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Ant Colony Optimization and Particle Swarm Optimization represent two widely used Swarm Intelligence (SI) optimization techniques. Information processing using Multiple-Valued Logic (MVL) is carried out using more than two discrete logic levels. In this paper, we compare two the SI-based algorithms in synthesizing MVL functions. A benchmark consisting of 50,000 randomly generated 2-variable 4-valued functions is used for assessing the performance of the algorithms using the benchmark. Simulation results show that the PSO outperforms the ACO technique in terms of the average number of product terms (PTs) needed. We also compare the results obtained using both ACO-MVL and PSO-MVL with those obtained using Espresso-MV logic minimizer. It is shown that on average, both of the SI-based techniques produced better results compared to those produced by Espresso-MV. We show that the SI-based techniques outperform the conventional direct-cover (DC) techniques in terms of the average number of product terms required.

This paper aims to evaluate the user satisfaction criterion for qualitative assessment of timeliness and efficacy of digital libraries based on the multivariate fuzzy logic technique.

In this paper, the performance of digital library services using fuzzy logic modeling are evaluated. This model based on fuzzy logic control is used to compute the dynamic response of users by using multiple independent variables. These parameters with inherent uncertainties in practical scenarios are characterized by fuzzy linguistic information.

Several parameters determining the user satisfaction metric in the deployment of digital library exhibit implicit uncertainties which can be intelligently modeled by means of fuzzy control systems. Given the sample data set for the proposed fuzzy multi-attribute decision-making framework, the simulation results are used to compute various error performance measures in the estimation of the fuzzy output variables.

The size of the considered sample data set is considerably small. Scalable real-world data sets can be used to reinforce the statistical efficiency and accuracy of the proposed model. Moreover, other techniques such as evolutionary multi-objective optimization and the Markovian process can be implemented to explore the efficient correlation between different parameters influencing the users’ behavior and facilitate the general application of the proposed technique.

The paper applied a fuzzy design methodology in which several attributes related to the service of digital library and the affiliated online resource provisions are used to assess their synchronous impact on user convenience in accessing and manipulating the library information. End-users’ satisfaction is crucial for quality-based valuation of compliance with the time limitations and proficiency of digital libraries.

This paper aims to present an evaluation of open source OCR for supporting research on material in small‐ to medium‐scale historical archives.

The approach was to develop a workflow engine to support the easy customisation of the OCR process towards the historical materials using open source technologies. Commercial OCR often fails to deliver sufficient results here, as their processing is optimised towards large‐scale commercially relevant collections. The approach presented here allows users to combine the most effective parts of different OCR tools.

The authors demonstrate their application and its flexibility and present two case studies, which demonstrate how OCR can be embedded into wider digitally enabled historical research. The first case study produces high‐quality research‐oriented digitisation outputs, utilizing services that the authors developed to allow for the direct linkage of digitisation image and OCR output. The second case study demonstrates what becomes possible if OCR can be customised directly within a larger research infrastructure for history. In such a scenario, further semantics can be added easily to the workflow, enhancing the research browse experience significantly.

There has been little work on the use of open source OCR technologies for historical research. This paper demonstrates that the authors' workflow approach allows users to combine commercial engines' ability to read a wider range of character sets with the flexibility of open source tools in terms of customisable pre‐processing and layout analysis. All this can be done without the need to develop dedicated code.

Audio-visual presentations – delivered either in real-life or virtually – feature heavily in educational assessments and employer recruitment. This study explored neurodivergent undergraduate students' experiences of presentations. The aim was to understand how neurodivergent students describe experiences of presentations in educational and workplace contexts and how neurodivergent students experienced training, support activities and learning technologies associated with presentations.

An exploratory qualitative phenomenological approach was taken, from students' perspectives. Overall, 12 neurodivergent undergraduate students (M_age = 21.89 years, SD_age = 2.57; nine women, two men, one non-binary) discussed their experiences of presentations within educational and/or professional contexts via semi-structured remote interviews. The sample included individuals with diagnoses of anxiety, depression, dyslexia, borderline personality disorder, dyscalculia, dyspraxia, and panic disorder.

Thematic Analysis of interview transcript data revealed four main themes (with sub-themes in parentheses): Control (preparedness; delivery); Audience Perceptions and Behaviours (expectations of “normality”; shared knowledge; audience “expertise”); Intervention Efficacy (early access; individuality; learning technologies) and Value of Presentation Skills (reciprocity between education – workplace; self-efficacy; self-esteem; learner development).

The dataset was extracted from a relatively small sample from a single university and indeed a single academic discipline. Furthermore, the dataset was collected during the ongoing COVID-19 pandemic – although this gives us a valuable snapshot of students' experiences and perceptions during this time, whether the author can extrapolate these findings in future is unclear.

The findings help understand how we better support students. Better ways to support learners can be developed in developing presentation and audience skills. This research shows that alternative assessment provisions must be based on individuals and their own specific needs and skills, rather than their divergence label. This research can inform the development of digital learning technologies.

This research can inform how educators, coaches, trainers, and facilitators “train” audiences to be more inclusive and less prejudicial/biased. We can understand how to better construct social spaces for presentations, in the classroom and the world of work.

