Search results

Digital humanities research platform for biographies of Malaysia personalities (DHRP-BMP) was collaboratively developed by the Research Center for Chinese Cultural Subjectivity in Taiwan, the Federation of Heng Ann Association Malaysia, and the Malaysian Chinese Research Center of Universiti Malaya in this study. Using The Biographies of Malaysia Henghua Personalities as the main archival sources, DHRP-BMP adopted the Omeka S, which is a next-generation Web publishing platform for institutions interested in connecting digital cultural heritage collections with other resources online, as the basic development system of the platform, to develop the functions of close reading and distant reading both combined together as the foundation of its digital humanities tools.

The results of the first-stage development are introduced in this study, and a case study of qualitative analysis is provided to describe the research process by a humanist scholar who used DHRP-BMP to discover the character relationships and contexts hidden in The Biographies of Malaysia Henghua Personalities.

Close reading provided by DHRP-BMP was able to support humanities scholars on comprehending full text contents through a user-friendly reading interface while distant reading developed in DHRP-BMP could assist humanities scholars on interpreting texts from a rather macro perspective through text analysis, with the functions such as keyword search, geographic information and social networks analysis for humanities scholars to master on the character relationships and geographic distribution from personality biographies, thus accelerating their text interpretation efficiency and uncovering the hidden context.

At present, a digital humanities research platform with real-time characters’ relationships analysis tool that can automatically generate visualized character relationship graphs based on Chinese named entity recognition (CNER) and character relationship identification technologies to effectively assist humanities scholars in interpreting characters’ relationships for digital humanities research is still lacking so far. This study thus presents the DHRP-BMP that offers the key features that can automatically identify characters’ names and characters’ relationships from personality biographies and provide a user-friendly visualization interface of characters’ relationships for supporting digital humanities research, so that humanities scholars could more efficiently and accurately explore characters’ relationships from the analyzed texts to explore complicated characters’ relationships and find out useful research findings.

An automatic text annotation system (ATAS) that can collect resources from different databases through Linked Data (LD) for automatically annotating ancient texts was developed in this study to support digital humanities research. It allows the humanists referring to resources from diverse databases when interpreting ancient texts as well as provides a friendly text annotation reader for humanists interpreting ancient text through reading. The paper aims to discuss whether the ATAS is helpful to support digital humanities research or not.

Based on the quasi-experimental design, the ATAS developed in this study and MARKUS semi-ATAS were compared whether the significant differences in the reading effectiveness and technology acceptance for supporting humanists interpreting ancient text of the Ming dynasty’s collections existed or not. Additionally, lag sequential analysis was also used to analyze users’ operation behaviors on the ATAS. A semi-structured in-depth interview was also applied to understand users’ opinions and perception of using the ATAS to interpret ancient texts through reading.

The experimental results reveal that the ATAS has higher reading effectiveness than MARKUS semi-ATAS, but not reaching the statistically significant difference. The technology acceptance of the ATAS is significantly higher than that of MARKUS semi-ATAS. Particularly, the function comparison of the two systems shows that the ATAS presents more perceived ease of use on the functions of term search, connection to source websites and adding annotation than MARKUS semi-ATAS. Furthermore, the reading interface of ATAS is simple and understandable and is more suitable for reading than MARKUS semi-ATAS. Among all the considered LD sources, Moedict, which is an online Chinese dictionary, was confirmed as the most helpful one.

This study adopted Jieba Chinese parser to perform the word segmentation process based on a parser lexicon for the Chinese ancient texts of the Ming dynasty’s collections. The accuracy of word segmentation to a lexicon-based Chinese parser is limited due to ignoring the grammar and semantics of ancient texts. Moreover, the original parser lexicon used in Jieba Chinese parser only contains the modern words. This will reduce the accuracy of word segmentation for Chinese ancient texts. The two limitations that affect Jieba Chinese parser to correctly perform the word segmentation process for Chinese ancient texts will significantly affect the effectiveness of using ATAS to support digital humanities research. This study thus proposed a practicable scheme by adding new terms into the parser lexicon based on humanists’ self-judgment to improve the accuracy of word segmentation of Jieba Chinese parser.

Although some digital humanities platforms have been successfully developed to support digital humanities research for humanists, most of them have still not provided a friendly digital reading environment to support humanists on interpreting texts. For this reason, this study developed an ATAS that can automatically retrieve LD sources from different databases on the Internet to supply rich annotation information on reading texts to help humanists interpret texts. This study brings digital humanities research to a new ground.

