In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, (...) the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature (GCC) for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions. (shrink)

To solve the problem that traditional trajectory prediction methods cannot meet the requirements of high-precision, multi-dimensional and real-time prediction, a 4D trajectory prediction model based on the backpropagation (BP) neural network was studied. First, the hierarchical clustering algorithm and the k-means clustering algorithm were adopted to analyze the total flight time. Then, cubic spline interpolation was used to interpolate the flight position to extract the main trajectory feature. The 4D trajectory prediction model was based on the BP neural network. It (...) was trained by Automatic Dependent Surveillance – Broadcast trajectory from Qingdao to Beijing and used to predict the flight trajectory at future moments. In this paper, the model is evaluated by the common measurement index such as maximum absolute error, mean absolute error and root mean square error. It also gives an analysis and comparison of the predicted over-point time, the predicted over-point altitude, the actual over-point time and the actual over-point altitude. The results indicate that the predicted 4D trajectory is close to the real flight data, and the time error at the crossing point is no more than 1 min and the altitude error at the crossing point is no more than 50 m, which is of high accuracy. (shrink)

Attention has been theorized as a system comprising three networks that can be estimated reliably by the attention network test ; the three networks are defined as alerting, orienting, and conflict control. The present study aims to identify the attention networks that are crucial for elite shooting and archery athletes and to examine whether mindfulness training can improve elite athletes' attention networks. We compared the performances in ANT between 62 elite athletes from the Chinese national team of shooting and archery (...) and 49 athletes from a provincial team in China. The results indicate three well-functioned attention networks in both groups, but elite athletes in the national team responded faster overall than athletes in the provincial team. The 62 elite athletes in the national team then received mindfulness training with varied periods ranging from 5 to 8 weeks, after which the ANT was re-administered. After mindfulness training, the elite athletes improved in orienting and conflict control networks compared with their pre-training performances. These results suggest that elite shooting and archery athletes in the national team are more efficient in all three attention networks, which means that they are able to reach the alerting state faster, make better use of environmental information, and suppress interference from distractors more efficiently. Moreover, the orienting and conflict control networks of the elite shooting and archery athletes can be improved by mindfulness training. We conclude that mindfulness practice should be considered as a useful addition to daily training for shooting and archery athletes. (shrink)

Through structural analysis of 8-year tag networks from online knowledge-sharing platforms, this study finds that, with the scale of tag networks growing quickly, the growth trend of number edges indicates that tag network follows densification law. The clustering coefficient and the average shortest path of the network show that the rapid growth of network size does not bring about the compartmentalization of the knowledge network, and the degree distribution of tag networks shows a truncated power-law distribution. According to the structural (...) characteristics of the tag network, this study proposes a tag network model based on the BA model. Based on the preference attachment, the triadic closure mechanism is employed to construct the edges between the old nodes, which revises the limitation that the BA model only connects edges between old and new nodes. The results show that the simulation model matches the actual tag network structure well. The generation mechanism of the tag network model provides a reference for understanding the knowledge construction process of the online knowledge-sharing platform to a certain extent. (shrink)

This paper presents a bioinspired lower extremity exoskeleton robot. The proposed exoskeleton robot can be adjusted in structure to meet the wearer’s height of 150–185 cm and has a good gait stability. In the gait control part, a method of identifying different locomotion modes is proposed; five common locomotion modes are considered in this paper, including sitting down, standing up, level-ground walking, ascending stairs, and descending stairs. The identification is depended on angle information of the hip, knee, and ankle joints. (...) A deep locomotion mode identification model based on long-short term memory architecture is proposed in this paper for exploiting the angle data. We conducted two experiments to verify the effectiveness of the proposed method. Experimental results show that the DLMIM is capable of learning inherent characteristics of joint angles and achieves more accurate identification than the other models. The last experiment demonstrates that the DLMIM can recognize transitions between different locomotion modes in time and the real-time performance varies with each individual. (shrink)

This study investigated the role of theme-based blocks play in enhancing Chinese children’s language capacity with a quasi-experiment. Altogether 61 young children were assigned to the experiment group and the control group. The experiment group was engaged in a 12-week theme-based block play intervention programs, whereas the control group received no interventions but free block play during the parallel time sessions. All the children were tested with the Language Assessment for Preschool Children before and after the intervention. The ANCOVA results (...) indicated that the experimental group significantly improved in LAPC test, whereas the control group showed no significant change. The educational implications of these findings are discussed. (shrink)

