Time trials on second-order and variable-learning-rate algorithms

The performance of seven minimization algorithms are compared on five neural network problems. These include a variable-step-size algorithm, conjugate gradient, and several methods with explicit analytic or numerical approximations to the Hessian.

An exploration of the determinants of innovation:the top management team, organisational climate and organisational learning

Some researchers argue that the top team, rather than the CEO, is a better predictor of an organisation’s fate (Finkelstein & Hambrick, 1996; Knight et al., 1999). However, others suggest that the importance of the top management team (TMT) composition literature is exaggerated (West & Schwenk, 1996). This has stimulated a need for further research on TMTs. While the importance of TMT is well documented in the innovation literature, the organisational environment also plays a key role in determining organisational outcomes. Therefore, the inclusion of both TMT characteristics and organisational variables (climate and organisational learning) in this study provides a more holistic picture of innovation. The research methodologies employed includes (i) interviews with TMT members in 35 Irish software companies (ii) a survey completed by managerial respondents and core workers in these companies (iii) in-depth interviews with TMT members from five companies. Data were gathered in two phases, time 1 (1998-2000) and time 2 (2003). The TMT played an important part in fostering innovation. However, it was a group process, rather than team demography, that was most strongly associated with innovation. Task reflexivity was an important predictor of innovation time 1, time 2). Only one measure of TMT diversity was associated with innovation - tenure diversity -in time 2 only. Organisational context played an important role in determining innovation. This was positively associated with innovation - but with one dimension of organisational learning only. The ability to share information (access to information) was not associated with innovation but the motivation to share information was (perceiving the sharing of information to be valuable). Innovative climate was also associated with innovation. This study suggests that this will lead to innovative outcomes if employees perceive the organisation to support risk, experimentation and other innovative behaviours.

Heritage and innovative learning approaches:an alternative approach to engineering education

Over recent years, the role of engineering in promoting a sustainable society has received much public attention [1] with particular emphasis given to the need to promote the future prosperity and security of society through the recruitment and education of more engineers [2,3]. From an employment perspective, the Leitch Review [4] suggested that ‘generic’ transferable employability skills development should constitute a more substantial part of university education. This paper argues that the global drivers impacting engineering education [5] correlate strongly to those underpinning the Leitch review, therefore the question of how to promote transferable employability skills within the wider engineering curriculum is increasingly relevant. By exploring the use of heritage in the engineering curriculum as a way to promote learning and engage students, a less familiar approach to study is discussed. This approach moves away from stereotypical notions of the use of information technology as representing the pinnacle of innovation in education. Taking the student experience as its starting point, the paper draws upon the findings of an exploratory study critically analysing the pedagogical value of using heritage in engineering education. It discusses a teaching approach in which engineering students are taken out of their ‘comfort zone’ - away from the classroom, laboratory and computer, to a heritage site some 100 miles away from the university. The primary learning objective underpinning this approach is to develop students’ transferable skills by encouraging them to consider how to apply theoretical concepts to a previously unexplored situation. By reflecting upon students’ perceptions of the value of this approach, and by identifying how heritage may be utilised as an innovative learning and teaching approach in engineering education, this paper makes a notable contribution to current pedagogical debates in the discipline.

Visual data mining using principled projection algorithms and information visualization techniques

We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.

Document understanding using data mining and machine learning techniques

With the explosive growth of the volume and complexity of document data (e.g., news, blogs, web pages), it has become a necessity to semantically understand documents and deliver meaningful information to users. Areas dealing with these problems are crossing data mining, information retrieval, and machine learning. For example, document clustering and summarization are two fundamental techniques for understanding document data and have attracted much attention in recent years. Given a collection of documents, document clustering aims to partition them into different groups to provide efficient document browsing and navigation mechanisms. One unrevealed area in document clustering is that how to generate meaningful interpretation for the each document cluster resulted from the clustering process. Document summarization is another effective technique for document understanding, which generates a summary by selecting sentences that deliver the major or topic-relevant information in the original documents. How to improve the automatic summarization performance and apply it to newly emerging problems are two valuable research directions. To assist people to capture the semantics of documents effectively and efficiently, the dissertation focuses on developing effective data mining and machine learning algorithms and systems for (1) integrating document clustering and summarization to obtain meaningful document clusters with summarized interpretation, (2) improving document summarization performance and building document understanding systems to solve real-world applications, and (3) summarizing the differences and evolution of multiple document sources.

The impact of pre -training interventions on cognitive, skill, and affective learning outcomes: A meta -analytic examination of four decades of research

Technological advancements and the ever-evolving demands of a global marketplace may have changed the way in which training is designed, implemented, and even managed, but the ultimate goal of organizational training programs remains the same: to facilitate learning of a knowledge, skill, or other outcome that will yield improvement in employee performance on the job and within the organization (Colquitt, LePine, & Noe, 2000; Tannenbaum & Yukl, 1992). Studies of organizational training have suggested medium to large effect sizes for the impact of training on employee learning (e.g., Arthur, Bennett, Edens, & Bell, 2003; Burke & Day, 1986). However, learning may be differentially affected by such factors as the (1) level and type of preparation provided prior to training, (2) targeted learning outcome, (3) training methods employed, and (4) content and goals of training (e.g., Baldwin & Ford, 1988). A variety of pre-training interventions have been identified as having the potential to enhance learning from training and practice (Cannon-Bowers, Rhodenizer, Salas, & Bowers, 1998). Numerous individual studies have been conducted examining the impact of one or more of these pre-training interventions on learning. ^ I conducted a meta-analytic examination of the effect of these pre-training interventions on cognitive, skill, and affective learning. Results compiled from 359 independent studies (total N = 37,038) reveal consistent positive effects for the role of pre-training interventions in enhancing learning. In most cases, the provision of a pre-training intervention explained approximately 5–10% of the variance in learning, and in some cases, explained up to 40–50% of variance in learning. Overall attentional advice and meta-cognitive strategies (as compared with advance organizers, goal orientation, and preparatory information) seem to result in the most consistent learning gains. Discussion focuses on the most beneficial match between an intervention and the learning outcome of interest, the most effective format of these interventions, and the most appropriate circumstances under which these interventions should be utilized. Also highlighted are the implications of these results for practice, as well as propositions for important avenues for future research. ^

