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1

BAUM, RUDY M. "At A Safe Distance." Chemical & Engineering News 74, no. 47 (November 18, 1996): 3. http://dx.doi.org/10.1021/cen-v074n047.p003.

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2

Hoseini, Seyyed Mohammad Sadat, Mahmmood Fathi, and Manouchehr Vaziri. "Controlling Longitudinal Safe Distance Between Vehicles." PROMET - Traffic&Transportation 21, no. 5 (March 2, 2012): 303–10. http://dx.doi.org/10.7307/ptt.v21i5.245.

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Controlling the safe distances between vehicles on freeways can be used to prevent many accidents. In this research, image-processing techniques have been used to develop an online system that calculates the longitudinal distances between vehicles. This system facilitates controlling safe distances between vehicles without the need for high technology devices. Our approach is real-time and simple, but efficient operations have been used to reduce the image occlusion problem. The main concept of this system is using simple, quick, and effective algorithms for calculating the position of each vehicle in each image. In this way, traffic parameters like speed and distances between vehicles can be calculated for each vehicle in real time. In addition, aggregate parameters like average speed, density, and traffic flow can be calculated using gathered data of single vehicles. As an application of the developed system, controlling the safe distance between vehicles has been introduced. In this system, in case of a driver who does not observe the safe distance, the scene of violation is stored and can be used by the police agencies. KEY WORDS: image processing, traffic, longitudinal safe distance, real time, occlusion
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3

Vickers, John. "Safer, but Not Safe Enough." Journal of Risk and Financial Management 12, no. 3 (September 19, 2019): 152. http://dx.doi.org/10.3390/jrfm12030152.

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The great divide between official analyses and economists’ views of optimal bank equity capital is not as wide as appears at first sight if the economics of risk is properly addressed. Adapting the BoE’s analysis to take account of abnormal risk conditions, a less benign view of the effectiveness of resolution regimes in systemic crisis, an international rather than domestic perspective, and a consistent approach to risk, takes one a good distance towards the economists’ view. The economic rationale for capital levels in the region of Basel III is left looking thin. It looks thinner still when, as now, price-to-book ratios are calling regulatory capital measures into question for some important banks
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4

Lilley, David G. "Minimum Safe Distance from Pool Fires." Journal of Propulsion and Power 16, no. 4 (July 2000): 649–52. http://dx.doi.org/10.2514/2.5623.

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5

Zimbelmann, Jörg, and Conrad Boley. "Underground explosions: estimating the safe distance." Geotechnical Research 3, no. 3 (September 2016): 67–89. http://dx.doi.org/10.1680/jgere.16.00005.

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6

Wicks, Gemma. "Head-up safe stopping distance display." Electronics Education 1997, no. 2 (1997): 37–38. http://dx.doi.org/10.1049/ee.1997.0049.

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7

Qu, Dayi, Xiufeng Chen, Wansan Yang, and Xiaohua Bian. "Modeling of Car-Following Required Safe Distance Based on Molecular Dynamics." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/604023.

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In car-following procedure, some distances are reserved between the vehicles, through which drivers can avoid collisions with vehicles before and after them in the same lane and keep a reasonable clearance with lateral vehicles. This paper investigates characters of vehicle operating safety in car following state based on required safe distance. To tackle this problem, we probe into required safe distance and car-following model using molecular dynamics, covering longitudinal and lateral safe distance. The model was developed and implemented to describe the relationship between longitudinal safe distance and lateral safe distance under the condition where the leader keeps uniform deceleration. The results obtained herein are deemed valuable for car-following theory and microscopic traffic simulation.
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8

Chu, Longjia, and Tien F. Fwa. "Incorporating Braking Distance Evaluation into Pavement Management System for Safe Road Operation." Transportation Research Record: Journal of the Transportation Research Board 2639, no. 1 (January 2017): 119–28. http://dx.doi.org/10.3141/2639-15.

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Maintaining a sufficiently short stopping distance is an important requirement for safe road operation. Stopping sight distances of road sections are decided during the highway alignment and roadway geometric design phase of the road development process. A pavement friction coefficient is used in the calculation of the stopping distances. Since pavement friction coefficient deteriorates with time under traffic action, and the available friction also reduces in wet weather, it is important for pavement maintenance engineers to ensure that sufficient skid resistance is maintained under actual operating conditions so that the stopping distances of road sections are less than the required safe stopping distance. This result requires pavement engineers to monitor regularly the available pavement skid resistance and the corresponding stopping distance of individual road sections. Because skid resistance is an accepted pavement condition to be measured in a pavement management system, it is proposed in this study that braking distance assessment be included as a part of the pavement condition monitoring program of a pavement management system. The proposed procedure consists of two parts: ( a) measurement of skid resistance and evaluation of braking distance and stopping distance and ( b) monitoring of the deterioration trends of individual road sections. The detailed procedure and the analytical tools necessary for the evaluation and prediction of braking and stopping distances, including a finite element skid resistance simulation model, are presented. A numerical example is presented to illustrate the concept and working of the proposed procedure.
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9

Hwang, Kun. "A safe distance between doctor and patient." Archives of Plastic Surgery 47, no. 3 (May 15, 2020): 201–2. http://dx.doi.org/10.5999/aps.2020.00290.

