500 research outputs found
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Aligning Children's Books With Digital Tools for Reader Response: The Text, the Tech, and the Task
No full textThrough an exploration of three vignettes, the authors share innovative ways young learners and their teachers are responding to children's literature using digital tools in the context of new literacies. In the first example, primary grade students use digital tools to gain agency in their literacy practices as part of project-based learning within a STEAM curriculum. In the second, struggling readers in an after-school program integrate traditional and out-of-school literacies to produce authentic literacy products outside the constraints of standards and established curricula. Finally, an example from a teacher education program shows how the next generation of teachers can become leaders in the use of new literacies through their own experiential learning. Despite the differences in context and content of each vignette, all three demonstrate strong use of literacies pedagogy to guide selection of digital tools for the creation and consumption of text
Entropy, the Information Processing Cycle, and the Forecasting of Bull and Bear Market Peaks and Troughs
No full textMany econophysics applications have modeled financial systems as if they were pure physical systems devoid of human limitations and errors. On the other hand, traditional financial theory has ignored limits that physics would impose on human interactions, communications, and computational abilities. The entropic yield curve blends the physical and human financial worlds in a new, powerful, and surprisingly simple way. This article uses this information theoretic perspective to provide a new explanation of the dynamics and timing of financial cycles. Additionally, the entropic yield curve offers a new method of forecasting market peaks and troughs
A Review of the Oxford Chichewa-English/English-Chichewa Dictionary by Steven Paas
No full textThis article reviews the Oxford Chichewa-English/English-Chichewa Dictionary compiled by Steven Paas, published in 2016 by Oxford University Press in Cape Town. Upon a review of the dictionary, a number of issues arise. The dictionary's significance rests in its use as reference material for language learners, its semantic precision and the relevance with which translation and other disciplines treat it. Regardless of its wide coverage of the Chichewa and English lexicons, the dictionary has a number of flaws which are misleading and confusing for the dictionary's users. Such errors include ambiguity over dictionary type, inclusion of proper nouns as lexical entries, lack of detailed grammatical information and silence on morphological typology among others. This paper, therefore, concludes that the dictionary leaves a lot to be desired and recommends that the next edition of the dictionary take into account the highlighted issues
Rainfall-Runoff Modeling of Sutlej River Basin (India) Using Soft Computing Techniques
No full textThe prediction of the runoff generated within a watershed is an important input in the design and management of water resources projects. Due to the tremendous spatial and temporal variability in precipitation, rainfall-runoff relationship becomes one of the most complex hydrologic phenomena. Under such circumstances, using soft computing approaches have proven to be an efficient tool in modeling of runoff. These models are capable of predicting river runoff values that can be used for hydrologic and hydraulic engineering design and water management purposes. It has been observed that the artificial neural networks (ANN) model performed well compared to other soft computing techniques such as fuzzy logic and radial basis function investigated in this study. In addition, comparison of scatter plots indicates that the values of runoff predicted by the ANN model are more precise than those found by RBF or Fuzzy Logic model
Employees' Participation in IT-Projects in the Public Sector: Mapping Participation to the Project Lifecycle
No full textEmployee participation in IT projects in the public sector is argued in the literature as a critical factor for the success and acceptance of IT. However, studies on employee participation reported on the lack of end-users participation in the public sector and on the need of improvement of participation concepts. This article investigates different participation practices and used methods for participation within different approaches such as Human Centered Design, Ethnography, Contextual Design and Human Resource Management, and explores opportunities for participation across the system developement life cycle in the public sector. The findings reveal a variety of participation opportunieties across the whole process. Finally, implications of these findings are discussed with suggestions for future research
The Learning Value of Personalization in Children's Reading Recommendation Systems: What Can We Learn From Constructionism?
