Results of the WMT16 Tuning Shared Task

This paper presents the results of the WMT16 Tuning Shared Task. We provided the participants of this task with a complete machine translation system and asked them to tune its internal parameters (feature weights). The tuned systems were used to translate the test set and the outputs were manually ranked for translation quality. We received 4 submissions in the Czech-English and 8 in the English-Czech translation direction. In addition, we ran 2 baseline setups, tuning the parameters with standard optimizers for BLEU score. In contrast to previous years, the tuned systems in 2016 rely on large data

Physicochemical and thermal properties of lignocellulosic fiber from sugar palm fibers: effect of treatment

Sugar palm fiber (SPF) is one of the prospective fibers used to reinforce polymer composites. The aim of this study is to evaluate the physicochemical, thermal, and morphological properties of SPF after alkali and sea water treatments. The chemical constituents group and thermal stability of the SPF were determined using scanning electronic microscopy (SEM) along with energy dispersive X-ray spectroscopy and thermogravimetric analysis (TGA). Fourier transform infrared spectroscopy was carried out to detect the presence of functional groups in untreated and treated SPF. The SEM images after both treatments showed that the external surface of the fiber became clean as a result. However, the sea water treatment affected the fiber properties physically, while the alkali treatment affected it both physically and chemically by dissolving the hemicellulose in the fiber. The TGA results showed that untreated fiber is significantly more stable than treated fiber. In conclusion, the results show that the fiber surface treatment significantly affected the characterization of the fiber

Influence of treatments on the dielectric properties of sugar palm fiber reinforced phenolic composites

The dielectric properties of sugar palm fiber (SPF) reinforced-phenolic (PF) composites have been studied in terms of bonding between fiber and matrix. The paper aims to investigate the effect of alkaline treatment and sea water treatment on SPF composite using the dielectric relaxation spectroscopy in the frequency range from 0.1 Hz to 0.1 MHz and temperature range from 80 °C to 200 °C. The results were discussed in terms of dynamic molecular and interfacial process. Our analysis suggests that interfacial adhesion in the case of alkaline treated composite is higher than those of untreated and sea water treated composites

Influence of treatments on the mechanical and thermal properties of sugar palm fibre reinforced phenolic composites

Sugar palm fibre (SPF) was used to prepare composites with phenolic resin. The SPF underwent treatment with either sea water for 30 d or a 0.5% alkaline solution for 4 h. The composites contained 30% (vol.) SPF in a powdered form, and the composite samples were fabricated by a hot press machine. The effects of the fibre treatments on the mechanical (flexural, impact, and compressive), thermal, and morphological properties of the composites were analyzed. The SPF treatments considerably improved the mechanical properties of the composites compared with the untreated composite. The alkaline treatment resulted in the most improved flexural and impact strength of the composites. In contrast, the sea water treatment had the best results for improving the compressive strength. Morphological analyses indicated that the surface treatments improved the fibre-matrix bonding. The thermal degradation analysis showed that both the sea water and alkaline treatments of the SPF slightly affected the thermal stability of the composites. Consequently, SPF can be effectively used as an alternative natural fibre for reinforcing bio-composites

Dynamic mechanical analysis of treated and untreated sugar palm fibre based phenolic composites

Phenolic-based sugar palm fibres (SPFs) were used as a filler for composites that were fabricated by hot pressing. The composites were prepared using various volume loadings of SPFs. Dynamic mechanical analysis (DMA) was carried out to evaluate the storage modulus (Eʹ), loss modulus (Eʺ), and tan delta as a function of temperature. The SPFs were treated by seawater for 30 days and a 0.5 alkaline solution for 4 days. The phenolic composites with 30% volume loading of SPFs were used to determine the effect of treatments on the DMA properties of the composites. The obtained results indicate that incorporating a SPF filler notably increased the Eʹ and Eʺ properties and decreased the damping factor of the phenolic composites. Both treatments affected the DMA results. However, the alkaline-treated composites showed higher DMA properties compared with the seawater-treated and untreated fibre composites

Effect of treatments on the physical and morphological properties of SPF/phenolic composites

This study aims at evaluating the physical properties and effects of fiber treatments of natural fiber reinforced polymer composite’s friction applications. Sugar palm fibers (SPFs) were used as fillers (≤ 150 µm) with phenolic resin to fabricate the composites by the hot press technique. The loading of SPFs varied from 0 to 40 vol.% with an interval of 10 vol.% in phenolic composites. The fibers were treated with sea water for 30 days, and with 0.5 M of alkaline solution for 4 hrs. Rockwell hardness, density, voids content, water/oil absorption, and moisture content were studied. Scanning electron microscopy (SEM) was used to investigate the morphology and interfacial bonding of the fiber-matrix in composites. With an increase in the SPF loading in the composites, the results indicated a decline in Rockwell hardness, an increase in water/oil absorption, and density. It was also observed that higher the density of the composites, lower was the voids content. In terms of physical properties, sea water treatment showed better improvement than alkaline treatment. The outcome of this research indicated that SPFs can be effectively used in reinforcing polymer composites, such as friction composites

