Search results

A Cu‐Al bonding system exists when copper wire is bonded onto an aluminum bond pad using thermosonic wire bonding technology. Aged Cu‐Al bonding system was analyzed by measuring the intermetallics layer thickness and its correlation to electrical contact resistance. Result shows that the thickness of Cu‐Al intermetallics layer grows almost linearly to aging time. The activation energy needed for Cu atoms to diffuse into Al was calculated using Fick's law; Q=129.66 kJ/mole and D₀=1.628×10⁻⁴ m²/s. The calculation of activation energy and impurity diffusity using Model Kidson also shows linear relationship. Electrical resistance of Cu‐Al intermetallics layer was calculated from contact resistance of Cu‐Al bonding system. The result shows that the electrical resistance of Cu‐Al intermetallics layer increases linearly with intermetallics thickness. Its growth rate that was calculated using Model of Braunovic and Alexandrov is double of Model of Murcko.

The circuit elements of every printed circuit board have the potential for failure during test and/or use. These failures can occur by forming short‐circuits between adjacent circuit elements, or by forming open‐circuits in the conductors. The risk sites can be identified by type, and the total number enumerated by manual inspection of the photolithographic masks used to fabricate the printed circuit layers. However, the circuit density of high performance printed circuit boards has become so great that meaningful manual analysis has become impractical. A more effective method is to use special graphics programs to analyse the computer‐aided design (CAD) data. The methodology developed to perform the CAD analysis of high performance printed circuit boards for short‐circuits utilises two powerful computer graphic tools: the Interactive Graphics System and the Unified Shapes Checking system. Test data for open‐circuits are generated using specially written alphanumeric routines. The data can be used for stress testing the printed circuit boards by wiring up special test modules that are plugged into the boards and then placing the boards into environmental test chambers. The printed circuits are checked for short‐circuits by putting them into groups that have no risk of shorting to each other (zero risk), and placing the groups in parallel under an electrical potential. The flow of current between the groups would indicate a short‐circuit. Similarly, the printed circuits can be checked for open‐circuits, by stringing them together into groups in series, and measuring the changes in resistance under thermal stress. Both types of test data can also be used for in‐process testing.

Job-seeking success relates to engagement with specific job-seeking strategies, so it is important to understand the beliefs that job-seekers have of them. Using multiple methods, this study aims to establish a typology of the beliefs job-seekers have about strategies, create and validate a measure of these beliefs and relate them to job-seeking behavior.

In the first sample, the authors interviewed 77 job-seekers about their job-seeking strategy beliefs. The authors then created a measure and verified its psychometric properties using 396 job-seekers. Finally, using a sample of 628 job-seekers, the authors continued their evaluation of the measure and related strategy beliefs to job-seeker motivation and behavior.

The authors initially identified 21 beliefs about job-seeking strategies. The authors ultimately found support for 15 dimensions, replicating the factor structure across samples. Strategies are perceived to differ on most beliefs, and eight beliefs had unique relationships with job-seeker effort and/or motivation.

The study results can help organizations and job-seekers increase job-seeking motivation by targeting specific beliefs found to have the strongest relationships with strategy use.

This is the first measure of job-seeking strategy beliefs that generalizes across strategies. Furthermore, the authors establish several beliefs that have the strongest relationships with job-seeking motivation.

This paper aims to present recently published resources on library instruction and information literacy, providing an introductory overview and a selected annotated bibliography of publications covering various library types, study populations and research contexts.

This paper introduces and annotates English-language periodical articles, monographs, dissertations, reports and other materials on library instruction and information literacy published in 2019.

The paper provides a brief description of all 370 sources and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians, researchers and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.

The purpose of this paper is to document health care needs expressed by people living with diabetes, describe the solutions they envisaged for improving the quality of primary care (PC) services and empower them to make better use of PC services.

A participatory research approach was used. Six workshops were organised to provide diabetes patients with knowledge on available services and to engage them in sharing their experience. Group discussions were recorded. Data were analysed using the thematic analysis method.

In total, 79 persons living with diabetes for a mean of 13 years participated. Needs expressed were grouped under seven themes: assurance of satisfactory follow-up by a family physician, continuous access to services adapted to evolving needs, motivation to adopt and maintain healthy behaviours, maintenance of knowledge about diabetes, psychological support, financial constraints, and collaboration with secondary-level services. Patients proposed solutions for improving services that were grouped under five themes: facilitating access to services, disseminating information about available services, centralising diabetes information on the internet, offering personalised services and improving interprofessional collaboration.

Needs expressed by diabetic patients concern different aspects of care such as accessibility, organisation, coordination, and better dissemination and visibility of services. The solutions proposed by patients focussed on better access to information and interprofessional services.

The workshop format used in this study offers an original and interesting approach and tool for actively engaging patients in quality improvement of services.

The purpose of this paper is threefold: first, to present a framework of five “facets,” i.e., distinct but complementary ways in which the observed appeal of a consumer shopping site’s features can potentially be generalized across product/service domains (the authors call this framework the feature appeal generalization perspective); second, to determine if and how observed feature preferences for consumer electronics, bookstores, and sites “in general” generalize across domains; third, to test hypotheses about the impact of frequency of domain usage upon feature generalizability.

Via an online survey administered in a controlled laboratory setting, 313 respondents evaluated 26 website features in three domains (books, electronics, general) for a total of 24,414 preference judgments.

Two facets, individual feature values and within domain evaluative dimensions, revealed minimal generalizability, while there was moderate comparability across all domains in between domain feature correspondence. Personal preference elevation could be generalized between books and general, but not between these two and electronics. Differentiating dimensions showed that preferences were not generalizable from electronics to books and general because consumers wanted electronics features to provide “flashy sizzle” and books/general features to give “comfortable safety.” As hypothesized, patterns of generalizability coincided with frequency of domain usage.

Practitioners should not apply published studies of feature appeal to their domain of interest unless those studies directly analyzed that domain. Scientists should incorporate all five facets in modeling what attracts consumers to commercial websites.

This is the first multidimensional analysis of the generalizability of site feature appeal across business-to-consumer product/service domains, and the first to propose this integrated evaluative framework with its unique facets.

Rapidly rising healthcare costs, partially due to preventable medical errors, have led hospitals to redouble their process improvement (PI) efforts. The purpose of this paper is to examine how PI initiatives mediate the effect of medical error sources to enhance three hospital outcomes (patient safety, operational effectiveness, and competitiveness).

Drawing from Dynamic Capabilities Theory, the authors develop a framework to explore three PI initiatives: Continuous Quality Improvement (CQI), Six Sigma Initiatives (SSI), and Lean Management Initiatives (LMI). Hierarchical regression analysis is employed to test the proposed model, using data from a nationwide survey of 210 US hospitals.

For enhancing patient safety outcomes, it was found that CQI and LMI were significant in mediating hospital error sources; however, SSI was not significant after accounting for the other two PI types. For improving organizational effectiveness, CQI and SSI were significant; whereas LMI was not significant over and above the other two PI types. Finally, only SSI was significant for superior sustainable competitive advantage.

The paper provides insight into which PI initiatives were most effective for various hospital outcomes. The findings can benefit healthcare practitioners as they select among different PI programs for enhancing healthcare results. Limitations of the study include the use of perceptual measures, relatively small sample size, and potential alternate relationships relevant to the outcome variables.

This is the first study to explore the mediating effects of three PI programs for the impact of medical errors on each of three hospital outcomes.