Back to the future: A fully automatic method for robust age progression

It has been shown that significant age difference between a probe and gallery face image can decrease the matching accuracy. If the face images can be normalized in age, there can be a huge impact on the face verification accuracy and thus many novel applications such as matching driver's license, passport and visa images with the real person's images can be effectively implemented. Face progression can address this issue by generating a face image for a specific age. Many researchers have attempted to address this problem focusing on predicting older faces from a younger face. In this paper, we propose a novel method for robust and automatic face progression in totally unconstrained conditions. Our method takes into account that faces belonging to the same age-groups share age patterns such as wrinkles while faces across different age-groups share some common patterns such as expressions and skin colors. Given training images of K different age-groups the proposed method learns to recover K low-rank age and one low-rank common components. These extracted components from the learning phase are used to progress an input face to younger as well as older ages in bidirectional fashion. Using standard datasets, we demonstrate that the proposed progression method outperforms state-of-the-art age progression methods and also improves matching accuracy in a face verification protocol that includes age progression

Ideologies inside textbooks: Vietnamization and re-khmerization of political education in Cambodia during the 1980s

This chapter analyzes school textbooks in Cambodia during the 1980s when the People’s Republic of Kampuchea (PRK) was in power. Our paper focuses on the portrayal inside textbooks of Democratic Kampuchea (DK), which was the regime that preceded the PRK and is commonly known as the Khmer Rouge. Education during this period attempted to unify survivors of the auto/genocide that occurred during the DK period (1975–1979) and was used as a political tool to create favorable public sentiment for the ruling power in the capital, Phnom Penh (Okada, 1998)

USED PATTERN OF METALS AND MINERALS IN ASHTANG HRIDAYA: THE BIRDS EYE VIEW

Human evolution and progress has count mainly on the discovery of metals. Primitive man used metals first time for making apparatuses and weaponries; as the information advances metals played a significant role in development of agriculture, transport arts, crafts and health care. Ayurveda have faith in the principle of YatPinde Tat Bramhande and therefore all these naturally occurring metals and minerals have major role in restoration of human health and treatment of any kind of illness. Classical treatise Ashtanga Hridaya is a very popular book among the physicians among south India. In this classic, eight types of Dhatu (metals), varieties of Ratna-Uparatna (precious stones and minerals) are mentioned for different purposes. Here an attempt is made to collect all these information of metals and minerals in a collective form to analyse their used pattern in therapeutic, Diagnostic (Nidana Panchaka), Pharmaceutical Benefits, Dincharya/ Pathya- Apathya, Panchakarma and Surgical/Para Surgical Procedure. All these metals and minerals are used in different formulations like Sneha (Oil &Ghee), Sandhana (Fermentation), Churna (powder), Vati (tablet), Lepa (Caoting powder) & Anjana (Collyrium). Human body is composed of almost every natural element found in nature and our civilization is completely reliant on metals and the science of metallurgy is now one of the most widely documented and researched material science

Web Usage Mining: A Survey on Pattern Extraction from Web Logs

As the size of web increases along with number of users, it is very much essential for the website owners to better understand their customers so that they can provide better service, and also enhance the quality of the website. To achieve this they depend on the web access log files. The web access log files can be mined to extract interesting pattern so that the user behaviour can be understood. This paper presents an overview of web usage mining and also provides a survey of the pattern extraction algorithms used for web usage mining

The Erythrocyte Sedimentation Rate is a Simple, Sensitive and Predictive Hematological Index for Non-Septic Diabetic Foot Syndrome: A Cross-Sectional Study

Objective: Several studies have found that the hematological index can be considered as a prognostic biomarker of diabetes mellitus. This study aimed to compare the level of the erythrocyte sedimentation rate (ESR) with other hematological indices as a predictive marker of non-infected diabetic foot syndrome (DFS). Materials and methods: A total of 137 patients with diabetes (53 males and 84 females) and another 30 healthy subjects (10 males and 20 females) were included in this study. The participants were grouped into Group I (healthy subjects, n = 30); Group II (n = 72, type 2 diabetes without clinical evidence of DFS features); and Group III (n = 65, type 2 diabetes with clinical evidence of DFS features (grade 0–2). Hematological indices were determined by a hematology autoanalyzer. Results: The serum fasting glucose levels were significantly higher among Group III patients compared with Groups I and II. The value of ESR was significantly higher among Group III patients compared with Group II. The ESR and red distribution width (RDW) values increased in tandem with the DFS upgrade. The area under the curve (AUC) of the ESR at a cutoff value of 18 mm/hour was 0.663 with 95% confidence intervals of 0.571–0.755, which was significantly (p < 0.001) higher than the AUC of RDW, platelet distribution width, mean platelet volume, and plateletcrit. Also, the area under the curve of the ESR increased as the upgrading of DFS increased. Conclusions: We conclude that determination of ESR serves as a predictor and discriminator of DFS and its upgrading.

