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This study developed two presentation modes of scientific articles and evaluated their usability with user experiments.

Two presentation modes of scientific articles, simply referred to as “genre presentation mode” and “argument presentation mode”, were constructed based on their genre structure and argument structure respectively. Their usability was evaluated by being compared against the existing RichHTML presentation mode in the experiments using eye-tracking and questionnaire methods.

The participants who were going to find the specific information of scientific articles rated the genre presentation mode higher than they did with either the argument or the RichHTML presentation mode for effectiveness. In contrast, those who were going to understand the general idea of scientific articles rated both the genre and argument presentation mode higher than they did with the RichHTML mode. In terms of efficiency, the participants took less reading time when the articles of non-native language were presented with the genre mode than they did when the articles were presented with the argument mode. When reading the articles in native language to understand the general idea, the participants took less reading time for the articles presented with the argument mode than they did for the articles presented with the genre mode. In comparison, they took less reading time when the articles were presented with the argument mode if they were going to find specific information. For satisfaction, the genre presentation mode was more popular than the argument mode and the RichHTML mode. However, the participants were less satisfied with the argument presentation mode than the other two when reading in native language and intending to find specific information.

The two presentation modes of scientific articles are found to improve the accuracy of information acquisition, shorten the total reading time and be more acceptable by readers.

The purpose of this paper is to semantically annotate the content of digital images with the use of Semantic Web technologies and thus facilitate retrieval, integration and knowledge discovery.

After a review and comparison of the existing semantic annotation models for images and a deep analysis of the characteristics of the content of images, a multi-dimensional and hierarchical general semantic annotation framework for digital images was proposed. On this basis, taking histories images, advertising images and biomedical images as examples, by integrating the characteristics of images in these specific domains with related domain knowledge, the general semantic annotation framework for digital images was customized to form a domain annotation ontology for the images in a specific domain. The application of semantic annotation of digital images, such as semantic retrieval, visual analysis and semantic reuse, were also explored.

The results showed that the semantic annotation framework for digital images constructed in this paper provided a solution for the semantic organization of the content of images. On this basis, deep knowledge services such as semantic retrieval, visual analysis can be provided.

The semantic annotation framework for digital images can reveal the fine-grained semantics in a multi-dimensional and hierarchical way, which can thus meet the demand for enrichment and retrieval of digital images.

This paper aims to reorganize the relevant information of Chinese ancient architectures with the use of Semantic Web technologies and thus facilitate its deep discovery and usage.

This paper proposes an ontology model for Chinese ancient architectures based on architectural narratives theory. To verify the availability of the ancient architecture ontology, we designed and implemented three experiments, including semantic retrieval based on SPARQL query, semantic reasoning with the use of Jena reasoner and visual analysis based on the Chinese Online Digital Humanities Resources Platform.

The proposed ontology provided a solution for the semantic annotation of the unstructured information of Chinese ancient architectures. On this basis, deep knowledge services such as semantic retrieval, semantic reasoning and visual analysis can be provided.

The proposed semantic model of ancient architectures can effectively improve the organization and access quality of the semantic content of Chinese ancient architectures.

This paper focuses on the semantic modelling for the unstructured information of Chinese ancient architectures to semantically describe the related entities (e.g. persons, events, places and times) and uncover their relationships, and thus it made contribution to the deep semantic annotations on ancient architectures.

The purpose of this research is to develop a method for automatic construction of multi‐document summaries of sets of news articles that might be retrieved by a web search engine in response to a user query.

Based on the cross‐document discourse analysis, an event‐based framework is proposed for integrating and organizing information extracted from different news articles. It has a hierarchical structure in which the summarized information is presented at the top level and more detailed information given at the lower levels. A tree‐view interface was implemented for displaying a multi‐document summary based on the framework. A preliminary user evaluation was performed by comparing the framework‐based summaries against the sentence‐based summaries.

In a small evaluation, all the human subjects preferred the framework‐based summaries to the sentence‐based summaries. It indicates that the event‐based framework is an effective way to summarize a set of news articles reporting an event or a series of relevant events.

Limited to event‐based news articles only, not applicable to news critiques and other kinds of news articles. A summarization system based on the event‐based framework is being implemented.

Multi‐document summarization of news articles can adopt the proposed event‐based framework.

An event‐based framework for summarizing sets of news articles was developed and evaluated using a tree‐view interface for displaying such summaries.

The purpose of this paper is to lay a theoretical foundation for identifying operational information units for library and information professional activities in the context of scholarly communication.

The study adopts a deduction-verification approach to formulate a typology of units for scholarly information. It first deduces possible units from an existing conceptualization of information, which defines information as the combined product of data and meaning, and then tests the usefulness of these units via two empirical investigations, one with a group of scholarly papers and the other with a sample of scholarly information users.

The results show that, on defining an information unit as a piece of information that is complete in both data and meaning, to such an extent that it remains meaningful to its target audience when retrieved and displayed independently in a database, it is then possible to formulate a hierarchical typology of units for scholarly information. The typology proposed in this study consists of three levels, which in turn, consists of 1, 5 and 44 units, respectively.

The result of this study has theoretical implications on both the philosophical and conceptual levels: on the philosophical level, it hinges on, and reinforces the objective view of information; on the conceptual level, it challenges the conceptualization of work by IFLA’s Functional Requirements for Bibliographic Records and Library Reference Model but endorses that by Library of Congress’s BIBFRAME 2.0 model.

It calls for reconsideration of existing operational units in a variety of library and information activities.

The study strengthens the conceptual foundation of operational information units and brings to light the primacy of “one work” as an information unit and the possibility for it to be supplemented by smaller units.

This paper proposes an improved algorithm to compute selective harmonics elimination pulse width modulation (SHEPWM) angles, based on the Newton‐Raphson (NR) iteration for cascaded multilevel inverter (CMI).

Newton Raphson (NR) is a very popular numerical method for transcendental equations that lack analytical solutions. It has been successfully used to compute the angles for selective harmonics elimination pulse width modulation (SHEPWM) schemes. Despite its effectiveness, NR has not been used for SHEPWM with cascaded multilevel inverter (CMI) structure with equal and non‐equal DC voltage sources. It is known that for CMI, inappropriate selection of initial angles causes long‐iteration time and possibly non‐convergence takes place. The computational difficulty is compounded by the fact that the SHEPWM switching angles need to be correctly sequenced, i.e. each angle must be assigned to the correct output voltage level of the CMI. In this work, an attempt is made to reduce the iteration time and to resolve the non‐convergence problem. The main idea is to relax the switching angle constraint by placing the switching angle sequencing outside the main loop of NR iteration. This allows for the program to run more freely and able to generate more possible solutions for the switching angles. Then these angles are selected to fulfill the requirements of multilevel sequencing. The performance of the proposed technique will be compared with the standard NR for CMI with equal and non‐equal DC sources. The latter case is quite common for CMI with renewable energy applications because the sources normally have different voltage levels.

Using MATLAB simulation, it will be shown that using this scheme, accurate SHEPWM angles can be achieved for a wide range of fundamental components. Furthermore, significant reduction in iteration time to compute the SHEPWM switching angles is achieved.

This paper proposes an improved algorithm to compute SHEPWM angles based on NR iteration.