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Genetic Algorithms have been successfully applied to various problems (for example, engineering design problems with a mix of continuous, integer and discrete design variables) that could not have been readily solved with traditional computational techniques. But, several problems for which conventional Genetic Algorithms are ill defined are premature convergence of solution and application of exterior penalty function. Therefore, we developed an Improved Genetic Algorithms(IGAs) to solve above two problems. As a case study, IGAs is applied to several nonlinear optimization problems and it is proved that this algorithm is very useful and efficient in comparison with traditional methods and conventional Genetic Algorithm.
The purpose of this study was to analyze kinematics variables on basic information for the improving the skill of balance attitude with understanding principle and development of balance attitude. For this study, national champion skilled 4 female rhythmic sport gymnastics were selected as subjects, and 3-demensional coordinates computation was used to DLT(Direct Linear Transformation) method of Walton(1981). 1. As for each phase performance time, all subjects are mo difference from phase 1 to phase 3, but phase 4 must stop attitude almost 0.433sec like as JEJ, CYR. To phase 5, during right leg gather, performance time act 0.267sec like as JEJ. 2. To displacement of COP, phase 1 is resulted lowest, and in phase 2, phase 3, phase 4 order to be high. And phase 5 is resulted again to be low. 3. To angle displacement of left heel , phase 1 is prepare position, and phase 2 is high, from phase 3 to phase 4 is resulted average 75.0. JEJ is resulted very ideal position to 85.5˚ 4. To angle displacement of right knee, phase 1 is prepare position, and phase 2 is resulted generally knee angle to be small, and phase 3 and phase 4 is resulted maximal extension to knee angle. CEJ is resulted ideal position from phase 2 to phase 5. To angle displacement of left knee, phase 1 is prepare position, and phase 2 is that support left leg and knee deep flexion during rising left leg to horizontal plane, phase 3 is extended maximal angle during maximal extension to knee angle of left support leg, phase 4 is decreased knee angle when right left is maximal rising and then resulted little power of supporting leg. But LNY is resulted very ideal left knee angle. 5. To displacement of hip joint angle, phase 1 is prepare position, and phase 2 is reduce angle during rising right leg to horizontal plane as hop joint is resulted by complex. When knee angle of left support leg is maximal extension to phase 3 and right leg is rising maximal to phase 4, the grater this angle magnitude to hip joint and then physical position straightly resulted. CEJ is that phase 4 is resulted 116.6˚ 6. To right toe velocity, toe velocity is very fast during right leg is down. Phase 1 is prepare position, and phase 2 is fast toe velocity during rising right leg to horizontal plane, phase 3 and phase 4 is resulted stop attitude to slow toe velocity. To summarize above, for fast right foot performance, accurate stop attitude and hip joint little complex, I think that performed very ideal position and effective motion as a lot of flexibility exercise training.
The Optimization problem is to select the best of many possible design alternatives in a complex design space. Genetic Algorithms, one of numerous techniques to search optimal solution, have been successfully applied to various problem(for example, parameter tuning in expert system, structural systems with a mix of continuous integer and discrete design variables) that could not have been readily solved with more conventional computational techniques, But, Conventional Genetic Algorithms are ill defined for two classes of problems ie, parameter convergence and penalty function. Therefore, this paper developed Revised Algorithms to solve these problems, As a case study, sin function example and design of gear train are demonstrated to show the effectiveness of The two Revised Genetic Algorithms(R. G. A & H. G. A.) and one of the Revised Genetic Algorithms was more effectiveness. That's H. G. A. It has robustness and problem-independent characteristics. In the reproduction step of the H. G. A. the roulette wheel method is replaced the random search and the creeping value method is modified to improve local optimum solutions in the mutation step. The encoding and decoding procedures are replaced with the real number representation method in the H. G. A.
