• Journal of Korean Neurosurgical Society
• /
• v.61 no.6
• /
• pp.731-736
• /
• 2018

Objective : Ultrasonography (US) is the most non-invasive, safe, and, especially in the period of infancy, best method for visualizing and examining the spinal cord. Furthermore, US is the primary work-up for development of the spinal canal, and for follow-up on issues relating to subcutaneous tissues, bone development, and the spinal cord. Conus medullaris terminates at the second lumbar vertebra, according to a consensus in the literature. Methods : Healthy children under the age of 6 months who were admitted to the radiology clinic for routine USG follow-ups between the dates of March 2012 to December 2014 were included in this study. Results : Our study includes data from 1125 lumbosacral ultrasounds. The terminal point of the conus level of the attended infants, superior, middle part, inferior of the vertebrae L1, L2, and L3. Furthermore, the termination of the discal distance ratio did not differ significantly between genders. Conclusion : Therefore, according to our results, gender is not an influencing factor in the termination of the spinal cord. Based on the study we performed, as well as the previous literature, in infants without a recognized spinal pathology, the spinal cord is detected below the vertebra L3.

• Structural Engineering and Mechanics
• /
• v.61 no.3
• /
• pp.347-357
• /
• 2017

The applications of active control is being more popular nowadays. Several control algorithms have been developed to determine optimum control force. In this paper, a Chaotic Particle Swarm Optimization (CPSO) technique, based on Logistic map, is used to compute the optimum control force of active tendon system. A chaotic exploration is used to search the solution space for optimum control force. The response control of Multi-Degree of Freedom (MDOF) shear buildings, equipped with active tendons, is introduced as an optimization problem, based on Instantaneous Optimal Active Control algorithm. Three MDOFs are simulated in this paper. Two examples out of three, which have been previously controlled using Lattice type Probabilistic Neural Network (LPNN) and Block Pulse Functions (BPFs), are taken from prior works in order to compare the efficiency of the current method. In the present study, a maximum allowable value of control force is added to the original problem. Later, a twenty-story shear building, as the third and more realistic example, is considered and controlled. Besides, the required Central Processing Unit (CPU) time of CPSO control algorithm is investigated. Although the CPU time of LPNN and BPFs methods of prior works is not available, the results show that a full state measurement is necessary, especially when there are more than three control devices. The results show that CPSO algorithm has a good performance, especially in the presence of the cut-off limit of tendon force; therefore, can widely be used in the field of optimum active control of actual buildings.