order tranylcypromine When application of simple public addr

When application of simple public address system based on the electro acoustics installed at the cathedral, improved sound pressure and clarity (SPL, C80, D50, ITDG, and RASTI were improved significantly, excluding reverberation characteristics) can be acquired as follows: SPL (74.5 dBA on average), EDT (3.76s on average), RT60 (3.89s on average), C80 (−2.8dB on average), D50 (29% on average), ITDG (23ms on average), and RASTI (42% on average). This can be explained in that acoustic problems derived from the long reverberation time caused by large space, a large number of columns, and masonry finishing materials in the unique Gothic cathedral architecture were supplemented through simple application of simple public address system. In fact, the public address system in Myeong-dong Cathedral designed with simple voice amplification devices such as audio power amplifiers (mono-channel 240W amplifier 6EA), graphic equalizer (64-band analog graphic equalizer 4EA), and loud speakers (2-way 30W column speaker 40EA; as shown Fig. 3), excluding a DSP (digital signal processor). This improvement can also be found in subjective evaluation survey results. Actually, there are similar tendencies on speech intelligibility for the voice recognition and reverberation of sound in the music recognition between the acoustical parameters and results of the subjective evaluation.
Acknowledgements This research was supported by a grant (Religious Architecture Research Fund 2016-01) from Catholic architect office of Roman Catholic Archdiocese of Seoul, Korea. Additionally, the authors would like to thank RPG Korea Diffusor Systems, Inc. for technical cooperation.
Introduction Hsieh and Wu, (2012) divided the performance evaluation of a building into five parts: (1) building envelope, (2) air conditioning and ventilation, (3) water heating system, (4) dynamic equipment, and (5) illumination. The building envelope was recognized as the most important factor with regard to order tranylcypromine efficiency. The researchers believe that if the properties of the building envelope can be improved, a suitable energy saving design can be attained, thereby leading to lower energy consumption during operation, as well as lower energy waste and carbon dioxide emissions. A defined energy amount has to be supplied for a building to operate at optimum capacity and functionality. This condition requires estimating the energy amount required and equating energy demand with energy supply. Thus, “the demand side is calculated, cumulating energy losses such as transmission and ventilation heat losses of the building envelope” (Schlueter and Thesseling, 2009). Various methods of evaluating the energy performance of buildings have been identified and employed by different researchers. A hybrid method in the energy analysis of building materials was applied (Alcorn and Baird, 1996). Previous researchers identified three types of energy analysis methods: (1) statistical analysis, (2) input–output analysis, and (3) process analysis. Statistical analysis employs published statistics to evaluate energy usage. Input–output analysis equates energy usage with the monetary flow within an economy. Process analysis deals with the systematic examination of the direct and indirect energy into a process. Similarly and in a more detailed format, energy performance analysis was classified into two types (Schlueter and Thesseling, 2009), namely, (1) physical calculation models and (2) statistical calculation models. The researchers argued that the physical calculation model provides the exact calculation of detailed performance analysis tasks, whereas the statistical calculation model applies empirical factors in the building performance analysis, thereby generating performance analysis estimates. Although the aforementioned methods seem to have worked in the past, recent developments in computational simulations now allow for the efficient analysis of the building envelope performance. Current computational optimization methods applied to sustainable building design problems were reviewed (Evins, 2013). The author identified three types of computational optimization: (1) generic optimization, (2) multi-objective optimization, and (3) algorithm. Bazjanac (2007) stated that “the quality of developed and used simulation model depends on data available at the given stage of the project, the knowledge and experience of the modeler, available resources, and various other external conditions and pressures”.