Mode-dependent templates and scan order for H.264/AVC-based intra lossless coding.

Science.gov (United States)

Gu, Zhouye; Lin, Weisi; Lee, Bu-Sung; Lau, Chiew Tong; Sun, Ming-Ting

2012-09-01

In H.264/advanced video coding (AVC), lossless coding and lossy coding share the same entropy coding module. However, the entropy coders in the H.264/AVC standard were original designed for lossy video coding and do not yield adequate performance for lossless video coding. In this paper, we analyze the problem with the current lossless coding scheme and propose a mode-dependent template (MD-template) based method for intra lossless coding. By exploring the statistical redundancy of the prediction residual in the H.264/AVC intra prediction modes, more zero coefficients are generated. By designing a new scan order for each MD-template, the scanned coefficients sequence fits the H.264/AVC entropy coders better. A fast implementation algorithm is also designed. With little computation increase, experimental results confirm that the proposed fast algorithm achieves about 7.2% bit saving compared with the current H.264/AVC fidelity range extensions high profile.

Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.

Science.gov (United States)

Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai

2011-01-01

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.

Wireless Magnetic Sensor Network for Road Traffic Monitoring and Vehicle Classification

Directory of Open Access Journals (Sweden)

Velisavljevic Vladan

2016-12-01

Full Text Available Efficiency of transportation of people and goods is playing a vital role in economic growth. A key component for enabling effective planning of transportation networks is the deployment and operation of autonomous monitoring and traffic analysis tools. For that reason, such systems have been developed to register and classify road traffic usage. In this paper, we propose a novel system for road traffic monitoring and classification based on highly energy efficient wireless magnetic sensor networks. We develop novel algorithms for vehicle speed and length estimation and vehicle classification that use multiple magnetic sensors. We also demonstrate that, using such a low-cost system with simplified installation and maintenance compared to current solutions, it is possible to achieve highly accurate estimation and a high rate of positive vehicle classification.

Automatic Voltage Control (AVC) of Danish Transmission System - Concept design

DEFF Research Database (Denmark)

Qin, Nan; Abildgaard, Hans; Lund, P.

2014-01-01

For more than 20 years it has been a consistent plan by all Danish governments to turn the Danish power production away from fossil fuels towards renewable energy. The result today is that 37% of the total Danish power consumption was covered by mainly wind energy in 2013 aiming at 50% by 2020......, objectives, constraints, algorithms for optimal power flow and some special functions in particular systems, which inspires the concept design of a Danish AVC system to address the future challenges of voltage control. In the concept, the Danish AVC design is based on a centralized control scheme. All...... the substation loses the telecommunications to the control center. RPCs will be integrated to the AVC system as normative regulators in the later stage. Distributed generation units can be organized as virtual power plants and participate in voltage control at transmission level. Energinet.dk as the Danish TSO...

Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.

Science.gov (United States)

Fischell, Erin M; Schmidt, Henrik

2015-12-01

One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7-9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834-875 (2010)].

Segmentation-driven compound document coding based on H.264/AVC-INTRA.

Science.gov (United States)

Zaghetto, Alexandre; de Queiroz, Ricardo L

2007-07-01

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.

Mitigation of voltage fluctuations with an Adaptive Var Compensator (AVC)

Energy Technology Data Exchange (ETDEWEB)

Chan, F [TransAlta Utilities Corp., Calgary, AB (Canada); Castanheira, A

1997-04-01

The installation of an Adaptive Var Compensator (AVC) to remedy a voltage flicker problem at the TIMEU sawmill in Fort Assiniboine, Alberta, was described. The TIMEU sawmill is a 980 kVA load at the end of a 25 kV feeder. Two older style J bar type saws, each driven by a 200 Hp motor, are used to operate the wood processing services. The sawing and chipping process resulted in the generation of significant voltage flicker on the 25 kV distribution system. The AVC provided cycle per cycle reactive compensation and voltage support; no further complaints of flicker were received.

Street-side vehicle detection, classification and change detection using mobile laser scanning data

Science.gov (United States)

Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

2016-04-01

Statistics on street-side car parks, e.g. occupancy rates, parked vehicle types, parking durations, are of great importance for urban planning and policy making. Related studies, e.g. vehicle detection and classification, mostly focus on static images or video. Whereas mobile laser scanning (MLS) systems are increasingly utilized for urban street environment perception due to their direct 3D information acquisition, high accuracy and movability. In this paper, we design a complete system for car park monitoring, including vehicle recognition, localization, classification and change detection, from laser scanning point clouds. The experimental data are acquired by an MLS system using high frequency laser scanner which scans the streets vertically along the system's moving trajectory. The point clouds are firstly classified as ground, building façade, and street objects which are then segmented using state-of-the-art methods. Each segment is treated as an object hypothesis, and its geometric features are extracted. Moreover, a deformable vehicle model is fitted to each object. By fitting an explicit model to the vehicle points, detailed information, such as precise position and orientation, can be obtained. The model parameters are also treated as vehicle features. Together with the geometric features, they are applied to a supervised learning procedure for vehicle or non-vehicle recognition. The classes of detected vehicles are also investigated. Whether vehicles have changed across two datasets acquired at different times is detected to estimate the durations. Here, vehicles are trained pair-wisely. Two same or different vehicles are paired up as training samples. As a result, the vehicle recognition, classification and change detection accuracies are 95.9%, 86.0% and 98.7%, respectively. Vehicle modelling improves not only the recognition rate, but also the localization precision compared to bounding boxes.

Fault classification method for the driving safety of electrified vehicles

Science.gov (United States)

Wanner, Daniel; Drugge, Lars; Stensson Trigell, Annika

2014-05-01

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.

Compression of computer generated phase-shifting hologram sequence using AVC and HEVC

Science.gov (United States)

Xing, Yafei; Pesquet-Popescu, Béatrice; Dufaux, Frederic

2013-09-01

With the capability of achieving twice the compression ratio of Advanced Video Coding (AVC) with similar reconstruction quality, High Efficiency Video Coding (HEVC) is expected to become the newleading technique of video coding. In order to reduce the storage and transmission burden of digital holograms, in this paper we propose to use HEVC for compressing the phase-shifting digital hologram sequences (PSDHS). By simulating phase-shifting digital holography (PSDH) interferometry, interference patterns between illuminated three dimensional( 3D) virtual objects and the stepwise phase changed reference wave are generated as digital holograms. The hologram sequences are obtained by the movement of the virtual objects and compressed by AVC and HEVC. The experimental results show that AVC and HEVC are efficient to compress PSDHS, with HEVC giving better performance. Good compression rate and reconstruction quality can be obtained with bitrate above 15000kbps.

An Unequal Secure Encryption Scheme for H.264/AVC Video Compression Standard

Science.gov (United States)

Fan, Yibo; Wang, Jidong; Ikenaga, Takeshi; Tsunoo, Yukiyasu; Goto, Satoshi

H.264/AVC is the newest video coding standard. There are many new features in it which can be easily used for video encryption. In this paper, we propose a new scheme to do video encryption for H.264/AVC video compression standard. We define Unequal Secure Encryption (USE) as an approach that applies different encryption schemes (with different security strength) to different parts of compressed video data. This USE scheme includes two parts: video data classification and unequal secure video data encryption. Firstly, we classify the video data into two partitions: Important data partition and unimportant data partition. Important data partition has small size with high secure protection, while unimportant data partition has large size with low secure protection. Secondly, we use AES as a block cipher to encrypt the important data partition and use LEX as a stream cipher to encrypt the unimportant data partition. AES is the most widely used symmetric cryptography which can ensure high security. LEX is a new stream cipher which is based on AES and its computational cost is much lower than AES. In this way, our scheme can achieve both high security and low computational cost. Besides the USE scheme, we propose a low cost design of hybrid AES/LEX encryption module. Our experimental results show that the computational cost of the USE scheme is low (about 25% of naive encryption at Level 0 with VEA used). The hardware cost for hybrid AES/LEX module is 4678 Gates and the AES encryption throughput is about 50Mbps.

Vehicle classification in WAMI imagery using deep network

Science.gov (United States)

Yi, Meng; Yang, Fan; Blasch, Erik; Sheaff, Carolyn; Liu, Kui; Chen, Genshe; Ling, Haibin

2016-05-01

Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our deep

Mining vehicle classifications from the Columbus Metropolitan Freeway Management System.

Science.gov (United States)

2015-01-01

Vehicle classification data are used in many transportation applications, including: pavement design, : environmental impact studies, traffic control, and traffic safety. Ohio has over 200 permanent count stations, : supplemented by many more short-t...

Efficient reversible data hiding in encrypted H.264/AVC videos

Science.gov (United States)

Xu, Dawen; Wang, Rangding

2014-09-01

Due to the security and privacy-preserving requirements for cloud data management, it is sometimes desired that video content is accessible in an encrypted form. Reversible data hiding in the encrypted domain is an emerging technology, as it can perform data hiding in encrypted videos without decryption, which preserves the confidentiality of the content. Furthermore, the original cover can be losslessly restored after decryption and data extraction. An efficient reversible data hiding scheme for encrypted H.264/AVC videos is proposed. During H.264/AVC encoding, the intraprediction mode, motion vector difference, and the sign bits of the residue coefficients are encrypted using a standard stream cipher. Then, the data-hider who does not know the original video content, may reversibly embed secret data into the encrypted H.264/AVC video by using a modified version of the histogram shifting technique. A scale factor is utilized for selecting the embedding zone, which is scalable for different capacity requirements. With an encrypted video containing hidden data, data extraction can be carried out either in the encrypted or decrypted domain. In addition, real reversibility is realized so that data extraction and video recovery are free of any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

Transcoding method from H.264/AVC to high efficiency video coding based on similarity of intraprediction, interprediction, and motion vector

Science.gov (United States)

Liu, Mei-Feng; Zhong, Guo-Yun; He, Xiao-Hai; Qing, Lin-Bo

2016-09-01

Currently, most video resources on line are encoded in the H.264/AVC format. More fluent video transmission can be obtained if these resources are encoded in the newest international video coding standard: high efficiency video coding (HEVC). In order to improve the video transmission and storage on line, a transcoding method from H.264/AVC to HEVC is proposed. In this transcoding algorithm, the coding information of intraprediction, interprediction, and motion vector (MV) in H.264/AVC video stream are used to accelerate the coding in HEVC. It is found through experiments that the region of interprediction in HEVC overlaps that in H.264/AVC. Therefore, the intraprediction for the region in HEVC, which is interpredicted in H.264/AVC, can be skipped to reduce coding complexity. Several macroblocks in H.264/AVC are combined into one PU in HEVC when the MV difference between two of the macroblocks in H.264/AVC is lower than a threshold. This method selects only one coding unit depth and one prediction unit (PU) mode to reduce the coding complexity. An MV interpolation method of combined PU in HEVC is proposed according to the areas and distances between the center of one macroblock in H.264/AVC and that of the PU in HEVC. The predicted MV accelerates the motion estimation for HEVC coding. The simulation results show that our proposed algorithm achieves significant coding time reduction with a little loss in bitrates distortion rate, compared to the existing transcoding algorithms and normal HEVC coding.

Vehicle Maneuver Detection with Accelerometer-Based Classification

Directory of Open Access Journals (Sweden)

Javier Cervantes-Villanueva

2016-09-01

Full Text Available In the mobile computing era, smartphones have become instrumental tools to develop innovative mobile context-aware systems. In that sense, their usage in the vehicular domain eases the development of novel and personal transportation solutions. In this frame, the present work introduces an innovative mechanism to perceive the current kinematic state of a vehicle on the basis of the accelerometer data from a smartphone mounted in the vehicle. Unlike previous proposals, the introduced architecture targets the computational limitations of such devices to carry out the detection process following an incremental approach. For its realization, we have evaluated different classification algorithms to act as agents within the architecture. Finally, our approach has been tested with a real-world dataset collected by means of the ad hoc mobile application developed.

FPSoC-Based Architecture for a Fast Motion Estimation Algorithm in H.264/AVC

Directory of Open Access Journals (Sweden)

Obianuju Ndili

2009-01-01

Full Text Available There is an increasing need for high quality video on low power, portable devices. Possible target applications range from entertainment and personal communications to security and health care. While H.264/AVC answers the need for high quality video at lower bit rates, it is significantly more complex than previous coding standards and thus results in greater power consumption in practical implementations. In particular, motion estimation (ME, in H.264/AVC consumes the largest power in an H.264/AVC encoder. It is therefore critical to speed-up integer ME in H.264/AVC via fast motion estimation (FME algorithms and hardware acceleration. In this paper, we present our hardware oriented modifications to a hybrid FME algorithm, our architecture based on the modified algorithm, and our implementation and prototype on a PowerPC-based Field Programmable System on Chip (FPSoC. Our results show that the modified hybrid FME algorithm on average, outperforms previous state-of-the-art FME algorithms, while its losses when compared with FSME, in terms of PSNR performance and computation time, are insignificant. We show that although our implementation platform is FPGA-based, our implementation results compare favourably with previous architectures implemented on ASICs. Finally we also show an improvement over some existing architectures implemented on FPGAs.

Classification Of Road Accidents From The Perspective Of Vehicle Safety Systems

Directory of Open Access Journals (Sweden)

Jirovský Václav

2015-11-01

Full Text Available Modern road accident investigation and database structures are focused on accident analysis and classification from the point of view of the accident itself. The presented article offers a new approach, which will describe the accident from the point of view of integrated safety vehicle systems. Seven main categories have been defined to specify the level of importance of automated system intervention. One of the proposed categories is a new approach to defining the collision probability of an ego-vehicle with another object. This approach focuses on determining a 2-D reaction space, which describes all possible positions of the vehicle or other moving object in the specified amount of time in the future. This is to be used for defining the probability of the vehicles interacting - when the intersection of two reaction spaces exists, an action has to be taken on the side of ego-vehicle. The currently used 1-D quantity of TTC (time-to-collision can be superseded by the new reaction space variable. Such new quantity, whose basic idea is described in the article, enables the option of counting not only with necessary braking time, but mitigation by changing direction is then easily feasible. Finally, transparent classification measures of a probable accident are proposed. Their application is highly effective not only during basic accident comparison, but also for an on-board safety system.

Mining vehicle classifications from the Columbus Metropolitan Freeway Management System : [summary].

Science.gov (United States)

2015-01-01

Vehicle classification data are used in many transportation applications, including: pavement design, : environmental impact studies, traffic control, and traffic safety. Ohio has over 200 permanent count : stations, supplemented by many more short-t...

Automatic Voltage Control (AVC) System under Uncertainty from Wind Power

DEFF Research Database (Denmark)

Qin, Nan; Abildgaard, Hans; Flynn, Damian

2016-01-01

An automatic voltage control (AVC) system maintains the voltage profile of a power system in an acceptable range and minimizes the operational cost by coordinating the regulation of controllable components. Typically, all of the parameters in the optimization problem are assumed to be certain...... and constant in the decision making process. However, for high shares of wind power, uncertainty in the decision process due to wind power variability may result in an infeasible AVC solution. This paper proposes a voltage control approach which considers the voltage uncertainty from wind power productions....... The proposed method improves the performance and the robustness of a scenario based approach by estimating the potential voltage variations due to fluctuating wind power production, and introduces a voltage margin to protect the decision against uncertainty for each scenario. The effectiveness of the proposed...

Video traffic characteristics of modern encoding standards: H.264/AVC with SVC and MVC extensions and H.265/HEVC.

Science.gov (United States)

Seeling, Patrick; Reisslein, Martin

2014-01-01

Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC.

Visual saliency in MPEG-4 AVC video stream

Science.gov (United States)

Ammar, M.; Mitrea, M.; Hasnaoui, M.; Le Callet, P.

2015-03-01

Visual saliency maps already proved their efficiency in a large variety of image/video communication application fields, covering from selective compression and channel coding to watermarking. Such saliency maps are generally based on different visual characteristics (like color, intensity, orientation, motion,…) computed from the pixel representation of the visual content. This paper resumes and extends our previous work devoted to the definition of a saliency map solely extracted from the MPEG-4 AVC stream syntax elements. The MPEG-4 AVC saliency map thus defined is a fusion of static and dynamic map. The static saliency map is in its turn a combination of intensity, color and orientation features maps. Despite the particular way in which all these elementary maps are computed, the fusion techniques allowing their combination plays a critical role in the final result and makes the object of the proposed study. A total of 48 fusion formulas (6 for combining static features and, for each of them, 8 to combine static to dynamic features) are investigated. The performances of the obtained maps are evaluated on a public database organized at IRCCyN, by computing two objective metrics: the Kullback-Leibler divergence and the area under curve.

Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors.

Science.gov (United States)

Lamas-Seco, José J; Castro, Paula M; Dapena, Adriana; Vazquez-Araujo, Francisco J

2015-10-26

Inductive Loop Detectors (ILDs) are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT) of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype.

An improved AVC strategy applied in distributed wind power system

Science.gov (United States)

Zhao, Y. N.; Liu, Q. H.; Song, S. Y.; Mao, W.

2016-08-01

Traditional AVC strategy is mainly used in wind farm and only concerns about grid connection point, which is not suitable for distributed wind power system. Therefore, this paper comes up with an improved AVC strategy applied in distributed wind power system. The strategy takes all nodes of distribution network into consideration and chooses the node having the most serious voltage deviation as control point to calculate the reactive power reference. In addition, distribution principles can be divided into two conditions: when wind generators access to network on single node, the reactive power reference is distributed according to reactive power capacity; when wind generators access to network on multi-node, the reference is distributed according to sensitivity. Simulation results show the correctness and reliability of the strategy. Compared with traditional control strategy, the strategy described in this paper can make full use of generators reactive power output ability according to the distribution network voltage condition and improve the distribution network voltage level effectively.

Vehicle Classification Using the Discrete Fourier Transform with Traffic Inductive Sensors

Directory of Open Access Journals (Sweden)

José J. Lamas-Seco

2015-10-01

Full Text Available Inductive Loop Detectors (ILDs are the most commonly used sensors in traffic management systems. This paper shows that some spectral features extracted from the Fourier Transform (FT of inductive signatures do not depend on the vehicle speed. Such a property is used to propose a novel method for vehicle classification based on only one signature acquired from a sensor single-loop, in contrast to standard methods using two sensor loops. Our proposal will be evaluated by means of real inductive signatures captured with our hardware prototype.

Adaptive deblocking and deringing of H.264/AVC video sequences

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Burini, Nino; Forchhammer, Søren

2013-01-01

We present a method to reduce blocking and ringing artifacts in H.264/AVC video sequences. For deblocking, the proposed method uses a quality measure of a block based coded image to find filtering modes. Based on filtering modes, the images are segmented to three classes and a specific deblocking...

The optimization of H.264/AVC baseline decoder on low-cost TriMedia DSP processor

Science.gov (United States)

Wang, Sung-Wen; Yang, Ya-Ting; Li, Chia-Ying; Tung, Yi-Shin; Wu, Ja-Ling

2004-11-01

The emerging video coding standard, H.264/AVC, exhibits the unprecedented coding performance. Comparing to traditional coders, e.g., MPEG-2 and MEPG-4 ASP, about half bitrate saving is shown in the official verification test. Such outstanding performance makes it become the video compression candidate for the upcoming HD-DVD. As a side effect, it was also blamed that H.264/AVC is much more logically complex and requires more computation power than any of the existing standards. A low-cost and efficient implementation of the international standard hence plays an important role of its success. In this paper, we realize an H.264/AVC baseline decoder by a low-cost DSP processor, i.e., Philips" TriMedia TM-1300, and illustrate that less computation demand for H.264/AVC decoding becomes feasible by using effective software core. To this end, we first consider different approaches and take advantage of SIMD instruction set to optimize critical time-consuming coding modules, such as the fractional motion compensation, spatial prediction and inverse transform. Next, we also present some other optimization approaches for entropy decoding and in-loop deblocking filtering, even though they cannot get benefits from utilizing SIMD. In our experiments, by exploiting appropriate instruction level parallelism and efficient algorithms, the decoding speed can be improved by a factor of 8~10; a CIF video sequence can be decoded at up to 19.74~28.97 fps on a 166-MHz TriMedia TM-1300 processor compared to 2.40~2.98 fps by the standard reference software.

H.264/AVC error resilience tools suitable for 3G mobile video services

Institute of Scientific and Technical Information of China (English)

LIU Lin; YE Xiu-zi; ZHANG San-yuan; ZHANG Yin

2005-01-01

The emergence of third generation mobile system (3G) makes video transmission in wireless environment possible,and the latest 3GPP/3GPP2 standards require 3G terminals support H.264/AVC. Due to high packet loss rate in wireless environment, error resilience for 3G terminals is necessary. Moreover, because of the hardware restrictions, 3G mobile terminals support only part of H.264/AVC error resilience tool. This paper analyzes various error resilience tools and their functions, and presents 2 error resilience strategies for 3G mobile streaming video services and mobile conversational services. Performances of the proposed error resilience strategies were tested using off-line common test conditions. Experiments showed that the proposed error resilience strategies can yield reasonably satisfactory results.

Efficient MPEG-2 to H.264/AVC Transcoding of Intra-Coded Video

Directory of Open Access Journals (Sweden)

Vetro Anthony

2007-01-01

Full Text Available This paper presents an efficient transform-domain architecture and corresponding mode decision algorithms for transcoding intra-coded video from MPEG-2 to H.264/AVC. Low complexity is achieved in several ways. First, our architecture employs direct conversion of the transform coefficients, which eliminates the need for the inverse discrete cosine transform (DCT and forward H.264/AVC transform. Then, within this transform-domain architecture, we perform macroblock-based mode decisions based on H.264/AVC transform coefficients, which is possible using a novel method of calculating distortion in the transform domain. The proposed method for distortion calculation could be used to make rate-distortion optimized mode decisions with lower complexity. Compared to the pixel-domain architecture with rate-distortion optimized mode decision, simulation results show that there is a negligible loss in quality incurred by the direct conversion of transform coefficients and the proposed transform-domain mode decision algorithms, while complexity is significantly reduced. To further reduce the complexity, we also propose two fast mode decision algorithms. The first algorithm ranks modes based on a simple cost function in the transform domain, then computes the rate-distortion optimal mode from a reduced set of ranked modes. The second algorithm exploits temporal correlations in the mode decision between temporally adjacent frames. Simulation results show that these algorithms provide additional computational savings over the proposed transform-domain architecture while maintaining virtually the same coding efficiency.

Drift-free MPEG-4 AVC semi-fragile watermarking

Science.gov (United States)

Hasnaoui, M.; Mitrea, M.

2014-02-01

While intra frame drifting is a concern for all types of MPEG-4 AVC compressed-domain video processing applications, it has a particular negative impact in watermarking. In order to avoid the drift drawbacks, two classes of solutions are currently considered in the literature. They try either to compensate the drift distortions at the expense of complex decoding/estimation algorithms or to restrict the insertion to the blocks which are not involved in the prediction, thus reducing the data payload. The present study follows a different approach. First, it algebraically models the drift distortion spread problem by considering the analytic expressions of the MPEG-4 AVC encoding operations. Secondly, it solves the underlying algebraic system under drift-free constraints. Finally, the advanced solution is adapted to take into account the watermarking peculiarities. The experiments consider an m-QIM semi-fragile watermarking method and a video surveillance corpus of 80 minutes. For prescribed data payload (100 bit/s), robustness (BER < 0.1 against transcoding at 50% in stream size), fragility (frame modification detection with accuracies of 1/81 from the frame size and 3s) and complexity constraints, the modified insertion results in gains in transparency of 2 dB in PSNR, of 0.4 in AAD, of 0.002 in IF, of 0.03 in SC, of 0.017 NCC and 22 in DVQ.

A novel frame-level constant-distortion bit allocation for smooth H.264/AVC video quality

Science.gov (United States)

Liu, Li; Zhuang, Xinhua

2009-01-01

It is known that quality fluctuation has a major negative effect on visual perception. In previous work, we introduced a constant-distortion bit allocation method [1] for H.263+ encoder. However, the method in [1] can not be adapted to the newest H.264/AVC encoder directly as the well-known chicken-egg dilemma resulted from the rate-distortion optimization (RDO) decision process. To solve this problem, we propose a new two stage constant-distortion bit allocation (CDBA) algorithm with enhanced rate control for H.264/AVC encoder. In stage-1, the algorithm performs RD optimization process with a constant quantization QP. Based on prediction residual signals from stage-1 and target distortion for smooth video quality purpose, the frame-level bit target is allocated by using a close-form approximations of ratedistortion relationship similar to [1], and a fast stage-2 encoding process is performed with enhanced basic unit rate control. Experimental results show that, compared with original rate control algorithm provided by H.264/AVC reference software JM12.1, the proposed constant-distortion frame-level bit allocation scheme reduces quality fluctuation and delivers much smoother PSNR on all testing sequences.

AVC Helps Teachers View the Atmosphere and Play in the Sand.

Science.gov (United States)

Klaus, Christopher; Andrew, Keith; McCollum, Timothy

2003-01-01

Describes the Atmospheric Visualization Collection (AVC), part of the National Science Digital Library (NSDL) that contains an archive of weather images as well as a collection of educational material that uses the images to teach atmospheric science concepts. Discusses the potential use of this information for K-12 and undergraduate students.…

Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

Science.gov (United States)

Kachach, Redouane; Cañas, José María

2016-05-01

Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

Entropy coders of the H.264/AVC standard

CERN Document Server

Tian, Xiaohua; Lian, Yong

2010-01-01

This book presents a collection of algorithms and VLSI architectures of entropy (or statistical) codecs of recent video compression standards, with focus on the H.264/AVC standard. For any visual data compression scheme, there exists a combination of two, or all of the following three stages: spatial, temporal, and statistical compression. General readers are first introduced with the various algorithms of the statistical coders. The VLSI implementations are also reviewed and discussed. Readers with limited hardware design background are also introduced with a design methodology starting from

An evaluation of the effect of JPEG, JPEG2000, and H.264/AVC on CQR codes decoding process

Science.gov (United States)

Vizcarra Melgar, Max E.; Farias, Mylène C. Q.; Zaghetto, Alexandre

2015-02-01

This paper presents a binarymatrix code based on QR Code (Quick Response Code), denoted as CQR Code (Colored Quick Response Code), and evaluates the effect of JPEG, JPEG2000 and H.264/AVC compression on the decoding process. The proposed CQR Code has three additional colors (red, green and blue), what enables twice as much storage capacity when compared to the traditional black and white QR Code. Using the Reed-Solomon error-correcting code, the CQR Code model has a theoretical correction capability of 38.41%. The goal of this paper is to evaluate the effect that degradations inserted by common image compression algorithms have on the decoding process. Results show that a successful decoding process can be achieved for compression rates up to 0.3877 bits/pixel, 0.1093 bits/pixel and 0.3808 bits/pixel for JPEG, JPEG2000 and H.264/AVC formats, respectively. The algorithm that presents the best performance is the H.264/AVC, followed by the JPEG2000, and JPEG.

Poster abstract: A machine learning approach for vehicle classification using passive infrared and ultrasonic sensors

KAUST Repository

Warriach, Ehsan Ullah

2013-01-01

This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN-SVM significantly outperforms other algorithms in terms of classification accuracy. We also show that some of these algorithms could run in real time on the prototype system. Copyright © 2013 ACM.

A Graphical User Interface (GUI) for Automated Classification of Bradley Fighting Vehicle Shock Absorbers

National Research Council Canada - National Science Library

Sincebaugh, Patrick

1998-01-01

.... We then explain the design and capabilities of the SSATS graphical user interface (GUI), which includes the integration of a neural network classification scheme. We finish by discussing recent results of utilizing the system to test and evaluate Bradley armored vehicle shock absorbers.

Fast mode decision algorithm in MPEG-2 to H.264/AVC transcoding including group of picture structure conversion

Science.gov (United States)

Lee, Kangjun; Jeon, Gwanggil; Jeong, Jechang

2009-05-01

The H.264/AVC baseline profile is used in many applications, including digital multimedia broadcasting, Internet protocol television, and storage devices, while the MPEG-2 main profile is widely used in applications, such as high-definition television and digital versatile disks. The MPEG-2 main profile supports B pictures for bidirectional motion prediction. Therefore, transcoding the MPEG-2 main profile to the H.264/AVC baseline is necessary for universal multimedia access. In the cascaded pixel domain transcoder architecture, the calculation of the rate distortion cost as part of the mode decision process in the H.264/AVC encoder requires extremely complex computations. To reduce the complexity inherent in the implementation of a real-time transcoder, we propose a fast mode decision algorithm based on complexity information from the reference region that is used for motion compensation. In this study, an adaptive mode decision process was used based on the modes assigned to the reference regions. Simulation results indicated that a significant reduction in complexity was achieved without significant degradation of video quality.

Poster abstract: A machine learning approach for vehicle classification using passive infrared and ultrasonic sensors

KAUST Repository

Warriach, Ehsan Ullah; Claudel, Christian G.

2013-01-01

This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN

Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

Science.gov (United States)

Garrido-Cantos, Rosario; De Cock, Jan; Martínez, Jose Luis; Van Leuven, Sebastian; Cuenca, Pedro; Garrido, Antonio

2013-12-01

Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

A Novel Steganography Technique for SDTV-H.264/AVC Encoded Video

Directory of Open Access Journals (Sweden)

Christian Di Laura

2016-01-01

Full Text Available Today, eavesdropping is becoming a common issue in the rapidly growing digital network and has foreseen the need for secret communication channels embedded in digital media. In this paper, a novel steganography technique designed for Standard Definition Digital Television (SDTV H.264/AVC encoded video sequences is presented. The algorithm introduced here makes use of the compression properties of the Context Adaptive Variable Length Coding (CAVLC entropy encoder to achieve a low complexity and real-time inserting method. The chosen scheme hides the private message directly in the H.264/AVC bit stream by modifying the AC frequency quantized residual luminance coefficients of intrapredicted I-frames. In order to avoid error propagation in adjacent blocks, an interlaced embedding strategy is applied. Likewise, the steganography technique proposed allows self-detection of the hidden message at the target destination. The code source was implemented by mixing MATLAB 2010 b and Java development environments. Finally, experimental results have been assessed through objective and subjective quality measures and reveal that less visible artifacts are produced with the technique proposed by reaching PSNR values above 40.0 dB and an embedding bit rate average per secret communication channel of 425 bits/sec. This exemplifies that steganography is affordable in digital television.

A fast inter mode decision algorithm in H.264/AVC for IPTV broadcasting services

Science.gov (United States)

Kim, Geun-Yong; Yoon, Bin-Yeong; Ho, Yo-Sung

2007-01-01

The new video coding standard H.264/AVC employs the rate-distortion optimization (RDO) method for choosing the best coding mode. However, since it increases the encoder complexity tremendously, it is not suitable for real-time applications, such as IPTV broadcasting services. Therefore we need a fast mode decision algorithm to reduce its encoding time. In this paper, we propose a fast mode decision algorithm considering quantization parameter (QP) because we have noticed that the frequency of best modes depends on QP. In order to consider these characteristics, we use the coded block pattern (CBP) that has "0" value when all quantized discrete cosine transform (DCT) coefficients are zero. We also use both the early SKIP mode and early 16x16 mode decisions. Experimental results show that the proposed algorithm reduces the encoding time by 74.6% for the baseline profile and 72.8% for the main profile, compared to the H.264/AVC reference software.

Subjective Quality Assessment of H.264/AVC Video Streaming with Packet Losses

Directory of Open Access Journals (Sweden)

Naccari Matteo

2011-01-01

Full Text Available Research in the field of video quality assessment relies on the availability of subjective scores, collected by means of experiments in which groups of people are asked to rate the quality of video sequences. The availability of subjective scores is fundamental to enable validation and comparative benchmarking of the objective algorithms that try to predict human perception of video quality by automatically analyzing the video sequences, in a way to support reproducible and reliable research results. In this paper, a publicly available database of subjective quality scores and corrupted video sequences is described. The scores refer to 156 sequences at CIF and 4CIF spatial resolutions, encoded with H.264/AVC and corrupted by simulating the transmission over an error-prone network. The subjective evaluation has been performed by 40 subjects at the premises of two academic institutions, in standard-compliant controlled environments. In order to support reproducible research in the field of full-reference, reduced-reference, and no-reference video quality assessment algorithms, both the uncompressed files and the H.264/AVC bitstreams, as well as the packet loss patterns, have been made available to the research community.

A influência dos principais factores de risco cardiovascular nos AVCs e consequente perturbação da linguagem adquirida

OpenAIRE

Ferreira, Elisabete Duarte

2013-01-01

Trabalho de Projeto apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Terapêutica da Fala, área de especialização em Linguagem no Adulto Introdução: O acidente vascular cerebral (AVC) constitui um dos principais problemas de saúde pública, de morbimortalidade e de incapacidade prolongada. As alterações decorrentes do AVC incluem os défices motores, os défices cognitivos e as perturbações da linguagem adquirida, tal como a afasia. Foi se...

Fréquence et caractéristiques des AVC impliquant les artères perforantes dans le Service de Neurologie de l’Hopital Bafelatanana, Antananarivo

Science.gov (United States)

Rasaholiarison, Nomena Finiavana; Randrianasolo, Rahamefy Odilon; Rajaonarison, Lala Andriamasinavalona; Rakotomanana, Jenny Larissa; Razafimahefa, Julien; Tehindrazanarivelo, Alain Djacoba

2017-01-01

Introduction Les accidents vasculaires cérébraux des artères perforantes sont surtout des artériolopathies. Ils évoluent vers la démence et la récurrence. Pour mieux prévenir ces complications notre étude avait pour but d'évaluer la fréquence et les caractéristiques de ces AVC. Méthodes c'est une étude descriptive rétrospective du 01 Mars au 25 Septembre 2015 au service de Neurologie CHU-JRB. Ont été inclus les patients présentant un déficit neurologique brutal et un scanner cérébral avec atteinte du territoire profonde. Les caractéristiques des AVC des artères perforantes ont été recueillies. Les données étaient traitées par le logiciel SPSS 20. Résultats Quatre-vingt-trois (48,25%) patients avaient des AVC des artères perforantes sur 172 AVC. Pour les AVC des artères perforantes la population était jeune avec 65,06% moins de 65 ans et à prédominance masculine avec 61,44%. Les formes hémorragiques étaient à 67,46%. Trente et un patients (37,34%) ont connu des récurrences et parmi eux presque le quart avait 2 récurrences avec 38,70% en moins de un an. Tous les patients avec récurrence avaient un trouble dysexécutif (p AVC pendant l'hospitalisation. Conclusion Un suivi spécifique en neurologie est nécessaire dès le premier accident vasculaire cérébral d'artère perforante pour dépister un début de démence et prévenir les récurrences. PMID:29255546

Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation

CSIR Research Space (South Africa)

Ngwangwa, HM

2010-04-01

Full Text Available -1 Journal of Terramechanics Volume 47, Issue 2, April 2010, Pages 97-111 Reconstruction of road defects and road roughness classification using vehicle responses with artificial neural networks simulation H.M. Ngwangwaa, P.S. Heynsa, , , F...

Classification of robotic battery service systems for unmanned aerial vehicles

Directory of Open Access Journals (Sweden)

Ngo Tien

2018-01-01

Full Text Available Existing examples of prototypes of ground-based robotic platforms used as a landing site for unmanned aerial vehicles are considered. In some cases, they are equipped with a maintenance mechanism for the power supply module. The main requirements for robotic multi-copter battery maintenance systems depending on operating conditions, required processing speed, operator experience and other parameters are analyzed. The key issues remain questions of the autonomous landing of the unmanned aerial vehicles on the platform and approach to servicing battery. The existing prototypes of service robotic platforms are differed in the complexity of internal mechanisms, speed of service, algorithms of joint work of the platform and unmanned aerial vehicles during the landing and maintenance of the battery. The classification of robotic systems for servicing the power supply of multi-copter batteries criteria is presented using the following: the type of basing, the method of navigation during landing, the shape of the landing pad, the method of restoring the power supply module. The proposed algorithmic model of the operation of battery power maintenance system of the multi-copter on ground-based robotic platform during solving the target agrarian problem is described. Wireless methods of battery recovery are most promising, so further development and prototyping of a wireless charging station for multi-copter batteries will be developed.

Low-Power Bitstream-Residual Decoder for H.264/AVC Baseline Profile Decoding

Directory of Open Access Journals (Sweden)

Xu Ke

2009-01-01

Full Text Available Abstract We present the design and VLSI implementation of a novel low-power bitstream-residual decoder for H.264/AVC baseline profile. It comprises a syntax parser, a parameter decoder, and an Inverse Quantization Inverse Transform (IQIT decoder. The syntax parser detects and decodes each incoming codeword in the bitstream under the control of a hierarchical Finite State Machine (FSM; the IQIT decoder performs inverse transform and quantization with pipelining and parallelism. Various power reduction techniques, such as data-driven based on statistic results, nonuniform partition, precomputation, guarded evaluation, hierarchical FSM decomposition, TAG method, zero-block skipping, and clock gating , are adopted and integrated throughout the bitstream-residual decoder. With innovative architecture, the proposed design is able to decode QCIF video sequences of 30 fps at a clock rate as low as 1.5 MHz. A prototype H.264/AVC baseline decoding chip utilizing the proposed decoder is fabricated in UMC 0.18  m 1P6M CMOS technology. The proposed design is measured under 1 V 1.8 V supply with 0.1 V step. It dissipates 76  W at 1 V and 253  W at 1.8 V.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

Directory of Open Access Journals (Sweden)

Sang-Il Oh

2017-01-01

Full Text Available To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN. The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

Predicting the Types of Ion Channel-Targeted Conotoxins Based on AVC-SVM Model.

Science.gov (United States)

Xianfang, Wang; Junmei, Wang; Xiaolei, Wang; Yue, Zhang

2017-01-01

The conotoxin proteins are disulfide-rich small peptides. Predicting the types of ion channel-targeted conotoxins has great value in the treatment of chronic diseases, epilepsy, and cardiovascular diseases. To solve the problem of information redundancy existing when using current methods, a new model is presented to predict the types of ion channel-targeted conotoxins based on AVC (Analysis of Variance and Correlation) and SVM (Support Vector Machine). First, the F value is used to measure the significance level of the feature for the result, and the attribute with smaller F value is filtered by rough selection. Secondly, redundancy degree is calculated by Pearson Correlation Coefficient. And the threshold is set to filter attributes with weak independence to get the result of the refinement. Finally, SVM is used to predict the types of ion channel-targeted conotoxins. The experimental results show the proposed AVC-SVM model reaches an overall accuracy of 91.98%, an average accuracy of 92.17%, and the total number of parameters of 68. The proposed model provides highly useful information for further experimental research. The prediction model will be accessed free of charge at our web server.

Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System

Science.gov (United States)

Velazquez-Pupo, Roxana; Sierra-Romero, Alberto; Torres-Roman, Deni; Shkvarko, Yuriy V.; Romero-Delgado, Misael

2018-01-01

This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. PMID:29382078

Detection of Double-Compressed H.264/AVC Video Incorporating the Features of the String of Data Bits and Skip Macroblocks

Directory of Open Access Journals (Sweden)

Heng Yao

2017-12-01

Full Text Available Today’s H.264/AVC coded videos have a high quality, high data-compression ratio. They also have a strong fault tolerance, better network adaptability, and have been widely applied on the Internet. With the popularity of powerful and easy-to-use video editing software, digital videos can be tampered with in various ways. Therefore, the double compression in the H.264/AVC video can be used as a first step in the study of video-tampering forensics. This paper proposes a simple, but effective, double-compression detection method that analyzes the periodic features of the string of data bits (SODBs and the skip macroblocks (S-MBs for all I-frames and P-frames in a double-compressed H.264/AVC video. For a given suspicious video, the SODBs and S-MBs are extracted for each frame. Both features are then incorporated to generate one enhanced feature to represent the periodic artifact of the double-compressed video. Finally, a time-domain analysis is conducted to detect the periodicity of the features. The primary Group of Pictures (GOP size is estimated based on an exhaustive strategy. The experimental results demonstrate the efficacy of the proposed method.

Complexity reduction in the H.264/AVC using highly adaptive fast mode decision based on macroblock motion activity

Science.gov (United States)

Abdellah, Skoudarli; Mokhtar, Nibouche; Amina, Serir

2015-11-01

The H.264/AVC video coding standard is used in a wide range of applications from video conferencing to high-definition television according to its high compression efficiency. This efficiency is mainly acquired from the newly allowed prediction schemes including variable block modes. However, these schemes require a high complexity to select the optimal mode. Consequently, complexity reduction in the H.264/AVC encoder has recently become a very challenging task in the video compression domain, especially when implementing the encoder in real-time applications. Fast mode decision algorithms play an important role in reducing the overall complexity of the encoder. In this paper, we propose an adaptive fast intermode algorithm based on motion activity, temporal stationarity, and spatial homogeneity. This algorithm predicts the motion activity of the current macroblock from its neighboring blocks and identifies temporal stationary regions and spatially homogeneous regions using adaptive threshold values based on content video features. Extensive experimental work has been done in high profile, and results show that the proposed source-coding algorithm effectively reduces the computational complexity by 53.18% on average compared with the reference software encoder, while maintaining the high-coding efficiency of H.264/AVC by incurring only 0.097 dB in total peak signal-to-noise ratio and 0.228% increment on the total bit rate.

Performance evaluation of H.264/AVC decoding and visualization using the GPU

OpenAIRE

Pieters, Bart; Van Rijsselbergen, Dieter; De Neve, Wesley; Van de Walle, Rik

2007-01-01

The coding efficiency of the H.264/AVC standard makes the decoding process computationally demanding. This has limited the availability of cost-effective, high-performance solutions. Modern computers are typically equipped with powerful yet cost-effective Graphics Processing Units (GPUs) to accelerate graphics operations. These GPUs can be addressed by means of a 3-D graphics API such as Microsoft Direct3D or OpenGL, using programmable shaders as generic processing units for vector data. The ...

Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos

Science.gov (United States)

Xu, Dawen; Wang, Rangding

2015-05-01

A scheme of data hiding directly in a partially encrypted version of H.264/AVC videos is proposed which includes three parts, i.e., selective encryption, data embedding and data extraction. Selective encryption is performed on context adaptive binary arithmetic coding (CABAC) bin-strings via stream ciphers. By careful selection of CABAC entropy coder syntax elements for selective encryption, the encrypted bitstream is format-compliant and has exactly the same bit rate. Then a data-hider embeds the additional data into partially encrypted H.264/AVC videos using a CABAC bin-string substitution technique without accessing the plaintext of the video content. Since bin-string substitution is carried out on those residual coefficients with approximately the same magnitude, the quality of the decrypted video is satisfactory. Video file size is strictly preserved even after data embedding. In order to adapt to different application scenarios, data extraction can be done either in the encrypted domain or in the decrypted domain. Experimental results have demonstrated the feasibility and efficiency of the proposed scheme.

Encoder power consumption comparison of Distributed Video Codec and H.264/AVC in low-complexity mode

DEFF Research Database (Denmark)

Ukhanova, Ann; Belyaev, Evgeny; Forchhammer, Søren

2010-01-01

(ME) and CABAC entropy coder consume much power so we eliminate ME from the codec and use CAVLC instead of CABAC. Some investigations show that low-complexity DVC outperforms other algorithms in terms of encoder side energy consumption . However, estimations of power consumption for H.264/AVC and DVC...

Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification

Directory of Open Access Journals (Sweden)

Maulidia Rahmah Hidayah

2017-05-01

Full Text Available The current topic that is interesting as a solution of the impact of public service improvement toward vehicle is License Plate Recognition (LPR, but it still needs to develop the research of LPR method. Some of the previous researchs showed that K-Nearest Neighbour (KNN succeed in car license plate recognition. The Objectives of this research was to determine the implementation and accuracy of Otsu Method toward license plate recognition. The method of this research was Otsu method to extract the characteristics and image of the plate into binary image and KNN as recognition classification method of each character. The development of the license plate recognition program by using Otsu method and classification of KNN is following the steps of pattern recognition, such as input and sensing, pre-processing, extraction feature Otsu method binary, segmentation, KNN classification method and post-processing by calculating the level of accuracy. The study showed that this program can recognize by 82% from 100 test plate with 93,75% of number recognition accuracy and 91,92% of letter recognition accuracy. 

Subjective Video Quality Assessment in H.264/AVC Video Coding Standard

Directory of Open Access Journals (Sweden)

Z. Miličević

2012-11-01

Full Text Available This paper seeks to provide an approach for subjective video quality assessment in the H.264/AVC standard. For this purpose a special software program for the subjective assessment of quality of all the tested video sequences is developed. It was developed in accordance with recommendation ITU-T P.910, since it is suitable for the testing of multimedia applications. The obtained results show that in the proposed selective intra prediction and optimized inter prediction algorithm there is a small difference in picture quality (signal-to-noise ratio between decoded original and modified video sequences.