Cognitive systems face a tension between stability and plasticity. The maintenance of long‐term representations that reflect the global regularities of the environment is often at odds with pressure to flexibly adjust to short‐term input regularities that may deviate from the norm. This tension is abundantly clear in speech communication when talkers with accents or dialects produce input that deviates from a listener's language community norms. Prior research demonstrates that when bottom‐up acoustic information or top‐down word knowledge is available to disambiguate (...) speech input, there is short‐term adaptive plasticity such that subsequent speech perception is shifted even in the absence of the disambiguating information. Although such effects are well‐documented, it is not yet known whether bottom‐up and top‐down resolution of ambiguity may operate through common processes, or how these information sources may interact in guiding the adaptive plasticity of speech perception. The present study investigates the joint contributions of bottom‐up information from the acoustic signal and top‐down information from lexical knowledge in the adaptive plasticity of speech categorization according to short‐term input regularities. The results implicate speech category activation, whether from top‐down or bottom‐up sources, in driving rapid adjustment of listeners' reliance on acoustic dimensions in speech categorization. Broadly, this pattern of perception is consistent with dynamic mapping of input to category representations that is flexibly tuned according to interactive processing accommodating both lexical knowledge and idiosyncrasies of the acoustic input. (shrink)

In this study, we aimed to address three comments proposed by Ogihara on a recent study where we found that unique names in China have become increasingly popular from 1950 to 2009. Using a large representative sample of Chinese names, we replicated the increase in uniqueness of Chinese names from 1920 to 2005, especially since the 1970s, with multiple uniqueness indices based on name-character frequency and name-length deviation. Over the years, Chinese characters that are rare in daily life or naming (...) practice were more often used in given names, and the length of given names became more deviant from typical practice. Taken together, these findings not only reconfirmed the increasing prevalence of unique names but also demonstrated the validity of various indices in assessing name uniqueness in China. (shrink)

The signals in numerous complex systems of engineering can be regarded as nonlinear parameter trend with noise which is identically distributed random signals or deterministic stationary chaotic signals. The commonly used methods for parameter estimation of nonlinear trend in signals are mainly based on least squares. It can cause inaccurate estimation results when the noise is complex. This paper proposes a calibration method for this issue in the case of single parameter via nonstationarity measure from the perspective of the stationarity (...) of residual sequence. Some numerical studies are conducted for validation. Results of numerical studies show that the proposed calibration method performs well for various models with different noise strengths and types and can significantly improve the accuracy of initial estimates obtained by least squares method. This is the first time that the nonstationarity measure is applied to the parameter calibration. All these results will be a guide for future studies of other parameter calibrations. (shrink)

Cooperative innovation has become a critical method for freight logistics firms in supply chain management. The previous study has proved that relational embeddedness has a positive effect on service innovation performance. However, the influence of organizational learning capacity has been widely ignored. This study focuses on explaining the mechanism of OLC on the relationship between RE and innovation performance of freight logistics service. Firstly, a theoretical model is constructed based on Social Network Theory, and four research hypotheses are presented. Secondly, (...) a sample of 236 respondents from freight logistics firms in China is analyzed to test the hypotheses. Finally, several management implications and recommendations are suggested. The research results demonstrate that both RE and OLC have positive effects on IPFLS. Meanwhile, OLC partially mediates the relationship between RE and IPFLS. The findings provide practical guidance for managers to strengthen the relationship with partners and enhance OLC. (shrink)

Customers are skeptical about shopping online because e-commerce environments are typically considered impersonal. To assure product quality and to enhance customer proclivity in such environments, post-sale services may be considered to alleviate customers’ skepticism. Therefore, this study’s objective is to investigate the role of an online retailer’s post-sale services on customers’ attitudinal and behavioral aspects. Structural equation modeling is applied to data collected through an online survey answered by 409 online customers of jd.com. Research findings show that product return, exchange, (...) and maintenance services are strongly predictive of online customer satisfaction, and satisfaction significantly impacts customer trust. Both customer satisfaction and trust, as indicators of relationship quality, further mediate the links between product return, exchange, and maintenance services and online customer repurchase intention. In addition, differences between male and female customers were found in various aspects of online retailers’ product return, exchange, and maintenance services. This is the first empirical study that not only examines the influence of all three dimensions of online retailers’ post-sale services on customers’ online shopping perceptions and decisions, but also considers differences between male and female customers. Finally, this research provides theoretical and managerial implications based on conceptual and empirical evidence. (shrink)

