500 research outputs found
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Social Robots for Pedagogical Rehabilitation: Trends and Novel Modeling Principles
No full textThe use of robots as educational learning tools is quite extensive worldwide, yet it is rather limited in special education. In particular, the use of robots in the field of special education is under skepticism since robots are frequently believed to be expensive with limited capacity. The latter may change with the advent of social robots, which can be used in special education as affordable tools for delivering sophisticated stimuli to children with learning difficulties also due to preexisting conditions. Pilot studies occasionally demonstrate the effectiveness of social robots in specific domains. This chapter overviews the engagement of social robots in special education including the authors' preliminary work in this field; moreover, it discusses their proposal for potential future extensions involving more autonomous (i.e., intelligent) social robots as well as feedback from human brain signals
Behavior Analysis of Customer Churn for a Customer Relationship System: An Empirical Case Study
No full textThis article describes how the bank industry in Taiwan must function in today's tough and fiercely competitive domestic credit card market and subdued global market. Banks are increasingly emphasizing the importance of retaining customers in order to sustain market share and remain profitable. This study proposes a new model which local banks can use to detect potential customer churn and provide an early warning indicator of problems that could lead to loss of customers. The model incorporates a customer relationship management database with a built-in time factor and applied temporal abstraction to represent data for a specific time period as defined by experts. Association rule mining is applied to analyze and detect abnormal customer behavior. The results of this article indicate that the system is relatively effective in detecting customer churn early on and thus helpful at assisting banks to address issues before they escalate. Furthermore, the tested rules are further scrutinized by experts to establish the relationship between the defined rules and management. This study provides an expert system for banks to assess the quality of their marketing campaigns and reestablish faltering customer relationships
Collaboration Network Analysis Based on Normalized Citation Count and Eigenvector Centrality
No full textIn the research community, the estimation of the scholarly impact of an individual is based on either citation-based indicators or network centrality measures. The network-based centrality measures like degree, closeness, betweenness & eigenvector centrality and the citation-based indicators such as h-index, g-index & i10-index, etc., are used and all of the indicators give full credit to all of the authors of a particular article. This is although the contribution of the authors are different. To determine the actual contribution of an author in a particular article, we have applied arithmetic, geometric and harmonic counting methods for finding the actual contribution of an individual. To find the prominent actor in the network, we have applied eigenvector centrality. To authenticate the proposed analysis, an experimental study has been conducted on 186007 authors collaboration network, that is extracted from IEEE Xplore. The experimental results show that the geometric counting-based credit distribution among scholars gives better results than others
Process Optimization and NVA Reduction by Network Analysis and Resequencing
No full textThe article discusses a methodology to reduce cycle times through an algorithmic, analytical framework for sequential process flows. Studying process flow flexibility for reducing bottlenecks has always continued to open new research avenues. This methodology has been formulated keeping in view of sequential manually executed assembly processes, where a single operator is involved, the process steps are entirely manual or semi-automated. The concept can also be extended to other scenarios by computing a process flexibility measure in terms of time, resources and methods. Essentially this article talks about the use of an algorithm for effective scheduling on assembly lines, computing the most optimal path that that the process flow could have taken given how the process has proceeded. Current activity scheduling methods tally the progress against a plan, which is ideal and does not account for unforeseen wait times. The output of the algorithm which is the most optimal approach as computed for a given scenario will help achieve rhythm and reduce wasted time in places where it's possible to avoid them. A standard tool to measure the exact amount of compressible wait time or Muda Type of waste is chosen, the overall equipment efficiency was adopted for gauging this approach. This discusses the generalization of the principle used and its formulation as an algorithm and a flow chart
Framing Historical Thinking in the Digital Age
No full textIt is undeniable that students today are fundamentally different than those of previous generations and that many students of this generation do not enjoy history, as it is typically ranked as one of the least favorite subjects in K-12 schools. A large reason for this is the fact that much of the curriculum and instructional approaches are outdated and of little interest to students and do not mirror the approaches and methods employed by historians. As educators increasingly move towards teaching in online environments, it is critical that history educators structure instruction to meet the needs of the student, while making it effective, engaging, and authentic. This chapter focuses on ways that educators, in a mixed-mode or online environment, can attend to the four dimensions of the college, career, and civic life (C3) framework for social studies state standards: helping students in evaluating sources and using evidence, developing questions and planning inquiries, applying disciplinary concepts and tools, and communicating conclusions and taking informed action