No full textThis article critically reviews the personalization logic embedded in reading recommendation systems developed for 2- to 11-year-old children and its (dis)alignment with Papert's constructionist and socio-constructionist theories of learning. It is argued that the current design fails to incorporate the computer culture that Papert envisioned for children's learning. While the personalization design focuses on child-centered design, it restricts the child's contribution to the database, minimises children's agency in shaping it and reinforces individual models of learning. The paper recommends that reading recommendation systems provide opportunities for what Papert described as self-discovery, experimentation, and development of abstract knowledge. Recommendation algorithms need to work in conjunction with diversification mechanisms to challenge and widen children's thinking and diversification should not be conflated with randomization. Practical examples are provided so that the approach described in this article can be used as a foundation for conceptualising and designing children's reading recommendation systems and data-based personalized learning more broadly
Big Data Analytics Platforms for Electric Vehicle Integration in Transport Oriented Smart Cities: Computing Platforms for Platforms for Electric Vehicle Integration in Smart Cities
No full textElectric vehicles (EVs) are key players for transport oriented smart cities (TOSC) powered by smart grids (SG) because they help those cities to become greener by reducing vehicle emissions and carbon footprint. In this article, the authors analyze different use-cases to show how big data analytics (BDA) can play vital role for successful electric vehicle (EV) to smart grid (SG) integration. Followed by this, this article presents an edge computing model and highlights the advantages of employing such distributed edge paradigms towards satisfying the store, compute and networking (SCN) requirements of smart EV applications in TOSCs. This article also highlights the distinguishing features of the edge paradigm, towards supporting BDA activities in EV to SG integration in TOSCs. Finally, the authors provide a detailed overview of opportunities, trends, and challenges of both these computing techniques. In particular, this article discusses the deployment challenges and state-of-the-art solutions in edge privacy and edge forensics
Towards a Text-World Approach to Translation and Its Pedagogical Implications
No full textAlthough it is widely acknowledged that translation is a cognitive process, there is scarcely any study establishing connections between the text and mental representations and giving a systematic and comprehensive explanation for this pivotal yet magical mechanism. Illuminated by Text World Theory, this study proposes a text-world approach to translation studies and addresses its implications for translator training. Translation is regarded as a cognitive communicative process of reproducing texts as worlds. The (in)coherence among text worlds as they are represented in translation provides a legitimate criterion for the evaluation of translation competence. To view translation as a cognitive-linguistic process of text-world construction and presentation may promise a more proactive approach to translator training by encouraging translator trainees to pay special attention to the expansion of their knowledge structures
Weighted SVMBoost based Hybrid Rule Extraction Methods for Software Defect Prediction
No full textThe software testing efforts and costs are mitigated by appropriate automatic defect prediction models. So far, many automatic software defect prediction (SDP) models were developed using machine learning methods. However, it is difficult for the end users to comprehend the knowledge extracted from these models. Further, the SDP data is of unbalanced in nature, which hampers the model performance. To address these problems, this paper presents a hybrid weighted SVMBoost-based rule extraction model such as WSVMBoost and Decision Tree, WSVMBoost and Ripper, and WSVMBoost and Bayesian Network for SDP problems. The extraction of the rules from the opaque SVMBoost is carried out in two phases: (i) knowledge extraction, (ii) rule extraction. The experimental results on four NASA MDP datasets have shown that the WSVMBoost and Decision tree hybrid yielded better performance than the other hybrids and WSVM
Impact of PDS Based kNN Classifiers on Kyoto Dataset
No full textThis article compares the performance of different Partial Distance Search-based (PDS) kNN classifiers on a benchmark Kyoto 2006+ dataset for Network Intrusion Detection Systems (NIDS). These PDS classifiers are named based on features indexing. They are: i) Simple PDS kNN, the features are not indexed (SPDS), ii) Variance indexing based kNN (VIPDS), the features are indexed by the variance of the features, and iii) Correlation coefficient indexing-based kNN (CIPDS), the features are indexed by the correlation coefficient of the features with a class label. For comparative study between these classifiers, the computational time and accuracy are considered performance measures. After the experimental study, it is observed that the CIPDS gives better performance in terms of computational time whereas VIPDS shows better accuracy, but not much significant difference when compared with CIPDS. The study suggests to adopt CIPDS when class labels were available without any ambiguity, otherwise it suggested the adoption of VIPDS