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The purpose of this paper is to examine the writing development of Hong Kong kindergarten students over 12 months. They attended 18 kindergartens territory-wide and were followed from June 2002 to June 2003 for the collection of three waves of teacher-rated data at six-month intervals.

First, the construct validity of the translated and culturally adapted version of Morrow’s (2012) checklist which assesses writing development was confirmed, considering that the students attended Hong Kong kindergartens who wrote in the Chinese language. The multilevel analysis, which employed corrected measures captured through Wolfe and Chiu’s (1999a, 1999b) five-step Rasch scaling method for a common frame of reference, estimated the effects of the factors, namely, student age, gender, class level and schools.

The children’s progress over the second six months was also apparently much smaller than the first SIX months for this cohort. The dramatic slow-down in the second six-month period for both cohorts might be partly attributed to the peculiar arrangement of schooling at that time.

The recommendation from this study is that random sampling and student test scores on writing need to be taken for the identification of the general trend of young children’s writing development in Hong Kong, as well as other Chinese communities alike.

The profile of the student’s emergent writing development at each six-month follow-up and over the 12 months was explored. Differences between the groups based on age, gender, class level and school in terms of student writing development on average were statistically significant.

On-orbit assembly technology is a promising research topic in spaceflight field. For purposes of studying the dynamic performance and reducing weight of an on-orbit assembly satellite structure frame, this paper aims to propose a structural optimization design method based on natural frequency.

The dynamic stability of the satellite under working condition depends on the mechanical properties of the structure matrix. A global structural optimization model is established, with the objective of mass minimization and the constraints of given natural frequencies and given structure requirements. The structural optimization and improvement design method is proposed using sequential quadratic programming calculation.

The optimal result of objective function is effectively obtained, and the best combination of structural geometric parameters is configurated. By analyzing the relationship between the structural variables and optimization parameters, the primary and secondary factors to the mass optimization process of the microsatellite satisfying the dynamic performance requirements are obtained, which improves the effectiveness and accuracy of the system optimization design.

This method can coordinate the relation between satellite vibration stability and weight reduction, which provides an effective way for the optimization design of on-orbit assembly microsatellite. It has reference significance for the similar spacecraft framework structure design.

Customer knowledge from social media can become an important organizational asset. The purpose of this paper is to identify useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers from social media data and facilitate social media-based customer knowledge management.

The authors conducted a case study to analyze people’s online discussion on Twitter regarding laptop brands and manufacturers. After collecting relevant tweets using Twitter search APIs, the authors applied statistical analysis, text mining and sentiment analysis techniques to analyze the social media data set and visualize relevant insights and patterns in order to identify customer knowledge.

The paper identifies useful insights and knowledge from customers and knowledge about customers from social media data. Furthermore, the paper shows how the authors can use knowledge from customers and knowledge about customers to help companies develop knowledge for customers.

This is an original social media analytics study that discusses how to transform large-scale social media data into useful customer knowledge including knowledge for customer, knowledge about customers and knowledge from customers.

Since the implementation of the regulatory inquiry system, research on its impact on information disclosure in the capital market has been increasing. This article focuses on a specific area of study using Chinese annual report inquiry letters as the basis. From a text mining perspective, we explore whether the textual information contained in these inquiry letters can help predict financial restatement behavior of the inquired companies.

Python was used to process the data, nonparametric tests were conducted for hypothesis testing and indicator selection, and six machine learning models were employed to predict financial restatements.

Some text feature indicators in the models that exhibit significant differences are useful for predicting financial restatements, particularly the proportion of formal positive words and stopwords, readability, total word count and certain textual topics. Securities regulatory authorities are increasingly focusing on the accounting and financial aspects of companies' annual reports.

This study explores the textual information in annual report inquiry letters, which can provide insights for other scholars into research methods and content. Besides, it can assist with decision making for participants in the capital market.

We use information technology to study the textual information in annual report inquiry letters and apply it to forecast financial restatements, which enriches the research in the field of regulatory inquiries.

Gaining the precise control over the matter at the nanometre scale is the main leitmotif in a majority of nanoscience oriented research measurements nowadays. The availability of new advanced tools, as a nanoindentation technique, for evaluation of the mechanical properties, seems to be prerequisite for exploitation of the dramatic development in nanoscience and meeting the emerging needs of the industries in new electronic applications. The nanoindentation technique was applied to evaluate the elastic modulus and hardness values as a function of indentation depth. However, in the presented experiment the nanoscale mechanical properties of BaBi₂Nb₂O₉ ceramics have been characterized and compared with the macroscale measurements with macroscale method with the implementation of ultrasound techniques. A draw conclusion indicates that expensive nanoscale characterisation presented here is not fully consisted with the microscale. The reasons of such state of things are widely discussed.

The purpose of this paper is to develop high-performance Au-coated Ag alloy wires (ACAA wires) and demonstrate the effect of Au coating layers on the bonding performance and oxidation resistance for stable and reliable electronic packaging applications.

ACAA wire with a diameter of approximately 25 µm and Au layer thickness of approximately 100 nm were prepared by the continuous casting, plating and wire drawing method. The bonding performance of the ACAA wires were studied through bonding on 3,535 chips. The oxidation resistance of ACAA wires and Ag alloy wires (AA wires) were comparatively studied by means of chemical oxidation tests, accelerated life tests and electrochemical tests systematically.

