scholarly journals In-Season Nutrition Strategies and Recovery Modalities to Enhance Recovery for Basketball Players: A Narrative Review

2021 ◽  
Author(s):  
Jon K. Davis ◽  
Sara Y. Oikawa ◽  
Shona Halson ◽  
Jessica Stephens ◽  
Shane O’Riordan ◽  
...  
Keyword(s):  
Future Research ◽  
Time Variability ◽  
Night Time ◽  
Basketball Players ◽  
Compression Garments ◽  
Practical Applications ◽  
Wake Time ◽  
The Road ◽  
Multiple Challenges ◽  
On The Road

AbstractBasketball players face multiple challenges to in-season recovery. The purpose of this article is to review the literature on recovery modalities and nutritional strategies for basketball players and practical applications that can be incorporated throughout the season at various levels of competition. Sleep, protein, carbohydrate, and fluids should be the foundational components emphasized throughout the season for home and away games to promote recovery. Travel, whether by air or bus, poses nutritional and sleep challenges, therefore teams should be strategic about packing snacks and fluid options while on the road. Practitioners should also plan for meals at hotels and during air travel for their players. Basketball players should aim for a minimum of 8 h of sleep per night and be encouraged to get extra sleep during congested schedules since back-to back games, high workloads, and travel may negatively influence night-time sleep. Regular sleep monitoring, education, and feedback may aid in optimizing sleep in basketball players. In addition, incorporating consistent training times may be beneficial to reduce bed and wake time variability. Hydrotherapy, compression garments, and massage may also provide an effective recovery modality to incorporate post-competition. Future research, however, is warranted to understand the influence these modalities have on enhancing recovery in basketball players. Overall, a strategic well-rounded approach, encompassing both nutrition and recovery modality strategies, should be carefully considered and implemented with teams to support basketball players’ recovery for training and competition throughout the season.

scholarly journals A NEW APPROACH TO HIGHWAY LANE DETECTION BY USING HOUGH TRANSFORM TECHNIQUE

2017 ◽  
Author(s):  
Nur Shazwani Aminuddin ◽  
Masrullizam Mat Ibrahim ◽  
Nursabillilah Mohd Ali ◽  
Syafeeza Ahmad Radzi ◽  
Wira Hidayat Mohd Saad ◽  
...  
Keyword(s):  
Hough Transform ◽  
Average Rate ◽  
Lane Detection ◽  
Frame Rate ◽  
Video Frame ◽  
Night Time ◽  
The Road ◽  
Main Technique ◽  
On The Road ◽  
Width Measurements

This paper presents the development of a road lane detection algorithm using image processing techniques. This algorithm is developed based on dynamic videos, which are recorded using on-board cameras installed in vehicles for Malaysian highway conditions. The recorded videos are dynamic scenes of the background and the foreground, in which the detection of the objects, presence on the road area such as vehicles and road signs are more challenging caused by interference from background elements such as buildings, trees, road dividers and other related elements or objects. Thus, this algorithm aims to detect the road lanes for three significant parameter operations; vanishing point detection, road width measurements, and Region of Interest (ROI) of the road area, for detection purposes. The techniques used in the algorithm are image enhancement and edges extraction by Sobel filter, and the main technique for lane detection is a Hough Transform. The performance of the algorithm is tested and validated by using three videos of highway scenes in Malaysia with normal weather conditions, raining and a night-time scene, and an additional scene of a sunny rural road area. The video frame rate is 30fps with dimensions of 720p (1280x720) HD pixels. In the final achievement analysis, the test result shows a true positive rate, a TP lane detection  average rate of 0.925 and the capability to be used in the final application implementation.  

