Blanca L. Delgado-Márquez

Human activity recognition based on a sensor weighting hierarchical classifier

The analysis of daily living human behavior has proven to be of key importance to prevent unhealthy habits. The diversity of activities and the individuals’ particular execution style determine that several sources of information are normally required. One of the main issues is to optimally combine them to guarantee performance, scalability and robustness. In this paper we present a fusion classification methodology which takes into account the potential of the individual decisions yielded at both activity and sensor classification levels. Particularly tested on a wearable sensors based system, the method reinforces the idea that some parts of the body (i.e., sensors) may be specially informative for the recognition of each particular activity, thus supporting the ranking of the decisions provided by each associated sensor decision entity. Our method systematically outperforms the results obtained by traditional multiclass models which otherwise may require a high-dimensional feature space to acquire a similar performance. The comparison with other activity-recognition fusion approaches also demonstrates our model scales significantly better for small sensor networks.

Internationalization of Higher Education: Theoretical and Empirical Investigation of Its Influence on University Institution Rankings

Internationalization constitutes a broadly widespread concept in the literature about management. However, it has recently started being applied to higher education institutions. In this paper, we investigate internationalization in university institutions from both theoretical and empirical perspectives. To achieve our aim, we place particular emphasis on the methodology applied to evaluate the internationalization of higher education institutions from both quantitative and qualitative approaches. We focus on the study of the three most widely accepted higher education institution rankings: Times Higher Education Supplement, Academic Ranking of World Universities and Webometrics Ranking. We find that, while the variable internationalization is included in such rankings through several items, its weight in the overall score is still limited. Additionally, our results demonstrate that the final position achieved by university institutions is hardly determined by their degree of internationalization, but rather relies on other institutional aspects, such as teaching quality and research quality, among others. Furthermore, we argue that internationalization indicators used in current university institution rankings, e.g., international faculty ratio and international students ratio, are far from reflecting the main variables involved in their internationalization processes.ResumenEl concepto de internacionalización está ampliamente difundido en la bibliografía sobre gestión. Pero recientemente también se ha empezado a utilizar en el ámbito de las instituciones de enseñanza superior. En este artículo investigaremos la internacionalización en las instituciones universitarias desde dos perspectivas, teórica y práctica. Para lograr nuestro objetivo, hemos dado especial importancia a la metodología utilizada para evaluar la internacionalización en las instituciones de enseñanza superior desde un punto de vista tanto cualitativo como cuantitativo. Nos hemos centrado en el estudio de las tres clasificaciones de instituciones de enseñanza superior más ampliamente aceptadas: Times Higher Education Supplement, Academic Ranking of World Universities y Webometrics Ranking. Hemos visto que, aunque la variable de la internacionalización se tiene en cuenta en dichas clasificaciones a través de varios factores, su peso en la puntuación global es aun limitado. Además, los resultados que hemos obtenido demuestran que el grado de internacionalización de las instituciones universitarias apenas determina su posición final en las clasificaciones, ya que esta depende de otros aspectos institucionales como la calidad de la enseñanza y la calidad de la investigación, entre otros factores. Asimismo hemos visto que los indicadores de internacionalización utilizados en las clasificaciones más corrientes de instituciones universitarias, como la proporción de personal docente internacional y la proporción de estudiantes internationales, distan mucho de reflejar las principales variables que intervienen en los procesos de internacionalización.

Advanced system for automously classify brain MRI in neurodegenerative disease

There are several dementias but Alzheimers Disease (AD) is leading cause of dementia in the world. There are an estimated 35.6 million people in the world with dementia and more than 18 million of them have Alzheimers disease, which supposes more of the 50% of the total people with dementia. In this paper, intelligent algorithms are designed and implemented in order to manipulate Magnetic Resonance Images (MRI) stored in a big data base of patients, with the main purpose of being able for decision-making in classification task. It will be possible to predict whether the patient is healthy, has Mild Cognitive Impairment (MCI), or already has Alzheimer Disease. We tested our method on data from a large data base (more than 1500 patient were analized), with a sensitivity of and specificity close to 90%which is considerable better the human experts, taking into account that in this paper also MCI is classified. It is noteworthy that with this last study we could offer a tool to assist the early diagnosis of dementia and has the potential to be a useful help for clinicians.

A more balanced composition of the European Parliament with degressive proportionality

Degressive proportionality constitutes the main conceptual criterion to determine the composition of the European Parliament (EP). In reality, however, this concept entails serious practical problems as exemplified by the current distribution of seats in the EP. This article takes up the call and presents a new method for a better balanced seat allocation in the EP after the 2014 elections. Comparing with recent methods in the field, our results reveal that the method proposed yields a more balanced and juster parliamentary seat distribution among all European member states by joining the strengths of the existing methods and avoiding their weaknesses. In light of upcoming rounds of enlargement and possible amendments to the EPs internal rules of procedure and existing EU Treaties, we contend that our results are not only of interest to the academic world.