This study serves the purpose of understanding the principles of kicking moves through kinematics analysis on elite sports aerobic athletes making the movement of high kicking. The study also intends to not only help instructors and coaches understand the accurate move of high kick and make a better judgement for athletes but also lay a basic resource for them to rely on. To accomplish all this, the time span of the each phase, the displacement of COG, the velocity of left/right forefoot, the angle displacement of left/right hip joint and the angle displacement of left/right ankle joint have been studied. The conclusions were as follows; 1. It took less time at phase 3(0.40sec) and phase 5(0.40sec) of returning the leg than at phase 2(0.56sec) and phase 4(0.43sec) of kicking up. 2. The displacement of COG was low at phase 1, 3, 5(103.02±5.70, 95.33±2.45, 96.66±3.20 cm) and high at phase 2(111.18±9.97) and phase 4 (111.61±5.62 cm). 3. About the velocity of left/right forefoot, kicking up the right foot was faster than returning it at phase 1-2(1081.63±40.62an/sec) and phase 2-3(992.92±45.68 cm/sec). With the left foot, kicking up was faster than returning at phase 3-4(1116.25±63.46cm/sec) and phase 4-5(1043.63±40.62cm/ sec). 4. The left and right angle displacement of hip joint showed the maximum extension at phase 1(174.4±52.36, 162.6±05.40deg/sec), phase 3 (170.66±5.94, 165.89±4.36deg/sec), phase 5(166.18±4.83, 157.05±3.59deg/sec), phase 2(26.19±5.40deg/sec) showed the minimum angle of the right angle and phase 4(27.67±5.31deg/sec) showed the minimum of the left angle. 5. In the left and right angle displacement of knee joint, the angle displacement on the right knee joint showed the maximum extension at phase 1, 2, 3, 4(169.10±2.96, 169.91±6.20, 153.14±6.32, 162.11deg/sec) and flexion at phase 3(140.45±10.37deg/sec). The left knee joint showed the maximum extension at phase 1, 3, 4, 5(169.15±4.25, 157.99±10.82, 172.14±3.06, 168.72deg/sec) and flexion at phase 2(148.17±9.64deg/sec). 6. The angle displacement on the right ankle joint showed flexion at phase 1, 3, 4, 5(125.15±4.81, 101.66+2.80, 102.88±8.89, 106.27±5.76deg/sec) and the maximum extension at phase 2(152.22±5.18deg/sec) The left ankle joint showed flexion at phase 1, 2, 3, 5(104.90±48.10, 116.06±15.84, 106.55±8.84, 118.79±6.89deg/sec) and showed the maximum extension at phase 4(153.57 ±4.65deg/ sec).
In this research, We were selected 10 students from Physical Education at the H University in Seoul through random sampling and by group they had no physical defects. We were compared them mutually through mechanical analysis according to muscular contraction type in the stretch-shortening cycle and shortening-stretch cycle in concentric and eccentric contractions. To investigate their differences, We were performed armcurl motion analysis. As a result, We were derived conclusions as follows. As for the maximum momentum of total segments that is a kinetic variable, that of SSC was higher by DM 0.06kg · m/sec. and by DM 0.97J in the mechanical energy of the total segments; and by DM 22.20N at the maximum power than that of CC. In the analysis of integral electromyography that is avariable of analysis of electromyography, the integral electromyography of biceps brachii muscle increased by DM 0.0240mv · s in the case of the SSC motion than when in the CC motion. There was no difference in the triceps brachii muscle. On the basis of this conclusion, We consider that the stretch-shortening cycle can affect many parts in the movement of the body. Through the results of the analysis of the armcurl motion, we can see that the stretch-shortening cycle is able to put out its strength by using elastic energy accumulated at the time of concentric contractions after accumulating elastic energy through pre-stretching before concentric contractions. Furthermore, since it puts out much more power 'in utilizing muscles compared to simple concentric contractions, We think the training method such as plyometric training can develop more power than previous training methods.
The demand for multimedia service using Ka-band satellite communication are growing rapi이y. So, in this paper, we have analyzed rain attenuation with typical model, and proposed prediction model of rain attenuation in high frequency(over 20[GHz]). Path loss model by rain attenuation is based upon rain rate of representative region(6 cities). Proposed prediction model of rain attenuation and parameter of satellite link can be available for the Ka-band satellite communication.