This study proposed a novel ATAS that can automatically annotate useful information on an ancient text to increase the readability of the ancient text based on LD sources from different databases, thus helping humanists obtain a deeper and broader understanding in the ancient text. Currently, there is no this kind of tool developed for humanists to support digital humanities research.

Digital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study develops a character social network relationship map tool (CSNRMT) that can semi-automatically assist digital humanists through human-computer interaction to more efficiently and accurately explore the character social network relationships from Chinese ancient texts for useful research findings.

With a counterbalanced design, semi-structured in-depth interview, and lag sequential analysis, a total of 21 research subjects participated in an experiment to examine the system effectiveness and technology acceptance of adopting the ancient book digital humanities research platform with and without the CSNRMT to interpret the characters and character social network relationships.

The experimental results reveal that the experimental group with the CSNRMT support appears higher system effectiveness on the interpretation of characters and character social network relationships than the control group without the CSNRMT, but does not achieve a statistically significant difference. Encouragingly, the experimental group with the CSNRMT support presents remarkably higher technology acceptance than the control group without the CSNRMT. Furthermore, use behaviors analyzed by lag sequential analysis reveal that the CSNRMT could assist digital humanists in the interpretation of character social network relationships. The results of the interview present positive opinions on the integration of system interface, smoothness of operation, and external search function.

Currently, the system effectiveness of exploring the character social network relationships from texts for useful research findings by using the CSNRMT developed in this study will be significantly affected by the accuracy of recognizing character names and character social network relationships from Chinese ancient texts. The developed CSNRMT will be more practical when the offered information about character names and character social network relationships is more accurate and broad.

This study develops an ancient book digital humanities research platform with an emerging CSNRMT that provides an easy-to-use real-time interaction interface to semi-automatically support digital humanists to perform digital humanities research with the need of exploring character social network relationships.

At present, a real-time social network analysis tool to provide a friendly interaction interface and effectively assist digital humanists in the digital humanities research with character social networks analysis is still lacked. This study thus presents the CSNRMT that can semi-automatically identify character names from Chinese ancient texts and provide an easy-to-use real-time interaction interface for supporting digital humanities research so that digital humanists could more efficiently and accurately establish character social network relationships from the analyzed texts to explore complicated character social networks relationship and find out useful research findings.

Developing attention-aware systems and interfaces based on eye tracking technology could revolutionize mainstream human–computer interaction to make the interaction between human beings and computers more intuitive, effective and immersive than can be achieved traditionally using a computer mouse. This paper aims to propose an eye-controlled interactive reading system (ECIRS) that uses human eyes instead of the traditional mouse to control digital text to support screen-based digital reading.

This study uses a quasi-experimental design to examine the effects of an experimental group and a control group of learners who, respectively, used the ECIRS and a mouse-controlled interactive reading system (MCIRS) to conduct their reading of two types of English-language text online – pure text and Q&A-type articles on reading comprehension, cognitive load, technology acceptance, and reading behavioural characteristics. Additionally, the effects of learners with field-independent (FI) and field-dependence (FD) cognitive styles who, respectively, used the ECIRS and MCIRS to conduct their reading of two types of English-language text online – pure text and Q&A-type articles on reading comprehension are also examined.

Analytical results reveal that the reading comprehension of learners in the experimental group significantly exceeded those in the control group for the Q&A article, but the difference was insignificant for the pure text article. Moreover, the ECIRS improved the reading comprehension of field-independent learners more than it did that of field-dependent learners. Moreover, neither the cognitive loads of the two groups nor their acceptance of the technology differed significantly, whereas the reading time of the experimental group significantly exceeded that of the control group. Interestingly, for all articles, the control group of learners read mostly from top to bottom without repetition, whereas most of the learners in the experimental group read most paragraphs more than once. Clearly, the proposed ECIRS supports deeper digital reading than does the MCIRS.

This study proposes an emerging ECIRS that can automatically provide supplementary information to a reader and control a reading text based on a reader’s eye movement to replace the widely used mouse-controlled reading system on a computer screen to effectively support digital reading for English language learning. The implications of this study are that the highly interactive reading patterns of digital text with ECIRS support increase motivation and willingness to learn while giving learners a more intuitive and natural reading experience as well as reading an article online with ECIRS support guides learners’ attention in deeper digital reading than does the MCIRS because of simultaneously integrating perceptual and cognitive processes of selection, awareness and control based on human eye movement.