Novel clustering schemes for full and compact polarimetric SAR data: An application for rice phenology characterization

Information on rice phenological stages from Synthetic Aperture Radar (SAR) images is of prime interest for in-season monitoring. Often, prior in-situ measurements of phenology are not available. In such situations, unsupervised clustering of SAR images might help in discriminating phenological stages of a crop throughout its growing period. Among the existing unsupervised clustering techniques using full-polarimetric (FP) SAR images, the eigenvalue-eigenvector based roll-invariant scattering-type parameter, and the scattering entropy parameter are widely used in the literature. In this study, we utilize a unique target scattering-type parameter, which jointly uses the Barakat degree of polarization and the elements of the polarimetric coherency matrix. Likewise, we also utilize an equivalent parameter proposed for compact-polarimetric (CP) SAR data. These scattering-type parameters are analogous to the Cloude-Pottier’s parameter for FP SAR data and the ellipticity parameter for CP SAR data. Besides this, we also introduce new clustering schemes for both FP and CP SAR data for segmenting diverse scattering mechanisms across the phenological stages of rice. In this study, we use the RADARSAT-2 FP and simulated CP SAR data acquired over the Indian test site of Vijayawada under the Joint Experiment for Crop Assessment and Monitoring (JECAM) initiative. The temporal analysis of the scattering-type parameters and the new clustering schemes help us to investigate detailed scattering characteristics from rice across its phenological stages.This work was supported in part by the Spanish Ministry of Science, Innovation and Universities, the State Agency of Research (AEI), and the European Funds for Regional Development (EFRD) under Project TEC 2017-85244-C 2-1-P. The work of Dipankar Mandal was supported by the Ministry of Human Resource Development, Government of India (New Delhi, India) towards his Ph.D. assistantship through grant no. RSPHD0210

Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

Sentinel-1 Synthetic Aperture Radar (SAR) data have provided an unprecedented opportunity for crop monitoring due to its high revisit frequency and wide spatial coverage. The dual-pol (VV-VH) Sentinel-1 SAR data are being utilized for the European Common Agricultural Policy (CAP) as well as for other national projects, which are providing Sentinel derived information to support crop monitoring networks. Among the Earth observation products identified for agriculture monitoring, indicators of vegetation status are deemed critical by end-user communities. In literature, several experiments usually utilize the backscatter intensities to characterize crops. In this study, we have jointly utilized the scattering information in terms of the degree of polarization and the eigenvalue spectrum to derive a new vegetation index from dual-pol (DpRVI) SAR data. We assess the utility of this index as an indicator of plant growth dynamics for canola, soybean, and wheat, over a test site in Canada. A temporal analysis of DpRVI with crop biophysical variables (viz., Plant Area Index (PAI), Vegetation Water Content (VWC), and dry biomass (DB)) at different phenological stages confirms its trend with plant growth dynamics. For each crop type, the DpRVI is compared with the cross and co-pol ratio (σVH0/σVV0) and dual-pol Radar Vegetation Index (RVI = 4σVH0/(σVV0 + σVH0)), Polarimetric Radar Vegetation Index (PRVI), and the Dual Polarization SAR Vegetation Index (DPSVI). Statistical analysis with biophysical variables shows that the DpRVI outperformed the other four vegetation indices, yielding significant correlations for all three crops. Correlations between DpRVI and biophysical variables are highest for canola, with coefficients of determination (R2) of 0.79 (PAI), 0.82 (VWC), and 0.75 (DB). DpRVI had a moderate correlation (R2≳ 0.6) with the biophysical parameters of wheat and soybean. Good retrieval accuracies of crop biophysical parameters are also observed for all three crops.This work was supported by the Spanish Ministry of Science, Innovation and Universities, the State Agency of Research (AEI) and the European Funds for Regional Development (EFRD) under Project TEC2017-85244-C2-1-P