Development of a Simple Traffic Sensor and System with Vehicle Classification Based on PVDF Film Element

Directory of Open Access Journals (Sweden)

D. R. SANTOSO

2011-03-01

Full Text Available In this paper, piezoelectric sensor system for measuring traffic flow with vehicle classification is proposed and investigated. Sensing element is made of PVDF film, which on both sides plastered with sheets of metal electrodes for making electrical connections. This sensor will generate electric voltage when subjected to mechanical pressure by the wheels of the vehicle. The signal conditioning is required to make sensor output voltage in the range of 0-5 Volts. To classify the types of vehicles crossing the sensor, three-level comparator is used, with specifications of a low voltage reference for motorcycles, medium voltage reference for a family vehicle, and a high voltage reference for buses, trucks and the like. Output of the comparators are already a logic '0' or '1' is then processed by a microcontroller based data acquisition system that the output shows the number and type of vehicles that crossed the road in the form of digital code. These data then transmitted to a control centre that was built based on a PC. At the control centre, traffic data tabulated in the form of measurement database and stored for further analysis.

Classification of Dynamic Vehicle Routing Systems

DEFF Research Database (Denmark)

Larsen, Allan; Madsen, Oli B.G.; Solomon, Marius M.

2007-01-01

This chapter discusses important characteristics seen within dynamic vehicle routing problems. We discuss the differences between the traditional static vehicle routing problems and its dynamic counterparts. We give an in-depth introduction to the degree of dynamism measure which can be used to c...

International Conference on Heavy Vehicles HVParis 2008 : Heavy Vehicle Transport Technology (HVTT 10)

OpenAIRE

JACOB, Bernard; NORDENGEN, Paul; O'CONNOR, Alan; BOUTELDJA, Mohamed

2008-01-01

Sommaire : Heavy vehicles and WIM technology, testing and standards. Interactions between heavy vehicles or trains and the infrastructure, environment and other system users. Heavy vehicle and road management information: measurements, data quality, data management. Freight mobility and safety. Vehicle classification, size and weight evaluation, regulations and enforcement. Traffic and road safety. WIM of road vehicles, trains and aeroplanes.

Aspects épidémiologiques des accidents vasculaires cérébraux (AVC) aux urgences de l'institut de cardiologie d'Abidjan (ICA)

Science.gov (United States)

N'goran, Yves N'da Kouakou; Traore, Fatou; Tano, Micesse; Kramoh, Kouadio Euloge; Kakou, Jean-Baptiste Anzouan; Konin, Christophe; Kakou, Maurice Guikahue

2015-01-01

Introduction L'objectif de notre étude était de décrire les caractéristiques sociodémographiques et les Facteurs de Risque cardio-Vasculaires (FRV) des patients admis pour accidents vasculaires cérébraux (AVC) dans un service autre que celui de la neurologie. Méthodes Étude transversale rétrospective sur une période de 2 ans (janv. 2010 et déc. 2011), réalisée aux urgences de l'institut de cardiologie d'Abidjan. Résultats Il s'agissait de 176 adultes avec un âge moyen de 60 ans, une prédominance féminine. Les facteurs de risque majeurs retrouvés étaient l'hypertension artérielle dans 86,4% des cas, le diabète dans 11,4% des cas, le tabagisme dans 2,2% des cas. Les motifs de consultation étaient la perte de connaissance dans 36,4% des cas, l'hémiplégie dans 31,8% des cas, les céphalées dans 17,4% des cas, les vertiges dans 10,9% et les palpitations dans 2,2% des cas. La tension artérielle systolique moyenne était à 174 mmHg, la tension artérielle diastolique moyenne était à 105 mmHg et la pression pulsée moyenne était à 70 mmHg. Les AVC étaient associés à une arythmie complète par fibrillation auriculaire dans 11,4% des cas. Les AVC ischémiques représentaient 84,1%. L’évolution aux urgences a été marquée par un décès dans 17% (30) des cas. Conclusion Les AVC constituent un problème majeur de santé publique. Malgré sa prédominance féminine, ils (AVC) touchaient 44% des hommes dans notre étude lorsqu'on sait qu'en Afrique l'activité sociale repose sur les hommes. Ils restent une pathologie grave par la forte létalité. PMID:26327997

[Infections as a preoperative problem in patients with tetralogy of Fallot (TOF) associated with complete atrioventricular canal septal defect (AVC)].

Science.gov (United States)

Szydłowski, Lesław; Marek-Szydłowska, Teresa; Rudziński, Andrzej; Pajak, Jacek; Morka, Jacek; Stołtny, Ludwik

2004-01-01

Tetralogy of Fallot (TOF) coexisting with atrioventricular canal septal defect (AVC) is a rare combination of anomalies. Additionally, in cases with concomitant Down syndrome, recurrent infections can be a serious problem in patients (pts.) waiting for cardiosurgery treatment. The purpose of the study was an analysis of types of infections and other factors complicating the preoperative period in those patients. The study group consisted of 17 pts. with TOF and AVC aged from 1 day to 9 years (mean 9.4 month). In this group there were 11 pts. with Down syndrome. All of them were subjected to physical examinations, blood analysis, ECG, chest X-ray and echocardiographic study. Additionally, in 8 pts. we performed catheterization. The signs of different types of infection were analyzed and results were compared in two groups: with and without Down syndrome. The differences were observed in the frequency of recurrent or chronic infections (21 v/s 4), time of hospitalization before surgery (17 v/s 9 days), necessity (11 v/s 3) and duration of antibiotic therapy (19 v/s 7 days) in the two studied groups. Elevated body temperature of unknown etiology was noted in 8 cases with Down syndrome, compared to 1 patient without trisomy 21. Also, the children with Down syndrome had to wait 11 days longer (19 v/s 8) for discharge after operation. Infections in children with TOF, AVC and Down syndrome significantly complicate the natural course of this anomaly. Prolonged preoperation time is characteristic of Down syndrome pts. compared to patients without chromosomal abnormalities.

Interação cuidador familiar-pessoa com AVC: autonomia compartilhada Interaction between stroke survivors and family caregivers: shared autonomy

Directory of Open Access Journals (Sweden)

Sílvia Cristina Mangini Bocchi

2005-09-01

Full Text Available Trata-se de um estudo qualitativo, utilizando-se como referencial metodológico a Grounded Theory e como referencial teórico o Interacionismo Simbólico, para compreender a experiência de cuidadores familiares de pessoas com AVC, acerca das modalidades de cuidado adotadas por eles, durante o processo de reabilitação de uma pessoa com AVC no domicílio. Tais modalidades podem ser exercidas: incentivando o doente a recuperar a sua autonomia; e não estimulando a autonomia do doente. Ao inter-relacionar os componentes relativos à experiência, evidenciamos que o próprio cuidador familiar percebe que os processos de retomada da autonomia - da pessoa vitimada pelo AVC e de sua própria - se configuram como interdependentes e condicionados ao nível de reabilitação alcançado pelo doente.This paper is a qualitative study using the Grounded Theory as a methodological reference and the Symbolic Interactionism as a theoretical reference. It aimed at understanding the family caregiver’s experience with stroke survivors on the care systems adopted by them during the home rehabilitation process, as it follows: - encouraging the patient’s autonomy recovering and - not encouraging the patient’s autonomy. As the components towards the experience have been interrelated, it could be observed that the own caregiver has perceived that the process of autonomy recovering either that of the CVA-patient or his own have been interdependent and related to the rehabilitation level reached by the patient.

Scout fourth stage attitude and velocity control (AVC) system feasibility study

Science.gov (United States)

Byars, L. B.

1975-01-01

The feasibility of incorporating a guidance system in the Scout fourth stage to achieve a significant improvement in expected payload delivery accuracy is studied. The technical investigations included the determination of the AVC equipment performance requirements, establishment of qualification and acceptance test levels, generation of layouts illustrating design approaches for the upper D and payload transition sections to incorporate the hardware, and the preparation of a vendor bid package. Correction concepts, utilizing inertial velocity and attitude, were identified and evaluated. Fourth stage attitude adjustments as determined from inertial velocity variation through the first three stages and a final velocity correction based upon the measured in-plane component errors at injection were employed. Results show radical reductions in apogee-perigee deviations.

A robust H.264/AVC video watermarking scheme with drift compensation.

Science.gov (United States)

Jiang, Xinghao; Sun, Tanfeng; Zhou, Yue; Wang, Wan; Shi, Yun-Qing

2014-01-01

A robust H.264/AVC video watermarking scheme for copyright protection with self-adaptive drift compensation is proposed. In our scheme, motion vector residuals of macroblocks with the smallest partition size are selected to hide copyright information in order to hold visual impact and distortion drift to a minimum. Drift compensation is also implemented to reduce the influence of watermark to the most extent. Besides, discrete cosine transform (DCT) with energy compact property is applied to the motion vector residual group, which can ensure robustness against intentional attacks. According to the experimental results, this scheme gains excellent imperceptibility and low bit-rate increase. Malicious attacks with different quantization parameters (QPs) or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression.

Piezo-electric automatic vehicle classification system : Oregon Department of Transportation with Castle Rock Consultants for a SHRP Long Term Pavement Performance Site.

Science.gov (United States)

1990-05-01

Oregon has twelve sites that are part of the Strategic Highway Research Program (SHRP), Long Term Pavement Performance (LTPP) studies. Part of the data gathering on these sites involves vehicle weight and classification. This pilot project was to hel...

Alcohol Use Disorder History Moderates the Relationship Between Avoidance Coping and Posttraumatic Stress Symptoms

OpenAIRE

Hruska, Bryce; Fallon, William; Spoonster, Eileen; Sledjeski, Eve M.; Delahanty, Douglas L.

2011-01-01

Avoidance coping (AVC) is common in individuals with posttraumatic stress disorder (PTSD) and in individuals with alcohol use disorder (AUD). Given that PTSD and AUD commonly co-occur, AVC may represent a risk factor for the development of comorbid post-traumatic stress and alcohol use. In this study, the relationship between AVC and PTSD symptoms (PTSS) was examined in individuals with versus without AUDs. Motor vehicle accident (MVA) victims were assessed 6-weeks post accident for AUD histo...

H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

Science.gov (United States)

Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

2014-01-01

This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

Efeitos da terapia espelho na recuperação motora e funcional do membro superior com paresia pós-AVC: uma revisão sistemática

OpenAIRE

Costa, Valton da Silva; Silveira, Júlio César Cunha da; Clementino, Tatiana Catarina Albuquerque; Borges, Lorenna Raquel Dantas de Macedo; Melo, Luciana Protásio de

2016-01-01

RESUMO Após um acidente vascular cerebral (AVC), o membro superior pode apresentar déficits motores que podem levar a incapacidades funcionais. A terapia espelho (TE) é uma possibilidade terapêutica na reabilitação do membro superior (MS). Este estudo objetivou reunir evidências que pudessem mostrar quais são os efeitos da TE na recuperação motora e funcional do MS com paresia pós-AVC. Foi realizada uma busca eletrônica nas bases de dados SciELO, LILACS, PubMed, PEDro e ScienceDirect, utiliza...

A Robust H.264/AVC Video Watermarking Scheme with Drift Compensation

Directory of Open Access Journals (Sweden)

Xinghao Jiang

2014-01-01

Full Text Available A robust H.264/AVC video watermarking scheme for copyright protection with self-adaptive drift compensation is proposed. In our scheme, motion vector residuals of macroblocks with the smallest partition size are selected to hide copyright information in order to hold visual impact and distortion drift to a minimum. Drift compensation is also implemented to reduce the influence of watermark to the most extent. Besides, discrete cosine transform (DCT with energy compact property is applied to the motion vector residual group, which can ensure robustness against intentional attacks. According to the experimental results, this scheme gains excellent imperceptibility and low bit-rate increase. Malicious attacks with different quantization parameters (QPs or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression.

Edge-preserving Intra mode for efficient depth map coding based on H.264/AVC

DEFF Research Database (Denmark)

Zamarin, Marco; Forchhammer, Søren

2014-01-01

Depth-image-based-rendering (DIBR) algorithms for 3D video communication systems based on the “multi-view video plus depth” format are very sensitive to the accuracy of depth information. Specifically, edge regions in the depth data should be preserved in the coding/decoding process to ensure good...... view synthesis performance, which directly affects the overall system performance. This paper proposes a novel scheme for edge-aware Intra depth compression based on the H.264/AVC framework enabled on both Intra (I) and Inter (P) slices. The proposed scheme includes a new Intra mode specifically...

Adaptive quantization-parameter clip scheme for smooth quality in H.264/AVC.

Science.gov (United States)

Hu, Sudeng; Wang, Hanli; Kwong, Sam

2012-04-01

In this paper, we investigate the issues over the smooth quality and the smooth bit rate during rate control (RC) in H.264/AVC. An adaptive quantization-parameter (Q(p)) clip scheme is proposed to optimize the quality smoothness while keeping the bit-rate fluctuation at an acceptable level. First, the frame complexity variation is studied by defining a complexity ratio between two nearby frames. Second, the range of the generated bits is analyzed to prevent the encoder buffer from overflow and underflow. Third, based on the safe range of the generated bits, an optimal Q(p) clip range is developed to reduce the quality fluctuation. Experimental results demonstrate that the proposed Q(p) clip scheme can achieve excellent performance in quality smoothness and buffer regulation.

Cross-Layer Framework for Multiuser Real Time H.264/AVC Video Encoding and Transmission over Block Fading MIMO Channels Using Outage Probability

Directory of Open Access Journals (Sweden)

Slavche Pejoski

2014-01-01

Full Text Available We present a framework for cross-layer optimized real time multiuser encoding of video using a single layer H.264/AVC and transmission over MIMO wireless channels. In the proposed cross-layer adaptation, the channel of every user is characterized by the probability density function of its channel mutual information and the performance of the H.264/AVC encoder is modeled by a rate distortion model that takes into account the channel errors. These models are used during the resource allocation of the available slots in a TDMA MIMO communication system with capacity achieving channel codes. This framework allows for adaptation to the statistics of the wireless channel and to the available resources in the system and utilization of the multiuser diversity of the transmitted video sequences. We show the effectiveness of the proposed framework for video transmission over Rayleigh MIMO block fading channels, when channel distribution information is available at the transmitter.

Piezo-electric automatic vehicle classification system : Oregon Department of Transportation with Castle Rock Consultants for a SHRP Long Term Pavement Performance Site : final report.

Science.gov (United States)

1991-07-01

Oregon has twelve pavement test sites that are part of the Strategic Highway Research Program (SHRP), Long Term Pavement Performance (LTPP) studies. Part of the data gathering on these sites involves vehicle weight and classification. This pilot proj...

Nppa and Nppb act redundantly during zebrafish cardiac development to confine AVC marker expression and reduce cardiac jelly volume.

Science.gov (United States)

Grassini, Daniela R; Lagendijk, Anne K; De Angelis, Jessica E; Da Silva, Jason; Jeanes, Angela; Zettler, Nicole; Bower, Neil I; Hogan, Benjamin M; Smith, Kelly A

2018-05-11

Atrial natriuretic peptide ( nppa/anf ) and brain natriuretic peptide ( nppb/bnp ) form a gene cluster with expression in the chambers of the developing heart. Despite restricted expression, a function in cardiac development has not been demonstrated by mutant analysis. This is attributed to functional redundancy however their genomic location in cis has impeded formal analysis. Using genome-editing, we generated mutants for nppa and nppb and found single mutants indistinguishable from wildtype whereas nppa / nppb double mutants display heart morphogenesis defects and pericardial oedema. Analysis of atrioventricular canal (AVC) markers show expansion of bmp4 , tbx2b, has2 and versican expression into the atrium of double mutants. This expanded expression correlates with increased extracellular matrix in the atrium. Using a biosensor for Hyaluronic acid to measure the cardiac jelly (cardiac extracellular matrix), we confirm cardiac jelly expansion in nppa / nppb double mutants. Finally, bmp4 knockdown rescues the expansion of has2 expression and cardiac jelly in double mutants. This definitively shows that nppa and nppb function redundantly during cardiac development to restrict gene expression to the AVC, preventing excessive cardiac jelly synthesis in the atrial chamber. © 2018. Published by The Company of Biologists Ltd.

Fast H.264/AVC FRExt intra coding using belief propagation.

Science.gov (United States)

Milani, Simone

2011-01-01

In the H.264/AVC FRExt coder, the coding performance of Intra coding significantly overcomes the previous still image coding standards, like JPEG2000, thanks to a massive use of spatial prediction. Unfortunately, the adoption of an extensive set of predictors induces a significant increase of the computational complexity required by the rate-distortion optimization routine. The paper presents a complexity reduction strategy that aims at reducing the computational load of the Intra coding with a small loss in the compression performance. The proposed algorithm relies on selecting a reduced set of prediction modes according to their probabilities, which are estimated adopting a belief-propagation procedure. Experimental results show that the proposed method permits saving up to 60 % of the coding time required by an exhaustive rate-distortion optimization method with a negligible loss in performance. Moreover, it permits an accurate control of the computational complexity unlike other methods where the computational complexity depends upon the coded sequence.

Algorithm and Hardware Design of a Fast Intra Frame Mode Decision Module for H.264/AVC Encoders

Directory of Open Access Journals (Sweden)

Daniel Palomino

2012-01-01

Full Text Available In the rate-distortion optimization (RDO, the process of choosing the best prediction mode is performed through exhaustive executions of the whole encoding process, increasing significantly the encoder computational complexity. Considering H.264/AVC intra frame prediction, there are several modes to encode a macroblock (MB. This work proposes an algorithm and the hardware design for a fast intra frame mode decision module for H.264/AVC encoders. The application of the proposed algorithm reduces in more than 10 times the number of encoding iterations for choosing the best intramode when compared with RDO-based decision. The architecture was synthesized to FPGA and achieved an operation frequency of 98 MHz processing more than 300 HD1080p frames per second. With this approach, we achieved one order-of-magnitude performance improvement compared with RDO-based approaches, which is very important not only from the performance but also from the energy consumption perspective for battery-operated devices. In order to compare the architecture with previously published works, we also synthesized it to standard cells. Compared with the best previous results reported, the implemented architecture achieves a complexity reduction of five times, a processing capability increase of 14 times, and a reduction in the number of clock cycles per MB of 11 times.

Improvement of the performance of animal crossing warning signs.

Science.gov (United States)

Khalilikhah, Majid; Heaslip, Kevin

2017-09-01

Animal-vehicle collisions (AVCs) can result in serious injury and death to drivers, animals' death, and significant economic costs. However, the cost effectiveness of the majority of AVC mitigation measures is a significant issue. A mobile-based data collection effort was deployed to measure signs under the Utah Department of Transportation's (UDOT) jurisdiction. The crash data were obtained from the UDOT risk management database. ArcGIS was employed to link these two data sets and extract animal-related crashes and signs. An algorithm was developed to process the data and identify AVCs that occurred within sign recognition distance. Kernel density estimation (KDE) technique was applied to identify potential crash hotspots. Only 2% of AVCs occurred within the recognition distance of animal crossing signs. Almost 58% of animal-related crashes took place on the Interstate and U.S. highways, wherein only 30% of animal crossing signs were installed. State routes with a higher average number of signs experienced a lower number of AVCs per mile. The differences between AVCs that occurred within versus outside of sign recognition distance were not statistically significant regarding crash severity, time of crash, weather condition, driver age, vehicle speed, and type of animal. It is more likely that drivers become accustomed to deer crossing signs than cow signs. Based on the historical crash data and landscape structure, with attention given to the low cost safety improvement methods, a combination of different types of AVC mitigation measures can be developed to reduce the number of animal-related crashes. After an in-depth analysis of AVC data, warning traffic signs, coupled with other low cost mitigation countermeasures can be successfully placed in areas with higher priority or in critical areas. Practical applications: The findings of this study assist transportation agencies in developing more efficient mitigation measures against AVCs. Copyright © 2017 National

Segmentation, classification, and pose estimation of military vehicles in low resolution laser radar images

Science.gov (United States)

Neulist, Joerg; Armbruster, Walter

2005-05-01

Model-based object recognition in range imagery typically involves matching the image data to the expected model data for each feasible model and pose hypothesis. Since the matching procedure is computationally expensive, the key to efficient object recognition is the reduction of the set of feasible hypotheses. This is particularly important for military vehicles, which may consist of several large moving parts such as the hull, turret, and gun of a tank, and hence require an eight or higher dimensional pose space to be searched. The presented paper outlines techniques for reducing the set of feasible hypotheses based on an estimation of target dimensions and orientation. Furthermore, the presence of a turret and a main gun and their orientations are determined. The vehicle parts dimensions as well as their error estimates restrict the number of model hypotheses whereas the position and orientation estimates and their error bounds reduce the number of pose hypotheses needing to be verified. The techniques are applied to several hundred laser radar images of eight different military vehicles with various part classifications and orientations. On-target resolution in azimuth, elevation and range is about 30 cm. The range images contain up to 20% dropouts due to atmospheric absorption. Additionally some target retro-reflectors produce outliers due to signal crosstalk. The presented algorithms are extremely robust with respect to these and other error sources. The hypothesis space for hull orientation is reduced to about 5 degrees as is the error for turret rotation and gun elevation, provided the main gun is visible.

Earthquake and Physical and Social Vulnerability Assessment for Settlements: Case Study Avcılar District

Directory of Open Access Journals (Sweden)

Görün ARUN

2010-01-01

Full Text Available Many settled areas in Turkey and across the globe suffer economical and social losses resulting from natural disasters such as earthquakes, floods, hurricanes and landslides. In this study, a vulnerability assessment model has been developed for earthquake prone areas in Turkey. The vulnerability assessment model includes ground factors, a building’s physical conditions, building evacuation and social (demographic and socioeconomic aspects of the settlement. The ground vulnerability factor is calculated using factors such as the earthquake zone, soil classification, land sliding and liquefaction threats. The physical vulnerability factor depends on the structural and non-structural threats of the building; the building evacuation vulnerability factor includes the position and structural system of the staircase, the width and natural illumination of the evacuation route, the size and opening of the building exit doors to the street and the distance of the building to the closest open area. The social vulnerability factor considers the age group, gender, family type, education, ownership, income etc of the building users. This vulnerability assessment model is applied to a case study - that of the Avcılar district of Istanbul. Forty different reinforced concrete residential buildings (349 apartments of 1225 people are assessed using the develop checklist. In order to evaluate the checklist and to assess the importance (relevance of vulnerability factors, a questionnaire is forwarded to various related professional groups (architecture, urban planning and civil engineering. The results of the questionnaire are examined using SPSS software with factor analysis. According to the results, most of the samples in the case study area can be classified as high vulnerable.

Evaluation of a Workplace Basic Skills Program: An Impact Study of AVC Edmonton's 1990 Job Effectiveness Training Program at Stelco Steel. Report Summary.

Science.gov (United States)

Barker, Kathryn Chang

The pilot Job Effectiveness Training (JET) workplace basic skills program, developed by Canada's Alberta Vocational College (AVC), Edmonton, for Stelco Steel during 1989-90, was evaluated in terms of impacts or changes from the perspective of the four major stakeholder groups: the students (12 Stelco employees); the employers (Stelco management);…

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

Science.gov (United States)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Overview of hybrid electric vehicle trend

Science.gov (United States)

Wang, Haomiao; Yang, Weidong; Chen, Yingshu; Wang, Yun

2018-04-01

With the increase of per capita energy consumption, environmental pollution is worsening. Using new alternative sources of energy, reducing the use of conventional fuel-powered engines is imperative. Due to the short period, pure electric vehicles cannot be mass-produced and there are many problems such as imperfect charging facilities. Therefore, the development of hybrid electric vehicles is particularly important in a certain period. In this paper, the classification of hybrid vehicle, research status of hybrid vehicle and future development trends of hybrid vehicles is introduced. It is conducive to the public understanding of hybrid electric vehicles, which has a certain theoretical significance.

WOODLAND MAPPING AT SINGLE-TREE LEVELS USING OBJECT-ORIENTED CLASSIFICATION OF UNMANNED AERIAL VEHICLE (UAV IMAGES

Directory of Open Access Journals (Sweden)

A. Chenari

2017-09-01

Full Text Available Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm gathered by real-time kinematic (RTK method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2 and wild almonds (3.97±1.69 m2 with no significant difference with their observed values (α=0.05. In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92 and wild almonds (accuracy of 0.90 and precision of 0.89 were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Edge-preserving Intra Depth Coding based on Context-coding and H.264/AVC

DEFF Research Database (Denmark)

Zamarin, Marco; Salmistraro, Matteo; Forchhammer, Søren

2013-01-01

Depth map coding plays a crucial role in 3D Video communication systems based on the “Multi-view Video plus Depth” representation as view synthesis performance is strongly affected by the accuracy of depth information, especially at edges in the depth map image. In this paper an efficient algorithm...... for edge-preserving intra depth compression based on H.264/AVC is presented. The proposed method introduces a new Intra mode specifically targeted to depth macroblocks with arbitrarily shaped edges, which are typically not efficiently represented by DCT. Edge macroblocks are partitioned into two regions...... each approximated by a flat surface. Edge information is encoded by means of contextcoding with an adaptive template. As a novel element, the proposed method allows exploiting the edge structure of previously encoded edge macroblocks during the context-coding step to further increase compression...

Research on the transfer learning of the vehicle logo recognition

Science.gov (United States)

Zhao, Wei

2017-08-01

The Convolutional Neural Network of Deep Learning has been a huge success in the field of image intelligent transportation system can effectively solve the traffic safety, congestion, vehicle management and other problems of traffic in the city. Vehicle identification is a vital part of intelligent transportation, and the effective information in vehicles is of great significance to vehicle identification. With the traffic system on the vehicle identification technology requirements are getting higher and higher, the vehicle as an important type of vehicle information, because it should not be removed, difficult to change and other features for vehicle identification provides an important method. The current vehicle identification recognition (VLR) is mostly used to extract the characteristics of the method of classification, which for complex classification of its generalization ability to be some constraints, if the use of depth learning technology, you need a lot of training samples. In this paper, the method of convolution neural network based on transfer learning can solve this problem effectively, and it has important practical application value in the task of vehicle mark recognition.

Multiple-source multiple-harmonic active vibration control of variable section cylindrical structures: A numerical study

Science.gov (United States)

Liu, Jinxin; Chen, Xuefeng; Gao, Jiawei; Zhang, Xingwu

2016-12-01

Air vehicles, space vehicles and underwater vehicles, the cabins of which can be viewed as variable section cylindrical structures, have multiple rotational vibration sources (e.g., engines, propellers, compressors and motors), making the spectrum of noise multiple-harmonic. The suppression of such noise has been a focus of interests in the field of active vibration control (AVC). In this paper, a multiple-source multiple-harmonic (MSMH) active vibration suppression algorithm with feed-forward structure is proposed based on reference amplitude rectification and conjugate gradient method (CGM). An AVC simulation scheme called finite element model in-loop simulation (FEMILS) is also proposed for rapid algorithm verification. Numerical studies of AVC are conducted on a variable section cylindrical structure based on the proposed MSMH algorithm and FEMILS scheme. It can be seen from the numerical studies that: (1) the proposed MSMH algorithm can individually suppress each component of the multiple-harmonic noise with an unified and improved convergence rate; (2) the FEMILS scheme is convenient and straightforward for multiple-source simulations with an acceptable loop time. Moreover, the simulations have similar procedure to real-life control and can be easily extended to physical model platform.

Low complexity video encoding for UAV inspection

DEFF Research Database (Denmark)

Søgaard, Jacob; Zhang, Ruo; Forchhammer, Søren

2016-01-01

In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC and anal......In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC...... for UAV infrared (IR) video are also provided....

Predicting vehicle fuel consumption patterns using floating vehicle data.

Science.gov (United States)

Du, Yiman; Wu, Jianping; Yang, Senyan; Zhou, Liutong

2017-09-01

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers' information and vehicles' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model. Copyright © 2017. Published by Elsevier B.V.

A CABAC codec of H.264AVC with secure arithmetic coding

Science.gov (United States)

Neji, Nihel; Jridi, Maher; Alfalou, Ayman; Masmoudi, Nouri

2013-02-01

This paper presents an optimized H.264/AVC coding system for HDTV displays based on a typical flow with high coding efficiency and statics adaptivity features. For high quality streaming, the codec uses a Binary Arithmetic Encoding/Decoding algorithm with high complexity and a JVCE (Joint Video compression and encryption) scheme. In fact, particular attention is given to simultaneous compression and encryption applications to gain security without compromising the speed of transactions [1]. The proposed design allows us to encrypt the information using a pseudo-random number generator (PRNG). Thus we achieved the two operations (compression and encryption) simultaneously and in a dependent manner which is a novelty in this kind of architecture. Moreover, we investigated the hardware implementation of CABAC (Context-based adaptive Binary Arithmetic Coding) codec. The proposed architecture is based on optimized binarizer/de-binarizer to handle significant pixel rates videos with low cost and high performance for most frequent SEs. This was checked using HD video frames. The obtained synthesis results using an FPGA (Xilinx's ISE) show that our design is relevant to code main profile video stream.

3-D Vision Techniques for Autonomous Vehicles

Science.gov (United States)

1988-08-01

TITLE (Include Security Classification) W 3-D Vision Techniques for Autonomous Vehicles 12 PERSONAL AUTHOR(S) Martial Hebert, Takeo Kanade, inso Kweoni... Autonomous Vehicles Martial Hebert, Takeo Kanade, Inso Kweon CMU-RI-TR-88-12 The Robotics Institute Carnegie Mellon University Acession For Pittsburgh

Sensor Architecture and Task Classification for Agricultural Vehicles and Environments

Directory of Open Access Journals (Sweden)

Francisco Rovira-Más

2010-12-01

Full Text Available The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way.

Aortic valve calcification - a commonly observed but frequently ignored finding during CT scanning of the chest.

Science.gov (United States)

Raju, Prashanth; Sallomi, David; George, Bindu; Patel, Hitesh; Patel, Nikhil; Lloyd, Guy

2012-06-01

To describe the frequency and severity of Aortic valve calcification (AVC) in an unselected cohort of patients undergoing chest CT scanning and to assess the frequency with which AVC was being reported in the radiology reports. Consecutive CT scan images of the chest and the radiological reports (December 2009 to May 2010) were reviewed at the district general hospital (DGH). AVC on CT scan was visually graded on a scale ranging from 0 to IV (0 = no calcification, IV = severe calcification). Total of 416 (232 male; 184 female) CT chest scans [Contrast enhanced 302 (72%), unenhanced 114 (28%)] were reviewed. Mean age was 70.55 ± 11.48 years. AVC in CT scans was identified in 95 of the 416 patients (22.83%). AVC classification was as follows: Grade I: 60 (63.15%), Grade II: 22 (23.15%), Grade III: 9 (9.47%), Grade IV: 4 (4.21%). Only one CT report mentioned AVC. Only 31 of 95 AVC had Transthoracic echocardiogram (TTE). The interval time between CT scan and TTE was variable.   Aortic valve calcification in CT chest scans is a common finding and studies have shown that it is strongly related to the presence and severity of aortic valve disease. As CT scans are considered as a valuable additional screening tool for detection of aortic stenosis, AVC should always be commented upon in the radiology reports. Furthermore, patients with at least Grade III and IV AVC should be sent for TTE. © 2012 Blackwell Publishing Ltd.

Comparative assessment of H.265/MPEG-HEVC, VP9, and H.264/MPEG-AVC encoders for low-delay video applications

Science.gov (United States)

Grois, Dan; Marpe, Detlev; Nguyen, Tung; Hadar, Ofer

2014-09-01

The popularity of low-delay video applications dramatically increased over the last years due to a rising demand for realtime video content (such as video conferencing or video surveillance), and also due to the increasing availability of relatively inexpensive heterogeneous devices (such as smartphones and tablets). To this end, this work presents a comparative assessment of the two latest video coding standards: H.265/MPEG-HEVC (High-Efficiency Video Coding), H.264/MPEG-AVC (Advanced Video Coding), and also of the VP9 proprietary video coding scheme. For evaluating H.264/MPEG-AVC, an open-source x264 encoder was selected, which has a multi-pass encoding mode, similarly to VP9. According to experimental results, which were obtained by using similar low-delay configurations for all three examined representative encoders, it was observed that H.265/MPEG-HEVC provides significant average bit-rate savings of 32.5%, and 40.8%, relative to VP9 and x264 for the 1-pass encoding, and average bit-rate savings of 32.6%, and 42.2% for the 2-pass encoding, respectively. On the other hand, compared to the x264 encoder, typical low-delay encoding times of the VP9 encoder, are about 2,000 times higher for the 1-pass encoding, and are about 400 times higher for the 2-pass encoding.

Multiple descriptions based on multirate coding for JPEG 2000 and H.264/AVC.

Science.gov (United States)

Tillo, Tammam; Baccaglini, Enrico; Olmo, Gabriella

2010-07-01

Multiple description coding (MDC) makes use of redundant representations of multimedia data to achieve resiliency. Descriptions should be generated so that the quality obtained when decoding a subset of them only depends on their number and not on the particular received subset. In this paper, we propose a method based on the principle of encoding the source at several rates, and properly blending the data encoded at different rates to generate the descriptions. The aim is to achieve efficient redundancy exploitation, and easy adaptation to different network scenarios by means of fine tuning of the encoder parameters. We apply this principle to both JPEG 2000 images and H.264/AVC video data. We consider as the reference scenario the distribution of contents on application-layer overlays with multiple-tree topology. The experimental results reveal that our method favorably compares with state-of-art MDC techniques.

Vision-based Vehicle Detection Survey

Directory of Open Access Journals (Sweden)

Alex David S

2016-03-01

Full Text Available Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

Current challenges in autonomous vehicle development

Science.gov (United States)

Connelly, J.; Hong, W. S.; Mahoney, R. B., Jr.; Sparrow, D. A.

2006-05-01

The field of autonomous vehicles is a rapidly growing one, with significant interest from both government and industry sectors. Autonomous vehicles represent the intersection of artificial intelligence (AI) and robotics, combining decision-making with real-time control. Autonomous vehicles are desired for use in search and rescue, urban reconnaissance, mine detonation, supply convoys, and more. The general adage is to use robots for anything dull, dirty, dangerous or dumb. While a great deal of research has been done on autonomous systems, there are only a handful of fielded examples incorporating machine autonomy beyond the level of teleoperation, especially in outdoor/complex environments. In an attempt to assess and understand the current state of the art in autonomous vehicle development, a few areas where unsolved problems remain became clear. This paper outlines those areas and provides suggestions for the focus of science and technology research. The first step in evaluating the current state of autonomous vehicle development was to develop a definition of autonomy. A number of autonomy level classification systems were reviewed. The resulting working definitions and classification schemes used by the authors are summarized in the opening sections of the paper. The remainder of the report discusses current approaches and challenges in decision-making and real-time control for autonomous vehicles. Suggested research focus areas for near-, mid-, and long-term development are also presented.

Real-time, resource-constrained object classification on a micro-air vehicle

Science.gov (United States)

Buck, Louis; Ray, Laura

2013-12-01

A real-time embedded object classification algorithm is developed through the novel combination of binary feature descriptors, a bag-of-visual-words object model and the cortico-striatal loop (CSL) learning algorithm. The BRIEF, ORB and FREAK binary descriptors are tested and compared to SIFT descriptors with regard to their respective classification accuracies, execution times, and memory requirements when used with CSL on a 12.6 g ARM Cortex embedded processor running at 800 MHz. Additionally, the effect of x2 feature mapping and opponent-color representations used with these descriptors is examined. These tests are performed on four data sets of varying sizes and difficulty, and the BRIEF descriptor is found to yield the best combination of speed and classification accuracy. Its use with CSL achieves accuracies between 67% and 95% of those achieved with SIFT descriptors and allows for the embedded classification of a 128x192 pixel image in 0.15 seconds, 60 times faster than classification with SIFT. X2 mapping is found to provide substantial improvements in classification accuracy for all of the descriptors at little cost, while opponent-color descriptors are offer accuracy improvements only on colorful datasets.

Temporal Scalability through Adaptive -Band Filter Banks for Robust H.264/MPEG-4 AVC Video Coding

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Pau G

2006-01-01

Full Text Available This paper presents different structures that use adaptive -band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

Statistical classification of road pavements using near field vehicle rolling noise measurements.

Science.gov (United States)

Paulo, Joel Preto; Coelho, J L Bento; Figueiredo, Mário A T

2010-10-01

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Feature Extraction in Radar Target Classification

Directory of Open Access Journals (Sweden)

Z. Kus

1999-09-01

Full Text Available This paper presents experimental results of extracting features in the Radar Target Classification process using the J frequency band pulse radar. The feature extraction is based on frequency analysis methods, the discrete-time Fourier Transform (DFT and Multiple Signal Characterisation (MUSIC, based on the detection of Doppler effect. The analysis has turned to the preference of DFT with implemented Hanning windowing function. We assumed to classify targets-vehicles into two classes, the wheeled vehicle and tracked vehicle. The results show that it is possible to classify them only while moving. The feature of the class results from a movement of moving parts of the vehicle. However, we have not found any feature to classify the wheeled and tracked vehicles while non-moving, although their engines are on.

Vehicle Detection and Classification Using Passive Infrared Sensing

KAUST Repository

Odat, Enas M.; Mousa, Mustafa; Claudel, Christian

2015-01-01

or multiple remote temperature sensors. We show an implementation of this device, and illustrate its performance in both traffic flow sensing. Field data shows that the sensor can detect vehicles with a 99% accuracy, in addition to estimating their speed

Towards autonomous vehicular clouds

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Stephan Olariu

2011-09-01

Full Text Available The dawn of the 21st century has seen a growing interest in vehicular networking and its myriad potential applications. The initial view of practitioners and researchers was that radio-equipped vehicles could keep the drivers informed about potential safety risks and increase their awareness of road conditions. The view then expanded to include access to the Internet and associated services. This position paper proposes and promotes a novel and more comprehensive vision namely, that advances in vehicular networks, embedded devices and cloud computing will enable the formation of autonomous clouds of vehicular computing, communication, sensing, power and physical resources. Hence, we coin the term, autonomous vehicular clouds (AVCs. A key feature distinguishing AVCs from conventional cloud computing is that mobile AVC resources can be pooled dynamically to serve authorized users and to enable autonomy in real-time service sharing and management on terrestrial, aerial, or aquatic pathways or theaters of operations. In addition to general-purpose AVCs, we also envision the emergence of specialized AVCs such as mobile analytics laboratories. Furthermore, we envision that the integration of AVCs with ubiquitous smart infrastructures including intelligent transportation systems, smart cities and smart electric power grids will have an enormous societal impact enabling ubiquitous utility cyber-physical services at the right place, right time and with right-sized resources.

The availability of unmanned air vehicles: a post-case study

NARCIS (Netherlands)

Smith, M.A.J.; Dekker, R.; Kos, J.; Hontelez, J.A.M.

2001-01-01

An Unmanned Air Vehicle (UAV) is an unmanned, remotely controlled, small air vehicle. It has an important role in antisurface warfare. This implies over-the-horizon detection, classification, targeting and battle damage assessment. To perform these tasks several UAVs are needed to assist or

Fast mode decision based on human noticeable luminance difference and rate distortion cost for H.264/AVC

Science.gov (United States)

Li, Mian-Shiuan; Chen, Mei-Juan; Tai, Kuang-Han; Sue, Kuen-Liang

2013-12-01

This article proposes a fast mode decision algorithm based on the correlation of the just-noticeable-difference (JND) and the rate distortion cost (RD cost) to reduce the computational complexity of H.264/AVC. First, the relationship between the average RD cost and the number of JND pixels is established by Gaussian distributions. Thus, the RD cost of the Inter 16 × 16 mode is compared with the predicted thresholds from these models for fast mode selection. In addition, we use the image content, the residual data, and JND visual model for horizontal/vertical detection, and then utilize the result to predict the partition in a macroblock. From the experimental results, a greater time saving can be achieved while the proposed algorithm also maintains performance and quality effectively.

Analysis of the ECO Test Results for Vehicles in the Republic of Croatia

Directory of Open Access Journals (Sweden)

Dražen Kovačević

2007-01-01

Full Text Available The work presents the classification of engines for theECO test requirement at the technical inspection of vehicles.The types of harmful components in the raw emission of internalcombustion engine are listed and described, as well asthe possibilities of their reduction. In accordance with theclassification of engines for the ECO test requirements the allowedvalues of harmful components according to the legallystipulated standards in Croatia are given. The study includedthe number of vehicles that passed the ECO test at technicalinspection in 2004 and these were then statistically processedand analyzed according to the type of vehicle, classification ofcar engines for the ECO test requirements and the year ofproduction.

Hybrid drive train technologies for vehicles

NARCIS (Netherlands)

Hofman, T.; Folkson, R.

This chapter provides a classification of electric hybrid systems for cars and describes the conflicting design challenges involved in designing advanced vehicle propulsion systems. In addition, the chapter provides an analysis of the solution methods currently provided in literature on the coupled

Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.

Science.gov (United States)

Tagliasacchi, Marco; Valenzise, Giuseppe; Tubaro, Stefano

2008-07-01

Consider the problem of transmitting multiple video streams to fulfill a constant bandwidth constraint. The available bit budget needs to be distributed across the sequences in order to meet some optimality criteria. For example, one might want to minimize the average distortion or, alternatively, minimize the distortion variance, in order to keep almost constant quality among the encoded sequences. By working in the rho-domain, we propose a low-delay rate allocation scheme that, at each time instant, provides a closed form solution for either the aforementioned problems. We show that minimizing the distortion variance instead of the average distortion leads, for each of the multiplexed sequences, to a coding penalty less than 0.5 dB, in terms of average PSNR. In addition, our analysis provides an explicit relationship between model parameters and this loss. In order to smooth the distortion also along time, we accommodate a shared encoder buffer to compensate for rate fluctuations. Although the proposed scheme is general, and it can be adopted for any video and image coding standard, we provide experimental evidence by transcoding bitstreams encoded using the state-of-the-art H.264/AVC standard. The results of our simulations reveal that is it possible to achieve distortion smoothing both in time and across the sequences, without sacrificing coding efficiency.

Brake fault diagnosis using Clonal Selection Classification Algorithm (CSCA – A statistical learning approach

Directory of Open Access Journals (Sweden)

R. Jegadeeshwaran

2015-03-01

Full Text Available In automobile, brake system is an essential part responsible for control of the vehicle. Any failure in the brake system impacts the vehicle's motion. It will generate frequent catastrophic effects on the vehicle cum passenger's safety. Thus the brake system plays a vital role in an automobile and hence condition monitoring of the brake system is essential. Vibration based condition monitoring using machine learning techniques are gaining momentum. This study is one such attempt to perform the condition monitoring of a hydraulic brake system through vibration analysis. In this research, the performance of a Clonal Selection Classification Algorithm (CSCA for brake fault diagnosis has been reported. A hydraulic brake system test rig was fabricated. Under good and faulty conditions of a brake system, the vibration signals were acquired using a piezoelectric transducer. The statistical parameters were extracted from the vibration signal. The best feature set was identified for classification using attribute evaluator. The selected features were then classified using CSCA. The classification accuracy of such artificial intelligence technique has been compared with other machine learning approaches and discussed. The Clonal Selection Classification Algorithm performs better and gives the maximum classification accuracy (96% for the fault diagnosis of a hydraulic brake system.

Vehicle Travel Information System (VTRIS) - Data Download Tool

Data.gov (United States)

Department of Transportation — The VTRIS W-Tables are designed to provide a standard format for presenting the outcome of the Vehicle Weighing and Classification efforts at truck weigh sites. The...

