scholarly journals Falling-Point Recognition and Scoring Algorithm in Table Tennis Using Dual-Channel Target Motion Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bo Yang ◽  
Zijian Chang ◽  
Ying Chen
Keyword(s):  
Motion Detection ◽  
High Speed ◽  
Target Motion ◽  
Table Tennis ◽  
Original Image ◽  
Data Set ◽  
Dual Channel ◽  
Sobel Operator ◽  
Multiple Input ◽  
Fully Connected

In table tennis, the ball has numerous characteristics of high speed, small size, and changeable trajectory. Due to these characteristics, the human eye often cannot accurately judge the ball’s movement and position, leading to the problem of precise detection of the ball’s falling point and movement tracking. In sports, the use of machine learning for locating and detecting the ball and the use of deep learning for reconstructing and displaying the ball’s trajectories are considered futuristic technologies. Therefore, this paper proposes a novel algorithm for identifying and scoring points in table tennis based on dual-channel target motion detection. The proposed algorithm consists of multiple input channels to jointly learn different features of table tennis images. The original image is used as the input of the first channel, and then the Sobel operator is used to extract the first-order derivative feature of the original image, which is used as the input of the second channel. The table tennis feature information from the two channels is then fused and sent to the 3D neural network module. The fully connected layer is used to identify the table tennis ball’s drop point, compare it with a standard drop point, calculate the error distance, and give a score. We also constructed a data set and conducted experiments. The experimental results show that the method in this paper is effective in sports.

Factors Affecting Driver Injury Severity in the Wrong-Way Crash: Accounting for Potential Heterogeneity in Means and Variances of Random Parameters

2021 ◽  
pp. 036119812110098
Author(s):  
Miao Yu ◽  
Jinxing Shen ◽  
Changxi Ma
Keyword(s):  
High Speed ◽  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Research Effort ◽  
Random Parameter ◽  
Policy Implications ◽  
Contributing Factors ◽  
Severe Injuries ◽  
Data Set ◽  
Severity Levels

Because of the high percentage of fatalities and severe injuries in wrong-way driving (WWD) crashes, numerous studies have focused on identifying contributing factors to the occurrence of WWD crashes. However, a limited number of research effort has investigated the factors associated with driver injury-severity in WWD crashes. This study intends to bridge the gap using a random parameter logit model with heterogeneity in means and variances approach that can account for the unobserved heterogeneity in the data set. Police-reported crash data collected from 2014 to 2017 in North Carolina are used. Four injury-severity levels are defined: fatal injury, severe injury, possible injury, and no injury. Explanatory variables, including driver characteristics, roadway characteristics, environmental characteristics, and crash characteristics, are used. Estimation results demonstrate that factors, including the involvement of alcohol, rural area, principal arterial, high speed limit (>60 mph), dark-lighted conditions, run-off-road collision, and head-on collision, significantly increase the severity levels in WWD crashes. Several policy implications are designed and recommended based on findings.

A New Dual-Channel Analyzer for Vibration of Rotary Machine

2008 ◽  
Author(s):  
Qing He ◽  
Dongmei Du
Keyword(s):  
Vibration Analysis ◽  
High Speed ◽  
Integral Transform ◽  
Vibration Measurement ◽  
Waveform Analysis ◽  
Rotating Speed ◽  
Rotary Machine ◽  
Vibration Sensors ◽  
Dual Channel ◽  
Channel Analyzer

A new simultaneous sampling and analyzer for dual-channel signal of vibration for rotating machine is developed based on the C8051F060, which is a high-speed SoC system and has two ADCs embedded with high sampling frequency. The signal condition circuits for various vibration sensors are designed, such as charge amplifier, integral transform and rotating speed detector. A colorful TFT LCD used can display all kinds of vibration analysis plots that are friendly in human-machine interface. The large capability non-volatile memory is used to restore up to one hundred of group of vibration waves. With many typical functions of vibration analysis, including waveform analysis, spectrum, orbit and balancing, this instrument is widely applied to vibration measurement and fault diagnosis of machine and equipment, especially for field balancing of rotary machine.

scholarly journals Is Peripheral Motion Detection Affected by Myopia?

