Time patterns and perceptions of online learning success factors

Online learning provides the opportunity to work on academic tasks at any time at the same time as doing other activities, such as using in web 2.0 tools. This study identifies factors that contribute to success in online learning from the students¿ perspective and their relationship with time patterns. A survey of learning outputs was used to find relationships between students¿ satisfaction, knowledge acquisition and knowledge transfer with time for working on academic tasks. In this study, 199 students from a university in Mexico completed the survey. Findings suggest that knowledge transfer has a significant association with the number of hours online per day, hours spent on social networks and the use made of e-learning during working hours. Learner satisfaction has a strong relationship with the time in years a learner has been using the Internet and the number of hours devoted to the course per week. The findings of this research will be helpful for faculty and instructional designers for implementing learning strategies.

Moda en la red : Análisis del sector en el ámbito del marketing online

El éxito del comercio electrónico, el manejo de nuevas plataformas para llevar a cabo campañas de marketing online, la aparición de influenciadores como los blogs y las redes sociales o los nuevos formatos de publicidad de moda en la red son algunos de los puntos que se analizarán en esta disertación.

Networks and partnerships in third party logistics service production

Third party logistics, and third party logistics providers and the services they offer have grown substantially in the last twenty years. Even though there has been extensive research on third party logistics providers, and regular industry reviews within the logistics industry, a closer research in the area of partner selection and network models in the third party logistics industry is missing. The perspective taken in this study was of expanding the network research into logistics service providers as the focal firm in the network. The purpose of the study is to analyze partnerships and networks in the third party logistics industry in order to define how networks are utilized in third party logistics markets, what have been the reasons for the partnerships, and whether there are benefits for the third party logistics provider that can be achieved through building networks and partnerships. The theoretical framework of this study was formed based on common theories in studying networks and partnerships in accordance with models of horizontal and vertical partnerships. The theories applied to the framework and context of this study included the strategic network view and the resource-based view. Applying these two network theories to the position and networks of third party logistics providers in an industrial supply chain, a theoretical model for analyzing the horizontal and vertical partnerships where the TPL provider is in focus was structured. The empirical analysis of TPL partnerships consisted of a qualitative document analysis of 33 partnership examples involving companies present in the Finnish TPL markets. For the research, existing documents providing secondary data on types of partnerships, reasons for the partnerships, and outcomes of the partnerships were searched from available online sources. Findings of the study revealed that third party logistics providers are evident in horizontal and vertical interactions varying in geographical coverage and the depth and nature of the relationship. Partnership decisions were found to be made on resource based reasons, as well as from strategic aspects. The discovered results of the partnerships in this study included cost reduction and effectiveness in the partnerships for improving existing services. In addition in partnerships created for innovative service extension, differentiation, and creation of additional value were discovered to have emerged as results of the cooperation. It can be concluded that benefits and competitive advantage can be created through building partnerships in order to expand service offering and seeking synergies.

Community Detection in Multi-Layer Networks

In the scope of the current thesis we review and analyse networks that are formed by nodes with several attributes. We suppose that different layers of communities are embedded in such networks, besides each of the layers is connected with nodes' attributes. For example, examine one of a variety of online social networks: an user participates in a plurality of different groups/communities – schoolfellows, colleagues, clients, etc. We introduce a detection algorithm for the above-mentioned communities. Normally the result of the detection is the community supplemented just by the most dominant attribute, disregarding others. We propose an algorithm that bypasses dominant communities and detects communities which are formed by other nodes' attributes. We also review formation models of the attributed networks and present a Human Communication Network (HCN) model. We introduce a High School Texting Network (HSTN) and examine our methods for that network.

Dynamics in large scale networks

In this thesis we study the properties of two large dynamic networks, the competition network of advertisers on the Google and Bing search engines and the dynamic network of friend relationships among avatars in the massively multiplayer online game (MMOG) Planetside 2. We are particularly interested in removal patterns in these networks. Our main finding is that in both of these networks the nodes which are most commonly removed are minor near isolated nodes. We also investigate the process of merging of two large networks using data captured during the merger of servers of Planetside 2. We found that the original network structures do not really merge but rather they get gradually replaced by newcomers not associated with the original structures. In the final part of the thesis we investigate the concept of motifs in the Barabási-Albert random graph. We establish some bounds on the number of motifs in this graph.

On-Line Handwritten Character Recognition using Kohonen Networks

This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds

Online Learning of Non-stationary Sequences

We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate a class of universal learning algorithms for this problem by expressing them as simple Bayesian algorithms operating on models analogous to Hidden Markov Models (HMMs). We derive a new performance bound for such algorithms which is considerably simpler than existing bounds. The bound provides the basis for learning the rate at which the identity of the optimal expert switches over time. We find an analytic expression for the a priori resolution at which we need to learn the rate parameter. We extend our scalar switching-rate result to models of the switching-rate that are governed by a matrix of parameters, i.e. arbitrary homogeneous HMMs. We apply and examine our algorithm in the context of the problem of energy management in wireless networks. We analyze the new results in the framework of Information Theory.

