Networks of Evolutionary Processors (NEP) as Decision Support Systems

This paper presents the application of Networks of Evolutionary Processors to Decision Support Systems, precisely Knowledge-Driven DSS. Symbolic information and rule-based behavior in Networks of Evolutionary Processors turn out to be a great tool to obtain decisions based on objects present in the network. The non-deterministic and massive parallel way of operation results in NP-problem solving in linear time. A working NEP example is shown.

A cloud-based farm management system:architecture and implementation

Recent technological advances have paved the way for developing and offering advanced services for the stakeholders in the agricultural sector. A paradigm shift is underway from proprietary and monolithic tools to Internet-based, cloud hosted, open systems that will enable more effective collaboration between stakeholders. This new paradigm includes the technological support of application developers to create specialized services that will seamlessly interoperate, thus creating a sophisticated and customisable working environment for the end users. We present the implementation of an open architecture that instantiates such an approach, based on a set of domain independent software tools called "generic enablers" that have been developed in the context of the FI-WARE project. The implementation is used to validate a number of innovative concepts for the agricultural sector such as the notion of a services' market place and the system's adaptation to network failures. During the design and implementation phase, the system has been evaluated by end users, offering us valuable feedback. The results of the evaluation process validate the acceptance of such a system and the need of farmers to have access to sophisticated services at affordable prices. A summary of this evaluation process is also presented in this paper. © 2013 Elsevier B.V.

Query Enrichment for Image Collections by Reuse of Classification Rules

User queries over image collections, based on semantic similarity, can be processed in several ways. In this paper, we propose to reuse the rules produced by rule-based classifiers in their recognition models as query pattern definitions for searching image collections.

Stakeholder preference and stated vs. derived importance satisfaction research

This paper presents a case study that reveals how stakeholders in the research process, by recommending specific data collection and analytical techniques, exert significant ‘hidden’ influence on the decisions made on the basis of market research findings. While disagreements amongst stakeholders regarding research design are likely, the possibility that strategies adopted by companies are dependent upon stakeholder research preferences has not been adequately addressed in the literature. Two widely used quantitative customer satisfaction evaluation approaches, involving stated and derived importance, are compared within a real life market research setting at an international bank. The comparative analysis informs an ongoing debate surrounding the applicability of explicit and implicit importance measures and demonstrates how recommendations are dependent upon the methodological and analytical techniques selected. The findings, therefore, have significant implications for importance based satisfaction market research planning and highlight the need to consider the impact of stakeholder preferences on research outcomes.

Making sense of microposts (#MSM2013) concept extraction challenge

Microposts are small fragments of social media content that have been published using a lightweight paradigm (e.g. Tweets, Facebook likes, foursquare check-ins). Microposts have been used for a variety of applications (e.g., sentiment analysis, opinion mining, trend analysis), by gleaning useful information, often using third-party concept extraction tools. There has been very large uptake of such tools in the last few years, along with the creation and adoption of new methods for concept extraction. However, the evaluation of such efforts has been largely consigned to document corpora (e.g. news articles), questioning the suitability of concept extraction tools and methods for Micropost data. This report describes the Making Sense of Microposts Workshop (#MSM2013) Concept Extraction Challenge, hosted in conjunction with the 2013 World Wide Web conference (WWW'13). The Challenge dataset comprised a manually annotated training corpus of Microposts and an unlabelled test corpus. Participants were set the task of engineering a concept extraction system for a defined set of concepts. Out of a total of 22 complete submissions 13 were accepted for presentation at the workshop; the submissions covered methods ranging from sequence mining algorithms for attribute extraction to part-of-speech tagging for Micropost cleaning and rule-based and discriminative models for token classification. In this report we describe the evaluation process and explain the performance of different approaches in different contexts.

Systematic microcarrier screening and agitated culture conditions improves human mesenchymal stem cell yield in bioreactors