On the Road to Ephesus

2015 ◽  
pp. 102-125
Author(s):  
Suzanne Roff-Wexler
Keyword(s):  
Big Data ◽  
Future Research ◽  
Review Of Literature ◽  
Healthcare Organizations ◽  
Research Directions ◽  
The Road ◽  
Future Research Directions ◽  
On The Road ◽  
Definition Of

Following a brief review of literature on big data as well as wisdom, this chapter provides a definition of data-based wisdom in the context of healthcare organizations and their visions. The author addresses barriers and ways to overcome barriers to data-based wisdom. Insights from interviews with leading healthcare professionals add practical meaning to the discussion. Finally, future research directions and questions are suggested, including the role of synchronicity and serendipity in data-based wisdom. In this chapter, developing data-based wisdom systems that flourish Wisdom, Virtue, Intellect, and Knowledge are encouraged.

On the Road to Ephesus

Big Data ◽  
2016 ◽  
pp. 2275-2299
Author(s):  
Suzanne Roff-Wexler
Keyword(s):  
Big Data ◽  
Future Research ◽  
Review Of Literature ◽  
Healthcare Organizations ◽  
Research Directions ◽  
The Road ◽  
Future Research Directions ◽  
On The Road ◽  
Definition Of

Following a brief review of literature on big data as well as wisdom, this chapter provides a definition of data-based wisdom in the context of healthcare organizations and their visions. The author addresses barriers and ways to overcome barriers to data-based wisdom. Insights from interviews with leading healthcare professionals add practical meaning to the discussion. Finally, future research directions and questions are suggested, including the role of synchronicity and serendipity in data-based wisdom. In this chapter, developing data-based wisdom systems that flourish Wisdom, Virtue, Intellect, and Knowledge are encouraged.

Current and Future Research Activities in Driver Training

1977 ◽  
Vol 21 (6) ◽  
pp. 482-484
Author(s):  
Robert M. Nicholson ◽  
Michael F. Smith
Keyword(s):  
Future Research ◽  
Safety Education ◽  
Driver Education ◽  
Driver Training ◽  
The Road ◽  
Elderly Driver ◽  
Research Activities ◽  
Driver Performance ◽  
Pros And Cons ◽  
On The Road

Research programs involving high school driver education, motorcyclist safety education, problem driver retraining, elderly driver retraining, handicapped driver training, commercial vehicle driver training, and an energy efficient driver training program are summarized. Some of the pros and cons of driver education are presented and problems with establishing valid on-the-road driver performance tests are discussed.

scholarly journals Computer Games as Learning Tool towards Children Road Safety Education

2018 ◽  
Vol 7 (4.15) ◽  
pp. 230
Author(s):  
Masnida Hussin ◽  
Nor Hanis Mohd Fouzi
Keyword(s):  
Computer Games ◽  
Road Safety ◽  
Road Traffic ◽  
Primary School Children ◽  
Future Research ◽  
Large Sample Size ◽  
Learning Tool ◽  
The Road ◽  
Safety Awareness ◽  
On The Road

Road safety awareness is one of the many awareness programs that are often highlighted and discussed around the world. The road accident statistics are increased due to the lack of exposure and awareness among communities about traffic environments and rules. Children are one of the most vulnerable populations involved in traffic accidents. The children are unable to familiarize themselves with the surroundings, especially when crossing the road. This research attempts to improve road-safety awareness among children by using computer games as a learning tool. Specifically, it determines the progress of knowledge on the road rules and conditions after the children using the tool. The computer online game is suitable methods to use for teaching them on road safety due to interactive application always intimate the children. Besides the survey questions that related to road traffic rules, we also measures the attitude towards road safety in the participant (i.e., children and adult). Descriptive analysis in frequency, mean, and percentage are used to describe the respondent’s information. Statistical Package for Social Science (SPSS) is used to analyze the findings. The overall findings show that all respondents have positive feedback on online games as a road safety tool. Interestingly, the significant output shows on the different knowledge about road safety when the children are analyzed for before and after they played the games. The future research is suggested to study the other group of participant as the respondent in this work is limited to the primary school children. It can be improved by involving the large sample size and wider location.                                                                                                                                           

