With the development of cities, urban congestion is nearly an unavoidable problem for almost every large-scale city. Road planning is an effective means to alleviate urban congestion, which is a classical non-deterministic polynomial time (NP) hard problem, and has become an important research hotspot in recent years. A K-means clustering algorithm is an iterative clustering analysis algorithm that has been regarded as an effective means to solve urban road planning problems by scholars for the past several decades; however, it is very difficult to determine the number of clusters and sensitively initialize the center cluster. In order to solve these problems, a novel K-means clustering algorithm based on a noise algorithm is developed to capture urban hotspots in this paper. The noise algorithm is employed to randomly enhance the attribution of data points and output results of clustering by adding noise judgment in order to automatically obtain the number of clusters for the given data and initialize the center cluster. Four unsupervised evaluation indexes, namely, DB, PBM, SC, and SSE, are directly used to evaluate and analyze the clustering results, and a nonparametric Wilcoxon statistical analysis method is employed to verify the distribution states and differences between clustering results. Finally, five taxi GPS datasets from Aracaju (Brazil), San Francisco (USA), Rome (Italy), Chongqing (China), and Beijing (China) are selected to test and verify the effectiveness of the proposed noise K-means clustering algorithm by comparing the algorithm with fuzzy C-means, K-means, and K-means plus approaches. The compared experiment results show that the noise algorithm can reasonably obtain the number of clusters and initialize the center cluster, and the proposed noise K-means clustering algorithm demonstrates better clustering performance and accurately obtains clustering results, as well as effectively capturing urban hotspots.

Théorie et pratique de la traduction en Chine Volume 44, numéro 1, mars 1999 URI : id.erudit.org/iderudit/003677ar

Tertiary-level interpreter training and education have developed rapidly in China, and over 200 undergraduate and over 200 postgraduate T&I programs have been launched over the past decade. Despite the rapid development, there has been no standardized framework allowing for the reliable and valid measurement of interpreting competence in China. Against this background, the China Standards of English (CSE), which are the Chinese counterpart to the Common European Framework of Reference (CEFR), were unveiled in 2018 after 4 years of government-funded research and validation. One vital component of the CSE is the descriptor-referenced interpreting competence scales. This article provides a systematic account of the design, development, and validation of the interpreting competence scales in China. Within the CSE, the construct of interpreting competence was defined according to an interactionist approach. It not only encompasses cognitive abilities, interpreting strategies, and subject-matter knowledge but also considers performance in typical communicative settings. Based on the construct definition, a corpus of relevant descriptors was built from three main sources, including: (a) interpreting training syllabuses, curricular frameworks, rating scales, and professional codes of conduct; (b) previous literature on interpreting performance assessment, competence development, and interpreter training and education; and (c) exemplar-generation data on assessing interpreting competence and typical interpreting activities, which were collected from interpreting professionals, trainers, and trainees. The corpus contains 9,208 descriptors of interpreting competence. A mixed-method survey was then conducted to analyze, scale, and validate the descriptors among 30,682 students, 5,787 teachers, and 139 interpreting professionals from 28 provinces, municipalities, and regions in China. The finalized set included 369 descriptors that reference interpreting competence. The CSE-Interpreting Competence Scales with theoretically and empirically based descriptors represent a major effort in research on interpreting competence and its assessment, and they have significant potential to be applied widely in interpreting training, research, and assessment.

The purpose of this article is to evaluate the economic results of the independent hotels in comparison with the chain hotels as well as to propose suggestions for the viability of the lodging industry. The survey took place in Greece concerning the period 2008-2011 and it was conducted via on-line questionnaires among 165 hotel units. The average means of efficiency and profitability indicators of the sampled hotels are benchmarked and the data of 2009 are utilized to further compare their ratios by using ratio analysis. Furthermore, ANOVA test is used to conduct mean difference analysis in order to identify the differences among the means along with their associated variables between independent and chain hotels. The main findings of the survey show that, generally, the independent hotels tend to be more profitable than chain hotels. The sector's good practices that have been identified through this study are highlighted as suggestions for the viability of the lodging industry both in Greece and worldwide. Based on the findings of the survey, investors and hotel operators may have a clearer picture of whether it is preferable to invest their funds in the development of an independent hotel or they should turn to chain ownership.

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