Assessing the Knowledge Structure of Information Systems Learners in Experience-Based Learning

The fundamental goal of this study was to investigate the effects of an experience-based learning environment on information systems students\u27 knowledge structure. The learning environment was structured in a way consistent with the problem solving approaches used by information systems experts. The focus of this paper is to report the assessment of the knowledge structure of the information systems learners in a self-managed and experience-based learning environment. The key issue here is whether information systems students can develop the necessary cognitive skills in such learning environment. To assess the knowledge structure of the learners, this study designed three research instruments that included a declarative-knowledge test, a problem-solving task, and a similarity-judgment task. The analysis results suggested that the learning outcome in this experience-based learning environment was very positive. The environment that imposed an expert-like organization both on information gathering and on problem solving activities resulted in improved problem-solving skills. The learners mastered the necessary declarative knowledge, as well as developed domain-specific basic skill and strategies

East-West Partnerships for Poverty Reduction: Experience Review and Institutional Innovation

As a general rule, companies have focused most of their improvement initiatives in manufacturing and operations, leaving their internal service processes behind. This study presents a FRACAS process which is underperforming in terms of lead time. The process is studied in detail and the people who work with it were interviewed to find out how they think the process inhibits their work. The contribution this study makes is that it provides an example of what lean FRACAS could mean. The studied process presents itself as non-compliant with what the employees wish from such a process. This in turn causes these employees to underperform since they think that the process does not seem to provide value to neither themselves nor the customers

Equity incentive, separation of two rights and corporate performance: research on corporate governance based on two types of agency costs

This paper discusses the impact of equity incentive and the separation of two rights on corporate performance and the intermediary role of two kinds of agency costs by using the revised stepwise method taking A-share listed companies as the research object and using the Jones model to remove the impact of earnings management on corporate performance. The classification of industry and nature is introduced to further judge the heterogeneity of the conclusions. The results show that equity incentive can significantly reduce the first kind of agency cost and improve corporate performance, but the intermediary effect of the first kind of agency cost between equity incentive and corporate performance is not significant. Limiting the degree of separation of the two rights can significantly reduce the second kind of agency cost to improve corporate performance, and the second kind of agency cost has a partial intermediary effect between the degree of separation of the two rights and corporate performance. The results of different industries are heterogeneous and need to be treated differently. It is further found that non-state-owned enterprises can improve corporate performance through governance measures, but state-owned enterprises have not achieved a significant governance effect. This paper clarifies the black box between corporate governance and corporate performance from the effects of the two types of agency costs and effectively supplements the existing research system, which also provides a reference for market regulators to formulate policies

Restructuring multimodal corrective feedback through Augmented Reality (AR)-enabled videoconferencing in L2 pronunciation teaching

The problem of cognitive overload is particularly pertinent in multimedia L2 classroom corrective feedback (CF), which involves rich communicative tools to help the class to notice the mismatch between the target input and learners’ pronunciation. Based on multimedia design principles, this study developed a new multimodal CF model through augmented reality (AR)-enabled videoconferencing to eliminate extraneous cognitive load and guide learners’ attention to the essential material. Using a quasi-experimental design, this study aims to examine the effectiveness of this new CF model in improving Chinese L2 students’ segmental production and identification of the targeted English consonants (dark /ɫ/, /ð/and /θ/), as well as their attitudes towards this application. Results indicated that the online multimodal CF environment equipped with AR annotation and filters played a significant role in improving the participants’ production of the target segments. However, this advantage was not found in the auditory identification tests compared to the offline CF multimedia class. In addition, the learners reported that the new CF model helped to direct their attention to the articulatory gestures of the student being corrected, and enhance the class efficiency. Implications for computer-assisted pronunciation training and the construction of online/offline multimedia learning environments are also discussed

A multi-objective optimization framework for terrain modification based on a combined hydrological and earthwork cost-benefit

The escalating risk of urban inundation has drawn increased attention to urban stormwater management. This study proposes a multi-objective optimization for terrain modification, combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with digital elevation model (DEM)-based hydrological cost factor analysis. To reduce the precipitation erosive forces and runoff kinetic energy, the resulting framework offers the possibility of efficiently searching numerous solutions for trade-off sets that meet three conflicting objectives: minimizing maximum flow velocity, maximizing runoff path length and minimizing earthwork costs. Our application case study in H{\o}je Taastrup, Denmark, demonstrates the ability of the optimization framework to iteratively generate diversified modification scenarios, which form the reference for topography planning. The three individual objective preferred solutions, a balanced solution, and twenty solutions under regular ordering are selected and visualized to determine the limits of the optimization and the cost-effectiveness tendency. Integrating genetic algorithms with DEM-based hydrological analysis demonstrates the potential to consider more complicated hydrological benefit objectives with open-ended characteristics. It provides a novel and efficient way to optimize topographic characteristics for improving holistic stormwater management strategies

Pollution level and risk assessment of heavy metals in sewage sludge from eight wastewater treatment plants in Wuhu City, China

Aim of study: To investigate the content, contamination levels and potential sources of five heavy metals (Hg, Pb, Cd, Cr, As) in sewage sludge from eight wastewater treatment plants (W1 to W8).Area of study: Wuhu, located in southeastern Anhui Province, southeastern China.Material and methods: The sewage sludge pollution assessment employed the single-factor pollution index, Nemerow’s synthetic pollution index, monomial potential ecological risk coefficient and potential ecological risk index. The potential sources among the five heavy metals were determined using the Pearson’s correlation analysis and principal component analysis (PCA).Main results: The mean concentrations of the heavy metals were 0.27 mg/kg (Hg), 70.78 mg/kg (Pb), 3.48 mg/kg (Cd), 143.65 mg/kg (Cr) and 22.17 mg/kg (As). W1, W5 and W6 sewage sludge samples showed the highest levels of heavy metal contamination, and cadmium had the highest contamination level in the study area. Pearson’s correlation analysis and PCA revealed that Pb and Cd mainly derived from traffic emissions and the manufacturing industry and that As and Cr originated from agricultural discharges.Research highlights: The pollution of cadmium in Wuhu should be controlled preferentially. The heavy metal pollution of W1, W5 and W6 sewage treatment plants is relatively high, they should be key prevention targets

New Interpretations of Normalization Methods in Deep Learning

In recent years, a variety of normalization methods have been proposed to help train neural networks, such as batch normalization (BN), layer normalization (LN), weight normalization (WN), group normalization (GN), etc. However, mathematical tools to analyze all these normalization methods are lacking. In this paper, we first propose a lemma to define some necessary tools. Then, we use these tools to make a deep analysis on popular normalization methods and obtain the following conclusions: 1) Most of the normalization methods can be interpreted in a unified framework, namely normalizing pre-activations or weights onto a sphere; 2) Since most of the existing normalization methods are scaling invariant, we can conduct optimization on a sphere with scaling symmetry removed, which can help stabilize the training of network; 3) We prove that training with these normalization methods can make the norm of weights increase, which could cause adversarial vulnerability as it amplifies the attack. Finally, a series of experiments are conducted to verify these claims.Comment: Accepted by AAAI 202