Results 31 to 40 of about 1,838,518 (246)
Introduction to Geographic and Spatial Approaches in the History of Archaeology
Who studies the historiography of archaeology? Who reads the history of the discipline? Recent years have seen growing interest in the history of archaeology as is reflected in works such as Christenson (1989), Trigger (1989; 2006), Chakrabarti (1988 ...
Neha Gupta, Bernard K Means
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The menu is one of the most fundamental aspects of business continuity in the culinary industry. One of the tools that can be used for menu analysis is menu engineering.
Nina Setiyawati +2 more
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The Lloyd-Max algorithm is a classical approach to perform K-means clustering. Unfortunately, its cost becomes prohibitive as the training dataset grows large. We propose a compressive version of K-means (CKM), that estimates cluster centers from a sketch, i.e. from a drastically compressed representation of the training dataset.
Keriven, Nicolas +3 more
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Advanced Approach of Material Region Detections on Fibre-Reinforced Concrete CT-Scans
Detections of material regions on CT-scans of solids are commonly treated manually by an expert. Although such manual detections have many advantages, some amount of human error is also incorporated. Moreover, expert opinions may vary significantly.
Marek Pecha +4 more
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K-means and fuzzy c-means algorithm comparison on regency/city grouping in Central Java Province
The Human Development Index (HDI) is very important in measuring the country's success as an effort to build the quality of life of people in a region, including Indonesia. The government needs to make groupings based on the needs of a city/district.
Ummu Wachidatul Latifah +2 more
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Deep k-Means: Jointly clustering with k-Means and learning representations
Under consideration at Pattern Recognition ...
Moradi Fard, Maziar +2 more
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Unsupervised K-Means Clustering Algorithm
The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the
Kristina P. Sinaga, Miin-Shen Yang
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A parametric k-means algorithm [PDF]
The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution.
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Penggunaan N-mers Frequency pada Analisis Barisan DNA
Salah satu metode untuk menganalisis barisan DNA adalah menggunaan N-mers Frequency. N-mers Frequency termasuk metode data mining pada barisan DNA, dimana barisan DNA yang merupakan data string “ACGT” akan diubah menjadi data numerik.
Khoirul Umam, Rahmat Sagara
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Diversified noise sources pose great challenges in the engineering of an ANC (active noise control) system design. To solve this problem, this paper proposes an ANC method based on VMD (variational mode decomposition) and Ensemble Learning.
Xiaobei Liang +4 more
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