Investigating Student Perceptions and the Effectiveness of K-12 Blended Learning Communities
No full textWhile the growth of blended learning environments in higher education and non-educational settings has continued to increase in recent years, this has not been the case in K-12 settings. Recently, in an effort to explore the viability and effectiveness of K-12 blended learning environments, Florida Virtual School (FLVS) has been piloting blended learning communities in a number of their schools, providing opportunities to explore factors that influence the effectiveness of K-12 blended learning communities. Thus, the purpose of this chapter is to report the results of a study designed to assess conditions that influence the effectiveness of K-12 blended learning communities, and to explore learner, instructor, course, and other factors important to successful blended learning communities. Findings will inform the design, development, and implementation of future K-12 blended teaching and learning environments in an effort to support and strengthen student achievement, the preparation of teachers to facilitate effective blended learning environments
CBC-Based Synthetic Speech Detection
No full textIn previous studies of synthetic speech detection (SSD), the most widely used features are based on a linear power spectrum. Different from conventional methods, this article proposes a new feature extraction method for SSD from octave power spectrum which is obtained from constant-Q transform (CQT). By combining CQT, block transform (BT) and discrete cosine transform (DCT), a new feature is obtained, namely, constant-Q block coefficients (CBC). In which, CQT is used to transform speech from the time domain into the frequency domain, BT is used to segment octave power spectrum into many blocks and DCT is used to extract principal information of every block. The experimental results on ASVspoof 2015 corpus shows that CBC is superior to other front-ends features that have been benchmarked on ASVspoof 2015 evaluation set in terms of equal error rate (EER)
Uncertainty Avoidance and Consumer Cognitive Innovativeness in E-Commerce
No full textThis article describes how despite the extensive academic interest in e-commerce, an investigation of consumer cognitive innovativeness towards new product purchase intention has been neglected. Based on the stimulus–organism–response (S–O–R) model, this study investigates the consumer cognitive innovativeness and the moderating role of the individual consumer-level uncertainty avoidance cultural value towards new product purchase intention in business-to-consumer (B2C) e-commerce. Structural equation modelling, such as partial least squares (PLS) path modelling was used to test the model, using a sample of 255 participants in Australia who have had prior online shopping experience. The findings show that the online store web atmosphere influences consumers' cognitive innovativeness to purchase new products in countries with diverse degrees of uncertainty avoidance such as Australia. The results provide some guidance for a B2C website design based on how individual's uncertainty avoidance and cognitive innovativeness can aid the online consumer purchasing decision-making process
Sociotechnical Factors in the Endorsement of Governmental E-Transactions
No full textThe success of governmental e-transactions in developing countries is due to the effective utilization of information communication technology. The current literature reports that e-transactions can meet with citizen reluctance. Due to its nature as a sociotechnical system, this article investigates the role of sociotechnical factors in the endorsement of e-transactions. Quantitative research was conducted to analyze online data from 663 participants from a population of 80,000 online users. Structural equation modelling was also performed to examine the association between sociotechnical factors and the acceptance of e-transactions. The results suggest that sociotechnical factors influence the usage of e-transactions. Thus, a theoretical sociotechnical model was developed which includes three levels: technical, organizational and social. A number of design and implementation activities, related to the three theorized levels, were suggested to guide governments in increasing the acceptance of e-transactions
The Effects of Image-Based Online Reviews on Customers' Perception Across Product Type and Gender
No full textOnline vendors consider image online reviews as an important format to improve customers' buying decision. Prior research examined the influence of review presentation format, but did not focus on image format. Little is known about customers' perception on image online reviews. This study developed a theoretical model to analyze the effect of image reviews across product type and gender. The 2×2×2 between-subject experimental design was conducted to test hypotheses. The results demonstrated that compared to text review, the influence of image format on customers' perception was more significant, but in varying degrees across product type and gender. This study found that image format had more positive impact for experience product's understanding compared to search product. The result also showed that the effect of image format on experience product was not significant greater for females than males, but the perception improvement degree from text to image reviews was saliently different between genders. This study discussed theoretical and managerial contributions of these results