Track classification within wireless sensor network

Science.gov (United States)

Doumerc, Robin; Pannetier, Benjamin; Moras, Julien; Dezert, Jean; Canevet, Loic

2017-05-01

In this paper, we present our study on track classification by taking into account environmental information and target estimated states. The tracker uses several motion model adapted to different target dynamics (pedestrian, ground vehicle and SUAV, i.e. small unmanned aerial vehicle) and works in centralized architecture. The main idea is to explore both: classification given by heterogeneous sensors and classification obtained with our fusion module. The fusion module, presented in his paper, provides a class on each track according to track location, velocity and associated uncertainty. To model the likelihood on each class, a fuzzy approach is used considering constraints on target capability to move in the environment. Then the evidential reasoning approach based on Dempster-Shafer Theory (DST) is used to perform a time integration of this classifier output. The fusion rules are tested and compared on real data obtained with our wireless sensor network.In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of this system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

O papel do enfermeiro como educador junto a cuidadores familiares de pessoas com AVC El papel del enfermero como educador de cuidadores familiares de personas con AVC The nurse's role as an educator toward people who care for BVA patients

Directory of Open Access Journals (Sweden)

Silvia Cristina Mangini Bocchi

2004-10-01

Full Text Available Trata-se de uma pesquisa do tipo bibliográfico com a finalidade de fazer uma análise temática da produção do conhecimento em periódicos, sobre o papel do enfermeiro como educador junto a cuidadores familiares de pessoas com AVC (Acidente Vascular Cerebral. O corpus de análise reuniu artigos localizados nas décadas de 80 e 90, a partir das bases de dados Medline, Lilacs e Cinahl. A análise de conteúdo foi o referencial metodológico que permitiu organizar o conhecimento em duas categorias: a intervenção educacional na fase aguda e o suporte após a alta hospitalar.Este trabajo es una investigación bibliográfica que tiene la finalidad de hacer un análisis temático de producción del conocimiento en periódicos, sobre el papel del enfermero educador de cuidadores familiares de personas con AVC (Accidente Vascular Cerebral. El corpus de análisis reunió artículos realizados en las décadas de 80 y 90 a partir de las bases de datos Mediline, Lilacs y Cinahl. El análisis del contenido fue el referencial teórico que permitió organizar el conocimiento en dos categorías: la intervención educativa en la fase aguda y el soporte después del alta hospitalario.This article was written based on bibliographical research aiming at making a thematic analysis of the production of knowledge in newspapers and magazines about the nurse's role as an educator toward people who care for BVA (brain vascular accident patients. The analysis gathered articles published in the 80's and 90's, from the Medline, Lilacs and Cinahl databases. Content analysis was the methodological background that allowed the organization of knowledge in two categories: educational intervention in the acute stage and the post-discharge support.

Network-based H.264/AVC whole frame loss visibility model and frame dropping methods.

Science.gov (United States)

Chang, Yueh-Lun; Lin, Ting-Lan; Cosman, Pamela C

2012-08-01

We examine the visual effect of whole frame loss by different decoders. Whole frame losses are introduced in H.264/AVC compressed videos which are then decoded by two different decoders with different common concealment effects: frame copy and frame interpolation. The videos are seen by human observers who respond to each glitch they spot. We found that about 39% of whole frame losses of B frames are not observed by any of the subjects, and over 58% of the B frame losses are observed by 20% or fewer of the subjects. Using simple predictive features which can be calculated inside a network node with no access to the original video and no pixel level reconstruction of the frame, we developed models which can predict the visibility of whole B frame losses. The models are then used in a router to predict the visual impact of a frame loss and perform intelligent frame dropping to relieve network congestion. Dropping frames based on their visual scores proves superior to random dropping of B frames.

Evaluation of a buried cable roadside animal detection system.

Science.gov (United States)

2015-06-01

Animal-vehicle collisions (AVC) are a concern for departments of transportation as they translate into hundreds of : human fatalities and billions of dollars in property damage each year. A recently published report states that the Virginia : Departm...

Tomada de decisão no IGT: estudo de caso pós-AVC de hemisfério direito versus esquerdo Toma de decisión en el IGT: estudio de caso post-AVC de hemisferio derecho versus isquierdo Decision making in IGT: a case study of post-CVA of left versus right hemisphere

Directory of Open Access Journals (Sweden)

Caroline de Oliveira Cardoso

2012-04-01

Full Text Available Investigou comparativamente o processo de tomada de decisão de dois adultos pós-AVC unilateral e verificar o papel da lateralidade hemisférica na performance do Iowa Gambling Task (IGT. Participaram um adulto com lesão de hemisfério direito (LHD e outro com lesão de hemisfério esquerdo (LHE, ambos pós-AVC isquêmico subcortical. O IGT foi utilizado para avaliar a tomada de decisão. Os pacientes apresentaram um desempenho adequado no IGT, demonstrando ter uma boa capacidade de tomar decisão. No entanto, somente o paciente com LHD apresentou uma curva sugestiva de aprendizagem. Esses dados indicam que uma lesão subcortical independente do hemisfério pode não interferir no desempenho do IGT. Sugere-se que estudos de grupos sejam conduzidos buscando comparar pacientes com lesão frontal e não-frontal, auxiliando na caracterização do processo de tomada de decisão na população com lesão vascular unilateral.Este estudio investiga comparativamente el proceso de toma de decisión de dos adultos post-AVC unilateral y verifica el papel de la lateralidad hemisférica en la performance del Iowa Gambling Task (IGT. Participaron un adulto con lesión de hemisferio derecho (LHD y otro con lesión de hemisferio izquierdo (LHE, ambos post-AVC isquémico subcortical. El IGT fue utilizado para evaluar la toma de decisión. Los pacientes presentaron un desempeño adecuado en el IGT, demostrando una buena capacidad de tomar decisiones. Sin embargo, solamente el paciente con LHD presentó una curva sugestiva de aprendizaje. Esos datos indican que una lesión subcortical independiente del hemisferio puede no interferir en el desempeño del IGT. Se sugiere que estudios comparativos de grupos sean conducidos buscando comparar pacientes con lesión frontal y no-frontal, auxiliando en la caracterización del proceso de toma de decisión en la población con lesión vascular unilateral.This study aimed at conducting a comparative investigation of the

Kardashev’s classification at 50+: A fine vehicle with room for improvement

Directory of Open Access Journals (Sweden)

Ćirković M.M.

2015-01-01

Full Text Available We review the history and status of the famous classification of extraterrestrial civilizations given by the great Russian astrophysicist Nikolai Semenovich Kardashev, roughly half a century after it has been proposed. While Kardashev’s classification (or Kardashev’s scale has often been seen as oversimplified, and multiple improvements, refinements, and alternatives to it have been suggested, it is still one of the major tools for serious theoretical investigation of SETI issues. During these 50+ years, several attempts at modifying or reforming the classification have been made; we review some of them here, together with presenting some of the scenarios which present difficulties to the standard version. Recent results in both theoretical and observational SETI studies, especially the ˆG infrared survey (2014-2015, have persuasively shown that the emphasis on detectability inherent in Kardashev’s classification obtains new significance and freshness. Several new movements and conceptual frameworks, such as the Dysonian SETI, tally extremely well with these developments. So, the apparent simplicity of the classification is highly deceptive: Kardashev’s work offers a wealth of still insufficiently studied methodological and epistemological ramifications and it remains, in both letter and spirit, perhaps the worthiest legacy of the SETI “founding fathers”. [Projekat Ministarstva nauke Republike Srbije, br. ON176021

Testing an integrated PDA-GPS system to collect standardized animal carcass removal data on Virginia roadways.

Science.gov (United States)

2008-01-01

Animal-vehicle collisions (AVCs) have a growing impact in the United States in terms of safety, economic loss, and species conservation. According to estimates from insurance claims, Virginia has consistently ranked as one of the top seven states for...

Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

Directory of Open Access Journals (Sweden)

Rui Sun

2016-08-01

Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

PROSPECÇÃO EM JOGOS SÉRIOS PARA REABILITAÇÃO DE PACIENTES PÓS-AVC

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Eric Moura Guimarães

2013-06-01

Full Text Available AVC ou acidente vascular cerebral, ocorre quando há uma obstrução ou rompimento de uma das artérias que transportam sangue ao cérebro e as principais causas são a hipertensão, o tabagismo ou diabetes. Hoje é uma das principais causas de morte e sequelas no mundo e tem uma grande atenção da comunidade fisioterapeuta a fim de melhorar a vida das pessoas por meio de métodos de recuperação inovadores como o uso de jogos sérios « Serious Game », por exemplo. O objetivo deste artigo é realizar uma prospecção para o conhecimento do estado da técnica do que existe dessas tecnologias no mundo. A pesquisa foi realizada no Banco Europeu de Patentes(EPO, no Banco da Organização Mundial de Propriedade Intelectual(WIPO e no Banco Americano de Marcas e Patentes(UPSTO.

Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning

Directory of Open Access Journals (Sweden)

Yingfeng Cai

2017-01-01

Full Text Available Discriminative tracking methods use binary classification to discriminate between the foreground and background and have achieved some useful results. However, the use of labeled training samples is insufficient for them to achieve accurate tracking. Hence, discriminative classifiers must use their own classification results to update themselves, which may lead to feedback-induced tracking drift. To overcome these problems, we propose a semisupervised tracking algorithm that uses deep representation and transfer learning. Firstly, a 2D multilayer deep belief network is trained with a large amount of unlabeled samples. The nonlinear mapping point at the top of this network is subtracted as the feature dictionary. Then, this feature dictionary is utilized to transfer train and update a deep tracker. The positive samples for training are the tracked vehicles, and the negative samples are the background images. Finally, a particle filter is used to estimate vehicle position. We demonstrate experimentally that our proposed vehicle tracking algorithm can effectively restrain drift while also maintaining the adaption of vehicle appearance. Compared with similar algorithms, our method achieves a better tracking success rate and fewer average central-pixel errors.

Non-tables look-up search algorithm for efficient H.264/AVC context-based adaptive variable length coding decoding

Science.gov (United States)

Han, Yishi; Luo, Zhixiao; Wang, Jianhua; Min, Zhixuan; Qin, Xinyu; Sun, Yunlong

2014-09-01

In general, context-based adaptive variable length coding (CAVLC) decoding in H.264/AVC standard requires frequent access to the unstructured variable length coding tables (VLCTs) and significant memory accesses are consumed. Heavy memory accesses will cause high power consumption and time delays, which are serious problems for applications in portable multimedia devices. We propose a method for high-efficiency CAVLC decoding by using a program instead of all the VLCTs. The decoded codeword from VLCTs can be obtained without any table look-up and memory access. The experimental results show that the proposed algorithm achieves 100% memory access saving and 40% decoding time saving without degrading video quality. Additionally, the proposed algorithm shows a better performance compared with conventional CAVLC decoding, such as table look-up by sequential search, table look-up by binary search, Moon's method, and Kim's method.

Optimized bit extraction using distortion modeling in the scalable extension of H.264/AVC.

Science.gov (United States)

Maani, Ehsan; Katsaggelos, Aggelos K

2009-09-01

The newly adopted scalable extension of H.264/AVC video coding standard (SVC) demonstrates significant improvements in coding efficiency in addition to an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. Due to the complicated hierarchical prediction structure of the SVC and the concept of key pictures, content-aware rate adaptation of SVC bit streams to intermediate bit rates is a nontrivial task. The concept of quality layers has been introduced in the design of the SVC to allow for fast content-aware prioritized rate adaptation. However, existing quality layer assignment methods are suboptimal and do not consider all network abstraction layer (NAL) units from different layers for the optimization. In this paper, we first propose a technique to accurately and efficiently estimate the quality degradation resulting from discarding an arbitrary number of NAL units from multiple layers of a bitstream by properly taking drift into account. Then, we utilize this distortion estimation technique to assign quality layers to NAL units for a more efficient extraction. Experimental results show that a significant gain can be achieved by the proposed scheme.

Length based vehicle classification on freeways from single loop detectors.

Science.gov (United States)

2009-10-15

Roadway usage, particularly by large vehicles, is one of the fundamental factors determining the lifespan : of highway infrastructure, e.g., as evidenced by the federally mandated Highway Performance : Monitoring System (HPMS). But the complexity of ...

Robust vehicle detection in aerial images based on salient region selection and superpixel classification

Science.gov (United States)

Sahli, Samir; Duval, Pierre-Luc; Sheng, Yunlong; Lavigne, Daniel A.

2011-05-01

For detecting vehicles in large scale aerial images we first used a non-parametric method proposed recently by Rosin to define the regions of interest, where the vehicles appear with dense edges. The saliency map is a sum of distance transforms (DT) of a set of edges maps, which are obtained by a threshold decomposition of the gradient image with a set of thresholds. A binary mask for highlighting the regions of interest is then obtained by a moment-preserving thresholding of the normalized saliency map. Secondly, the regions of interest were over-segmented by the SLIC superpixels proposed recently by Achanta et al. to cluster pixels into the color constancy sub-regions. In the aerial images of 11.2 cm/pixel resolution, the vehicles in general do not exceed 20 x 40 pixels. We introduced a size constraint to guarantee no superpixels exceed the size of a vehicle. The superpixels were then classified to vehicle or non-vehicle by the Support Vector Machine (SVM), in which the Scale Invariant Feature Transform (SIFT) features and the Linear Binary Pattern (LBP) texture features were used. Both features were extracted at two scales with two size patches. The small patches capture local structures and the larger patches include the neighborhood information. Preliminary results show a significant gain in the detection. The vehicles were detected with a dense concentration of the vehicle-class superpixels. Even dark color cars were successfully detected. A validation process will follow to reduce the presence of isolated false alarms in the background.

Object-based detection of vehicles using combined optical and elevation data

Science.gov (United States)

Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

2018-02-01

The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consists of three consecutive stages: candidate identification, classification, and single vehicle extraction. Unlike in most previous approaches, fusion of both data sources is strongly pursued at all stages. While the first stage utilizes the fact that most man-made objects are rectangular in shape, the second and third stages employ machine learning techniques combined with specific features. The stages are designed to handle multiple sensor input, which results in a significant improvement. A detailed evaluation shows the benefits of our workflow, which includes hand-tailored features; even in comparison with classification approaches based on Convolutional Neural Networks, which are state of the art in computer vision, we could obtain a comparable or superior performance (F1 score of 0.96-0.94).

Unmanned Ground Vehicle Perception Using Thermal Infrared Cameras

Science.gov (United States)

Rankin, Arturo; Huertas, Andres; Matthies, Larry; Bajracharya, Max; Assad, Christopher; Brennan, Shane; Bellut, Paolo; Sherwin, Gary

2011-01-01

TIR cameras can be used for day/night Unmanned Ground Vehicle (UGV) autonomous navigation when stealth is required. The quality of uncooled TIR cameras has significantly improved over the last decade, making them a viable option at low speed Limiting factors for stereo ranging with uncooled LWIR cameras are image blur and low texture scenes TIR perception capabilities JPL has explored includes: (1) single and dual band TIR terrain classification (2) obstacle detection (pedestrian, vehicle, tree trunks, ditches, and water) (3) perception thru obscurants

Vehicle Detection and Classification Using Passive Infrared Sensing

KAUST Repository

Odat, Enas M.

2015-10-19

We propose a new sensing device that can simultaneously monitor urban traffic congestion and another phenomenon of interest (flash floods on the present case). This sensing device is based on the combination of an ultrasonic rangefinder with one or multiple remote temperature sensors. We show an implementation of this device, and illustrate its performance in both traffic flow sensing. Field data shows that the sensor can detect vehicles with a 99% accuracy, in addition to estimating their speed and classifying them in function of their length. The same sensor can also monitor urban water levels with an accuracy of less than 2 cm.

Colour based off-road environment and terrain type classification

NARCIS (Netherlands)

Jansen, P.; Mark, W. van der; Heuvel, J.C. van den; Groen, F.C.A.

2005-01-01

Terrain classification is an important problem that still remains to be solved for off-road autonomous robot vehicle guidance. Often, obstacle detection systems are used which cannot distinguish between solid obstacles such as rocks or soft obstacles such as tall patches of grass. Terrain

Traffic and Quality Characterization of the H.264/AVC Scalable Video Coding Extension

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Geert Van der Auwera

2008-01-01

Full Text Available The recent scalable video coding (SVC extension to the H.264/AVC video coding standard has unprecedented compression efficiency while supporting a wide range of scalability modes, including temporal, spatial, and quality (SNR scalability, as well as combined spatiotemporal SNR scalability. The traffic characteristics, especially the bit rate variabilities, of the individual layer streams critically affect their network transport. We study the SVC traffic statistics, including the bit rate distortion and bit rate variability distortion, with long CIF resolution video sequences and compare them with the corresponding MPEG-4 Part 2 traffic statistics. We consider (i temporal scalability with three temporal layers, (ii spatial scalability with a QCIF base layer and a CIF enhancement layer, as well as (iii quality scalability modes FGS and MGS. We find that the significant improvement in RD efficiency of SVC is accompanied by substantially higher traffic variabilities as compared to the equivalent MPEG-4 Part 2 streams. We find that separately analyzing the traffic of temporal-scalability only encodings gives reasonable estimates of the traffic statistics of the temporal layers embedded in combined spatiotemporal encodings and in the base layer of combined FGS-temporal encodings. Overall, we find that SVC achieves significantly higher compression ratios than MPEG-4 Part 2, but produces unprecedented levels of traffic variability, thus presenting new challenges for the network transport of scalable video.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

Science.gov (United States)

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-02-19

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

Transportation Modes Classification Using Sensors on Smartphones

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Shih-Hau Fang

2016-08-01

Full Text Available This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including decision trees, K-nearest neighbor, and support vector machine to classify the user’s transportation and vehicular modes. In the experiments, we discussed and compared the performance from different perspectives including the accuracy for both modes, the executive time, and the model size. Results show that the proposed features enhance the accuracy, in which the support vector machine provides the best performance in classification accuracy whereas it consumes the largest prediction time. This paper also investigates the vehicle classification mode and compares the results with that of the transportation modes.

Lane-Level Road Information Mining from Vehicle GPS Trajectories Based on Naïve Bayesian Classification

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Luliang Tang

2015-11-01

Full Text Available In this paper, we propose a novel approach for mining lane-level road network information from low-precision vehicle GPS trajectories (MLIT, which includes the number and turn rules of traffic lanes based on naïve Bayesian classification. First, the proposed method (MLIT uses an adaptive density optimization method to remove outliers from the raw GPS trajectories based on their space-time distribution and density clustering. Second, MLIT acquires the number of lanes in two steps. The first step establishes a naïve Bayesian classifier according to the trace features of the road plane and road profiles and the real number of lanes, as found in the training samples. The second step confirms the number of lanes using test samples in reference to the naïve Bayesian classifier using the known trace features of test sample. Third, MLIT infers the turn rules of each lane through tracking GPS trajectories. Experiments were conducted using the GPS trajectories of taxis in Wuhan, China. Compared with human-interpreted results, the automatically generated lane-level road network information was demonstrated to be of higher quality in terms of displaying detailed road networks with the number of lanes and turn rules of each lane.

Classification deficits in Alzheimer's disease with special reference to living and nonliving things.

Science.gov (United States)

Montanes, P; Goldblum, M C; Boller, F

1996-08-01

The present study was conducted to assess the hypothesis that visual similarity between exemplars within a semantic category may affect differentially the recognition process of living and nonliving things, according to task demands, in patients with semantic memory disorders. Thirty-nine Alzheimer's patients and 39 normal elderly subjects were presented with a task in which they had to classify pictures and words, depicting either living or nonliving things, at two levels of classification: subordinate (e.g., mammals versus birds or tools versus vehicles) and attribute (e.g., wild versus domestic animals or fast versus slow vehicles). Contrary to previous results (Montañes, Goldblum, & Boller, 1995) in a naming task, but as expected, living things were better classified than nonliving ones by both controls and patients. As expected, classifications at the subordinate level also gave rise to better performance than classifications at the attribute level. Although (and somewhat unexpectedly) no advantage of picture over word classification emerged, some effects consistent with the hypothesis that visual similarity affects picture classification emerged, in particular within a subgroup of patients with predominant verbal deficits and the most severe semantic memory disorders. This subgroup obtained a better score on classification of pictures than of words depicting living items (that share many visual features) when classification is at the subordinate level (for which visual similarity is a reliable clue to classification), but met with major difficulties when classifying those pictures at the attribute level (for which shared visual features are not reliable clues to classification). These results emphasize the fact that some "normal" effects specific to items in living and nonliving categories have to be considered among the factors causing selective category-specific deficits in patients, as well as their relevance in achieving tasks which require either

Unified transform architecture for AVC, AVS, VC-1 and HEVC high-performance codecs

Science.gov (United States)

Dias, Tiago; Roma, Nuno; Sousa, Leonel

2014-12-01

A unified architecture for fast and efficient computation of the set of two-dimensional (2-D) transforms adopted by the most recent state-of-the-art digital video standards is presented in this paper. Contrasting to other designs with similar functionality, the presented architecture is supported on a scalable, modular and completely configurable processing structure. This flexible structure not only allows to easily reconfigure the architecture to support different transform kernels, but it also permits its resizing to efficiently support transforms of different orders (e.g. order-4, order-8, order-16 and order-32). Consequently, not only is it highly suitable to realize high-performance multi-standard transform cores, but it also offers highly efficient implementations of specialized processing structures addressing only a reduced subset of transforms that are used by a specific video standard. The experimental results that were obtained by prototyping several configurations of this processing structure in a Xilinx Virtex-7 FPGA show the superior performance and hardware efficiency levels provided by the proposed unified architecture for the implementation of transform cores for the Advanced Video Coding (AVC), Audio Video coding Standard (AVS), VC-1 and High Efficiency Video Coding (HEVC) standards. In addition, such results also demonstrate the ability of this processing structure to realize multi-standard transform cores supporting all the standards mentioned above and that are capable of processing the 8k Ultra High Definition Television (UHDTV) video format (7,680 × 4,320 at 30 fps) in real time.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

Directory of Open Access Journals (Sweden)

Zutao Zhang

2016-02-01

Full Text Available In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT is adopted to extract the EEG power spectrum density (PSD. In this step, sparse representation classification combined with k-singular value decomposition (KSVD is firstly introduced in PSD to estimate the driver’s vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

Human-inspired sound environment recognition system for assistive vehicles

Science.gov (United States)

González Vidal, Eduardo; Fredes Zarricueta, Ernesto; Auat Cheein, Fernando

2015-02-01

Objective. The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars. These vehicles need environment information to ensure safe navigation. Approach. In the field of environment recognition, range sensors (such as LiDAR and ultrasonic systems) and artificial vision devices are widely used; however, these sensors depend on environment constraints (such as lighting variability or color of objects), and sound can provide important information for the characterization of an environment. In this work, we propose a sound-based approach to enhance the environment recognition process, mainly for cases that compromise human integrity, according to the International Classification of Functioning (ICF). Our proposal is based on a neural network implementation that is able to classify up to 15 different environments, each selected according to the ICF considerations on environment factors in the community-based physical activities of people with disabilities. Main results. The accuracy rates in environment classification ranges from 84% to 93%. This classification is later used to constrain assistive vehicle navigation in order to protect the user during daily activities. This work also includes real-time outdoor experimentation (performed on an assistive vehicle) by seven volunteers with different disabilities (but without cognitive impairment and experienced in the use of wheelchairs), statistical validation, comparison with previously published work, and a discussion section where the pros and cons of our system are evaluated. Significance

Perceptual quality estimation of H.264/AVC videos using reduced-reference and no-reference models

Science.gov (United States)

Shahid, Muhammad; Pandremmenou, Katerina; Kondi, Lisimachos P.; Rossholm, Andreas; Lövström, Benny

2016-09-01

Reduced-reference (RR) and no-reference (NR) models for video quality estimation, using features that account for the impact of coding artifacts, spatio-temporal complexity, and packet losses, are proposed. The purpose of this study is to analyze a number of potentially quality-relevant features in order to select the most suitable set of features for building the desired models. The proposed sets of features have not been used in the literature and some of the features are used for the first time in this study. The features are employed by the least absolute shrinkage and selection operator (LASSO), which selects only the most influential of them toward perceptual quality. For comparison, we apply feature selection in the complete feature sets and ridge regression on the reduced sets. The models are validated using a database of H.264/AVC encoded videos that were subjectively assessed for quality in an ITU-T compliant laboratory. We infer that just two features selected by RR LASSO and two bitstream-based features selected by NR LASSO are able to estimate perceptual quality with high accuracy, higher than that of ridge, which uses more features. The comparisons with competing works and two full-reference metrics also verify the superiority of our models.

Graceful Degradation in 3GPP MBMS Mobile TV Services Using H.264/AVC Temporal Scalability

Directory of Open Access Journals (Sweden)

Thomas Wiegand

2009-01-01

Full Text Available These days, there is an increasing interest in Mobile TV broadcast services shown by customers as well as service providers. One general problem of Mobile TV broadcast services is to maximize the coverage of users receiving an acceptable service quality, which is mainly influenced by the user's position and mobility within the cell. In this paper, graceful degradation is considered as an approach for improved service availability and coverage. We present a layered transmission approach for 3GPP's Release 6 Multimedia and Broadcast Service (MBMS based on temporal scalability using H.264/AVC Baseline Profile. A differentiation in robustness between temporal quality layers is achieved by unequal error protection approach based on either application layer Forward Error Correction (FEC or unequal transmit power for the layers or even a combination of both. We discuss the corresponding MBMS service as well as network settings and define measures allowing for evaluating the amount of users reached with a certain mobile terminal play-out quality while considering the network cell capacity usage. Using simulated 3GPP Rel. 6 network conditions, we show that if the service and network settings are chosen carefully, a noticeable extension of the coverage of the MBMS service can be achieved.

The development of regulations for road vehicles used in the conveyance of dangerous goods

International Nuclear Information System (INIS)

Kdolsky, L.

1980-01-01

Aspects of dangerous goods transport are classified according to risks associated with control of the vehicles themselves, trailers, traffic, the goods carried, safety of packing materials, crates and containers and the handling problems. Eight different classifications of goods (e.g. explosive, inflammable, radioactive) listed as potentially dangerous by European authorities are quoted. Theoretical studies are outlined, requiring 6 hours for general studies of the official (ADR) classifications, and 3 hours for specialist work. Documentation involved includes accident reports, licence applications, personnel and traffic records. Practical work (3 hours study) includes examination of vehicles and goods and visual displays (e.g. by film) of typical accidents, causes, consequences and negotiations with civil authorities. (G.C.)

Dollar Summary of Federal Supply Classification and Service Category by Company, FY83, Part 1 (1005-5811).

Science.gov (United States)

1983-01-01

E STATE TOTAL 590 LEAR S b1 . . . . • I . i I I I . DEPARTMENT OF DEFENSE PAGE 381 PRIME CONTRACTS OVER $25. 000 BY FEDERAL STOCK CLASSIFICATION...MOTOR VEHICLE MAINTENANCE EQUIPMENT 94 RONAN & KUNZL INC MICHIGAN ARMY MOTOR VEHICLE MAINTENANCE EQUIPMENT C9 RUGBY INDUSTRIES INC MINNESOTA ARMY MOTOR

Severidade clínica e funcionalidade de pacientes hemiplégicos pós-AVC agudo atendidos nos serviços públicos de fisioterapia de Natal (RN Clinical severity and functionality of acute stroke patients attended at the physiotherapy public services of Natal, Rio Grande do Norte State, Brazil

Directory of Open Access Journals (Sweden)

Fabrícia Azevêdo da Costa

2011-01-01

Full Text Available O acidente vascular cerebral (AVC representa a terceira causa de morte em vários países do mundo e principal causa de incapacidade física. O objetivo deste estudo foi investigar por meio de uma equipe multidisciplinar a severidade clínica e a independência funcional de pacientes hemiplégicos pós-AVC. Trata-se de estudo descritivo composto por quarenta hemiplégicos atendidos nos quatro maiores serviços públicos de fisioterapia da cidade de Natal (RN. Foram utilizados uma ficha de avaliação, a medida de independência funcional e o NIHSS. A amostra é predominantemente feminina(55%, AVC isquêmico(90%, hemisfério cerebral direito(52,5% e fator de risco hipertensão(90%. A média da severidade clínica é 13,32±4,7 e da independência funcional, 54,6±17,15. Não houve diferença significativa entre as médias funcionais dos pacientes quanto ao lado do AVC (pvalor=0,66. Existiu relação significativa entre severidade clínica e independência funcional (r=-0,45 pvalor=0,003. A severidade clínica e a dependência funcional de pacientes com AVC, ao darem entrada na fisioterapia, são significativas e evidenciam a necessidade de, além do tratamento clássico, serem incentivadas condutas educacionais que visem à conscientização da população.This article investigates the severity and functional independence of hemiplegics patients' post-acute stroke by means of a multidisciplinary clinical staff. It is a descriptive study composed by 40 hemiplegics attended at the four largest physiotherapy public services in Natal, Rio Grande do Norte State. The methods used were an evaluation form, Functional Independence Measure and NIHSS. The results showed a sample predominantly female (55%, stroke ischemic (90%, right brain hemisphere (52.5% and Hypertension Risk Factor (90%. The mean of clinical severity and functional independence was 13.32±4.7 and 54.6±17.15 respectively. There was no significant difference between the mean of

Siamese-GAN: Learning Invariant Representations for Aerial Vehicle Image Categorization

Directory of Open Access Journals (Sweden)

Laila Bashmal

2018-02-01

Full Text Available In this paper, we present a new algorithm for cross-domain classification in aerial vehicle images based on generative adversarial networks (GANs. The proposed method, called Siamese-GAN, learns invariant feature representations for both labeled and unlabeled images coming from two different domains. To this end, we train in an adversarial manner a Siamese encoder–decoder architecture coupled with a discriminator network. The encoder–decoder network has the task of matching the distributions of both domains in a shared space regularized by the reconstruction ability, while the discriminator seeks to distinguish between them. After this phase, we feed the resulting encoded labeled and unlabeled features to another network composed of two fully-connected layers for training and classification, respectively. Experiments on several cross-domain datasets composed of extremely high resolution (EHR images acquired by manned/unmanned aerial vehicles (MAV/UAV over the cities of Vaihingen, Toronto, Potsdam, and Trento are reported and discussed.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner.

Science.gov (United States)

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-07-20

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation.

Energy Star Concepts for Highway Vehicles

Energy Technology Data Exchange (ETDEWEB)

Greene, D.L.

2003-06-24

The authors of this report, under the sponsorship of the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Weatherization and Intergovernmental Program, have investigated the possible application of Energy Star ratings to passenger cars and light trucks. This study establishes a framework for formulating and evaluating Energy Star rating methods that is comprised of energy- and environmental-based metrics, potential vehicle classification systems, vehicle technology factors, and vehicle selection criteria. The study tests several concepts and Energy Star rating methods using model-year 2000 vehicle data--a spreadsheet model has been developed to facilitate these analyses. This study tests two primary types of rating systems: (1) an outcome-based system that rates vehicles based on fuel economy, GHG emissions, and oil use and (2) a technology-based system that rates vehicles based on the energy-saving technologies they use. Rating methods were evaluated based on their ability to select vehicles with high fuel economy, low GHG emissions, and low oil use while preserving a full range of service (size and acceleration) and body style choice. This study concludes that an Energy Star rating for passenger cars and light trucks is feasible and that several methods could be used to achieve reasonable tradeoffs between low energy use and emissions and diversity in size, performance, and body type. It also shows that methods that consider only fuel economy, GHG emissions, or oil use will not select a diverse mix of vehicles. Finally, analyses suggest that methods that encourage the use of technology only, may result in increases in acceleration power and weight rather than reductions in oil use and GHG emissions and improvements in fuel economy.

Autonomous vehicles: from paradigms to technology

Science.gov (United States)

Ionita, Silviu

2017-10-01

Mobility is a basic necessity of contemporary society and it is a key factor in global economic development. The basic requirements for the transport of people and goods are: safety and duration of travel, but also a number of additional criteria are very important: energy saving, pollution, passenger comfort. Due to advances in hardware and software, automation has penetrated massively in transport systems both on infrastructure and on vehicles, but man is still the key element in vehicle driving. However, the classic concept of ‘human-in-the-loop’ in terms of ‘hands on’ in driving the cars is competing aside from the self-driving startups working towards so-called ‘Level 4 autonomy’, which is defined as “a self-driving system that does not requires human intervention in most scenarios”. In this paper, a conceptual synthesis of the autonomous vehicle issue is made in connection with the artificial intelligence paradigm. It presents a classification of the tasks that take place during the driving of the vehicle and its modeling from the perspective of traditional control engineering and artificial intelligence. The issue of autonomous vehicle management is addressed on three levels: navigation, movement in traffic, respectively effective maneuver and vehicle dynamics control. Each level is then described in terms of specific tasks, such as: route selection, planning and reconfiguration, recognition of traffic signs and reaction to signaling and traffic events, as well as control of effective speed, distance and direction. The approach will lead to a better understanding of the way technology is moving when talking about autonomous cars, smart/intelligent cars or intelligent transport systems. Keywords: self-driving vehicle, artificial intelligence, deep learning, intelligent transport systems.

High-resolution, low-delay, and error-resilient medical ultrasound video communication using H.264/AVC over mobile WiMAX networks.

Science.gov (United States)

Panayides, Andreas; Antoniou, Zinonas C; Mylonas, Yiannos; Pattichis, Marios S; Pitsillides, Andreas; Pattichis, Constantinos S

2013-05-01

In this study, we describe an effective video communication framework for the wireless transmission of H.264/AVC medical ultrasound video over mobile WiMAX networks. Medical ultrasound video is encoded using diagnostically-driven, error resilient encoding, where quantization levels are varied as a function of the diagnostic significance of each image region. We demonstrate how our proposed system allows for the transmission of high-resolution clinical video that is encoded at the clinical acquisition resolution and can then be decoded with low-delay. To validate performance, we perform OPNET simulations of mobile WiMAX Medium Access Control (MAC) and Physical (PHY) layers characteristics that include service prioritization classes, different modulation and coding schemes, fading channels conditions, and mobility. We encode the medical ultrasound videos at the 4CIF (704 × 576) resolution that can accommodate clinical acquisition that is typically performed at lower resolutions. Video quality assessment is based on both clinical (subjective) and objective evaluations.

Use of UAV-Borne Spectrometer for Land Cover Classification

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Sowmya Natesan

2018-04-01

Full Text Available Unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification using visible light and multi-spectral sensors. The objective of this work was to investigate the use of UAV equipped with a compact spectrometer for land cover classification. The UAV platform used was a DJI Flamewheel F550 hexacopter equipped with GPS and Inertial Measurement Unit (IMU navigation sensors, and a Raspberry Pi processor and camera module. The spectrometer used was the FLAME-NIR, a near-infrared spectrometer for hyperspectral measurements. RGB images and spectrometer data were captured simultaneously. As spectrometer data do not provide continuous terrain coverage, the locations of their ground elliptical footprints were determined from the bundle adjustment solution of the captured images. For each of the spectrometer ground ellipses, the land cover signature at the footprint location was determined to enable the characterization, identification, and classification of land cover elements. To attain a continuous land cover classification map, spatial interpolation was carried out from the irregularly distributed labeled spectrometer points. The accuracy of the classification was assessed using spatial intersection with the object-based image classification performed using the RGB images. Results show that in homogeneous land cover, like water, the accuracy of classification is 78% and in mixed classes, like grass, trees and manmade features, the average accuracy is 50%, thus, indicating the contribution of hyperspectral measurements of low altitude UAV-borne spectrometers to improve land cover classification.

Properties of road unevenness inducing the kinematical excitation of vehicles

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Kúdelčíková Mária

2017-01-01

Full Text Available The submitted paper is devoted to the mapping of the surface road profile and to the mathematical description of unevenness in one vehicle track. Its statistical parameters are analyzed and the classification of the road into a category based on power spectral density of unevenness is made.

Embedded and real-time vehicle detection system for challenging on-road scenes

Science.gov (United States)

Gu, Qin; Yang, Jianyu; Kong, Lingjiang; Yan, Wei Qi; Klette, Reinhard

2017-06-01

Vehicle detection is an important topic for advanced driver-assistance systems. This paper proposes an adaptive approach for an embedded system by focusing on monocular vehicle detection in real time, also aiming at being accurate under challenging conditions. Scene classification is accomplished by using a simplified convolution neural network with hypothesis generation by SoftMax regression. The output is consequently taken into account to optimize detection parameters for hypothesis generation and testing. Thus, we offer a sample-reorganization mechanism to improve the performance of vehicle hypothesis verification. A hypothesis leap mechanism is in use to improve the operating efficiency of the on-board system. A practical on-road test is employed to verify vehicle detection (i.e., accuracy) and also the performance of the designed on-board system regarding speed.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner

Directory of Open Access Journals (Sweden)

Jhonghyun An

2016-07-01

Full Text Available There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1 static local coordinate occupancy grid map (SLOGM building and (2 intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation.

Automatic vehicle counting system for traffic monitoring

Science.gov (United States)

Crouzil, Alain; Khoudour, Louahdi; Valiere, Paul; Truong Cong, Dung Nghy

2016-09-01

The article is dedicated to the presentation of a vision-based system for road vehicle counting and classification. The system is able to achieve counting with a very good accuracy even in difficult scenarios linked to occlusions and/or presence of shadows. The principle of the system is to use already installed cameras in road networks without any additional calibration procedure. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. First, the approach models each pixel of the background with an adaptive Gaussian distribution. This model is coupled with a motion detection procedure, which allows correctly location of moving vehicles in space and time. The nature of trials carried out, including peak periods and various vehicle types, leads to an increase of occlusions between cars and between cars and trucks. A specific method for severe occlusion detection, based on the notion of solidity, has been carried out and tested. Furthermore, the method developed in this work is capable of managing shadows with high resolution. The related algorithm has been tested and compared to a classical method. Experimental results based on four large datasets show that our method can count and classify vehicles in real time with a high level of performance (>98%) under different environmental situations, thus performing better than the conventional inductive loop detectors.

Real-time people and vehicle detection from UAV imagery

Science.gov (United States)

Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

2011-01-01

A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

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Sheng Wang

2007-07-01

Full Text Available Wireless sensor networks (WSNs are autonomous networks that have beenfrequently deployed to collaboratively perform target localization and classification tasks.Their autonomous and collaborative features resemble the characteristics of agents. Suchsimilarities inspire the development of heterogeneous agent architecture for WSN in thispaper. The proposed agent architecture views WSN as multi-agent systems and mobileagents are employed to reduce in-network communication. According to the architecture,an energy based acoustic localization algorithm is proposed. In localization, estimate oftarget location is obtained by steepest descent search. The search algorithm adapts tomeasurement environments by dynamically adjusting its termination condition. With theagent architecture, target classification is accomplished by distributed support vectormachine (SVM. Mobile agents are employed for feature extraction and distributed SVMlearning to reduce communication load. Desirable learning performance is guaranteed bycombining support vectors and convex hull vectors. Fusion algorithms are designed tomerge SVM classification decisions made from various modalities. Real world experimentswith MICAz sensor nodes are conducted for vehicle localization and classification.Experimental results show the proposed agent architecture remarkably facilitates WSNdesigns and algorithm implementation. The localization and classification algorithms alsoprove to be accurate and energy efficient.

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

DEFF Research Database (Denmark)

Hu, Junjie; Morais, Hugo; Sousa, Tiago

2016-01-01

Electric vehicles can become integral parts of a smart grid, since they are capable of providing valuable services to power systems other than just consuming power. On the transmission system level, electric vehicles are regarded as an important means of balancing the intermittent renewable energy...... resources such as wind power. This is because electric vehicles can be used to absorb the energy during the period of high electricity penetration and feed the electricity back into the grid when the demand is high or in situations of insufficient electricity generation. However, on the distribution system...... and industries. This paper presents a review and classification of methods for smart charging (including power to vehicle and vehicle-to-grid) of electric vehicles for fleet operators. The study firstly presents service relationships between fleet operators and other four actors in smart grids; then, modeling...

Aortic valve calcifications on chest films: how much calcium do I need?

Science.gov (United States)

Mahnken, Andreas H; Dohmen, Guido; Koos, Ralf

2011-08-01

Aortic valve calcifications (AVC) as seen on conventional chest films or on CT are associated with aortic valve stenosis (AVS). The absence of AVC on chest films does not exclude high grade AVS. The aim of this study was to analyse if there is a threshold for the detection of AVC from conventional chest films in patients suffering from high grade AVS. The explanted aortic valves of 29 patients (16 male, mean age 72.3 +/- 11.5 years) with high grade AVS were examined by dual-source CT. AVC were quantified using the Agatston AVC score. In all patients conventional chest films obtained the day before surgery were evaluated for the presence of AVC. Results were analysed with students t-test, Spearman's rank correlation and ROC analysis. On conventional chest films AVC were visible in 18 patients. On CT all specimen presented with AVC with an Agatston AVC score ranging from 40.7 to 1870 (mean 991.3 +/- 463.1). In patients with AVC visible on chest films the AVC score was significantly higher (1264.0 +/- 318.2) when compared with patients without visible calcifications (544.9 +/- 274.4; P AVC score and the visibility of AVC on chest films (r = 0.781). ROC analysis identified an ideal threshold of 718 for AVC score to separate conventional chest films with and without visible AVC. Unlike in coronary calcifications, there is a threshold for identifying AVC from conventional chest films. This finding may be of diagnostic value, as conventional chest films may be used to semiquantitatively evaluate the extent of AVC.

Low-Complexity Hierarchical Mode Decision Algorithms Targeting VLSI Architecture Design for the H.264/AVC Video Encoder

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Guilherme Corrêa

2012-01-01

Full Text Available In H.264/AVC, the encoding process can occur according to one of the 13 intraframe coding modes or according to one of the 8 available interframes block sizes, besides the SKIP mode. In the Joint Model reference software, the choice of the best mode is performed through exhaustive executions of the entire encoding process, which significantly increases the encoder's computational complexity and sometimes even forbids its use in real-time applications. Considering this context, this work proposes a set of heuristic algorithms targeting hardware architectures that lead to earlier selection of one encoding mode. The amount of repetitions of the encoding process is reduced by 47 times, at the cost of a relatively small cost in compression performance. When compared to other works, the fast hierarchical mode decision results are expressively more satisfactory in terms of computational complexity reduction, quality, and bit rate. The low-complexity mode decision architecture proposed is thus a very good option for real-time coding of high-resolution videos. The solution is especially interesting for embedded and mobile applications with support to multimedia systems, since it yields good compression rates and image quality with a very high reduction in the encoder complexity.

Personnel and Vehicle Data Collection at Aberdeen Proving Ground (APG) and its Distribution for Research

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2015-10-01

28 Magnetometer Applied Physics Model 1540-digital 3-axis fluxgate 5 Amplifiers Alligator Technologies USBPGF-S1 programmable instrumentation...Acoustic, Seismic, magnetic, footstep, vehicle, magnetometer , geophone, unattended ground sensor (UGS) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

Rapid hyperspectral image classification to enable autonomous search systems

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Raj Bridgelal

2016-11-01

Full Text Available The emergence of lightweight full-frame hyperspectral cameras is destined to enable autonomous search vehicles in the air, on the ground and in water. Self-contained and long-endurance systems will yield important new applications, for example, in emergency response and the timely identification of environmental hazards. One missing capability is rapid classification of hyperspectral scenes so that search vehicles can immediately take actions to verify potential targets. Onsite verifications minimise false positives and preclude the expense of repeat missions. Verifications will require enhanced image quality, which is achievable by either moving closer to the potential target or by adjusting the optical system. Such a solution, however, is currently impractical for small mobile platforms with finite energy sources. Rapid classifications with current methods demand large computing capacity that will quickly deplete the on-board battery or fuel. To develop the missing capability, the authors propose a low-complexity hyperspectral image classifier that approaches the performance of prevalent classifiers. This research determines that the new method will require at least 19-fold less computing capacity than the prevalent classifier. To assess relative performances, the authors developed a benchmark that compares a statistic of library endmember separability in their respective feature spaces.

Data Applicability of Heritage and New Hardware for Launch Vehicle System Reliability Models

Science.gov (United States)

Al Hassan Mohammad; Novack, Steven

2015-01-01

Many launch vehicle systems are designed and developed using heritage and new hardware. In most cases, the heritage hardware undergoes modifications to fit new functional system requirements, impacting the failure rates and, ultimately, the reliability data. New hardware, which lacks historical data, is often compared to like systems when estimating failure rates. Some qualification of applicability for the data source to the current system should be made. Accurately characterizing the reliability data applicability and quality under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This presentation will demonstrate a data-source classification method that ranks reliability data according to applicability and quality criteria to a new launch vehicle. This method accounts for similarities/dissimilarities in source and applicability, as well as operating environments like vibrations, acoustic regime, and shock. This classification approach will be followed by uncertainty-importance routines to assess the need for additional data to reduce uncertainty.

Vehicles instability criteria for flood risk assessment of a street network

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C. Arrighi

2016-05-01

Full Text Available The mutual interaction between floods and human activity is a process, which has been evolving over history and has shaped flood risk pathways. In developed countries, many events have illustrated that the majority of the fatalities during a flood occurs in a vehicle, which is considered as a safe shelter but it may turn into a trap for several combinations of water depth and velocity. Thus, driving a car in floodwaters is recognized as the most crucial aggravating factor for people safety. On the other hand, the entrainment of vehicles may locally cause obstructions to the flow and induce the collapse of infrastructures. Flood risk to vehicles can be defined as the combination of the probability of a vehicle of being swept away (i.e. the hazard and the actual traffic/parking density, i.e. the vulnerability. Hazard for vehicles can be assessed through the spatial identification and mapping of the critical conditions for vehicles incipient motion. This analysis requires a flood map with information on water depth and velocity and consistent instability criteria accounting for flood and vehicles characteristics. Vulnerability is evaluated thanks to the road network and traffic data. Therefore, vehicles flood risk mapping can support people's education and management practices in order to reduce the casualties. In this work, a flood hazard classification for vehicles is introduced and an application to a real case study is presented and discussed.

