3,942 research outputs found
Distributed client selection with multi-objective in federated learning assisted Internet of Vehicles
Federated learning is an emerging distributed machine learning framework in
the Internet of Vehicles (IoV). In IoV, millions of vehicles are willing to
train the model to share their knowledge. Maintaining an active state means the
participants must update their state to the FL server in a fixed interval and
participate to next round. However, the cost by maintaining an active state is
very large when there are a huge number of participating vehicles. In this
paper, we proposed a distributed client selection scheme to reduce the cost of
maintaining the active state for all participants. The clients with the highest
evaluation are elected among the neighbours. In the evaluator, four variables
are considered including sample quantity, throughput available, computational
capability and the quality of the local dataset. We adopted fuzzy logic as the
evaluator since the closed-form solution over four variables does not exist.
Extensive simulation results show our proposal approximates the centralized
client selection in terms of accuracy and can significantly reduce the
communication overhead
Flowers For The World: Developing a Business Game to Support the Teaching of IS Concepts
One of the key problems in teaching fundamental concepts in information systems is how to ground the theory in experiences that the students can relate to. To overcome this problem, a business game called Flowers For The World has been developed and used across a wide variety of IS courses. This paper will describe the game and the result of using it for a 300-level course in analysis and design. The possibility exists that the game could be developed to provide a common business foundation across all business school curricula
Understanding the Influence of Blog on the Development of Social Capital
The rapid use and application of blogs in diverse areas such as education, marketing, journalism, and human resource management in recent years underlines the need for a better understanding of the impact of this new technology on social capital. Social capital reflects the norm of reciprocity and the level of trust among individuals who connect, interact, and benefit from one another. Blog is expected to influence the extent and the scope of this interaction by providing new means of networking among people. This paper examines the relationship between blog use and social capital and reports on the results of an exploratory study that examines this relationship using survey data from 326 blog users. Results suggest a significant and positive impact of blog use on social capital and its components: social connections, reciprocity, and trust. Implications of these findings for research and practice are discussed
The development and test of a relationship model on system use, job learning, and impact
This exploratory study examined the role of job learning on the relationship between information
systems use and impact. Data from 308 end-users were analyzed to evaluate the relationship
between systems use, job learning, and technology impact. System use was conceptualized as
decision support, work integration, and customer service. Technology impact was conceptualized
as effect on management control, task innovation, task productivity, and customer satisfaction.
Two sets of hypotheses are presented for these relationships. Results suggest that the pattern of
system use significantly and positively influenced job learning. Job learning was found to
significantly and positively influence technology impact. We theorize that individuals learned
about their job as a result of systems usage. In turn, job learning influenced technology impact.
The study findings are discussed
The Effect Of IFRS Adoption On Likelihood Of Management Earnings Forecasts: Evidence In Korea
Korean listed companies adopted International financial reporting standards (IFRS) in 2011 mandatorily. The IFRS adoption modifies corporate financial reporting structure and further it can affect managers’ incentive for disclosing their earnings forecasts. We investigate the association between IFRS adoption and likelihood of management earnings forecasts. From the empirical results, we find that mandatory IFRS adopted companies are less likely to issue their earnings forecasts after IFRS adoption. It implies that investors’ belief about management earnings forecasts as useful information is weakened after IFRS adoption compare to pre-IFRS adoption period. Therefore, managers’ incentive for providing earnings forecasts decreases. This study will contribute to academics and disclosure-related practitioners by reporting how IFRS adoption makes an influence to managers’ incentive of management earnings forecasts issuance. We also believe that the empirical evidence may shed some lights on the understanding of the spillover effect of IFRS adoption to management earnings forecasts.
Clarifying the Role of Self-Efficacy and Metacognition as Indicators of Learning: Construct Development and Test
We propose extending our understanding of self-efficacy by comparing self-efficacy with a related construct called metacognition. Metacognition involves the monitoring and control of one\u27s thought processes and is often related, as is self-efficacy, to performance on a task. We develop an instrument that attempts to measure both self-efficacy and metacognition with respect to one\u27s performance on a test covering declarative and procedural knowledge (knowing that, and knowing how) of DFDs and ERDs. With data collected from a sample of 124 students, we use partial least squares (PLS) to show that self-efficacy and metacognition are distinct yet related constructs. While self-efficacy is a predictor of both declarative and procedural knowledge, metacognition is only related to procedural knowledge. We discuss the implications of these results and suggest further research is needed to compare and contrast the role of these constructs in assessing learning outcomes
Formative versus reflective measurement: Comment on Marakas, Johnson, and Clay (2007)
In a recent issue of the Journal of the Association for Information Systems, Marakas, Johnson, and Clay (2007) presented an interesting and important discussion on formative versus reflective measurement, specifically related to the measurement of the computer self-efficacy (CSE) construct. However, we believe their recommendation to measure CSE constructs using formative indicators merits additional dialogue before being adopted by researchers. In the current study we discuss why the substantive theory underlying the CSE construct suggests that it is best measured using reflective indicators. We then provide empirical evidence demonstrating how the misspecification of existing CSE measures as formative can result in unstable estimates across varying endogenous variables and research contexts. Specifically, we demonstrate how formative indicator weights are dependent on the endogenous variable used to estimate them. Given that the strength of formative indicator weights is one metric used for determining indicator retention, and adding or dropping formative indicators can result in changes in the conceptual meaning of a construct, the use of formative measurement can result in the retention of different indicators and ultimately the measurement of different concepts across studies. As a result, the comparison of findings across studies over time becomes conceptually problematic and compromises our ability to replicate and extend research in a particular domain. We discuss not only the consequences of using formative versus reflective measures in CSE research but also the broader implications this choice has on research in other domains
Prepare your mind for learning
The learning process must evolve and expand throughout one\u27s IT career. Most would agree that\u27s often easier said than done. Here are some ways professionals can overcome mental blocks that may prevent learning
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