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10

Roberts, William O. "Children and Running: At What Distance Safe?" Clinical Journal of Sport Medicine 15, no. 2 (March 2005): 109–10. http://dx.doi.org/10.1097/01.jsm.0000158290.30642.d8.

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11

Farshchi, Seyyed Mohammad Reza, and Saeed Toosizadeh. "A safe authentication system for distance education." Computer Applications in Engineering Education 22, no. 4 (November 2, 2011): 593–603. http://dx.doi.org/10.1002/cae.20583.

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12

Robins, Kevin, and Mark Terkessidis. "Seeing The World From A Safe Distance." Science as Culture 10, no. 4 (December 2001): 531–39. http://dx.doi.org/10.1080/09505430120093612.

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13

Yoshida, Tomoki, Ichiro Takeuchi, and Masayuki Karasuyama. "Safe Triplet Screening for Distance Metric Learning." Neural Computation 31, no. 12 (December 2019): 2432–91. http://dx.doi.org/10.1162/neco_a_01240.

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Distance metric learning has been widely used to obtain the optimal distance function based on the given training data. We focus on a triplet-based loss function, which imposes a penalty such that a pair of instances in the same class is closer than a pair in different classes. However, the number of possible triplets can be quite large even for a small data set, and this considerably increases the computational cost for metric optimization. In this letter, we propose safe triplet screening that identifies triplets that can be safely removed from the optimization problem without losing the optimality. In comparison with existing safe screening studies, triplet screening is particularly significant because of the huge number of possible triplets and the semidefinite constraint in the optimization problem. We demonstrate and verify the effectiveness of our screening rules by using several benchmark data sets.
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14

Yang, Da, Li-ling Zhu, Dan Yu, Fei Yang, and Yun Pu. "An enhanced safe distance car-following model." Journal of Shanghai Jiaotong University (Science) 19, no. 1 (January 21, 2014): 115–22. http://dx.doi.org/10.1007/s12204-014-1479-5.

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15

Spader, Heather S., Linda Ratanaprasatporn, John F. Morrison, Jonathan A. Grossberg, and G. Rees Cosgrove. "Programmable shunts and headphones: Are they safe together?" Journal of Neurosurgery: Pediatrics 16, no. 4 (October 2015): 402–5. http://dx.doi.org/10.3171/2015.1.peds14400.

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OBJECT Programmable shunts have a valuable role in the treatment of patients with hydrocephalus, but because a magnet is used to change valve settings, interactions with external magnets may reprogram these shunts. Previous studies have demonstrated the ability of magnetic toys and iPads to erroneously reprogram shunts. Headphones are even more ubiquitous, and they contain an electromagnet for sound projection that sits on the head very close to the shunt valve. This study is the first to look at the magnetic field emissions of headphones and their effect on reprogrammable shunt valves to ascertain whether headphones are safe for patients with these shunts to wear. METHODS In this in vitro study of the magnetic properties of headphones and their interactions with 3 different programmable shunts, the authors evaluated Apple earbuds, Beats by Dr. Dre, and Bose QuietComfort Acoustic Noise Cancelling headphones. Each headphone was tested for electromagnetic field emissions using a direct current gaussmeter. The following valves were evaluated: Codman Hakim programmable valve, Medtronic Strata II valve, and Aesculap proGAV. Each valve was tested at distances of 0 to 50 mm (in 5-mm increments) from each headphone. The exposure time at each distance was 1 minute, and 3 trials were performed to confirm results at each valve setting and distance. RESULTS All 3 headphones generated magnetic fields greater than the respective shunt manufacturer's recommended strength of exposure, but these fields did not persist beyond 5 mm. By 2 cm, the fields levels were below 20 G, well below the Medtronic recommendation of 90 G and the Codman recommendation of 80 G. Because the mechanism for the proGAV is different, there is no recommended gauss level. There was no change in gauss-level emissions by the headphones with changes in frequency and amplitude. Both the Strata and Codman-Hakim valves were reprogrammed by direct contact (distance 0 mm) with the Bose headphones. When a rotation component was added, all 3 headphones reprogrammed the Strata and Codman-Hakim valves at 0 mm. At all distances above 0 mm, the headphones did not affect the shunts. The proGAV valve was not affected by headphones at any distance. CONCLUSIONS Although all the headphones studied generated significant gauss fields at distances less than 5 mm, the programmable valve settings only changed at a distance of 0 mm (i.e., with direct contact). Given the subcutaneous location of the valve, the authors conclude that is highly unlikely that commercially available or customary headphones can contribute to the reprogramming of shunts.
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16

