In conventional signature analysis, faulty units are identified by mismatch between the actual and reference signatures. The amount of reference signatures can be quite large for a complex system that requires high te...
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In conventional signature analysis, faulty units are identified by mismatch between the actual and reference signatures. The amount of reference signatures can be quite large for a complex system that requires high testing resolution. This complicates the diagnosis procedure. We show how under certain restrictions this amount can be reduced, preserving the diagnosis resolution and the aliasing rate. We construct a signature analyzer that is capable of locating faulty units. If the analyzer is implemented in the external automated test equipment, its throughput requirements can be diminished.
Survivability and reliability are critical for the operation of shipboard power system both in normal and damage conditions. This paper presents a novel dynamic reconfiguration approach for shipboard power system by u...
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Survivability and reliability are critical for the operation of shipboard power system both in normal and damage conditions. This paper presents a novel dynamic reconfiguration approach for shipboard power system by using multi-agent system. With the similar topology of the shipboard power system, the multi-agent system is generalized to constraint satisfaction problem (CSP). The environment- reactive rules-agents (ERA) approach, which is multi-agent oriented, is used to support the organization formation behavior in dynamic reconfiguration. The effectiveness of the proposed approach is illustrated by test results in a reduced shipboard power system.
The problem of vehicle detection and segmentation in outdoor scenes is tackled. Vehicle shadows pose problems in vehicle segmentation step. In this paper, it is proposed to employ temporal edge density information as ...
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The problem of vehicle detection and segmentation in outdoor scenes is tackled. Vehicle shadows pose problems in vehicle segmentation step. In this paper, it is proposed to employ temporal edge density information as prior knowledge to distinguish moving vehicle from moving shadow and background in a traffic surveillance system. Experimental results showed good moving vehicle segmentation performance. The proposed approach is currently limited to free-flowing traffic scenes.
In many cases, protein mass-spectrometry data are imbalanced, i.e. the number of positive examples is much less than that of negative ones, which generally degrade the performance of classifiers used for protein recog...
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In many cases, protein mass-spectrometry data are imbalanced, i.e. the number of positive examples is much less than that of negative ones, which generally degrade the performance of classifiers used for protein recognition. Despite its importance, few works have been conducted to handle this problem. In this paper, we present a new method that utilizes the EasyEnsemble algorithm to cope with the imbalance problem in mass-spectrometry data. Furthermore, two feature selection algorithms, namely PREE (Prediction Risk based feature selection for EasyEnsemble) and PRIEE (Prediction Risk based feature selection for Individuals of EasyEnsemble), are proposed to select informative features and improve the performance of the EasyEnsemble classifier. Experimental results on three mass spectra data sets demonstrate that the proposed methods outperform two existing filter feature selection methods, which prove the effectiveness of the proposed methods.
This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorit...
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This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. The second one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle models are computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithm fuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.
This research studies the proof of concept to road traffic estimation based on the position and velocity of cellular phones. The positioning technique, received signal strength method, was applied to obtain road traff...
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This research studies the proof of concept to road traffic estimation based on the position and velocity of cellular phones. The positioning technique, received signal strength method, was applied to obtain road traffic data. The two algorithms: Linear interpolation of position from signal strength and centroid of signal strength were implemented to identify the positions and velocity of a mobile phone in cars. Successfully estimated results, position and speed, showed that both of two methods have the potential to estimate traffic congestion while the first method is more efficient than another. According to the first method, it yielded an average error of 190.8 m, while the velocity estimation yielded an average error of 10.38 km/hr. The errors from another are 195.29 m and 10.39 km/hr respectively.
In this paper, a class of hybrid impulsive systems with time delays and stochastic effects are considered. We obtain some criteria on the global exponential stability in mean square for the impulsive stochastic delaye...
In this paper, a class of hybrid impulsive systems with time delays and stochastic effects are considered. We obtain some criteria on the global exponential stability in mean square for the impulsive stochastic delayed systems. To do this, differential inequalities and ℒ-operator inequalities are developed. An example is given to illustrate the effectiveness of our results.
We propose a system that can record driving events and detect unsafe driving behaviors. Three sensors, an engine control unit (ECU) reader, a 3-axis accelerometer, and a camera are used, in which they represent the ca...
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We propose a system that can record driving events and detect unsafe driving behaviors. Three sensors, an engine control unit (ECU) reader, a 3-axis accelerometer, and a camera are used, in which they represent the car, the passenger, and the driverpsilas perspective. Our system combines data from these three sensors with a fuzzy inference system to identify an event of hazardous driving. The output of the system is the driving risk level ranging from 1 to 3, where 1 is the safest. The output of the system was verified by comparison with a questionnaire from three passengers in a test run experiment.
Using induced L 2 -norm minimization, a robust controller was developed for insulin delivery in Type I diabetic patients. The high-complexity nonlinear diabetic patient Sorensen-model [1] was considered. LPV (Linear P...
Using induced L 2 -norm minimization, a robust controller was developed for insulin delivery in Type I diabetic patients. The high-complexity nonlinear diabetic patient Sorensen-model [1] was considered. LPV (Linear Parameter Varying) methodology was used to develop open loop model and robust controller. Considering the normoglycemic set point (81.1 mg/dL), a polytopic set was created over the physiologic boundaries of the glucose-insulin interaction of the Sorensen-model. In this way, LPV model formalism was defined. The robust control was developed considering input and output multiplicative uncertainties with other weighting functions.
We have addressed the improvement of production efficiency and the review of business process for an automotive parts supplier, and the goal of this study is the development of production management software. This pap...
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We have addressed the improvement of production efficiency and the review of business process for an automotive parts supplier, and the goal of this study is the development of production management software. This paper describes the business result analysis in printing process and a formulation of the tacit procedure by observing worker's empirical rule to develop the knowledge-based scheduling software. The whole of business processes are clarified by our previous researches, and the scheduling problem of printing process has been mainly discussed. Previously the printing process has been improved only by theoretical aspect, however it cannot flexibly respond to the change of production conditions such as the dispersion of order, the interrupt of urgent task, and the inventory quantity of parts in spite of the actual field can handle these. Therefore this paper regards that the technical know-how of tacit knowledge in the actual printing field is absolutely necessary factor in response to the change of production conditions, and a formulation designed to the minimization of setup operation are expressed.
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