Creating Geo-specific Road Databases From Aerial Photos For Driving Simulation

Geo-specific road database development is important to a driving simulation system and a very labor intensive process. Road databases for driving simulation need high resolution and accuracy. Even though commercial software is available on the market, a lot of manual work still has to be done when the road crosssectional profile is not uniform. This research deals with geo-specific road databases development, especially for roads with non-uniform cross sections. In this research, the United States Geographical Survey (USGS) road information is used with aerial photos to accurately extract road boundaries, using image segmentation and data compression techniques. Image segmentation plays an important role in extracting road boundary information. There are numerous methods developed for image segmentation. Six methods have been tried for the purpose of road image segmentation. The major problems with road segmentation are due to the large variety of road appearances and the many linear features in roads. A method that does not require a database of sample images is desired. Furthermore, this method should be able to handle the complexity of road appearances. The proposed method for road segmentation is based on the mean-shift clustering algorithm and it yields a high accuracy. In the phase of building road databases and visual databases based on road segmentation results, the Linde-Buzo-Gray (LBG) vector quantization algorithm is used to identify repeatable cross section profiles. In the phase of texture mapping, five major uniform textures are considered - pavement, white marker, yellow marker, concrete and grass. They are automatically mapped to polygons. In the chapter of results, snapshots of road/visual database are presented

An Experimental Study on Attribute Validity of Code Quality Evaluation Model

Regarding the practicality of the quality evaluation model, the lack of quantitative experimental evaluation affects the effective use of the quality model, and also a lack of effective guidance for choosing the model. Aiming at this problem, based on the sensitivity of the quality evaluation model to code defects, a machine learning-based quality evaluation attribute validity verification method is proposed. This method conducts comparative experiments by controlling variables. First, extract the basic metric elements; then, convert them into quality attributes of the software; finally, to verify the quality evaluation model and the effectiveness of medium quality attributes, this paper compares machine learning methods based on quality attributes with those based on text features, and conducts experimental evaluation in two data sets. The result shows that the effectiveness of quality attributes under control variables is better, and leads by 15% in AdaBoostClassifier; when the text feature extraction method is increased to 50 - 150 dimensions, the performance of the text feature in the four machine learning algorithms overtakes the quality attributes; but when the peak is reached, quality attributes are more stable. This also provides a direction for the optimization of the quality model and the use of quality assessment in different situations

Notch1 Pathway Protects against Burn-Induced Myocardial Injury by Repressing Reactive Oxygen Species Production through JAK2/STAT3 Signaling

Oxidative stress plays an important role in burn-induced myocardial injury, but the cellular mechanisms that control reactive oxygen species (ROS) production and scavenging are not fully understood. This study demonstrated that blockade of Notch signaling via knockout of the transcription factor RBP-J or a pharmacological inhibitor aggravated postburn myocardial injury, which manifested as deteriorated serum CK, CK-MB, and LDH levels and increased apoptosis in vitro and in vivo. Interruption of Notch signaling increased intracellular ROS production, and a ROS scavenger reversed the exacerbated myocardial injury after Notch signaling blockade. These results suggest that Notch signaling deficiency aggravated postburn myocardial injury through increased ROS levels. Notch signaling blockade also decreased MnSOD expression in vitro and in vivo. Notably, Notch signaling blockade downregulated p-JAK2 and p-STAT3 expression. Inhibition of JAK2/STAT3 signaling with AG490 markedly decreased MnSOD expression, increased ROS production, and aggravated myocardial injury. AG490 plus GSI exerted no additional effects. These results demonstrate that Notch signaling protects against burn-induced myocardial injury through JAK2/STAT3 signaling, which activates the expression of MnSOD and leads to decreased ROS levels

A photo-triggered and photo-calibrated nitric oxide donor: rational design, spectral characterizations, and biological applications

Nitric oxide (NO) donors are valuable tools to probe the profound implications of NO in health and disease. The elusive nature of NO bio-relevance has largely limited the use of spontaneous NO donors and promoted the development of next generation NO donors, whose NO release is not only stimulated by a trigger, but also readily monitored via a judiciously built-in self-calibration mechanism. Light is without a doubt the most sensitive, versatile and biocompatible method of choice for both triggering and monitoring, for applications in complex biological matrices. Herein, we designed and synthesized an N-nitroso rhodamine derivative (NOD560) as a photo-triggered and photo-calibrated NO donor to address this need. NOD560 is essentially non-fluorescent. Upon irradiation by green light (532nm), it efficiently release NO and a rhodamine dye, the dramatic fluorescence turn-on from which could be harnessed to conveniently monitor the localization, flux, and dose of NO release. The potentials of NOD560 for in vitro biological applications were also exemplified in in vitro biological models, i.e. mesenchymal stem cell (MSC) migration suppression. NOD560 is expected to complement the existing NO donors and find widespread applications in chemical biological studies