The Influence of Driver Expectation when Recognizing Lighted Targets at Nighttime

2016 ◽  
Vol 60 (1) ◽  
pp. 489-493 ◽  
Author(s):  
Jeffrey W. Muttart ◽  
Swaroop Dinakar ◽  
Gregory Vandenberg ◽  
Michael Yosko
Keyword(s):  
Information Theory ◽  
Light Source ◽  
Search Model ◽  
Theory Approach ◽  
Night Time ◽  
The Road ◽  
Driving Scenario ◽  
The Difference ◽  
On The Road

Over the years, in a night time driving scenario, expectancy has been linked with faster night time recognition. This study tries to evaluate the ability of observers to identify illuminated objects on the road in the absence of an associative pattern. In this study 47 of 60 participants did not respond to a light source that was in the drivers’ travel lane ahead. Of those who did not respond to the light when directly ahead, 64% indicated that had seen it beforehand. When the light was 2 meters to the drivers’ right, 33% that saw the light failed to respond. All of the drivers who saw the light before striking it claimed that they thought it was off the road until too late. When the drivers did not know what the light source was, they could not decipher where the light was. However, once aware of the presence of the light the average recognition distance improved 192 meters (632 feet) with 100% recognition. These results fit well with the SEEV search model and an Information Theory approach to driver expectancy. Previous claims that the difference between expected and unexpected driver responses is a 2 to 1 ratio was not supported by this research.

scholarly journals A Study on Building a “Real-Time Vehicle Accident and Road Obstacle Notification Model” Using AI CCTV

2021 ◽  
Vol 11 (17) ◽  
pp. 8210
Author(s):  
Chaeyoung Lee ◽  
Hyomin Kim ◽  
Sejong Oh ◽  
Illchul Doo
Keyword(s):  
Deep Learning ◽  
Traffic Safety ◽  
Research Direction ◽  
Detection Algorithm ◽  
Obstacle Detection ◽  
Video Data ◽  
Future Research ◽  
The Road ◽  
Detection Model ◽  
On The Road

This research produced a model that detects abnormal phenomena on the road, based on deep learning, and proposes a service that can prevent accidents because of other cars and traffic congestion. After extracting accident images based on traffic accident video data by using FFmpeg for model production, car collision types are classified, and only the head-on collision types are processed by using the deep learning object-detection algorithm YOLO (You Only Look Once). Using the car accident detection model that we built and the provided road obstacle-detection model, we programmed, for when the model detects abnormalities on the road, warning notification and photos that captures the accidents or obstacles, which are then transferred to the application. The proposed service was verified through application notification simulations and virtual experiments using CCTVs in Daegu, Busan, and Gwangju. By providing services, the goal is to improve traffic safety and achieve the development of a self-driving vehicle sector. As a future research direction, it is suggested that an efficient CCTV control system be introduced for the transportation environment.

Driving Performance as a Function of Time on the Road

1987 ◽  
Vol 31 (7) ◽  
pp. 766-769
Author(s):  
Thomas A. Ranney ◽  
Valerie J. Gawron
Keyword(s):  
Reaction Time ◽  
Driving Simulator ◽  
Lateral Acceleration ◽  
Time Variability ◽  
Reaction Time Variability ◽  
The Road ◽  
Driving Time ◽  
On The Road ◽  
Instrumented Vehicle ◽  
Fatigue Driving

The effects of driving time were examined in two experiments, both involving two-hour drives. Experiment 1 used a fully instrumented vehicle on a closed course under nighttime conditions. Experiment 2 used an interactive driving simulator. In Experiment 1 effects of driving time were increases in the frequency of right-side lane departures, decreased speed, and increased speed variability, all consistent with decreased arousal associated with fatigue. Driving time effects in Experiment 2 included increased reaction time and reaction-time variability to signs as well increases in speed, lateral acceleration and in overall performance as reflected in pay, indicating compensation for the effects of fatigue. Differences between the experiments were examined as possible explanations for differences in results.

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