A makerspace has recently been identified as an essential learning field for cultivating students’ creative and thinking abilities. Creating a makerspace service within a university library is vital, as it fosters innovation, interdisciplinary learning, practical skills, entrepreneurship and career readiness while transforming the library into a dynamic centre for hands-on education and collaboration. Nevertheless, the wide-ranging functions and uses of makerspace equipment can potentially lead to a situation where librarians are overwhelmed by their duties due to manpower constraints. Therefore, this study aims to develop a novel game-based augmented reality navigation system (GARNS) based on the Octalysis gamification framework and scaffolding theory to support makerspace user education, hoping to promote learners’ learning motivation and their immersive experience and to enhance the learning performance of makerspace user education.

With a true experimental research method, 24 grade 11 students from a high school in Keelung City, Taiwan, were recruited to participate in the experiment on makerspace user education. Among them, ten students were randomly assigned to the experimental group using the GARNS and the other seven students were randomly assigned to a control group using the Web navigation system. The remaining seven students were assigned to a second control group using the narrative guided tour with a librarian to conduct makerspace user education.

Analytical results show that learners can achieve significant learning effectiveness using the GARNS, Web navigation system or traditional narrative guided tour with a librarian for makerspace user education. There were no significant differences in learning effectiveness and motivation neither between the GARNS group and the narrative guided tour with a librarian group nor between the Web navigation system group and the narrative guided tour with a librarian group. However, there were significant differences in learning effectiveness and motivation in terms of the value and expectation dimensions of learning motivation between the GARNS group and the Web navigation system group, and the GARNS group was significantly better than the Web navigation system group.

The study’s practical implication on makerspace user education is to reduce the manpower of a university library with makerspace services by the proposed GARNS that can offer a practical solution to enhance the learning effectiveness and motivation of makerspace through immersive game-based autonomous learning. Additionally, the study’s theoretical contribution lies in its innovative combination of game-based learning and scaffolding theory, while its practical significance stems from its potential to revolutionize makerspace user education, enhance motivation and performance and influence the broader landscape of educational technology.

This study combines game-based learning with augmented reality tools to develop a novel GARNS, which provides an innovative and effective learning tool suitable for the characteristics of makerspace and contributes to promoting makerspace user education and diversified learning modes. Additionally, most interviewees believed that using GARNS for educating makerspace users could assist them in consistently evaluating, choosing and discovering educational tasks in a library makerspace. This study contributes to promoting the popularization of makerspace user education.

With the rapid development of digital humanities, some digital humanities platforms have been successfully developed to support digital humanities research for humanists. However, most of them have still not provided a friendly digital reading environment and practicable social network analysis tool to support humanists on interpreting texts and exploring characters’ social network relationships. Moreover, the advancement of digitization technologies for the retrieval and use of Chinese ancient books is arising an unprecedented challenge and opportunity. For these reasons, this paper aims to present a Chinese ancient books digital humanities research platform (CABDHRP) to support historical China studies. In addition to providing digital archives, digital reading, basic search and advanced search functions for Chinese ancient books, this platform still provides two novel functions that can more effectively support digital humanities research, including an automatic text annotation system (ATAS) for interpreting texts and a character social network relationship map tool (CSNRMT) for exploring characters’ social network relationships.

This study adopted DSpace, an open-source institutional repository system, to serve as a digital archives system for archiving scanned images, metadata, and full texts to develop the CABDHRP for supporting digital humanities (DH) research. Moreover, the ATAS developed in the CABDHRP used the Node.js framework to implement the system’s front- and back-end services, as well as application programming interfaces (APIs) provided by different databases, such as China Biographical Database (CBDB) and TGAZ, used to retrieve the useful linked data (LD) sources for interpreting ancient texts. Also, Neo4j which is an open-source graph database management system was used to implement the CSNRMT of the CABDHRP. Finally, JavaScript and jQuery were applied to develop a monitoring program embedded in the CABDHRP to record the use processes from humanists based on xAPI (experience API). To understand the research participants’ perception when interpreting the historical texts and characters’ social network relationships with the support of ATAS and CSNRMT, semi-structured interviews with 21 research participants were conducted.

An ATAS embedded in the reading interface of CABDHRP can collect resources from different databases through LD for automatically annotating ancient texts to support digital humanities research. It allows the humanists to refer to resources from diverse databases when interpreting ancient texts, as well as provides a friendly text annotation reader for humanists to interpret ancient text through reading. Additionally, the CSNRMT provided by the CABDHRP can semi-automatically identify characters’ names based on Chinese word segmentation technology and humanists’ support to confirm and analyze characters’ social network relationships from Chinese ancient books based on visualizing characters’ social networks as a knowledge graph. The CABDHRP not only can stimulate humanists to explore new viewpoints in a humanistic research, but also can promote the public to emerge the learning interest and awareness of Chinese ancient books.