Vehicles instability criteria for flood risk assessment of a street network

Science.gov (United States)

Arrighi, Chiara; Huybrechts, Nicolas; Ouahsine, Abdellatif; Chassé, Patrick; Oumeraci, Hocine; Castelli, Fabio

2016-05-01

The mutual interaction between floods and human activity is a process, which has been evolving over history and has shaped flood risk pathways. In developed countries, many events have illustrated that the majority of the fatalities during a flood occurs in a vehicle, which is considered as a safe shelter but it may turn into a trap for several combinations of water depth and velocity. Thus, driving a car in floodwaters is recognized as the most crucial aggravating factor for people safety. On the other hand, the entrainment of vehicles may locally cause obstructions to the flow and induce the collapse of infrastructures. Flood risk to vehicles can be defined as the combination of the probability of a vehicle of being swept away (i.e. the hazard) and the actual traffic/parking density, i.e. the vulnerability. Hazard for vehicles can be assessed through the spatial identification and mapping of the critical conditions for vehicles incipient motion. This analysis requires a flood map with information on water depth and velocity and consistent instability criteria accounting for flood and vehicles characteristics. Vulnerability is evaluated thanks to the road network and traffic data. Therefore, vehicles flood risk mapping can support people's education and management practices in order to reduce the casualties. In this work, a flood hazard classification for vehicles is introduced and an application to a real case study is presented and discussed.

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

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Xiangwei Xing

2014-01-01

Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Classification of time series patterns from complex dynamic systems

Energy Technology Data Exchange (ETDEWEB)

Schryver, J.C.; Rao, N.

1998-07-01

An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately, the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.

Evaluation of ISO CRS Envelopes Relative to U.S. Vehicles and Child Restraint Systems.

Science.gov (United States)

Hu, Jingwen; Manary, Miriam A; Klinich, Kathleen D; Reed, Matthew P

2015-01-01

The objectives of this study are to use computer simulation to evaluate the International Organization for Standardization (ISO) 13216-3:2006(E) child restraint system (CRS) envelopes relative to rear seat compartments from vehicles and CRSs in the U.S. market, investigate the potential compatibility issues of U.S. vehicles and CRSs, and demonstrate whether necessary modifications can be made to introduce such a system into compatibility evaluations between U.S. vehicles and CRSs. Three-dimensional geometry models for 26 vehicles and 16 convertible CRS designs developed previously were used. Geometry models of 3 forward-facing and 3 rear-facing CRS envelopes provided by the ISO were built in the current study. The virtual fit process closely followed the physical procedures described in the ISO standards. The results showed that the current ISO rear-facing envelopes can provide reasonable classifications for CRSs and vehicles, but the forward-facing envelopes do not represent products currently in the U.S. market. In particular, all of the selected vehicles could accommodate the largest forward-facing CRS envelope at the second-row seat location behind the driver seat. In contrast, half of the selected CRSs could not fit within any of the forward-facing ISO CRS envelopes, mainly due to protrusion at the rear-top corner of the envelope. The results also indicate that the rear seat compartment in U.S. vehicles often cannot accommodate a large portion of convertible CRSs in the rear-facing position. The increased demand for vehicle fuel economy and the recommendation to keep children rear-facing longer may lead to smaller cars and larger CRSs, which may increase the potential for fit problems. The virtual classifications indicated that contact between the forward-facing CRSs and the head restraints in the rear seats as well as that between the rear-facing CRSs and the back of the front seats is a main concern regarding the compatibility between the vehicles and the

Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

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Ming-Der Yang

2017-06-01

Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

Support Vector Machine Classification of Drunk Driving Behaviour.

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Chen, Huiqin; Chen, Lei

2017-01-23

Alcohol is the root cause of numerous traffic accidents due to its pharmacological action on the human central nervous system. This study conducted a detection process to distinguish drunk driving from normal driving under simulated driving conditions. The classification was performed by a support vector machine (SVM) classifier trained to distinguish between these two classes by integrating both driving performance and physiological measurements. In addition, principal component analysis was conducted to rank the weights of the features. The standard deviation of R-R intervals (SDNN), the root mean square value of the difference of the adjacent R-R interval series (RMSSD), low frequency (LF), high frequency (HF), the ratio of the low and high frequencies (LF/HF), and average blink duration were the highest weighted features in the study. The results show that SVM classification can successfully distinguish drunk driving from normal driving with an accuracy of 70%. The driving performance data and the physiological measurements reported by this paper combined with air-alcohol concentration could be integrated using the support vector regression classification method to establish a better early warning model, thereby improving vehicle safety.

Support Vector Machine Classification of Drunk Driving Behaviour

Directory of Open Access Journals (Sweden)

Huiqin Chen

2017-01-01

Full Text Available Alcohol is the root cause of numerous traffic accidents due to its pharmacological action on the human central nervous system. This study conducted a detection process to distinguish drunk driving from normal driving under simulated driving conditions. The classification was performed by a support vector machine (SVM classifier trained to distinguish between these two classes by integrating both driving performance and physiological measurements. In addition, principal component analysis was conducted to rank the weights of the features. The standard deviation of R–R intervals (SDNN, the root mean square value of the difference of the adjacent R–R interval series (RMSSD, low frequency (LF, high frequency (HF, the ratio of the low and high frequencies (LF/HF, and average blink duration were the highest weighted features in the study. The results show that SVM classification can successfully distinguish drunk driving from normal driving with an accuracy of 70%. The driving performance data and the physiological measurements reported by this paper combined with air-alcohol concentration could be integrated using the support vector regression classification method to establish a better early warning model, thereby improving vehicle safety.

Quantification of Aortic Valve Calcifications Detected During Lung Cancer-Screening CT Helps Stratify Subjects Necessitating Echocardiography for Aortic Stenosis Diagnosis.

Science.gov (United States)

Lee, Hee Young; Kim, Sung Mok; Lee, Kyung Soo; Park, Seung Woo; Chung, Myung Jin; Cho, Hyoun; Jung, Jung Im; Jang, Hye Won; Jung, Sin-Ho; Goo, Juna

2016-05-01

No study has been published on aortic valve calcification (AVC) extent at lung cancer screening low-dose CT (LDCT) and its relationship with aortic stenosis (AS). The purpose of this study was to estimate the cutoff value of AVC on LDCT for detecting AS in asymptomatic Asian subjects. Six thousand three hundred thirty-eight subjects (mean age, 55.9 years ± 8.6) self-referred to health-promotion center underwent LDCT, coronary calcium scoring CT (CSCT), and echocardiography. AVC was quantified using Agatston methods on CT. AVC extent on LDCT was compared with that on CSCT, and AVC threshold for diagnosing AS was calculated. Clinical factors associated with AS and AVC were sought.AVC was observed in 403 subjects (64.9 years ± 8.7) on LDCT (6.4%), and AVC score measured from LDCT showed strong positive correlation with that from CSCT (r = 0.83, P AVC score for detecting AS was 138.37 with sensitivity of 90.0% and specificity 83.2%. On multivariate analysis, age (odds ratio [OR] = 1.10, 95% CI: 1.09-1.12) and hypertension (OR = 1.39, 95% CI: 1.10-1.76) were associated with the presence of AVC, whereas AVC extent at LDCT (OR = 104.32, 95% CI: 16.16-673.70) was the only significant clinical factor associated with AS; AVC extent on LDCT (OR = 104.32, 95% CI: 16.16-673.70) was the significant clinical factor associated with AS.The AVC extent on LDCT is significantly related to the presence of AS, and we recommend echocardiography for screening AS based on quantified AVC values on LDCT.

Intelligent behaviors through vehicle-to-vehicle and vehicle-to-infrastructure communication

Science.gov (United States)

Garcia, Richard D.; Sturgeon, Purser; Brown, Mike

2012-06-01

The last decade has seen a significant increase in intelligent safety devices on private automobiles. These devices have both increased and augmented the situational awareness of the driver and in some cases provided automated vehicle responses. To date almost all intelligent safety devices have relied on data directly perceived by the vehicle. This constraint has a direct impact on the types of solutions available to the vehicle. In an effort to improve the safety options available to a vehicle, numerous research laboratories and government agencies are investing time and resources into connecting vehicles to each other and to infrastructure-based devices. This work details several efforts in both the commercial vehicle and the private auto industries to increase vehicle safety and driver situational awareness through vehicle-to-vehicle and vehicle-to-infrastructure communication. It will specifically discuss intelligent behaviors being designed to automatically disable non-compliant vehicles, warn tractor trailer vehicles of unsafe lane maneuvers such as lane changes, passing, and merging, and alert drivers to non-line-of-sight emergencies.

Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

Science.gov (United States)

Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

2015-12-01

The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

Hyper-spectral frequency selection for the classification of vegetation diseases

OpenAIRE

Dijkstra, Klaas; van de Loosdrecht, Jaap; Schomaker, Lambert; Wiering, Marco

2017-01-01

Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the...

Predominance of Abdominal Visceral Adipose Tissue Reflects the Presence of Aortic Valve Calcification.

Science.gov (United States)

Oikawa, Masayoshi; Owada, Takashi; Yamauchi, Hiroyuki; Misaka, Tomofumi; Machii, Hirofumi; Yamaki, Takayoshi; Sugimoto, Koichi; Kunii, Hiroyuki; Nakazato, Kazuhiko; Suzuki, Hitoshi; Saitoh, Shu-Ichi; Takeishi, Yasuchika

2016-01-01

Background. Aortic valve calcification (AVC) is a common feature of aging and is related to coronary artery disease. Although abdominal visceral adipose tissue (VAT) plays fundamental roles in coronary artery disease, the relationship between abdominal VAT and AVC is not fully understood. Methods. We investigated 259 patients who underwent cardiac and abdominal computed tomography (CT). AVC was defined as calcified lesion on the aortic valve by CT. %abdominal VAT was calculated as abdominal VAT area/total adipose tissue area. Results. AVC was detected in 75 patients, and these patients showed higher %abdominal VAT (44% versus 38%, p AVC. When the cutoff value of %abdominal VAT was set at 40.9%, the area under the curve to diagnose AVC was 0.626. Multivariable logistic regression analysis showed that age (OR 1.120, 95% CI 1.078-1.168, p AVC. The net reclassification improvement value for detecting AVC was increased when %abdominal VAT was added to the model: 0.5093 (95% CI 0.2489-0.7697, p AVC.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

Science.gov (United States)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Incidence and progression of aortic valve calcium in the Multi-ethnic Study of Atherosclerosis (MESA).

Science.gov (United States)

Owens, David S; Katz, Ronit; Takasu, Junichiro; Kronmal, Richard; Budoff, Matthew J; O'Brien, Kevin D

2010-03-01

Aortic valve calcium (AVC) is common among older adults and shares epidemiologic and histopathologic similarities to atherosclerosis. However, prospective studies have failed to identify meaningful risk associations with incident ("new") AVC or its progression. In the present study, AVC was quantified from serial computed tomographic images from 5,880 participants (aged 45 to 84 years) in the Multi-Ethnic Study of Atherosclerosis, using the Agatston method. Multivariate backward selection modeling was used to identify the risk factors for incident AVC and AVC progression. During a mean follow-up of 2.4 +/- 0.9 years, 210 subjects (4.1%) developed incident AVC. The incidence rate (mean 1.7%/year) increased significantly with age (p AVC included age, male gender, body mass index, current smoking, and the use of lipid-lowering and antihypertensive medications. Among those with AVC at baseline, the median rate of AVC progression was 2 Agatston units/year (interquartile range -21 to 37). The baseline Agatston score was a strong, independent predictor of progression, especially among those with high calcium scores at baseline. In conclusion, in this ethnically diverse, preclinical cohort, the rate of incident AVC increased significantly with age. The incident AVC risk was associated with several traditional cardiovascular risk factors, specifically age, male gender, body mass index, current smoking, and the use of both antihypertensive and lipid-lowering medications. AVC progression risk was associated with male gender and the baseline Agatston score. Additional research is needed to determine whether age- and stage-specific mechanisms underlie the risk of AVC progression. Copyright 2010 Elsevier Inc. All rights reserved.

a Two-Step Classification Approach to Distinguishing Similar Objects in Mobile LIDAR Point Clouds

Science.gov (United States)

He, H.; Khoshelham, K.; Fraser, C.

2017-09-01

Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

Development of Degree-of-Priority Based Control Strategy for Emergency Vehicle Preemption Operation

Directory of Open Access Journals (Sweden)

Jiawen Wang

2013-01-01

Full Text Available This paper proposes a degree-of-priority based control strategy for emergency vehicle preemption operation to decrease the impacts of emergency vehicles on normal traffic. The proposed model features its effectiveness to the following three aspects: (1 a multilayer fuzzy model was established to determine the degree-of-priority based on emergency vehicle preemption demand intensity and preemption influence intensity; (2 for emergency vehicles with proper classification, a travel time estimation model for emergency traffic was formulated, an optimal emergency route determines model based on the level of priority of emergency events, and the emergency vehicle travel time was developed to minimize evacuation time as well as minimize the adverse impacts of preemption on normal traffic; and (3 a conditional traffic signals priority control method at each intersection of the evacuation route was built, so that traffic queue at each intersection can be cleared before the arrival of emergency vehicles. A simulation model based on field data was developed, and the performance of the proposed strategy was compared with the conventional local detection based method under the microscopic simulation model. The results validated the efficiency of the proposed strategy in terms of minimizing the delay of emergency vehicles and reducing adverse impacts on normal traffic.

Asynchronous vehicle pose correction using visual detection of ground features

International Nuclear Information System (INIS)

Harnarinesingh, Randy E S; Syan, Chanan S

2014-01-01

The inherent noise associated with odometry manifests itself as errors in localization for autonomous vehicles. Visual odometry has been previously used in order to supplement classical vehicle odometry. However, visual odometry is limited in its ability to reduce errors in localization for large travel distances that entail the cumulative summing of individual frame-to-frame image errors. In this paper, a novel machine vision approach for tiled surfaces is proposed to address this problem. Tile edges in a laboratory environment are used to define a travel trajectory for the Quansar Qbot (autonomous vehicle) built on the iRobot iRoomba platform with a forward facing camera. Tile intersections are used to enable asynchronous error recovery for vehicle position and orientation. The proposed approach employs real-time image classification and is feasible for error mitigation for large travel distances. The average position error for an 8m travel distance using classical odometry was measured to be 0.28m. However, implementation of the proposed approach resulted in an error of 0.028m. The proposed approach therefore significantly reduces pose estimation error and could be used to supplement existing modalities such as GPS and Laser-based range sensors

Sensor network based vehicle classification and license plate identification system

Energy Technology Data Exchange (ETDEWEB)

Frigo, Janette Rose [Los Alamos National Laboratory; Brennan, Sean M [Los Alamos National Laboratory; Rosten, Edward J [Los Alamos National Laboratory; Raby, Eric Y [Los Alamos National Laboratory; Kulathumani, Vinod K [WEST VIRGINIA UNIV.

2009-01-01

Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform. Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.

Arterial wave reflection and aortic valve calcification in an elderly community-based cohort.

Science.gov (United States)

Sera, Fusako; Russo, Cesare; Iwata, Shinichi; Jin, Zhezhen; Rundek, Tatjana; Elkind, Mitchell S V; Homma, Shunichi; Sacco, Ralph L; Di Tullio, Marco R

2015-04-01

Aortic valve calcification (AVC) without stenosis is common in the elderly, is associated with cardiovascular morbidity and mortality, and may progress to aortic valve stenosis. Arterial stiffness and pulse-wave reflection are important components of proximal aortic hemodynamics, but their relationship with AVC is not established. To investigate the relationship of arterial wave reflection and stiffness with AVC, pulse wave analysis and AVC evaluation by echocardiography were performed in 867 participants from the Cardiovascular Abnormalities and Brain Lesions study. Participants were divided into four categories on the basis of the severity and extent of AVC: (1) none or mild focal AVC, (2) mild diffuse AVC, (3) moderate to severe focal AVC, and (4) moderate to severe diffuse AVC. Central blood pressures and pulse pressure, total arterial compliance, augmentation index, and time to wave reflection were assessed using applanation tonometry. Indicators of arterial stiffness and wave reflection were significantly associated with AVC severity, except for central systolic and diastolic pressures and time to reflection. After adjustment for pertinent covariates (age, sex, race/ethnicity, and estimated glomerular filtration rate), only augmentation pressure (P = .02) and augmentation index (P = .002) were associated with the severity of AVC. Multivariate logistic regression analysis revealed that augmentation pressure (odds ratio per mm Hg, 1.14; 95% confidence interval, 1.02-1.27; P = .02) and augmentation index (odds ratio per percentage point, 1.07; 95% confidence interval, 1.01-1.13; P = .02) were associated with an increased risk for moderate to severe diffuse AVC, even when central blood pressure value was included in the same model. Arterial wave reflection is associated with AVC severity, independent of blood pressure values. Increased contribution of wave reflection to central blood pressure could be involved in the process leading to AVC. Copyright © 2015

Autoregressive Integrated Adaptive Neural Networks Classifier for EEG-P300 Classification

Directory of Open Access Journals (Sweden)

Demi Soetraprawata

2013-06-01

Full Text Available Brain Computer Interface has a potency to be applied in mechatronics apparatus and vehicles in the future. Compared to the other techniques, EEG is the most preferred for BCI designs. In this paper, a new adaptive neural network classifier of different mental activities from EEG-based P300 signals is proposed. To overcome the over-training that is caused by noisy and non-stationary data, the EEG signals are filtered and extracted using autoregressive models before passed to the adaptive neural networks classifier. To test the improvement in the EEG classification performance with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis. The experiment results show that the all subjects achieve a classification accuracy of 100%.

Generalized Linear Models in Vehicle Insurance

Directory of Open Access Journals (Sweden)

Silvie Kafková

2014-01-01

Full Text Available Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC. Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.

Optimizing Multiple Kernel Learning for the Classification of UAV Data

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Caroline M. Gevaert

2016-12-01

Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing high-quality orthoimagery and 3D information in the form of point clouds at a relatively low cost. Their increasing popularity stresses the necessity of understanding which algorithms are especially suited for processing the data obtained from UAVs. The features that are extracted from the point cloud and imagery have different statistical characteristics and can be considered as heterogeneous, which motivates the use of Multiple Kernel Learning (MKL for classification problems. In this paper, we illustrate the utility of applying MKL for the classification of heterogeneous features obtained from UAV data through a case study of an informal settlement in Kigali, Rwanda. Results indicate that MKL can achieve a classification accuracy of 90.6%, a 5.2% increase over a standard single-kernel Support Vector Machine (SVM. A comparison of seven MKL methods indicates that linearly-weighted kernel combinations based on simple heuristics are competitive with respect to computationally-complex, non-linear kernel combination methods. We further underline the importance of utilizing appropriate feature grouping strategies for MKL, which has not been directly addressed in the literature, and we propose a novel, automated feature grouping method that achieves a high classification accuracy for various MKL methods.

Classification of LIDAR Data for Generating a High-Precision Roadway Map

Science.gov (United States)

Jeong, J.; Lee, I.

2016-06-01

Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.

CLASSIFICATION OF LIDAR DATA FOR GENERATING A HIGH-PRECISION ROADWAY MAP

Directory of Open Access Journals (Sweden)

J. Jeong

2016-06-01

Full Text Available Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.

Quality optimization of H.264/AVC video transmission over noisy environments using a sparse regression framework

Science.gov (United States)

Pandremmenou, K.; Tziortziotis, N.; Paluri, S.; Zhang, W.; Blekas, K.; Kondi, L. P.; Kumar, S.

2015-03-01

We propose the use of the Least Absolute Shrinkage and Selection Operator (LASSO) regression method in order to predict the Cumulative Mean Squared Error (CMSE), incurred by the loss of individual slices in video transmission. We extract a number of quality-relevant features from the H.264/AVC video sequences, which are given as input to the LASSO. This method has the benefit of not only keeping a subset of the features that have the strongest effects towards video quality, but also produces accurate CMSE predictions. Particularly, we study the LASSO regression through two different architectures; the Global LASSO (G.LASSO) and Local LASSO (L.LASSO). In G.LASSO, a single regression model is trained for all slice types together, while in L.LASSO, motivated by the fact that the values for some features are closely dependent on the considered slice type, each slice type has its own regression model, in an e ort to improve LASSO's prediction capability. Based on the predicted CMSE values, we group the video slices into four priority classes. Additionally, we consider a video transmission scenario over a noisy channel, where Unequal Error Protection (UEP) is applied to all prioritized slices. The provided results demonstrate the efficiency of LASSO in estimating CMSE with high accuracy, using only a few features. les that typically contain high-entropy data, producing a footprint that is far less conspicuous than existing methods. The system uses a local web server to provide a le system, user interface and applications through an web architecture.

Relationship of metabolic syndrome with incident aortic valve calcium and aortic valve calcium progression: the Multi-Ethnic Study of Atherosclerosis (MESA).

Science.gov (United States)

Katz, Ronit; Budoff, Matthew J; Takasu, Junichiro; Shavelle, David M; Bertoni, Alain; Blumenthal, Roger S; Ouyang, Pamela; Wong, Nathan D; O'Brien, Kevin D

2009-04-01

Metabolic syndrome (MetS) has been associated with increased prevalence of aortic valve calcium (AVC) and with increased progression of aortic stenosis. The purpose of this study was to determine whether MetS is associated with increased risks for the development of new ("incident") AVC or for progression of established AVC as assessed by CT. The relationships of MetS or its components as well as of diabetes to risks for incident AVC or AVC progression were studied among participants with CT scans performed at baseline and at either year 2 or year 3 examinations in the Multi-Ethnic Study of Atherosclerosis (MESA). Of 5,723 MESA participants meeting criteria for inclusion, 1,674 had MetS by Adult Treatment Panel III criteria, whereas 761 had diabetes. Among the 5,123 participants without baseline AVC, risks for incident AVC, adjusted for time between scans, age, sex, race/ethnicity, LDL cholesterol, lipid-lowering medications, and smoking, were increased significantly for MetS (odds ratio [OR] 1.67 [95% CI 1.21-2.31]) or diabetes (2.06 [1.39-3.06]). In addition, there was an increase in incident AVC risk with increasing number of MetS components. Similar results were found using the International Diabetes Federation MetS criteria. Among the 600 participants (10.5%) with baseline AVC, neither MetS nor diabetes was associated with AVC progression. In the MESA cohort, MetS was associated with a significant increase in incident ("new") AVC, raising the possibility that MetS may be a potential therapeutic target to prevent AVC development.

Coronary artery calcification correlates with the presence and severity of valve calcification.

Science.gov (United States)

Koulaouzidis, G; Nicoll, R; MacArthur, T; Jenkins, P J; Henein, M Y

2013-10-15

To investigate the prevalence of coronary artery calcification (CAC) in symptomatic individuals with CT evidence for left heart valve calcification, aortic valve (AVC), mitral valve (MAC) or both. This is a retrospective study of 282 consecutive patients with calcification in either the aortic valve or mitral annulus. Calcium scoring of the coronary artery, aortic and mitral valve was measured using the Agatston score. AVC was more prevalent than MAC (64% vs. 2.5%, p AVC + CAC were observed in 53.5%, MAC and CAC in 2.1%, and combined AVC, MAC and CAC in 31.6%. The median CAC score was higher in individuals with combined AVC+MAC, followed by those with AVC and lowest was in the MAC group. The majority (40%) of individuals with AVC had CAC score >400, and only in 16% had CAC = 0. The same pattern was more evident in individuals with AVC + MAC, where 70% had CAC score >400 and only 6% had CAC score of 0. These results were irrespective of gender. There was no correlation between AVC and MAC but there was modest correlation between CAC score and AVC score (r = 0.28, p = 0.0001), MAC (r = 0.36, p = 0.0001) and with combined AVC + MAC (r = 0.5, p = 0.0001). AVC score of 262 had a sensitivity of 78% and specificity of 92% for the prediction of presence of CAC. The presence and extent of calcification in the aortic valve or/and mitral valves are associated with severe coronary artery calcification. © 2013.

System for Detecting Vehicle Features from Low Quality Data

Directory of Open Access Journals (Sweden)

Marcin Dominik Bugdol

2018-02-01

Full Text Available The paper presents a system that recognizes the make, colour and type of the vehicle. The classification has been performed using low quality data from real-traffic measurement devices. For detecting vehicles’ specific features three methods have been developed. They employ several image and signal recognition techniques, e.g. Mamdani Fuzzy Inference System for colour recognition or Scale Invariant Features Transform for make identification. The obtained results are very promising, especially because only on-site equipment, not dedicated for such application, has been employed. In case of car type, the proposed system has better performance than commonly used inductive loops. Extensive information about the vehicle can be used in many fields of Intelligent Transport Systems, especially for traffic supervision.

A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

Science.gov (United States)

Liu, Huawei; Li, Baoqing; Yuan, Xiaobing; Zhou, Qianwei; Huang, Jingchang

2018-03-27

Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.

Association between aortic valve calcification measured on non-contrast computed tomography and aortic valve stenosis in the general population.

Science.gov (United States)

Paulsen, Niels Herluf; Carlsen, Bjarke Bønløkke; Dahl, Jordi Sanchez; Carter-Storch, Rasmus; Christensen, Nicolaj Lyhne; Khurrami, Lida; Møller, Jacob Eifer; Lindholt, Jes Sandal; Diederichsen, Axel Cosmus Pyndt

2016-01-01

Aortic valve calcification (AVC) measured on non-contrast computed tomography (CT) has shown correlation to severity of aortic valve stenosis (AS) and mortality in patients with known AS. The aim of this study was to determine the association of CT verified AVC and subclinical AS in a general population undergoing CT. CT scans from 566 randomly selected male participants (age 65-74) in the Danish cardiovascular screening study (DANCAVAS) were analyzed for AVC. All participants with a moderately or severely increased AVC score (≥300 arbitrary units (AU)) and a matched control group were invited for a supplementary echocardiography. AS was graded by indexed aortic valve area (AVAi) on echocardiography as moderate 0.6-0.85 cm(2)/m(2) and severe AVC scoring. Moderate or severe increased AVC was observed in 10.7% (95% CI: 8.4-13.7). Echocardiography was performed in 101 individuals; 32.7% (95% CI: 21.8 to 46.0) with moderate or high AVC score had moderate or severe AS, while none with no or low AVC. A ROC analysis defined an AVC score ≥588 AU to be suggestive of moderate or severe AS (AUC 0.89 ± 0.04, sensitivity 83% and specificity 87%). In the univariate analyses, AVC was the only variable significantly associated with AS. This study indicates an association between CT verified AVC and subclinical AS. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

ELECTROMAGNETIC BIOSPHERE POLLUTION BY MOTOR TRANSPORT (VEHICLES, ELECTRIC VEHICLES, HYBRID VEHICLES

Directory of Open Access Journals (Sweden)

S. Selivanov

2009-01-01

Full Text Available The physics of the electromagnetic field is considered. The analysis of electromagnetic radiation on the human-being, the origin of which is the vehicle the electric vehicle, the hybrid vehicle is being considered. The monitoring of electromagnetic radiation of vehicles is carried out.

Classifying Classifications

DEFF Research Database (Denmark)

Debus, Michael S.

2017-01-01

This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

A TWO-STEP CLASSIFICATION APPROACH TO DISTINGUISHING SIMILAR OBJECTS IN MOBILE LIDAR POINT CLOUDS

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H. He

2017-09-01

Full Text Available Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

Knowledge basis concerning the market for electric vehicles and plug-in hybrids (KAMEL); Kunskapsunderlag angaaende marknaden foer elfordon och laddhybrider (KAMEL)

Energy Technology Data Exchange (ETDEWEB)

2009-07-01

The Swedish Energy Agency is proposing a four-year demonstration and development program to support the market introduction of electric vehicles and plug-in hybrids (electric vehicle applications). This in light of the uncertainties in the market introduction of vehicles, cost of key components such as batteries, the possibility of industrial development in Sweden and the uncertainty of how to complement to existing charging infrastructure in an socioeconomic way. In addition to this, the more general aid to electric cars and plug-in hybrids is to be reviewed. Today, electric vehicles, hybrids, ethanol vehicles, bio-gas vehicles and fuel-efficient vehicles, are supported by the green car definition and the environmental classification system. Furthermore, ethanol vehicles and biogas vehicles have support through tax reduction for biofuels. Overall, community support for electric vehicles and plug-in hybrids is lower than for the introduction of ethanol vehicles and biogas vehicles which do not reflect the environmental benefits they have. The review of the general subsidies for electric vehicles and the support through a demonstration program represent a concerted strategy to overcome the initially very high additional cost of these vehicles

Relationship of aortic valve calcification with coronary artery calcium severity: the Multi-Ethnic Study of Atherosclerosis (MESA).

Science.gov (United States)

Nasir, Khurram; Katz, Ronit; Al-Mallah, Mouaz; Takasu, Junichiro; Shavelle, David M; Carr, Jeffery J; Kronmal, Richard; Blumenthal, Roger S; O'Brien, Kevin; Budoff, Matthew J

2010-01-01

Aortic valve calcification (AVC) and atherosclerosis share causative and pathologic features. We evaluated the relationship between AVC and coronary artery calcium (CAC) severity in the Multi-Ethnic Study of Atherosclerosis (MESA). Men and women aged 45-84 years (n=6809; mean age, 62 years) were studied. The presence and burden of AVC and CAC were determined by noncontrast cardiac computed tomography. Relative risk regression was used to model the probability of AVC as a function of CAC > 0 as well as CAC categories (0, 1-99, 100-399, and > or = 400) with the reference group being CAC=0. The prevalence of AVC and CAC was 13% and 50%, respectively. Among those without CAC, the prevalence of AVC was 5% and increased across levels of CAC severity such that 14%, 25%, and 38% had AVC with increasing CAC scores of 1-99, 100-399, and > or = 400, respectively (P for trendAVC among those with mild CAC (1-99) was 1.83 (95% CI, 1.45-2.31) and increased to 3.36 (95% CI, 2.56-4.42) for CAC > or = 400. Similar statistically significant increased risk of AVC was found when CAC was assessed as a continuous variable. Our study shows that AVC is independently associated with increasing severity of CAC. 2010 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Worsening atrioventricular conduction after hospital discharge in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention: the HORIZONS-AMI trial.

Science.gov (United States)

Kosmidou, Ioanna; Redfors, Björn; McAndrew, Thomas; Embacher, Monica; Mehran, Roxana; Dizon, José M; Ben-Yehuda, Ori; Mintz, Gary S; Stone, Gregg W

2017-11-01

The chronic effects of ST-segment elevation myocardial infarction (STEMI) on the atrioventricular conduction (AVC) system have not been elucidated. This study aimed to evaluate the incidence, predictors, and outcomes of worsened AVC post-STEMI in patients treated with a primary percutaneous coronary intervention (PCI). The current analysis included patients from the HORIZONS-AMI trial who underwent primary PCI and had available ECGs. Patients with high-grade atrioventricular block or pacemaker implant at baseline were excluded. Analysis of ECGs excluding the acute hospitalization period indicated worsened AVC in 131 patients (worsened AVC group) and stable AVC in 2833 patients (stable AVC group). Patients with worsened AVC were older, had a higher frequency of hypertension, diabetes, renal insufficiency, previous coronary artery bypass grafting, and predominant left anterior descending culprit lesions. Predictors of worsened AVC included age, hypertension, and previous history of coronary artery disease. Worsened AVC was associated with an increased rate of all-cause death and major adverse cardiac events (death, myocardial infarction, ischemic target vessel revascularization, and stroke) as well as death or reinfarction at 3 years. On multivariable analysis, worsened AVC remained an independent predictor of all-cause death (hazard ratio: 2.005, confidence interval: 1.051-3.827, P=0.0348) and major adverse cardiac events (hazard ratio 1.542, confidence interval: 1.059-2.244, P=0.0238). Progression of AVC system disease in patients with STEMI treated with primary PCI is uncommon, occurs primarily in the setting of anterior myocardial infarction, and portends a high risk for death and major adverse cardiac events.

Data fusion for target tracking and classification with wireless sensor network

Science.gov (United States)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

Science.gov (United States)

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

A review of supervised object-based land-cover image classification

Science.gov (United States)

Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue

2017-08-01

vehicle) or agricultural sites where it also correlates with the number of targeted classes. More than 95.6% of studies involve an area less than 300 ha, and the spatial resolution of images is predominantly between 0 and 2 m. Furthermore, we identify some methods that may advance supervised object-based image classification. For example, deep learning and type-2 fuzzy techniques may further improve classification accuracy. Lastly, scientists are strongly encouraged to report results of uncertainty studies to further explore the effects of varied factors on supervised object-based image classification.

Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

Directory of Open Access Journals (Sweden)

Haijian Bai

2017-01-01

Full Text Available Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC. Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lane-changing model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

Serum phosphate is associated with aortic valve calcification in the Multi-ethnic Study of Atherosclerosis (MESA).

Science.gov (United States)

Linefsky, Jason P; O'Brien, Kevin D; Sachs, Michael; Katz, Ronit; Eng, John; Michos, Erin D; Budoff, Matthew J; de Boer, Ian; Kestenbaum, Bryan

2014-04-01

This study sought to investigate associations of phosphate metabolism biomarkers with aortic valve calcification (AVC). Calcific aortic valve disease (CAVD) is a common progressive condition that involves inflammatory and calcification mediators. Currently there are no effective medical treatments, but mineral metabolism pathways may be important in the development and progression of disease. We examined associations of phosphate metabolism biomarkers, including serum phosphate, urine phosphate, parathyroid hormone (PTH) and serum fibroblast growth factor (FGF)-23, with CT-assessed AVC at study baseline and in short-term follow-up in 6814 participants of the Multi-Ethnic Study of Atherosclerosis (MESA). At baseline, AVC prevalence was 13.2%. Higher serum phosphate levels were associated with significantly greater AVC prevalence (relative risk 1.3 per 1 mg/dL increment, 95% confidence incidence: 1.1 to 1.5, pAVC. Average follow-up CT evaluation was 2.4 years (range 0.9-4.9 years) with an AVC incidence of 4.1%. Overall, phosphate metabolism biomarkers were not associated with incident AVC except in the top FGF-23 quartile. Serum phosphate levels are significantly associated with AVC prevalence. Further study of phosphate metabolism as a modifiable risk factor for AVC is warranted. Published by Elsevier Ireland Ltd.

Time Series of Images to Improve Tree Species Classification

Science.gov (United States)

Miyoshi, G. T.; Imai, N. N.; de Moraes, M. V. A.; Tommaselli, A. M. G.; Näsi, R.

2017-10-01

Tree species classification provides valuable information to forest monitoring and management. The high floristic variation of the tree species appears as a challenging issue in the tree species classification because the vegetation characteristics changes according to the season. To help to monitor this complex environment, the imaging spectroscopy has been largely applied since the development of miniaturized sensors attached to Unmanned Aerial Vehicles (UAV). Considering the seasonal changes in forests and the higher spectral and spatial resolution acquired with sensors attached to UAV, we present the use of time series of images to classify four tree species. The study area is an Atlantic Forest area located in the western part of São Paulo State. Images were acquired in August 2015 and August 2016, generating three data sets of images: only with the image spectra of 2015; only with the image spectra of 2016; with the layer stacking of images from 2015 and 2016. Four tree species were classified using Spectral angle mapper (SAM), Spectral information divergence (SID) and Random Forest (RF). The results showed that SAM and SID caused an overfitting of the data whereas RF showed better results and the use of the layer stacking improved the classification achieving a kappa coefficient of 18.26 %.

Myocardial Tbx20 regulates early atrioventricular canal formation and endocardial epithelial-mesenchymal transition via Bmp2.

Science.gov (United States)

Cai, Xiaoqiang; Nomura-Kitabayashi, Aya; Cai, Weibin; Yan, Jianyun; Christoffels, Vincent M; Cai, Chen-Leng

2011-12-15

During early embryogenesis, the formation of the cardiac atrioventricular canal (AVC) facilitates the transition of the heart from a linear tube into a chambered organ. However, the genetic pathways underlying this developmental process are poorly understood. The T-box transcription factor Tbx20 is expressed predominantly in the AVC of early heart tube. It was shown that Tbx20 activates Nmyc1 and suppresses Tbx2 expression to promote proliferation and specification of the atrial and ventricular chambers, yet it is not known if Tbx20 is involved in early AVC development. Here, we report that mice lacking Tbx20 in the AVC myocardium fail to form the AVC constriction, and the endocardial epithelial-mesenchymal transition (EMT) is severely perturbed. Tbx20 maintains expression of a variety of genes, including Bmp2, Tbx3 and Hand1 in the AVC myocardium. Intriguingly, we found Bmp2 downstream genes involved in the EMT initiation are also downregulated. In addition, re-expression of Bmp2 in the AVC myocardium substantially rescues the EMT defects resulting from the lack of Tbx20, suggesting Bmp2 is one of the key downstream targets of Tbx20 in AVC development. Our data support a complex signaling network with Tbx20 suppressing Tbx2 in the AVC myocardium but also indirectly promoting Tbx2 expression through Bmp2. The spatiotemporal expression of Tbx2 in the AVC appears to be balanced between these two opposing signals. Overall, our study provides genetic evidence that Tbx20 has essential roles in regulating AVC development that coordinate early cardiac chamber formation. Copyright © 2011 Elsevier Inc. All rights reserved.

Effects of vehicle power on passenger vehicle speeds.

Science.gov (United States)

McCartt, Anne T; Hu, Wen

2017-07-04

During the past 2 decades, there have been large increases in mean horsepower and the mean horsepower-to-vehicle weight ratio for all types of new passenger vehicles in the United States. This study examined the relationship between travel speeds and vehicle power, defined as horsepower per 100 pounds of vehicle weight. Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit. After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant. Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash

Short-term optimization of the new Avce pumping plant and three existing hydro power plants on the Soca river in Slovenia

International Nuclear Information System (INIS)

Bregar, Zvonko

2007-01-01

In the following years a new pumping plant Avce is going to join the existing cascade of three small-regulating-basin hydro power plants (HPPs) on the Soca river in Slovenia. The pumping plant operation will have to be synchronous to the operation of existing plants and vice versa since all four plants depend upon the same inflow and since they all belong to the same generation company that buys and sells electricity to a day-ahead electricity market. The Soca river has torrent alpine characteristics so there are doubts about the operation of the system in frequent dry seasons. As shown in this article, such questions can be effectively solved by first presenting the hydro system of four HPPs under study as a directed graph and then as a mixed integer linear program (MILP): a set of equations and inequations modeling technical issues of HPPs and a target function (the day-ahead market price) modeling the electricity market. A small and simple MILP model called Flores has been used for this study. The MILP approach requires only to specify the problem since the solution is found by using available commercial computer solvers. It can be applied on-line and it can be augmented to include also the transmission constraints, ancillary services, etc. (author)

Short-term optimization of the new Avce pumping plant and three existing hydro power plants on the Soca river in Slovenia

Energy Technology Data Exchange (ETDEWEB)

Bregar, Zvonko [Milan Vidmar Electric Power Research Institute, Hajdrihova 2, SI-1000 Ljubljana (Slovenia)

2007-08-15

In the following years a new pumping plant Avce is going to join the existing cascade of three small-regulating-basin hydro power plants (HPPs) on the Soca river in Slovenia. The pumping plant operation will have to be synchronous to the operation of existing plants and vice versa since all four plants depend upon the same inflow and since they all belong to the same generation company that buys and sells electricity to a day-ahead electricity market. The Soca river has torrent alpine characteristics so there are doubts about the operation of the system in frequent dry seasons. As shown in this article, such questions can be effectively solved by first presenting the hydro system of four HPPs under study as a directed graph and then as a mixed integer linear program (MILP): a set of equations and inequations modeling technical issues of HPPs and a target function (the day-ahead market price) modeling the electricity market. A small and simple MILP model called Flores has been used for this study. The MILP approach requires only to specify the problem since the solution is found by using available commercial computer solvers. It can be applied on-line and it can be augmented to include also the transmission constraints, ancillary services, etc. (author)

Relationship of Aortic Wall Distensibility to Mitral and Aortic Valve Calcification: The Multi-Ethnic Study of Atherosclerosis.

Science.gov (United States)

Cohoon, Kevin P; Criqui, Michael H; Budoff, Matthew J; Lima, Joao A; Blaha, Michael J; Decker, Paul A; Durazo, Ramon; Liu, Kiang; Kramer, Holly

2018-05-01

Data are limited on whether valvular calcification is associated with aortic wall stiffness. We tested whether aortic valve calcification (AVC) and/or mitral valve calcification (MVC) is inversely associated with aortic distensibility (AD). Cross-sectional study conducted in a subset of the Multi-Ethnic Study of Atherosclerosis (MESA) included 3676 MESA participants aged 44 to 84 years with AD measured with magnetic resonance imaging and with AVC and MVC measured with noncontrast cardiac computed tomography scans. Both AVC and MVC were divided into 3 categories: zero, AVC and MVC, while 6% (n = 211) and 4% (n = 156) had low, and 6% (n = 209) and 4% (n = 155) had high values of AVC and MVC, respectively. The AVC was independently associated with AD after adjusting for age, gender, and ethnicity ( P = .035). No association was noted between AVC groups and AD after adjustment for all covariates or MVC groups and AD in any model.

Association between aortic valve calcification measured on non-contrast computed tomography and aortic valve stenosis in the general population

DEFF Research Database (Denmark)

Paulsen, Niels Herluf; Bønløkke Carlsen, Bjarke; Dahl, Jordi Sanchez

2016-01-01

BACKGROUND: Aortic valve calcification (AVC) measured on non-contrast computed tomography (CT) has shown correlation to severity of aortic valve stenosis (AS) and mortality in patients with known AS. The aim of this study was to determine the association of CT verified AVC and subclinical...... AS in a general population undergoing CT. METHODS: CT scans from 566 randomly selected male participants (age 65-74) in the Danish cardiovascular screening study (DANCAVAS) were analyzed for AVC. All participants with a moderately or severely increased AVC score (≥300 arbitrary units (AU)) and a matched control...... ICD leads 16 individuals were excluded from the AVC scoring. Moderate or severe increased AVC was observed in 10.7% (95% CI: 8.4-13.7). Echocardiography was performed in 101 individuals; 32.7% (95% CI: 21.8 to 46.0) with moderate or high AVC score had moderate or severe AS, while none with no or low...

Electric vehicle equipment for grid-integrated vehicles

Science.gov (United States)

Kempton, Willett

2013-08-13

Methods, systems, and apparatus for interfacing an electric vehicle with an electric power grid are disclosed. An exemplary apparatus may include a station communication port for interfacing with electric vehicle station equipment (EVSE), a vehicle communication port for interfacing with a vehicle management system (VMS), and a processor coupled to the station communication port and the vehicle communication port to establish communication with the EVSE via the station communication port, receive EVSE attributes from the EVSE, and issue commands to the VMS to manage power flow between the electric vehicle and the EVSE based on the EVSE attributes. An electric vehicle may interface with the grid by establishing communication with the EVSE, receiving the EVSE attributes, and managing power flow between the EVE and the grid based on the EVSE attributes.

The influence of aortic valve calcification on the risk of periprocedural myocardial injury after elective coronary intervention.

Science.gov (United States)

Chen, Zhang-Wei; Yang, Hong-Bo; Chen, Ying-Hua; Qian, Ju-Ying; Shu, Xian-Hong; Ge, Jun-Bo

2015-10-01

Aortic valve calcification (AVC) is a common progressive condition that involves several inflammatory and atherosclerotic mediators. However, it is unclear whether the occurrence of periprocedural myocardial injury (PMI) after elective coronary intervention is associated with AVC in stable coronary artery disease (CAD) patients. A total of 530 stable CAD patients who underwent elective coronary intervention were enrolled in this clinical study. High sensitive cardiac troponin T (hs-cTnT) was detected before and after the procedure. PMI was defined as hs-cTnT after coronary intervention higher than 99th percentile upper reference limit (URL). All patients underwent echocardiography to detect the occurrence of AVC. Univariate and multivariate analyses were applied to analyze risk factors of PMI. A total of 210 patients (39.6 %) were diagnosed with PMI after elective coronary intervention. Compared with non-AVC patients (n = 386), AVC patients (n = 144) had higher rate of PMI (64.6 vs. 30.3 %, P AVC had higher Gensini score (39.9 ± 26.6 vs. 34.2 ± 22.1, P AVC patients had increased risk of PMI compared with non-AVC patients. Importantly, even after being adjusted by multivariate analysis, AVC still independently increased the risk of PMI (OR = 3.329, 95 % CI = 2.087-5.308, P AVC significantly increased the risk of PMI after elective coronary intervention. It could be one of the independent predictors for PMI in stable CAD patients.

Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

Science.gov (United States)

Dieckman, Eric Allen

In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

Aortic valve calcification as a predictor of location and severity of paravalvular regurgitation after transcatheter aortic valve implantation.

