Micro-expression recognition from local facial regions

MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods.     

Temperature dependent negative permittivity in solid solutions Sr2Mn1-xSnxO4 (x = 0, 0.3, 0.5)

A few compositions of the system Sr₂Mn_1-xSn_xO₄ (x = 0.0, 0.3, 0.5) were synthesized in the air by the solid-state ceramic route. A change in the sign (positive to negative) of the permittivity above a particular temperature (T_C) is observed at all the measured frequencies. The negative permittivity was analyzed by the Drude-Lorentz model. It was found that negative permittivity is caused by the plasma oscillations of thermally excited free charge carriers. Analysis of XPS spectra confirmed the presence of mixed-valence states of both Mn (Mn⁴⁺ and Mn³⁺) and Sn (Sn⁴⁺ and Sn²⁺) ions. The UV–vis.-IR spectroscopy results indicated generation of a large number of defect states in the forbidden bandgap region of Sr₂MnO₄ on the substitution of Sn at Mn site. Synthesized samples are promising metamaterials for radio frequency (10 Hz -2 MHz) region applications due to the high-temperature plasmonic behavior.     

Cross project defect prediction: a comprehensive survey with its SWOT analysis

Innovations in Systems and Software Engineering - Software fault prediction (SFP) refers to the process of identifying (or predicting) faulty modules based on its characteristics/software metrics....     

Importance of optical homogeneity for high-quality transparent ceramics

Two types of transparent Y₂O₃ ceramics without including large scattering sources such as residual pores, one with very high optical homogeneity (type A) and another one with slightly insufficient optical homogeneity (type B), are purposely prepared, and their optical properties are investigated and compared qualitatively and quantitatively. Type A ceramic exhibits transmittance characteristics with very low internal loss in the visible to infrared wavelength region, while type B ceramic is inferior in various optical performances especially in the short (visible) wavelength region. In type B ceramic, birefringence occurs due to optical inhomogeneity in the visible region, resulting in a decrease in the extinction ratio. Non-uniform refractive index distribution is also observed in the Schlieren image of type B ceramic, hence the laser beam quality through that material is degraded. This study proved the importance of optical homogeneity of transparent ceramics and clarified the problems in actual applications.     

Quantification of Dendritic Spines Remodeling under Physiological Stimuli and in Pathological Conditions

Numerous brain diseases are associated with abnormalities in morphology and density of dendritic spines, small membranous protrusions whose structural geometry correlates with the strength of synaptic connections. Thus, the quantitative analysis of dendritic spines remodeling in microscopic images is one of the key elements towards understanding mechanisms of structural neuronal plasticity and bases of brain pathology. In the following article, we review experimental approaches designed to assess quantitative features of dendritic spines under physiological stimuli and in pathological conditions. We compare various methodological pipelines of biological models, sample preparation, data analysis, image acquisition, sample size, and statistical analysis. The methodology and results of relevant experiments are systematically summarized in a tabular form. In particular, we focus on quantitative data regarding the number of animals, cells, dendritic spines, types of studied parameters, size of observed changes, and their statistical significance.     

A comparative study between PVO-based framework and multi-predictor mechanism in reversible data hiding

Sorting-based reversible data hiding (RDH) methods like pixel-value-ordering (PVO) can predict pixel values accurately and achieve an extremely low distortion on the embedded image. However, the excellent performance of these methods was not well explained in previous works, and there are unexploited common points among them. In this paper, we propose a general multi-predictor (GMP) framework to summarize PVO-based RDH methods and explain their high prediction accuracy. Moreover, by utilizing the proposed GMP framework, a more efficient sorting-based RDH method is given as an example to show the generality and applicability of our framework. Comparing with other PVO-based methods, the proposed example method can achieve significant improvement in embedding performance. It is hopeful that more efficient sorting-based RDH algorithms can be designed according to our proposed framework by designing better predictors and their combination methods.     

The prevalence of asthma and severe asthma in children influenced by transportation factors: Evidence from spatial analysis in Seoul,Korea

Although the causes of asthma are inconclusive, it is fairly known that exposure to outdoor air pollutants can cause asthma, especially children's asthma morbidity. Whereas transportation is one of the major sectors that generate air pollutants, previous research that investigates the correlation between transportation and asthma narrowly focuses on the contribution of automobile traffic to children's asthma. Developing three spatial regression models (a spatial lag (SL) model, a spatial error (SE) model, and a general spatial (SAC) model), this paper investigates the roles of a variety of transportation factors in two distinct stages of children's asthma morbidity; asthma and severe asthma. With consideration to asthma-related socio-economic factors in the City of Seoul, the SE (R² = 0.31) and SAC (R² = 0.34) models consistently indicate that three out of four transportation factors associate with children's severe asthma at statistically significant level. They include the negative influence of bus transit and dense intersections, and the positive influence of active transportation activities on children's asthma severity. Interestingly, however, no significant contribution of transportation factors to children's asthma morbidity was identified by the SE (R² = 0.29) and SAC (R² = 0.28) models. Shedding more light on the complexity of children's asthma morbidity and severity, this paper proposes collaborative partnerships not only among multi- dimensional agencies, but also among multi-level government organizations.     

Evolution of core–rim structures and phase transformations in infra-red transmitting Y-α-SiAlON ceramics

Core–rim structures were observed as common features in Y-α-SiAlON ceramics hot-pressed between 1550?1950 °C. We found most dopants were taken into α’-rims, and a transition layer grown first on α-cores from liquid-phase over-saturated with metal solutes. Elongated β’-grain were formed as minor phase with α’- or AlN-cores thus only after the α’ matrix had consumed up all Y solutes, revealing that the α’ → β’ transformation is controlled by the transient liquid-phase and similar defects and dangling bonds could be detected in both SiAlON phases by cathodoluminescence. Quantitative assessment of Y_m/3Si_12?(m+n)Al_m+nO_nN_16?n demonstrates the multiphase evolution, initiated by over-saturation of Y solutes at low temperatures thus retaining α-phase as cores to lower the infra-red transmittance, dictated by homogenization of Al solutes at higher temperature. The elimination of those phase boundaries leads to better dopant and sintering design for achieving transparent and high-performance SiAlON ceramics.     

A single-phase algorithm for mining high utility itemsets using compressed tree structures

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+ algorithms.