Design Principles-Based Interactive Learning Tool for Solving Nonlinear Equations

Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback,visibility,affordance,consistency,and constraints.It also compares these methods by the number of iterations and time required to display the result.This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods.The tool is implemented using the MATLAB app and is evaluated through usability testing with two groups of users that are categorized by their level of experience with root-finding.Users with no knowledge in root-finding confirmed that they understood the root-finding concept when interacting with the designed tool.The positive results of the user evaluation showed that the tool can be recommended to other users.

The Effects of B2C Interaction on Customer Loyalty

Purpose： This research attempts to examine the relationship between B2C interaction and customer loyalty in Business-to-Customer（B2C） context from a new perspective of the interactive tool.Design/methodology/approach： The scale for B2C interactive tools is of seven dimensions： efficiency, security, fulfillment, mobility, community, cultivation, and customization. A model reflecting the influences of these attributes on customer loyalty is developed and empirically examined based on data collected from 265 B2C customers. Findings： Results reveal that the fulfillment, mobility, community, and customization of B2C interactive tools can enhance customer loyalty directly and significantly. Efficiency and security, serving as the premise for possible purchase behavior, facilitate fulfillment. In addition, cultivation promotes the formation of customization, which directly strengthens customer loyalty.Research limitations： Models considering individual-level indicators and combined with classic loyalty mechanisms in B2C context may lead to a deeper understanding of the tested effects of interaction on customer loyalty.Practical implications： To strengthen B2C interaction and further cultivate loyal customers, making interactive tools more fundamental, flexible, and personalized is critical for B2C enterprises. Originality/value： This study proposes a new perspective from interactive tools when measuring the relationship between B2C interaction and customer loyalty, and offers a useful theoretical lens and reasonable explanations for investigating customer loyalty in B2C e-commerce context.

Flexible visualization framework for head-mounted display with gesture interaction interface

As the development of new visualization systems,within the field of simulation,offers their users more insights from their simulations,immersive systems are becoming a part of the visualization techniques.With the recent advancements of the Head-Mounted Displays(HMDs)and popularity of motion sensors,human beings and computer become more interactive.This study aims to evaluate the potential of such systems as a visualization tool through the development of a new flexible framework for visualization within virtual reality(VR)environment,using an Oculus Rift and a Leap Motion.Two approaches are then compared:high-3D object rendering within the virtual scene approach and a user experience-oriented system with an intuitive interface.To assess the quality of the interface and its relevance for the user,different types of gestures are implemented and tested.From an experiment on users to evaluate the developed system as a proper visualization tool,the HMDs,paired with a motion sensor to make a gesture-controlled interface seem to be promising mediums despite various constraints on development regarding the technology limitations.

Computational Approaches for Prioritizing Candidate Disease Genes Based on PPI Networks

With the continuing development and improvement of genome-wide techniques, a great number of candidate genes are discovered. How to identify the most likely disease genes among a large number of candidates becomes a fundamental challenge in human health. A common view is that genes related to a specific or similar disease tend to reside in the same neighbourhood of biomolecular networks. Recently, based on such observations,many methods have been developed to tackle this challenge. In this review, we firstly introduce the concept of disease genes, their properties, and available data for identifying them. Then we review the recent computational approaches for prioritizing candidate disease genes based on Protein-Protein Interaction（PPI） networks and investigate their advantages and disadvantages. Furthermore, some pieces of existing software and network resources are summarized. Finally, we discuss key issues in prioritizing candidate disease genes and point out some future research directions.