Science.gov (United States)

Koh, Ezra Y; Lam, Kayan Y; Bindraban, Navin R; Cocchieri, Riccardo; Planken, R Nils; Koch, Karel T; Baan, Jan; de Mol, Bas A; Marquering, Henk A

2015-03-01

To determine whether the location of aortic valve calcium (AVC) influences the location of paravalvular regurgitation (PR). PR is an adverse effect of transcatheter aortic valve implantation (TAVI) with a negative effect on long-term patient survival. The relationship between AVC and the occurrence of PR has been documented. However, the relationship between the distribution of AVC and the location of PR is still sparsely studied. The purpose of this study was to correlate severity and location of AVC with PR in patients treated with TAVI. Fifty-six consecutive patients who underwent transaortic or transapical TAVI and had preoperative computed tomography scans were included in this retrospective study. The volume, mass and location of AVC was determined and compared between patients with and without PR using a non-parametric t-test. Postoperative echocardiography was performed to determine the presence and location of PR, which was associated with the cusp with highest AVC using a χ(2) test. Valve deployment was successful in all 56 patients. PR was present in 38 patients (68%) after TAVI. There was a non-significantly higher volume of AVC in the PR group [214 (70-418) vs 371 (254-606) cm(3), P = 0.15]. AVC mass was significantly higher in patients with PR than in patients without PR [282 (188-421) vs 142 (48-259) mg, respectively, P = 0.043]. The location of PR was determined in 36 of these patients. Of these 36 patients, PR occurred at the cusp with the highest AVC in 20 patients (56%, χ(2) P = 0.030). In our population, PR was associated with greater AVC mass. Moreover, the location of PR was associated with the cusp with the highest amount of AVC. © The Author 2014. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Beyond Framingham risk factors and coronary calcification: does aortic valve calcification improve risk prediction? The Heinz Nixdorf Recall Study.

Science.gov (United States)

Kälsch, Hagen; Lehmann, Nils; Mahabadi, Amir A; Bauer, Marcus; Kara, Kaffer; Hüppe, Patricia; Moebus, Susanne; Möhlenkamp, Stefan; Dragano, Nico; Schmermund, Axel; Stang, Andreas; Jöckel, Karl-Heinz; Erbel, Raimund

2014-06-01

Aortic valve calcification (AVC) is considered a manifestation of atherosclerosis. In this study, we investigated whether AVC adds to cardiovascular risk prediction beyond Framingham risk factors and coronary artery calcification (CAC). A total of 3944 subjects from the population based Heinz Nixdorf Recall Study (59.3±7.7 years; 53% females) were evaluated for coronary events, stroke, and cardiovascular disease (CVD) events (including all plus CV death) over 9.1±1.9 years. CT scans were performed to quantify AVC. Cox proportional hazards regressions and Harrell's C were used to examine AVC as event predictor in addition to risk factors and CAC. During follow-up, 138 (3.5%) subjects experienced coronary events, 101 (2.6%) had a stroke, and 257 (6.5%) experienced CVD events. In subjects with AVC>0 versus AVC=0 the incidence of coronary events was 8.0% versus 3.0% (pAVC scores (pAVC scores (3rd tertile) remained independently associated with coronary events (HR 2.21, 95% CI 1.28 to 3.81) and CVD events (HR 1.67, 95% CI 1.08 to 2.58). After further adjustment for CAC score, HRs were attenuated (coronary events 1.55, 95% CI 0.89 to 2.69; CVD events 1.29, 95% CI 0.83 to 2.00). When adding AVC to the model containing traditional risk factors and CAC, Harrell's C indices did not increase for coronary events (from 0.744 to 0.744) or CVD events (from 0.759 to 0.759). AVC is associated with incident coronary and CVD events independent of Framingham risk factors. However, AVC fails to improve cardiovascular event prediction over Framingham risk factors and CAC. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

O espessamento da íntima-média associa-se independentemente ao Acidente Vascular Cerebral Isquêmico

Directory of Open Access Journals (Sweden)

Dário Freitas

2012-06-01

Full Text Available FUNDAMENTO: O Acidente Vascular Cerebral (AVC constitui uma das primeiras causas de morte a nível mundial. A importância do espessamento da íntima-média na estratificação de risco cardiovascular tem sido recorrentemente estudada; contudo, essa relação gera ainda alguma controvérsia. OBJETIVOS: Determinar se o espessamento da íntima-média na Artéria Carótida Comum (ACC pode ser utilizado como um marcador independente de alto risco para a ocorrência do AVC. MÉTODOS: A amostra compreende um grupo de 948 doentes consecutivamente estudados por Triplex Scan Cervical no período compreendido entre janeiro de 2004 e junho de 2009. Esses doentes foram agrupados em razão da presença ou ausência de AVC recente, do que resultou um grupo de doentes com AVC Isquémico (AVC I (n = 452, 48%, outro com AVC Hemorrágico (AVC H (n = 22, 2% e um grupo de doentes Sem Eventos (n = 474, 50%. RESULTADOS: Na análise de regressão logística ajustada para fatores de risco cardiovascular clássicos, o espessamento da íntima-média na ACC associou-se significativamente e de forma aproximadamente linear com o AVC I (Odds Ratio = 1.808, Intervalo de Confiança: 1.291-2.534, p = 0,01, mas não com o AVC H (p = ns. Uma interação significativa com a idade foi também encontrada, demonstrando-se uma capacidade discriminativa do risco de AVC I maior em indivíduos com idade inferior a 50 anos. CONCLUSÕES: O espessamento da íntima-média na ACC revelou-se um preditor de risco independente para o AVC I, mas não para AVC H reforçando assim a utilidade da sua avaliação na prática clínica. (Arq Bras Cardiol. 2012; [online].ahead print, PP.0-0

Use of unmanned aerial vehicles for efficient beach litter monitoring

KAUST Repository

Martin, Cecilia

2018-05-05

A global beach litter assessment is challenged by use of low-efficiency methodologies and incomparable protocols that impede data integration and acquisition at a national scale. The implementation of an objective, reproducible and efficient approach is therefore required. Here we show the application of a remote sensing based methodology using a test beach located on the Saudi Arabian Red Sea coastline. Litter was recorded via image acquisition from an Unmanned Aerial Vehicle, while an automatic processing of the high volume of imagery was developed through machine learning, employed for debris detection and classification in three categories. Application of the method resulted in an almost 40 times faster beach coverage when compared to a standard visual-census approach. While the machine learning tool faced some challenges in correctly detecting objects of interest, first classification results are promising and motivate efforts to further develop the technique and implement it at much larger scales.

Use of unmanned aerial vehicles for efficient beach litter monitoring

KAUST Repository

Martin, Cecilia; Parkes, Stephen; Zhang, Qiannan; Zhang, Xiangliang; McCabe, Matthew; Duarte, Carlos M.

2018-01-01

A global beach litter assessment is challenged by use of low-efficiency methodologies and incomparable protocols that impede data integration and acquisition at a national scale. The implementation of an objective, reproducible and efficient approach is therefore required. Here we show the application of a remote sensing based methodology using a test beach located on the Saudi Arabian Red Sea coastline. Litter was recorded via image acquisition from an Unmanned Aerial Vehicle, while an automatic processing of the high volume of imagery was developed through machine learning, employed for debris detection and classification in three categories. Application of the method resulted in an almost 40 times faster beach coverage when compared to a standard visual-census approach. While the machine learning tool faced some challenges in correctly detecting objects of interest, first classification results are promising and motivate efforts to further develop the technique and implement it at much larger scales.

Classification of Maize in Complex Smallholder Farming Systems Using UAV Imagery

Directory of Open Access Journals (Sweden)

Ola Hall

2018-06-01

Full Text Available Yield estimates and yield gap analysis are important for identifying poor agricultural productivity. Remote sensing holds great promise for measuring yield and thus determining yield gaps. Farming systems in sub-Saharan Africa (SSA are commonly characterized by small field size, intercropping, different crop species with similar phenologies, and sometimes high cloud frequency during the growing season, all of which pose real challenges to remote sensing. Here, an unmanned aerial vehicle (UAV system based on a quadcopter equipped with two consumer-grade cameras was used for the delineation and classification of maize plants on smallholder farms in Ghana. Object-oriented image classification methods were applied to the imagery, combined with measures of image texture and intensity, hue, and saturation (IHS, in order to achieve delineation. It was found that the inclusion of a near-infrared (NIR channel and red–green–blue (RGB spectra, in combination with texture or IHS, increased the classification accuracy for both single and mosaic images to above 94%. Thus, the system proved suitable for delineating and classifying maize using RGB and NIR imagery and calculating the vegetation fraction, an important parameter in producing yield estimates for heterogeneous smallholder farming systems.

Patent Keyword Extraction Algorithm Based on Distributed Representation for Patent Classification

Directory of Open Access Journals (Sweden)

Jie Hu

2018-02-01

Full Text Available Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM classification, which are valuable when human-annotated keywords are not available. We used a standard benchmark dataset and a homemade patent dataset to evaluate the performance of PKEA. Our patent dataset includes 2500 patents from five distinct technological fields related to autonomous cars (GPS systems, lidar systems, object recognition systems, radar systems, and vehicle control systems. We compared our method with Frequency, Term Frequency-Inverse Document Frequency (TF-IDF, TextRank and Rapid Automatic Keyword Extraction (RAKE. The experimental results show that our proposed algorithm provides a promising way to extract keywords from patent texts for patent classification.

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

Directory of Open Access Journals (Sweden)

Matheus dos Santos

2017-09-01

Full Text Available The submarine exploration using robots has been increasing in recent years. The automation of tasks such as monitoring, inspection, and underwater maintenance requires the understanding of the robot’s environment. The object recognition in the scene is becoming a critical issue for these systems. On this work, an underwater object classification pipeline applied in acoustic images acquired by Forward-Looking Sonar (FLS are studied. The object segmentation combines thresholding, connected pixels searching and peak of intensity analyzing techniques. The object descriptor extract intensity and geometric features of the detected objects. A comparison between the Support Vector Machine, K-Nearest Neighbors, and Random Trees classifiers are presented. An open-source tool was developed to annotate and classify the objects and evaluate their classification performance. The proposed method efficiently segments and classifies the structures in the scene using a real dataset acquired by an underwater vehicle in a harbor area. Experimental results demonstrate the robustness and accuracy of the method described in this paper.

A New Classification Approach Based on Multiple Classification Rules

OpenAIRE

Zhongmei Zhou

2014-01-01

A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

PAVS: A New Privacy-Preserving Data Aggregation Scheme for Vehicle Sensing Systems.

Science.gov (United States)

Xu, Chang; Lu, Rongxing; Wang, Huaxiong; Zhu, Liehuang; Huang, Cheng

2017-03-03

Air pollution has become one of the most pressing environmental issues in recent years. According to a World Health Organization (WHO) report, air pollution has led to the deaths of millions of people worldwide. Accordingly, expensive and complex air-monitoring instruments have been exploited to measure air pollution. Comparatively, a vehicle sensing system (VSS), as it can be effectively used for many purposes and can bring huge financial benefits in reducing high maintenance and repair costs, has received considerable attention. However, the privacy issues of VSS including vehicles' location privacy have not been well addressed. Therefore, in this paper, we propose a new privacy-preserving data aggregation scheme, called PAVS, for VSS. Specifically, PAVS combines privacy-preserving classification and privacy-preserving statistics on both the mean E(·) and variance Var(·), which makes VSS more promising, as, with minimal privacy leakage, more vehicles are willing to participate in sensing. Detailed analysis shows that the proposed PAVS can achieve the properties of privacy preservation, data accuracy and scalability. In addition, the performance evaluations via extensive simulations also demonstrate its efficiency.

78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

2013-11-18

...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and... response to requests from the U.S. cotton industry and ICE, AMS will offer a futures classification option...

Association of aortic valve calcification severity with the degree of aortic regurgitation after transcatheter aortic valve implantation.

Science.gov (United States)

Koos, Ralf; Mahnken, Andreas Horst; Dohmen, Guido; Brehmer, Kathrin; Günther, Rolf W; Autschbach, Rüdiger; Marx, Nikolaus; Hoffmann, Rainer

2011-07-15

This study sought to examine a possible relationship between the severity of aortic valve calcification (AVC), the distribution of AVC and the degree of aortic valve regurgitation (AR) after transcatheter aortic valve implantation (TAVI) for severe aortic stenosis (AS). 57 patients (22 men, 81 ± 5 years) with symptomatic AS and with a logistic EuroSCORE of 24 ± 12 were included. 38 patients (67%) received a third (18F)-generation CoreValve® aortic valve prosthesis, in 19 patients (33%) an Edwards SAPIEN™ prosthesis was implanted. Prior to TAVI dual-source computed tomography for assessment of AVC was performed. To determine the distribution of AVC the percentage of the calcium load of the most severely calcified cusp was calculated. After TAVI the degree of AR was determined by angiography and echocardiography. The severity of AR after TAVI was related to the severity and distribution of AVC. There was no association between the distribution of AVC and the degree of paravalvular AR after TAVI as assessed by angiography (r = -0.02, p = 0.88). Agatston AVC scores were significantly higher in patients with AR grade ≥ 3 (5055 ± 1753, n = 3) than in patients with AR grade AVC scores > 3000 were associated with a relevant paravalvular AR and showed a trend for increased need for second manoeuvres. There was a significant correlation between the severity of AVC and the degree of AR after AVR (r = 0.50, p AVC have an increased risk for a relevant AR after TAVI as well as a trend for increased need for additional procedures. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Relation of thoracic aortic and aortic valve calcium to coronary artery calcium and risk assessment.

Science.gov (United States)

Wong, Nathan D; Sciammarella, Maria; Arad, Yadon; Miranda-Peats, Romalisa; Polk, Donna; Hachamovich, Rory; Friedman, John; Hayes, Sean; Daniell, Anthony; Berman, Daniel S

2003-10-15

Aortic calcium, aortic valve calcium (AVC), and coronary artery calcium (CAC) have been associated with cardiovascular event risk. We examined the prevalence of thoracic aortic calcium (TAC) and AVC in relation to the presence and extent of CAC, cardiovascular risk factors, and estimated risk of coronary heart disease (CHD). In 2,740 persons without known CHD aged 20 to 79 years, CAC was assessed by electron beam- or multidetector-computed tomography. We determined the prevalence of TAC and AVC in relation to CAC, CHD risk factors, and predicted 10-year risk of CHD. A close correspondence of TAC and AVC was observed with CAC. TAC and AVC increased with age; by the eighth decade of life, the prevalence of TAC was similar to that of CAC (>80%), and 36% of men and 24% of women had AVC. Age, male gender, and low-density lipoprotein cholesterol were directly related to the likelihood of CAC, TAC, and AVC; higher diastolic blood pressure and cigarette smoking additionally predicted CAC. Body mass index and higher systolic and lower diastolic blood pressures were also related to TAC, and higher body mass index and lower diastolic blood pressure were related to AVC. Calculated risk of CHD increased with the presence of AVC and TAC across levels of CAC. TAC and AVC provided incremental value over CAC in association with the 10-year calculated risk of CHD. If longitudinal studies show an incremental value of aortic and aortic valve calcium over that of CAC for prediction of cardiovascular events, future guidelines for risk assessment incorporating CAC assessment may additionally incorporate the measurement of aortic and/or aortic valve calcium.

Atrial flutter with spontaneous 1:1 atrioventricular conduction in adults: an uncommon but frequently missed cause for syncope/presyncope.

Science.gov (United States)

Turitto, Gioia; Akhrass, Philippe; Leonardi, Marino; Saponieri, Cesare; Sette, Antonella; El-Sherif, Nabil

2009-01-01

To compare patients with atrial flutter (AFl) and 1:1 atrioventricular conduction (AVC) with patients with AFl and higher AVC. The characteristics of 19 patients with AFl and 1:1 AVC (group A) were compared with those of 116 consecutive patients with AFl and 2:1 AVC or higher degree AV block (group B). Age, gender, and left ventricular function were similar in the two groups. In group A versus group B, more patients had no structural heart disease (42% vs 17%, P AVC or vice versa was associated with small but definite changes in AFl CL, which showed larger variations in response to sympathetic stimulation. In group A patients who were studied off drugs, the atrial-His interval was not different from group B, but maximal atrial pacing rate with 1:1 AVC was faster. In group A, five patients were misdiagnosed as ventricular tachyarrhythmias, and three with a defibrillator received inappropriate shocks. Four patients had ablation of AVC and six had ablation of AFl circuit. The main difference between groups A and B may be an inherent capacity of the AV node for faster conduction, especially in response to increased sympathetic tone. The latter affects not only AVC but also the AFl CL. One should be aware of the different presentations of AFl with 1:1 AVC to avoid misdiagnosis/mismanagement and to consider the diagnosis in patients with narrow or wide QRS tachycardia and rates above 220/min.

Association of aortic valve calcification to the presence, extent, and composition of coronary artery plaque burden: from the Rule Out Myocardial Infarction using Computer Assisted Tomography (ROMICAT) trial.

Science.gov (United States)

Mahabadi, Amir A; Bamberg, Fabian; Toepker, Michael; Schlett, Christopher L; Rogers, Ian S; Nagurney, John T; Brady, Thomas J; Hoffmann, Udo; Truong, Quynh A

2009-10-01

Aortic valve calcification (AVC) is associated with cardiovascular risk factors and coronary artery calcification. We sought to determine whether AVC is associated with the presence and extent of overall plaque burden, as well as to plaque composition (calcified, mixed, and noncalcified). We examined 357 subjects (mean age 53 +/- 12 years, 61% male) who underwent contrast-enhanced electrocardiogram-gated 64-slice multidetector computed tomography from the ROMICAT trial for the assessment of presence and extent of coronary plaque burden according to the 17-coronary segment model and presence of AVC. Patients with AVC (n = 37, 10%) were more likely than those without AVC (n = 320, 90%) to have coexisting presence of any coronary plaque (89% vs 46%, P AVC had >3-fold increase odds of having any plaque (adjusted odds ratio [OR] 3.6, P = .047) and an increase of 2.5 segments of plaque (P AVC. When stratified by plaque composition, AVC was associated most with calcified plaque (OR 5.2, P = .004), then mixed plaque (OR 3.2, P = .02), but not with noncalcified plaque (P = .96). Aortic valve calcification is associated with the presence and greater extent of coronary artery plaque burden and may be part of the later stages of the atherosclerosis process, as its relation is strongest with calcified plaque, less with mixed plaque, and nonsignificant with noncalcified plaque. If AVC is present, consideration for aggressive medical therapy may be warranted.

HAND2 Target Gene Regulatory Networks Control Atrioventricular Canal and Cardiac Valve Development.

Science.gov (United States)

Laurent, Frédéric; Girdziusaite, Ausra; Gamart, Julie; Barozzi, Iros; Osterwalder, Marco; Akiyama, Jennifer A; Lincoln, Joy; Lopez-Rios, Javier; Visel, Axel; Zuniga, Aimée; Zeller, Rolf

2017-05-23

The HAND2 transcriptional regulator controls cardiac development, and we uncover additional essential functions in the endothelial to mesenchymal transition (EMT) underlying cardiac cushion development in the atrioventricular canal (AVC). In Hand2-deficient mouse embryos, the EMT underlying AVC cardiac cushion formation is disrupted, and we combined ChIP-seq of embryonic hearts with transcriptome analysis of wild-type and mutants AVCs to identify the functionally relevant HAND2 target genes. The HAND2 target gene regulatory network (GRN) includes most genes with known functions in EMT processes and AVC cardiac cushion formation. One of these is Snai1, an EMT master regulator whose expression is lost from Hand2-deficient AVCs. Re-expression of Snai1 in mutant AVC explants partially restores this EMT and mesenchymal cell migration. Furthermore, the HAND2-interacting enhancers in the Snai1 genomic landscape are active in embryonic hearts and other Snai1-expressing tissues. These results show that HAND2 directly regulates the molecular cascades initiating AVC cardiac valve development. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Factors associated with young adults' knowledge regarding family history of Stroke.

Science.gov (United States)

Lima, Maria Jose Melo Ramos; Moreira, Thereza Maria Magalhães; Florêncio, Raquel Sampaio; Braga, Predro

2016-11-21

to analyze the factors associated with young adults' knowledge regarding family history of stroke. an analytical transversal study, with 579 young adults from state schools, with collection of sociodemographic, clinical and risk factor-related variables, analyzed using logistic regression (backward elimination). a statistical association was detected between age, civil status, and classification of arterial blood pressure and abdominal circumference with knowledge of family history of stroke. In the final logistic regression model, a statistical association was observed between knowledge regarding family history of stroke and the civil status of having a partner (ORa=1.61[1.07-2.42]; p=0.023), abdominal circumference (ORa=0.98[0.96-0.99]; p=0.012) and normal arterial blood pressure (ORa=2.56[1.19-5.52]; p=0.016). an association was observed between socioeconomic factors and risk factors for stroke and knowledge of family history of stroke, suggesting the need for health education or even educational programs on this topic for the clientele in question. analisar os fatores associados ao conhecimento dos adultos jovens sobre histórico familiar de Acidente Vascular Cerebral (AVC). estudo transversal analítico, com 579 adultos jovens de escolas públicas, com coleta de variáveis sociodemográficas, clínicas e de fatores de risco em formulário, analisados utilizando-se regressão logística (backward elimination). detectou-se associação estatística de idade, situação conjugal, classificação da pressão arterial e circunferência abdominal com conhecimento do histórico familiar de AVC. No modelo final de regressão logística, observou-se associação estatística do conhecimento sobre histórico familiar de AVC com situação conjugal com companheiro (ORa=1,61[1,07-2,42]; p=0,023), circunferência abdominal (ORa=0,98[0,96-0,99]; p=0,012) e pressão arterial normal (ORa=2,56[1,19-5,52]; p=0,016). foi constatada associação de fatores socioeconômicos e de

Electric vehicle station equipment for grid-integrated vehicles

Science.gov (United States)

Kempton, Willett; Kiamilev, Fouad; McGee, Rodney; Waite, Nick

2017-09-05

Methods, systems, and apparatus transferring power between the grid and an electric vehicle are disclosed. The apparatus may include at least one vehicle communication port for interfacing with electric vehicle equipment (EVE) and a processor coupled to the at least one vehicle communication port to establish communication with the EVE, receive EVE attributes from the EVE, and transmit electric vehicle station equipment (EVSE) attributes to the EVE. Power may be transferred between the grid and the electric vehicle by maintaining EVSE attributes, establishing communication with the EVE, and transmitting the EVSE maintained attributes to the EVE.

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles.

Science.gov (United States)

Zhang, Duona; Ding, Wenrui; Zhang, Baochang; Xie, Chunyu; Li, Hongguang; Liu, Chunhui; Han, Jungong

2018-03-20

Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network.

Project, Aerodynamic, Thermal and Ballistic Analysis of a Lifting-Body Reentry Vehicle

Directory of Open Access Journals (Sweden)

A. N. Eliseev

2015-01-01

Full Text Available The objective of this article is to assess the prospects for an increasingly maneuverable reentry vehicle (RV of class "lifting body". In this regard, a project aerodynamic thermal and ballistic analysis has been conducted and the results have been compared with some well-known projects of the RV of the same class, made both in our country and abroad.The project analysis begins with finding a position of the "lifting body" vehicle in the classification system. Said classification distribution allows correct formulation of requirements for the conceptual structure of an aerospace vehicle at the initial stage of design in terms of system positions, since just the initial phase of the design often determines the success of the whole program.Then the paper compares design characteristics of the RV of class "lifting body" with vehicles such as X-15 rocket plane, the orbiter "Space Shuttle», M2-F2, HL-10, SV-5, and NASP "Hermes". It also gives a comparative estimate of the "lifting body" RV mass in a wide range of dimensions. The paper shows the sustainability of various landing complexes with reference to the Russian experience in developing the RV " Soyuz", and the conditions for using the vehicles of class "lifting body" in space programs.The aerodynamic analysis uses method for the approximate Newtonian theory to calculate aerodynamic characteristics of the perspective RV of class "lifting body" in the hypersonic descent phase. To obtain the desired aerodynamic performance and reduce balancing weight is contemplated a possibility to provide balance by introducing additional boards. The ballistic analysis considers four modes of descent:1. zero roll descent;2. maximum cross-range descent without restriction;3. maximum cross-range descent with restriction of maximum overload and maximum temperature;4. ballistic descent.To calculate the RV ballistic characteristics a system of equations of the vehicle motion in the atmosphere is used. The vehicle

Is overall similarity classification less effortful than single-dimension classification?

Science.gov (United States)

Wills, Andy J; Milton, Fraser; Longmore, Christopher A; Hester, Sarah; Robinson, Jo

2013-01-01

It is sometimes argued that the implementation of an overall similarity classification is less effortful than the implementation of a single-dimension classification. In the current article, we argue that the evidence securely in support of this view is limited, and report additional evidence in support of the opposite proposition--overall similarity classification is more effortful than single-dimension classification. Using a match-to-standards procedure, Experiments 1A, 1B and 2 demonstrate that concurrent load reduces the prevalence of overall similarity classification, and that this effect is robust to changes in the concurrent load task employed, the level of time pressure experienced, and the short-term memory requirements of the classification task. Experiment 3 demonstrates that participants who produced overall similarity classifications from the outset have larger working memory capacities than those who produced single-dimension classifications initially, and Experiment 4 demonstrates that instructions to respond meticulously increase the prevalence of overall similarity classification.

Supervised Learning Applied to Air Traffic Trajectory Classification

Science.gov (United States)

Bosson, Christabelle; Nikoleris, Tasos

2018-01-01

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Association between aortic valve calcification and myocardial ischemia, especially in asymptomatic patients.

Science.gov (United States)

Yamazato, Ryo; Yamamoto, Hideya; Tadehara, Futoshi; Teragawa, Hiroki; Kurisu, Satoshi; Dohi, Yoshihiro; Ishibashi, Ken; Kunita, Eiji; Utsunomiya, Hiroto; Oka, Toshiharu; Kihara, Yasuki

2012-08-01

Aortic valve calcification (AVC) is recognized as a manifestation of systemic arteriosclerosis. However, it is unclear whether AVC is associated with myocardial ischemia. Stress myocardial perfusion SPECT (MPS) is widely used for the diagnosis of myocardial ischemia. However, routine MPS is not recommended, particularly in asymptomatic patients. Accordingly, we investigated the hypothesis that the presence of AVC is strongly associated with inducible myocardial ischemia, even among asymptomatic patients. We investigated 669 consecutive patients who underwent both adenosine stress (201)Tl MPS and echocardiography. We evaluated the extent and severity of myocardial ischemia by the summed difference score (SDS). We defined the presence of myocardial ischemia as SDS ≥ 3 and moderate to severe ischemia as SDS ≥ 8. We classified the severity of AVC according to the number of affected aortic leaflets. We also compared the mean SDS and the prevalence of SDS ≥ 3 and SDS ≥ 8 among patients stratified by the severity of AVC. The presence of AVC was significantly associated with myocardial ischemia (odds ratio [OR], 1.56; 95% confidence interval [CI], 1.10-2.23; P = 0.013) and moderate to severe ischemia (OR, 2.16; 95% CI, 1.26-3.80; P = 0.0061). In 311 asymptomatic patients, AVC was strongly associated with moderate to severe ischemia (OR, 4.31; 95% CI, 1.67-12.8; P = 0.0043). However, the SDS value and the prevalence of SDS ≥ 3 and SDS ≥ 8 did not increase with increasing number of affected aortic leaflets. The presence of AVC may be associated with the presence of myocardial ischemia, particularly in asymptomatic patients. However, we found no association between the extent of AVC and inducible myocardial ischemia. The presence of AVC may be a useful anatomic marker to help identify patients at high risk of myocardial ischemia, particularly asymptomatic patients.

Serum magnesium, phosphorus, and calcium levels and subclinical calcific aortic valve disease: A population-based study.

Science.gov (United States)

Hisamatsu, Takashi; Miura, Katsuyuki; Fujiyoshi, Akira; Kadota, Aya; Miyagawa, Naoko; Satoh, Atsushi; Zaid, Maryam; Yamamoto, Takashi; Horie, Minoru; Ueshima, Hirotsugu

2018-06-01

Calcific aortic valve disease (CAVD) is the most common valve disease. Although micronutrients are known to contribute to cardiovascular disease, the relationship with CAVD remains poorly evaluated. We examined the association of serum levels of magnesium, phosphorus, and calcium with prevalence, incidence, and progression of aortic valve calcification (AVC). We conducted a prospective study in a population-based sample of Japanese men aged 40-79 years without known cardiovascular disease and chronic kidney disease at baseline, and quantified AVC from serial computed tomographic images with the Agatston method. Of 938 participants at baseline (mean age, 63.7 ± 9.9 years), AVC prevalence was observed in 173 (18.4%). Of 596 participants without baseline AVC at follow-up (median duration, 5.1 years), AVC incidence was observed in 138 (23.2%). After adjustment for demographics, behaviors and cardiovascular risk factors, relative risks (95% confidence intervals) in the highest versus lowest categories of serum magnesium, phosphorus, and calcium were 0.62 (0.44-0.86), 1.45 (1.02-2.04), and 1.43 (0.95-2.15), respectively, for AVC prevalence and 0.62 (0.42-0.92), 1.93 (1.28-2.91), and 1.09 (0.77-1.55), respectively, for AVC incidence. Their linear trends of serum magnesium and phosphorus were also all statistically significant. Of 131 participants with baseline AVC, there was no association of any serum micronutrients with AVC progression. Serum magnesium was inversely associated, while serum phosphorus was positively associated with AVC prevalence and incidence, suggesting that these serum micronutrients may be potential candidates for risk prediction or prevention of CAVD, and warranting further studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Computed Tomography Aortic Valve Calcium Scoring in Patients With Aortic Stenosis.

Science.gov (United States)

Pawade, Tania; Clavel, Marie-Annick; Tribouilloy, Christophe; Dreyfus, Julien; Mathieu, Tiffany; Tastet, Lionel; Renard, Cedric; Gun, Mesut; Jenkins, William Steven Arthur; Macron, Laurent; Sechrist, Jacob W; Lacomis, Joan M; Nguyen, Virginia; Galian Gay, Laura; Cuéllar Calabria, Hug; Ntalas, Ioannis; Cartlidge, Timothy Robert Graham; Prendergast, Bernard; Rajani, Ronak; Evangelista, Arturo; Cavalcante, João L; Newby, David E; Pibarot, Philippe; Messika Zeitoun, David; Dweck, Marc R

2018-03-01

Computed tomography aortic valve calcium scoring (CT-AVC) holds promise for the assessment of patients with aortic stenosis (AS). We sought to establish the clinical utility of CT-AVC in an international multicenter cohort of patients. Patients with AS who underwent ECG-gated CT-AVC within 3 months of echocardiography were entered into an international, multicenter, observational registry. Optimal CT-AVC thresholds for diagnosing severe AS were determined in patients with concordant echocardiographic assessments, before being used to arbitrate disease severity in those with discordant measurements. In patients with long-term follow-up, we assessed whether CT-AVC thresholds predicted aortic valve replacement and death. In 918 patients from 8 centers (age, 77±10 years; 60% men; peak velocity, 3.88±0.90 m/s), 708 (77%) patients had concordant echocardiographic assessments, in whom CT-AVC provided excellent discrimination for severe AS (C statistic: women 0.92, men 0.89). Our optimal sex-specific CT-AVC thresholds (women 1377 Agatston unit and men 2062 Agatston unit) were nearly identical to those previously reported (women 1274 Agatston unit and men 2065 Agatston unit). Clinical outcomes were available in 215 patients (follow-up 1029 [126-2251] days). Sex-specific CT-AVC thresholds independently predicted aortic valve replacement and death (hazard ratio, 3.90 [95% confidence interval, 2.19-6.78]; P AVC scores, which again were an independent predictor of clinical outcomes (hazard ratio, 3.67 [95% confidence interval, 1.39-9.73]; P =0.010). Sex-specific CT-AVC thresholds accurately identify severe AS and provide powerful prognostic information. These findings support their integration into routine clinical practice. URL: http://www.clinicaltrials.gov. Unique identifiers: NCT01358513, NCT02132026, NCT00338676, NCT00647088, NCT01679431. © 2018 American Heart Association, Inc.

Electric-Drive Vehicles

Energy Technology Data Exchange (ETDEWEB)

Septon, Kendall K [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-09-11

Electric-drive vehicles use electricity as their primary fuel or to improve the efficiency of conventional vehicle designs. These vehicles can be divided into three categories: Hybrid electric vehicles (HEVs), Plug-in hybrid electric vehicles (PHEVs), All-electric vehicles (EVs). Together, PHEVs and EVs can also be referred to as plug-in electric vehicles (PEVs).

Electric-Drive Vehicles

Energy Technology Data Exchange (ETDEWEB)

None

2017-09-01

Electric-drive vehicles use electricity as their primary fuel or to improve the efficiency of conventional vehicle designs. These vehicles can be divided into three categories: Hybrid electric vehicles (HEVs), Plug-in hybrid electric vehicles (PHEVs), All-electric vehicles (EVs). Together, PHEVs and EVs can also be referred to as plug-in electric vehicles (PEVs).

Environmental Evaluation of New Generation Vehicles and Vehicle Components

Energy Technology Data Exchange (ETDEWEB)

Schexnayder, S.M.

2002-02-06

This report documents assessments that address waste issues and life cycle impacts associated with the vehicle materials and vehicle technologies being developed under the Partnership for a New Generation of Vehicles (PNGV) program. We refer to these vehicles as 3XVs, referring to the PNGV goal that their fuel mileage be three times better than the baseline vehicle. To meet the program's fuel consumption goals, these vehicles substitute lightweight materials for heavier materials such as steel and iron that currently dominate the composition of vehicles, and use engineering and power system changes. Alternative power systems being developed through the PNGV program include batteries for hybrid electric vehicles and fuel cells. With respect to all these developments, it is imperative to learn what effects they will have on the environment before adopting these designs and technologies on a large-scale basis.

Research on application of LADAR in ground vehicle recognition

Science.gov (United States)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Canonical wnt signaling regulates atrioventricular junction programming and electrophysiological properties

NARCIS (Netherlands)

Gillers, Benjamin S.; Chiplunkar, Aditi; Aly, Haytham; Valenta, Tomas; Basler, Konrad; Christoffels, Vincent M.; Efimov, Igor R.; Boukens, Bastiaan J.; Rentschler, Stacey

2015-01-01

Proper patterning of the atrioventricular canal (AVC) is essential for delay of electrical impulses between atria and ventricles, and defects in AVC maturation can result in congenital heart disease. To determine the role of canonical Wnt signaling in the myocardium during AVC development. We used a

SAW Classification Algorithm for Chinese Text Classification

OpenAIRE

Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

2015-01-01

Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles

Directory of Open Access Journals (Sweden)

Duona Zhang

2018-03-01

Full Text Available Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC. It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF method to solve the problem in a unified framework. The contributions include the following: (1 a convolutional neural network (CNN and long short-term memory (LSTM are combined by two different ways without prior knowledge involved; (2 a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs based on a real geographical environment; and (3 experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network.

Description of light-vehicle pre-crash scenarios for safety applications based on vehicle-to-vehicle communications

Science.gov (United States)

2013-05-31

This report describes pre-crash scenarios that might be addressed by vehicle-to-vehicle communications. The focus is on crashes involving at least 1 light vehicle with a gross vehicle weight rating of 10,000 pounds or less. The 2004-2008 General Esti...

Classification in context

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

Electric vehicles

Science.gov (United States)

1990-03-01

Quiet, clean, and efficient, electric vehicles (EVs) may someday become a practical mode of transportation for the general public. Electric vehicles can provide many advantages for the nation's environment and energy supply because they run on electricity, which can be produced from many sources of energy such as coal, natural gas, uranium, and hydropower. These vehicles offer fuel versatility to the transportation sector, which depends almost solely on oil for its energy needs. Electric vehicles are any mode of transportation operated by a motor that receives electricity from a battery or fuel cell. EVs come in all shapes and sizes and may be used for different tasks. Some EVs are small and simple, such as golf carts and electric wheel chairs. Others are larger and more complex, such as automobile and vans. Some EVs, such as fork lifts, are used in industries. In this fact sheet, we will discuss mostly automobiles and vans. There are also variations on electric vehicles, such as hybrid vehicles and solar-powered vehicles. Hybrid vehicles use electricity as their primary source of energy, however, they also use a backup source of energy, such as gasoline, methanol or ethanol. Solar-powered vehicles are electric vehicles that use photovoltaic cells (cells that convert solar energy to electricity) rather than utility-supplied electricity to recharge the batteries. These concepts are discussed.

Classification

DEFF Research Database (Denmark)

Hjørland, Birger

2017-01-01

This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

Empirical analysis of gross vehicle weight and free flow speed and consideration on its relation with differential speed limit.

Science.gov (United States)

Saifizul, Ahmad Abdullah; Yamanaka, Hideo; Karim, Mohamed Rehan

2011-05-01

Most highly motorized countries in the world have implemented different speed limits for light weight and heavy weight vehicles. The heavy vehicle speed limit is usually chosen to be lower than that of passenger cars due to the difficulty for the drivers to safely maneuver the heavy vehicle at high speed and greater impact during a crash. However, in many cases, the speed limit for heavy vehicle is set by only considering the vehicle size or category, mostly due to simplicity in enforcement. In this study, traffic and vehicular data for all vehicle types were collected using a weigh-in-motion system installed at Federal Route 54 in Malaysia. The first finding from the data showed that the weight variation for each vehicle category is considerable. Therefore, the effect of gross vehicle weight (GVW) and category of heavy vehicle on free flow speed and their interaction were analyzed using statistical techniques. Empirical analysis results showed that statistically for each type of heavy vehicle, there was a significant relationship between free flow speed of a heavy vehicle and GVW. Specifically, the results suggest that the mean and variance of free flow speed decrease with an increase GVW by the amount unrelated to size and shape for all GVW range. Then, based on the 85th percentile principle, the study proposed a new concept for setting the speed limit for heavy vehicle by incorporating GVW where a different speed limit is imposed to the heavy vehicle, not only based on vehicle classification, but also according to its GVW. Copyright © 2010 Elsevier Ltd. All rights reserved.

Improving left ventricular outflow tract obstruction repair in common atrioventricular canal defects.

Science.gov (United States)

Myers, Patrick O; del Nido, Pedro J; Marx, Gerald R; Emani, Sitaram; Mayer, John E; Pigula, Frank A; Baird, Christopher W

2012-08-01

Left ventricular outflow tract obstruction (LVOTO) is the second most frequent reason for reoperation after atrioventricular canal (AVC) defect repair. Limited data are available on the mechanisms of LVOTO, their treatment, and outcomes. Between 1998 and 2010, 56 consecutive children with AVC underwent 68 LVOTO procedures. The AVC was partial in 4, transitional in 9, and complete in 43. The LVOTO procedure was required in 21 patients at the primary AVC repair, and the initial LVOTO procedure in 35 patients was a late reoperation after AVC repair. During a mean follow-up of 50±41 months, 5 patients (24%) with LVOTO repair at AVC repair required a reoperation for LVOTO, and 7 patients (20%) whose initial LVOTO repair was a reoperation required a second reoperation for LVOTO repair. Overall freedom from LVOTO reoperation was 98.5% at 1 year, 92.5% at 3 years, 81% at 5 years, 72.2% at 7 years, and 52.5% at 10 and 12 years. The freedom from reoperation was neither significantly different between partial, transitional, and complete AVC (p=0.78) nor between timing of the LVOT procedure (p=0.49). Modified single-patch AVC repair was associated with a higher LVOTO reoperation rate (p=0.04). Neither the mechanisms leading to LVOTO nor the surgical techniques used were independent predictors of reoperation. LVOTO in AVC is a complex and multifactorial disease. Aggressive surgical repair has improved late outcomes; however, risk factors for reoperation and the ideal approach for repair remain to be defined. Copyright © 2012 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Echocardiographic aortic valve calcification and outcomes in women and men with aortic stenosis.

Science.gov (United States)

Thomassen, Henrik K; Cioffi, Giovanni; Gerdts, Eva; Einarsen, Eigir; Midtbø, Helga Bergljot; Mancusi, Costantino; Cramariuc, Dana

2017-10-01

Sex differences in risk factors of aortic valve calcification (AVC) by echocardiography have not been reported from a large prospective study in aortic stenosis (AS). AVC was assessed using a prognostically validated visual score and grouped into none/mild or moderate/severe AVC in 1725 men and women with asymptomatic AS in the Simvastatin Ezetimibe in Aortic Stenosis study. The severity of AS was assessed by the energy loss index (ELI) taking pressure recovery in the aortic root into account. More men than women had moderate/severe AVC at baseline despite less severe AS by ELI (pAVC at baseline was independently associated with lower aortic compliance and more severe AS in both sexes, and with increased high-sensitive C reactive protein (hs-CRP) only in men (all pAVC at baseline was associated with a 2.5-fold (95% CI 1.64 to 3.80) higher hazard rate of major cardiovascular events in women, and a 2.2-fold higher hazard rate in men (95% CI 1.54 to 3.17) (both pAVC at baseline also predicted a 1.8-fold higher hazard rate of all-cause mortality in men (95% CI 1.04 to 3.06, pAVC scored by echocardiography has sex-specific characteristics in AS. Moderate/severe AVC is associated with higher cardiovascular morbidity in both sexes, and with higher all-cause mortality in men. ClinicalTrials.gov identifier: NCT00092677. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Inspection vehicle

International Nuclear Information System (INIS)

Takahashi, Masaki; Omote, Tatsuyuki; Yoneya, Yutaka; Tanaka, Keiji; Waki, Tetsuro; Yoshida, Tomiji; Kido, Tsuyoshi.

1993-01-01

An inspection vehicle comprises a small-sized battery directly connected with a power motor or a direct power source from trolly lines and a switching circuit operated by external signals. The switch judges advance or retreat by two kinds of signals and the inspection vehicle is recovered by self-running. In order to recover the abnormally stopped inspection vehicle to the targeted place, the inspection vehicle is made in a free-running state by using a clutch mechanism and is pushed by an other vehicle. (T.M.)

Track-to-track association for object matching in an inter-vehicle communication system

Science.gov (United States)

Yuan, Ting; Roth, Tobias; Chen, Qi; Breu, Jakob; Bogdanovic, Miro; Weiss, Christian A.

2015-09-01

Autonomous driving poses unique challenges for vehicle environment perception due to the complex driving environment the autonomous vehicle finds itself in and differentiates from remote vehicles. Due to inherent uncertainty of the traffic environments and incomplete knowledge due to sensor limitation, an autonomous driving system using only local onboard sensor information is generally not sufficiently enough for conducting a reliable intelligent driving with guaranteed safety. In order to overcome limitations of the local (host) vehicle sensing system and to increase the likelihood of correct detections and classifications, collaborative information from cooperative remote vehicles could substantially facilitate effectiveness of vehicle decision making process. Dedicated Short Range Communication (DSRC) system provides a powerful inter-vehicle wireless communication channel to enhance host vehicle environment perceiving capability with the aid of transmitted information from remote vehicles. However, there is a major challenge before one can fuse the DSRC-transmitted remote information and host vehicle Radar-observed information (in the present case): the remote DRSC data must be correctly associated with the corresponding onboard Radar data; namely, an object matching problem. Direct raw data association (i.e., measurement-to-measurement association - M2MA) is straightforward but error-prone, due to inherent uncertain nature of the observation data. The uncertainties could lead to serious difficulty in matching decision, especially, using non-stationary data. In this study, we present an object matching algorithm based on track-to-track association (T2TA) and evaluate the proposed approach with prototype vehicles in real traffic scenarios. To fully exploit potential of the DSRC system, only GPS position data from remote vehicle are used in fusion center (at host vehicle), i.e., we try to get what we need from the least amount of information; additional feature

78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

2013-09-09

... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

Traffic Information Unit, Traffic Information System, Vehicle Management System, Vehicle, and Method of Controlling a Vehicle

NARCIS (Netherlands)

Papp, Z.; Doodeman, G.J.N.; Nelisse, M.W.; Sijs, J.; Theeuwes, J.A.C.; Driessen, B.J.F.

2010-01-01

A traffic information unit (MD1, MD2, MD3) according to the invention comprises a facility (MI) for tracking vehicle state information of individual vehicles present at a traffic infrastructure and a facility (T) for transmitting said vehicle state information to a vehicle (70B, 70E). A traffic

CLASSIFICATION OF INFORMAL SETTLEMENTS THROUGH THE INTEGRATION OF 2D AND 3D FEATURES EXTRACTED FROM UAV DATA

Directory of Open Access Journals (Sweden)

C. M. Gevaert

2016-06-01

Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

Vehicle Tracking System, Vehicle Infrastructure Provided with Vehicle Tracking System and Method for Tracking

NARCIS (Netherlands)

Papp, Z.; Doodeman, G.J.N.; Nelisse, M.W.; Sijs, J.; Theeuwes, J.A.C.; Driessen, B.J.F.

