The technology competitions of automobile manufacturers are getting hot. The characteristics of the environment friendly automobile are not only lowering the emission of harmful exhaust gas through the change of the power source, but also paying great attention to improvement of the power efficiency. As the market for pure electric vehicles continues to grow, we have analyzed the global technology competitiveness by DCT (Dual Clutch Transmission) patents. Clustering can be classified into five types ; 1) a cluster associated with a dual clutch transmission system, 2) a cluster of a torque transmission device and a reverse speed ratio, 3) a cluster of co-planar sets and dual clutch assemblies related to transmitting devices, 4) Device clusters, and 5) a cluster of synchronizers and clusters to prevent simultaneous operation of dual clutch transmissions. In recent years, demand for pure electric vehicles has been rapidly increasing, and patent applications related to DCT have been steadily increasing for energy efficiency of motor power sources.

Since the so-called diesel gates of German automobiles, interest in environmentally-friendly vehicles has been rising, among other alternatives, hydrogen-fueled electric vehicles with 0% vehicle emissions are expected to replace a significant portion of passenger cars. Here, we analyze trends of US, Europe, PCT (WO) 3-patent offices application of hydrogen-fueled electric vehicles and analyze the patent application trends of national and individual companies, the patent application trend of detailed technology through clustering analysis, technology competitiveness. The global market for hydrogen-fueled electric vehicles, which is currently only 0.01% of other alternatives, is expected to grow to several percent in 2020. Major automobile makers such as Japan, United States of America, Germany, and Korea continue to fiercely compete for eco-friendly vehicles.

We estimate the fractal dimension of the ρ Ophiuchus Molecular Cloud Complex, associated with star forming regions. We selected a cube (v, l, b) database, obtained with J = 1−0 transition lines of 12CO and 13CO at a resolution of 22′′ using a multibeam receiver system on the 14-m telescope of the Five College Radio Astronomy Observatory. Using a code developed within IRAF, we identified slice-clouds with two threshold temperatures to estimate the fractal dimension. With threshold temperatures of 2.25 K (3σ) and 3.75 K (5σ), the fractal dimension of the target cloud is estimated to be D = 1.52–1.54, where P / AD/2 , which is larger than previous results. We suggest that the sampling rate (spatial resolution) of observed data must be an important parameter when estimating the fractal dimension, and that narrower or wider dispersion around an arbitrary fit line and the intercepts at NP = 100 should be checked whether they relate to rms noise level or characteristic structure of the target cloud. This issue could be investigated by analysing several high resolution databases with different quality (low or moderate sensitivity).