ACAA wires could form axi-symmetrical spherical free air balls with controllable diameter of 1.5∼2.5 times of the wire diameter after electric flame-off process. The ball shear strength of ACAA wire was higher than that of AA wires. Most importantly, because of the surface Au coating layer, the oxidation resistance of ACAA wires was much enhanced.

ACAA wires with different lengths of heat affected zone were not developed in this study, which limited their application with different loop height requirements.

With higher bonding strength and oxidation resistance, ACAA wires would be a better choice than previous reported AA wire in chip packaging which require high stability and reliability.

This paper provides a kind of novel ACAA wire, which possess the merits of high bonding strength and reliability, and show great potential in electronic packaging applications.

PBO and p-aramids fibers were compared on thermal degradation in TG and DTG experiments, and PBO fiber showed the highest degradation temperature in both air and nitrogen atmosphere. Annealed under high temperature of 100°C, 200°C, 300°C and 400°C for 1.5 hours, the tenacity of these samples all decreased with the temperature, while PBO fiber showed the best tensile retention property. Whereas using the xenon arc light to simulate sunlight irradiated on the PBO and Kevlar samples for different time respectively, PBO showed the worst tensile retention property. In contrast, the p-aramid fibers showed their relatively good mechanical stability when exposed to the simulated sunlight. Therefore, the application of PBO fibers should be careful in the state of sunlight irradiation although PBO has the highest original mechanical and thermal property.

Online customer reviews could shed light into their experience, opinions, feelings, and concerns. To gain valuable knowledge about customers, it becomes increasingly important for businesses to collect, monitor, analyze, summarize, and visualize online customer reviews posted on social media platforms such as online forums. However, analyzing social media data is challenging due to the vast increase of social media data. The purpose of this paper is to present an approach of using natural language preprocessing, text mining and sentiment analysis techniques to analyze online customer reviews related to various hotels through a case study.

This paper presents a tested approach of using natural language preprocessing, text mining, and sentiment analysis techniques to analyze online textual content. The value of the proposed approach was demonstrated through a case study using online hotel reviews.

The study found that the overall review star rating correlates pretty well with the sentiment scores for both the title and the full content of the online customer review. The case study also revealed that both extremely satisfied and extremely dissatisfied hotel customers share a common interest in the five categories: food, location, rooms, service, and staff.

This study analyzed the online reviews from English-speaking hotel customers in China to understand their preferred hotel attributes, main concerns or demands. This study also provides a feasible approach and a case study as an example to help enterprises more effectively apply social media analytics in practice.

With the advancement of social economy, science and technology, nowadays, people face increasingly complex decision-making problems and ever-growing decision-associated information contents. Owing to the unique advantages of the evidence theory, evidence decision flow fits in well with the cognitive process of human beings, which provides us with an effective decision method. However, traditional evidence theories are built upon the one-dimensional evidence recognition framework, which merely reflects the reliability of information determined by evidence source and as such may fail to present the characteristic information of evidence source itself or the information required for the process of determining reliability. This greatly influences processes in decision-making, such as evidence processing and combination. This essay aims to propose a two-dimensional evidence-reasoning theory to address specific decision problems.

This article uses a two-dimensional evidence framework to reflect the process and characteristic information of evidence source based on the traditional evidence framework. As a result, evidence is processed and combined by two-dimensional modified information.

This research is of theoretical and practical significance by extending theoretical connotation, fully utilizing precise evidence information and therefore meeting the requirements of efficient and accurate decision-making performances.

The theory adds a two-dimension to modify and capture evidence on the basis of the traditional evidence framework. This proposal has significant theoretical and practical value to expand evidence theory and provides more accurate use of evidence information, higher efficiency and quality requirements and more precise decision-making.

The paper aims to present a tracked robot comprised of several biochemical sampling instruments and a universal control architecture. In addition, a dynamic motion planning strategy and autonomous modules in sampling tasks are designed and illustrated at length.

Several sampling instruments with position tolerance and sealing property are specifically developed, and a robotic operation system (ROS)-based universal control architecture is established. Then, based on the system, two typical problems in sampling tasks, i.e. arm motion planning in unknown environment and autonomous modules, are discussed, implemented and tested. Inspired by the idea of Gaussian process classification (GPC) and Gaussian process (GP) information entropy, three-dimensional (3D) geometric modeling and arm obstacle avoidance strategy are implemented and proven successfully. Moreover, autonomous modules during sampling process are discussed and realized.

Smooth implementations of the two experiments justify the validity and extensibility of the robot control scheme. Furthermore, the former experiment proves the efficiency of arm obstacle avoidance strategy, while the later one demonstrates the time reduction and accuracy improvement in sampling tasks as the autonomous actions.

The proposed control architecture can be applied to more mobile and industrial robots for its feasible and extensible scheme, and the utility function in arm path planning strategy can also be utilized for other information-driven exploration tasks.

Several specific biochemical sampling instruments are presented in detail, while ROS and Moveit! are integrated into the system scheme, making the robot extensible, achievable and real-time. Based on the control scheme, an information-driven path planning algorithm and automation in sampling tasks are conceived and implemented.