2010-01-01

A vehicle tracking system is described comprising - a plurality of sensor nodes (10) that each provide a message (D) indicative for an occupancy status of a detection area of an vehicle infrastructure monitored by said sensor node, said sensor nodes (10) being arranged in the vehicle infrastructure

Financial Accounting: Classifications and Standard Terminology for Local and State School Systems. State Educational Records and Reports Series: Handbook II, Revised.

Science.gov (United States)

Roberts, Charles T., Comp.; Lichtenberger, Allan R., Comp.

This handbook has been prepared as a vehicle or mechanism for program cost accounting and as a guide to standard school accounting terminology for use in all types of local and intermediate education agencies. In addition to classification descriptions, program accounting definitions, and proration of cost procedures, some units of measure and…

Classification of refrigerants; Classification des fluides frigorigenes

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

How important is vehicle safety in the new vehicle purchase process?

Science.gov (United States)

Koppel, Sjaanie; Charlton, Judith; Fildes, Brian; Fitzharris, Michael

2008-05-01

Whilst there has been a significant increase in the amount of consumer interest in the safety performance of privately owned vehicles, the role that it plays in consumers' purchase decisions is poorly understood. The aims of the current study were to determine: how important vehicle safety is in the new vehicle purchase process; what importance consumers place on safety options/features relative to other convenience and comfort features, and how consumers conceptualise vehicle safety. In addition, the study aimed to investigate the key parameters associated with ranking 'vehicle safety' as the most important consideration in the new vehicle purchase. Participants recruited in Sweden and Spain completed a questionnaire about their new vehicle purchase. The findings from the questionnaire indicated that participants ranked safety-related factors (e.g., EuroNCAP (or other) safety ratings) as more important in the new vehicle purchase process than other vehicle factors (e.g., price, reliability etc.). Similarly, participants ranked safety-related features (e.g., advanced braking systems, front passenger airbags etc.) as more important than non-safety-related features (e.g., route navigation systems, air-conditioning etc.). Consistent with previous research, most participants equated vehicle safety with the presence of specific vehicle safety features or technologies rather than vehicle crash safety/test results or crashworthiness. The key parameters associated with ranking 'vehicle safety' as the most important consideration in the new vehicle purchase were: use of EuroNCAP, gender and education level, age, drivers' concern about crash involvement, first vehicle purchase, annual driving distance, person for whom the vehicle was purchased, and traffic infringement history. The findings from this study are important for policy makers, manufacturers and other stakeholders to assist in setting priorities with regard to the promotion and publicity of vehicle safety features

Id4 functions downstream of Bmp signaling to restrict TCF function in endocardial cells during atrioventricular valve development.

Science.gov (United States)

Ahuja, Suchit; Dogra, Deepika; Stainier, Didier Y R; Reischauer, Sven

2016-04-01

The atrioventricular canal (AVC) connects the atrial and ventricular chambers of the heart and its formation is critical for the development of the cardiac valves, chamber septation and formation of the cardiac conduction system. Consequently, problems in AVC formation can lead to congenital defects ranging from cardiac arrhythmia to incomplete cardiac septation. While our knowledge about early heart tube formation is relatively comprehensive, much remains to be investigated about the genes that regulate AVC formation. Here we identify a new role for the basic helix-loop-helix factor Id4 in zebrafish AVC valve development and function. id4 is first expressed in the AVC endocardium and later becomes more highly expressed in the atrial chamber. TALEN induced inactivation of id4 causes retrograde blood flow at the AV canal under heat induced stress conditions, indicating defects in AV valve function. At the molecular level, we found that id4 inactivation causes misexpression of several genes important for AVC and AV valve formation including bmp4 and spp1. We further show that id4 appears to control the number of endocardial cells that contribute to the AV valves by regulating Wnt signaling in the developing AVC endocardium. Copyright © 2016 Elsevier Inc. All rights reserved.

CLASSIFICATION OF TRAFFIC RELATED SHORT TEXTS TO ANALYSE ROAD PROBLEMS IN URBAN AREAS

Directory of Open Access Journals (Sweden)

A. M. M. Saldana-Perez

2017-09-01

Full Text Available The Volunteer Geographic Information (VGI can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media’s publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas

Science.gov (United States)

Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.

2017-09-01

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Observational and Genetic Associations of Resting Heart Rate With Aortic Valve Calcium.

Science.gov (United States)

Whelton, Seamus P; Mauer, Andreas C; Pencina, Karol M; Massaro, Joseph M; D'Agostino, Ralph B; Fox, Caroline S; Hoffmann, Udo; Michos, Erin D; Peloso, Gina M; Dufresne, Line; Engert, James C; Kathiresan, Sekar; Budoff, Matthew; Post, Wendy S; Thanassoulis, George; O'Donnell, Christopher J

2018-05-15

It is unknown if lifelong exposure to increased hemodynamic stress from an elevated resting heart rate (HR) may contribute to aortic valve calcium (AVC). We performed multivariate regression analyses using data from 1,266 Framingham Heart Study (FHS) Offspring cohort participants and 6,764 Multi-Ethnic Study of Atherosclerosis (MESA) participants. We constructed a genetic risk score (GRS) for HR using summary-level data in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) AVC Consortium to investigate if there was evidence in favor of a causal relation. AVC was present in 39% of FHS Offspring cohort participants and in 13% of MESA cohort participants. In multivariate adjusted models, participants in the highest resting HR quartiles had significantly greater prevalence of AVC, with a prevalence ratio of 1.19 (95% confidence interval [CI] 0.99 to 1.44) for the FHS Offspring cohort and 1.32 (95% CI 1.12 to 1.63) for the MESA cohort, compared with those in the lowest quartile. There was a similar increase in the prevalence of AVC per standard deviation increase in resting HR in both FHS Offspring (prevalence ratio 1.08, 95% CI 1.01 to 1.15) and MESA (1.10, 95% CI 1.03 to 1.17). In contrast with these observational findings, a HR associated GRS was not significantly associated with AVC. Although our observational analysis indicates that a higher resting HR is associated with AVC, our genetic results do not support a causal relation. Unmeasured environmental and/or lifestyle factors associated with both increased resting HR and AVC that are not fully explained by covariates in our observational models may account for the association between resting HR and AVC. Copyright © 2018. Published by Elsevier Inc.

Resting heart rate and the incidence and progression of valvular calcium: The Multi-Ethnic Study of Atherosclerosis (MESA).

Science.gov (United States)

Amoakwa, Kojo; Fashanu, Oluwaseun E; Tibuakuu, Martin; Zhao, Di; Guallar, Eliseo; Whelton, Seamus P; O'Neal, Wesley T; Post, Wendy S; Budoff, Matthew J; Michos, Erin D

2018-06-01

Left-sided valvular calcification is associated with cardiovascular disease (CVD) morbidity and mortality. Resting heart rate (RHR) may influence valvular calcium progression through shear stress. Whether RHR, an established CVD risk factor, is associated with valvular calcium progression is unknown. We assessed whether RHR predicts incidence and progression of mitral annular calcium (MAC) and aortic valve calcium (AVC) in a community-based cohort free of CVD at baseline. RHR was obtained from baseline electrocardiograms of 5498 MESA participants. MAC and AVC were quantified using Agatston scoring from cardiac computed tomography scans obtained at baseline and at a second examination during follow-up. We examined associations of RHR with incident MAC/AVC and annual change in MAC/AVC scores, after adjusting for demographics, CVD risk factors, physical activity, and atrioventricular nodal blocker use. At baseline, participants had mean age of 62 ± 10 years and mean RHR of 63 ± 10 bpm; 12.3% and 8.9% had prevalent AVC and MAC, respectively. Over a median of 2.3 years, 4.1% and 4.5% developed incident AVC and MAC, respectively. Each 10 bpm higher RHR was significantly associated with incident MAC [Risk Ratio 1.17 (95% CI 1.03-1.34)], but not incident AVC. However, RHR was associated with AVC progression [β = 1.62 (0.45-2.80) Agatston units/year for every 10 bpm increment], but not MAC progression. Higher RHR was associated with MAC incidence and AVC progression, independent of traditional CVD risk factors. Future studies are needed to determine whether modification of RHR through lifestyle or pharmacologic interventions can reduce valvular calcium incidence or progression. Copyright © 2018 Elsevier B.V. All rights reserved.

Anxiolytic-like effects of alverine citrate in experimental mouse models of anxiety.

Science.gov (United States)

Gupta, Deepali; Radhakrishnan, Mahesh; Kurhe, Yeshwant

2014-11-05

Anxiety disorders are widely spread psychiatric illnesses that are a cause of major concern. Despite a consistent increase in anxiolytics, the prevalence of anxiety is static; this necessitates the development of new compounds with potential activity and minimum unwanted effects. A serotonergic (5HT) system plays an important role in pathogenesis of anxiety and predominantly involves 5HT1A receptor action in mediating anxiety-like behavior; the antagonism of 5HT1A receptor has demonstrated to produce anxiolytic-like effects. Alverine citrate (AVC) is reported as a 5HT1A antagonist; however, its effects on anxiety-like behavior are not investigated. Thus, the present study, by utilizing a neurobehavioral approach, examined the anxiolytic-like effects of AVC in experimental mouse models of anxiety. Mice were acutely treated with AVC (5-20mg/kg, i.p.)/diazepam (DIA, 2mg/kg, i.p.) and subjected to four validated anxiety models viz. elevated plus-maze (EPM), light/dark (L/D), hole-board (HB) and marble burying (MB) tests. AVC (15-20mg/kg) and DIA significantly increased open arm activity in EPM, exploration in light chamber in L/D test, exploratory behavior in HB and reduced MB behavior in marble burying test. AVC (5mg/kg) had no effect on all behavioral tests, while AVC (10mg/kg) produced partial effects. It revealed anxiolytic-like effects of AVC. Furthermore, anxiolytic-like effects of AVC at higher doses (15-20mg/kg) were more pronounced than lower doses (10mg/kg) and were quite similar to the standard drug DIA. The present finding demonstrates, for the first time, the anxiolytic-like effects of AVC, which may be an alternative approach for management of anxiety-related disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

Improving the Procurement of Information Technology Commodities

Science.gov (United States)

1994-04-12

and 0 the federal government. Apply Electronic Data Interchange (EDI) to order processing at AVC. Implementing EDI at AVC and throughout the Air Force...ordering process by approximately 2 weeks. 4. Centralize the Central Order Processing Offices. By consolidating AVC and SSCs order processing responsibilities...Im plem entation ..................................................................................... 21 5. ORDER PROCESSING WITH EDI

Stress analysis on passenger deck due to modification from passenger ship to vehicle-carrying ship

Science.gov (United States)

Zubaydi, A.; Sujiatanti, S. H.; Hariyanto, T. R.

2018-03-01

Stress is a basic concept in learning about material mechanism. The main focus that needs to be brought to attention in analyzing stress is strength, which is the structural capacity to carry or distribute loads. The structural capacity not only measured by comparing the maximum stress with the material’s yield strength but also with the permissible stress required by the Indonesian Classification Bureau (BKI), which certainly makes it much safer. This final project analyzes stress in passenger deck that experiences modification due to load changes, from passenger load to vehicle one, carrying: 6-wheels truck with maximum weight of 14 tons, a passenger car with maximum weight of 3.5 tons, and a motorcycle with maximum weight of 0.4 tons. The deck structure is modelled using finite element software. The boundary conditions given to the structural model are fix and simple constraint. The load that works on this deck is the deck load which comes from the vehicles on deck with three vehicles’ arrangement plans. After that, software modelling is conducted for analysis purpose. Analysis result shows a variation of maximum stress that occurs i.e. 135 N/mm2, 133 N/mm2, and 152 N/mm2. Those maximum stresses will not affect the structure of passenger deck’s because the maximum stress that occurs indicates smaller value compared to the Indonesian Classification Bureau’s permissible stress (175 N/mm2) as well as the material’s yield strength (235 N/mm2). Thus, the structural strength of passenger deck is shown to be capable of carrying the weight of vehicles in accordance with the three vehicles’ arrangement plans.

Comparison of manual and automated measurements of monodominant follicle diameter with different follicle size in infertile patients.

Directory of Open Access Journals (Sweden)

Ping Pan

Full Text Available This study evaluated the consistency of manual and automated measurements of monodominant follicle diameter with different follicle size in infertile patients. Transvaginal two-dimensional (2D ultrasound and SonoAVC (Sonography-based Automated Volume Calculation were both performed in 226 infertile patients with monodominant follicle growth. 2D diameters were separately compared with SonoAVC-generated d(V and m-d values in different follicle category, i.e. >10 to 14 mm, >14 to 18 mm, >18 to 22 mm and >22 mm. There was moderate degree of consistency between 2D diameter and SonoAVC-generated parameters regardless of follicle size. The mean differences were 0.82 mm between 2D diameter and SonoAVC-generated d(V value, and 0.22 mm between 2D diameter and SonoAVC-generated m-d value, respectively. The discrepancy of manual and automated measurements tended to increase as follicle size increased. Our study suggested that compared with manual measurement, SonoAVC might underestimate follicle size. The absolute size of a follicle affected the consistency of two techniques.

Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.

Directory of Open Access Journals (Sweden)

Rodolfo I Meneguette

Full Text Available Intelligent Transportation Systems (ITS rely on Inter-Vehicle Communication (IVC to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT. The main goal of the proposed solution is to reduce the average trip time, CO emissions and fuel consumption by allowing motorists to avoid congested roads. The simulation results show that our proposed solution leads to short delays and a low overhead. Moreover, it is efficient with regard to the coverage of the event and the distance to which the information can be propagated. The findings of the investigation show that the proposed solution leads to (i high hit rate in the classification of the level of congestion, (ii a reduction in average trip time, (iii a reduction in fuel consumption, and (iv reduced CO emissions.

Vision-Based Leader Vehicle Trajectory Tracking for Multiple Agricultural Vehicles.

Science.gov (United States)

Zhang, Linhuan; Ahamed, Tofael; Zhang, Yan; Gao, Pengbo; Takigawa, Tomohiro

2016-04-22

The aim of this study was to design a navigation system composed of a human-controlled leader vehicle and a follower vehicle. The follower vehicle automatically tracks the leader vehicle. With such a system, a human driver can control two vehicles efficiently in agricultural operations. The tracking system was developed for the leader and the follower vehicle, and control of the follower was performed using a camera vision system. A stable and accurate monocular vision-based sensing system was designed, consisting of a camera and rectangular markers. Noise in the data acquisition was reduced by using the least-squares method. A feedback control algorithm was used to allow the follower vehicle to track the trajectory of the leader vehicle. A proportional-integral-derivative (PID) controller was introduced to maintain the required distance between the leader and the follower vehicle. Field experiments were conducted to evaluate the sensing and tracking performances of the leader-follower system while the leader vehicle was driven at an average speed of 0.3 m/s. In the case of linear trajectory tracking, the RMS errors were 6.5 cm, 8.9 cm and 16.4 cm for straight, turning and zigzag paths, respectively. Again, for parallel trajectory tracking, the root mean square (RMS) errors were found to be 7.1 cm, 14.6 cm and 14.0 cm for straight, turning and zigzag paths, respectively. The navigation performances indicated that the autonomous follower vehicle was able to follow the leader vehicle, and the tracking accuracy was found to be satisfactory. Therefore, the developed leader-follower system can be implemented for the harvesting of grains, using a combine as the leader and an unloader as the autonomous follower vehicle.

Image classification independent of orientation and scale

Science.gov (United States)

Arsenault, Henri H.; Parent, Sebastien; Moisan, Sylvain

1998-04-01

The recognition of targets independently of orientation has become fairly well developed in recent years for in-plane rotation. The out-of-plane rotation problem is much less advanced. When both out-of-plane rotations and changes of scale are present, the problem becomes very difficult. In this paper we describe our research on the combined out-of- plane rotation problem and the scale invariance problem. The rotations were limited to rotations about an axis perpendicular to the line of sight. The objects to be classified were three kinds of military vehicles. The inputs used were infrared imagery and photographs. We used a variation of a method proposed by Neiberg and Casasent, where a neural network is trained with a subset of the database and a minimum distances from lines in feature space are used for classification instead of nearest neighbors. Each line in the feature space corresponds to one class of objects, and points on one line correspond to different orientations of the same target. We found that the training samples needed to be closer for some orientations than for others, and that the most difficult orientations are where the target is head-on to the observer. By means of some additional training of the neural network, we were able to achieve 100% correct classification for 360 degree rotation and a range of scales over a factor of five.

Does Driving Range of Electric Vehicles Influence Electric Vehicle Adoption?

Directory of Open Access Journals (Sweden)

Seiho Kim

2017-10-01

Full Text Available This study aims to determine the influential factors on the market share of electric vehicles through panel data analysis based on time series data from 2011 to 2015 in 31 countries. We selected five significant independent variables that are expected to affect electric vehicle adoption based on literature review. The econometric model in this study suggests that the relative price of electric vehicle compared to internal combustion engine vehicle, driving range, and number of models available in markets are correlated to the market share of electric vehicles. On the other hand, relationship between recharging infrastructure—an important factor for electric vehicle adoption in many studies—and market share of electric vehicles turned out to be insignificant in this study. From a political point of view, we argue that policy makers need to allocate more resources to research and development in order to extend driving range at the early stage of electric vehicle deployment in the markets.

Development and psychometric properties of ECPICID-AVC to measure informal caregivers' skills when caring for older stroke survivors at home.

Science.gov (United States)

Araújo, Odete; Lage, Isabel; Cabrita, José; Teixeira, Laetitia

2016-12-01

Informal caregivers provide a significant part of the total care needed by dependent older people poststroke. Although informal care is often the preferred option of those who provide and those who receive informal care, informal caregivers often report lack of preparation to take care of older dependent people. This article outlines the development and psychometric testing of informal caregivers' skills when providing care to older people after a stroke - ECPICID-AVC. Prospective psychometric instrument validation study. Eleven experts participated in a focus group in order to delineate, develop and validate the instrument. Data were gathered among adult informal caregivers (n = 186) living in the community in Northern Portugal from August 2013 to January 2014. The 32-item scale describes several aspects of informal caregiver's skills. The scale has eight factors: skill to feed/hydrate by nasogastric feeding, skill to assist the person in personal hygiene, skill to assist the person for transferring, skill to assist the person for positioning, skill to provide technical aids, skill to assist the person to use the toilet, skill to feed/hydrate and skill to provide technical aids for dressing/undressing. Analysis demonstrated adequate internal consistency (Cronbach's alpha = 0.83) and good temporal stability 0.988 (0.984-0.991). The psychometric properties of the measurement tool showed acceptable results allowing its implementation in clinical practice by the nursing community staff for evaluating practical skills in informal caregivers when providing care to older stroke survivors living at home. © 2016 Nordic College of Caring Science.

Relationship between aortic valve calcification and the severity of coronary atherosclerotic disease.

Science.gov (United States)

Qian, Juying; Chen, Zhangwei; Ge, Junbo; Ma, Jianying; Chang, Shufu; Fan, Bing; Liu, Xuebo; Ge, Lei

2010-07-01

Aortic valve calcification (AVC), which has been confirmed to be associated with various risk factors of cardiac disease, is common in the elderly and associated with increased cardiovascular mortality. It has been hypothesized that AVC is associated with coronary atherosclerotic disease, and its severity. Between July 2007 and November 2007, a total of 235 patients with chest pain or chest distress were admitted to the authors' institution for coronary angiography. The severity of coronary atherosclerotic disease (CAD) was evaluated by the Gensini score, the number of stenosed vessels, and the prevalence of total occlusion. All patients underwent transthoracic echocardiography to detect AVC. Patients with CAD had a higher prevalence of AVC than those without CAD (44% versus 26%, p = 0.005). Likewise, the prevalence of AVC was significantly higher in patients with a higher Gensini score than in those with a lower score. Patients with AVC had a higher prevalence of CAD, and higher Gensini scores and numbers of stenosed coronary arteries, even after stratification by age (65 years). On multivariable logistic regression analysis for CAD, the odds ratio (OR) of AVC was 2.315 (95% confidence interval (CI): 1.158-4.629, p = 0.018); this value was higher than that for total cholesterol (OR = 1.637, p = 0.008), lipoprotein-a (OR = 1.003, p = 0.015) and fibrinogen (OR = 1.009, p = 0.006), and marginally less than that for male gender (OR = 2.665, p = 0.005). Patients with AVC had a higher prevalence and greater severity of CAD.

Prevalence and severity of coronary artery disease in diabetic patients with aortic valve calcification.

Science.gov (United States)

Chen, Zhang-wei; Qian, Ju-ying; Jian, Ying; Ge, Lei; Liu, Xue-bo; Shu, Xian-hong; Ge, Junbo

2011-02-01

Aortic valve calcification (AVC) is common in the elderly and associated with increased cardiovascular mortality, while diabetes is one of the confirmed risk factors for coronary artery disease (CAD). In this study, we aimed to evaluate the prevalence and severity of CAD in type-2 diabetic patients with AVC. From June to December in 2007, a total of 325 consecutive patients with chest pain or chest distress were admitted for coronary angiography. The severity of CAD was evaluated by the Gensini score and the number of stenosed vessels. All patients underwent transthoracic echocardiography for detecting AVC. Compared with the patients without diabetes (n = 221), the type-2 diabetic patients (n = 104) had a similar prevalence of CAD (66.5% vs. 72.1%, P = 0.312). Further classified by the presence of AVC, patients with AVC had a higher prevalence of CAD, average Gensini score and the number of stenosed vessels, both in the group with and without diabetes. It was also demonstrated that the odds ratio (OR) of AVC for CAD in the diabetic patients was higher than in the non-diabetic ones (3.405 vs 2.515) after chi-square analysis (single-variable). However, at multivariable logistic regression analysis for CAD, the OR of AVC was 3.757 (P = 0.03) in diabetic group, while it did not achieve statistical significance in the non-diabetic group (OR = 2.130, P= 0.074). Type-2 diabetic patients with AVC had a higher prevalence of and more severe CAD.

Classification of hydrocephalus: critical analysis of classification categories and advantages of "Multi-categorical Hydrocephalus Classification" (Mc HC).

Science.gov (United States)

Oi, Shizuo

2011-10-01

Hydrocephalus is a complex pathophysiology with disturbed cerebrospinal fluid (CSF) circulation. There are numerous numbers of classification trials published focusing on various criteria, such as associated anomalies/underlying lesions, CSF circulation/intracranial pressure patterns, clinical features, and other categories. However, no definitive classification exists comprehensively to cover the variety of these aspects. The new classification of hydrocephalus, "Multi-categorical Hydrocephalus Classification" (Mc HC), was invented and developed to cover the entire aspects of hydrocephalus with all considerable classification items and categories. Ten categories include "Mc HC" category I: onset (age, phase), II: cause, III: underlying lesion, IV: symptomatology, V: pathophysiology 1-CSF circulation, VI: pathophysiology 2-ICP dynamics, VII: chronology, VII: post-shunt, VIII: post-endoscopic third ventriculostomy, and X: others. From a 100-year search of publication related to the classification of hydrocephalus, 14 representative publications were reviewed and divided into the 10 categories. The Baumkuchen classification graph made from the round o'clock classification demonstrated the historical tendency of deviation to the categories in pathophysiology, either CSF or ICP dynamics. In the preliminary clinical application, it was concluded that "Mc HC" is extremely effective in expressing the individual state with various categories in the past and present condition or among the compatible cases of hydrocephalus along with the possible chronological change in the future.

Cost-Effective Class-Imbalance Aware CNN for Vehicle Localization and Categorization in High Resolution Aerial Images

Directory of Open Access Journals (Sweden)

Feimo Li

2017-05-01

Full Text Available Joint vehicle localization and categorization in high resolution aerial images can provide useful information for applications such as traffic flow structure analysis. To maintain sufficient features to recognize small-scaled vehicles, a regions with convolutional neural network features (R-CNN -like detection structure is employed. In this setting, cascaded localization error can be averted by equally treating the negatives and differently typed positives as a multi-class classification task, but the problem of class-imbalance remains. To address this issue, a cost-effective network extension scheme is proposed. In it, the correlated convolution and connection costs during extension are reduced by feature map selection and bi-partite main-side network construction, which are realized with the assistance of a novel feature map class-importance measurement and a new class-imbalance sensitive main-side loss function. By using an image classification dataset established from a set of traditional real-colored aerial images with 0.13 m ground sampling distance which are taken from the height of 1000 m by an imaging system composed of non-metric cameras, the effectiveness of the proposed network extension is verified by comparing with its similarly shaped strong counter-parts. Experiments show an equivalent or better performance, while requiring the least parameter and memory overheads are required.

Classification

Science.gov (United States)

Clary, Renee; Wandersee, James

2013-01-01

In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

Joint passive radar tracking and target classification using radar cross section

Science.gov (United States)

Herman, Shawn M.

2004-01-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Pedestrian signalization and the risk of pedestrian-motor vehicle collisions in Lima, Peru.

Science.gov (United States)

Quistberg, D Alex; Koepsell, Thomas D; Boyle, Linda Ng; Miranda, J Jaime; Johnston, Brian D; Ebel, Beth E

2014-09-01

Safe walking environments are essential for protecting pedestrians and promoting physical activity. In Peru, pedestrians comprise over three-quarters of road fatality victims. Pedestrian signalization plays an important role managing pedestrian and vehicle traffic and may help improve pedestrian safety. We examined the relationship between pedestrian-motor vehicle collisions and the presence of visible traffic signals, pedestrian signals, and signal timing to determine whether these countermeasures improved pedestrian safety. A matched case-control design was used where the units of study were crossing locations. We randomly sampled 97 control-matched collisions (weighted N=1134) at intersections occurring from October, 2010 to January, 2011 in Lima. Each case-control pair was matched on proximity, street classification, and number of lanes. Sites were visited between February, 2011 and September, 2011. Each analysis accounted for sampling weight and matching and was adjusted for vehicle and pedestrian traffic flow, crossing width, and mean vehicle speed. Collisions were more common where a phased pedestrian signal (green or red-light signal) was present compared to no signalization (odds ratio [OR] 8.88, 95% Confidence Interval [CI] 1.32-59.6). A longer pedestrian-specific signal duration was associated with collision risk (OR 5.31, 95% CI 1.02-9.60 per 15-s interval). Collisions occurred more commonly in the presence of any signalization visible to pedestrians or pedestrian-specific signalization, though these associations were not statistically significant. Signalization efforts were not associated with lower risk for pedestrians; rather, they were associated with an increased risk of pedestrian-vehicle collisions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Aortic root, not valve, calcification correlates with coronary artery calcification in patients with severe aortic stenosis

DEFF Research Database (Denmark)

Henein, Michael; Hällgren, Peter; Holmgren, Anders

2015-01-01

calcification (AVC), due to tissue similarity between the two types of vessel rather than with the valve leaflet tissue. MATERIAL AND METHODS: We studied 212 consecutive patients (age 72.5 ± 7.9 years, 91 females) with AS requiring aortic valve replacement (AVR) in two Heart Centers, who underwent multidetector...... cardiac CT preoperatively. CAC, AVC and ARC were quantified using Agatston scoring. Correlations were tested by Spearman's test and Mann-Whitney U-test was used for comparing different subgroups; bicuspid (BAV) vs tricuspid (TAV) aortic valve. RESULTS: CAC was present in 92%, AVC in 100% and ARC in 82......% of patients. CAC correlated with ARC (rho = 0.51, p AVC. The number of calcified coronary arteries correlated with ARC (rho = 0.45, p AVC. 29/152 patients had echocardiographic evidence of BAV and 123 TAV, who were older (p

Study on the Vehicle Dynamic Load Considering the Vehicle-Pavement Coupled Effect

Science.gov (United States)

Xu, H. L.; He, L.; An, D.

2017-11-01

The vibration of vehicle-pavement interaction system is sophisticated random vibration process and the vehicle-pavement coupled effect was not considered in the previous study. A new linear elastic model of the vehicle-pavement coupled system was established in the paper. The new model was verified with field measurement which could reflect the real vibration between vehicle and pavement. Using the new model, the study on the vehicle dynamic load considering the vehicle-pavement coupled effect showed that random forces (centralization) between vehicle and pavement were influenced largely by vehicle-pavement coupled effect. Numerical calculation indicated that the maximum of random forces in coupled model was 2.4 times than that in uncoupled model. Inquiring the reason, it was found that the main vibration frequency of the vehicle non-suspension system was similar with that of the vehicle suspension system in the coupled model and the resonance vibration lead to vehicle dynamic load increase significantly.

Establishing bonds between vehicle certification data and real-world vehicle fuel consumption – A Vehicle Specific Power approach

International Nuclear Information System (INIS)

Duarte, G.O.; Gonçalves, G.A.; Baptista, P.C.; Farias, T.L.

2015-01-01

Highlights: • Innovative methodology to estimate VSP fuel consumption based on public available data. • Model validation with accurate fuel consumption results (absolute deviation from 4.7% to 9.2%). • Best-selling vehicles in Portugal case study was developed for different driving cycles. - Abstract: A method to perform the energy characterization of a vehicle according to the specific power required while driving was developed using public vehicle certification data. Using a portable emission measurement system, fuel consumption was quantified in a second-by-second basis under on-road conditions for 19 vehicles (spark-ignition, compression-ignition and hybrids). This data allowed building generic curves of fuel consumption as a function of the specific power, according to Vehicle Specific Power methodology. Comparing on-road measurements and the model estimates, a R 2 higher than 0.9 for conventional and hybrid vehicles was obtained regarding modal fuel consumption. Comparing the fuel consumption measured on the drive cycles performed by each vehicle and the correspondent estimates, an absolute deviation of 9.2% ± 9.2% was found for conventional vehicles and 4.7% ± 1.8% for hybrids vehicles. This methodology was validated and applied to estimate the energy impacts of the best-selling vehicles in Portugal for different driving cycles. This prompt method, that does not require vehicle monitoring, can estimate curves of fuel consumption in g/s, as a function of specific power, which allows quantifying the absolute fuel use for any driving cycle

Hand eczema classification

DEFF Research Database (Denmark)

Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

2008-01-01

of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

Vehicle State Estimator based regenerative braking implementation on an electric vehicle to improve lateral vehicle stability

NARCIS (Netherlands)

Jansen, S.T.H.; van Boekel, J.J.P.; Iersel, van S.S.; Besselink, I.J.M.; Nijmeijer, H.

2013-01-01

The driving range of electric vehicles can be extended using regenerative braking. Regenerative braking uses the electric drive system, and therefore only the driven wheels, for decelerating the vehicle. Braking on one axle affects the stability of the vehicle, especially for road conditions with

Vehicle state estimator based regenerative braking implementation on an electric vehicle to improve lateral vehicle stability

NARCIS (Netherlands)

Jansen, S.T.H.; Boekel, J.J.P. van; Iersel, S.S. van; Besselink, I.J.M.; Nijmeijer, H.

2013-01-01

The driving range of electric vehicles can be extended using regenerative braking. Regenerative braking uses the elctric drive system, and therefore only the driven wheels, for decelerating the vehicle. Braking on one axle affects the stability of the vehicle, especially for road conditions with

Classification of the web

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

Security classification of information

Energy Technology Data Exchange (ETDEWEB)

Quist, A.S.

1993-04-01

This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

41 CFR 102-34.85 - What motor vehicles require motor vehicle identification?

Science.gov (United States)

2010-07-01

... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What motor vehicles require motor vehicle identification? 102-34.85 Section 102-34.85 Public Contracts and Property Management... 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Motor Vehicle Identification...

Vehicle to Vehicle Services

DEFF Research Database (Denmark)

Brønsted, Jeppe Rørbæk

2008-01-01

location aware infotainment, increase safety, and lessen environmental strain. This dissertation is about service oriented architecture for pervasive computing with an emphasis on vehicle to vehicle applications. If devices are exposed as services, applications can be created by composing a set of services...... be evaluated. Service composition mechanisms for pervasive computing are categorized and we discuss how the characteristics of pervasive computing can be supported by service composition mechanisms. Finally, we investigate how to make pervasive computing systems capable of being noticed and understood...

Vehicle barrier systems

International Nuclear Information System (INIS)

Sena, P.A.

1986-01-01

The ground vehicle is one of the most effective tools available to an adversary force. Vehicles can be used to penetrate many types of perimeter barriers, transport equipment and personnel rapidly over long distances, and deliver large amounts of explosives directly to facilities in suicide missions. The function of a vehicle barrier system is to detain or disable a defined threat vehicle at a selected distance from a protected facility. Numerous facilities are installing, or planning to install, vehicle barrier systems and many of these facilities are requesting guidance to do so adequately. Therefore, vehicle barriers are being evaluated to determine their stopping capabilities so that systems can be designed that are both balanced and capable of providing a desired degree of protection. Equally important, many of the considerations that should be taken into account when establishing a vehicle barrier system have been identified. These considerations which pertain to site preparation, barrier selection, system integration and operation, and vehicle/barrier interaction, are discussed in this paper

Connected vehicle applications : safety.

Science.gov (United States)

2016-01-01

Connected vehicle safety applications are designed to increase situational awareness : and reduce or eliminate crashes through vehicle-to-infrastructure, vehicle-to-vehicle, : and vehicle-to-pedestrian data transmissions. Applications support advisor...

Influence of the Quantity of Aortic Valve Calcium on the Agreement Between Automated 3-Dimensional Transesophageal Echocardiography and Multidetector Row Computed Tomography for Aortic Annulus Sizing.

Science.gov (United States)

Podlesnikar, Tomaz; Prihadi, Edgard A; van Rosendael, Philippe J; Vollema, E Mara; van der Kley, Frank; de Weger, Arend; Ajmone Marsan, Nina; Naji, Franjo; Fras, Zlatko; Bax, Jeroen J; Delgado, Victoria

2018-01-01

Accurate aortic annulus sizing is key for selection of appropriate transcatheter aortic valve implantation (TAVI) prosthesis size. The present study compared novel automated 3-dimensional (3D) transesophageal echocardiography (TEE) software and multidetector row computed tomography (MDCT) for aortic annulus sizing and investigated the influence of the quantity of aortic valve calcium (AVC) on the selection of TAVI prosthesis size. A total of 83 patients with severe aortic stenosis undergoing TAVI were evaluated. Maximal and minimal aortic annulus diameter, perimeter, and area were measured. AVC was assessed with computed tomography. The low and high AVC burden groups were defined according to the median AVC score. Overall, 3D TEE measurements slightly underestimated the aortic annulus dimensions as compared with MDCT (mean differences between maximum, minimum diameter, perimeter, and area: -1.7 mm, 0.5 mm, -2.7 mm, and -13 mm 2 , respectively). The agreement between 3D TEE and MDCT on aortic annulus dimensions was superior among patients with low AVC burden (AVC burden (≥3,025 arbitrary units). The interobserver variability was excellent for both methods. 3D TEE and MDCT led to the same prosthesis size selection in 88%, 95%, and 81% of patients in the total population, the low, and the high AVC burden group, respectively. In conclusion, the novel automated 3D TEE imaging software allows accurate and highly reproducible measurements of the aortic annulus dimensions and shows excellent agreement with MDCT to determine the TAVI prosthesis size, particularly in patients with low AVC burden. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Cardiac valve calcifications on low-dose unenhanced ungated chest computed tomography: inter-observer and inter-examination reliability, agreement and variability

International Nuclear Information System (INIS)

Hamersvelt, Robbert W. van; Willemink, Martin J.; Takx, Richard A.P.; Eikendal, Anouk L.M.; Budde, Ricardo P.J.; Leiner, Tim; Jong, Pim A. de; Mol, Christian P.; Isgum, Ivana

2014-01-01

To determine inter-observer and inter-examination variability for aortic valve calcification (AVC) and mitral valve and annulus calcification (MC) in low-dose unenhanced ungated lung cancer screening chest computed tomography (CT). We included 578 lung cancer screening trial participants who were examined by CT twice within 3 months to follow indeterminate pulmonary nodules. On these CTs, AVC and MC were measured in cubic millimetres. One hundred CTs were examined by five observers to determine the inter-observer variability. Reliability was assessed by kappa statistics (κ) and intra-class correlation coefficients (ICCs). Variability was expressed as the mean difference ± standard deviation (SD). Inter-examination reliability was excellent for AVC (κ = 0.94, ICC = 0.96) and MC (κ = 0.95, ICC = 0.90). Inter-examination variability was 12.7 ± 118.2 mm 3 for AVC and 31.5 ± 219.2 mm 3 for MC. Inter-observer reliability ranged from κ = 0.68 to κ = 0.92 for AVC and from κ = 0.20 to κ = 0.66 for MC. Inter-observer ICC was 0.94 for AVC and ranged from 0.56 to 0.97 for MC. Inter-observer variability ranged from -30.5 ± 252.0 mm 3 to 84.0 ± 240.5 mm 3 for AVC and from -95.2 ± 210.0 mm 3 to 303.7 ± 501.6 mm 3 for MC. AVC can be quantified with excellent reliability on ungated unenhanced low-dose chest CT, but manual detection of MC can be subject to substantial inter-observer variability. Lung cancer screening CT may be used for detection and quantification of cardiac valve calcifications. (orig.)

Hazard classification methodology

International Nuclear Information System (INIS)

Brereton, S.J.

1996-01-01

This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

Vehicle following controller design for autonomous intelligent vehicles

Science.gov (United States)

Chien, C. C.; Lai, M. C.; Mayr, R.

1994-01-01

A new vehicle following controller is proposed for autonomous intelligent vehicles. The proposed vehicle following controller not only provides smooth transient maneuvers for unavoidable nonzero initial conditions but also guarantees the asymptotic platoon stability without the availability of feedforward information. Furthermore, the achieved asymptotic platoon stability is shown to be robust to sensor delays and an upper bound for the allowable sensor delays is also provided in this paper.

Light vehicle crash avoidance needs and countermeasure profiles for safety applications based on vehicle-to-vehicle communications

Science.gov (United States)

2013-04-30

This report discusses light-vehicle crash countermeasure profiles and functions for five target pre-crash scenario groups based on vehicle-to-vehicle (V2V) communications. Target pre-crash scenario groups include rear-end, lane change, opposite direc...

Calcific aortic valve damage as a risk factor for cardiovascular events

International Nuclear Information System (INIS)

Wasilewski, Jarosław; Mirota, Kryspin; Wilczek, Krzysztof; Głowacki, Jan; Poloński, Lech

2012-01-01

Aortic valve calcification (AVC) is a common disease of the elderly. It is a progressive disease ranging from mild valve thickening to severe calcification with aortic valve stenosis. Risk factors for AVC are similar to those for atherosclerosis: age, gender, hypercholesterolemia, diabetes, hypertension, smoking and renal failure. AVC shares many similarities to atherosclerosis, including inflammatory cells and calcium deposits, and correlates with coronary plaque burden. Presence of AVC is associated with increased risk of adverse cardiovascular events. The objective for this review is to discuss the clinical features, natural history and prognostic significance of aortic valve calcifications, including mechanical and hemodynamic factors of flow distribution

State-of-the-art assessment of electric vehicles and hybrid vehicles

Science.gov (United States)

1977-01-01

The Electric and Hybrid Vehicle Research, Development, and Demonstration Act of 1976 (PL 94-413) requires that data be developed to characterize the state of the art of vehicles powered by an electric motor and those propelled by a combination of an electric motor and an internal combustion engine or other power sources. Data obtained from controlled tests of a representative number of sample vehicles, from information supplied by manufacturers or contained in the literature, and from surveys of fleet operators of individual owners of electric vehicles is discussed. The results of track and dynamometer tests conducted by NASA on 22 electric, 2 hybrid, and 5 conventional vehicles, as well as on 5 spark-ignition-engine-powered vehicles, the conventional counterparts of 5 of the vehicles, are presented.

Desempenho ocupacional de pessoas hemiplégicas pós-avc a partir do uso de tecnologias assistivas/Post-CVA hemiplegic patients occupational performance fromthe use of assistive technologies

Directory of Open Access Journals (Sweden)

Andressa Ribas Mildner

2017-09-01

Full Text Available O objetivo do estudo foi identificar as atividades cotidianas comprometidas pela hemiplegia de pessoas acometidas por AVC e verificar a influência do uso de tecnologias assistivas no desempenho ocupacional das mesmas. Para tanto, trata-se de um estudo quantitativo, descritivo, com delineamento transversal. Houve a participação de quatro pessoas acometidas por AVC com sequela de hemiplegia, sendo utilizados como instrumentos uma entrevista semiestruturada e a Medida Canadense de Desempenho Ocupacional. Os participantes foram avaliados e por doze semanas receberam intervenções terapêuticas ocupacionais – prescrições, confecção e treinamentos dos dispositivos de tecnologias assistivas, sendo reavaliados posteriormente. Como resultados, pode-se observar que todos os participantes apresentavam restrições em atividades envolvendo as áreas do autocuidado, a produtividade e o lazer, principalmente nos cuidados pessoais, tarefas domésticas e na recreação tranquila. Após identificar as principais atividades-problemas, e com as intervenções terapêuticas ocupacionais e inclusão dos dispositivos de tecnologias assitivas nas atividades cotidianas, observou-se melhora no desempenho ocupacional, tanto na percepção do desempenho como da satisfação, tendo um aumento de 2,1 pontos em ambas. Assim, conclui-se que o uso da COPM possibilita identificar atividades-problema para se pensar em estratégias de intervenção como criação de dispositivos de TA. Assim, o uso de TA pode influenciar na melhora do desempenho ocupacional de pessoas com limitações e restrições na realização de atividade cotidianas, sendo coadjuvante da função para minimizar os comprometimentos e facilitar a realização das atividades importantes. AbstractThe objective ofth estudy was to identify daily activities which were compromised by hemiplegia in people who had suffered a stroke, as well as to verify thein fluence of the use of assistive technologie son

Can vehicle longitudinal jerk be used to identify aggressive drivers? An examination using naturalistic driving data.

Science.gov (United States)

Feng, Fred; Bao, Shan; Sayer, James R; Flannagan, Carol; Manser, Michael; Wunderlich, Robert

2017-07-01

This paper investigated the characteristics of vehicle longitudinal jerk (change rate of acceleration with respect to time) by using vehicle sensor data from an existing naturalistic driving study. The main objective was to examine whether vehicle jerk contains useful information that could be potentially used to identify aggressive drivers. Initial investigation showed that there are unique characteristics of vehicle jerk in drivers' gas and brake pedal operations. Thus two jerk-based metrics were examined: (1) driver's frequency of using large positive jerk when pressing the gas pedal, and (2) driver's frequency of using large negative jerk when pressing the brake pedal. To validate the performance of the two metrics, drivers were firstly divided into an aggressive group and a normal group using three classification methods (1) traveling at excessive speed (speeding), (2) following too closely to a front vehicle (tailgating), and (3) their association with crashes or near-crashes in the dataset. The results show that those aggressive drivers defined using any of the three methods above were associated with significantly higher values of the two jerk-based metrics. Between the two metrics the frequency of using large negative jerk seems to have better performance in identifying aggressive drivers. A sensitivity analysis shows the findings were largely consistent with varying parameters in the analysis. The potential applications of this work include developing quantitative surrogate safety measures to identify aggressive drivers and aggressive driving, which could be potentially used to, for example, provide real-time or post-ride performance feedback to the drivers, or warn the surrounding drivers or vehicles using the connected vehicle technologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Connected vehicle application : safety.

Science.gov (United States)

2015-01-01

Connected vehicle safety applications are designed to increase situational awareness : and reduce or eliminate crashes through vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and vehicle-to-pedestrian (V2P) data transmissions. Applications...

Telemedicine in general neurology: use of audiovisual consultation for on call back-up service in an acute care hospital.

Science.gov (United States)

Janssen, Frank; Awadallah, Mohammed; Alhalabi, Awed; Körber, Barbara; Lang, Reinhard; Scibor, Mateusz; Handschu, René

2018-04-01

While telemedicine is in expanding use in acute stroke care, little is known about its use in general neurology, especially in acute care. We sought to investigate the feasibility and possible effects of a telemedicine device within the neurological back-up service of an acute care hospital. In a 450 bed academic teaching hospital an experienced neurologist (EN) is on call to support the junior doctor at the hospital. Support was possible whether by standard telephone advice (TA) or by audiovisual consultations (AVC). In AVC the expert used a mobile telemedicine device and so he could establish audiovisual contact from his home to the emergency room and examine newly admitted patients. Technical and patient details including timing and diagnosis were recorded. Video and audio quality as well as impact of AVC on diagnosis was rated by the EN. Out of about 1200 cases in off peak times, during the study period, 164 AVC including remote video examination were done (13.6%). Also 48 cases were documented by pure TA. Video quality was rated to a medium of 1.7, audio quality to 2.1. In 36 cases the audiovisual consultation was influenced by technical issues leading to cessation of AVC in 8 cases. Duration of teleconsultation was 17.3 min in AVC compared to 8.7 min for TA. The consultation diagnosis in AVC was confirmed in 74.4% of all cases compared to 57.7% in TA. AVC was rated as a valuable contribution to the diagnostic workup in 74.3% of all cases seen. In about 40% of all cases AVC was not possible due to technical or organizational reasons. Audiovisual consultation seems to be a feasible and useful support in routine neurology back-up service of an acute care hospital. Better mobility of devices and flexibility of service is needed to improve availability and quality of this valuable tool.

