1,776 research outputs found
Modelling of Rheological Behavior of Self-Compacting Concrete by Discrete Element Method
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Estimating the spatial distribution of soil penetration resistance in a field as a function of water content and bulk de
No full textTaiwan’s International Tourism: A Time Series Analysis with Calendar Effects and Joint Outlier Adjustments
No full textLong-term crustal movement caused by the Chiuchiungkeng Fault in southwestern Taiwan: Constraints from luminescence dating
No full textComparative studies on the induction of muscle contracture in mouse diaphragm and Ca2+ release from sarcoplasmic reticul_TTS.DATE
No full textMalus baccata var. gracilis T. C. Ku
No full text1b. Malus baccata var. gracilis (Rehder) T.C.Ku Figs 7–8 Flora of China 9: 181 (Ku & Spongberg 2003). Malus baccata f. gracilis Rehder, Journal of the Arnold Arboretum 2 (1): 49 (Rehder 1920). – Type : CHINA • Shaanxi, Yenan Fu; 14 May 1919; fl; Purdom 327; type: A [A00026586]! Examined specimens CHINA – Gansu • Heshui; 21 Jul. 1954; fr; Yellow River Investigation Team 163; PE [PE00927499] • Pingliang; 8Aug. 1956; fr; Yellow River Investigation Team 2051; PE [PE00927502] • Yen Kwan; s.d.; fr; Fenzel & Pai 2826; PE. – Qinghai • Xining; 8 May 1990; fl; Z.H. Zhang et al. 5559; HNWP [HNWP160546]. – Shaanxi • Ganquan Laoshan; 10 May 1953; fl; Y.W. Cui 10001; PE [PE00927495] • ibid.; 23 May 1953; fl; Y.W. Cui 10077; PE • Meixian; 15 Oct. 1953; fr; Y.W. Cui 10937; PE. Description Small tree, 4‒6 m high; branches terete, pendulous. Pedicel ca 3 cm long. Petals ca 1.0 × 0.6 cm, white, obovate. Styles 3 or 4. Pome ca 0.7 × 0.8 cm. Distribution China (Gansu, Qinghai, Shaanxi) (Fig. 7). Chromosome number 2n = 34.Published as part of Liu, Jian-quan & Gao, Xin-fen, 2022, A revision of the genus Malus Mill. (Rosaceae), pp. 1-127 in European Journal of Taxonomy 853 on pages 18-19, DOI: 10.5852/ejt.2022.853.2019, http://zenodo.org/record/750137
High performance latent dirichlet allocation for text mining
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Latent Dirichlet Allocation (LDA), a total probability generative model, is a three-tier Bayesian model. LDA computes the latent topic structure of the data and obtains the significant information of documents. However, traditional LDA has several limitations in practical applications. LDA cannot be directly used in classification because it is a non-supervised learning model. It needs to be embedded into appropriate classification algorithms. LDA is a generative model as it normally generates the latent topics in the categories where the target documents do not belong to, producing the deviation in computation and reducing the classification accuracy. The number of topics in LDA influences the learning process of model parameters greatly. Noise samples in the training data also affect the final text classification result. And, the quality of LDA based classifiers depends on the quality of the training samples to a great extent. Although parallel LDA algorithms are proposed to deal with huge amounts of data, balancing computing loads in a computer cluster poses another challenge. This thesis presents a text classification method which combines the LDA model and Support Vector Machine (SVM) classification algorithm for an improved accuracy in classification when reducing the dimension of datasets. Based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN), the algorithm automatically optimizes the number of topics to be selected which reduces the number of iterations in computation. Furthermore, this thesis presents a noise data reduction scheme to process noise data. When the noise ratio is large in the training data set, the noise reduction scheme can always produce a high level of accuracy in classification. Finally, the thesis parallelizes LDA using the MapReduce model which is the de facto computing standard in supporting data intensive applications. A genetic algorithm based load balancing algorithm is designed to balance the workloads among computers in a heterogeneous MapReduce cluster where the computers have a variety of computing resources in terms of CPU speed, memory space and hard disk space
Sixteen Conjoined Divination Inscriptions of the Huang Group
No full text甲骨卜辭綴合促使辭例訊息本身的完整性，亦得以逐漸拼湊出甲骨原樣。本文以卜辭黃組為例，搜羅近來綴合成果共十六則；關於卜辭黃組時代，大抵在帝乙、帝辛時期，此時亦以龜腹甲、胛骨為主要占卜之物，本文十六則綴合中，二例屬龜腹甲，其餘十四例則為胛骨之綴合。且其中五組是在前人的基礎上進行加綴，另外十一組則為本人所新綴，過程中並懷疑前人的一則誤綴，文內將此誤綴的兩版，再重新與其他二版進行綴合。Conjunction of divination inscriptions on oracle bones not only contributes to the completeness of inscription decipherment but also helps to restore oracle bones to their original appearances. The inscriptions of the Huang Group approximately date from the reign of Di Yi and Di Xin [Emperors Yi and Xin], when tortoise plastrons and animals’ scapulae are the main divination tools. This article collects sixteen recently conjoined divination inscriptions of the Huang Group; two of them are incised on tortoise plastrons and the other fourteen on animals’ scapulae. Five of them are the author’s additions to previous scholarly works, while the other eleven are newly conjoined by the author. During the process of conjoining, the author discovers that two divination inscriptions have mistakenly been pieced together by previous scholars and therefore re-conjoins them with other two inscriptions
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