The Large High Altitude Air Shower Observatory (LHAASO) Science White Paper

The Large High Altitude Air Shower Observatory (LHAASO) project is a new generation multi-component instrument, to be built at 4410 meters of altitude in the Sichuan province of China, with the aim to study with unprecedented sensitivity the spec trum, the composition and the anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$ eV, as well as to act simultaneously as a wide aperture (one stereoradiant), continuously-operated gamma ray telescope in the energy range between 10$^{11}$ and $10^{15}$ eV. The experiment will be able of continuously surveying the TeV sky for steady and transient sources from 100 GeV to 1 PeV, t hus opening for the first time the 100-1000 TeV range to the direct observations of the high energy cosmic ray sources. In addition, the different observables (electronic, muonic and Cherenkov/fluorescence components) that will be measured in LHAASO will allow to investigate origin, acceleration and propagation of the radiation through a measurement of energy spec trum, elemental composition and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO in cosmic rays physics and gamma astronomy would play a key-role in the comprehensive general program to explore the High Energy Universe. LHAASO will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. In this document we introduce the concept of LHAASO and the main science goals, providing an overview of the project.Comment: This document is a collaborative effort, 185 pages, 110 figure

T2-F: A Comprehensive and Hands-on Undergraduate Course on Cloud Computing

Cloud computing has been widely adopted in the field of software development and deployment. Cloud vendors provide a great variety of services. Currently, the most used cloud vendor, Amazon Web Services, provides fifty-five different services, without mentioning combined services. It is a challenge to cover a representative subset of these services in a class so that it enables students to use cloud computing technologies in school projects as well as in their professional careers. We have recently developed a comprehensive course on cloud computing, the coverage of which is aligned with an industry recognized certificate. Compared with existing cloud computing courses previously presented in the literature, our course is unique in its wide coverage of cloud computing services. In addition, this course is highly hands-on, consisting of eleven labs. In this article, we discuss the course topics, labs, assessment of student performance, student feedback, and instructor observations. Overall, our assessment of the first implementation of the course shows that students performed well, felt they gained a lot from the course, and were overall satisfied with how the course was delivered

Effect Of A Pavement Marking Countermeasure On Improving Signalized Intersection Safety

In this feature, a pavement marking countermeasure is proposed for signalized intersection to assist drivers in making a clear stop/go decision at the onset of the yellow change interval. to test the effectiveness of the countermeasure, a driving simulator expirement was conducted to compare driving behavior at intersections with and without the marking

Effects Of Major-Road Vehicle Speed And Driver Age And Gender On Left-Turn Gap Acceptance

Because the driver\u27s gap-acceptance maneuver is a complex and risky driving behavior, it is a highly concerned topic for traffic safety and operation. Previous studies have mainly focused on the driver\u27s gap acceptance decision itself but did not pay attention to the maneuver process and driving behaviors. Using a driving simulator experiment for left-turn gap acceptance at a stop-controlled intersection, this study evaluated the effects of major traffic speed and driver age and gender on gap acceptance behaviors. The experiment results illustrate relationships among drivers\u27 left-turn gap decision, driver\u27s acceleration rate, steering action, and the influence of the gap-acceptance maneuver on the vehicles in the major traffic stream. The experiment results identified an association between high crash risk and high traffic speed at stop-controlled intersections. The older drivers, especially older female drivers, displayed a conservative driving attitude as a compensation for reduced driving ability, but also showed to be the most vulnerable group for the relatively complex driving maneuvers. © 2007 Elsevier Ltd. All rights reserved

Creating Geo-Specific Road Databases From Aerial Photos For Driving Simulation

Geo-specific road databases are sometimes necessary for driving simulation studies. However, manually creating them is very time consuming. One of the reasons is that a real road can have non-uniform cross sections due to irregular shaped road boundaries. Additionally, in the UCF (University of Central Florida) driving simulator system, the road database format requires identification of repeatable cross sections, also a labor intensive process. Even though some commercial software applications, such as the MultiGen Road Tool have road modeling functions, roads with non-uniform cross-sectional profiles are still hard to model