A multi-criteria context-sensitive approach for social image collection summarization

Recent increase in the number of digital photos in the content sharing and social networking websites has created an endless demand for techniques to analyze, navigate, and summarize these images. In this paper, we focus on image collection summarization. Earlier methods in image collection summarization consider representativeness and diversity criteria while recent ones also consider other criteria such as image quality, aesthetic or appeal. In this paper, we propose a multi-criteria context-sensitive approach for social image collection summarization. In the proposed method, two different sets of features are combined while each one looks at different criteria for image collection summarization: social attractiveness features and semantic features. The first feature set considers different aspects that make an image appealing such as image quality, aesthetic, and emotion to create attractiveness score for input images while the second one covers semantic content of images and assigns semantic score to them. We use social network infrastructure to identify attractiveness features and domain ontology for extracting ontology features. The final summarization is provided by integrating the attractiveness and semantic features of input images. The experimental results on a collection of human generated summaries on a set of Flickr images demonstrate the effectiveness of the proposed image collection summarization approach.     

Efficient PL Emission from p-type Porous Silicon: A Comparative Study for Selection of Effective Anodization Parameters

The physical mechanism of highly efficient photoluminescence (PL) emission from p-type silicon is described by a comparative study of the effectiveness of the etching parameters in an electrochemical anodization technique. Two series of porous silicon samples were prepared in a combination of anodization current and time, to maintain the total amount of anodic charge transfer constant. Photoluminescence studies show that irrespective of the amount of charge transfer, the samples prepared with comparatively higher current density show an efficient PL as well as stronger blueshift in the emission energy vis-à-vis the samples prepared for longer durations. An overall decrease in crystallite size, as estimated by Raman spectral analysis, was observed for both series of samples with the progress of charge transfer. Comparative analysis shows a marginal difference in crystallite size for both series of samples in the initial state of charge transfer, whereas major differences arise at higher values. This is explained with the formation of silicon suboxide on the porous surface at higher current density, leading to initiation of side wall reaction, and higher reduction rate in crystallite size as well as strong luminescence due to the carrier quantum confinement effect.     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.     

Matrix Transformation in Boron Containing High-Temperature Co–Re–Cr Alloys

An addition of boron largely increases the ductility in polycrystalline high-temperature Co–Re alloys. Therefore, the effect of boron on the alloy structural characteristics is of high importance for the stability of the matrix at operational temperatures. Volume fractions of ε (hexagonal close-packed—hcp), γ (face-centered cubic—fcc) and σ (Cr₂Re₃ type) phases were measured at ambient and high temperatures (up to 1500 °C) for a boron-containing Co–17Re–23Cr alloy using neutron diffraction. The matrix phase undergoes an allotropic transformation from ε to γ structure at high temperatures, similar to pure cobalt and to the previously investigated, more complex Co–17Re–23Cr–1.2Ta–2.6C alloy. It was determined in this study that the transformation temperature depends on the boron content (0–1000 wt. ppm). Nevertheless, the transformation temperature did not change monotonically with the increase in the boron content but reached a minimum at approximately 200 ppm of boron. A probable reason is the interplay between the amount of boron in the matrix and the amount of σ phase, which binds hcp-stabilizing elements (Cr and Re). Moreover, borides were identified in alloys with high boron content.     

Imaging of two-dimensional unsaturated moisture flows in uncracked and cracked cement-based materials using electrical capacitance tomography

The development of visualizing tools to monitor unsaturated moisture flow in cement-based materials is of great importance, as most degradation processes in cement-based materials are connected to and take place in the presence moisture. This paper investigates the ability of electrical capacitance tomography (ECT) to image two-dimensional (2D) unsaturated moisture flow in cement-based materials. In ECT, the electrical permittivity distribution within an object is reconstructed based on measured capacitances between electrodes attached on the object’s surface. In a series of experiments, mortar specimens with and without discrete cracks were imaged with ECT during a 2D moisture ingress. The results show that ECT is able to monitor the evolution of the moisture flow, and to approximate the shape and position of the moisture front. These findings indicate that ECT is a viable method for monitoring and visualizing 2D unsaturated moisture flow in cement-based materials in the presence and absence of discrete cracks.     

Appraisal of Agriglass in Promoting Maize Production Under Abiotic Stress Conditions

An agriglass composition containing different oxides acts as a slow release for macro and micro nutrients and was chosen to improve maize yield under most important abiotic stresses which affecting agriculture development; salinity and drought. A field experiment was performed in salt affected soil (EC =?7.5 dSm^??1) by using different water deficit rates (I1 = 100, I2 = 85 and I3 = 70% of maize water requirements). Irrigation levels were located in main plots. Every main-plot divided into six sub-plots contained glassy fertilizer treatments [F1 = 55 kg fed^?1 with 1/2 mm diameter of agriglass (fed. =?4200 m²), F2 = 55 kg fed^?1 with 1 mm diameter, F3 = 80 kg fed^?1 with 1/2 mm diameter, F4 = 80 kg fed^?1 with 1 mm diameter, F5 = Recommendations of Ministry of Agriculture and F6 = control]. The experimental results demonstrated that, ears, straw, grains and biological yields increased with increasing both water and agriglass rates. Application of agriglass as a slow release fertilizer improved yield more than mineral fertilizer. Some growth parameters, water use efficiency (IWUE), macronutrients concentration and their relations were included. Other studies on residual effect of agriglass and the annual application rates to withstand salinity and drought stress by strategic crops are required.