Statistical analysis of different artificial intelligent techniques applied to Intrusion Detection System

Intrusion Detection System (IDS) which are increasingly a key part of system defense are used to identify abnormal activities in a computer system. In general, the traditional IDS relies on the extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been used in the literature. The experiments and evaluations of the proposed intrusion detection system are performed with the NSL-KDD intrusion detection dataset. We will apply different learning algorithms on NSL-KDD data set, to recognize between normal and attack connections and compare their performing in different scenarios- discretization, features selections and algorithm method for classification- using a powerful statistical analysis: ANOVA. In this study, both the accuracy of the configuration of different system and methodologies used, and also the computational time and complexity of the methodologies are analyzed.

Industries Regulation and Firm Environmental Disclosure A Stakeholders’ Perspective on the Importance of Legitimation and International Activities

The potential negative environmental consequences of the activities of international firms has been scrutinized. In response to these pressures, international firms have started to disclose (voluntarily or not) environmental information in order to increase transparency and ensure legitimacy. While several factors have been pointed out as the drivers of such disclosing behavior, the role of industrial regulation has remained underesearched. To better understand this challenge, we rely on a sample of 1,150 international firms (top vs. nontop) worldwide from regulated and unregulated sectors. Our results suggest that unregulated firms disclose—to cope with higher stakeholders pressures—more environmental information than firms operating in regulated environments. Additionally, a firm’s international position positively influences its environmental disclosure, but it does negatively and partially moderate the relationship between industrial regulation of the sector in which the firm operates and such firm’s environmental disclosure. Our findings may also entail interesting contributions both for practitioners and scholars.

Does knowledge explain trust behaviors and outcomes? The different influences of initial knowledge and experiential knowledge on personal trust interactions.

This paper examines the influences of initial knowledge and experiential knowledge on trust behaviors and trust outcomes, respectively, at an interpersonal level. We use an experimental dynamic trust game, and our results show that (1) the initial knowledge that exists a priori between a trustor and a trustee helps to explain the trustors trust behaviors toward the trustee, and (2) the experiential knowledge gained directly by a trustor during a specific trust interaction with a trustee influences the trust outcome, i.e. the difference between the original expectations of the trustor and the subsequent trust behaviors. Our results contribute to human resource literature by clarifying the specific influences of different types of knowledge on interpersonal trust relationships (e.g. between managers and employees) and by supplementing the traditional notion that trust within a firm develops slowly by showing that personal expectations have an immediate and important influence on trust output.

Geographical Distribution and Regional Specialization of Knowledge-Intensive Business Services: An Empirical Investigation Across European Regions

This chapter is aimed at investigating both geographical concentration and regional specialization in KIBS during the last years. Specifically, this chapter focuses on European regions and seeks (a) to identify the location of KIBS, (b) to investigate regional specialization profiles in KIBS and (c) to shed light on the variables driving the location of KIBS. Results on spatial concentration show a process of spatial dispersion between 1995 and 2007 that is modified afterwards due to the economic crisis. Furthermore, the data also reveal important differences in terms of regional specialization for each category of KIBS. Finally, our analyses confirm the existence of significant influences of several variables related to economies of agglomeration and accessibility to clients and knowledge resources on regional specialization in KIBS across European regions, as stated by the previous literature.

Relationships between corruption, political orientation, and income inequality: evidence from Latin America

ABSTRACT This research sheds light on the analysis of the impact of corruption and political orientation on income distribution in Latin America. Although it has been theoretically demonstrated that corruption worsens the income distribution, the empirical evidence has yielded ambiguous results based on biased estimates not considering a measurement error in the estimation of inequality. This article fills this gap by correcting the previous measurement error bias in the fixed-effects estimation. Additionally, political orientation and its relationship with income inequality are also investigated. The sample covers 18 Latin American countries between 1996 and 2012. Results reveal that corruption increases income inequality.

A network view of innovation performance for multinational corporation subsidiaries

ABSTRACT A network view of innovation performance for multinational corporation subsidiaries: functionality and geography. Regional Studies. The literature has recognized the need to understand better the role of network partner characteristics on innovative performance in cases of multiple network embeddedness. This study argues that innovation performance is partly a function of the value created through intra- and inter-organizational flows of knowledge within and across regions. The analyses are based on two random-effects logistic models with sample selection. Results show that the functional breadth of a subsidiary’s inter-organizational network has an inverted ‘U’-shaped relationship with its radical and incremental innovation performance. Additionally, radical innovation performance is influenced by internal and external partners from different geographical locations.