Haiyan Wang

The KNN algorithm is one of the most famous algorithms in machine learning and data mining. It does not preprocess the data before classification, which leads to longer time and more errors. To solve the problems, this paper first proposes a PK-means++ algorithm, which can better ensure the stability of a random experiment. Then, based on it and spherical region division, an improved KNNPK+ is proposed. The algorithm can select the center of the spherical region appropriately and then construct an initial classifier for the training set to improve the accuracy and time of classification.

This article primarily explains how China Daily — an exemplary representative of China’s press — modified the disaster discourse, to provide coverage of the Wenchuan earthquake in 2008, through the exclusion of rational thought and in doing so created a people-centred myth. The secondary aim is to understand why the need for legitimacy was the reason behind the Government’s decision to allow media coverage of the disaster. Critical linguistics and critical discourse analysis underpin the study. The article concludes that the Government’s aim in ‘opening up’ access to the media to provide coverage was to provide a public relations exercise, nationally and globally, of the Communist Party of China’s governance capabilities.

BackgroundDepression and alcohol dependence are among the most prevalent psychiatric disorders that commonly co-occur. Therefore, gaining a better grasp of factors related to this comorbidity is particularly interesting for clinicians. Past research has highlighted the significant role that time perspective and family history of alcohol dependence play in the occurrence of depression and AD. However, much remains unexplored in the understanding of the association between them. This study explored how temporal profile and other sociodemographic characteristics of patients diagnosed with AD impact the severity of depression and AD in them.MethodsThis study was multi-centered, including 381 patients. Cross-sectional information was collected from both inpatient and outpatient psychiatric clinics in China. Data were acquired using validated self-report scales, including Michigan Alcoholism Screening Test, Zung Self-Rating Depression Scale, and Zimbardo Time Perspective Inventory-Chinese version. Multiple linear regression analyzes were conducted to control social demographic variables and construct prediction models to inspect the influence factors of variables. Moderation models were constructed to inspect further interplay between variables using hierarchical regression and PROCESS Macro.ResultsResults showed that of all the patients in Chinese psychiatry clinics diagnosed with AD according to the International Classification of Diseases-10, 59.9% met the criteria of depression according to the questionnaire, and time perspective was correlated with the severity of depression. Furthermore, using regression analysis, we found that time perspective and depression could predict AD severity. The moderating role of a past negative time perspective and FH was confirmed between depression and AD. We found that, in our study, only in patients with FH and relatively moderate to high scores of past negative time perspective could the severity of depression predict the severity of AD. Therefore, during the treatment and care of patients with AD, their depression level, time perspective score, and FH should be considered.