Search results for "oftware"
showing 10 items of 7396 documents
Integrating Computational Linguistic Analysis of Multilingual Learning Data and Educational Measurement Approaches to Explore Learning in Higher Educ…
2017
This chapter develops a computational linguistic model for analyzing and comparing multilingual data as well as its application to a large body of standardized assessment data from higher education. The approach employs both an automatic and a manual annotation of the data on several linguistic layers (including parts of speech, text structure and content). Quantitative features of the textual data are explored that are related to both the students’ (domain-specific knowledge) test results and their level of academic experience. The respective analysis involves statistics of distance correlation, text categorization with respect to text types (questions and response options) as well as lang…
Can easy-to-use software deliver effective e-learning in dental education? A randomised controlled study
2012
Introduction: For the production of computer-based learning environments, a wide range of software solutions can be used which differ not only in their functionality but also vary in cost and ease to program. The aim of our study was to evaluate the overall efficiency and student′s perception of two case-based e-learning programs that were produced with either an easy-to-use or a complex software. Materials and Methods: Eighty-five dental students were randomly assigned to one of two experimental groups. One group studied with a laborious, high-interactive e-learning program (complex-software group). The second group studied within a low-interactive learning environment (easy-software gro…
Bhaskar’s Theory of Publishing and Its Contribution to Theorizing (Evolving New Forms of) Educational Media
2021
Enterprises which are usually categorized as educational publishers increasingly develop and market products like learning platforms. Such products are at least to a considerable extent pieces of software rather than products based on content in the sense of texts, images, and maybe moving images or sounds (which typically constitute products of the media industries). Michael Bhaskar’s The Content Machine. Towards a Theory of Publishing (2013) represents one of the most comprehensive theoretical approaches to publishing in recent years. This contribution discusses, how far products like learning platforms can be described as results of acts of (educational) publishing or can be considered (…
Towards Understanding Startup Product Development as Effectual Entrepreneurial Behaviors
2017
With the rapid development of technology and competitiveness of IT sectors, the speed of learning and evolving is vital for success of software startups. However, software startups often face with multiple technical and business challenges, which lengthen the duration of their idea-to-launch process. Little is known about the relation of entrepreneurial characteristics of software startups and their product development. We conducted an empirical study on twenty software startups to understand their challenges that leads long idea-to-launch processes. Six engineering-related challenges were identified and interpreted via a lens of an entrepreneurial behavior theory. Our main finding is that …
Entrepreneurial Decision-Making Logic Related to Software Development in Different Growth Phases of INVs
2019
Software-based innovations with global market-potential are the main product offering of digital-based International New Ventures, an emerging type of rapidly internationalizing firm. Despite increasing research attention on the internationalization phases of these firms, knowledge of how the characteristics of the firm’s software offerings change over time remains scarce. In this paper, we analyze how standardization, customization and localization evolve through the growth and commitment of International New Ventures in foreign markets. Specifically, we posit that an entrepreneurial decision-making logic based on a logic of effectuation or causation acts as a trigger mechanism for specifi…
Efficient Graph Models for Retrieving Top-k News Feeds from Ego Networks
2012
A key challenge of web platforms like social networking sites and services for news feed aggregation is the efficient and targeted distribution of new content items to users. This can be formulated as the problem of retrieving the top-k news items out of the d-degree ego network of each given user, where the set of all users producing feeds is of size n, with n >> d >> k and typically k
Analysis of different geometrical features to achieve close-to-bone stiffness material properties in medical device: A feasibility numerical study
2021
Background and objective: In orthopedic medical devices, elasto-plastic behavior differences between bone and metallic materials could lead to mechanical issues at the bone-implant interface, as stress shielding. Those issue are mainly related to knee and hip arthroplasty, and they could be responsible for implant failure. To reduce mismatching-related adverse events between bone and prosthesis mechanical properties, modifying the implant's internal geometry varying the bulk stiffness and density could be the right approach. Therefore, this feasibility study aims to assess which in-body gap geometry improves, by reducing, the bulk stiffness. Methods: Using five finite element models, a unia…
Regularized extreme learning machine for regression problems
2011
Extreme learning machine (ELM) is a new learning algorithm for single-hidden layer feedforward networks (SLFNs) proposed by Huang et al. [1]. Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This paper proposes an algorithm for pruning ELM networks by using regularized regression methods, thus obtaining a suitable number of the hidden nodes in the network architecture. Beginning from an initial large number of hidden nodes, irrelevant nodes are then pruned using ridge regression, elastic net and lasso methods; hence, the architectural design of ELM network can be automated. Empirical studies…
An entropy-based machine learning algorithm for combining macroeconomic forecasts
2019
This paper applies a Machine Learning approach with the aim of providing a single aggregated prediction from a set of individual predictions. Departing from the well-known maximum-entropy inference methodology, a new factor capturing the distance between the true and the estimated aggregated predictions presents a new problem. Algorithms such as ridge, lasso or elastic net help in finding a new methodology to tackle this issue. We carry out a simulation study to evaluate the performance of such a procedure and apply it in order to forecast and measure predictive ability using a dataset of predictions on Spanish gross domestic product.
A machine learning application to predict early lung involvement in scleroderma: A feasibility evaluation
2021
Introduction: Systemic sclerosis (SSc) is a systemic immune-mediated disease, featuring fibrosis of the skin and organs, and has the greatest mortality among rheumatic diseases. The nervous system involvement has recently been demonstrated, although actual lung involvement is considered the leading cause of death in SSc and, therefore, should be diagnosed early. Pulmonary function tests are not sensitive enough to be used for screening purposes, thus they should be flanked by other clinical examinations