Lin, Li-Mei, Shu-Fang Wang, Ru-Ping Lee, Bang-Gee Hsu, Nu-Man Tsai, and Tai-Chu Peng. "Changes in Skin Surface Temperature at An Acupuncture Point with Moxibustion." Acupuncture in Medicine 31, no. 2 (June 2013): 195–201. http://dx.doi.org/10.1136/acupmed-2012-010268.

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Objective This study evaluates the thermographic changes associated with moxa burner moxibustion at the SP6 acupuncture point to establish an appropriate, safe distance of efficacy for moxibustion. Methods Baseline temperature changes using a moxa burner were obtained for a paper substrate at various distances and times, and the tested with volunteers in a pilot study. A single-group trial was then conducted with 36 healthy women to monitor temperature changes on the body surface at the acupuncture point (SP6). Results Based on the temperature changes seen for the paper substrate and in the pilot study, a distance of 3 cm was chosen as the intervention distance. Moxibustion significantly increased the SP6 point skin surface temperature, with a peak increase of 11°C at 4 min (p <0.001). This study also found that during moxibustion the temperature of the moxa burner's rubber layer and moxa cautery were 56.9±0.9°C and 65.8±1.2°C, as compared to baseline values of 35.1°C and 43.8°C (p<0.001). Conclusions We determined 3 cm was a safe distance between the moxa burner and acupuncture point. Moxibustion can increase the skin surface temperature at the SP6 point. This data will aid traditional Chinese medicine (TCM) practitioners in gauging safer treatment distances when using moxibustion treatments.
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17

Gorodokin, V. A., Z. V. Al’metova, V. D. SHepelev, and O. V. Geraskina. "Calculation of safe distance before the maneuver «overtaking»." Herald of the Ural State University of Railway Transport, no. 4 (2018): 18–26. http://dx.doi.org/10.20291/2079-0392-2018-4-18-26.

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18

Safeea, Mohammad, Nuno Mendes, and Pedro Neto. "Minimum Distance Calculation for Safe Human Robot Interaction." Procedia Manufacturing 11 (2017): 99–106. http://dx.doi.org/10.1016/j.promfg.2017.07.157.

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19

Fang, Feng, Yuanli Cai, and Faryar Jabbari. "3D optimal defensive guidance strategy with safe distance." Transactions of the Institute of Measurement and Control 41, no. 15 (June 20, 2019): 4285–300. http://dx.doi.org/10.1177/0142331219856193.

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This work investigates the active defense problem wherein a target aircraft launches a defending missile (i.e. a defender) to intercept an attacking missile in three-dimensional (3D) space. The novelty of this work includes: adding a safe distance for the target, which protects the target from being influenced by defensive interception, and designing a new 3D defensive guidance strategy without linearization to meet different guidance requirements. The defensive guidance strategy combines the approach of analyzing 3D pursuit-evasion engagement and the optimal control to obtain the guidance law. The approach derives the analytical solutions of 3D pursuit-evasion engagement, and a fast algorithm to predict the trajectory of attacking missile is proposed based on these analytical solutions. The advantages of this guidance strategy include incorporation of the added safe distance requirement directly without hindering the ability of the optimal guidance law to meet other requirements, and straight-forward extension for advanced scenarios where multi-defenders intercept the attacking missile simultaneously from different directions. The performance of the 3D defensive guidance law is evaluated via simulations.
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20

Seong, Dong-Su. "Improvement of Safe Return Service using Distance Information." Journal of Digital Contents Society 20, no. 5 (May 31, 2019): 1023–28. http://dx.doi.org/10.9728/dcs.2019.20.5.1023.

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21

Xie, Haibo, Zhengjiang Liu, Xingkang Xu, and Jiping Zhang. "Research on the safe distance between passing ship and offshore drilling platform based on theory and statistics." Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 234, no. 3 (March 4, 2020): 642–50. http://dx.doi.org/10.1177/1475090220902305.