2021 ◽  
Vol 15 ◽  
Author(s):  
Junhan Wei ◽  
Deying Kong ◽  
Xi Yu ◽  
Lili Wei ◽  
Yue Xiong ◽  
...  
Keyword(s):  
Visual Field ◽  
Spatial Frequency ◽  
Motion Detection ◽  
High Speed ◽  
Detection Threshold ◽  
High Spatial Frequency ◽  
Spherical Equivalent ◽  
Detection Thresholds ◽  
Significant Difference ◽  
Motion Speed

PurposeThe current study was to investigate whether myopia affected peripheral motion detection and whether the potential effect interacted with spatial frequency, motion speed, or eccentricity.MethodsSeventeen young adults aged 22–26 years participated in the study. They were six low to medium myopes [spherical equivalent refractions −1.0 to −5.0 D (diopter)], five high myopes (<-5.5 D) and six emmetropes (+0.5 to −0.5 D). All myopes were corrected by self-prepared, habitual soft contact lenses. A four-alternative forced-choice task in which the subject was to determine the location of the phase-shifting Gabor from the four quadrants (superior, inferior, nasal, and temporal) of the visual field, was employed. The experiment was blocked by eccentricity (20° and 27°), spatial frequency (0.6, 1.2, 2.4, and 4.0 cycles per degree (c/d) for 20° eccentricity, and 0.6, 1.2, 2.0, and 3.2 c/d for 27° eccentricity), as well as the motion speed [2 and 6 degree per second (d/s)].ResultsMixed-model analysis of variances showed no significant difference in the thresholds of peripheral motion detection between three refractive groups at either 20° (F[2,14] = 0.145, p = 0.866) or 27° (F[2,14] = 0.475, p = 0.632). At 20°, lower motion detection thresholds were associated with higher myopia (p < 0.05) mostly for low spatial frequency and high-speed targets in the nasal and superior quadrants, and for high spatial frequency and high-speed targets in the temporal quadrant in myopic viewers. Whereas at 27°, no significant correlation was found between the spherical equivalent and the peripheral motion detection threshold under all conditions (all p > 0.1). Spatial frequency, speed, and quadrant of the visual field all showed significant effect on the peripheral motion detection threshold.ConclusionThere was no significant difference between the three refractive groups in peripheral motion detection. However, lower motion detection thresholds were associated with higher myopia, mostly for low spatial frequency targets, at 20° in myopic viewers.

scholarly journals Study and Investigation on 5G Technology: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 26
Author(s):  
Ramraj Dangi ◽  
Praveen Lalwani ◽  
Gaurav Choudhary ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Mobile Networks ◽  
High Speed ◽  
Future Research ◽  
Mobile System ◽  
Fifth Generation ◽  
Research Article ◽  
Next Generation Mobile Networks ◽  
Multiple Input ◽  
Multiple Challenges ◽  
Mobile Communication Technology

In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobile networks, 5G provides a high-speed internet facility, anytime, anywhere, for everyone. 5G is slightly different due to its novel features such as interconnecting people, controlling devices, objects, and machines. 5G mobile system will bring diverse levels of performance and capability, which will serve as new user experiences and connect new enterprises. Therefore, it is essential to know where the enterprise can utilize the benefits of 5G. In this research article, it was observed that extensive research and analysis unfolds different aspects, namely, millimeter wave (mmWave), massive multiple-input and multiple-output (Massive-MIMO), small cell, mobile edge computing (MEC), beamforming, different antenna technology, etc. This article’s main aim is to highlight some of the most recent enhancements made towards the 5G mobile system and discuss its future research objectives.

scholarly journals Forensic Engineering Analysis Of Bicycle Versus Pickup Collision

2010 ◽  
Vol 27 (1) ◽  
Author(s):  
Jerry S. Ogden
Keyword(s):  
High Speed ◽  
Engineering Analysis ◽  
Test Procedures ◽  
Data Set ◽  
Vehicle To Vehicle ◽  
Vehicle Collision ◽  
Vehicle Impact ◽  
General Test ◽  
Forensic Engineering ◽  
A Minor

The Forensic Engineering Analysis Of Bicycle-Vehicle Incidents Presents Its Own Unique Set Of Challenges. Often, The Forensic Engineer Is Faced With A Limited Data Set For Determining Vehicle Impact Speed From The Physical Evidence Produced By A Bicycle Collision With An Automobile, Which May Not Be Of Issue For A Vehicle-To-Vehicle Collision At Similar Speeds. This Paper Analyzes A Collision Between A Light Duty Pickup Pulling A Tandem Axle Utility Trailer And A Bicycle Ridden By A Minor Child. There Were Allegations That The Pickup Was Traveling At A High Speed Above The Speed Limit, As Well As Passing Another Vehicle At The Time Of The Incident. In Order To Accurately And Dependably Determine The Speed Of The Ford F350 Pickup Involved In This Incident Event, This Forensic Engineer Elected To Recreate The Vehicle Locked Wheel Skidding Evidence That Was Produced During The Incident Event And Photographically Recorded By Police Investigators. The Dynamic Skid Testing Technique, Test Equipment, And General Test Procedures Used To Accurately Determine Vehicle Speeds For This Incident Event, And How It Can Be Applied To Similar Collision Events Are Discussed In This Paper

scholarly journals Context-Aware Driver’s Behaviour Monitoring System in Vehicular Ad-Hoc Network

