estimated location is not so accurate (about a 30 mm error), the rotation angle is accurately estimated (about 2.33 degree error on average). The result suggests that the proposed method will be useful for estimating the location and the direction of an object.
In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle...
In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle. Three electrodes made from conductive cloth were adhered to the handle. A method detecting heart-rate from the obtained electrocardiogram was also proposed. To assess the applicability of the proposed system, a simple experiment was performed. The experiment was performed in four conditions of road surfaces; lawn, asphalt, a tiled, and an uneven road. Experimental result suggests that the proposed system can be useful for obtaining R waves while riding a bicycle.
Nanoscale porous silicon waveguides, both on silicon substrates and free-standing membranes, are explored for biosensing applications. Measured detection limits in the nanomolar range are reported for DNA sensing. ...
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This paper presents the design and mechatronics implementation of a human stress detection system (HSDS) using a biomechanics approach. A simple, compact and easy to use system is developed and built on a 2-layer PCB....
This paper presents the design and mechatronics implementation of a human stress detection system (HSDS) using a biomechanics approach. A simple, compact and easy to use system is developed and built on a 2-layer PCB. It consists of two transducers, an LCD display and a micro-controller chip along with their respective interfacing circuits. After characterizing the two transducers, an algorithm was developed based on the measurements to classify the human stress condition. A simple classification rule that was adopted revealed that the system can detect 78% of the stressed examinees. The overall system success rate in identifying one of three states (relaxed, half stressed and stressed) was 60%. One major application for HSDS could be in the automotive industry were the driver condition is constantly monitored, and if a stress state is detected, the driver can be notified to stop the car and relax.
The rapid growth of the biomedical literature and genomic information presents a major challenge for determining the functional relationships among genes. In this study, we develop a Web-based bioinformatics software ...
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The rapid growth of the biomedical literature and genomic information presents a major challenge for determining the functional relationships among genes. In this study, we develop a Web-based bioinformatics software environment called FAUN or feature annotation using nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity and parameterization of NMF for processing gene sets are discussed. We tested FAUN on three manually constructed gene document collections, and then used it to analyze several microarray-derived gene sets obtained from studies of the developing cerebellum in normal and mutant mice. FAUN provides utilities for collaborative knowledge discovery and identification of new gene relationships from text streams and repositories (e.g., MEDLINE). It is particularly useful for the validation and analysis of gene associations suggested by microarray experimentation.
In this paper, we present a parallelization of a filtering algorithm related to non-linear anisotropic diffusion, used to enhance the performance of an application in a parallel distributed system. The anisotropic dif...
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ISBN:
(纸本)9780769532578
In this paper, we present a parallelization of a filtering algorithm related to non-linear anisotropic diffusion, used to enhance the performance of an application in a parallel distributed system. The anisotropic diffusion is a well-established technique for image enhancement by means of diffusivity functions, which act as border attenuators. However, it requires a high computational cost when a large amount of data is used. The proposed implementation was parallelized considering both point-to-point and collective communications, adopting the MPI paradigm. Results from both approaches indicate that the proposed algorithm has reached interesting levels of performance (81% and 93% of efficiency, respectively) when compared to the execution of one process in a single computer node. In addition, our results indicate an enhancement of around 21% utilizing the collective communication strategy when compared to point-to-point communication.
This work presents a method that provides organizations and their project managers with a better understanding of the implications of the risks that software projects are subjected to. The method, which is based upon ...
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ISBN:
(纸本)9781424421916
This work presents a method that provides organizations and their project managers with a better understanding of the implications of the risks that software projects are subjected to. The method, which is based upon a novel approach to cluster analysis, generates a set of business rules indicating how risk factors may influence project performance. These rules are easy to read and understand, making it easier for managers to identify what needs to be done and when it needs to be done, before the worst happens.
Intrusion detection systems continuously watch the activity on a network or computer, looking for attack and intrusion evidences. However, host-based intrusion detectors are particularly vulnerable, as they can be dis...
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Intrusion detection systems continuously watch the activity on a network or computer, looking for attack and intrusion evidences. However, host-based intrusion detectors are particularly vulnerable, as they can be disabled or tampered by successful intruders. This work proposes and implements an architecture model aimed to protect host-based intrusion detectors, through the application of the virtual machine concept. Virtual machine environments are becoming an interesting alternative for several computing systems due to their advantages in terms of cost and portability. The architecture proposed here makes use of the execution spaces separation provided by a virtual machine monitor, in order to separate the intrusion detection system from the system under monitoring. As a consequence, the intrusion detector becomes invisible and inaccessible to intruders. The prototype implementation and the tests performed show the viability of this solution. (c) 2006 Elsevier B.V. All rights reserved.
Emerging 64 bitOSpsilas supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages e...
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Emerging 64 bitOSpsilas supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages efficiently, especially in a dedicated cluster which has a high-speed network such as 10 GbE and Infiniband. In this paper, we propose the distributed large memory system (DLM), which provides very large virtual memory by using remote memory distributed over the nodes in a cluster. The performance of DLM programs using remote memory is compared to ordinary programs using local memory. The results of STREAM, NPB and Himeno benchmarks show that the DLM achieves better performance than other remote paging schemes using a block swap device to access remote memory. In addition to performance, DLM offers the advantages of easy availability and high portability, because it is a user-level software without the need for special hardware. To obtain high performance, the DLM can tune its parameters independently from kernel swap parameters. We also found that DLMpsilas independence of kernel swapping provides more stable behavior.
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