Face detection and recognition of natural human emotion using Markov random fields

This paper presents an integrated system for emotion detection. In this research effort, we have taken into account the fact that emotions are most widely represented with eye and mouth expressions. The proposed system uses color images and it is consisted of three modules. The first module implements skin detection, using Markov random fields models for image segmentation and skin detection. A set of several colored images with human faces have been considered as the training set. A second module is responsible for eye and mouth detection and extraction. The specific module uses the HLV color space of the specified eye and mouth region. The third module detects the emotions pictured in the eyes and mouth, using edge detection and measuring the gradient of eyes’ and mouth’s region figure. The paper provides results from the system application, along with proposals for further research.     

Giant Anomalous Hall and Nernst Conductivities in Magnetic All-d Metal Heusler Alloys

All-d Heuslers are a category of novel compounds combining versatile functionalities such as caloric responses and spintronics with enhanced mechanical properties. Despite the promising transport properties (anomalous Hall (AHC) and anomalous Nernst (ANC) conductivities) shown in the conventional Co₂XY Heuslers with p-d hybridization, the all-d Heuslers with only d-d hybridization open a new horizon to search for new candidates with outstanding transport properties. In this work, the AHC and ANC are evaluated for thermodynamically stable ferro/ferri-magnetic all-d-metal regular Heusler compounds based on high-throughput first-principles calculations. It is observed that quite a few materials exhibit giant AHCs and ANCs, such as cubic Re₂TaMn with an AHC of 2011 S cm^-1, and tetragonal Pt₂CrRh with an AHC of 1966 S cm^-1 and an ANC of 7.50 A m^-1K^-1. Comprehensive analysis on the electronic structure reveals that the high AHC can be attributed to the occurrence of the Weyl nodes or gapped nodal lines in the neighborhood of the Fermi level. The correlations between such transport properties and the number of valence electrons are also thoroughly investigated, which provides a practical guidance to tailor AHC and ANC via chemical doping for transverse thermoelectric applications.     

HISYCOL a hybrid computational intelligence system for combined machine learning: the case of air pollution modeling in Athens

The analysis of air quality and the continuous monitoring of air pollution levels are important subjects of the environmental science and research. This problem actually has real impact in the human health and quality of life. The determination of the conditions which favor high concentration of pollutants and most of all the timely forecast of such cases is really crucial, as it facilitates the imposition of specific protection and prevention actions by civil protection. This research paper discusses an innovative threefold intelligent hybrid system of combined machine learning algorithms HISYCOL (henceforth). First, it deals with the correlation of the conditions under which high pollutants concentrations emerge. On the other hand, it proposes and presents an ensemble system using combination of machine learning algorithms capable of forecasting the values of air pollutants. What is really important and gives this modeling effort a hybrid nature is the fact that it uses clustered datasets. Moreover, this approach improves the accuracy of existing forecasting models by using unsupervised machine learning to cluster the data vectors and trace hidden knowledge. Finally, it employs a Mamdani fuzzy inference system for each air pollutant in order to forecast even more effectively its concentrations.     

Accessibility-based reranking in multimedia search engines

Multimedia Tools and Applications - Traditional multimedia search engines retrieve results based mostly on the query submitted by the user, or using a log of previous searches to provide...     

Efficiently Testing Sparse <Emphasis Type="Italic">GF</Emphasis>(2) Polynomials

We give the first algorithm that is both query-efficient and time-efficient for testing whether an unknown function f:{0,1} ⁿ →{−1,1} is an s-sparse GF(2) polynomial versus ε-far from every such polynomial. Our algorithm makes poly(s,1/ε) black-box queries to f and runs in time n⋅poly(s,1/ε). The only previous algorithm for this testing problem (Diakonikolas et al. in Proceedings of the 48th Annual Symposium on Foundations of Computer Science, FOCS, pp. 549–558, 2007) used poly(s,1/ε) queries, but had running time exponential in s and super-polynomial in 1/ε.     

Computer mediated communication for social and academic purposes: Profiles of use and University students’ gratifications

The present study approaches the Internet as a social space, where university students make use of computer mediated communication (CMC) applications, i.e. e-mail, instant messaging and social network sites, in order to satisfy social and academic needs. We focus on university students, because they represent one of the most avid groups of CMC users and additionally, because they are expected to carry their perceptions of media with them into the work place and their social life. In order to investigate this issue, we conducted an empirical research using, as a target group, a sample of students from a specific Greek University. Grounded in the “uses and gratifications” perspective, we investigated the various profiles of CMC use by students along with (a) the students’ perceptions about social and academic usefulness of CMC applications, (b) the extent up to which these perceptions are correlated with students’ prior experience with the use of CMC applications, and (c) how both of these factors can predict the frequency of present use of CMC for social or academic purposes respectively. The results reveal that although these three CMC applications constitute “functional alternatives” (media that satisfy similar needs) they are different to the degree of their “functionality” for the gratification of social and academic needs. Furthermore, the degree of CMC use by students is not correlated with the years of CMC experience, but with the profile of use that students dynamically adopt according to their daily needs and preferences. The results provide evidence for the current CMC use by university students and can be useful for the implementation of further academic policies regarding CMC use in Higher Education settings.     

Controlling Salmonella infections in pig farms: A framework modelling approach

Human salmonellosis is an important food-borne disease and S. Typhimurium is the most common serotype attributed to pork products. Under a farm-to-fork strategy, reducing the levels of Salmonella-positive pigs entering the slaughterhouse is an important goal. A framework model was developed, where the effect of dynamic (infection characteristics) and non-dynamic (cleanness and disinfection, biosecurity measures, etc.) factors were considered. Four baseline scenarios were created, corresponding to different levels associated with national Salmonella monitoring programs, and sensitivity analyses were run for the non-dynamic factors. Moreover, the option of vaccination was incorporated into the model, in order to provide with a tool for the formulation of an optimum vaccination strategy depending on the characteristics of the vaccine.