QoS online routing and MPLS multilevel protection: a survey

A survey of MPLS protection methods and their utilization in combination with online routing methods is presented in this article. Usually, fault management methods pre-establish backup paths to recover traffic after a failure. In addition, MPLS allows the creation of different backup types, and hence MPLS is a suitable method to support traffic-engineered networks. In this article, an introduction of several label switch path backup types and their pros and cons are pointed out. The creation of an LSP involves a routing phase, which should include QoS aspects. In a similar way, to achieve a reliable network the LSP backups must also be routed by a QoS routing method. When LSP creation requests arrive one by one (a dynamic network scenario), online routing methods are applied. The relationship between MPLS fault management and QoS online routing methods is unavoidable, in particular during the creation of LSP backups. Both aspects are discussed in this article. Several ideas on how these actual technologies could be applied together are presented and compared

CIP-OSN; Networks as Graphs

Curriculum Innovation Programme - Online Social Networks (UOSM2012) - Networks as Graphs

Utilidad de los conceptos y estrategias comunitarias en el marketing online para la prevención de la copia ilegal en el mercado musical

Esta investigación se dirige a determinar cuál es la utilidad de los conceptos y estrategias comunitarias en el marketing online para la prevención de la copia ilegal en el mercado musical. Con este proyecto se desea que por medio de una nueva disquera enfocada en el comercio online, y usando los conceptos del mercadeo comunitario y el mercadeo relacional, se pueda desarrollar nuevas estrategias de mercadeo en donde se logre incentivar y promover la compra de música original por medio de la creación de una relación más estrecha entre la compañía y el cliente, en la cual pueda afectar de forma positiva a la comunidad a la que este pertenece. El objetivo general es determinar cuál es la utilidad de los conceptos y estrategias comunitarias en el marketing online para la prevención de la copia ilegal en el mercado musical. Los objetivos específicos son: 1. Mostrar la utilidad de los conceptos y estrategias del marketing comunitario en la prevención de la copia ilegal del mercado musical y 2. Implementar las estrategias logradas en la investigación en un plan de creación de empresa. Se utilizará el método de investigación y análisis de caso, utilizando el plan de empresa en la creación de una empresa del mercado musical, tomando la relación estratégica comunitaria y el marketing dentro del plan de mercadeo como estrategia para la prevención de la copia ilegal. Mediante este proyecto se desea que por medio del marketing relacional y de los conceptos del mercadeo hacia comunidades, enfocado en une- marketing sepuedanestablecerestrategiasparalaprevencióndelacopiailegalydelacomprade estos productos Además, se busca implementar dichos resultados en la empresa que se pretende crear en el sector de la industria musical, puesto que la seguridad que tendrán los productos a la venta, serán la ventaja competitiva de la empresa.

Estrategias de mercadeo online para el lanzamiento de la marca Rio Technology® en Colombia

RIO TECHNOLOGY SAS es una empresa que lleva 11 años en el mercado de la distribución al por mayor de tecnología a todo nivel y suministros para oficina en Bogotá y en algunas otras ciudades del país. Fue constituida formalmente en el año 2001 ante la cámara de comercio de Bogotá como una sociedad anónima, y en el año 2010 cambió su tipo de sociedad, y se convirtió en sociedad por acciones simplificada, aprovechando los beneficios que este tipo de sociedad comercial brinda a las empresas medianas y pequeñas en Colombia. La idea de este proyecto nace porque desde Julio del año 2013, la marca RIO® se encuentra registrada, lo que genera grandes inquietudes acerca del cómo poder aprovechar esta situación para que la empresa RIO TECHNOLOGY se dé a conocer en el mercado y lograr un mayor crecimiento de la misma mediante la promoción y fortalecimiento de su marca, generando mayores utilidades. El mercadeo online podría ser una excelente alternativa para lanzar la marca RIO® al mercado; usando las redes sociales, por ejemplo, pues estas han sido creadas para conectar personas, grupos, páginas, etc. Y además son un medio de comunicación muy efectivo, por lo que la empresa RIO TECHNOLOGY podría estar en contacto permanente y cercano con sus clientes, dando a conocer en todo momento su marca RIO® mediante estrategias promocionales. En la actualidad, las redes sociales han significado una gran oportunidad tanto para las grandes empresas como para las Pymes; pues por medio de ellas se llega a una gran cantidad de personas en cuestión de segundos, con lo cual, usando estrategias eficientes, se logran resultados potenciales que se ven reflejados en un fortalecimiento de marca. El objetivo de este proyecto es presentar a RIO TECHNOLOGY un plan estratégico de mercadeo online para lanzar y fortalecer su marca. Se busca que la empresa mejore potencialmente el nivel de sus ventas y comience a posicionar su marca en el mercado.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Bayesian parameter estimation for latent Markov random fields and social networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.

BodyCloud: a SaaS approach for community body sensor networks

Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals.