Sejarah Kebangkitan Nasional Daerah Riau

Pada zaman sriwijaya yang berlangsung dari abad ke-7 sampai abad ke-14 Masehi seluruh Daerah Tingkat 1 Riau sekarang ini termasuk ke dalam wilayah kekuasaan kerajaan besar itu. Tatkala kekuasaan Sriwijaya sudah mulai menurun, maka timbullah kerajaan-kerajaan di Riau yang kian berkembang seperti kerajaan Siak Gasib, Bintan, Indragiri, dll. Untuk beberapa waktu mereka mengakui kekuasaan mojopahit yang kuat. Tetapi setelah kerajaan Malaka berkembang dengan pesat dan merupakan kekuasaan politik dan sosial budaya di Asia Tenggara, maka kerajaan-kerajaan yang disebutkan tadi menjadi bagian dari kerajaan malaka

Make the Most Out of Your Net: Alternating Between Canonical and Hard Datasets for Improved Image Demosaicing

Image demosaicing is an important step in the image processing pipeline for digital cameras, and it is one of the many tasks within the field of image restoration. A well-known characteristic of natural images is that most patches are smooth, while high-content patches like textures or repetitive patterns are much rarer, which results in a long-tailed distribution. This distribution can create an inductive bias when training machine learning algorithms for image restoration tasks and for image demosaicing in particular. There have been many different approaches to address this challenge, such as utilizing specific losses or designing special network architectures. What makes our work is unique in that it tackles the problem from a training protocol perspective. Our proposed training regime consists of two key steps. The first step is a data-mining stage where sub-categories are created and then refined through an elimination process to only retain the most helpful sub-categories. The second step is a cyclic training process where the neural network is trained on both the mined sub-categories and the original dataset. We have conducted various experiments to demonstrate the effectiveness of our training method for the image demosaicing task. Our results show that this method outperforms standard training across a range of architecture sizes and types, including CNNs and Transformers. Moreover, we are able to achieve state-of-the-art results with a significantly smaller neural network, compared to previous state-of-the-art methods

On the interface properties of Cantonese verb-object compounds.