User Interface Design for Electronic Learning Software: Promoting Usability and Facilitating Learning for Children

Computing devices have become ubiquitous in our technologically-advanced world, serving as vehicles for software applications that provide users with a wide array of functions. Among these applications are electronic learning software, which are increasingly being used to educate and evaluate individuals ranging from grade school students to career professionals. This study will evaluate the design and implementation of user interfaces in these pieces of software. Specifically, it will explore how these interfaces can be developed to facilitate the use of electronic learning software by children. In order to do this, research will be performed in the area of human-computer interaction, focusing on cognitive psychology, user interface design, and software development. This information will be analyzed in order to design a user interface that provides an optimal user experience for children. This group will test said interface, as well as existing applications, in order to measure its usability. The objective of this study is to design a user interface that makes electronic learning software more usable for children, facilitating their learning process and increasing their academic performance. This study will be conducted by using the Adobe Creative Suite to design the user interface and an Integrated Development Environment to implement functionality. These are digital tools that are available on computing devices such as desktop computers, laptops, and smartphones, which will be used for the development of software. By using these tools, I hope to create a user interface for electronic learning software that promotes usability while maintaining functionality. This study will address the increasing complexity of computing software seen today – an issue that has risen due to the progressive implementation of new functionality. This issue is having a detrimental effect on the usability of electronic learning software, increasing the learning curve for targeted users such as children. As we make electronic learning software an integral part of educational programs in our schools, it is important to address this in order to guarantee them a successful learning experience.

User Interface Design for Electronic Learning Software: Promoting Usability and Facilitating Learning for Children

Computing devices have become ubiquitous in our technologically-advanced world, serving as vehicles for software applications that provide users with a wide array of functions. Among these applications are electronic learning software, which are increasingly being used to educate and evaluate individuals ranging from grade school students to career professionals. This study will evaluate the design and implementation of user interfaces in these pieces of software. Specifically, it will explore how these interfaces can be developed to facilitate the use of electronic learning software by children. In order to do this, research will be performed in the area of human-computer interaction, focusing on cognitive psychology, user interface design, and software development. This information will be analyzed in order to design a user interface that provides an optimal user experience for children. This group will test said interface, as well as existing applications, in order to measure its usability. The objective of this study is to design a user interface that makes electronic learning software more usable for children, facilitating their learning process and increasing their academic performance. This study will be conducted by using the Adobe Creative Suite to design the user interface and an Integrated Development Environment to implement functionality. These are digital tools that are available on computing devices such as desktop computers, laptops, and smartphones, which will be used for the development of software. By using these tools, I hope to create a user interface for electronic learning software that promotes usability while maintaining functionality. This study will address the increasing complexity of computing software seen today – an issue that has risen due to the progressive implementation of new functionality. This issue is having a detrimental effect on the usability of electronic learning software, increasing the learning curve for targeted users such as children. As we make electronic learning software an integral part of educational programs in our schools, it is important to address this in order to guarantee them a successful learning experience.

Learning Management Systems (LMS) and e-learning management: an integrative review and research agenda

Information Technology (IT) can be an important component for innovation since enabling e-learning it can provide conditions to which the organization can work with new business and improved processes. In this regard, the Learning Management Systems (LMS) allows communication and interaction between teachers and students in virtual spaces. However the literature indicates that there are gaps in the researches, especially concerning the use of IT for the management of e-learning. The purpose of this paper is to analyze the available literature about the application of LMS for the e-learning management, seeking to present possibilities for researches in the field. An integrative literature review was performed considering the Web of Science, Scopus, Ebsco and Scielo databases, where 78 references were found, of which 25 were full papers. This analysis derives interesting characteristics from scientific studies, highlighting gaps and guidelines for future research.

Inauguration Speech of the school year 1993 of the School of Library, Documentation and Information

Since the child starts in the teaching - learning is made aware that there is a division of natural resources: renewable and nonrenewable. It also says that every natural resource is useless unless it explodes. But to apply such resources necessary knowledge. We realize today that the same biological systems of living things (renewable resources) are transmitters of information. He uses that information to nurture their knowledge, and this is essential for the use and conservation of resources, making valid then the principle that "there is no knowledge without information."

The library of the Institute of Alajuela address the information and communication technologies: User training and information literacy

The Library of the Institute of Alajuela made an induction experience and training of users and ventured into the information literacy and engaged in the work of the teaching-learning as an integral part of the curriculum. The actions of the library in developing search strategies, location, selection and use of information brought inthe health service, changes to the role of the library, the librarian, the book and the information in the educational environment.By sharing this experience is intended to provide information that can motivate staff of educational institutions that wish toenter the field of information literacy as a strategy to support the development oflifelong independent learning skills and meaningful learning. Currently, the library should be a proactive part in the education of students but also teachers, administrative and family.This will result in a benefit to Costa Rica: the development of youth and their proper integration into the workplace.

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.