High versus Low Aggressive Priming During Video Game Training: Effects on Game Violence, State Affect, Heart Rate, and Blood Pressure

Playing violent video games is related to increased negative affect and cardiovascular reactivity. We examined the influence of high and low aggressive priming during video-game training on violence during game play (e.g., shooting, choking), hostility, frustration with game play, blood pressure, and heart rate. Male undergraduates (N = 36) were assigned to a high aggressive or low aggressive video-game priming condition. After training, they played Metal Gear Solid™, which allows players to advance by using stealth, violence, or both. Participants in the high aggressive priming condition used significantly more violent action during game play and reported more hostility than those in the low aggressive priming condition. Heart rate was correlated with feelings of hostility. These findings indicate that both aggressive priming and use of game violence influence arousal and negative affect and might increase behavioral aggression

Automatic video censoring system using deep learning

Due to the extensive use of video-sharing platforms and services, the amount of such all kinds of content on the web has become massive. This abundance of information is a problem controlling the kind of content that may be present in such a video. More than telling if the content is suitable for children and sensitive people or not, figuring it out is also important what parts of it contains such content, for preserving parts that would be discarded in a simple broad analysis. To tackle this problem, a comparison was done for popular image deep learning models: MobileNetV2, Xception model, InceptionV3, VGG16, VGG19, ResNet101 and ResNet50 to seek the one that is most suitable for the required application. Also, a system is developed that would automatically censor inappropriate content such as violent scenes with the help of deep learning. The system uses a transfer learning mechanism using the VGG16 model. The experiments suggested that the model showed excellent performance for the automatic censoring application that could also be used in other similar applications

Validation through finite element simulation of the behaviour of a polyurethane shock absorber under in-service and extreme conditions

ABSTRACT: The safety rules for the construction and installation of lifts, currently in force in Europe, include several requirements concerning the behaviour of the shock absorbers when stopping an elevator. In this paper, a finite element model simulating the behaviour of a cellular polyurethane shock absorber has been developed. The material mechanical behaviour was simulated by means of an elastomeric foam theoretical model, previously calibrated in a former paper. Several in-service and extreme condition scenarios have been analysed with this numerical model, thus verifying the fulfilment of the requirements of the standard

Temperature lapse rate as an adjunct to wind shear detection

Several meteorological parameters were examined to determine if measurable atmospheric conditions can improve windshear detection devices. Lapse rate, the temperature change with altitude, shows promise as being an important parameter in the prediction of severe wind shears. It is easily measured from existing aircraft instrumentation, and it can be important indicator of convective activity including thunderstorms and microbursts. The meteorological theory behind lapse rate measurement is briefly reviewed, and and FAA certified system is described that is currently implemented in the Honeywell Wind Shear Detection and Guidance System

Additive Manufacturing Part Failure Detection

The objective of this project is to create a part failure detection sensor system that will allow Lawrence Livermore National Laboratory to detect cracking during the building process. Due to the time intensive nature of the SLM process, a part that may take 14 days to create could have a defect within the first hour of manufacturing, but the operator would have no idea that there was a fault in the manufacturing until culmination of the process. The proposed system will allow the operator to know when in the process the part became defective, and therefore save resources and machine time. There is currently no solution to this issue, so any progress made by the Cal Poly team will greatly enhance the understanding of the failure modes that occur. In addition to preventing wastage of time and resources, by determining when in the process the failures occur, the engineers and technicians working with this technology will be able to better understand what features of the design are contributing to failure. Since there is currently no diagnostic data available for this process, the engineers working with parts that fail are required to reverse-engineer the causes of any failures, and modify the design based on their analysis. With the results from this project, it will be clear when during the build a failure occurred, therefore easy to tell what the cause of failure was