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The offshore drilling platform is the main equipment for oil and gas exploration. The increase in offshore drilling platform results in the apparently increased contradiction between oilfield exploitation and safe navigation of ships. In order to ensure safe navigation and the normal exploitation of oil and gas fields in a limited space, it is necessary to quantify the distance between ships and coastal drilling platforms. In this investigation, the relevant theoretical calculation models were developed, including a drift model for ship out of control and a ship emergency stopping model. By selecting appropriate ship samples, theoretical safe distances under different models can be obtained. With the use of statistical correlation theory based on the Automatic Identification System data of ship, the safe distance between passing ship and platform was further studied. Finally, the recommended safe distance in different waters was summarized by comparing different model calculation results and data statistics results. Research results are beneficial for the safety of ship navigation, safe operation of the platform, and the revision of relevant standards.
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22

Nitek, Stanisław, Leopold Bakoń, Mansoor Sharifi, Maciej Rysz, Lechosław P. Chmielik, and Iwona Sadowska-Krawczenko. "Morphometry of the Orbit in East-European Population Based on Three-Dimensional CT Reconstruction." Advances in Anatomy 2015 (October 29, 2015): 1–10. http://dx.doi.org/10.1155/2015/101438.

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Objectives. To determine safe distances within the orbit outlining reliable operative area on the basis of multislice computed tomography (MSCT) scans. Patients and Methods. MSCT of orbits of 50 Caucasian patients (26 males and 24 females, mean age 56) were analysed. Native scans resolutions were in all cases 0.625 mm. Measurements were done in postprocessing workstation with 2D and 3D reconstructions. The safe distances values were calculated by subtracting three standard deviations from the arithmetical average (X=AVG-3 STD). This method was chosen because this range covers 99.86% of every population. Results. The results of the measurements in men and women, respectively, are as follows (1) distance from optic canal to supraorbital foramen, mean 46,49 mm and 43,29 mm, (2) distance from the optic canal to maxillozygomatic suture at the inferior margin of the orbit mean 45,24 mm and 42,8 mm, (3) distance from the optic canal to frontozygomatic suture 46,15 mm and 43,58 mm, (4) distance from the optic canal to anterior lacrimal crest 40,40 mm and 38,39 mm, (5) distance from superior orbital fissure to the frontozygomatic suture 34,06 mm and 32,62 mm, and (6) distance from supraorbital foramen to the superior orbital fissure 42,32 mm and 39,39 mm. Conclusion. The most probable safe distances calculated by adopted formula were for the superior orbital fissure 23,39–30,58 mm and for the orbital opening of the optic canal 31,9–38,0 mm from the bony structures of the orbital entrance depending on the orbital quadrant.
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23

Lenart, Andrzej S. "Analysis of Collision Threat Parameters and Criteria." Journal of Navigation 68, no. 5 (March 26, 2015): 887–96. http://dx.doi.org/10.1017/s0373463315000223.

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In this paper collision threat parameters such as the distance at closest point of approach and time to the closest point of approach are derived and analysed for special cases and features; collision criteria are analysed for limitations. A new collision threat parameter - time to safe distance - is proposed and its different applications to collision avoidance are presented. Time to safe distance can replace time to the closest point of approach, as it gives a safer time in a dangerous situation. It can be applied in Automatic Radar Plotting Aids (ARPAs) to detect dangerous objects and to display possible evasive manoeuvres.
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Petroski, Henry. "The Distance We've Come." Mechanical Engineering 122, no. 01 (January 1, 2000): 48–53. http://dx.doi.org/10.1115/1.2000-jan-2.

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This article discusses contribution of engineering technologies through years. It is achievements and advances in engineering that changed all. The development of safe drinking water supplies, sanitary sewer systems, and wastewater treatment schemes drastically reduced diseases that were rampant a hundred years ago, and so reduced infant mortality. Mechanical engineering has changed the quality of life significantly from that of a century ago. Air conditioning, which was developed early in the 20th century to control humidity in plants, factories, and mills where manufacturing processes were affected by too damp a sheet of paper or too dry a spool of thread, was widely domesticated in the second half of the century. Air travel is similarly comfortable and even safer, and few of my generation grow anxious even when flying across the country or around the world. The level of engineering accomplishment and dependability embodied in our terrestrial travel seems to be rivalled only by that achieved in space travel, a distinctly 20th-century engineering achievement.
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Kim, Chung Hwan, Eugene Kim, Young Jun Choi, Soo Jung Choi, Joo Hyun Kim, Kyoung Hwan Kim, and Jeong Ho Kang. "Safe Approaching Angle and Distance in Percutaneous Endoscopic Discectomy." Journal of Korean Society of Spine Surgery 11, no. 4 (2004): 210. http://dx.doi.org/10.4184/jkss.2004.11.4.210.

