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On account of competence‐led market demands, it is important that employees gain new knowledge efficiently. One solution is to set‐up IT‐based courses using interactive media for learning (IML) so that employees can learn at their workplace and also learn as a part of their ordinary work. Choosing technology as a media for learning is not simply chosen for its own sake rather because it is more efficient for the task. However, for a number of reasons, it is becoming increasingly difficult to assess the efficient use of technology. Thus there are needs for processes to quality assure usability or even to create a process to certify usability. Before this is possible a number of issues have to be resolved. All issues are fundamental to assure usability. We address each issue in our paper. The purpose of this paper is to review current approaches to quality assurance as applied in the field of IML. This paper discusses the difficulties of distinguishing between learning and usability in an IML context. We discuss quality‐assuring usability in terms of learning and we outline a certification process for IML in terms of usability. Our concluding remarks indicate possible future research directions.

In the fall of 2002, the University of Illinois Library at Urbana‐Champaign received a grant from the Institute of Museum and Library Services (IMLS) to implement a collection registry and item‐level metadata repository for digital collections and content created by or associated with projects funded under the IMLS National Leadership Grant (NLG) program. When built, the registry and metadata repository will facilitate retrieval of information about digital content related to past and present NLG projects. The process of creating these services also is allowing us to research and gain insight into the many issues associated with implementing such services and the magnitude of the potential benefit and utility of such services as a way to connect, bring together, and make more visible a broad range of heterogeneous digital content. This paper describes the genesis of the project, the rationale for architectural design decisions, challenges faced, and our progress to date.

The purpose of this paper is to compare the reliability and intermetallic layer (IML) of solder joints prepared with infrared (IR) and vapour phase (VP) soldering. The reliability of 0603-sized resistors’ solder joints formed with IR and VP soldering was investigated. The IML of the joints was analysed based on image processing algorithm automatically.

For the reliability analyses, the ageing method was a highly accelerated stress test (HAST) with +105°C maximum temperature, fully saturated (100 per cent) relative humidity at +0.5 atm overpressure. The joints were characterised based on the thickness of their IML and on their shear strength in as-reflowed stage, and after 400, 800, 1,200, 1,600 and 2,000 hours of HAST. An image processing algorithm was developed to measure the thickness of the IMLs on cross-sectional scanning electron microscopy (SEM) images automatically.

The increase of the IML thickness is lower in the case of HAST ageing compared to other methods. The thickness increment of the Cu₆Sn₅ layer was higher for IR and lower for VP soldering; the Cu₃Sn layer cannot be inspected even after 2,000 hours of HAST ageing. The results of shear strength measurements show better reliability for VP soldered joints.

The developed image processing method is applicable to obtain quantitative results about the IMLs in an effective fast way.

There is a lack of information in the literature regarding the reliability comparison of solder joints formed with VP and conventional reflow processes. Thus, we performed research about the lifetime of solder joints formed with VP and IR reflow method.

This paper examines the role of illiquidity and duration factor in understanding the momentum profit in the Korean stock market. We find that the foreigner/institutional illiquidity factor explains the momentum effect. In addition, this paper finds that duration factor defined as the difference in returns of short-duration and long-duration stocks captures well the momentum profits. That is, a two-factor model with the market and duration factor performs much better than competing asset pricing models in explaining the momentum effect. Finally, when controlling for the duration factor, the explanatory power of the foreign/institutional illiquidity factor on the momentum profits disappears. In sum, our empirical finding indicates that the duration factor is the most important ingredient in understanding the momentum effect in the Korean stock market.

As a federally‐funded independent granting agency, The Institute of Museum and Library Services (IMLS) became involved in digitization in the late 1990s when Congress gave it statutory authority to fund digitization of library and museum collections. Since that time, IMLS has funded more than 100 exemplary digitization projects through its National Leadership Grant program. Collectively, these projects have helped to identify best practices for the creation, management, preservation and use of digital content. Most importantly, they demonstrate the important role that museums and libraries can play in supporting both formal education and lifelong learning. Ultimately, this work will help libraries and museums to fulfill their roles as educational institutions. IMLS grants support the spectrum of learning from independent inquiry through formal education to the development of “learning communities.”

This chapter explores differences in fringe, distant, and remote rural public library assets for asset-based community development (ABCD) and the relationships of those assets to geographic regions, governance structures, and demographics.