This report presents a valid and valuable methodological approach, conducted and reported transparently. This research was conducted during a crucial, unprecedented and precarious time period for learners and education professionals. Implications are considered with respect to the design of teaching, learning and assessment activities; facilitator, learner, and peer behaviours; the role of digital learning technologies; and employment/employability.

Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.

An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.

With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.

Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.

This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.

The purpose of this paper is to describe the role and characteristics of the summer internship program (Digital Summer Clinic) delivered by Eastern Michigan University. The authors report the results of an exploratory study of interns participating in the Digital Summer Clinic over a five-year time period. The study captures and analyzes the experiences of interns as expressed in structured interviews and blog posts.

The study data were text from structured interviews and blog posts capturing the “voice” of the interns. A natural language processing (NLP) analysis of the text corpus, consisting of 43 interviews and blog posts, resulted in the identification of 242 unique stem-terms used by interns in describing the internship experiences. The authors used the JMP Pro 15.2 Text Explorer algorithm (It is defined as a suite of computer programs for statistical analysis developed by the JMP business unit of SAS Institute) to extract the terms that were subsequently transformed and analyzed with factor analysis and regression to address the research questions.

The factor analysis results found six dimensions or themes, defined by the stem-terms used by student interns, best described the internship experience. The authors then explored the relationship between the six themes and the umbrella term “internship” with multiple regression analysis. The regression findings suggest a hierarchy of effects with the theme “Introducing Professional Opportunities” being the theme most predictive of the umbrella term.

The methodology used within the paper is unique in several ways when compared to other research investigating internship programs. First, it uses NLP analysis for the qualitative analysis of text-based descriptions of student experiences over a five-year time horizon. Second, the data analysis uses transformed text to quantitatively determine the major dimensions or themes expressed by the interns about their experiences in the Summer Clinic program. Finally, the relative importance of the themes identified provided direction for future program development.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

The purpose of this paper is to create a research framework to scrutinize how individuals' digital technology use produces tangible and intangible outcomes in online (digital) and offline realms.

The paper applies the Bourdieusian e-capital perspective to create a theory-based framework. The framework was used to guide a survey design to explore women's “social media-assisted reuse” at the micro-scale in Helsinki, Finland.

The paper argues that a new form of capital emerges when individuals utilize digital technologies in correspondence to their goals to gain added value that would be impossible or significantly more arduous to gain without the digital realm. The survey indicates that the respondents utilize the digital space – set objectives and gain capital-related outcomes – in correspondence to their differing social, economic and cultural positions and related resources in- and outside of the digital realm.

If digital spaces – due to social inequality and underlying power structures – become increasingly stratified, there will be significant impacts on how individuals from differing backgrounds gain accumulated forms of capital through the digital realm. The question is of great importance for battling inequality.

The paper enhances and synthesizes recent discussions on different forms of capital and outcomes of the use of digital technologies and presents a combined “e-capital–digital divide” framework that offers a more complete agenda for investigating the finely nuanced links between the inputs, outputs and outcomes of digital technology use.

The purpose of this study is to explore the role of e-government in reducing corruption and achieving transparency from the perspective of citizens and public servants of the National Statistics and Information Authority in Afghanistan.

This study applies a mixed-method research design to explore whether e-government can combat corruption and increase transparency in the public sector of a developing nation. The data collection involves a survey of (n = 280) citizens and interviews with six National Statistics and Information Authority public servants. Data analysis includes descriptive statistics, Spearman’s correlation for the survey and qualitative content analysis for the interviews.

The results of this study reveal that e-government distributes and decentralizes power among public servants, reduces corruption and promotes transparency and accountability by reporting corruption through social media, online complaint forms, emails and the 450 toll-free number. In addition, the major factors are identified that reduce corruption through e-government.

This study proposes a model for using e-government that has implications for designers, developers and policymakers to create user-friendly systems that reduce bureaucracy and physical interactions with public servants while minimizing paper-based systems.

Governments can reduce corruption among high-ranking public servants by implementing a decentralized system that prevents system manipulation. This involves measures like surveillance, ICT training, process automation, reduced bureaucracy, simplified procedures and real-time customer support.

Despite the potential of e-government to reduce monopoly power and intermediaries among low-ranking officials, high-ranking Afghan officials still engage in corrupt practices. Nonetheless, 75% of Afghans believe e-government promotes transparency and accountability and reduces corruption.

To the best of the authors’ knowledge, this is the first study in the Afghan public sector that explores the role of e-government to reduce corruption and achieve transparency.

This paper presents a co-authorship study of authors who published in Digital Humanities journals and examines the apparent influence of gender, or more specifically, the quantitatively detectable influence of gender in the networks they form.

This study applied co-authorship network analysis. Data has been collected from three canonical Digital Humanities journals over 52 years (1966–2017) and analysed.

The results are presented as visualised networks and suggest that female scholars in Digital Humanities play more central roles and act as the main bridges of collaborative networks even though overall female authors are fewer in number than male authors in the network.

This is the first co-authorship network study in Digital Humanities to examine the role that gender appears to play in these co-authorship networks using statistical analysis and visualisation.