The Study on the Style and Value of Stone Buddha Statue of Hoeamsa Temple in Yangju

This study focus on the characteristics and of the Fragment of Stone Buddha of Hoeamsa Temple(檜巖寺). As is well known, this temple had been developed rebuilding by supporting of the royal family from the late of Korea Dynasty to the early of Joseon Dynasty(朝鮮). The Hoeamsa Temple Site in Yangju(陽州) is believed to have been destroyed in a fire in the late 16th century, and various artifacts have been excavated after several excavations since 1999. This Temple has been excavated a variety of Fragment of Stone Buddha statues. The Buddha statue of Hoeamsa Temple in Yangju has a hole on top of high usnisa(肉髻), and special folds in the left arm and a thick clothing style. It was reflects the sculptural Joseon style modified by the Tibet-Chinese style. This style is very similar to that of Buddha statues produced in the 15th century, supported by the royal family of Joseon. In particular, these statues were believed to have been produced around the first half of the 15th century when the temple was heavily fortified with the support of Prince Hyo-ryeong(孝寧大君). It is also interesting to note that these statues show the sculptural features of the early Joseon Dynasty, reflecting the Tibetan-Chinese sculptures style, compared to those of the Buddhist sculptures in the first half of the 15th century during the year of Yeongrak (1403~1424) and Seondeok (1426~1435), the kings of the Ming Dynasty. This reflects the development of Buddhist sculptures in the early Joseon Dynasty in line with the trend of Buddhist art in East Asia.

Investigation of the visual appearance of different skirt styles and materials during the fitting simulation with Lectra Modaris

This paper examines the influence of different fabric types and material properties on the visual appearance of three types of skirt styles using numerical simulation. The purpose of the simulation is to present and analyze the appearance of virtual garments, create the best-fitting pattern pieces, and choose the appropriate fabric type based on the multiple clothing styles to achieve the intended design. The results show that when the type of fabric changes without changing the clothing style and on the other hand the style changes without changing the type of material, the appearance of the garment changes and the effect can be clearly seen with the 3d comparison result. These changes should be taken into account when choosing the right fabric for different styles.

Design and implementation of fake two-piece fully formed process for blouse

PurposeFully formed knitting technology is a cutting-edge technology in the design and production of knitted apparel. Using this technology and its supporting design system, a new development mode of fully formed knitted apparel with double-layer structure and fake two-piece knitwear is proposed.Design/methodology/approachBased on the upper body structure feature points of human body characteristics and single-layer knitted garment prototype, a double-layer structure knitted garment pattern was established by pattern expansion method. The model was introduced into SDS-APPEX3 design system for process design, including three aspects consists: the inner vest, the outer blouse and double-layer joint part, analysis of the process and forming principle. Weaving on four-needle bed computerized flat knitting machine of MACH-2XS, through the setting of the machine parameters. Finally, a full-shaped fake two-piece knitted blouse was formed.FindingsOn the basis of single-layer knitted garment pattern, a double-layer garment pattern is constructed, and the design and weaving are completed on the four-needle bed computerized knitting machine of MACH-2XS and its supporting SDS-APPEX3 design system through the fake two-piece double-layer garment style design. The double-layer joint model is an effective reference for the construction of this kind of fake two-piece fully formed knitted clothing.Originality/valueIn this paper, a design and knitting method of fully formed double-layer structure fake two-piece knitted garment is proposed. The integrated knitting of fully formed double-layer structure sweater is realized for the first time, which provides ideas for the development of fully formed double-layer structure knitted clothing style and enriches the fully formed clothing style.

Pedestrian Attribute Recognition using Gabor Wavelet Layers

We address the problem of Pedestrian Attribute Recognition (PAR) in this paper. Owing to the presence of surveillance cameras in almost all outdoor and indoor public spaces, keeping and eye on pedestrian is a sought-after task with many useful applications. The problem entails recognizing attributes such as age-group, clothing style, accessories, footwear style etc. This is a multi-label problem and challenging even for human observers. We propose using a convolution neural network (CNN) with trainable Gabor wavelets (TGW) layers. The proposed layers are learnable and adapt to the dataset for a better recognition. The proposed multi-branch neural network is a mix of TGW and convolutional layers and we show its effectiveness on a public dataset.

THE VISUAL ANALYSIS OF MUSLIMAH CLOTHING STYLE IN JAVA (15-20 th CENTURY)

Islam entered Indonesia in the 7th century and began to spread out in the 13th century with the establishment of Demak Sultanate. After the expansion of Islamic kingdoms or Sultanates, the spread of Islam in Java and Sumatra strengthened the application of Islamic law (Sharia). It was slowly replacing customary law yet still maintaining and even acculturating the local culture, with no exception concerning Muslimah clothing style (hijab or (jilbab). This non-interactive qualitative research analyzed the factual data related to the transformation of Muslimah clothing from the 15th to the 20th century focusing on Java island. The data were analyzed using the Fashion Design Components theory proposed by Stone (2006) and Seivewright (2012) to get detailed visualization of Muslimah clothing style in those eras. The result showed that Islamic values influenced the clothing style of Javanese Muslim women in terms of silhouettes, colors, details, and materials (textures) without neglecting the local culture.Islam masuk ke Indonesia pada abad ke-7 dan mulai menyebar pada abad ke-13 Masehi dengan berdirinya Kerajaan Islam Demak. Penerapan hukum Syariah Islam secara perlahan menggantikan hukum Adat namun demikian tetap mengakomodasi bahkan berkakulturasi dengan budaya setempat, termasuk dalam hal penerapan busana Muslimah (jilbab). Penelitian ini bertujuan untuk menganalisis visualisasi busana Muslimah di Indonesia khususnya di Jawa pada abad 15-20 Masehi. Penelitian kualitatif non-interaktif ini menggunakan pendekatan deskriptif yang menekankan pada data-data faktual terkait perkembangan busana wanita Muslim. Data dianalisis menggunakan teori elemen desain mode (the components of fashion) yang terdiri dari siluet, warna, detail, dan tekstur untuk mengetahui gambaran bentuk busana Muslimah pada masa tersebut. Hasil penelitian menunjukan ajaran Islam mempengaruhi gaya berpakaian wanita Muslim Jawa, baik dari segi elemen visual bentuk (siluet), warna, detail, dan material (tekstur), namun demikian tetap mempertahankan budaya lokal yang berlaku.