Chin Kin-Chung.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 191-201).Abstracts in English and Chinese.Acknowledgements --- p.iAbbreviations and Symbols --- p.viAbstract (English) --- p.viiAbstract (Chinese) --- p.viiiChapter Chapter One --- Characteristics of Compounds: An Overview --- p.1Chapter 1.0 --- Introduction --- p.1Chapter 1.1 --- General Properties of Compounds --- p.3Chapter 1.1.1 --- Lexical Properties --- p.4Chapter 1.1.2 --- Phrasal Properties --- p.12Chapter 1.1.3 --- Complexity of the Status of Compounds --- p.16Chapter 1.2 --- Relation between Morphology and Syntax --- p.16Chapter 1.2.1 --- Lexicalist Approach --- p.18Chapter 1.2.2 --- Syntactic Approach --- p.19Chapter 1.2.3 --- Parallel Approach --- p.20Chapter 1.2.4 --- A Note on the Lexicon --- p.21Chapter 1.3 --- Research Objectives --- p.24Chapter 1.4 --- Summary and Organization of the Thesis --- p.29Chapter Chapter Two --- "Notions of Word, Compound and Phrase" --- p.31Chapter 2.0 --- Introduction --- p.31Chapter 2.1 --- Criteria of Wordhood --- p.32Chapter 2.2 --- Distinction between Compounds and Phrases --- p.38Chapter 2.2.1 --- Introduction --- p.39Chapter 2.2.2 --- Syntactic Aspect --- p.43Chapter 2.2.3 --- Semantic Aspect --- p.45Chapter 2.2.4 --- Morphological and Phonological Aspects --- p.48Chapter 2.2.5 --- Summary --- p.50Chapter 2.3 --- The Lexical Integrity Hypothesis (LIH) --- p.52Chapter 2.4 --- Further Consideration on the Nature of Compound --- p.60Chapter 2.4.1 --- Compounding and Other Combinatory Processes --- p.60Chapter 2.4.2 --- Status of the Constituents --- p.62Chapter 2.4.3 --- Degree of Separability --- p.64Chapter 2.4.4 --- Definitions of Compounds --- p.66Chapter 2.5 --- Summary --- p.69Chapter Chapter Three --- Issues on Cantonese Verb-Object Compounds (VOCs) --- p.70Chapter 3.0 --- Introduction --- p.70Chapter 3.1 --- General Properties of Cantonese VOCs --- p.74Chapter 3.1.1 --- Meaning --- p.75Chapter 3.1.1.1 --- Compositionality of Meaning --- p.75Chapter 3.1.1.2 --- Anaphoric Reference --- p.79Chapter 3.1.2 --- Movement --- p.80Chapter 3.1.2.1 --- Topicalization --- p.80Chapter 3.1.2.2 --- Passivization --- p.83Chapter 3.1.3 --- Separability --- p.84Chapter 3.1.3.1 --- Semantic Object --- p.85Chapter 3.1.3.2 --- Aspect Markers --- p.88Chapter 3.1.3.3 --- Duration and Frequency Adverbials --- p.91Chapter 3.1.4 --- Status of the Cantonese VOCs --- p.94Chapter 3.2 --- Analyses of VOCs --- p.96Chapter 3.2.1 --- S.-F. Huang (1984) --- p.96Chapter 3.2.2 --- C.-T. Huang (1984) --- p.99Chapter 3.2.3 --- Paul (1988) --- p.103Chapter 3.2.4 --- Wang (1994) --- p.105Chapter 3.2.5 --- Her (1997) --- p.110Chapter 3.3 --- Existence of Two Types of VOCs in Cantonese --- p.113Chapter 3.3.1 --- Distinction between Lexical and Phrasal VOCs --- p.113Chapter 3.3.2 --- Diagnostic Tests for the Lexical-Phrasal VOC Distinction --- p.117Chapter 3.4 --- Summary --- p.120Chapter Chapter Four --- Nature and Formation of Cantonese VOCs --- p.121Chapter 4.0 --- Introduction --- p.121Chapter 4.1 --- Theoretical Assumptions --- p.123Chapter 4.1.1 --- Parallel Morphology --- p.123Chapter 4.1.2 --- Lexical-Semantic and Lexical-Syntactic Representations --- p.134Chapter 4.1.3 --- Lexical Syntax --- p.139Chapter 4.1.4 --- VP Shell --- p.141Chapter 4.2 --- Levels of Formation of Cantonese VOCs --- p.143Chapter 4.3 --- Mechanism of the Formation Processes --- p.147Chapter 4.3.1 --- Issue of Transitivity --- p.147Chapter 4.3.2 --- Formation of Lexical VOCs --- p.154Chapter 4.3.3 --- Formation of Phrasal VOCs --- p.158Chapter 4.4 --- Phenomena in Relation to Cantonese VOCs --- p.161Chapter 4.4.1 --- Separation of Constituents of Phrasal VOCs --- p.161Chapter 4.4.2 --- Positions of Aspect Markers --- p.168Chapter 4.5 --- Summary and Theoretical Consequences --- p.172Chapter Chapter Five --- Concluding Remarks --- p.176Endnotes --- p.181References --- p.19

Sejarah daerah propinsi Daerah Istimewa Aceh

Buku Sejarah Daerah Propinsi Daerah Istimewa Aceh merupakan salah satu hasil pelaksanaan kegiatan penelitian Proyek Penelitian dan Pencatatan Kebudayaan, Daerah Pusat Penelitian Sejarah dan Budaya, Departemen Pendidikan dan Kebudayaan tahun 1977/1978. Proyek tersebut menerbitkannya pada tahun 1979/1980 sebagai cetakan pertama. Buku ini memuat uraian peristiwa-peristiwa yang terjadi di Propinsi :Daerah Istimewa Aceh. Dimulai dari zaman prasejarah yang meliputi asal-usul penghuni yang pertama, teknologi, organisasi masyarakat, kehidupan sosial ekonomi dan sosial budaya serta kepercayaan mereka. Kemudian dilanjutkan ke periode-periode selanjutnya, yaitu zaman kuno. zaman baru, abad ke-19, zaman Kebangkitan Nasional, zaman Pendudukan Jepang, dan zaman Kemerdekaan. Masing-masing periode diuraikan tentang kehidupan pemerintahan dan kenegaraan, penyelenggaraan hidup dalam masyarakat, kehidupan seni budaya, alam pikiran dan kepercayaan serta hubungan luar negeri

