A Classifier Model based on the Features Quantitative Analysis for Facial Expression Recognition

In recent decades computer technology has considerable developed in use of intelligent systems for classification. The development of HCI systems is highly depended on accurate understanding of emotions. However, facial expressions are difficult to classify by a mathematical models because of natural quality. In this paper, quantitative analysis is used in order to find the most effective features movements between the selected facial feature points. Therefore, the features are extracted not only based on the psychological studies, but also based on the quantitative methods to arise the accuracy of recognitions. Also in this model, fuzzy logic and genetic algorithm are used to classify facial expressions. Genetic algorithm is an exclusive attribute of proposed model which is used for tuning membership functions and increasing the accuracy

Facial Expression Recognition Using Uniform Local Binary Pattern with Improved Firefly Feature Selection

Facial expressions are essential communication tools in our daily life. In this paper, the uniform local binary pattern is employed to extract features from the face. However, this feature representation is very high in dimensionality. The high dimensionality would not only affect the recognition accuracy but also can impose computational constraints. Hence, to reduce the dimensionality of the feature vector, the firefly algorithm is used to select the optimal subset that leads to better classification accuracy. However, the standard firefly algorithm suffers from the risk of being trapped in local optima after a certain number of generations. Hence, this limitation has been addressed by proposing an improved version of the firefly where the great deluge algorithm (GDA) has been integrated. The great deluge is a local search algorithm that helps to enhance the exploitation ability of the firefly algorithm, thus preventing being trapped in local optima. The improved firefly algorithm has been employed in a facial expression system. Experimental results using the Japanese female facial expression database show that the proposed approach yielded good classification accuracy compared to state-of-the-art methods. The best classification accuracy obtained by the proposed method is 96.7% with 1230 selected features, whereas, Gabor-SRC method achieved 97.6% with 2560 features

Face Verification without False Acceptance

Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA) are two popular approaches in face recognition and verification. The methods are classified under appearance-based approach and are considered to be highly-correlated. The last factor deems a fusion of both methods to be unfavorable. Nevertheless the authors will demonstrate a verification performance in which the fusion of both method produces an improved rate compared to individual performance. Tests are carried out on FERET (Facial Recognition Technology) database using a modified protocol. A major drawback in applying LDA is that it requires a large set of individual face images sample to extract the intra-class variations. In real life application data enrolment incurs costs such as human time and hardware setup. Tests are therefore conducted using virtual images and its performance and behaviour recorded as an option for multiple sample. The FERET database is chosen because it is widely used by researchers and published results are available for comparisons. Performance is presented as the rate of verification when false acceptance rate is zero, in other words, no impostors allowed. Initial results using fusion of two verification experts shows that a fusion of T-Zone LDA with Gabor LDA of whole face produces the best verification rate of 98.2% which is over 2% improvement compared with the best individual expert

Apolipoprotein B100 autoimmunity and atherosclerosis - disease mechanisms and therapeutic potential.

PURPOSE OF REVIEW: Adaptive immune responses have been shown to play an important role in the atherosclerotic disease process and both pathogenic and protective immunity has been identified. Apolipoprotein (apo) B100 appears to be a key antigen and novel therapies modulating immune responses against apo B100 have shown promising results in experimental models. This review will discuss recent developments in the mechanistic understanding of apo B100 autoimmunity and approaches taken to use this knowledge for development of novel therapies. RECENT FINDINGS: It has recently been shown that not only apo B100 modified by oxidation but also nonmodified apo B100 is targeted by autoimmune responses. This implies that a corresponding set of regulatory T cells with the same antigen specificity must exist and that these cells under normal circumstances are able to prevent autoimmunity against LDL. Recent studies also suggest that the atheroprotective effect of apo B100 peptide immunization acts by re-enforcing the activity of such cells. SUMMARY: These novel findings suggest that aggravation of plaque inflammation may occur as a result of a local loss of tolerance against LDL in the plaque due to insufficient activity of regulatory T cells. Restoration of lost tolerance represents an interesting novel approach for treatment of cardiovascular disease

Emerging biomarkers and intervention targets for immune-modulation of atherosclerosis - A review of the experimental evidence.

The role of inflammation in atherosclerosis and plaque vulnerability is well recognized. However, it is only during recent years it has become evident that this inflammation is modulated by immune responses against plaque antigens such as oxidized LDL. Interestingly, both protective and pathogenic immune responses exist and experimental data from animal studies suggest that modulation of these immune responses represents a promising new target for treatment of cardiovascular disease. It has been proposed that during early stages of the disease, autoimmune responses against plaque antigens are controlled by regulatory T cells that inhibit the activity of auto-reactive Th1 effector T cells by release of anti-inflammatory cytokines such as IL-10 and TGF-β. As the disease progresses this control is gradually lost and immune responses towards plaque antigens switch towards activation of Th1 effector T cells and release of pro-inflammatory cytokines such as interferon-γ, TNF-α and IL-1β. Several novel immune-modulatory therapies that promote or mimic tolerogenic immune responses against plaque antigens have demonstrated athero-protective effects in experimental models and a first generation of such immune-modulatory therapies are now in early or about to enter into clinical testing. A challenge in the clinical development of these therapies is that our knowledge of the role of the immune system in atherosclerosis largely rests on data from animal models of the disease. It is therefore critical that more attention is given to the characterization and evaluation of immune biomarkers for cardiovascular risk

Using mHealth applications for self-care – An integrative review on perceptions among adults with type 1 diabetes