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26

Hsia, Kuo-Hsien, Jia-Hong Cai, Shu-Li Pai, and Evgeni Magid. "Control System for Maintaining Safe Following Distance while Driving." Journal of Robotics, Networking and Artificial Life 5, no. 4 (2019): 261. http://dx.doi.org/10.2991/jrnal.k.190220.012.

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Hsia, Kuo-Hsien, Jia-Hong Cai, Shu-Li Pai, and Evgeni Magid. "Control System for Maintaining Safe Following Distance while Driving." Proceedings of International Conference on Artificial Life and Robotics 24 (January 10, 2019): 49–52. http://dx.doi.org/10.5954/icarob.2019.os1-5.

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28

Jeong, Seungwon, Dongchan Min, Sangyoup Kim, Taeyup Sung, and Jaisung Choi. "Evaluating Safe Passing Sight Distance Criteria Using Reliability Analysis." International Journal of Highway Engineering 22, no. 2 (April 30, 2020): 101–11. http://dx.doi.org/10.7855/ijhe.2020.22.2.101.

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29

Nuszkowski, John, Harlan Smith, Michael McKinney, Nicholas McMahan, Benjamin Wilder, Eric Boehringer, Blair Clarkson, Cutler Littleton, and Kyle Parker. "Increasing the on-road fuel economy by trailing at a safe distance." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 9 (April 30, 2017): 1303–11. http://dx.doi.org/10.1177/0954407017703233.

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Energy is a driving force for automotive applications. Reducing the energy demand of the vehicle is one method of increasing the fuel economy of a vehicle. Heavy-duty commercial vehicles have large frontal areas that provide large amounts of aerodynamic drag at highway speeds. Reducing the aerodynamic drag lowers the engine demand and therefore increases the fuel economy of the vehicle. This study tested the fuel economy and the front air velocity of a 10.7 m box truck trailing another box truck by distances of 3.1 times the truck length, 4.7 times the truck length, and 6.3 times the truck length at a highway speed of 28 m/s. The distance of 6.3 times the vehicle length was considered ‘safe’ for trailing another vehicle, whereas the distances of 3.1 times the truck length and 4.7 times the truck length were not considered safe by the United States Fire Administration. The results showed significant reductions in the air velocity in front of the trailing vehicle of 8.5%, 6.5%, and 3.8% for trailing distances of 3.1 times the vehicle length, 4.7 times the vehicle length, and 6.3 times the vehicle length respectively. The fuel economy of the trailing truck increased significantly by 7.4–8.0%, 8.2–9.0%, and 6.5%–7.7%, for trailing distances of 3.1 times the vehicle length, 4.7 times the vehicle length, and 6.3 times the vehicle length respectively. Based on a road load analysis, these fuel economy improvements indicated a reduction in the drag coefficient of the trailing vehicle of 8–10%. Therefore, a box truck trailing another box truck at a safe distance results in a reduction in the aerodynamics drag and a significant increase in the fuel economy.
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30

Karwowski, W., H. Parsaei, A. Soundararajan, and N. Pongpatanasuegsa. "Estimation of Safe Distance from the Robot Arm as a Guide for Limiting Slow Speed of Robot Motions." Proceedings of the Human Factors Society Annual Meeting 36, no. 13 (October 1992): 992–96. http://dx.doi.org/10.1177/154193129203601315.

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The main objective of this laboratory study was to determine the minimum distance from the robot considered as safe for monitoring purposes, and the corresponding perception of danger for close interaction in robot teaching tasks. Five speed levels of robot motions, i.e.: 10, 20, 30, 40 and 50 cm/sec, were used. The three motion types of the robot arm were forward, swing (from right) and swing (from left), he response variables were the minimum distance from the robot that the subject selected as safe for monitoring purposes, and the perception of danger due to robot speed at the selected safe distances. The subjects selected significantly different values of safe distances from the robot arm moving at the speed of 10 cm/s, than they did for the range of robot speeds from 20 to 40 cm/s. The corresponding perception of danger due to the robot motions at the selected safe distances was the lowest for the speed of 10 cm/s, while the values of perceived danger for the speed range of 20-40 cm/s did not significantly differ between each other. The above results indicate that the range of slow speeds of robot motions from 20 to 40 cm/s is similarly perceived by the subjects with respect to the potential hazards from the moving robot arm. It was suggested that the safe slow speed of robot motions for teaching and programming purposes lies somewhere between 10 and 20 cm/s, and that current recommendation of 25.0 cm/s for safe reduced speed of robot motions should be redefined.
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Wang, Tao, Jing Zhang, Guangyao Li, Keyu Xu, and Shubin Li. "A New Car-Following Model with Consideration of Dynamic Safety Distance." Discrete Dynamics in Nature and Society 2018 (November 12, 2018): 1–5. http://dx.doi.org/10.1155/2018/5326947.