Classification with Margin Constraints: A Unification with Applications to Optimization

This paper introduces Classification with Margin Constraints (CMC), a simple generalization of cost-sensitive classification that unifies several learning settings. In particular, we show that a CMC classifier can be used, out of the box, to solve regression, quantile estimation, and several anomaly detection formulations. On the one hand, our reductions to CMC are at the loss level: the optimization problem to solve under the equivalent CMC setting is exactly the same as the optimization problem under the original (e.g. regression) setting. On the other hand, due to the close relationship between CMC and standard binary classification, the ideas proposed for efficient optimization in binary classification naturally extend to CMC. As such, any improvement in CMC optimization immediately transfers to the domains reduced to CMC, without the need for new derivations or programs. To our knowledge, this unified view has been overlooked by the existing practice in the literature, where an optimization technique (such as SMO or PEGASOS) is first developed for binary classification and then extended to other problem domains on a case-by-case basis. We demonstrate the flexibility of CMC by reducing two recent anomaly detection and quantile learning methods to CMC

Non-Centricity and Apathy: An Introduction to Hong Kong Literature

Hong Kong literature, with particular historical and social factors, can be regarded as a non-centric literary form. While the majority of Hong Kong people speaks Cantonese as their mother tongue, they are required to write in Mandarin. Additionally, Hong Kong literature struggles to attract attention from an apathetic audience, to produce local writers, and to resonate with foreign readers. As serious literature continues to lose its purchase, more and more writers attempt to break out from this predicament and inject new blood into this fading industry. Efforts include circumventing traditional constraints and incorporating more colloquial Cantonese into various publications, as well as a mushrooming of internet novels. Unfortunately, Chinese education remains rigid and inflexible, hindering students’ ability to use writing as a creative outlet. Literature is also heavily commodified. In light of this, I suggest that reading be encouraged and literature be de-commodified. Hong Kong literature, with its distinctive features and strengths, have the potential to thrive. All it needs is sufficient support from the government, the private sector and the general public.         &nbsp

On Investigations of Machine Learning and Deep Learning Techniques for MIMO Detection

This paper reviews in detail the various types of multiple input multiple output (MIMO) detector algorithms. The current MIMO detectors are not suitable for massive MIMO (mMIMO) scenarios where there are a large number of antennas. Their performance degrades with the increase in number of antennas in the MIMO system. For combatting the issues, machine learning (ML) and deep learning (DL) based detection algorithms are being researched and developed. An extensive survey of these detectors is provided in this paper, alongwith their advantages and challenges. The issues discussed have to be resolved before using them for final deployment

Sejarah Daerah Propinsi Daerah Istimewa Aceh

Sejarah daerah-daerah di Indonesia yang direkonstruksikan dengan pandangan "Indonesia sentris", akan menempatkan banpa Indonesia sebagai dramatic personea dengan peranannya dalam kerangka Indonesia. Hal ini dimaksudkan juga sebagai antithese terhadap sejarah Indonesia yang diwariskan oleh penulis-penulis kolonial yang bersifat "Eropa-sentris" -pada umumnya dan "Neerlandosentris" khususnya. Selanjutnya dari pencatatan ini tentu juga diharapkan akan diperoleh tidak hanya fakta-fakta, tetapi juga pengertian-pengertian serta ciri-ciri pokok dari berbagai peristiwa sejarah yang terjadi pada masa lampau di negara kita yang bersifat Bhinneka Tungal Ika