Similar to Sumerian proto-cuneiform writing, the nature of Chinese writing is fundamentally ideographic, in which concepts or thoughts are represented visually rather than through abstract speech sounds. This paper explores ten ways to form Chinese characters by using the decoded characters through their ideograms. A character comes from thoughts, the thoughts come from images, and the images themselves come from the object or the event depicted. Therefore, the same character can be used in different dialects or languages to depict the same concepts. Only when there are enough ideograms to create their graphs for phonography can we develop phonography. During the first stage of hundreds of years, most Sumerian clay characters were pictograms and ideograms. The majority of the phono-semantic compounds appeared in the second stage when the foreign Akkadians used Sumerian characters. Just as the majority of Shang bone characters were pictograms and ideograms, most phono-semantic compound characters were modified and created by the foreign Zhou people later. At present, western theories have not followed the traditional path to the meaning of thought. The ten strategies of ideographic writing are the conventional path to the meaning of thought, rather than a bridge between language.

Zhu (朱) is a pictophonetic character and associative compound. Mu (木) and Zhu (丶) indicate the meaning, and especially the latter refers to the pronunciation as well. Its original meaning is wood with red inside. Zhu (朱) assumes the semantic function in pictophonetic characters. The meaning of the expression comes from two sources: one is that it derives from the extended meaning of Zhu (丶) as the phonetic symbol of Zhu (朱) means red or bright; the other is that it derives from the extended meaning or rebus of a short form for Zhu (鼄), which means ‘to cut off’ or ‘a name of the place’.

Steam tables including superheated, saturated and compressed region were simultaneously modeled using the neural networks. Pressure and temperature were used as two inputs for superheated and compressed region. On the other hand Pressure and dryness fraction were two inputs for saturated region. The outputs were specific volume, specific enthalpy and specific entropy. The neural network model were compared with the linear interpolation model in terms of the percentage relative errors. The criterion of judgement was selected with the percentage relative error of 1%. In conclusion the neural networks showed better results than the interpolation method for all data of superheated and compressed region and specific volume of saturated region, but similar for specific enthalpy and entropy of saturated region.

The steam table in saturated and superheated region was modeled simultaneously using the neural networks. A variable was introduced to distinguish between the saturation and the superheat. The relative errors were compared with the quadratic spline interpolation method. The relative errors by the neural networks were superior to those by the quadratic spline interpolation method over almost all ranges of temperatures and properties. The overall errors in the saturated region were better than those in the superheated region. From the analysis, it was confirmed that the neural networks could be a very powerful tool for simultaneous modeling of superheated and saturated steam table

The thermodynamic state variables in superheated region of steam table are not wholy obtained by measurements. This means that steam table contains a little error. In this study small error was artificially added to superheated variables and modeled using neural networks. The results were compared with the analysis using quadratic spline interpolation method. By and large the relative errors of variables by neural networks were sufficiently small and similar to or less than those by quadratic spline interpolation method. It was concluded that neural networks could be one good way of modeling for superheated steam table.

In this paper, we study the structure of the Daegyupyo (大圭表, Large Gnomon) of the early Joseon dynasty. A Gyupyo (圭表, Gnomon that is Guibiao as pronounced in Chinese) is composed of a Pyo (表, Biao as pronounced in Chinese) making a shadow and a Gyu (圭, Gui as pronounced in Chinese) measuring its length. It is known that the Daegyupyo with the 40-feet height was constructed between the sixteenth to seventeenth year of the King Sejong reign (1444 - 1445) on the basis of the record of Yuanshi (元史, the History of the Yuan Dynasty). By analyzing historical documents such as Joseonwangjosillok (朝鮮王朝實錄, the Annals of the Joseon Dynasty), Yuanshi, and Jegaryeoksangjip (諸家曆象集, a work written by Sunji Lee), we found a possibility that the Ji (池, a pond) on the Gyu was located in the north side of the Pyo. This structure is different from that in previous studies, but is in a good agreement with that of the 40-feet Guibiao remaining in Dengfeng (登封) of China. Regarding to the Hoengyang (橫梁, cross-bar), we suggest that it was set up by double 5-feet supporting arms apart from the north tip of the Pyo in the radial direction. The 3:4:5 ratio in a rectangular triangle was used to place the Heongyang on the top of the Pyo at a distance of 4-feet (3-feet) in the vertical (horizontal) direction. We also discuss the structural problem when the Hoengyang is positioned apart from the top of the Pyo by supporting arms. In conclusion, we think that this study should be useful in restoring the Daegyupyo of the Joseon dynasty.