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A new option in resequencing output from online searches of journal literatures is proposed: computerized sorting of hits by the journals in which they appear, and then of journals, high to low, by the number of hits appearing in each. This two‐step operation is called ‘Bradfordizing’ since it ranks journals in order of their yields of hits, in the manner used by S. C. Bradford in formulating his much‐studied law. Benefits envisioned from Bradfordizing output include (1) an online summary report that would show, before hits were printed out, the journals involved in the retrieval and their respective yields; (2) capability to retrieve hits selectively by journal, based on the report; (3) capability to display certain statistics to help in making retrieval decisions, or in the interest of bibliometric research; and (4) printouts of hits arranged in a way that corresponds to journal runs on shelves, thereby helping librarians provide copies of desired items.

The author examines the history of the part III examination of the Institution of Electrical Engineers in its role as one entry to the profession of electrical engineering, and points out serious defects.

Digital humanities (DH) is a scholarly lens through which computing methods and technological tools are used for the research of humanistic disciplines. The purpose of this study is to identify the current practicing situation of DH in the university libraries of Bangladesh.

Survey methods were used for gathering data using a well-structured questionnaire. The websites of different universities national and international organizations, and DH-related websites from different corners of the globe were also used for the gathering of data and information.

The findings revealed that there are some hindrances to practicing DH, such as lack of IT skills, funds and problems with intellectual property rights act practicing and provided some suitable suggestions for the advancement of DH in the university libraries of Bangladesh.

The outcome of this paper might be a valuable reference tool for researchers and professionals of the DH discipline. The insights and views of the respondents regarding computational tools and technologies obtained from this study are original and unique in nature.

This study aims to explore knowledge structure and research trends in the domain of digital humanities (DH) in the recent decade. The study identified prevailing topics and then, analyzed trends of such topics over time in the DH field.

Research bibliographic data in the area of DH were collected from scholarly databases. Multiple text mining techniques were used to identify prevailing research topics and trends, such as keyword co-occurrences, bigram analysis, structural topic models and bi-term topic models.

Term-level analysis revealed that cultural heritage, geographic information, semantic web, linked data and digital media were among the most popular topics in the recent decade. Structural topic models identified that linked open data, text mining, semantic web and ontology, text digitization and social network analysis received increased attention in the DH field.

This study applied existent text mining techniques to understand the research domain in DH. The study collected a large set of bibliographic text, representing the area of DH from multiple academic databases and explored research trends based on structural topic models.

Digital Humanities is a robust area of research and practice at universities and their libraries across the world. This case study investigates the unique DH practices of seven US academic libraries to provide insights into how varied academic libraries operate their DH programs.

Semi-structured interviews with nine library staff in DH or DH-adjacent positions at seven US academic libraries were used to investigate library DH practices.

This case study highlighted key areas of academic library DH practices including Space, Technology, Staff, Instruction and Collaboration. Practices in these areas were compared against each other and literature to comment on the current state of DH library practices and offer some recommendations for select areas.

This case study interviewed staff in a limited number of US libraries and is not generalizable to or a reflection of the many academic libraries in the US or across the world.

The juxtaposition of multiple libraries’ DH activities provides a unique perspective on academic library DH practice, as many studies investigate only a single library as their subject.

The purpose of this paper is to dissect key issues and debates in digital humanities, an emerging field of theory and practice. Digital humanities stands greatly to impact the Information and Library Science (ILS) professions (and vice versa) as well as the traditional humanities disciplines.

This paper explores the contours of digital humanities as a field, touching upon fundamental issues related to the field’s coalescence and thus to its structure and epistemology. It looks at the ways in which digital humanities brings new approaches and sheds new light on manifold humanities foci.

Digital humanities work represents a vital new current of interdisciplinary, collaborative intellectual activity both in- and outside the academy; it merits particular attention from ILS.

This paper helps potential stakeholders understand the intellectual and practical framework of the digital humanities and “its relationship” to their own intellectual and professional work.

This paper critically synthesizes previous scholarly work in digital humanities. It has particular value for those in ILS, a community that has proven especially receptive to the field, as well as to scholars working in many humanities disciplines. Digital humanities has already made an important impact on both LIS and the humanities; its impact is sure to grow.

This paper seeks to provide a description and reflection on some of the structural problems and challenges faced when developing a digital humanities (DH) project in a Mexican public university.

As DH is a relatively new field and practice in Mexican academia, this article is based on a case study of developing the Biblioteca Digital de Pensamiento Novohispano (Digital Library of New Hispanic Thought). This is one of the few DH at the Universidad Nacional Autónoma de México (UNAM), the largest public university in the country.

It was found that there were three central problems for developing a DH project in a Mexican public university: existing technical knowledge and abilities at the UNAM will be challenged by DH projects; projects are the place to train human resources in DH methodology; and researchers need to consider different long‐term infrastructure and hosting solutions, with or without using institutional infrastructure, at the same time researches need to work within the institution to establish a specific policy for research projects.

The paper concludes that the structure, goals and products of DH projects need to be modified and expanded in order to also consider alternative goals and products such as: proposals of institutional policy, creation of infrastructure and academic and student training. DH projects must be regarded as disruptive, that is that the project needs to assume rupture as a part of the project itself.

The experience of innovation and disruption is not necessarily the same in all fields and all institutions. This article documents for the first time the particular experiences of a public university in a developing country with DH projects. It has been found that the delay in using computers in the humanities in Mexico has led to the development of a specific paradox: a gap between institutional interest and disposition in the use of computers in humanities, and the lack of DH culture in those who have to develop the project.

The Children Act 1989 ended a period of four decades during which the education of children and young people in care was almost entirely neglected. However, it was another 20 years before education took its rightful place at the centre of provision for the care of children away from home. This article considers the contribution made to this process by the Act and its accompanying Guidance, what progress has been made and what were the obstacles, past and continuing, that have made it so difficult to narrow the gap in attainment between looked‐after children and others.

This paper aims to use different machine learning (ML) algorithms for the prediction of inverse kinematic solutions in parallel manipulators (PMs) to overcome the computational difficulties and approximations involved with the analytical methods. The results obtained from the ML algorithms and the Denavit–Hartenberg (DH) approach are compared with the experimental results to evaluate their performances. The study is performed on a novel 6-degree of freedom (DoF) PM that offers precise motions with a large workspace for the end effector.

The kinematic model for the proposed 3-PPSS PM is obtained using the modified DH approach and its inverse kinematic solutions are determined using the Levenberg–Marquardt algorithm. Various prediction algorithms such as the multiple linear regression, multi-variate polynomial regression, support vector, decision tree, random forest regression and multi-layer perceptron networks are applied to predict the inverse kinematic solutions for the manipulator. The data set required to train the network is generated experimentally by recording the poses of the end effector for different instantaneous positions of the slider using the concept of ArUco markers.

This paper fully demonstrates the possibility to use artificial intelligence for the prediction of inverse kinematic solutions especially for complex geometries.

As the analytical models derived from the geometrical method, Screw theory or numerical techniques involve approximations and needs more computational power, it is not advisable for real-time control of the manipulator. In addition, the data set obtained from the derived inverse kinematic equations to train the network may lead to inaccuracies in the predicted results. This error may generate significant deviations in the end-effector position from the desired position. The present work attempts to resolve this issue by proposing a camera-based approach that uses ArUco library and ML algorithms to create the data set experimentally and predict the inverse kinematic solutions accurately.