2021 ◽  
Vol 10 (2) ◽  
pp. 701-709
Keyword(s):  
Monitoring System ◽  
Ad Hoc Network ◽  
High Speed ◽  
Ad Hoc ◽  
Detection System ◽  
Vehicular Ad Hoc Network ◽  
Context Aware ◽  
Road Accidents ◽  
Road Transportation ◽  
Data Set

The number of deaths resulting from road accidents and mishaps has increased at an alarming rate over the years. Road transportation is the most popularly used means of transportation in developing countries like Nigeria and most of these road accidents are associated with reckless driving habits. Context-aware systems provide intelligent recommendations allowing digital devices to make correct and timely recommendations when required. Furthermore, in a Vehicular Ad-hoc Network (VANET), communication links between vehicles and roadside units are improved thus enabling vehicle and road safety. Hence, a non-intrusive driver behaviour detection system that incorporates context-aware monitoring features in VANET is proposed in this study. By making use of a one-dimensional highway (1D) road with one-way traffic movement and incorporating GSM technology, irregular actions (high speed, alcohol while driving, and pressure) exhibited by drivers are monitored and alerts are sent to other nearby vehicles and roadside units to avoid accidents. The proposed system adopted a real-time VANET prototype with three entities involved in the context-aware driver’s behaviour monitoring system namely, the driver, vehicle, and environment. The analytical tests with actual data set indicate that, when detected, the model measures the pace of the vehicle, the level of alcohol in the breath, and the driver's heart rate in-breath per minute (BPM). Therefore, it can be used as an appropriate model for the Context-aware driver’s monitoring system in VANET.

scholarly journals A Contrast Calibration Protocol for X-ray Speckle Visibility Spectroscopy

2021 ◽  
Vol 11 (21) ◽  
pp. 10041
Author(s):  
Yanwen Sun ◽  
Vincent Esposito ◽  
Philip Adam Hart ◽  
Conny Hansson ◽  
Haoyuan Li ◽  
...  
Keyword(s):  
High Speed ◽  
Coherent Scattering ◽  
Atomic Scale ◽  
Photon Statistics ◽  
Free Electron Lasers ◽  
Data Set ◽  
X Ray ◽  
Charge Cloud ◽  
Typical Experiment ◽  
Calibration Protocol

X-ray free electron lasers, with their ultrashort highly coherent pulses, opened up the opportunity of probing ultrafast nano- and atomic-scale dynamics in amorphous and disordered material systems via speckle visibility spectroscopy. However, the anticipated count rate in a typical experiment is usually low. Therefore, visibility needs to be extracted via photon statistics analysis, i.e., by estimating the probabilities of multiple photons per pixel events using pixelated detectors. Considering the realistic X-ray detector responses including charge cloud sharing between pixels, pixel readout noise, and gain non-uniformity, speckle visibility extraction relying on photon assignment algorithms are often computationally demanding and suffer from systematic errors. In this paper, we present a systematic study of the commonly-used algorithms by applying them to an experimental data set containing small-angle coherent scattering with visibility levels ranging from below 1% to ∼60%. We also propose a contrast calibration protocol and show that a computationally lightweight algorithm can be implemented for high-speed correlation evaluation.

scholarly journals Artificial intelligence method to classify ophthalmic emergency severity based on symptoms: a validation study

BMJ Open ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. e037161
Author(s):  
Hyunmin Ahn
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Model Performance ◽  
Armed Forces ◽  
Validation Data ◽  
Data Set ◽  
Orange Yellow ◽  
Hospital Visits ◽  
Input Variables ◽  
Fully Connected

ObjectivesWe investigated the usefulness of machine learning artificial intelligence (AI) in classifying the severity of ophthalmic emergency for timely hospital visits.Study designThis retrospective study analysed the patients who first visited the Armed Forces Daegu Hospital between May and December 2019. General patient information, events and symptoms were input variables. Events, symptoms, diagnoses and treatments were output variables. The output variables were classified into four classes (red, orange, yellow and green, indicating immediate to no emergency cases). About 200 cases of the class-balanced validation data set were randomly selected before all training procedures. An ensemble AI model using combinations of fully connected neural networks with the synthetic minority oversampling technique algorithm was adopted.ParticipantsA total of 1681 patients were included.Major outcomesModel performance was evaluated using accuracy, precision, recall and F1 scores.ResultsThe accuracy of the model was 99.05%. The precision of each class (red, orange, yellow and green) was 100%, 98.10%, 92.73% and 100%. The recalls of each class were 100%, 100%, 98.08% and 95.33%. The F1 scores of each class were 100%, 99.04%, 95.33% and 96.00%.ConclusionsWe provided support for an AI method to classify ophthalmic emergency severity based on symptoms.

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