Production of human mesenchymal stem cells for allogeneic cell therapies requires scalable, cost-effective manufacturing processes. Microcarriers enable the culture of anchorage-dependent cells in stirred-tank bioreactors. However, no robust, transferable methodology for microcarrier selection exists, with studies providing little or no reason explaining why a microcarrier was employed. We systematically evaluated 13 microcarriers for human bone marrow-derived MSC (hBM-MSCs) expansion from three donors to establish a reproducible and transferable methodology for microcarrier selection. Monolayer studies demonstrated input cell line variability with respect to growth kinetics and metabolite flux. HBM-MSC1 underwent more cumulative population doublings over three passages in comparison to hBM-MSC2 and hBM-MSC3. In 100 mL spinner flasks, agitated conditions were significantly better than static conditions, irrespective of donor, and relative microcarrier performance was identical where the same microcarriers outperformed others with respect to growth kinetics and metabolite flux. Relative growth kinetics between donor cells on the microcarriers were the same as the monolayer study. Plastic microcarriers were selected as the optimal microcarrier for hBM-MSC expansion. HBM-MSCs were successfully harvested and characterised, demonstrating hBM-MSC immunophenotype and differentiation capacity. This approach provides a systematic method for microcarrier selection, and the findings identify potentially significant bioprocessing implications for microcarrier-based allogeneic cell therapy manufacture. Large-scale production of human bone-marrow derived mesenchymal stem cells (hBM-MSCs) requires expansion on microcarriers in agitated systems. This study demonstrates the importance of microcarrier selection and presents a systematic methodology for selection of an optimal microcarrier. The study also highlights the impact of an agitated culture environment in comparison to a static system, resulting in a significantly higher hBM-MSC yield under agitated conditions.

What counts versus what can be counted:the complex interplay of market orientation and marketing performance measurement

Market orientation (MO) and marketing performance measurement (MPM) are two of the most widespread strategic marketing concepts among practitioners. However, some have questioned the benefits of extensive investments in MO and MPM. More importantly, little is known about which combinations of MO and MPM are optimal in ensuring high business performance. To address this research gap, the authors analyze a unique data set of 628 firms with a novel method of configurational analysis: fuzzy-set qualitative comparative analysis. In line with prior research, the authors find that MO is an important determinant of business performance. However, to reap its benefits, managers need to complement it with appropriate MPM, the level and focus of which vary across firms. For example, whereas large firms and market leaders generally benefit from comprehensive MPM, small firms may benefit from measuring marketing performance only selectively or by focusing on particular dimensions of marketing performance. The study also finds that many of the highest-performing firms do not follow any of the particular best practices identified.

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

Are Consumers Ready for Mobile Payment? An Examination of Consumer Acceptance of Mobile Payment Technology in Restaurant Industry

As an emerging payment method, mobile payment technology is perceived to be a secure and effective substitute of traditional debit/credit card payment. Although several reports and scholars claimed that mobile payment technology would become a major future payment method, consumers rather caught on this trend slowly, and little is known about key determinants of consumers’ acceptance of mobile payment. To close that gap, the current study extended the classic Technology Acceptance Model by adding four additional predictors that are relevant to hospitality industry. The study results suggested that compatibility with lifestyle was the strongest predictor of consumers’ intention to adopt mobile payment technology in restaurants, followed by perceived usefulness, subjective norm, security, and previous experience with mobile payment. Important theoretical and practical implications were provided based on our findings.

Empirical likelihood based longitudinal studies

In longitudinal data analysis, our primary interest is in the regression parameters for the marginal expectations of the longitudinal responses; the longitudinal correlation parameters are of secondary interest. The joint likelihood function for longitudinal data is challenging, particularly for correlated discrete outcome data. Marginal modeling approaches such as generalized estimating equations (GEEs) have received much attention in the context of longitudinal regression. These methods are based on the estimates of the first two moments of the data and the working correlation structure. The confidence regions and hypothesis tests are based on the asymptotic normality. The methods are sensitive to misspecification of the variance function and the working correlation structure. Because of such misspecifications, the estimates can be inefficient and inconsistent, and inference may give incorrect results. To overcome this problem, we propose an empirical likelihood (EL) procedure based on a set of estimating equations for the parameter of interest and discuss its characteristics and asymptotic properties. We also provide an algorithm based on EL principles for the estimation of the regression parameters and the construction of a confidence region for the parameter of interest. We extend our approach to variable selection for highdimensional longitudinal data with many covariates. In this situation it is necessary to identify a submodel that adequately represents the data. Including redundant variables may impact the model’s accuracy and efficiency for inference. We propose a penalized empirical likelihood (PEL) variable selection based on GEEs; the variable selection and the estimation of the coefficients are carried out simultaneously. We discuss its characteristics and asymptotic properties, and present an algorithm for optimizing PEL. Simulation studies show that when the model assumptions are correct, our method performs as well as existing methods, and when the model is misspecified, it has clear advantages. We have applied the method to two case examples.

