• Journal of Korea Society of Industrial Information Systems
• /
• v.19 no.2
• /
• pp.1-13
• /
• 2014

In IEEE 802.11p/1609-based vehicular networks, vehicles are allowed to exchange safety and control messages only within time periods, called control channel (CCH) interval, which are scheduled periodically. Currently, the length of the CCH interval is set to the fixed value (i.e. 50ms). However, the fixed-length intervals cannot be effective for dynamically changing traffic load. Hence, some protocols have been recently proposed to support variable-length CCH intervals in order to improve channel utilization. In existing protocols, the CCH interval is subdivided into safety and non-safety intervals, and the length of each interval is dynamically adjusted to accommodate the estimated traffic load. However, they do not consider the presence of hidden nodes. Consequently, messages transmitted in each interval are likely to overlap with simultaneous transmissions (i.e. interference) from hidden nodes. Particularly, life-critical safety messages which are exchanged within the safety interval can be unreliably delivered due to such interference, which deteriorates QoS of safety applications such as cooperative collision warning. In this paper, we therefore propose a new interference-aware Dynamic Safety Interval (DSI) protocol. DSI calculates the number of vehicles sharing the channel with the consideration of hidden nodes. The safety interval is derived based on the measured number of vehicles. From simulation study using the ns-2, we verified that DSI outperforms the existing protocols in terms of various metrics such as broadcast delivery ration, collision probability and safety message delay.

• Journal of Bio-Environment Control
• /
• v.4 no.2
• /
• pp.195-202
• /
• 1995

As the pipe houses were constructed by imitation and routine without a structural design by now, they were often destructed by a strong wind or a heavy snowfall. The purpose of this study was to provide the basic data for the safety structural design of the pipe houses in Kyungpook region to prevent meteorological disaster. It was shown that the change of frame interval according to the safety factor under the wind load was similar that under the snow load. But the safety frame interval under the snow load was approximately 0.5-0.6m greater than that under the wind load for equal safety factor. Therefore, it seemed that the maximum safety frame interval was to be decided by the snow load. The frame of the pipe houses in Seungju region was structurally stable under the design snow load in recurrence intervals of 8-15years, but was unstable in Kolyong region.

• Journal of the Korean Society of Safety
• /
• v.10 no.2
• /
• pp.10-16
• /
• 1995

In estimating the fatigue data, only the uniform safety rate has been applied so far However, since more reasonable design concepts such as machine structures or subsidiary materials will be required in the future, the importance of a statistical estimation method for fatigue data is being highlighted. With such basic conception in mind, this study was aimed at critically discussing the interval estimation method which has been applied using the classical statistics thus far It was conceived that this conventional method would result in the estimation of the unstable side from the viewpoint of the likelihood Interval estimation method. In this regard, this study aimed at estimating the fatigue strength through the likelihood interval estimation method comparing it with the conventional interval estimation method would result in the estimation of the unstable side from the viewpoint of the likelihood interval estimation method. One of the methods using the likelihood for estimation data is the Bayes method. Based on this theory, statistical estimations were positivly applied, and thereupon, the fatigue data were estimated.

• Journal of the Korea Safety Management & Science
• /
• v.6 no.1
• /
• pp.61-70
• /
• 2004

In this paper, a group replacement policy based on a failure count is analysed. For a group of identical repairable units, a maintenance policy is performed with two phase considerations: a repair interval phase and a waiting interval phase. Each unit undergoes minimal repair at failure during the repair interval. Beyond the interval, no repair is made until a number of failures. The expected cost rate expressions under the policy is derived. A method to obtain the optimal values of decision variables are explored. Numerical examples are given to demonstrate the results.

• Journal of the Korean Society of Safety
• /
• v.7 no.3
• /
• pp.60-65
• /
• 1992

As many industrial workers have been involved with computer terminal tasks, for example, monitor ing, inspection, or computer da4a entry etc., concerns for difficulty evaluation of computer terminal tasks are Increased. This study provides that eyeblink can be used as a means of difficulty evaluation of a computer terminal lask. Four subjects without color blindness are asked to perform the monitoring task of the binary choice type under five levels of task difficulty. In each task, eyeblink rates and eyeblink interval times were measured from the subjects. The results show that the eyeblink rate does decrease with an Increase in task difficulty. In addition, it was found that both eyeblink interval time and eyeblink Interval time variation increased with an increase in task difficulty. It was concluded that the change of eyeblink rate, eyeblink interval time and eyeblink interval time and eyeblink interval time variation could be regarded as a generalized response to the imposition of task difficulty.

