Ordinal regression by a gravitational model in the field of educational data mining

Educational data mining (EDM) is a research area where the goal is to develop data mining methods to examine data critically from educational environments. Traditionally, EDM has addressed the following problems: clustering, classification, regression, anomaly detection and association rule mining. In this paper, the ordinal regression (OR) paradigm, is introduced in the field of EDM. The goal of OR problems is the classification of items in an ordinal scale. For instance, the prediction of students' performance in categories (where the different grades could be ordered according to A ? B ? C ? D) is a classical example of an OR problem. The EDM community has not yet explored this paradigm (despite the importance of these problems in the field of EDM). Furthermore, an amenable and interpretable OR model based on the concept of gravitation is proposed. The model is an extension of a recently proposed gravitational model that tackles imbalanced nominal classification problems. The model is carefully adapted to the ordinal scenario and validated with four EDM datasets. The results obtained were compared with state‐of‐the‐art OR algorithms and nominal classification ones. The proposed models can be used to better understand the learning–teaching process in higher education environments.     

Stability of Local On‐Ramp Metering Control Laws

A framework for stability analysis of local on‐ramp metering control strategies based on the cell transmission model is presented. Within this framework, it is possible to formulate Lyapunov and input‐state stability results for on‐ramp metering control strategies in an open section of highway with on‐ramps. Using this analysis, recommendations for the design of on‐ramp metering control laws set points are derived. Two examples on the use of such analysis are presented. One deals with the stability analysis of a local on‐ramp metering control law and the other with the design of a disturbance observer that, used in combination with the local on‐ramp metering control law, provides a more robust response to traffic regulation. Simulation results are included that confirm the possibility of using this framework to test the impact of local on‐ramp metering control strategies.     

On location observability notions for switching systems

The focus of this paper is on the analysis of initial discrete state distinguishability notions for switching systems, in a discrete time setting. Moreover, the relationship between initial discrete state distinguishability and the problem of reconstructing the current discrete state is addressed.     

Selfish Bin Packing

Following recent interest in the study of computer science problems in a game theoretic setting, we consider the well known bin packing problem where the items are controlled by selfish agents. Each agent is charged with a cost according to the fraction of the used bin space its item requires. That is, the cost of the bin is split among the agents, proportionally to their sizes. Thus, the selfish agents prefer their items to be packed in a bin that is as full as possible. The social goal is to minimize the number of the bins used. The social cost in this case is therefore the number of bins used in the packing.     

Utilizing national public-key infrastructure in mobile payment systems

Payments are the locomotive behind any business domain. It has been predicted that mobile payments will become one of the most successful mobile services, and the security of payments is an important requirement. However, it is difficult to strongly authenticate mobile users remotely and provide an adequate level of non-repudiation of transactions. In this article, we argue that a nationwide public-key infrastructure supported by governmental bodies can be used in a mobile payment system. Not only does it provide strong security, but it also makes the system open to any mobile user, merchant, or financial service provider. Two payment protocols are described: one for virtual point-of-sale payments, and one for vending machine payments. We argue that such a system can be implemented using open development platforms, and its performance is adequate for enabling swift transactions. A prototype of a system which accepts virtual point-of-sale payments is implemented, and its performance and usability are evaluated.     

Influence of temperature on the liver circadian clock in the ruin lizard Podarcis sicula

Reptiles represent an interesting animal model to investigate the influence of temperature on molecular circadian clocks. The ruin lizard Podarcis sicula lives in a continental climate and it is subjected to wide range of environmental temperatures during the course of the year. As consequence, ruin lizard daily activity pattern includes either the hibernation or periods of inactivity determined by hypothermia. Here we showed the rhythmic expression of two clock genes, lPer2 and lClock, in the liver of active lizards exposed to summer photo-thermoperiodic conditions. Interestingly, the exposition of lizards to hypothermic conditions, typical of winter season, induced a strong dampening of clock genes mRNA rhythmicity with a coincident decrease of levels. We also examined the qualitative and quantitative distribution of lPER2 and lCLOCK protein in different cellular compartments during the 24-h cycle. In the liver of active lizards both proteins showed a rhythmic expression profile in all cellular compartments. After 3 days at 6 degrees C, some temporal fluctuations of the lCLOCK and lPER2 are still detectable, although, with some marked modifications in respect to the values detected in the liver of active lizards. Besides demonstrating the influence of low temperature on the lizard liver circadian oscillators, present results could provide new essential information for comparative studies on the influence of temperature on the circadian system across vertebrate classes.     

Electro-oxidation of two reactive azo dyes on boron-doped diamond electrode

Electrochemical oxidation (decolorization/degradation) of blue and red commercial reactive azo dyes was carried out on boron-doped diamond (BDD) electrode. The effect of various quantities of FeSO(4) was investigated in the electro-Fenton reaction on BDD. Progress of dyes degradation during the electrolysis and electro-Fenton reaction was monitored by UV-visible absorption and by estimation of the chemical oxygen demand (COD). Direct electrolysis showed a limiting capacity for red and blue dye removal even at high current densities, e.g. maximum red color and COD removal were 70 and 20%, respectively at 30 mA cm(-2) after 300 min. Higher red and blue color removal efficiencies were achieved by electro-Fenton oxidation. Current density of 30 mA cm(-2) in the presence of 0.05 mmol/L of FeSO(4) resulted in the red color and COD removal of 98 and 96%, respectively. The optimum FeSO(4) concentration for the electro-Fenton reaction was determined to be 0.05 mmol/L. Instantaneous current efficiency (ICE) in the presence of FeSO(4) was almost three times higher than for experiments carried out without FeSO(4).     

Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.     

Distance maps from unthresholded magnitudes

A straightforward algorithm that computes distance maps from unthresholded magnitudes is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of spatial and temporal coherence of distance map values, showing better results in both measurements than those obtained with Sobel or Deriche gradients and classic chessboard distance transforms.