This study proposed a novel CABDHRP that provides the advanced features, including the automatic word segmentation of Chinese text, automatic Chinese text annotation, semi-automatic character social network analysis and user behavior analysis, that are different from other existed digital humanities platforms. Currently, there is no this kind of digital humanities platform developed for humanists to support digital humanities research.

Collaboratively annotating digital texts allow users to add valued information, share ideas and create knowledge. Most importantly, annotated content can help users obtain a deeper and broader understanding of a text compared to digital content without annotations. This work proposes a novel collaborative annotation system (CAS) with four types of multimedia annotations including text annotation, picture annotation, voice annotation and video annotation which can embedded into any HTML Web pages to enable users to collaboratively add and manage annotations on these pages and provide a shared mechanism for discussing shared annotations among multiple users. By applying the CAS in a mashup on static HTML Web pages, this study aims to discuss the applications of CAS in digital curation, crowdsourcing and digital humanities to encourage existing strong relations among them.

This work adopted asynchronous JavaScript (Ajax) and a model-view-controller framework to implement a CAS with reading annotation tools for knowledge creating, archiving and sharing services, as well as applying the implemented CAS to support digital curation, crowdsourcing and digital humanities. A questionnaire survey method was used to investigate the ideas and satisfaction of visitors who attended a digital curation with CAS support in the item dimensions of the interactivity with displayed products, the attraction and the content absorption effect. Also, to collect qualitative data that may not be revealed by the questionnaire survey, semi-structured interviews were performed at the end of the digital curation exhibition activity. Additionally, the effects of the crowdsourcing and digital humanities with CAS support on collecting and organizing ideas and opinions for historical events and promoting humanity research outcomes were considered as future works because they all need to take a long time to investigate.

Based on the questionnaire survey, this work found that the digital curation with CAS support revealed the highest rating score in terms of the item dimension of attraction effect. The result shows applying CAS to support digital curation is practicable, novel and interesting to visitors. Additionally, this work also successfully applied the developed CAS to crowdsourcing and digital humanities so that the two research fields may be brought into a new ground.

Based on the CAS, this work developed a novel digital curation approach which has a high degree of satisfaction on attraction effect to visitors, an innovative crowdsourcing platform that combined with a digital archive system to efficiently gather collective intelligence to solve the difficult problems of identifying digital archive contents and a high potential digital humanity research mode that can assist humanities scholars to annotate the texts with distinct interpretation and viewpoints on an ancient map, as well as discuss with other humanities scholars to stimulate discussion on more issues.

This study aims to develop a hierarchical topic analysis tool (HTAT) based on hierarchical Latent Dirichelet allocation (hLDA) to support digital humanities research that is associated with the need of topic exploration on the Digital Humanities Platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW). HTAT can assist humanities scholars on distant reading with analysis of hierarchical text topics, through classifying time-stamped texts into multiple historical eras, conducting hierarchical topic modeling (HTM) according to the texts from different eras and presenting through visualization. The comparative network diagram is another function provided to assist humanities scholars in comparing the difference in the topics they wish to explore and to track how the concept of a topic changes over time from a particular perspective. In addition, HTAT can also provide humanities scholars with the feature to view source texts, thus having high potential to be applied in promoting the effectiveness of topic exploration due to simultaneously integrating both the topic exploration functions of distant reading and close reading.

This study adopts a counterbalanced experimental design to examine whether there is significant differences in the effectiveness of topic inquiry, the number of relevant topics inquired and the time spent on them when research participants were alternately conducting text exploration using DHP-LCLW with HTAT or DHP-LCLW with Single-layer Topic Analysis Tool (SLTAT). A technology acceptance questionnaire and semi-structured interviews were also conducted to understand the research participants' perception and feelings toward using the two different tools to assist topic inquiry.

The experimental results show that DHP-LCLW with HTAT could better assist the research participants, in comparison with DHP-LCLW with SLTAT, to grasp the topic context of the texts from two particular perspectives assigned by this study within a short period. In addition, the results of the interviews revealed that DHP-LCLW with HTAT, in comparison with SLTAT, was able to provide a topic terms that better met research participnats' expectations and needs, and effectively guided them to the corresponding texts for close reading. In the analysis of technology acceptance and interview data, it can be found that the research participants have a high and positive tendency toward using DHP-LCLW with HTAT to assist topic inquiry.