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In the traditional optimal velocity model, safe distance is usually a constant, which, however, is not representative of actual traffic conditions. This paper attempts to study the impact of dynamic safety distance on vehicular stream through a car-following model. Firstly, a new car-following model is proposed, in which the traditional safety distance is replaced by a dynamic term. Then, the phase diagram in the headway, speed, and sensitivity spaces is given to illustrate the impact of a variable safe distance on traffic flow. Finally, numerical methods are conducted to examine the performance of the proposed model with regard to two aspects: compared with the optimal velocity model, the new model can suppress traffic congestion effectively and, for different safety distances, the dynamic safety distance can improve the stability of vehicular stream. Simulation results suggest that the new model is able to enhance traffic flow stability.
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32

Lai, Yong Biao, Meng Shu Wang, and Cheng Uang Bai. "Predicting Model of Safe Distance between Tunnel and Karst Cave." Applied Mechanics and Materials 470 (December 2013): 862–65. http://dx.doi.org/10.4028/www.scientific.net/amm.470.862.

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A method of predicting safe distance between tunnel and karst cave based on support vector machine was proposed, 10 parameters (rock density,elasticity modulusE, poisson ratio, friction angle, cohesionC, lateral pressure coefficient , the karst cave spanL,rate between height and span of the Karst caveR, tunnel deepH,cave position) were chosen for safe distance influence factors, then an intelligent predicting model of safe distance between tunnel and karst cave was built, this predicting model can predict 7 kinds position of safe distance between tunnel and concealed karst cave and was feasible and high prediction precision, which was verified by engineering example.
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Lai, Yong Biao, Meng Shu Wang, and Cheng Guang Bai. "Numerical Simulation Method of Safe Distance between Concealed Karst Cave and Tunnel Based on Energy Catastrophe." Applied Mechanics and Materials 353-356 (August 2013): 1470–74. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.1470.

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Stability of rock stratum between concealed karst cave and tunnel is evaluated by the catastrophe theory. The numerical simulation method of safe distance between concealed karst cave and tunnel is proposed based on catastrophe theory energy catastrophe. Through array of rock stratum energy change and distance change between concealed karst cave and tunnel, a cusp catastrophe model of safe distance between concealed karst cave and tunnel is built. The simulation of safe distance between concealed karst cave and tunnel can be finished by Ansys program and Matlab, and automatically calculates the safe distance by a compile interface program, which is verified by engineering example.
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34

Niu, Qin Yu, and Zhi Chao Cao. "Application Study of the Automotive Active Collision Safety System." Advanced Materials Research 1006-1007 (August 2014): 604–8. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.604.

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This paper introduces the principle of automotive active collision safety protection system. Establish the speed relationship that our car with the car of before and after model for calculating the safe distance. Introducing the visibility, coefficient of road adhesion and other factors. The model of calculating the safe distance closer to the actual driving environment, the model of calculating the safe overcome the existing safety distance model in some special environment the safety distance small or large defects.
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35

Son, Kwang-Hyun, Jae Ho Cho, Jin Woo Lee, Kyu-Sung Kwack, and Seung Hwan Han. "Is the Anterior Tibial Artery Safe During Ankle Arthroscopy?" American Journal of Sports Medicine 39, no. 11 (July 22, 2011): 2452–56. http://dx.doi.org/10.1177/0363546511416317.

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Background: Pseudoaneurysm of the anterior tibial artery (ATA) after ankle arthroscopy is an uncommon complication but can cause unexpected consequences. However, its contributing factor is not fully understood. Hypothesis: Anatomic factors, such as ATA variations and the distance between the ATA and joint capsule, may contribute to the occurrence of pseudoaneurysm. Study Design: Case series; Level of evidence, 4. Methods: The magnetic resonance images and medical records of 358 ankle cases were analyzed. According to locations of the ATA in relation to the peroneus tertius (PT) and the extensor digitorum longus (EDL) tendon on axial magnetic resonance imaging, patients were classified as type 1 (safe type), type 2 (increased risk type), or type 3 (high-risk type). In addition, distances between the anterior joint capsule and the ATA were measured to evaluate the thickness of the anterior fat pad, which contains the ATA and anterior compartment tendons. Results: In 336 cases (93.8%), the ATA was located medial to the EDL (type 1, safe). In 7 cases (2.0%), the ATA was located lateral to the EDL and PT tendon (type 2, increased risk); and in 15 cases (4.2%), the branching artery was observed lateral to the EDL and PT tendon and the ATA was in the normal position (type 3, high risk). The mean distance between the anterior joint capsule and the ATA was 2.3 ± 1.1 mm. Conclusion: In 22 (6.2%) of the 358 cases, the ATA and its branches were located near the anterolateral ankle portal, which introduces the risk of vascular damage during arthroscopic surgery. Furthermore, the mean distance between the ATA and the joint capsule was only 2.3 ± 1.1 mm, and thus the ATA is very close to the anterior working space of the ankle joint. Careful preoperative evaluation and an intra-articular procedure may reduce the risk of vascular complications attributable to ankle arthroscopy.
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36