Vehicle to grid: electric vehicles as an energy storage solution

Science.gov (United States)

McGee, Rodney; Waite, Nicholas; Wells, Nicole; Kiamilev, Fouad E.; Kempton, Willett M.

2013-05-01

With increased focus on intermittent renewable energy sources such as wind turbines and photovoltaics, there comes a rising need for large-scale energy storage. The vehicle to grid (V2G) project seeks to meet this need using electric vehicles, whose high power capacity and existing power electronics make them a promising energy storage solution. This paper will describe a charging system designed by the V2G team that facilitates selective charging and backfeeding by electric vehicles. The system consists of a custom circuit board attached to an embedded linux computer that is installed both in the EVSE (electric vehicle supply equipment) and in the power electronics unit of the vehicle. The boards establish an in-band communication link between the EVSE and the vehicle, giving the vehicle internet connectivity and the ability to make intelligent decisions about when to charge and discharge. This is done while maintaining compliance with existing charging protocols (SAEJ1772, IEC62196) and compatibility with standard "nonintelligent" cars and chargers. Through this system, the vehicles in a test fleet have been able to successfully serve as portable temporary grid storage, which has implications for regulating the electrical grid, providing emergency power, or supplying power to forward military bases.

RFID-based vehicle positioning and its applications in connected vehicles.

Science.gov (United States)

Wang, Jianqiang; Ni, Daiheng; Li, Keqiang

2014-03-04

This paper proposed an RFID-based vehicle positioning approach to facilitate connected vehicles applications. When a vehicle passes over an RFID tag, the vehicle position is given by the accurate position stored in the tag. At locations without RFID coverage, the vehicle position is estimated from the most recent tag location using a kinematics integration algorithm till updates from the next tag. The accuracy of RFID positioning is verified empirically in two independent ways with one using radar and the other a photoelectric switch. The former is designed to verify whether the dynamic position obtained from RFID tags matches the position measured by radar that is regarded as accurate. The latter aims to verify whether the position estimated from the kinematics integration matches the position obtained from RFID tags. Both means supports the accuracy of RFID-based positioning. As a supplement to GPS which suffers from issues such as inaccuracy and loss of signal, RFID positioning is promising in facilitating connected vehicles applications. Two conceptual applications are provided here with one in vehicle operational control and the other in Level IV intersection control.

AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.

Science.gov (United States)

Sun, Lei; Wang, Jun; Wei, Jinmao

2017-03-14

The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance in biomedical field. Owing to its superiority in dealing with imbalanced and cost-sensitive data, the ROC curve has been exploited as a popular metric to evaluate and find out disease-related genes (features). The existing ROC-based feature selection approaches are simple and effective in evaluating individual features. However, these approaches may fail to find real target feature subset due to their lack of effective means to reduce the redundancy between features, which is essential in machine learning. In this paper, we propose to assess feature complementarity by a trick of measuring the distances between the misclassified instances and their nearest misses on the dimensions of pairwise features. If a misclassified instance and its nearest miss on one feature dimension are far apart on another feature dimension, the two features are regarded as complementary to each other. Subsequently, we propose a novel filter feature selection approach on the basis of the ROC analysis. The new approach employs an efficient heuristic search strategy to select optimal features with highest complementarities. The experimental results on a broad range of microarray data sets validate that the classifiers built on the feature subset selected by our approach can get the minimal balanced error rate with a small amount of significant features. Compared with other ROC-based feature selection approaches, our new approach can select fewer features and effectively improve the classification performance.

Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones

Directory of Open Access Journals (Sweden)

Dang-Nhac Lu

2018-03-01

Full Text Available In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS, that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers’ vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97

Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones.

Science.gov (United States)

Lu, Dang-Nhac; Nguyen, Duc-Nhan; Nguyen, Thi-Hau; Nguyen, Ha-Nam

2018-03-29

In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers' vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features) as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine) contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97.33% that is

A method of vehicle license plate recognition based on PCANet and compressive sensing

Science.gov (United States)

Ye, Xianyi; Min, Feng

2018-03-01

The manual feature extraction of the traditional method for vehicle license plates has no good robustness to change in diversity. And the high feature dimension that is extracted with Principal Component Analysis Network (PCANet) leads to low classification efficiency. For solving these problems, a method of vehicle license plate recognition based on PCANet and compressive sensing is proposed. First, PCANet is used to extract the feature from the images of characters. And then, the sparse measurement matrix which is a very sparse matrix and consistent with Restricted Isometry Property (RIP) condition of the compressed sensing is used to reduce the dimensions of extracted features. Finally, the Support Vector Machine (SVM) is used to train and recognize the features whose dimension has been reduced. Experimental results demonstrate that the proposed method has better performance than Convolutional Neural Network (CNN) in the recognition and time. Compared with no compression sensing, the proposed method has lower feature dimension for the increase of efficiency.

Classification, disease, and diagnosis.

Science.gov (United States)

Jutel, Annemarie

2011-01-01

Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

Modelling the Effect of Driving Events on Electrical Vehicle Energy Consumption Using Inertial Sensors in Smartphones

Directory of Open Access Journals (Sweden)

David Jiménez

2018-02-01

Full Text Available Air pollution and climate change are some of the main problems that humankind is currently facing. The electrification of the transport sector will help to reduce these problems, but one of the major barriers for the massive adoption of electric vehicles is their limited range. The energy consumption in these vehicles is affected, among other variables, by the driving behavior, making range a value that must be personalized to each driver and each type of electric vehicle. In this paper we offer a way to estimate a personalized energy consumption model by the use of the vehicle dynamics and the driving events detected by the use of the smartphone inertial sensors, allowing an easy and non-intrusive manner to predict the correct range for each user. This paper proposes, for the classification of events, a deep neural network (Long-Short Time Memory which has been trained with more than 22,000 car trips, and the application to improve the consumption model taking into account the driver behavior captured across different trips, allowing a personalized prediction. Results and validation in real cases show that errors in the predicted consumption values are halved when abrupt events are considered in the model.

Broadband vehicle-to-vehicle communication using an extended autonomous cruise control sensor

Science.gov (United States)

Heddebaut, M.; Rioult, J.; Ghys, J. P.; Gransart, Ch; Ambellouis, S.

2005-06-01

For several years road vehicle autonomous cruise control (ACC) systems as well as anti-collision radar have been developed. Several manufacturers currently sell this equipment. The current generation of ACC sensors only track the first preceding vehicle to deduce its speed and position. These data are then used to compute, manage and optimize a safety distance between vehicles, thus providing some assistance to car drivers. However, in real conditions, to elaborate and update a real time driving solution, car drivers use information about speed and position of preceding and following vehicles. This information is essentially perceived using the driver's eyes, binocular stereoscopic vision performed through the windscreens and rear-view mirrors. Furthermore, within a line of vehicles, the frontal road perception of the first vehicle is very particular and highly significant. Currently, all these available data remain strictly on-board the vehicle that has captured the perception information and performed these measurements. To get the maximum effectiveness of all these approaches, we propose that this information be shared in real time with the following vehicles, within the convoy. On the basis of these considerations, this paper technically explores a cost-effective solution to extend the basic ACC sensor function in order to simultaneously provide a vehicle-to-vehicle radio link. This millimetre wave radio link transmits relevant broadband perception data (video, localization...) to following vehicles, along the line of vehicles. The propagation path between the vehicles uses essentially grazing angles of incidence of signals over the road surface including millimetre wave paths beneath the cars.

Design optimisation of a flywheel hybrid vehicle

Energy Technology Data Exchange (ETDEWEB)

Kok, D.B.

1999-11-04

during the engine start-up and shutdown periods. Correct throttle valve control ensures that hydrocarbon emissions are not critical for legislative emission limits, but the engine's standard lambda control cannot prevent an increase of nitric oxides. In order to improve tailpipe emissions, the thermo-chemical behaviour of the catalytic converter is investigated and adapted for hybrid vehicle application. In cold-start situations, the fuel consumption and exhaust gas emissions of a mechanical driveline with internal combustion engine increase. A detailed numerical investigation of the thermal behaviour of the hybrid driveline showed that the energy-efficient operation of the engine decreases thermal waste energy that is available to warm up driveline components. Therefore, a redesign of the cooling circuitry and thermal management of the driveline was required to improve system warm-up. A computer model has been developed that combines the functional description of the flywheel hybrid vehicle with the calculation of energy losses. Apart from standardised European drive cycles, velocity profiles that represent more realistic vehicle utilisation are used to assess and optimise the hybrid vehicle's fuel economy, exhaust gas emission and acceleration performance. Subdivision of energy consumption enabled the classification of those systems and components that have a major effect on fuel consumption. Of these, the optimised flywheel system, the hydraulic system, and the transmission consume energy of comparable magnitude in city driving. It is shown that the system's fuel economy is mainly a result of the improved engine operation. Regenerative braking has only limited effect on vehicle fuel consumption. Experiments with an early prototype of the hybrid driveline yielded no gains in fuel consumption when compared to a conventional CVT reference vehicle due to high storage losses in the flywheel system. However, the improved prototype of the flywheel hybrid

Vehicle underbody fairing

Science.gov (United States)

Ortega, Jason M.; Salari, Kambiz; McCallen, Rose

2010-11-09

A vehicle underbody fairing apparatus for reducing aerodynamic drag caused by a vehicle wheel assembly, by reducing the size of a recirculation zone formed under the vehicle body immediately downstream of the vehicle wheel assembly. The fairing body has a tapered aerodynamic surface that extends from a front end to a rear end of the fairing body with a substantially U-shaped cross-section that tapers in both height and width. Fasteners or other mounting devices secure the fairing body to an underside surface of the vehicle body, so that the front end is immediately downstream of the vehicle wheel assembly and a bottom section of the tapered aerodynamic surface rises towards the underside surface as it extends in a downstream direction.

"Can Vehicle-to-Grid Revenue Help Electric Vehicles on the Market?"

OpenAIRE

George R. Parsons; Michael K. Hidrue; Willett Kempton; Meryl P. Gardner

2011-01-01

Vehicle-to-grid (V2G) electric vehicles can return power stored in their batteries back to the power grid and be programmed to do so at times when power prices are high. Since providing this service can lead to payments to owners of vehicles, it effectively reduces the cost of electric vehicles. Using data from a national stated preference survey (n = 3029), this paper presents the first study of the potential consumer demand for V2G electric vehicles. In our choice experiment, 3029 responden...

Vehicle technologies, fuel-economy policies, and fuel-consumption rates of Chinese vehicles

International Nuclear Information System (INIS)

Huo Hong; He Kebin; Wang, Michael; Yao Zhiliang

2012-01-01

One of the principal ways to reduce transport-related energy use is to reduce fuel-consumption rates of motor vehicles (usually measured in liters of fuel per 100 km). Since 2004, China has implemented policies to improve vehicle technologies and lower the fuel-consumption rates of individual vehicles. Policy evaluation requires accurate and adequate information on vehicle fuel-consumption rates. However, such information, especially for Chinese vehicles under real-world operating conditions, is rarely available from official sources in China. For each vehicle type we first review the vehicle technologies and fuel-economy policies currently in place in China and their impacts. We then derive real-world (or on-road) fuel-consumption rates on the basis of information collected from various sources. We estimate that the real-world fuel-consumption rates of vehicles in China sold in 2009 are 9 L/100 km for light-duty passenger vehicles, 11.4 L/100 km for light-duty trucks, 22 L/100 km for inter-city transport buses, 40 L/100 km for urban transit buses, and 24.9 L/100 km for heavy-duty trucks. These results aid in understanding the levels of fuel consumption of existing Chinese vehicle fleets and the effectiveness of policies in reducing on-road fuel consumption, which can help in designing and evaluating future vehicle energy-efficiency policies. - Highlights: ► Vehicle fuel-consumption rate (VFCR) data are rarely available in China. ► We review the fuel-economy policies currently in place in China and their impacts. ► We derive real-world VFCRs on the basis of information collected from various sources. ► Results aid in understanding the fuel consumption levels of Chinese vehicle fleets. ► Results help in designing and evaluating future vehicle energy-efficiency policies.

Standard classification: Physics

International Nuclear Information System (INIS)

1977-01-01

This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

No-Reference Video Quality Assessment using Codec Analysis

DEFF Research Database (Denmark)

Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

2015-01-01

types of videos, estimating the level of quantization used in the I-frames, and exploiting this information to assess the video quality. In order to do this for H.264/AVC, the distribution of the DCT-coefficients after intra-prediction and deblocking are modeled. To obtain VQA features for H.264/AVC, we......A no-reference video quality assessment (VQA) method is presented for videos distorted by H.264/AVC and MPEG-2. The assessment is performed without access to the bit-stream. Instead we analyze and estimate coefficients based on decoded pixels. The approach involves distinguishing between the two...... propose a novel estimation method of the quantization in H.264/AVC videos without bitstream access, which can also be used for Peak Signalto-Noise Ratio (PSNR) estimation. The results from the MPEG-2 and H.264/AVC analysis are mapped to a perceptual measure of video quality by Support Vector Regression...

Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology.

Science.gov (United States)

Cruzan, Mitchell B; Weinstein, Ben G; Grasty, Monica R; Kohrn, Brendan F; Hendrickson, Elizabeth C; Arredondo, Tina M; Thompson, Pamela G

2016-09-01

Low-elevation surveys with small aerial drones (micro-unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology.

Object Classification Based on Analysis of Spectral Characteristics of Seismic Signal Envelopes

Science.gov (United States)

Morozov, Yu. V.; Spektor, A. A.

2017-11-01

A method for classifying moving objects having a seismic effect on the ground surface is proposed which is based on statistical analysis of the envelopes of received signals. The values of the components of the amplitude spectrum of the envelopes obtained applying Hilbert and Fourier transforms are used as classification criteria. Examples illustrating the statistical properties of spectra and the operation of the seismic classifier are given for an ensemble of objects of four classes (person, group of people, large animal, vehicle). It is shown that the computational procedures for processing seismic signals are quite simple and can therefore be used in real-time systems with modest requirements for computational resources.

Cardiac valve calcifications on low-dose unenhanced ungated chest computed tomography: inter-observer and inter-examination reliability, agreement and variability

Energy Technology Data Exchange (ETDEWEB)

Hamersvelt, Robbert W. van; Willemink, Martin J.; Takx, Richard A.P.; Eikendal, Anouk L.M.; Budde, Ricardo P.J.; Leiner, Tim; Jong, Pim A. de [University Medical Center Utrecht, Department of Radiology, Utrecht (Netherlands); Mol, Christian P.; Isgum, Ivana [University Medical Center Utrecht, Image Sciences Institute, Utrecht (Netherlands)

2014-07-15

To determine inter-observer and inter-examination variability for aortic valve calcification (AVC) and mitral valve and annulus calcification (MC) in low-dose unenhanced ungated lung cancer screening chest computed tomography (CT). We included 578 lung cancer screening trial participants who were examined by CT twice within 3 months to follow indeterminate pulmonary nodules. On these CTs, AVC and MC were measured in cubic millimetres. One hundred CTs were examined by five observers to determine the inter-observer variability. Reliability was assessed by kappa statistics (κ) and intra-class correlation coefficients (ICCs). Variability was expressed as the mean difference ± standard deviation (SD). Inter-examination reliability was excellent for AVC (κ = 0.94, ICC = 0.96) and MC (κ = 0.95, ICC = 0.90). Inter-examination variability was 12.7 ± 118.2 mm{sup 3} for AVC and 31.5 ± 219.2 mm{sup 3} for MC. Inter-observer reliability ranged from κ = 0.68 to κ = 0.92 for AVC and from κ = 0.20 to κ = 0.66 for MC. Inter-observer ICC was 0.94 for AVC and ranged from 0.56 to 0.97 for MC. Inter-observer variability ranged from -30.5 ± 252.0 mm{sup 3} to 84.0 ± 240.5 mm{sup 3} for AVC and from -95.2 ± 210.0 mm{sup 3} to 303.7 ± 501.6 mm{sup 3} for MC. AVC can be quantified with excellent reliability on ungated unenhanced low-dose chest CT, but manual detection of MC can be subject to substantial inter-observer variability. Lung cancer screening CT may be used for detection and quantification of cardiac valve calcifications. (orig.)

DksA-HapR-RpoS axis regulates haemagglutinin protease production in Vibrio cholerae.

Science.gov (United States)

Basu, Pallabi; Pal, Ritesh Ranjan; Dasgupta, Shreya; Bhadra, Rupak K

2017-06-01

DksA acts as a co-factor for the intracellular small signalling molecule ppGpp during the stringent response. We recently reported that the expression of the haemagglutinin protease (HAP), which is needed for shedding of the cholera pathogen Vibrio cholerae during the late phase of infection, is significantly downregulated in V. cholerae ∆dksA mutant (∆dksAVc) cells. So far, it has been shown that HAP production by V. cholerae cells is critically regulated by HapR and also by RpoS. Here, we provide evidence that V. cholerae DksA (DksAVc) positively regulates HapR at both the transcriptional and post-transcriptional levels. We show that in ∆dksAVc cells the CsrB/C/D sRNAs, required for the maintenance of intracellular levels of hapR transcripts during the stationary growth, are distinctly downregulated. Moreover, the expression of exponential phase regulatory protein Fis, a known negative regulator of HapR, was found to continue even during the stationary phase in ∆dksAVc cells compared to that of wild-type strain, suggesting another layer of complex regulation of HapR by DksAVc. Extensive reporter construct-based and quantitative reverse-transcriptase PCR (qRT-PCR) analyses supported that RpoS is distinctly downregulated at the post-transcriptional/translational levels in stationary phase-grown ∆dksAVc cells. Since HAP expression through HapR and RpoS is stationary phase-specific in V. cholerae, it appears that DksAVc is also a critical stationary phase regulator for fine tuning of the expression of HAP. Moreover, experimental evidence provided in this study clearly supports that DksAVc is sitting at the top of the hierarchy of regulation of expression of HAP in V. cholerae.

RFID-Based Vehicle Positioning and Its Applications in Connected Vehicles

Science.gov (United States)

Wang, Jianqiang; Ni, Daiheng; Li, Keqiang

2014-01-01

This paper proposed an RFID-based vehicle positioning approach to facilitate connected vehicles applications. When a vehicle passes over an RFID tag, the vehicle position is given by the accurate position stored in the tag. At locations without RFID coverage, the vehicle position is estimated from the most recent tag location using a kinematics integration algorithm till updates from the next tag. The accuracy of RFID positioning is verified empirically in two independent ways with one using radar and the other a photoelectric switch. The former is designed to verify whether the dynamic position obtained from RFID tags matches the position measured by radar that is regarded as accurate. The latter aims to verify whether the position estimated from the kinematics integration matches the position obtained from RFID tags. Both means supports the accuracy of RFID-based positioning. As a supplement to GPS which suffers from issues such as inaccuracy and loss of signal, RFID positioning is promising in facilitating connected vehicles applications. Two conceptual applications are provided here with one in vehicle operational control and the other in Level IV intersection control. PMID:24599188

RFID-Based Vehicle Positioning and Its Applications in Connected Vehicles

Directory of Open Access Journals (Sweden)

Jianqiang Wang

2014-03-01

Full Text Available This paper proposed an RFID-based vehicle positioning approach to facilitate connected vehicles applications. When a vehicle passes over an RFID tag, the vehicle position is given by the accurate position stored in the tag. At locations without RFID coverage, the vehicle position is estimated from the most recent tag location using a kinematics integration algorithm till updates from the next tag. The accuracy of RFID positioning is verified empirically in two independent ways with one using radar and the other a photoelectric switch. The former is designed to verify whether the dynamic position obtained from RFID tags matches the position measured by radar that is regarded as accurate. The latter aims to verify whether the position estimated from the kinematics integration matches the position obtained from RFID tags. Both means supports the accuracy of RFID-based positioning. As a supplement to GPS which suffers from issues such as inaccuracy and loss of signal, RFID positioning is promising in facilitating connected vehicles applications. Two conceptual applications are provided here with one in vehicle operational control and the other in Level IV intersection control.

Space vehicle chassis

Science.gov (United States)

Judd, Stephen; Dallmann, Nicholas; Seitz, Daniel; Martinez, John; Storms, Steven; Kestell, Gayle

2017-07-18

A modular space vehicle chassis may facilitate convenient access to internal components of the space vehicle. Each module may be removable from the others such that each module may be worked on individually. Multiple panels of at least one of the modules may swing open or otherwise be removable, exposing large portions of the internal components of the space vehicle. Such chassis architectures may reduce the time required for and difficulty of performing maintenance or modifications, may allow multiple space vehicles to take advantage of a common chassis design, and may further allow for highly customizable space vehicles.

Integrated Vehicle Thermal Management - Combining Fluid Loops in Electric Drive Vehicles (Presentation)

Energy Technology Data Exchange (ETDEWEB)

Rugh, J. P.

2013-07-01

Plug-in hybrid electric vehicles and electric vehicles have increased vehicle thermal management complexity, using separate coolant loop for advanced power electronics and electric motors. Additional thermal components result in higher costs. Multiple cooling loops lead to reduced range due to increased weight. Energy is required to meet thermal requirements. This presentation for the 2013 Annual Merit Review discusses integrated vehicle thermal management by combining fluid loops in electric drive vehicles.

Potassium-cobalt sulphate crystal growth assisted by low frequency vibrations

Science.gov (United States)

Sadovsky, A.; Ermochenkov, I.; Dubovenko, E.; Sukhanova, E.; Bebyakin, M.; Dubov, V.; Avetissov, I.

2018-02-01

Single crystals of K2Co(SO4)2·6H2O were grown from solution using the temperature reduction method enhanced by the axial low frequency vibration control technique (AVC-technique). Physical modeling of heat-mass transfer in solution under the AVC action was performed. The growth rate of the AVC grown crystal was found to be twice that of the crystal grown under natural convection conditions. Analysis of spectral characteristics (absorption and Raman spectra) as well as structural properties (dislocation density and microhardness) of the grown crystals showed the significant superiority of the AVC technique for the growth of K2Co(SO4)2·6H2O crystals.

Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

Science.gov (United States)

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-01-01

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

Science.gov (United States)

Schultz, Gregory M.; Keranen, Joe; Miller, Jonathan S.; Shubitidze, Fridon

2014-06-01

The remediation of explosive remnants of war (ERW) and associated unexploded ordnance (UXO) has seen improvements through the injection of modern technological advances and streamlined standard operating procedures. However, reliable and cost-effective detection and geophysical mapping of sites contaminated with UXO such as cluster munitions, abandoned ordnance, and improvised explosive devices rely on the ability to discriminate hazardous items from metallic clutter. In addition to anthropogenic clutter, handheld and vehicle-based metal detector systems are plagued by natural geologic and environmental noise in many post conflict areas. We present new and advanced electromagnetic induction (EMI) technologies including man-portable and towed EMI arrays and associated data processing software. While these systems feature vastly different form factors and transmit-receive configurations, they all exhibit several fundamental traits that enable successful classification of EMI anomalies. Specifically, multidirectional sampling of scattered magnetic fields from targets and corresponding high volume of unique data provide rich information for extracting useful classification features for clutter rejection analysis. The quality of classification features depends largely on the extent to which the data resolve unique physics-based parameters. To date, most of the advanced sensors enable high quality inversion by producing data that are extremely rich in spatial content through multi-angle illumination and multi-point reception.

The paradox of atheoretical classification

DEFF Research Database (Denmark)

Hjørland, Birger

2016-01-01

A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

Conversion of Diesel Vehicles to Electric Vehicles and Controlled by PID Controller

OpenAIRE

Mengi, Onur Özdal

2017-01-01

Internal combustion engine vehicles are the most producedand sold vehicles on the market. In recent years, interest in electric vehicleshas begun to increase, especially due to the environmental problems. In thenear future, it is estimated that gasoline and diesel vehicles will becompletely electric vehicles. For this reason, many studies have been conductedon electric vehicles. Particularly the change of the engine parts, the turningof the internal combustion part to the electric motor, and ...

Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery

Science.gov (United States)

Bockelmann, Thomas R [Battle Creek, MI; Beaty, Kevin D [Kalamazoo, MI; Zou, Zhanijang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI

2009-07-21

A battery control system for controlling a state of charge of a hybrid vehicle battery includes a detecting arrangement for determining a vehicle operating state or an intended vehicle operating state and a controller for setting a target state of charge level of the battery based on the vehicle operating state or the intended vehicle operating state. The controller is operable to set a target state of charge level at a first level during a mobile vehicle operating state and at a second level during a stationary vehicle operating state or in anticipation of the vehicle operating in the stationary vehicle operating state. The invention further includes a method for controlling a state of charge of a hybrid vehicle battery.

An Aloe Vera-Based Cosmeceutical Cream Delays and Mitigates Ionizing Radiation-Induced Dermatitis in Head and Neck Cancer Patients Undergoing Curative Radiotherapy: A Clinical Study.

Science.gov (United States)

Rao, Suresh; Hegde, Sanath Kumar; Baliga-Rao, Manjeshwar Poonam; Palatty, Princy Louis; George, Thomas; Baliga, Manjeshwar Shrinath

2017-06-24

Background: This study was planned to evaluate the efficacy of topical application of an Aloe vera -based cream (AVC) for the prevention of ionizing radiation (X ray)-induced dermatitis in head and neck cancer patients requiring therapeutic radiation treatment (>62 Gy). Methods: From July 2012 to December 2012, a total of 60 head and neck cancer patients requiring curative radiotherapy (RT) of more than 66 Gy were prospectively enrolled and treated with AVC or a comparator Johnson's Baby Oil (JBO). Acute skin reaction was monitored and classified according to the Radiation Therapy Oncology Group (RTOG) four-point rating scale on a weekly basis. Results: The results indicate that there was a statistically significant delay in the incidence ( p = 0.04) of dermatitis at week three in the AVC application group. Application of AVC reduced the incidence of Grade 1, 2, and 3 dermatitis at subsequent time points, while Grade 4 dermatitis was not seen in either cohort. The other most important observation was that the continued application of AVC two weeks after the completion of RT was effective in reducing the average grade of dermatitis and was statistically significant ( p AVC-based cream is thus effective in delaying radiation dermatitis in head and neck cancer.

Transporter Classification Database (TCDB)

Data.gov (United States)

U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

The Electric Vehicle Development

DEFF Research Database (Denmark)

Wang, Jingyu; Liu, Yingqi; Kokko, Ari

2014-01-01

In order to respond to the energy crisis and environment problem, countries carry out their research and promotion about electric vehicles. As the ten cities one thousand new energy buses started in 2009, the new energy vehicles have been greatly developed in China, while the development...... in three aspects-city environment, government and stakeholders. Then the paper discusses the promotion ways and role of government and consumer. Finally, the paper offers some suggestions to promote electric vehicles in China: focusing on feasibility and adaptability of electric vehicles, playing...... of electric vehicles is not that good. This paper selects four cities-Los Angeles, Kanagawa, Hamburg, Amsterdam-that promote electric vehicles successfully and deeply analyzes the development of electric vehicles in these four cities and analyzes the factors that affect the development of electric vehicles...

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

Energy Technology Data Exchange (ETDEWEB)

Jürgens, Björn, E-mail: bjurgens@agenciaidea.es [Agency of Innovation and Development of Andalusia, CITPIA PATLIB Centre (Spain); Herrero-Solana, Victor, E-mail: victorhs@ugr.es [University of Granada, SCImago-UGR (SEJ036) (Spain)

2017-04-15

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

International Nuclear Information System (INIS)

Jürgens, Björn; Herrero-Solana, Victor

2017-01-01

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

Evaluating the accuracy of vehicle tracking data obtained from Unmanned Aerial Vehicles

Directory of Open Access Journals (Sweden)

Giuseppe Guido

2016-10-01

Full Text Available This paper presents a methodology for tracking moving vehicles that integrates Unmanned Aerial Vehicles with video processing techniques. The authors investigated the usefulness of Unmanned Aerial Vehicles to capture reliable individual vehicle data by using GPS technology as a benchmark. A video processing algorithm for vehicles trajectory acquisition is introduced. The algorithm is based on OpenCV libraries. In order to assess the accuracy of the proposed video processing algorithm an instrumented vehicle was equipped with a high precision GPS. The video capture experiments were performed in two case studies. From the field, about 24,000 positioning data were acquired for the analysis. The results of these experiments highlight the versatility of the Unmanned Aerial Vehicles technology combined with video processing technique in monitoring real traffic data.

Unmanned Aerial Vehicles (UAVs and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

Directory of Open Access Journals (Sweden)

Luis F. Gonzalez

2016-01-01

Full Text Available Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV, artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

Science.gov (United States)

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Electric vehicles and renewable energy in the transport sector - energy system consequences. Main focus: Battery electric vehicles and hydrogen based fuel cell vehicles

DEFF Research Database (Denmark)

Nielsen, L.H.; Jørgensen K.

2000-01-01

The aim of the project is to analyse energy, environmental and economic aspects of integrating electric vehicles in the future Danish energy system. Consequences of large-scale utilisation of electric vehicles are analysed. The aim is furthermore toillustrate the potential synergistic interplay...... between the utilisation of electric vehicles and large-scale utilisation of fluctuating renewable energy resources, such as wind power. Economic aspects for electric vehicles interacting with a liberalisedelectricity market are analysed. The project focuses on battery electric vehicles and fuel cell...... vehicles based on hydrogen. Based on assumptions on the future technical development for battery electric vehicles, fuel cell vehicles on hydrogen, and forthe conventional internal combustion engine vehicles, scenarios are set up to reflect expected options for the long-term development of road transport...

Lane-Level Vehicle Trajectory Reckoning for Cooperative Vehicle-Infrastructure System

Directory of Open Access Journals (Sweden)

Yinsong Wang

2012-01-01

Full Text Available This paper presents a lane-level positioning method by trajectory reckoning without Global Positioning System (GPS equipment in the environment of Cooperative Vehicle-Infrastructure System (CVIS. Firstly, the accuracy requirements of vehicle position in CVIS applications and the applicability of GPS positioning methods were analyzed. Then, a trajectory reckoning method based on speed and steering data from vehicle’s Control Area Network (CAN and roadside calibration facilities was proposed, which consists of three critical models, including real-time estimation of steering angle and vehicle direction, vehicle movement reckoning, and wireless calibration. Finally, the proposed method was validated through simulation and field tests under a variety of traffic conditions. Results show that the accuracy of the reckoned vehicle position can reach the lane level and match the requirements of common CVIS applications.

How important is vehicle safety for older consumers in the vehicle purchase process?

Science.gov (United States)

Koppel, Sjaan; Clark, Belinda; Hoareau, Effie; Charlton, Judith L; Newstead, Stuart V

2013-01-01

This study aimed to investigate the importance of vehicle safety to older consumers in the vehicle purchase process. Older (n = 102), middle-aged (n = 791), and younger (n = 109) participants throughout the eastern Australian states of Victoria, New South Wales, and Queensland who had recently purchased a new or used vehicle completed an online questionnaire about their vehicle purchase process. When asked to list the 3 most important considerations in the vehicle purchase process (in an open-ended format), older consumers were mostly likely to list price as their most important consideration (43%). Similarly, when presented with a list of vehicle factors (such as price, design, Australasian New Car Assessment Program [ANCAP] rating), older consumers were most likely to identify price as the most important vehicle factor (36%). When presented with a list of vehicle features (such as automatic transmission, braking, air bags), older consumers in the current study were most likely to identify an antilock braking system (41%) as the most important vehicle feature, and 50 percent of older consumers identified a safety-related vehicle feature as the highest priority vehicle feature (50%). When asked to list up to 3 factors that make a vehicle safe, older consumers in the current study were most likely to list braking systems (35%), air bags (22%), and the driver's behavior or skill (11%). When asked about the influence of safety in the new vehicle purchase process, one third of older consumers reported that all new vehicles are safe (33%) and almost half of the older consumers rated their vehicle as safer than average (49%). A logistic regression model was developed to predict the profile of older consumers more likely to assign a higher priority to safety features in the vehicle purchasing process. The model predicted that the importance of safety-related features was influenced by several variables, including older consumers' beliefs that they could protect themselves

Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

Science.gov (United States)

Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

1990-01-01

Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

Small-scale classification schemes

DEFF Research Database (Denmark)

Hertzum, Morten

2004-01-01

Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

Sex differences in aortic valve calcification measured by multidetector computed tomography in aortic stenosis.

Science.gov (United States)

Aggarwal, Shivani R; Clavel, Marie-Annick; Messika-Zeitoun, David; Cueff, Caroline; Malouf, Joseph; Araoz, Philip A; Mankad, Rekha; Michelena, Hector; Vahanian, Alec; Enriquez-Sarano, Maurice

2013-01-01

Aortic valve calcification (AVC) is the intrinsic mechanism of valvular obstruction leading to aortic stenosis (AS) and is measurable by multidetector computed tomography. The link between sex and AS is controversial and that with AVC is unknown. We prospectively performed multidetector computed tomography in 665 patients with AS (aortic valve area, 1.05±0.35 cm(2); mean gradient, 39±19 mm Hg) to measure AVC and to assess the impact of sex on the AVC-AS severity link in men and women. AS severity was comparable between women and men (peak aortic jet velocity: 4.05±0.99 versus 3.93±0.91 m/s, P=0.11; aortic valve area index: 0.55±0.20 versus 0.56±0.18 cm(2)/m(2); P=0.46). Conversely, AVC load was lower in women versus men (1703±1321 versus 2694±1628 arbitrary units; PAVC load were much greater in men than in women (odds ratio, 5.07; PAVC showed good associations with hemodynamic AS severity in men and women (all r>0.67; PAVC load, absolute or indexed, was higher in men versus women (all P≤0.01). In this large AS population, women incurred similar AS severity than men for lower AVC loads, even after indexing for their smaller body size. Hence, the relationship between valvular calcification process and AS severity differs in women and men, warranting further pathophysiological inquiry. For AS severity diagnostic purposes, interpretation of AVC load should be different in men and in women.

Statistical analysis of vehicle loads measured with three different vehicle weighing devices

CSIR Research Space (South Africa)

Mkhize, ZQP

2005-07-01

Full Text Available MEASURED WITH THREE DIFFERENT VEHICLE WEIGHING DEVICES Z Q P MKHIZE and M DE BEER CSIR Transportek, PO Box 395, Pretoria, 0001 ABSTRACT This study introduces a new scale for weighing individual tyres of slow moving vehicles. The new technology... that vehicles exert on pavements plays a vital part in the deterioration of the structural and functional capacity of the road. It also influences the safety of the vehicles, especially when vehicles are operated under overloaded and/or inappropriately loaded...

The impact of vehicle appearance and vehicle behavior on pedestrian interaction with autonomous vehicles

NARCIS (Netherlands)

Dey, D.; Martens, M.H.; Eggen, J.H.; Terken, J.M.B.

2017-01-01

In this paper, we present the preliminary results of a study that aims to investigate the role of an approaching vehicle's behavior and outer appearance in determining pedestrians' decisions while crossing a street. Concerning appearance, some vehicles are designed to look more assertive than

The Impact of Vehicle Appearance and Vehicle Behavior on Pedestrian Interaction with Autonomous Vehicles

NARCIS (Netherlands)

Dey, Debargha; Martens, Marieke; Eggen, Berry; Terken, Jacques

2017-01-01

In this paper, we present the preliminary results of a study that aims to investigate the role of an approaching vehicle's behavior and outer appearance in determining pedestrians' decisions while crossing a street. Concerning appearance, some vehicles are designed to look more assertive than

Protection against malevolent use of vehicles at Nuclear Power Plants. Vehicle barrier system selection guidance

International Nuclear Information System (INIS)

Nebuda, D.T.

1994-08-01

This manual provides a simplified procedure for selecting land vehicle barriers that will stop the design basis vehicle threat adopted by the U.S. Nuclear Regulatory Commission. Proper selection and construction of vehicle barriers should prevent intrusion of the design basis vehicle. In addition, vital safety related equipment should survive a design basis vehicle bomb attack when vehicle barriers are properly selected, sited, and constructed. This manual addresses passive vehicle barriers, active vehicle barriers, and site design features that can be used to reduce vehicle impact velocity

Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery

Science.gov (United States)

Bockelmann, Thomas R [Battle Creek, MI; Hope, Mark E [Marshall, MI; Zou, Zhanjiang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI

2009-02-10

A battery control system for hybrid vehicle includes a hybrid powertrain battery, a vehicle accessory battery, and a prime mover driven generator adapted to charge the vehicle accessory battery. A detecting arrangement is configured to monitor the vehicle accessory battery's state of charge. A controller is configured to activate the prime mover to drive the generator and recharge the vehicle accessory battery in response to the vehicle accessory battery's state of charge falling below a first predetermined level, or transfer electrical power from the hybrid powertrain battery to the vehicle accessory battery in response to the vehicle accessory battery's state of charge falling below a second predetermined level. The invention further includes a method for controlling a hybrid vehicle powertrain system.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

Science.gov (United States)

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning

Directory of Open Access Journals (Sweden)

Victoria Plaza-Leiva

2017-03-01

Full Text Available Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM, Gaussian processes (GP, and Gaussian mixture models (GMM. A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl. Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning.

Science.gov (United States)

Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

2017-03-15

Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

Science.gov (United States)

Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

2009-01-01

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

Information gathering for CLP classification

Directory of Open Access Journals (Sweden)

Ida Marcello

2011-01-01

Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

Multiple Attribute Decision Making Based Relay Vehicle Selection for Electric Vehicle Communication

Directory of Open Access Journals (Sweden)

Zhao Qiang

2015-01-01

Full Text Available Large-scale electric vehicle integration into power grid and charging randomly will cause serious impacts on the normal operation of power grid. Therefore, it is necessary to control the charging behavior of electric vehicle, while information transmission for electric vehicle is significant. Due to the highly mobile characteristics of vehicle, transferring information to power grid directly might be inaccessible. Relay vehicle (RV can be used for supporting multi-hop connection between SV and power grid. This paper proposes a multiple attribute decision making (MADM-based RV selection algorithm, which considers multiple attribute, including data transfer rate, delay, route duration. It takes the characteristics of electric vehicle communication into account, which can provide protection for the communication services of electric vehicle charging and discharging. Numerical results demonstrate that compared to previous algorithm, the proposed algorithm offer better performance in terms of throughput, transmission delay.

VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION

Directory of Open Access Journals (Sweden)

A. Schlichting

2016-06-01

Full Text Available LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position and 0.06° (heading, and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

Science.gov (United States)

Schlichting, A.; Brenner, C.

2016-06-01

LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

Vehicle Based Vector Sensor

Science.gov (United States)

2015-09-28

buoyant underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength...underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength; an...unmanned underwater vehicle that can function as an acoustic vector sensor. (2) Description of the Prior Art [0004] It is known that a propagating

ASIST SIG/CR Classification Workshop 2000: Classification for User Support and Learning.

Science.gov (United States)

Soergel, Dagobert

2001-01-01

Reports on papers presented at the 62nd Annual Meeting of ASIST (American Society for Information Science and Technology) for the Special Interest Group in Classification Research (SIG/CR). Topics include types of knowledge; developing user-oriented classifications, including domain analysis; classification in the user interface; and automatic…

Couinaud's classification v.s. Cho's classification. Their feasibility in the right hepatic lobe

International Nuclear Information System (INIS)

Shioyama, Yasukazu; Ikeda, Hiroaki; Sato, Motohito; Yoshimi, Fuyo; Kishi, Kazushi; Sato, Morio; Kimura, Masashi

2008-01-01

The objective of this study was to investigate if the new classification system proposed by Cho is feasible to clinical usage comparing with the classical Couinaud's one. One hundred consecutive cases of abdominal CT were studied using a 64 or an 8 slice multislice CT and created three dimensional portal vein images for analysis by the Workstation. We applied both Cho's classification and the classical Couinaud's one for each cases according to their definitions. Three diagnostic radiologists assessed their feasibility as category one (unable to classify) to five (clear to classify with total suit with the original classification criteria). And in each cases, we tried to judge whether Cho's or the classical Couinaud' classification could more easily transmit anatomical information. Analyzers could classified portal veins clearly (category 5) in 77 to 80% of cases and clearly (category 5) or almost clearly (category 4) in 86-93% along with both classifications. In the feasibility of classification, there was no statistically significant difference between two classifications. In 15 cases we felt that using Couinaud's classification is more convenient for us to transmit anatomical information to physicians than using Cho's one, because in these cases we noticed two large portal veins ramify from right main portal vein cranialy and caudaly and then we could not classify P5 as a branch of antero-ventral segment (AVS). Conversely in 17 cases we felt Cho's classification is more convenient because we could not divide right posterior branch as P6 and P7 and in these cases the right posterior portal vein ramified to several small branches. The anterior fissure vein was clearly noticed in only 60 cases. Comparing the classical Couinaud's classification and Cho's one in feasility of classification, there was no statistically significant difference. We propose we routinely report hepatic anatomy with the classical Couinauds classification and in the preoperative cases we

Refining Time-Activity Classification of Human Subjects Using the Global Positioning System.

Science.gov (United States)

Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun

2016-01-01

Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well

The influence of the day of the week of hospital admission on the prognosis of stroke patients Influencia del día de la semana de admisión hospitalaria en el pronóstico de pacientes con accidente vascular cerebral O dia da semana de admissão hospitalar influenciando o prognóstico de pacientes com acidente vascular cerebral

Directory of Open Access Journals (Sweden)

Paulo A. Lotufo

2013-04-01

Full Text Available This study aimed to evaluate the weekday and weekend distribution of stroke case hospital admissions and their respective prognosis based on a sample from the Estudo de Mortalidade e Morbidade do Acidente Vascular Cerebral (EMMA, a cohort of stroke patients admitted to a community hospital in the city of São Paulo, Brazil. We ascertained all consecutive cases of first-time strokes between April 2006 and December 2008 and performed a subsequent one-year follow-up. No association was found between frequency of hospital admissions due to ischemic and hemorrhagic strokes and the specific day of the week on which the admission occurred. However, ten-day and twelve-month case-fatality was higher in hemorrhagic stroke patients admitted at the weekend. We also found that intracerebral hemorrhage patients admitted on weekends had a worse survival rate (50% compared with those admitted during weekdays (25.6%, P log-rank = 0.03. We found a multivariate hazard ratio of 2.49 (95%CI: 1.10-5.81, P trend = 0.03 for risk of death at the weekend compared to weekdays for intracerebral hemorrhage cases. No difference in survival was observed with respect to the overall sample of stroke or ischemic stroke patients.El estudio evaluó la distribución de casos incidentes de accidente vascular cerebral (AVC que fueron al hospital de lunes a viernes o durante los fines de semana en el Estudio de Mortalidad y Morbilidad del AVC (EMMA. El EMMA es una cohorte de pacientes con AVC en un hospital comunitario de la ciudad de São Paulo, Brasil. Casos consecutivos de primer episodio de AVC internados, entre abril de 2006 y diciembre de 2008, fueron seguidos prospectivamente durante un año. No hubo diferencia en la frecuencia de las internaciones por AVC isquémico o hemorrágico durante los días de la semana. Sin embargo, la letalidad en 10 días y tras un año había aumentado en el AVC hemorrágico. En el análisis de supervivencia de un año, pacientes admitidos los

Electric/Hybrid Vehicle Simulation

Science.gov (United States)

Slusser, R. A.; Chapman, C. P.; Brennand, J. P.

1985-01-01

ELVEC computer program provides vehicle designer with simulation tool for detailed studies of electric and hybrid vehicle performance and cost. ELVEC simulates performance of user-specified electric or hybrid vehicle under user specified driving schedule profile or operating schedule. ELVEC performs vehicle design and life cycle cost analysis.