The optimization of high-dimensional functions is an important problem in both science and engineering. Wolf pack algorithm is a technique often used for computing the global optimum of a multivariable function. In this paper, we develop a new wolf pack algorithm that can accurately compute the optimal value of a high-dimensional function. First, chaotic opposite initialization is designed to improve the quality of initial solution. Second, the disturbance factor is added in the scouting process to enhance the searching ability of (...) wolves, and an adaptive step length is designed to enhance the global searching ability to prevent wolves from falling into the local optimum effectively. A set of standard test functions are selected to test the performance of the proposed algorithm, and the test results are compared with other algorithms. The high-dimensional and ultrahigh-dimensional functions are tested. The experimental results show that the proposed algorithm features in good global convergence, high accuracy calculation, strong robustness, and excellent performance in high-dimensional functions. (shrink)

Poverty alleviation through tourism is an important way for China to achieve targeted poverty alleviation and win the battle of poverty alleviation. As a region with deep poverty and great difficulty in poverty alleviation, whether tourism development has injected key impetus into ethnic minority areas needs to be tested by both qualitative analysis and quantitative measurement. This paper takes eight ethnic provinces in China as an example to conduct an empirical study. Based on the Data Envelopment Analysis -BCC model and (...) Malmquist index, it evaluates the tourism investment and tourism poverty alleviation efficiency of the ethnic regions in the two stages of tourism poverty alleviation, and analyzes them by classification. The results of the study show: The pure technical efficiency in the first stage is relatively high, but the total factor productivity of each region is declining; The pure technical efficiency in the second stage is also relatively high, but the scale efficiency is low, and the change rate of total factor productivity of the provinces in China has increased significantly; The “double high” type includes Guangxi, Inner Mongolia, and Guizhou, and the “double low” type includes Qinghai, Yunnan, Tibet, Xinjiang, and Ningxia. The results of the study generally show that tourism poverty alleviation has brought about the improvement of the living standards of residents and the development of local economy, but the efficiency of tourism poverty alleviation needs to be improved. On this basis, the article puts forward corresponding improvement measures, in order to further help the ethnic minority areas get rid of poverty in a comprehensive way by promoting the efficient and sustainable development of tourism. (shrink)

The interpretability of AI is just as important as its performance. In the LegalAI field, there have been efforts to enhance the interpretability of models, but a trade-off between interpretability and prediction accuracy remains inevitable. In this paper, we introduce a novel framework called LK-IB for compulsory measure prediction (CMP), one of the critical tasks in LegalAI. LK-IB leverages Legal Knowledge and combines an Interpretable model and a Black-box model to balance interpretability and prediction performance. Specifically, LK-IB involves three steps: (...) (1) inputting cases into the first module, where first-order logic (FOL) rules are used to make predictions and output them directly if possible; (2) sending cases to the second module if FOL rules are not applicable, where a case distributor categorizes them as either “simple” or “complex“; and (3) sending simple cases to an interpretable model with strong interpretability and complex cases to a black-box model with outstanding performance. Experimental results demonstrate that the LK-IB framework provides more interpretable and accurate predictions than other state-of-the-art models. Given that the majority of cases in LegalAI are simple, the idea of model combination has significant potential for practical applications. (shrink)

This study investigates the internationalization of small family businesses by classifying the effects of external socioemotional wealth vs. internal socioemotional wealth. The study involved 2,704 small family businesses in China, and the results support the hypothesis that family reputation has a positive effect on internationalization, while family involvement has a negative effect on internationalization. Moreover, entrepreneurial spirit reinforces the positive effect of family reputation on internationalization and enhances the negative relationship between family involvement and internationalization. This study contributes by examining (...) the effect of entrepreneurial spirit as a potential balancing factor for the paradoxical influence of internal vs. external socioemotional wealth. (shrink)

Aiming at the problem of insufficient health monitoring of the elderly in the existing home care system, this paper designs a health information analysis and early warning system based on the Internet of Things technology, which can monitor the physiological data of the elderly in real time. It also can be based on the elderly real-time monitoring data, physical examination data, and other types of health data, which can be used to predict diseases, so as to achieve “early detection and (...) early treatment” of diseases. First, analyse and design the architecture and content of the home care monitoring system based on the Internet of Things. Secondly, based on the collected heart rate, blood pressure, and three-axis acceleration information of the elderly, it is analysed to determine whether the elderly are in danger of falling, and the designed system is used for early warning. Finally, this paper analyses the prediction algorithm theory of the disease prediction module in the health monitoring software of the home care system. In order to improve the accuracy of prediction, the DS evidence theory is used to optimize the traditional BP neural network algorithm and conduct experimental tests. The test results show that the health information analysis and early warning software of the home care system meet actual needs and achieve the expected goals. (shrink)