Background Individually designed interventions delivered through mobile health applications (mHealth apps) may be able to effectively support diabetes self-care. Our aim was to review and synthesize available evidence in the literature regarding perception of adults with type 1 diabetes on the features of mHealth apps that help promote diabetes self-care, as well as facilitators and barriers to their use. An additional aim was to review literature on changes in patient reported outcome measures (PROMs) in the same population while using mHealth apps for diabetes self-care. Methods Quantitative and qualitative studies focusing on adults aged 18 years and over with type 1 diabetes in any context were included. A systematic literature search using selected databases was conducted. Data was synthesised using narrative synthesis. Results We found that features of mHealth apps designed to help promote and maintain diabetes self-care could be categorized into self-care data monitoring, app display, feedback & reminders, data entry, data sharing, and additional features. Factors affecting the use of mHealth apps reported in the literature were personal factors, app design or usability factors, privacy and safety factors, or socioeconomic factors. Quality of life and diabetes distress were the most commonly reported PROMs in the included studies. Conclusion We are unable to reach a conclusive result due to the heterogeneity of the included studies as well as the limited number of studies reporting on these areas among adults with type 1 diabetes. We therefore recommend further large-scale studies looking into these areas that can ultimately improve mHealth app use in type 1 diabetes self-care.publishedVersio

Incident and Traffic-Bottleneck Detection Algorithm in High-Resolution Remote Sensing Imagery

One  of  the  most  important  methods  to  solve  traffic  congestion  is  to detect the incident state of a roadway. This paper describes the development of a method  for  road  traffic  monitoring  aimed  at  the  acquisition  and  analysis  of remote  sensing  imagery.  We  propose  a  strategy  for  road  extraction,  vehicle detection  and incident detection  from remote sensing imagery using techniques based on neural networks, Radon transform  for angle detection and traffic-flow measurements.  Traffic-bottleneck  detection  is  another  method  that  is  proposed for recognizing incidents in both offline and real-time mode. Traffic flows and incidents are extracted from aerial images of bottleneck zones. The results show that the proposed approach has a reasonable detection performance compared to other methods. The best performance of the learning system was a detection rate of 87% and a false alarm rate of less than 18% on 45 aerial images of roadways. The performance of the traffic-bottleneck detection  method had a detection rate of 87.5%

Fructooligosaccharides in honey and effects of honey on growth of Bifidobacterium longum BB 536

This research was carried out to determine the fructooligosaccharides content in local honey samples, namely the wild Malaysian Tualang honey and common wild honey obtained from Tapah, Perak and a commercial Tualang honey. Local wild honeys were found to contain a higher concentration of fructooligosaccharides (FOS) compared to the commercial Tualang honey. The FOS quantified from local wild honeys was inulobiose, kestose and nystose. Nystoses were found at a very low amount in the commercial Tualang honey. The effects of honey on the growth of Bifidobacterium longum BB 536 were investigated. Both wild and commercial honey samples including FOS standard were found to support the growth of B. longum. The pH value of the skim milk + honey inoculated with the probiotic strain decreases as expected. Addition of honey was found to support the growth of B. longum BB 536

An image reconstruction algorithm for a dual modality tomographic system.

This thesis describes an investigation into the use of dual modality tomography to measure component concentrations within a cross-section. The benefits and limitations of using dual modality compared with single modality are investigated and discussed. A number of methods are available to provide imaging systems for process tomography applications and seven imaging techniques are reviewed. Two modalities of tomography were chosen for investigation (i.e. Electrical Impedance Tomography (EIT) and optical tomography) and the proposed dual modality system is presented. Image reconstruction algorithms for EIT (based on modified Newton-Raphson method), optical tomography (based on back-projection method) and with both modalities combined together to produce a single tomographic imaging system are described, enabling comparisons to be made between the individual and combined modalities.To analyse the performance of the image reconstruction algorithms used in the EIT, optical tomography and dual modality investigations, a sequence of reconstructions using a series of phantoms is performed on a simulated vessel. Results from two distinct cases are presented, a) simulation of a vertical pipe in which the cross-section is filled with liquid or liquid and objects being imaged and b) simulation of a horizontal pipe where the conveying liquid level may vary from pipe full down to 14% of liquid. A computer simulation of an EIT imaging system based on a 16 electrode sensor array is used. The quantitative images obtained from simulated reconstruction are compared in term of percentage area with the actual cross-section of the model. It is shown from the results that useful reconstructions may be obtained with widely differing levels of liquid, despite the limitations in accuracy of the reconstructions. The test results obtained using the phantoms with optical tomography, based on two projections each of sixteen views, show that the images produced agree closely on a quantitative basis with the physical models. The accuracy of the optical reconstructions, neglecting the effects of aliasing due to only two projections, is much higher than for the EIT reconstructions. Neglecting aliasing, the measured accuracies range from 0.1% to 0.8% for the pipe filled with water. For the sewer condition, i.e. the pipe not filled with water, the major phase is measured with an accuracy of 1% to 3.4%. For the single optical modality the minor components are measured with accuracies 6.6% to 19%. The test results obtained using the phantoms show that the images produced by combining both EIT and optical tomography method agree quantitatively with the physical models. The EIT eliminates most of the aliasing and the results now show that the optical part of the system provides accuracies for the minor components in the range 1% to 5%. It is concluded that the dual modality system shows a measurable increase in accuracy compared with the single modality systems. The dual modality system should be investigated further using laboratory flow rigs in order to check accuracies and determine practical limitations. Finally, suggestions for future work on improving the accuracy, speed and resolution of the dual modality imaging system is presented