Determining the Effectiveness of Incorporating Geographic Information Into Vehicle Performance Algorithms

Energy Technology Data Exchange (ETDEWEB)

Sera White

2012-04-01

This thesis presents a research study using one year of driving data obtained from plug-in hybrid electric vehicles (PHEV) located in Sacramento and San Francisco, California to determine the effectiveness of incorporating geographic information into vehicle performance algorithms. Sacramento and San Francisco were chosen because of the availability of high resolution (1/9 arc second) digital elevation data. First, I present a method for obtaining instantaneous road slope, given a latitude and longitude, and introduce its use into common driving intensity algorithms. I show that for trips characterized by >40m of net elevation change (from key on to key off), the use of instantaneous road slope significantly changes the results of driving intensity calculations. For trips exhibiting elevation loss, algorithms ignoring road slope overestimated driving intensity by as much as 211 Wh/mile, while for trips exhibiting elevation gain these algorithms underestimated driving intensity by as much as 333 Wh/mile. Second, I describe and test an algorithm that incorporates vehicle route type into computations of city and highway fuel economy. Route type was determined by intersecting trip GPS points with ESRI StreetMap road types and assigning each trip as either city or highway route type according to whichever road type comprised the largest distance traveled. The fuel economy results produced by the geographic classification were compared to the fuel economy results produced by algorithms that assign route type based on average speed or driving style. Most results were within 1 mile per gallon ({approx}3%) of one another; the largest difference was 1.4 miles per gallon for charge depleting highway trips. The methods for acquiring and using geographic data introduced in this thesis will enable other vehicle technology researchers to incorporate geographic data into their research problems.

Sustainable Federal Fleets: Deploying Electric Vehicles and Electric Vehicle Supply Equipment

Energy Technology Data Exchange (ETDEWEB)

2017-01-01

The U.S. Department of Energy (DOE) Federal Energy Management Program (FEMP) helps federal agencies reduce petroleum consumption and increase alternative fuel use through its resources for Sustainable Federal Fleets. To assist agencies with the transition to plug-in electric vehicles (PEVs), including battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), FEMP offers technical guidance on electric vehicle supply equipment (EVSE) installations and site-specific planning through partnerships with the National Renewable Energy Laboratory's (NREL's) EVSE Tiger Teams.

Classification with support hyperplanes

NARCIS (Netherlands)

G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

2006-01-01

textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

Electric Vehicle Technician

Science.gov (United States)

Moore, Pam

2011-01-01

With President Obama's goal to have one million electric vehicles (EV) on the road by 2015, the electric vehicle technician should have a promising and busy future. "The job force in the car industry is ramping up for a revitalized green car industry," according to Greencareersguide.com. An electric vehicle technician will safely troubleshoot and…

Hyperspectral Vehicle BRDF Learning: An Exploration of Vehicle Reflectance Variation and Optimal Measures of Spectral Similarity for Vehicle Reacquisition and Tracking Algorithms

Science.gov (United States)

Svejkosky, Joseph

The spectral signatures of vehicles in hyperspectral imagery exhibit temporal variations due to the preponderance of surfaces with material properties that display non-Lambertian bi-directional reflectance distribution functions (BRDFs). These temporal variations are caused by changing illumination conditions, changing sun-target-sensor geometry, changing road surface properties, and changing vehicle orientations. To quantify these variations and determine their relative importance in a sub-pixel vehicle reacquisition and tracking scenario, a hyperspectral vehicle BRDF sampling experiment was conducted in which four vehicles were rotated at different orientations and imaged over a six-hour period. The hyperspectral imagery was calibrated using novel in-scene methods and converted to reflectance imagery. The resulting BRDF sampled time-series imagery showed a strong vehicle level BRDF dependence on vehicle shape in off-nadir imaging scenarios and a strong dependence on vehicle color in simulated nadir imaging scenarios. The imagery also exhibited spectral features characteristic of sampling the BRDF of non-Lambertian targets, which were subsequently verified with simulations. In addition, the imagery demonstrated that the illumination contribution from vehicle adjacent horizontal surfaces significantly altered the shape and magnitude of the vehicle reflectance spectrum. The results of the BRDF sampling experiment illustrate the need for a target vehicle BRDF model and detection scheme that incorporates non-Lambertian BRDFs. A new detection algorithm called Eigenvector Loading Regression (ELR) is proposed that learns a hyperspectral vehicle BRDF from a series of BRDF measurements using regression in a lower dimensional space and then applies the learned BRDF to make test spectrum predictions. In cases of non-Lambertian vehicle BRDF, this detection methodology performs favorably when compared to subspace detections algorithms and graph-based detection algorithms that

Classification of Flotation Frothers

Directory of Open Access Journals (Sweden)

Jan Drzymala

2018-02-01

Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

Waste Collection Vehicle Routing Problem: Literature Review

Directory of Open Access Journals (Sweden)

Hui Han

2015-08-01

Full Text Available Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP in literature. Based on a classification of waste collection (residential, commercial and industrial, firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP.

DOE LLW classification rationale

International Nuclear Information System (INIS)

Flores, A.Y.

1991-01-01

This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems

Vehicle electrification. Quo vadis?

Energy Technology Data Exchange (ETDEWEB)

Brinkman, N. [GM Global Research and Development, Warren, MI (United States); Eberle, U.; Formanski, V.; Grebe, U.D.; Matthe, R. [General Motors Europe, Ruesselsheim (Germany)

2012-11-01

This publication describes the development of electrified propulsion systems from the invention of the automobile to the present and then provides an outlook on expected technology progress. Vehicle application areas for the various systems are identified based on a range of energy supply chains and the technological limits of electric powertrain components. GM anticipates that vehicle electrification will increase in the future. Battery-electric vehicles will become competitive for some applications, especially intra-urban, short-distance driving. Range-extended electric vehicles provide longer driving range and offer full capability; with this technology, electric vehicles can serve as the prime vehicle for many customers. Hydrogen-powered fuel cell-electric powertrains have potential for application across most of the vehicle segments. They produce zero emissions during all phases of operation, offer short refueling times, but have powertrain cooling and hydrogen storage packaging constraints. While the market share of electrified vehicles is expected to increase significantly, GM expects conventional powertrains with internal combustion engines to also have a long future - however, a lot of them will be supported by various levels of electrification. (orig.)

Quantified degree of eccentricity of aortic valve calcification predicts risk of paravalvular regurgitation and response to balloon post-dilation after self-expandable transcatheter aortic valve replacement.

Science.gov (United States)

Park, Jun-Bean; Hwang, In-Chang; Lee, Whal; Han, Jung-Kyu; Kim, Chi-Hoon; Lee, Seung-Pyo; Yang, Han-Mo; Park, Eun-Ah; Kim, Hyung-Kwan; Chiam, Paul T L; Kim, Yong-Jin; Koo, Bon-Kwon; Sohn, Dae-Won; Ahn, Hyuk; Kang, Joon-Won; Park, Seung-Jung; Kim, Hyo-Soo

2018-05-15

Limited data exist regarding the impact of aortic valve calcification (AVC) eccentricity on the risk of paravalvular regurgitation (PVR) and response to balloon post-dilation (BPD) after transcatheter aortic valve replacement (TAVR). We investigated the prognostic value of AVC eccentricity in predicting the risk of PVR and response to BPD in patients undergoing TAVR. We analyzed 85 patients with severe aortic stenosis who underwent self-expandable TAVR (43 women; 77.2±7.1years). AVC was quantified as the total amount of calcification (total AVC load) and as the eccentricity of calcium (EoC) using calcium volume scoring with contrast computed tomography angiography (CTA). The EoC was defined as the maximum absolute difference in calcium volume scores between 2 adjacent sectors (bi-partition method) or between sectors based on leaflets (leaflet-based method). Total AVC load and bi-partition EoC, but not leaflet-based EoC, were significant predictors for the occurrence of ≥moderate PVR, and bi-partition EoC had a better predictive value than total AVC load (area under the curve [AUC]=0.863 versus 0.760, p for difference=0.006). In multivariate analysis, bi-partition EoC was an independent predictor for the risk of ≥moderate PVR regardless of perimeter oversizing index. The greater bi-partition EoC was the only significant parameter to predict poor response to BPD (AUC=0.775, p=0.004). Pre-procedural assessment of AVC eccentricity using CTA as "bi-partition EoC" provides useful predictive information on the risk of significant PVR and response to BPD in patients undergoing TAVR with self-expandable valves. Copyright © 2017 Elsevier B.V. All rights reserved.

Asteroid taxonomic classifications

International Nuclear Information System (INIS)

Tholen, D.J.

1989-01-01

This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

The New START Treaty: Central Limits and Key Provisions

Science.gov (United States)

2014-08-27

article-by-article analysis can be found at http://www.state.gov/t/ avc /newstart/c44126.htm. 2 For a brief summary of the original START Treaty, as...2014, http://www.state.gov/t/ avc /rls/224236.htm . The fact sheet does not display warhead subtotals for each delivery system; it only includes an...of Strategic Offensive Forces, Fact Sheet, Washington, DC, April 1, 2014, http://www.state.gov/t/ avc /rls/228652.htm. The New START Treaty: Central

Vehicle-to-vehicle communications : readiness of V2V technology for application.

Science.gov (United States)

2014-08-01

The purpose of this research report is to assess the readiness for application of vehicle-to-vehicle (V2V) : communications, a system designed to transmit basic safety information between vehicles to facilitate warnings to : drivers concerning impend...

75 FR 22317 - Federal Motor Vehicle Safety Standards; Small Business Impacts of Motor Vehicle Safety

Science.gov (United States)

2010-04-28

... 1300 [Docket No. NHTSA-2010-0054] Federal Motor Vehicle Safety Standards; Small Business Impacts of Motor Vehicle Safety AGENCY: National Highway Traffic Safety Administration (NHTSA), Department of..., multipurpose passenger vehicles, trucks, buses, trailers, incomplete vehicles, motorcycles, and motor vehicle...

Sensing and control for autonomous vehicles applications to land, water and air vehicles

CERN Document Server

Pettersen, Kristin; Nijmeijer, Henk

2017-01-01

This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light intervention work, underwater survey and collection of oceanographic/biological data. Autonomous unmanned aerial systems can be used in a large number of applications such as inspection, monitoring, data collection, surveillance, etc. At present, vehicles operate with limited autonomy and a minimum of intelligence. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles. Unmanned vehicles with high levels of autonomy may be used for safe and efficient collection of environmental data, for assimilation of climate and environmental models and to complement global satellite sy...

Usability Analysis of Collision Avoidance System in Vehicle-to-Vehicle Communication Environment

Directory of Open Access Journals (Sweden)

Hong Cho

2014-01-01

Full Text Available Conventional intelligent vehicles have performance limitations owing to the short road and obstacle detection range of the installed sensors. In this study, to overcome this limitation, we tested the usability of a new conceptual autonomous emergency braking (AEB system that employs vehicle-to-vehicle (V2V communication technology in the existing AEB system. To this end, a radar sensor and a driving and communication environment constituting the AEB system were simulated; the simulation was then linked by applying vehicle dynamics and control logic. The simulation results show that the collision avoidance relaxation rate of V2V communication-based AEB system was reduced compared with that of existing vehicle-mounted-sensor-based system. Thus, a method that can lower the collision risk of the existing AEB system, which uses only a sensor cluster installed on the vehicle, is realized.

Choice of teenagers' vehicles and views on vehicle safety: survey of parents of novice teenage drivers.

Science.gov (United States)

Hellinga, Laurie A; McCartt, Anne T; Haire, Emily R

2007-01-01

To examine parental decisions about vehicles driven by teenagers and parental knowledge of vehicle safety. About 300 parents were interviewed during spring 2006 in Minnesota, North Carolina, and Rhode Island while teenagers took their first on-road driving tests. Fewer than half of parents surveyed said teenagers would be the primary drivers of the chosen vehicles. Parents most often cited safety, existing family vehicle, and reliability when explaining the choices for their teenagers' vehicles. About half of the vehicles intended for teenagers were small/mini/sports cars, pickups, or SUVs - vehicles considered less safe for teenagers than midsize/large cars or minivans. A large majority of vehicles were 2001 models or earlier. Vehicles purchased in anticipation of adding a new driver to the family were more likely to be the sizes/types considered less safe than vehicles already owned. Few parents insisted on side airbags or electronic stability control, despite strong evidence of their safety benefits. Even when asked to identify ideal vehicles for their teenagers to drive, about half of parents identified less safe vehicle sizes/types. Most parents knew that midsize/large vehicles are safer than small vehicles, and at least half of parents said SUVs and pickups are not safe for teenage drivers, citing instability. The majority of parents understood some of the important criteria for choosing safe vehicles for their teenagers. However, parents actually selected many vehicles for teenagers that provide inferior crash protection. Vehicle safety varies substantially by vehicle size, type, and safety features. Many teenagers are driving inferior vehicles in terms of crashworthiness and crash avoidance.

Vehicle test report: Electric Vehicle Associates electric conversion of an AMC Pacer

Science.gov (United States)

Price, T. W.; Wirth, V. A., Jr.; Pompa, M. F.

1981-01-01

Tests were performed to characterize certain parameters of the EVA Pacer and to provide baseline data that can be used for the comparison of improved batteries that may be incorporated into the vehicle at a later time. The vehicle tests were concentrated on the electrical drive subsystem; i.e., the batteries, controller and motor. The tests included coastdowns to characterize the road load, and range evaluations for both cyclic and constant speed conditions. A qualitative evaluation of the vehicle's performance was made by comparing its constant speed range performance with other electric and hybrid vehicles. The Pacer performance was approximately equal to the majority of those vehicles assessed in 1977.

Electric and hybrid vehicles

Science.gov (United States)

1979-01-01

Report characterizes state-of-the-art electric and hybrid (combined electric and heat engine) vehicles. Performance data for representative number of these vehicles were obtained from track and dynamometer tests. User experience information was obtained from fleet operators and individual owners of electric vehicles. Data on performance and physical characteristics of large number of vehicles were obtained from manufacturers and available literature.

Supercavitating Vehicle Control

Science.gov (United States)

2008-10-10

401) 832-1511. DISTRIBUTION STATEMENT Approved for Public Release Distribution is unlimited 20081027289 Attorney Docket No. 96674 SUPERCAVITATING ...methods and more specifically to systems and methods for controlling a trajectory of a supercavitating vehicle. (2) Description of the Prior Art [0004...1 [0005) Some investigations into reducing the drag of high-speed, underwater vehicles have focused attention on supercavitating underwater vehicles

32 CFR 2001.15 - Classification guides.

Science.gov (United States)

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

Hydrogen vehicle fueling station

Energy Technology Data Exchange (ETDEWEB)

Daney, D.E.; Edeskuty, F.J.; Daugherty, M.A. [Los Alamos National Lab., NM (United States)] [and others

1995-09-01

Hydrogen fueling stations are an essential element in the practical application of hydrogen as a vehicle fuel, and a number of issues such as safety, efficiency, design, and operating procedures can only be accurately addressed by a practical demonstration. Regardless of whether the vehicle is powered by an internal combustion engine or fuel cell, or whether the vehicle has a liquid or gaseous fuel tank, the fueling station is a critical technology which is the link between the local storage facility and the vehicle. Because most merchant hydrogen delivered in the US today (and in the near future) is in liquid form due to the overall economics of production and delivery, we believe a practical refueling station should be designed to receive liquid. Systems studies confirm this assumption for stations fueling up to about 300 vehicles. Our fueling station, aimed at refueling fleet vehicles, will receive hydrogen as a liquid and dispense it as either liquid, high pressure gas, or low pressure gas. Thus, it can refuel any of the three types of tanks proposed for hydrogen-powered vehicles -- liquid, gaseous, or hydride. The paper discusses the fueling station design. Results of a numerical model of liquid hydrogen vehicle tank filling, with emphasis on no vent filling, are presented to illustrate the usefulness of the model as a design tool. Results of our vehicle performance model illustrate our thesis that it is too early to judge what the preferred method of on-board vehicle fuel storage will be in practice -- thus our decision to accommodate all three methods.

Procurement Policy for Armored Vehicles

National Research Council Canada - National Science Library

Jolliffe, Richard B; Burton, Bruce A; Carros, Deborah L; Schaefer, Beth K; Truong, Linh; Palmer, Kevin A; Chun, Judy M; Smith, Jessica M; Abraham, Amanda M; Peters, Anthony R

2007-01-01

...., and Armor Holdings, Inc., for armored vehicles. This report addresses armored vehicles, specifically the Buffalo Mine Protected Clearance Vehicle, the Cougar, the Joint Explosive Ordnance Disposal Rapid Response Vehicle (JERRV...

FACET CLASSIFICATIONS OF E-LEARNING TOOLS

Directory of Open Access Journals (Sweden)

Olena Yu. Balalaieva

2013-12-01

Full Text Available The article deals with the classification of e-learning tools based on the facet method, which suggests the separation of the parallel set of objects into independent classification groups; at the same time it is not assumed rigid classification structure and pre-built finite groups classification groups are formed by a combination of values taken from the relevant facets. An attempt to systematize the existing classification of e-learning tools from the standpoint of classification theory is made for the first time. Modern Ukrainian and foreign facet classifications of e-learning tools are described; their positive and negative features compared to classifications based on a hierarchical method are analyzed. The original author's facet classification of e-learning tools is proposed.

Solar-coupled electric vehicles

International Nuclear Information System (INIS)

Buchheim, R.

1993-01-01

Electric cars must have the same safety standards as those which are now state of the art for the compact class of car. Electric vehicles should substitute for conventional vehicles and should not lead to an increase in the stock of vehicles. The current subject of 'side impact protection' shows that design measures are necessary for this, which cannot be achieved in the smallest vehicles. (orig.) [de

Mixing geometric and radiometric features for change classification

Science.gov (United States)

Fournier, Alexandre; Descombes, Xavier; Zerubia, Josiane

2008-02-01

Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data.

Abandoned vehicles

CERN Multimedia

Relations with the Host States Service

2004-01-01

The services in charge of managing the CERN site have recently noted an increase in the number of abandoned vehicles. This poses a risk from the point of view of safety and security and, on the eve of several important events in honour of CERN's fiftieth anniversary, is detrimental to the Organization's image. Owners of vehicles that have been left immobile for some time on the CERN site, including on the external car park by the flags, are therefore invited to contact the Reception and Access Control Service (service-parking-longterm@cern.ch) before 1st October 2004 and, where appropriate, move their vehicle to a designated long-term parking area. After this date, any vehicle whose owner has failed to respond to this request and which is without a number plate, has been stationary for several weeks or is out of service, may be impounded at the owner's risk and expense. Relations with the Host States Service Tel. 72848

Electric vehicles and renewable energy in the transport sector - energy system consequences. Main focus: Battery electric vehicles and hydrogen based fuel cell vehicles

Energy Technology Data Exchange (ETDEWEB)

Nielsen, L.H.; Joergensen, K.

2000-04-01

The aim of the project is to analyse energy, environmental and economic aspects of integrating electric vehicles in the future Danish energy system. Consequences of large-scale utilisation of electric vehicles are analysed. The aim is furthermore to illustrate the potential synergistic interplay between the utilisation of electric vehicles and large-scale utilisation of fluctuating renewable energy resources, such as wind power. Economic aspects for electric vehicles interacting with a liberalised electricity market are analysed. The project focuses on battery electric vehicles and fuel cell vehicles based on hydrogen. Based on assumptions on the future technical development for battery electric vehicles, fuel cell vehicles on hydrogen, and for the conventional internal combustion engine vehicles, scenarios are set up to reflect expected options for the long-term development of road transport vehicles. Focus is put on the Danish fleet of passenger cars and delivery vans. The scenario analysis includes assumptions on market potential developments and market penetration for the alternative vehicles. Vehicle replacement rates in the Danish transport fleet and the size of fleet development are based on data from The Danish Road Directorate. The electricity supply system development assumed is based on the Danish energy plan, Energy 21, The Plan scenario. The time horizon of the analysis is year 2030. Results from the scenario analysis include the time scales involved for the potential transition towards electricity based vehicles, the fleet composition development, the associated developments in transport fuel consumption and fuel substitution, and the potential CO{sub 2}-emission reduction achievable in the overall transport and power supply system. Detailed model simulations, on an hourly basis, have furthermore been carried out for year 2005 that address potential electricity purchase options for electric vehicles in the context of a liberalised electricity market

Electric vehicles and renewable energy in the transport sector - energy system consequences. Main focus: Battery electric vehicles and hydrogen based fuel cell vehicles

International Nuclear Information System (INIS)

Nielsen, L.H.; Joergensen, K.

2000-04-01

The aim of the project is to analyse energy, environmental and economic aspects of integrating electric vehicles in the future Danish energy system. Consequences of large-scale utilisation of electric vehicles are analysed. The aim is furthermore to illustrate the potential synergistic interplay between the utilisation of electric vehicles and large-scale utilisation of fluctuating renewable energy resources, such as wind power. Economic aspects for electric vehicles interacting with a liberalised electricity market are analysed. The project focuses on battery electric vehicles and fuel cell vehicles based on hydrogen. Based on assumptions on the future technical development for battery electric vehicles, fuel cell vehicles on hydrogen, and for the conventional internal combustion engine vehicles, scenarios are set up to reflect expected options for the long-term development of road transport vehicles. Focus is put on the Danish fleet of passenger cars and delivery vans. The scenario analysis includes assumptions on market potential developments and market penetration for the alternative vehicles. Vehicle replacement rates in the Danish transport fleet and the size of fleet development are based on data from The Danish Road Directorate. The electricity supply system development assumed is based on the Danish energy plan, Energy 21, The Plan scenario. The time horizon of the analysis is year 2030. Results from the scenario analysis include the time scales involved for the potential transition towards electricity based vehicles, the fleet composition development, the associated developments in transport fuel consumption and fuel substitution, and the potential CO 2 -emission reduction achievable in the overall transport and power supply system. Detailed model simulations, on an hourly basis, have furthermore been carried out for year 2005 that address potential electricity purchase options for electric vehicles in the context of a liberalised electricity market. The

Ariane transfer vehicle scenario

Science.gov (United States)

Deutscher, Norbert; Cougnet, Claude

1990-10-01

ESA's Ariane Transfer Vehicle (ATV) is a vehicle design concept for the transfer of payloads from Ariane 5 launch vehicle orbit insertion to a space station, on the basis of the Ariane 5 program-developed Upper Stage Propulsion Module and Vehicle Equipment Bay. The ATV is conceived as a complement to the Hermes manned vehicle for lower cost unmanned carriage of logistics modules and other large structural elements, as well as waste disposal. It is also anticipated that the ATV will have an essential role in the building block transportation logistics of any prospective European space station.

Vehicle Development Laboratory

Data.gov (United States)

Federal Laboratory Consortium — FUNCTION: Supports the development of prototype deployment platform vehicles for offboard countermeasure systems.DESCRIPTION: The Vehicle Development Laboratory is...

Maxillectomy defects: a suggested classification scheme.

Science.gov (United States)

Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

2013-06-01

The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

Metabolic mapping of the brain's response to visual stimulation: studies in humans

International Nuclear Information System (INIS)

Phelps, M.E.; Kuhl, D.E.; Mazziotta, J.C.

1981-01-01

These studies demonstrated increasing glucose metabolic rates in the human primary (PVC) and associative (AVC) visual cortex as the complexity of visual scenes increased. The metabolic response of the AVC increased more rapidly with scene complexity than that of the PVC, indicating the greater involvement of the higher order AVC for complex visual interpretations. Increases in local metabolic activity by as much as a factor of 2 above that of control subjects with eyes closed indicate the wide range and metabolic reserve of the visual cortex

Constructing criticality by classification

DEFF Research Database (Denmark)

Machacek, Erika

2017-01-01

" in the bureaucratic practice of classification: Experts construct material criticality in assessments as they allot information on the materials to the parameters of the assessment framework. In so doing, they ascribe a new set of connotations to the materials, namely supply risk, and their importance to clean energy......, legitimizing a criticality discourse.Specifically, the paper introduces a typology delineating the inferences made by the experts from their produced recommendations in the classification of rare earth element criticality. The paper argues that the classification is a specific process of constructing risk....... It proposes that the expert bureaucratic practice of classification legitimizes (i) the valorisation that was made in the drafting of the assessment framework for the classification, and (ii) political operationalization when enacted that might have (non-)distributive implications for the allocation of public...

12 CFR 403.4 - Derivative classification.

Science.gov (United States)

2010-01-01

... SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative classification. (1) Unlike original classification which is an initial determination, derivative classification... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4...

A Classification-oriented Method of Feature Image Generation for Vehicle-borne Laser Scanning Point Clouds

Directory of Open Access Journals (Sweden)

YANG Bisheng

2016-02-01

Full Text Available An efficient method of feature image generation of point clouds to automatically classify dense point clouds into different categories is proposed, such as terrain points, building points. The method first uses planar projection to sort points into different grids, then calculates the weights and feature values of grids according to the distribution of laser scanning points, and finally generates the feature image of point clouds. Thus, the proposed method adopts contour extraction and tracing means to extract the boundaries and point clouds of man-made objects (e.g. buildings and trees in 3D based on the image generated. Experiments show that the proposed method provides a promising solution for classifying and extracting man-made objects from vehicle-borne laser scanning point clouds.

Comparison performance of split plug-in hybrid electric vehicle and hybrid electric vehicle using ADVISOR

Directory of Open Access Journals (Sweden)

Mohd Rashid Muhammad Ikram

2017-01-01

Full Text Available Electric vehicle suffers from relatively short range and long charging times and consequently has not become an acceptable solution to the automotive consumer. The addition of an internal combustion engine to extend the range of the electric vehicle is one method of exploiting the high efficiency and lack of emissions of the electric vehicle while retaining the range and convenient refuelling times of a conventional gasoline powered vehicle. The term that describes this type of vehicle is a hybrid electric vehicle. Many configurations of hybrid electric vehicles have been designed and implemented, namely the series, parallel and power-split configurations. This paper discusses the comparison between Split Plug-in Hybrid Electric Vehicle(SPHEV and Hybrid Electric Vehicle(HEV. Modelling methods such as physics-based Resistive Companion Form technique and Bond Graph method are presented with powertrain component and system modelling examples. The modelling and simulation capability of existing tools such as ADvanced VehIcle SimulatOR (ADVISOR is demonstrated through application examples. Since power electronics is indispensable in hybrid vehicles, the issue of numerical oscillations in dynamic simulations involving power electronics is briefly addressed.

Connected vehicles and cybersecurity.

Science.gov (United States)

2016-01-01

Connected vehicles are a next-generation technology in vehicles and in infrastructure that will make travel safer, cleaner, and more efficient. The advanced wireless technology enables vehicles to share and communicate information with each other and...

Supernova Photometric Lightcurve Classification

Science.gov (United States)

Zaidi, Tayeb; Narayan, Gautham

2016-01-01

This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

Advanced Vehicle Testing and Evaluation

Energy Technology Data Exchange (ETDEWEB)

Garetson, Thomas [The Clarity Group, Incorporated, Chicago, IL (United States)

2013-03-31

The objective of the United States (U.S.) Department of Energy's (DOEs) Advanced Vehicle Testing and Evaluation (AVTE) project was to provide test and evaluation services for advanced technology vehicles, to establish a performance baseline, to determine vehicle reliability, and to evaluate vehicle operating costs in fleet operations.Vehicles tested include light and medium-duty vehicles in conventional, hybrid, and all-electric configurations using conventional and alternative fuels, including hydrogen in internal combustion engines. Vehicles were tested on closed tracks and chassis dynamometers, as well as operated on public roads, in fleet operations, and over prescribed routes. All testing was controlled by procedures developed specifically to support such testing.

Project implementation : classification of organic soils and classification of marls - training of INDOT personnel.

Science.gov (United States)

2012-09-01

This is an implementation project for the research completed as part of the following projects: SPR3005 Classification of Organic Soils : and SPR3227 Classification of Marl Soils. The methods developed for the classification of both soi...

45 CFR 601.5 - Derivative classification.

Science.gov (United States)

2010-10-01

... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... classification guide, need not possess original classification authority. (a) If a person who applies derivative...

De alcoholverkeercursussen : interimverslag van het evaluatie-onderzoek

NARCIS (Netherlands)

Brouwers, M.; Leuw, E.

1990-01-01

Het onderzoek is erop gericht informatie te geven over de volgende punten:Welke typen alcohol-verkeerswet overtreders worden door de Alcoholverkeercurussen (AVC's) bereikt?Welke effecten hebben de AVC's op relevante kennis, attituden en gedragingen van de cursisten?

Design and Implementation of an Emergency Vehicle Signal Preemption System Based on Cooperative Vehicle-Infrastructure Technology

OpenAIRE

Yinsong Wang; Zhizhou Wu; Xiaoguang Yang; Luoyi Huang

2013-01-01

Emergency vehicle is an important part of traffic flow. The efficiency, reliability, and safety of emergency vehicle operations dropped due to increasing traffic congestion. With the advancement of the wireless communication technologies and the development of the vehicle-to-vehicle (v2v) and vehicle-to-infrastructure (v2i) systems, called Cooperative Vehicle-Infrastructure System (CVIS), there is an opportunity to provide appropriate traffic signal preemption for emergency vehicle based on r...

Household vehicles energy consumption 1994

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-08-01

Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

Ground Vehicle Convoying

Science.gov (United States)

Gage, Douglas W.; Pletta, J. Bryan

1987-01-01

Initial investigations into two different approaches for applying autonomous ground vehicle technology to the vehicle convoying application are described. A minimal capability system that would maintain desired speed and vehicle spacing while a human driver provided steering control could improve convoy performance and provide positive control at night and in inclement weather, but would not reduce driver manpower requirements. Such a system could be implemented in a modular and relatively low cost manner. A more capable system would eliminate the human driver in following vehicles and reduce manpower requirements for the transportation of supplies. This technology could also be used to aid in the deployment of teleoperated vehicles in a battlefield environment. The needs, requirements, and several proposed solutions for such an Attachable Robotic Convoy Capability (ARCC) system will be discussed. Included are discussions of sensors, communications, computers, control systems and safety issues. This advanced robotic convoy system will provide a much greater capability, but will be more difficult and expensive to implement.

Learning features for tissue classification with the classification restricted Boltzmann machine

DEFF Research Database (Denmark)

van Tulder, Gijs; de Bruijne, Marleen

2014-01-01

Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce the convo...... outperform conventional RBM-based feature learning, which is unsupervised and uses only a generative learning objective, as well as often-used filter banks. We show that a mixture of generative and discriminative learning can produce filters that give a higher classification accuracy....

Vehicle regulations.

NARCIS (Netherlands)

2006-01-01

In the Netherlands, all vehicles using public roads must meet so-called permanent requirements. This is enforced by the police and, for some categories, also during the MOT. In the Netherlands, most types of motor vehicle1 can only be introduced to the market if they meet the entry requirements. For

Classifications, applications, and design challenges of drones: A review

Science.gov (United States)

Hassanalian, M.; Abdelkefi, A.

2017-05-01

Nowadays, there is a growing need for flying drones with diverse capabilities for both civilian and military applications. There is also a significant interest in the development of novel drones which can autonomously fly in different environments and locations and can perform various missions. In the past decade, the broad spectrum of applications of these drones has received most attention which led to the invention of various types of drones with different sizes and weights. In this review paper, we identify a novel classification of flying drones that ranges from unmanned air vehicles to smart dusts at both ends of this spectrum, with their new defined applications. Design and fabrication challenges of micro drones, existing methods for increasing their endurance, and various navigation and control approaches are discussed in details. Limitations of the existing drones, proposed solutions for the next generation of drones, and recommendations are also presented and discussed.

Experimental Semiautonomous Vehicle

Science.gov (United States)

Wilcox, Brian H.; Mishkin, Andrew H.; Litwin, Todd E.; Matthies, Larry H.; Cooper, Brian K.; Nguyen, Tam T.; Gat, Erann; Gennery, Donald B.; Firby, Robert J.; Miller, David P.;

Hybrid vehicle control

Science.gov (United States)

Shallvari, Iva; Velnati, Sashidhar; DeGroot, Kenneth P.

2015-07-28

A method and apparatus for heating a catalytic converter's catalyst to an efficient operating temperature in a hybrid electric vehicle when the vehicle is in a charge limited mode such as e.g., the charge depleting mode or when the vehicle's high voltage battery is otherwise charge limited. The method and apparatus determine whether a high voltage battery of the vehicle is incapable of accepting a first amount of charge associated with a first procedure to warm-up the catalyst. If it is determined that the high voltage battery is incapable of accepting the first amount of charge, a second procedure with an acceptable amount of charge is performed to warm-up the catalyst.

Automatic target classification of man-made objects in synthetic aperture radar images using Gabor wavelet and neural network

Science.gov (United States)

Vasuki, Perumal; Roomi, S. Mohamed Mansoor

2013-01-01

Processing of synthetic aperture radar (SAR) images has led to the development of automatic target classification approaches. These approaches help to classify individual and mass military ground vehicles. This work aims to develop an automatic target classification technique to classify military targets like truck/tank/armored car/cannon/bulldozer. The proposed method consists of three stages via preprocessing, feature extraction, and neural network (NN). The first stage removes speckle noise in a SAR image by the identified frost filter and enhances the image by histogram equalization. The second stage uses a Gabor wavelet to extract the image features. The third stage classifies the target by an NN classifier using image features. The proposed work performs better than its counterparts, like K-nearest neighbor (KNN). The proposed work performs better on databases like moving and stationary target acquisition and recognition against the earlier methods by KNN.

A Joint Watermarking and ROI Coding Scheme for Annotating Traffic Surveillance Videos

Directory of Open Access Journals (Sweden)

Su Po-Chyi

2010-01-01

Full Text Available We propose a new application of information hiding by employing the digital watermarking techniques to facilitate the data annotation in traffic surveillance videos. There are two parts in the proposed scheme. The first part is the object-based watermarking, in which the information of each vehicle collected by the intelligent transportation system will be conveyed/stored along with the visual data via information hiding. The scheme is integrated with H.264/AVC, which is assumed to be adopted by the surveillance system, to achieve an efficient implementation. The second part is a Region of Interest (ROI rate control mechanism for encoding traffic surveillance videos, which helps to improve the overall performance. The quality of vehicles in the video will be better preserved and a good rate-distortion performance can be attained. Experimental results show that this potential scheme works well in traffic surveillance videos.

Classification of smooth Fano polytopes

DEFF Research Database (Denmark)

Øbro, Mikkel

A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

A survey of light-vehicle driver education curriculum on sharing the road with heavy vehicles.

Science.gov (United States)

Baker, Stephanie; Schaudt, William A; Freed, J C; Toole, Laura

2012-07-01

Light-vehicle driver education programs that contain content about sharing the road with heavy vehicles may be helpful in reducing future light-vehicle/heavy-vehicle interactions. However, the extent of curricula in the United States including such content is unclear. Researchers developed an online survey targeted at instructors/administrators of state driver education programs to identify curricula addressing heavy vehicles and to determine perceived effectiveness. Ninety-one percent of respondents indicated that the light-vehicle driver education curriculum they teach/administer included a component covering how to safely share the road with heavy vehicles (82% perceived this component to be effective). Although a large proportion of these programs included a component on how to safely share the road with heavy vehicles, participants indicated there may be room for improvement. Participants recommended that future improvements to driver education programs include updated materials and student hands-on experience with heavy vehicles. Copyright © 2012 Elsevier Ltd. All rights reserved.

Depiction of priority light-vehicle pre-crash scenarios for safety applications based on vehicle-to-vehicle communications

Science.gov (United States)

2013-04-30

A template of pre-crash scenarios is presented to depict national crash statistics and kinematic information of time-to-collision for the design of appropriate crash countermeasures based on vehicle-to-vehicle (V2V) communications. This template serv...

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan

2014-09-07

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

2014-01-01

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

Intelligent Vehicle Health Management

Science.gov (United States)

Paris, Deidre E.; Trevino, Luis; Watson, Michael D.

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission

Vehicle Speed Estimation and Forecasting Methods Based on Cellular Floating Vehicle Data

Directory of Open Access Journals (Sweden)

Wei-Kuang Lai

2016-02-01

Full Text Available Traffic information estimation and forecasting methods based on cellular floating vehicle data (CFVD are proposed to analyze the signals (e.g., handovers (HOs, call arrivals (CAs, normal location updates (NLUs and periodic location updates (PLUs from cellular networks. For traffic information estimation, analytic models are proposed to estimate the traffic flow in accordance with the amounts of HOs and NLUs and to estimate the traffic density in accordance with the amounts of CAs and PLUs. Then, the vehicle speeds can be estimated in accordance with the estimated traffic flows and estimated traffic densities. For vehicle speed forecasting, a back-propagation neural network algorithm is considered to predict the future vehicle speed in accordance with the current traffic information (i.e., the estimated vehicle speeds from CFVD. In the experimental environment, this study adopted the practical traffic information (i.e., traffic flow and vehicle speed from Taiwan Area National Freeway Bureau as the input characteristics of the traffic simulation program and referred to the mobile station (MS communication behaviors from Chunghwa Telecom to simulate the traffic information and communication records. The experimental results illustrated that the average accuracy of the vehicle speed forecasting method is 95.72%. Therefore, the proposed methods based on CFVD are suitable for an intelligent transportation system.

Hybrid vehicle potential assessment. Volume 7: Hybrid vehicle review

Science.gov (United States)

Leschly, K. O.

1979-01-01

Review of hybrid vehicles built during the past ten years or planned to be built in the near future is presented. An attempt is made to classify and analyze these vehicles to get an overall picture of their key characteristics. The review includes onroad hybrid passenger cars, trucks, vans, and buses.

Vehicle recovery and towing guideline

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-01-15

This guideline was developed to provide light and medium duty vehicles operators in the oil and gas industry with a set of best practices for avoiding injury and damage during the recovery of stuck vehicles. The aim of the guideline was to increase awareness of safety issues and promote the safe usage of the vehicles by personnel throughout the petroleum industry and to establish minimum standards of practice for vehicle recovery. The guideline included a step-by-step guide for pulling out a vehicle with a recovery strap as well as vehicle-mounted winch procedures. Pre-job checklists for both procedures were provided. Issues related to the strength rating of vehicle tow hooks and hitch receivers were discussed, as well as some of the hazards associated with steep terrains and heavy mud. The guideline also included recommendations for a vehicle recovery kit with instructions on vehicle recovery, a recovery strap, a recovery hitch and shackle, a collapsible shovel, traffic cones and reflector flares, and a heavy blanket and gloves. 7 refs., 2 tabs., 13 figs.

Visiting Vehicle Ground Trajectory Tool

Science.gov (United States)

Hamm, Dustin

2013-01-01

The International Space Station (ISS) Visiting Vehicle Group needed a targeting tool for vehicles that rendezvous with the ISS. The Visiting Vehicle Ground Trajectory targeting tool provides the ability to perform both realtime and planning operations for the Visiting Vehicle Group. This tool provides a highly reconfigurable base, which allows the Visiting Vehicle Group to perform their work. The application is composed of a telemetry processing function, a relative motion function, a targeting function, a vector view, and 2D/3D world map type graphics. The software tool provides the ability to plan a rendezvous trajectory for vehicles that visit the ISS. It models these relative trajectories using planned and realtime data from the vehicle. The tool monitors ongoing rendezvous trajectory relative motion, and ensures visiting vehicles stay within agreed corridors. The software provides the ability to update or re-plan a rendezvous to support contingency operations. Adding new parameters and incorporating them into the system was previously not available on-the-fly. If an unanticipated capability wasn't discovered until the vehicle was flying, there was no way to update things.

Emergency Brake for Tracked Vehicles

Science.gov (United States)

Green, G. L.; Hooper, S. L.

1986-01-01

Caliper brake automatically stops tracked vehicle as vehicle nears end of travel. Bar on vehicle, traveling to right, dislodges block between brake pads. Pads then press against bar, slowing vehicle by friction. Emergencybraking system suitable for elevators, amusement rides and machine tools.

Black carbon concentrations in California vehicles and estimation of in-vehicle diesel exhaust particulate matter exposures

Science.gov (United States)

Fruin, Scott A.; Winer, Arthur M.; Rodes, Charles E.

This research assessed in-vehicle exposures to black carbon (BC) as an indicator of diesel particulate matter (DPM) exposures. Approximately 50 h of real-time Aethalometer BC measurements were made inside vehicles driven on freeway and arterial loops in Los Angeles and Sacramento. Video tapes of the driver's view were transcribed to record the traffic conditions, vehicles followed, and vehicle occupant observations, and these results were tested for their associations with BC concentration. In-vehicle BC concentrations were highest when directly following diesel-powered vehicles, particularly those with low exhaust pipe locations. The lowest BC concentrations were observed while following gasoline-powered passenger cars, on average no different than not following any vehicle. Because diesel vehicles were over-sampled in the field study, results were not representative of real-world driving. To calculate representative exposures, in-vehicle BC concentrations were grouped by the type of vehicle followed, for each road type and congestion level. These groupings were then re-sampled stochastically, in proportion to the fraction of statewide vehicle miles traveled (VMT) under each of those conditions. The approximately 6% of time spent following diesel vehicles led to 23% of the in-vehicle BC exposure, while the remaining exposure was due to elevated roadway BC concentrations. In-vehicle BC exposures averaged 6 μg m -3 in Los Angeles and the Bay Area, the regions with the highest congestion and the majority of the state's VMT. The statewide average in-vehicle BC exposure was 4 μg m -3, corresponding to DPM concentrations of 7-23 μg m -3, depending on the Aethalometer response to elemental carbon (EC) and the EC fraction of the DPM. In-vehicle contributions to overall DPM exposures ranged from approximately 30% to 55% of total DPM exposure on a statewide population basis. Thus, although time spent in vehicles was only 1.5 h day -1 on average, vehicles may be the most

Vehicle Emissions Risk Management

International Nuclear Information System (INIS)

Ibrahem, L.G.

2004-01-01

Vehicle emissions are considered as a main source for air pollution. Emissions regulation is now well developed in most countries to meet cleaner air quality. Reducing emissions by using cleaner fuels, which meet certain specification, is not enough to get cleaner air, yet the vehicle technology is not improved. Here we will outline the following: - development in fuel specification and emissions regulation. main facts linking vehicle emissions, fuel properties and air quality. catalytic converter technology. Emissions sources: In modem cities, vehicle traffic is potentially a major source of emissions. However sometimes other sources of emissions from industry and other stationary sources can be equally important and include emissions that are of greater toxicity than those from vehicles

Energy harvesting water vehicle

KAUST Repository

Singh, Devendra

2018-01-04

An efficient energy harvesting (EEH) water vehicle is disclosed. The base of the EEH water vehicle is fabricated with rolling cylindrical drums that can rotate freely in the same direction of the water medium. The drums reduce the drag at the vehicle-water interface. This reduction in drag corresponds to an increase in speed and/or greater fuel efficiency. The mechanical energy of the rolling cylindrical drums is also transformed into electrical energy using an electricity producing device, such as a dynamo or an alternator. Thus, the efficiency of the vehicle is enhanced in two parallel modes: from the reduction in drag at the vehicle-water interface, and from capturing power from the rotational motion of the drums.

Modeling vehicle emissions in different types of Chinese cities: Importance of vehicle fleet and local features

International Nuclear Information System (INIS)

Huo Hong; Zhang Qiang; He Kebin; Yao Zhiliang; Wang Xintong; Zheng Bo; Streets, David G.; Wang Qidong; Ding Yan

2011-01-01

We propose a method to simulate vehicle emissions in Chinese cities of different sizes and development stages. Twenty two cities are examined in this study. The target year is 2007. Among the cities, the vehicle emission factors were remarkably different (the highest is 50-90% higher than the lowest) owing to their distinct local features and vehicle technology levels, and the major contributors to total vehicle emissions were also different. A substantial increase in vehicle emissions is foreseeable unless stronger measures are implemented because the benefit of current policies can be quickly offset by the vehicle growth. Major efforts should be focused on all cities, especially developing cities where the requirements are lenient. This work aims a better understanding of vehicle emissions in all types of Chinese cities. The proposed method could benefit national emission inventory studies in improving accuracy and help in designing national and local policies for vehicle emission control. - Highlights: → We examine vehicle emissions in 22 Chinese cities of different types and locations. → Vehicle emission factors of the cities differ by 50-90% due to distinct local features. → Each vehicle type contributes differently to total emissions among the cities. → A substantial increase in vehicle emissions in most Chinese cities is foreseeable. → City-specific fleet and local features are important in research and policy making. - Vehicle emission characteristics of Chinese cities are remarkably different, and local features need to be taken into account in vehicle emission studies and control strategy.

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

Electric vehicle demonstration

Energy Technology Data Exchange (ETDEWEB)

Ouellet, M. [National Centre for Advanced Transportation, Saint-Jerome, PQ (Canada)

2010-07-01

The desirable characteristics of Canadian projects that demonstrate vehicle use in real-world operation and the appropriate mechanism to collect and disseminate the monitoring data were discussed in this presentation. The scope of the project was on passenger cars and light duty trucks operating in plug-in electric vehicle (PHEV) or battery electric vehicle modes. The presentation also discussed the funding, stakeholders involved, Canadian travel pattern analysis, regulatory framework, current and recent electric vehicle demonstration projects, and project guidelines. It was concluded that some demonstration project activities may have been duplicated as communication between the proponents was insufficient. It was recommended that data monitoring using automatic data logging with minimum reliance on logbooks and other user entry should be emphasized. figs.

Ontologies vs. Classification Systems

DEFF Research Database (Denmark)

Madsen, Bodil Nistrup; Erdman Thomsen, Hanne