Long chain diols and diol indices of surface sediments of the Iberian Atlantic margin

Long chain diols are lipids that have gained interest over the last years due to their high potential to serve as biomarkers and diol indices have been proposed to reconstruct upwelling conditions and sea surface temperature (SST). However, little is known about the sources of the diols and the mechanisms impacting their distribution. Here we studied the factors controlling diol distributions in the Iberian Atlantic margin, which is characterized by a dynamic continental shelf under the influence of upwelling of nutrient-rich cold deep waters, and fluvial input. We analyzed suspended particulate matter (SPM) of the Tagus river, marine SPM and marine surface sediments along five transects off the Iberian margin, as well as riverbank sediments and soil from the catchment area of the Tagus river. Relatively high fractional abundances of the C32 1,15-diol (normalized with respect to the 1,13- and 1,15-diols) were observed in surface sediments in front of major river mouths and this abundance correlates strongly with the BIT index, a tracer for continental input of organic carbon. Together with an even higher fractional abundance of the C32 1,15-diol in the Tagus river SPM, and the absence of long chain diols in the watershed riverbank sediments and soils, we suggest that this long chain diol is produced in-situ in the river. Further support for this hypothesis comes from the small but distinct stable carbon isotopic difference of 1.3? with the marine C28 1,13-diol. The 1,14-diols are relatively abundant in surface sediments directly along the northern part of the coast, close to the upwelling zone, suggesting that Diol Indices based on 1,14-diols would work well as upwelling tracers in this region. Strikingly, we observed a significant difference in stable carbon isotopic composition between the monounsaturated C30:1 1,14- and the saturated C28 1,14-diol (3.8±0.7 per mil), suggesting different sources, in accordance with their different distributions. In addition, the Long chain Diol Index (LDI), a proxy for sea surface temperature, was applied for the surface sediments. The results correlate well with satellite SSTs offshore but reveal a significant discrepancy with satellite-derived SSTs in front of the Tagus and Sado rivers. This suggests that river outflow might compromise the applicability of this proxy.

Migrant women’s employment in paid reproductive work through the crisis: the case of Italy (2007-2012)

Paid reproductive work, especially in the case of cleaning and home-care for elderly people, is an important sector for foreign women in Italy. For this reason, since the beginning of the current economic crisis, scholars have wondered about the impact of the recession on migrant domestic workers. They have looked particularly at possible competition with Italian women entering the sector for lack of better alternatives. Our paper takes this discussion a step further by assessing the overall changes affecting migrant women in the Italian labour market, 2007-2012. We will look at how their position has been transformed, by taking both an ethnic perspective, in relation to Italian women, and a gender perspective, in relation to migrant men. By way of a conclusion, the argument will be made that there is a substantial lack of competition between Italian and foreign women in the care and domestic sector due to differences in their earnings, hours of work and activities.

Long-term modifications of coastal defences enhance marine biodiversity

Realization that hard coastal infrastructures support lower biodiversity than natural habitats has prompted a wealth of research seeking to identify design enhancements offering ecological benefits. Some studies showed that artificial structures could be modified to increase levels of diversity. Most studies, however, only considered the short-term ecological effects of such modifications, even though reliance on results from short-term studies may lead to serious misjudgements in conservation. In this study, a seven-year experiment examined how the addition of small pits to otherwise featureless seawalls may enhance the stocks of a highly-exploited limpet. Modified areas of the seawall supported enhanced stocks of limpets seven years after the addition of pits. Modified areas of the seawall also supported a community that differed in the abundance of littorinids, barnacles and macroalgae compared to the controls. Responses to different treatments (numbers and size of pits) were species-specific and, while some species responded directly to differences among treatments, others might have responded indirectly via changes in the distribution of competing species. This type of habitat enhancement can have positive long-lasting effects on the ecology of urban seascapes. Understanding of species interactions could be used to develop a rule-based approach to enhance biodiversity.

Long-term modifications of coastal defences enhance marine biodiversity

Realization that hard coastal infrastructures support lower biodiversity than natural habitats has prompted a wealth of research seeking to identify design enhancements offering ecological benefits. Some studies showed that artificial structures could be modified to increase levels of diversity. Most studies, however, only considered the short-term ecological effects of such modifications, even though reliance on results from short-term studies may lead to serious misjudgements in conservation. In this study, a seven-year experiment examined how the addition of small pits to otherwise featureless seawalls may enhance the stocks of a highly-exploited limpet. Modified areas of the seawall supported enhanced stocks of limpets seven years after the addition of pits. Modified areas of the seawall also supported a community that differed in the abundance of littorinids, barnacles and macroalgae compared to the controls. Responses to different treatments (numbers and size of pits) were species-specific and, while some species responded directly to differences among treatments, others might have responded indirectly via changes in the distribution of competing species. This type of habitat enhancement can have positive long-lasting effects on the ecology of urban seascapes. Understanding of species interactions could be used to develop a rule-based approach to enhance biodiversity.