The author analyzes 2013 data from the Institute of Museum and Library Services (IMLS) and U.S. Department of Agriculture using nonparametric statistics and data mining random forest supervised classification algorithms.

There are statistically significant differences between fringe, distant, and remote library assets. Unexpectedly, median per capita outlets (along with service hours and staff) increase as distances from urban areas increase. The Southeast region ranks high in unemployment and poverty and low in median household income, which aligns with the Southeast’s low median per capita library expenditures, staff, hours, inventory, and programs. However, the Southeast’s relatively high percentage of rural libraries with at least one staff member with a Master of Library and Information Science promises future asset growth in those libraries. State and federal contributions to Alaska libraries propelled the remote Far West to the number one ranking in median per capita staff, inventory, and programs.

This study is based on IMLS library system-wide data and does not include rural library branches operated by nonrural central libraries.

State and federal contributions to rural libraries increase economic, cultural, and social capital creation in the most remote communities. On a per capita basis, economic capital from state and federal agencies assists small, remote rural libraries in providing infrastructure and services that are more closely aligned with libraries in more populated areas and increases library assets available for ABCD initiatives in otherwise underserved communities.

Even the smallest rural library can contribute to ABCD initiatives by connecting their communities to outside resources and creating new economic, cultural, and social assets.

Analyzing rural public library assets within their geographic, political, and demographic contexts highlights their potential contributions to ABCD initiatives.

This chapter examines the challenges of developing and implementing a new national evaluation approach in a complex library funding program. The approach shifts a prior outcome-based evaluation legacy using logic models to one relying on nonlinear logic mapping. The new approach is explored by studying the Measuring Success initiative, launched in March 2011 for the largest funded library services program in the United States, the Institute for Museum and Library Services formula-based Grants to States program. The chapter explores the relative benefits of nonlinear logic maps and emphasizes the importance of scaling evaluation from individual projects toward clusters of similar library services and activities. The introduction of this new evaluation approach required a new conceptual frame, drawing on diffusion, strategic planning, and other current evaluation theories. The new approach can be widely generalized to many library services, although its focus is on a uniform interorganizational social network embedded in service delivery. The chapter offers a new evaluation perspective for library service professionals by moving from narrow methodological concerns involving measurement to broader administrative issues including diffusion of library use, effective integration of systematic data into program planning and management, and strengthening multi-stakeholder communication.

The US Federal government is a potential source of support for advancing Library and Information Science (LIS) through funding experimentation, innovation, and demonstration. Most agencies are not as much interested in advancing the research front in LIS as they are in LIS contributions that advance other fields. The full potential of federal funding to impact LIS is far from realized. LIS researchers should be aware of each agency's mission as well as the types of research that each one supports. Many people contribute to research agendas but the most influential are researchers themselves. Becoming more successful in winning grants will require researchers to become better grant writers and to collaborate with people outside LIS.

The purpose is twofold. First, this study aims to establish that black box tree-based machine learning (ML) models have better predictive performance than a standard linear regression (LR) hedonic model for rent prediction. Second, it shows the added value of analyzing tree-based ML models with interpretable machine learning (IML) techniques.

Data on Belgian residential rental properties were collected. Tree-based ML models, random forest regression and eXtreme gradient boosting regression were applied to derive rent prediction models to compare predictive performance with a LR model. Interpretations of the tree-based models regarding important factors in predicting rent were made using SHapley Additive exPlanations (SHAP) feature importance (FI) plots and SHAP summary plots.

Results indicate that tree-based models perform better than a LR model for Belgian residential rent prediction. The SHAP FI plots agree that asking price, cadastral income, surface livable, number of bedrooms, number of bathrooms and variables measuring the proximity to points of interest are dominant predictors. The direction of relationships between rent and its factors is determined with SHAP summary plots. In addition to linear relationships, it emerges that nonlinear relationships exist.

Rent prediction using ML is relatively less studied than house price prediction. In addition, studying prediction models using IML techniques is relatively new in real estate economics. Moreover, to the best of the authors’ knowledge, this study is the first to derive insights of driving determinants of predicted rents from SHAP FI and SHAP summary plots.

With the financial support of a donor gift and a grant from the Institute for Museum and Library Services (IMLS), Temple University Libraries embarked on a major digital imaging enterprise. The first year’s pilot projects, their costs, and lessons learned are discussed. Plans are outlined for continued expansion of their image database and related programs, which will be funded by a second IMLS grant and other sources.