Abstract: Urban regeneration projects have been actively promoted in Korea. In particular, Jeonju Hanok Village is evaluated as one of representative cases in terms of utilizing local cultural heritage sits in the urban regeneration project. However, recently, there has been a growing concern in this area, due to the ‘gentrification’, caused by the excessive commercialization and surging tourists. This trend was changing land and building use and resulted in the loss of identity of the region. In this regard, this study analyzed the land use transformation between 2010 and 2016 to identify the commercialization trend in Jeonju Hanok Village. In addition, it conducted SNS big data analysis on Jeonju Hanok Village from February 14th, 2016 to March 31st, 2016 to identify visitors’ awareness of the village. The study results demonstrate that rapid commercialization was underway, unlikely the initial intention, so that planners and officials in city government should reconsider the project direction and rebuild deliberate management strategies. This study is meaningful in that it analyzed the land use transformation and SNS big data to identify the current situation in urban regeneration area. Furthermore, it is expected that the study results will contribute to the vitalization of regeneration area.
Abstract: For cycling, the analysis of the pedal force is one of the
important factors in the study of exercise ability assessment and
overuse injuries. In past studies, a two-axis measurement sensor was
used at the sagittal plane to measure the force only in the anterior,
posterior, and vertical directions and to analyze the loss of force and
the injury on the frontal plane due to the forces in the right and left
directions. In this study, which is a basic study on diverse analyses of
the pedal force that consider the forces on the sagittal plane and the
frontal plane, a three-axis pedal force measurement sensor was
developed to measure the anterior-posterior (Fx), medio-lateral (Fz),
and vertical (Fy) forces. The sensor was fabricated with a size and
shape similar to those of the general flat pedal, and had a 550g weight
that allowed smooth pedaling. Its measurement range was ±1000 N for
Fx and Fz and ±2000 N for Fy, and its non-linearity, hysteresis, and
repeatability were approximately 0.5%. The data were sampled at
1000 Hz using a signal collector. To use the developed sensor, the
pedaling efficiency (index of efficiency, IE) and the range of left and
right (medio-lateral, ML) forces were measured with two seat heights
(low and high). The results of the measurement showed that the IE was
higher and the force range in the ML direction was lower with the high
position than with the low position. The developed measurement
sensor and its application results will be useful in understanding and
explaining the complicated pedaling technique, and will enable
diverse kinematic analyses of the pedal force on the sagittal plane and
the frontal plane.
Abstract: It is difficult to study the effect of various variables on
cycle fitting through actual experiment. To overcome such difficulty,
the forward dynamics of a musculoskeletal model was applied to cycle
fitting in this study. The measured EMG data weres compared with the
muscle activities of the musculoskeletal model through forward
dynamics. EMG data were measured from five cyclists who do not
have musculoskeletal diseases during three minutes pedaling with a
constant load (150 W) and cadence (90 RPM). The muscles used for
the analysis were the Vastus Lateralis (VL), Tibialis Anterior (TA),
Bicep Femoris (BF), and Gastrocnemius Medial (GM). Person’s
correlation coefficients of the muscle activity patterns, the peak timing
of the maximum muscle activities, and the total muscle activities were
calculated and compared. BIKE3D model of AnyBody (Anybodytech,
Denmark) was used for the musculoskeletal model simulation. The
comparisons of the actual experiments with the simulation results
showed significant correlations in the muscle activity patterns (VL:
0.789, TA: 0.503, BF: 0.468, GM: 0.670). The peak timings of the
maximum muscle activities were distributed at particular phases. The
total muscle activities were compared with the normalized muscle
activities, and the comparison showed about 10% difference in the VL
(+10%), TA (+9.7%), and BF (+10%), excluding the GM (+29.4%).
Thus, it can be concluded that muscle activities of model &
experiment showed similar results. The results of this study indicated
that it was possible to apply the simulation of further improved
musculoskeletal model to cycle fitting.