Fashioning culture: Transforming perspectives from Oceania

In this introductory article we discuss what might be gained from examining more familiar areas of anthropological research such as cloth, dress or material culture through fashion as an analytical category and, in turn, how insights from Pacific clothing cultures can broaden understandings of fashion. Our aim is to unsettle the ethnographic gaze that is often brought to bear on non-western cultures of fashion, cloth, clothing, style and innovation. Fashion, as we conceive of it, spans from the physical production and design of garments and objects to everyday appearances, the desire to be ‘in vogue’ and the consumption of aesthetic objects that are considered popular. From this starting point we move analyses of fashion from the systemic to the experiential, reflecting ethnographic sensitivity to everyday embodied practice and the constant political and creative negotiation of values and norms that takes place in quotidian social relations. We situate these analyses in a region that is often perceived to be at the very edge of the world economy and invite further discussion about the relationship between fashion and the global flow of people, ideas and commodities.

Pedestrian attribute recognition using two-branch trainable Gabor wavelets network

Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age-group, clothing style, accessories, footwear style etc. This multi-label problem is extremely challenging even for human observers and has rightly garnered attention from the computer vision community. Towards a solution to this problem, in this paper, we adopt trainable Gabor wavelets (TGW) layers and cascade them with a convolution neural network (CNN). Whereas other researchers are using fixed Gabor filters with the CNN, the proposed layers are learnable and adapt to the dataset for a better recognition. We propose a two-branch neural network where mixed layers, a combination of the TGW and convolutional layers, make up the building block of our deep neural network. We test our method on twoo challenging publicly available datasets and compare our results with state of the art.

FENOMENA CROSS HIJAB DAN PENGARUHNYA TERHADAP PERGESERAN SAKRALITAS KEAGAMAAN DI MASYARAKAT

Religion within Indonesian society is considered as a sacred institution. The appearance of a Cross Hijab phenomenon in social media has created a controversy for netizens because of its cross-gender clothing style. The presence of members of this group has caused unrest among most Muslims in Indonesia because its potential to decrease the sacredness of the hijab in society. This paper aims to analyze how cross hijab affects religious sacredness in society. This study used a qualitative approach in tracing cross-hijab group data on social media, and conducting a survey of 165 respondents from junior high school, high school, undergraduate, graduate, and non-Islamic boarding schools. The theory uses in this study is the sacred and profane theory of Mircea Eliade. The results showed that the emergence of the cross hijab phenomenon can have a major effect on the level of sacredness in some Islamic values of Indonesian Muslim communities. Besides, it also causes a shift in views and social situations regarding the function of hijab which theologically means sacred to something profane (accessories).Agama dalam masyarakat Indonesia merupakan salah satu institusi yang memiliki nilai sakral. Munculnya Cross Hijab di media sosial menimbulkan pro-kontra di masyarakat karena anggotanya mengenakan pakaian lintas gender yaitu hijab. Kehadiran anggota kelompok ini menimbulkan keresahan pada sebagian besar muslim di Indonesia karena dianggap dapat menggeser sakralitas hijab di masyarakat. Tulisan ini bertujuan untuk menganalisis bagaimana cross hijab mempengaruhi sakralitas keagamaan di masyarakat. Penelitian ini menggunakan pendekatan kualitatif berupa penelusuran data kelompok cross hijab di media sosial, dan diperkuat dengan melakukan survey terhadap 165 responden dari jenjang pendidikan SMP, SMA, S1, S2, S3, lulusan pesantren maupun non-pesantren. Adapun teori yang penulis gunakan sebagai alat analisis adalah teori sakral dan profan dari Mircea Eliade. Hasil penelitian menunjukan bahwa munculnya fenomena cross hijab dapat berpengaruh besar terhadap tingkat sakralitas pada sebagian nilai keislaman masyarakat muslim Indonesia. Disamping itu juga menimbulkan pergeseran pandangan dan situasi sosial tentang perubahan fungsi hijab yang secara teologis bermakna sakral menjadi sesuatu yang profan (aksesoris).

Multideep Feature Fusion Algorithm for Clothing Style Recognition

In order to improve recognition accuracy of clothing style and fully exploit the advantages of deep learning in extracting deep semantic features from global to local features of clothing images, this paper utilizes the target detection technology and deep residual network (ResNet) to extract comprehensive clothing features, which aims at focusing on clothing itself in the process of feature extraction procedure. Based on that, we propose a multideep feature fusion algorithm for clothing image style recognition. First, we use the improved target detection model to extract the global area, main part, and part areas of clothing, which constitute the image, so as to weaken the influence of the background and other interference factors. Then, the three parts were inputted, respectively, to improve ResNet for feature extraction, which has been trained beforehand. The ResNet model is improved by optimizing the convolution layer in the residual block and adjusting the order of the batch-normalized layer and the activation layer. Finally, the multicategory fusion features were obtained by combining the overall features of the clothing image from the global area, the main part, to the part areas. The experimental results show that the proposed algorithm eliminates the influence of interference factors, makes the recognition process focus on clothing itself, greatly improves the accuracy of the clothing style recognition, and is better than the traditional deep residual network-based methods.