TIPOLOGI TENDA SEBAGAI STUDI ARSITEKTUR PORTABEL

Architecture trends are continuously searching for a new design alternative. If architecture is dominated by a permanent structure in the last decades, the latest trend suggests temporal, ephemeral, and informal architecture to emerge as the other alternative. While the world becomes complex, these other spatial forms are in demand, resulting in various installations, pop-up stores, container architecture, and portable, temporal architecture constructed throughout the cityscape. Its portability, elasticity, and fluidity have offered different human activity transformations compared to permanent architecture. Tent, one of the most popular portable architecture, has been used for myriad human activities, although fewer researches are found regarding the typology of the tent, which is considered beneficial to understand its transformation. The qualitative interpretive method is used to understand the typology of the contemporary tent. The diagram is utilized as a tool to investigate its form, structure, and physical appearance. The research steps are drawing a diagram, pattern extraction, and pattern interpretation. The phases are elimination of tent’s elaboration and decoration, pattern structure extraction, pattern illustration. The result is tent typology diagram. The novelty is tent basic pattern extraction. Keywords: Architecture; Portable; Tend; Type; Typology. AbstrakLatar belakang penelitian adalah fenomena tren arsitektur dunia yang mulai mempertanyakan alternatif lain keruangan. Permasalahannya pada dekade terakhir arsitektur dunia didominasi oleh pemahaman ruang permanen pada makna arsitektur yang seolah bersifat absolut, padahal belakangan konsep-konsep keruangan temporal, ephemeral dan informal semakin dibutuhkan untuk mengisi stagnansi arsitektur permanen. Kebutuhan ruang portabel meningkat; hal ini terbukti dari tingginya permintaan akan: instalasi, paviliun, pop-up store, kontainer dan jenis keruangan lain yang lebih ringan, cair dan mudah dimodifikasi. Tenda adalah salah satu alternatif keruangan temporal yang telah berkembang sejak dulu kala, keunggulannya sebagai arsitektur portabel masih relevan di saat ini. Meski demikian, belum banyak perkembangan dan penelitian tenda yang berfokus pada tipe dan struktur untuk gaya hidup masa depan, sementara dominasi pengembangan tenda adalah untuk kebutuhan berkemah atau liburan saja. Penelitian ini bertujuan untuk menginvestigasi tipologi tenda sebagai arsitektur portabel Metode penelitian adalah tipologi arsitektur untuk mengangkat kualitas arsitektur tenda. Diagram arsitektur digunakan untuk menghasilkan ilustrasi yang dapat diinterpretasikan dalam memahami pola struktur tenda, Langkah penelitian sebagai berikut: 1) menggambar diagram keruangan; 2) mengekstraksi pola; 3) menginterpretasi pola. Tahapan penelitian disusun sebagai berikut: 1) Mengeliminasi elaborasi dan dekorasi tenda, 2) Mengekstraksi struktur tenda, 3) Menggambar pola. Hasilnya adalah diagram arsitektur tipologi tenda. Kebaruannya adalah ekstraksi pola dasar tenda sebagai arsitektur portabel.

Editorial for Special Issue “Fine Art Pattern Extraction and Recognition”

Cultural heritage, especially the fine arts, plays an invaluable role in the cultural, historical, and economic growth of our societies [...]

Testing Methods of Pattern Extraction for Climate Data Using Synthetic Modes

In this paper we develop a method to quantify the accuracy of different pattern extraction techniques for the additive space–time modes often assumed to be present in climate data. It has previously been shown that the standard technique of principal component analysis (PCA; also known as empirical orthogonal functions) may extract patterns that are not physically meaningful. Here we analyze two modern pattern extraction methods, namely dynamical mode decomposition (DMD) and slow feature analysis (SFA), in comparison with PCA. We develop a Monte Carlo method to generate synthetic additive modes that mimic the properties of climate modes described in the literature. The datasets composed of these generated modes do not satisfy the assumptions of any pattern extraction method presented. We find that both alternative methods significantly outperform PCA in extracting local and global modes in the synthetic data. These techniques had a higher mean accuracy across modes in 60 out of 60 mixed synthetic climates, with SFA slightly outperforming DMD. We show that in the majority of simple cases PCA extracts modes that are not significantly better than a random guess. Finally, when applied to real climate data these alternative techniques extract a more coherent and less noisy global warming signal, as well as an El Niño signal with a clearer spectral peak in the time series, and more a physically plausible spatial pattern.