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As section average velocity that is one of the most important traffic flow parameters has a wide range of sources of data, different sources of data vary in standards, advantages and disadvantages. Single-detect equipment can't meet the needs of multi-purpose and different environments. What's more, under certain conditions, the detector performance is defective, and it can't get rich and high-quality...
This paper analyzes the parameter identification of the macroscopic traffic flow model METANET. In previous papers [1] [2], this calibration has been done by minimizing numerically the difference between the data and the prediction of the model. Results indicate that this optimization usually falls in quite suboptimal local minima, especially when there are sensors only available in some segments...
This paper presents a method to improve the mispronunciation detection performance for low-resource acoustic model. The 1h speech data is randomly selected from CU-CHLOE to imitate the low-resource non-native English situation. The Tandem feature derived from articulatory based Multi-Layer Perception (MLP) is employed to replace the traditional spectral feature (e.g. PLP). Further, motivated by similar...
We report on our experience with model-based testing using SpecExplorer within the Flat X-Ray Detection (FXD) Department of Philips Healthcare. Our initial experiments showed a practical obstacle in combining traditional functional testing techniques with model-based testing using SpecExplorer. We overcome this obstacle by specifying the constraints on our data domain in a spreadsheet and interfacing...
Channel estimation is a crucial task for the overall communication performance of a wireless receiver. Compared to traditional approaches the estimation of the wireless channel can be improved by using iterative estimation with feedback from other receiver components, however the VLSI implementation of such iterative channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency...
Channel estimation is a crucial task for the overall communication performance of a wireless receiver. Compared to traditional approaches the estimation of the wireless channel can be improved by using iterative estimation with feedback from other receiver components, however the VLSI implementation of such iterative channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency...
The paper presents IntelliFusion, an algorithm that fuses inductive loop detector data with real-time vehicle probe data obtained from Connected Vehicles to enhance back of the queue estimates. The work also presents an evaluation of the data fusion algorithm using datasets produced by eTEXAS, a microscopic traffic simulation model for signalized intersections. Results of the evaluation show queue...
Congestion estimation for arterial roads has become an emerging research topic in the US while freeway congestion has already been widely studied. Considering the fact that more than 40 percent of US vehicle traveled miles are on the arterial roads, how to cost-effectively monitor and estimate the arterial congestion levels using data from existing ITS facilities is highly demanded by government agencies...
Real-time estimations of current and future traffic states are an essential part of traffic management and traffic information systems. Within the Mobile Millennium project considerable effort has been invested in the research and development of a real-time estimation system that can fuse several sources of data collected in California. During the past year this system has been adapted to also handle...
In this paper we present a visual person tracking-by-detection system based on on-line-learned instance-specific information along with the kinematic relation of measurements provided by a generic person-category detector. The proposed system is able to initialize tracks on individual persons and start learning their appearance even in crowded situations and does not require that a person enters the...
Travel time information is a fundamental component in Advanced Traveler Information System. In this paper, we propose a short-term travel time estimation and prediction framework for long freeway corridor, considering measurements from vehicle detectors (VD) and floating car data (FCD). The modeling approach is based on a modified Nearest-Neighborhood (NN) model with threshold and a regression model...
As the field of code clone research grows, the continuing problem of interoperability between code clone detection and analysis tools grows with it. As a step toward solving this problem, this paper presents a draft proposal for a generic model of code clone detection results. Using an online wiki, we hope to generate discussion and solidify a shared understanding of the core concepts of the problem...
This paper presents a time travel estimation model based on a decision tree. The proposed model was tested on the most widely used arterial in Prague and also in the Czech Republic. This road section has many unmeasured inputs and outputs and with regards to only two detectors within a section it is difficult to estimate the travel time. A temporary installation of ALPR system is used for training...
This paper presents a new adaptive radar signal processing technique for dismount detection using Synthetic Aperture Radar (SAR). The new approach uses the complex nature of the Doppler response scattering from the dismounts rotary motion to modify the conventional Space-Time Adaptive Processing (STAP). This is used for dismount detection wherein resolution is dictated by the sensor system platform...
Advanced devices for embedded and ambient applications represent one of the most compelling classes of electronic systems, but they also impose more severe constraints on system resources than ever before. Although platform non-idealities have always posed a fundamental limitation, the overheads of conventional margining are now reaching intolerable levels. We describe an alternate approach to hardware...
The generalized coherence (GC) estimate is a well studied statistic for detection of a common but unknown signal on several noisy channels. In this paper, it is shown that the GC detector arises naturally from a Bayesian perspective. Specifically, it is derived as a test of the hypothesis that the signals in the channels are independent Gaussian processes against the hypothesis that the processes...
This paper examines a new problem in large scale stream data: abnormality detection which is localized to a data segmentation process. Unlike traditional abnormality detection methods which typically build one unified model across data stream, we propose that building multiple detection models focused on different coherent sections of the video stream would result in better detection performance....
We propose a novel approach for view-invariant vehicle detection in traffic surveillance videos. Instead of building a monolithic object detector that can model all possible viewpoints, we learn a large array of efficient view-specific models corresponding to different camera views (source domains). When presented with an unseen viewpoint (target domain), closely related models in the source domain...
This paper describes an improved speaker diarization system for multiple distance microphone (MDM) meeting conversations. First, the new system includes a modified speech activity detector (SAD). Second, it adopts the new spectral features based on equivalent rectangular bandwidth (ERB) or bark scale, which are compared with the traditional Mel Frequency Cepstral Coefficients (MFCC) features. Third,...
To improve the accuracy of arterial mean speed estimation through data fusion in road traffic, this paper presented a speed estimation method based on space-matching fusion model. In the method, an urban road model is proposed, which divided road into several equal length segments. The loop detector data is matched to each segment by the adjusted coefficient. Because of the strongly complementary...
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