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"The Serat Tiyang Gegriya or “Book for people on running their homes and households” is a Javanese versification of the famous seventeenth-century Chinese treatise Zhuzi Zhijia geyan (‘Master Zhu’s Household Rules‘), better known in the Anglophone world as “Maxims for managing the home” or “Family regulations”. Propagating the basic principles of Confucian ethics, this small treatise instructed generations of Chinese readers, presumedly adult males, lessons in proper behaviour. Today, Master Zhu’s little compendium is among the most reprinted works of classical Chinese popular literature. The Serat Tiyang Gegriya exists in the form of a manuscript, written in Surabaya in 1878, and was subsequently published ten years later in the same city. The appearance of this popular Confucian tract in Javanese seems to have been born of a perceived sense of crisis and alarm at the decline of “Chineseness” among the Chinese minority in a foreign land, the upshot of the seemingly inexorable process of acculturation taking place in the Sino-Javanese community at the end of the nineteenth century. Paradoxically, however, the Serat Tiyang Gegriya itself is a fine product of acculturation, transmitting Chinese moral teachings in the form of the Javanese piwulang genre, or lessons on how to live a good life, composed in the mother tongue of the mothers of the intended readers as this group was unable t"

"Buku ini merupakan novel terjemahan dari karya Maksim Gorky yang berjudul Мать = Mat. Novel ini diterjemahkan ke dalam bahasa Inggris oleh Margaret Wettlin dengan judul Mother."

"Buku ini merupakan novel dua babak karangan Maksim Gorky yang berjudul Мать = mat'. Novel ini diterjemahkan ke dalam bahasa Inggris oleh Margaret Wettlin."

"The highly valued diagnostic technique that has been used for centuries by cultures around the world. A reliable diagnostic tool for monitoring the overall state of health. Easy to learn, effective and accurate. Determines a person's unique constitution. Detects imbalances and potential disease in the early stages. Reveals the underlying cause, stage and progression of a disease. Reflects the quality of Prana, blood, bodily fluids, and essence. Examines the expression of the Five Elements in each organ. Determines the state of physical, mental and emotional health. Mirrors the function of the organs, strength and depth of pathogenic factors. Provides immediate access to the body's pH balance, energy levels and health of the digestive system. [back cover"

"Sistem klasifikasi citra lidah telah banyak digunakan dalam kepentingan medis dan diagnosis kesehatan. Penelitian ini berfokus pada peningkatan peforma akurasi klasifikasi pada sistem prediksi perokok berdasarkan analisis letak persebaran Smoker Melanosis pada citra lidah. Teknik diagonis lidah yang dibangun adalah metode yang non-invasif serta berbasis pencitraan hiperspektral (HSI). Berbagai pendekatan dan arsitektur Deep Learning  telah diusulkan untuk mengatasi analisis data HSI dan telah mencapai akurasi klasifikasi yang relatif tinggi. Pada penelitian ini, arisitektur Convolutional Neural Network (CNN) dipakai dalam konfigurasi spektral-spasial yang terutama digunakan dengan tujuan ekstraksi fitur dan klasifikasi. Peneliti membuat beberapa arsitektur CNN untuk melakukan beberapa pengujian. Peneliti mengklasifikasikannya sebagai Single CNN dan Hybrid CNN. Pada algoritma Single CNN ada 2 arsitektur yang dibuat  yaitu CNN-Autoencoder dan CNN-Alexnet. Pada algoritma Hybrid CNN ada 2 arsitektur yang dibuat yaitu Proposed Hybrid CNN dengan satu cabang dan Hybrid CNN Resnet18 dengan 8 cabang. Peneliti menguji dampak kernel pada setiap subjek segmentasi yang berbeda dan terlihat bahwa akurasi klasifikasi tertinggi setiap subjek bervariasi terhadap ukuran kernel. Oleh karena itu, model Hybrid-CNN ini diusulkan untuk dapat membuat arsitektur hibrida dan skala konvolusi hibrida. Pada model Proposed Hybrid CNN yang diusulkan, akurasi pada subjek Lateral A bisa mencapai 90,6%, Lateral B mencapai 86,5%, dan Persepsi Dokter mencapai 99,2%. Pada model Hybrid CNN-Resnet18 yang diusulkan, Lateral A bisa mencapai 89,4%, Lateral B mencaapai 84,6%, dan Persepsi Dokter mencapai 97,4%. Secara umum hasil akurasi model yang diusulkan berhasil mencapai peforma yang lebih baik.

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The tongue image classification system has been widely used in medical interests and health diagnosis. This research emphasizes on improving the performance of classification accuracy in the Smoker prediction system based on the location analysis of the SmokerMelanosis distribution on the tongue image. The tongue diagonalization technique developed is a non-invasive method based on hyperspectral imaging (HSI). Various considerations and architecture In-depth learning have been proposed to overcome the analysis of HSI data and has obtained relatively high classification completion. In this study, the Convolutional Neural Network (CNN) architecture is used in the spectral-spatial configuration used for feature extraction and classification. CNN to do some testing. Researchers classified it as Single CNN and Hybrid CNN. In the Single CNN algorithm, there are 2 architectures created, namely CNN-Autoencoder and CNNAlexnet. In the Hybrid CNN algorithm, there are 2 architectures created, namely Proposed Hybrid CNN with one branch and Hybrid CNN Resnet18 with 8 branches. Learn more about the kernel in each different subject segmentation and look at the kernel classification. Therefore, the Hybrid-CNN model is proposed to be able to make hybrid architecture and hybrid convolution scale. In the approved Proposed Hybrid CNN model, approved on the subject of Lateral A can reach 90,60%, Lateral B reaches 86,5%, and Doctor Perception reaches 99,2%. In the CNN-Resnet18 Hybrid model obtained, Lateral A can reach 89,4%, Lateral B reaches 84,6%, and Doctor Perception reaches 97,4%. In general, the results of the completion of the approved model have achieved better performance. "