• Proceedings of the Safety Management and Science Conference
• /
• 2012.11a
• /
• pp.461-471
• /
• 2012

Most useful statistical techniques in six sigma DMAIC are hypothesis testing and interval estimation. So this paper reviews and derives sample size formula by considering significance level, power of detectability and effect difference. The quality practioners can effectively interpret the practical and statistical significance with the rational sample sizing.

• Proceedings of the Safety Management and Science Conference
• /
• 2009.04a
• /
• pp.365-370
• /
• 2009

The present study proposes the various hypothesis tests and interval estimations for homogeneous and heterogeneous populations in the continuous and discrete process. These results can be used to complement the QC story 15 steps for quality improvement circle and DMAIC processes for six sigma innovation.

• Nuclear Engineering and Technology
• /
• v.23 no.2
• /
• pp.174-182
• /
• 1991

Effects of human error relevant to the periodic test are incorporated in the evaluations of the unavailability and optimal test interval of a safety system. Two types of possible human error with respect to the test and maintenance are considered. One is the possibility that a good safety system is inadvertently left in a bad state after test（Type A human error) and the other is the possibility that a bad safety system is undetected upon the test（Type B human error). An event tree model is developed for the steady-state unavailability of a safety system in order to determine the effects of human errors on the system unavailability and the optimal test interval. A reliability analysis of the Safety Injection System (SIS) was peformed to evaluate the effects of human error on the SIS unavailability. Results of various sensitivity analyses show that ; (1) the steady-state unavailability of the safety system increases as the probabilities of both types of human error increase and it is far more sensitive to Type A human error, (2) the optimal test interval increases slightly as the probability of Type A human error increases but it decreases as the probability of Type B human error increases, and (3) provided that the test interval of the safety injction pump is kept unchanged, the unavailability of SIS increases significantly as the probability of Type A human error increases but slightly as the probability of Type B human error increases. Therefore, to obtain the realistic result of reliability analysis, one should take shorter test interval (not optimal test interval) so that the unavailability of SIS can be maintained at the same level irrespective of human error. Since Type A human error during test & maintenance influeces greatly on the system unavailability, special efforts to reduce the possibility of Type A human error are essential in the course of test & maintenance.

• Journal of the Korean Society of Safety
• /
• v.30 no.3
• /
• pp.13-19
• /
• 2015

Railway vehicle equipment goes back again to the state just before when failure by the repair. In repairable system, we are interested in the failure interval. As such, a statistical model of the point process, NHPP power law is often used for the reliability analysis of a repairable system. In order to derive a quantitative reliability value of repairable system, we analyze the failure data of the air brake system of the train line 7. The quantitative value is the failure intensity function that was modified, converted into a cost-rate function. Finally we studied the optimal number and optimal interval in which the costs to a minimum consumption point as cost-rate function. The minimum cost point was 194,613 (won/day) during the total life cycle of the braking system, then the optimal interval were 2,251days and the number of optimal preventive maintenance were 7 times. Additionally, we were compared to the cost of a currently fixed interval(4Y) and the optimum interval then the optimal interval is 3,853(won/day) consuming smaller. In addition, judging from the total life, "fixed interval" is smaller than 1,157 days as "optimal interval".

• Korean Journal of Food Science and Technology
• /
• v.38 no.3
• /
• pp.456-459
• /
• 2006

Effects of pork thickness (5 and 7 mm), heating temperature (190 and $220^{\circ}C$) and time (40-180 sec), and flipping interval (10 and 30 sec) during cooking against survival levels of general bacteria and pathogenic microorganisms in pork were investigated. Under same heating temperature and time, 10 sec interval of flipping was more effective in sterilizing bacteria than 30 sec interval. Bacteria was not detected in 5-mm thick pork cooked for 80 sec at $190^{\circ}C$ with 10 sec flipping interval, and 120 sec heating at $190^{\circ}C$ and 30 sec flipping interval. Bacteria were not detected in most 7-mm thick pork cooked for 100 sec at $190^{\circ}C$ with 10 sec flipping interval, and 180 sec heating at $190^{\circ}C$ and 30 sec interval. Bacteria were not detected in most 5- and 7-mm thick pork cooked for 80 sec at $220^{\circ}C$ with 10 sec flipping interval, and 120 sec heating with 30 sec interval.