The Universal Space–Time Mapping Hypothesis suggests that temporal expression is based on spatial metaphor for all human beings. This study examines its applicability in the Chinese language using the data elicited from the Early Childhood Mandarin Corpus, which collected the utterances produced by 168 Mandarin-speaking preschoolers in a semistructured play context. The unique pair of Chinese words, qian and hou, which can be used to express either time or space in daily communication, was the unit of analysis. The results indicated (...) that: there was a significant age effect in the production of “qian/hou,” indicating that the period before the age of 4.5 may be critical for the development of temporal and spatial expression; the pair was produced to express time much earlier than space, indicating that the expression of time might not necessarily be based on the spatial metaphor; and the pair was used more frequently to express time than space by the preschoolers, thus challenging the hypothesis. (shrink)

This article supplements the article by Fubin Yang in vol. 39 (2010) of this journal. The goal is to account for the recent surge of interest in process thought in China.

Li Bai es un poeta chino relevante en toda la historia de la poesía china, y actualmente emergen numerosas traducciones sobre sus poesías clásicas, entre ellos, destacan especialmente las traducciones de Chen Guojian y Anne-Hélène Suárez Girard. Son escasas las investigaciones que se han dedicado a la comparación de sus versiones de traducción, y se trata de un enfoque relevante para aprender los métodos recurridos diferentes por traductores de ambos países y ha sido una importante inspiración para los traductores principiantes (...) para sacar las ventajas de ambas partes procurando una mejor traducción. (shrink)

One prominent theory of fairness is John Broome's. This article identifies several problems with Broome's theory but defends Broome's claim that fairness requires the proportionate satisfaction of claims. This article also shows how Broome's conception of fairness is compatible with fairness as comparative desert.

Evidence suggests divergent thinking is the cognitive basis of creative thoughts. Neuroimaging literature using resting-state functional connectivity has revealed network reorganizations during divergent thinking. Recent studies have revealed the changes of network organizations when performing creativity tasks, but such brain reconfigurations may be prolonged after task and be modulated by the trait of creativity. To investigate the dynamic reconfiguration, 40 young participants were recruited to perform consecutive Alternative Uses Tasks for divergent thinking and two resting-state scans were used for mapping (...) the brain reorganizations after AUT. We split participants into high- and low-creative groups based on creative achievement questionnaire and targeted on reconfigurations of the two brain networks: default-mode network and the network seeded at the left inferior frontal gyrus because the between-group difference of AUT-induced brain activation located at the left IFG. The changes of post-AUT RSFCs indicated the prolonged effect of divergent thinking. More specifically, the alterations of RSFCIFG−AG and RSFCIFG−IPL in the high-creative group had positive relationship with their AUT performances, but not found in the low-creative group. Furthermore, the RSFC changes of DMN did not present significant relationships with AUT performances. The findings not only confirmed the possibility of brain dynamic reconfiguration following divergent thinking, but also suggested the distinct IFGN reconfiguration between individuals with different creativity levels. (shrink)

The closed world assumption plays a fundamental role in the theory of deductive databases. On the other hand, multi-valued logics occupy a vast field in non-classical logics. Some questions are better explained and expressed in terms of such logics. To enhance the expressive power and the declarative ability of a deductive database, we extend various CWA formalizations, including the naive CWA, the generalized CWA and the careful CWA, to multi-valued logics. The basic idea is to embed logic formulae into some (...) polynomial ring. The extensions can be applied in a uniform manner to any finitely multi-valued logics. Therefore they have also computational interest. (shrink)

There is no well-built theory on credit risk measurement and decision analysis for financial big data, and an effective and scientific evaluation system for them has not been formed. A review of them can contribute to grasping the abovementioned topics, understanding current issues, analyzing research problems, mastering research challenges, and predicting future research directions. Besides, this paper points out four research directions of credit risk measurement and decision analysis for financial big data. Moreover, this paper can provide some guidance directions (...) and insights for practitioners, researchers, financial institutions, and government departments who have an interest in complex decision-making in big data. (shrink)

吴光辉,湖北省武汉市人,现为厦门大学外文学院讲师,日本语教育研究中心副主任。著有《传统与超越》。.