The Jieba Chinese word segmentation system was used in the Mr. Lo Chia-Lun’s Writings Database in this study, to perform word segmentation on Mr. Lo Chia-Lun’s writing texts for topic modeling based on hLDA. Since Jieba word segmentation system is a lexicon based word segmentation system, it cannot identify new words that have still not been collected in the lexicon well. In this case, the correctness of word segmentation on the target texts will affect the results of hLDA topic modeling, and the effectiveness of HTAT in assisting humanities scholars for topic inquiry.

An HTAT was developed to support digital humanities research in this study. With HTAT, DHP-LCLW provides hmanities scholars with topic clues from different hierarchical perspectives for textual exploration, and with temporal and comparative network diagrams to assist humanities scholars in tracking the evolution of the topics of specific perspectives over time, to gain a more comprehensive understanding of the overall context of the texts.

In recent years, topic analysis technology that can automatically extract key topic information from a large amount of texts has been developed rapidly, but the topics generated from traditional topic analysis models like LDA (Latent Dirichelet allocation) make it difficult for users to understand the differences in the topics of texts with different hierarchical levels. Thus, this study proposes HTAT which uses hLDA to build a hierarchical topic tree with a tree-like structure without the need to define the number of topics in advance, enabling humanities scholars to quickly grasp the concept of textual topics and use different hierarchical perspectives for further textual exploration. At the same time, it also provides a combination function of temporal division and comparative network diagram to assist humanities scholars in exploring topics and their changes in different eras, which helps them discover more useful research clues or findings.

The purpose of this study was to examine the influence of adding a small amount of Ti to a Cu-based alloy, specifically the commercial Hyper Titanium Copper alloy (C1990 HP), which contains Cu-3.28 wt.% Ti, on its interfacial reaction with Sn-9.0 wt.% Zn (SnZn) solder, using the liquid/solid reaction couple technique.

The SnZn/C1990 HP couples were subjected to a reaction temperature of 240–270°C for a duration of 0.5–5 h. The resulting reaction couple was characterized using a scanning electron microscope, energy dispersive spectrometer, electron probe microanalyzer and X-ray diffractometer.

It was observed that the scallop-shaped CuZn5 and planar Cu5Zn8 phases were formed in almost all SnZn/C1990 HP couples. With increased reaction duration and temperature, the Cu-rich intermetallic compound (IMC)-Cu5Zn8 phase became a dominant IMC formed at the interface. The total thickness of the IMCs was increased with the increase in the reaction duration and temperature. The IMC growth obeyed the parabolic law, and the IMC growth mechanism was diffusion controlled. The activation energy of the SnZn/C1990 HP couple was 64.71 kJ/mol.

This article presents an analysis of the IMC thickness in each sample using ImageJ software, followed by kinetic analysis using Origin software at various reaction temperatures of SnZn/C1990 HP in liquid/solid couples. The study also includes detailed reports on the morphology, interface composition and X-ray diffraction analysis, as well as the activation energy. The findings can serve as a valuable reference for electronic packaging companies that utilize C1990 HP substrates.

The purpose of this paper is to present a novel position estimation method to accurately locate an object. An accelerometer-based error correction method is also developed to correct the positioning error caused by signal drift of a wireless network. Finally, the method is also utilized to locate cows in a farm for monitoring the action of standing heat.

The proposed method adopts the received signal strength indicator (RSSI) of a wireless sensor network (WSN) to compute the position of an object. The RSSI signal can be submitted from an endpoint device. A complex environment destabilizes the RSSI value, making the position estimation inaccurate. Therefore, a three-axial accelerometer is adopted to correct the position estimation accuracy. Timer and acceleration are two major factors in computing the error correction value to adjust the position estimate.

The proposed method is tested on a farm management system for positioning dairy cows accurately. Devices with WSN module and three-axial accelerometer are mounted on the cows to monitor their positions and actions.

If cows in a crowded farm are close to each other, then the position estimation method is unable to position each cow correctly because too many close objects cause interference in the wireless network.

Experimental results demonstrate that the proposed method improves the position accuracy, and monitor the heat action of the cows effectively.

No position estimation method has been utilized to locate cows in a farm, especially for monitoring their actions via WSN and accelerometer. The proposed method adopts an accelerometer to efficiently improve the position error caused from the signal drift of WSN.