Comparison of gain-loss asymmetry behavior for stocks and indexes

Investment horizon approach has been used to analyze indexes of Polish stock market.Optimal time horizon for each return value is evaluated by fitting appropriate function form of the distribution. Strong asymmetry of gain-loss curves is observed for WIG index, whereas gain and loss curves look similar for WIG20 and for most of individual companies stocks. The gain-loss asymmetry for these data, measured by the coefficient, that we postulated before \cite{karpio}, has opposite sign to this for WIG index.Comment: To be published in Acta Phys. Pol.

Application of bagging, boosting and stacking to intrusion detection

This paper investigates the possibility of using ensemble algorithms to improve the performance of network intrusion detection systems. We use an ensemble of three different methods, bagging, boosting and stacking, in order to improve the accuracy and reduce the false positive rate. We use four different data mining algorithms, naïve bayes, J48 (decision tree), JRip (rule induction) and iBK( nearest neighbour), as base classifiers for those ensemble methods. Our experiment shows that the prototype which implements four base classifiers and three ensemble algorithms achieves an accuracy of more than 99% in detecting known intrusions, but failed to detect novel intrusions with the accuracy rates of around just 60%. The use of bagging, boosting and stacking is unable to significantly improve the accuracy. Stacking is the only method that was able to reduce the false positive rate by a significantly high amount (46.84%); unfortunately, this method has the longest execution time and so is insufficient to implement in the intrusion detection fiel

Methodological identification of opportunities for development of smart specialization in Pomorskie Voivodship in Poland

Smart specialization as a concept plays a more and more important role in development of the regions. David, Foray and Hall point it, as an important instrument for creating a strategy for the development of innovation at the state and regional level as well as for defining and building the knowledge-based economy. This term is present in a number of strategic development documents in the European Union, including Europe 2020, published by the European Commission in 2010. It implies the need for countries and regions to specialize as well as focus development of innovation in areas that are consistent with their endogenous potentials. This paper presents the method as well as results of the studies undertaken to define the smart specialization of Pomerania, which is one of two Polish voivodeships with access to the Baltic Sea. Its main settlement node is the emerging metropolitan area of Gdansk - the fourth largest in Poland. Part of this research was project Identification of Smart Specialization in Pomerania Voivodeship - Technological Convergence, commissioned by the Regional Government. Technological convergence was defined as phenomenon of the use of technologies from different industries for the creation of a new specialization in order to gain a competitive advantage. The aim of the project was to analyze and evaluate the economic potential of the Voivodeship, indicating possible areas of cooperation between representatives of different industries. It was assumed that the process of identifying smart specialization would be a bottom-up approach. Regional Government invited all actors to build a partnership. They worked on identifying potentials then building on this analysis, developed a common strategy for the development of technological and functional smart specialization. Analytical and diagnostic processes included: desk research, expert studies, individual in-depth interviews, focus group interviews, workshops and the Delphi study, SWOT analysis. The result is an aid for all stakeholders to identify opportunities and specify areas of development of smart specializations for the Voivodship. The method of identification of the priorities and implementation of the actions for the development of smart specializations assumes that the process itself should be flexible, meaning that adopted priorities and allocation of resources need to be reviewed and modified if such need occurs. The authors also present their recommendation to enhance this method; propose its modification and expansion to include e.g. conduct the Competitive Position Analysis of Porter's Five Forces

Student success on face-to-face instruction and MOOCs : what can learning analytics uncover?

There are fundamental differences between the face-to-faceinstruction model and that of Massive Open Online Courses.This paper hypothesises that despite these fundamental dif-ferences, the success factors in these learning contexts arecomparable. The factors contributing to student successmight be related to the same basic principles, even if mani-festing themselves differently in each context - especially asthe very definition of success is closely dependent on whatcan be measured. Learning analytics can help to uncover theindicators which have the potential for identifying studentsat-risk and for institutions to exercise a timely intervention.Publisher PDFPeer reviewe

Reprogramming embedded systems at run-time

The dynamic re-programming of embedded systems is a long-standing problem in the field. With the advent of wireless sensor networks and the 'Internet of Things' it has now become necessary to be able to reprogram at run-time due to the difficulty of gaining access to such systems once deployed. The issues of power consumption, flexibility, and operating system protections are examined for a range of approaches, and a critical comparison is given. A combination of approaches is recommended for the implementation of real-world systems and areas where further work is required are highlighted.Postprin