Lai, Yong Biao, Chun Sheng Qiao, and Chen Guang Bai. "Research of Safe Distance between Concealed Karst Cave and Tunnel." Applied Mechanics and Materials 405-408 (September 2013): 1283–87. http://dx.doi.org/10.4028/www.scientific.net/amm.405-408.1283.

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Based on the catastrophe theory, a research method of safe distance between concealed karst cave and tunnel is put forward. The stability of rock stratum between concealed karst cave and tunnel is evaluated by the catastrophe theory, the catastrophe mode of rock strata system destabilization is established through the research of rock stratum total potential energy between karst cave and tunnel, then the safe distance calculation formula between concealed karst cave and tunnel are deduced, which is veried by an engineering example.
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37

Sadeghi, Javad, and M. Hassan Esmaeili. "Safe distance of cultural and historical buildings from subway lines." Soil Dynamics and Earthquake Engineering 96 (May 2017): 89–103. http://dx.doi.org/10.1016/j.soildyn.2017.02.008.

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38

Wang, Jiange, Xiaoyuan Luo, Wai-Choong Wong, and Xinping Guan. "Specified-Time Vehicular Platoon Control With Flexible Safe Distance Constraint." IEEE Transactions on Vehicular Technology 68, no. 11 (November 2019): 10489–503. http://dx.doi.org/10.1109/tvt.2019.2939558.

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39

HUEY, SPENCER, and JAMES C. NIEH. "Foraging at a safe distance: crab spider effects on pollinators." Ecological Entomology 42, no. 4 (April 4, 2017): 469–76. http://dx.doi.org/10.1111/een.12406.

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40

Kim, Jong-Sung. "A Basic Study on the VTS Operator's Minimum Safe Distance." Journal of the Korean Society of Marine Environment and Safety 19, no. 5 (October 31, 2013): 476–82. http://dx.doi.org/10.7837/kosomes.2013.19.5.476.

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41

King, A. "Keeping A Safe Distance: Individualism and the Less Punitive Public." British Journal of Criminology 48, no. 2 (December 6, 2007): 190–208. http://dx.doi.org/10.1093/bjc/azm069.

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42

Wong, L. T. "Evaluation of Safe Distance of Fire Shutters in Shopping Malls." Architectural Science Review 46, no. 4 (December 2003): 403–9. http://dx.doi.org/10.1080/00038628.2003.9697012.

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43

Salehi, S. D., and M. M. Shokrieh. "Repeated slitting safe distance in the measurement of residual stresses." International Journal of Mechanical Sciences 157-158 (July 2019): 599–608. http://dx.doi.org/10.1016/j.ijmecsci.2019.05.010.

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44

Adell, E., A. Várhelyi, M. Alonso, and J. Plaza. "Developing human–machine interaction components for a driver assistance system for safe speed and safe distance." IET Intelligent Transport Systems 2, no. 1 (2008): 1. http://dx.doi.org/10.1049/iet-its:20070009.

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45

Palatnik de Sousa, Iam, Carlos R. H. Barbosa, and Elisabeth Costa Monteiro. "Safe exposure distances for transcranial magnetic stimulation based on computer simulations." PeerJ 6 (June 18, 2018): e5034. http://dx.doi.org/10.7717/peerj.5034.

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The results of a computer simulation examining the compliance of a given transcranial magnetic stimulation device to the 2010 International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines are presented. The objective was to update the safe distance estimates with the most current safety guidelines, as well as comparing these to values reported in previous publications. The 3D data generated was compared against results available in the literature, regarding the MCB-70 coil by Medtronic. Regarding occupational exposure, safe distances of 1.46 m and 0.96 m are derived from the simulation according to the 2003 and 2010 ICNIRP guidelines, respectively. These values are then compared to safe distances previously reported in other studies.
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46

Singhal, Vivek, Divya Anand, Hani Moaiteq Aljahdali, Nitin Goyal, Aman Singh, and Seifedine Kadry. "An Intelligent and Autonomous Sight Distance Evaluation Framework for Sustainable Transportation." Sustainability 13, no. 16 (August 9, 2021): 8885. http://dx.doi.org/10.3390/su13168885.

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Railways are facing a serious problem of road vehicle–train collisions at unmanned railway level crossings. The purpose of the study is the development of a safe stopping sight distance and sight distance from road to rail track model with appropriate computation and analysis. The scope of the study lies in avoiding road vehicle–train collisions at unmanned railway level crossings. An intelligent and autonomous framework is being developed using supervised machine learning regression algorithms. Further, a sight distance from road to rail track model is being developed for road vehicles of 0.5 to 10 m length using the observed geometric characteristics of the route. The model prediction accuracy obtained better results in the development of a stopping sight distance model in comparison to other intelligent algorithms. The developed model suggested an increment of approximately 23% in the current safe stopping sight distance on all unmanned railway level crossings. Further, the feature analysis indicates the ‘approach road gradient’ to be the major contributing parameter for safe stopping sight distance determination. The accident prediction study finally indicates that, as the safe stopping sight distance is increased by following the developed model, it is predicted to decrease road vehicle–train collisions.
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47

Schwarzbach, Paul, Julia Engelbrecht, Albrecht Michler, Michael Schultz, and Oliver Michler. "Evaluation of Technology-Supported Distance Measuring to Ensure Safe Aircraft Boarding during COVID-19 Pandemic." Sustainability 12, no. 20 (October 21, 2020): 8724. http://dx.doi.org/10.3390/su12208724.

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With the rise of COVID-19, the sustainability of air transport is a major challenge, as there is limited space in aircraft cabins, resulting in a higher risk of virus transmission. In order to detect possible chains of infection, technology-supported apps are used for social distancing. These COVID-19 applications are based on the display of the received signal strength for distance estimation, which is strongly influenced by the spreading environment due to the signal multipath reception. Therefore, we evaluate the applicability of technology-based social distancing methods in an aircraft cabin environment using a radio propagation simulation based on a three-dimensional aircraft model. We demonstrate the susceptibility to errors of the conventional COVID-19 distance estimation, which can lead to large errors in the determination of distances and to the impracticability of traditional tracing approaches during passenger boarding/deboarding. In the context of the future connected cabin, a robust distance measurement must be implemented to ensure safe travel. Finally, our results can be transferred to similar fields of application, e.g., trains or public transport.
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Pan, Deng, and Yingping Zheng. "Dynamic Control of High-speed Train Following Operation." PROMET - Traffic&Transportation 26, no. 4 (August 7, 2014): 291–97. http://dx.doi.org/10.7307/ptt.v26i4.1256.

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Both safety and efficiency should be considered in high-speed train following control. The real-time calculation of dynamic safety following distance is used by the following train to understand the quality of its own following behavior. A new velocity difference control law can help the following train to adjust its own behavior from a safe and efficient steady-following state to another one if the actual following distance is greater than the safe following distance. Meanwhile, the stopping control law would work for collision avoidance when the actual following distance is less than the safe following distance. The simulation shows that the dynamic control of actual inter-train distance can be well accomplished by the behavioral adjustment of the following train, and verifies the effectiveness and feasibility of our presented methods for train following control.
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Krizek, Gerd Christian, Rene Hausleitner, Laura Böhme, and Cristina Olaverri-Monreal. "Empirical Analysis of Safe Distance Calculation by the Stereoscopic Capturing and Processing of Images Through the Tailigator System." Sensors 19, no. 22 (November 19, 2019): 5044. http://dx.doi.org/10.3390/s19225044.

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Driver disregard for the minimum safety distance increases the probability of rear-end collisions. In order to contribute to active safety on the road, we propose in this work a low-cost Forward Collision Warning system that captures and processes images. Using cameras located in the rear section of a leading vehicle, this system serves the purpose of discouraging tailgating behavior from the vehicle driving behind. We perform in this paper the pertinent field tests to assess system performance, focusing on the calculated distance from the processing of images and the error margins in a straight line, as well as in a curve. Based on the evaluation results, the current version of the Tailigator can be used at speeds up to 50 km per hour without any restrictions. The measurements showed similar characteristics both on the straight line and in the curve. At close distances, between 3 and 5 m, the values deviated from the real value. At average distances, around 10 to 15 m, the Tailigator achieved the best results. From distances higher than 20 m, the deviations increased steadily with the distance. We contribute to the state of the art with an innovative low-cost system to identify tailgating behavior and raise awareness, which works independently of the rear vehicle’s communication capabilities or equipment.
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Adell, Emeli, Andras Varhelyi, Mario Dalla Fontana, and Laure Bruel. "Test of HMI Alternatives for Driver Support to Keep Safe Speed and Safe Distance - A Simulator Study." Open Transportation Journal 2, no. 1 (October 30, 2008): 53–64. http://dx.doi.org/10.2174/1874447800802010053.

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