Effective Image Segmentation using Composite Energy Metric in Levelset Based Curve Evolution

Accurate segmentation of anatomical organs in medical images is a complex task due to wide interpatient variability and several acquisition dependent artefacts. Moreover, image noise, low contrast and intensity inhomogeneity in medical data further amplifies the challeng. In this work, we propose an effective yet simple algorithm based on composite energy metric for precise detection of object boundaries. A number of methods have been proposed in literature for image segmentation; however, these methods employ individual characteristics of image including gradient, regional intensity or texture map. Segmentation based on individual featres often fail for complex images, especially for medical imagery. Accordingly, we propose that the segmentation quality can be improved by integrating local and global image features in the curve evolution. This work employs the classic snake model aka active contour model; however, the curve evolution force has been updated. In contast to the conventional image-based regional intensity statistics, the proposed snake model evolves using composite image energy. Hence, the proposed method offers a greater resistance to the local optima problem as well as initialization perturbations. Experimental results for both synthetic and 2D (Two Dimensional) real clinal images are presented in this work to validate the performance of the proposed method. The performance of the proposed model is evaluated with respect to expert-based manual ground truth. Accordingly, the proposed model achieves higher accuracy in comparison to the state-of-the-art region based segmentation methods of Lankton and Yin as reported in results section

The mechanical performance of sugar palm fibres (Ijuk) reinforced phenolic composites

Sugar palm fibres are one of the natural fibres which have many features and need further study to understand their properties. The aim of this work is to investigate the flexural, compressive and impact properties of sugar palm fibres reinforced phenolic composites. Sugar palm fibres were used as a filler (particle size 150 μm) and with loading of 0, 10, 20, 30, and 40 vol.%. The fibres were treated by sea water and then fabricated into composites by hot press technique. Flexural, compressive, and impact tests were carried out as per ASTM D790, ASTM D695-08a, and ASTM D256 standards, respectively. Scanning electron microscopy (SEM) was used to investigate the morphology and the interfacial bonding of the fibres-matrix in composites. The results show that the mechanical properties of the composites improve with the incorporation of fibres. The composite of 30 vol.% particle loading exhibit optimum values which are 32.23 MPa, 61.66 MPa, and 4.12 kJ/m2 for flexural, compressive, and impact strength, respectively. This was because good compatibility of fibre-matrix bonding. Consequently, sugar palm fibre is one of the prospective fibres and could be used as a potential resource to reinforcement polymer composite

Statistical Machine Translation between Languages with Significant Word Order Differences

One of the difficulties statistical machine translation (SMT) systems face are differences in word order. When translating from a language with rather fixed SVO word order, such as English, to a language where the preferred word order is dramatically different (such as the SOV order of Urdu, Hindi, Korean, ...), the system has to learn long-distance reordering of the words. Higher degree of freedom of the word order of the target language is usually accompanied by higher morphological diversity, i.e. word affixes have to be generated based on the fixed word order in the source sentence. The goal of the thesis is to explore the two mentioned (and possibly other related) classes of problems in practice, and to implement and evaluate techniques expected to help the SMT system to solve them. This includes: 1. Selecting a language pair with word order differences and collecting parallel data for the pair. 2. Training an existing SMT system on the data. 3. Evaluating the performance of the system and analyzing the errors it does. Estimating how much the accuracy of translation is affected by the problems mentioned above, and possibly what are the other types of error causes that dominate the output. 4. Implementing preprocessing and/or other techniques aimed at minimizing the found classes of errors. Evaluating..

Statistical Machine Translation between Languages with Significant Word Order Differences

One of the difficulties statistical machine translation (SMT) systems face are differences in word order. When translating from a language with rather fixed SVO word order, such as English, to a language where the preferred word order is dramatically different (such as the SOV order of Urdu, Hindi, Korean, ...), the system has to learn long-distance reordering of the words. Higher degree of freedom of the word order of the target language is usually accompanied by higher morphological diversity, i.e. word affixes have to be generated based on the fixed word order in the source sentence. The goal of the thesis is to explore the two mentioned (and possibly other related) classes of problems in practice, and to implement and evaluate techniques expected to help the SMT system to solve them. This includes: 1. Selecting a language pair with word order differences and collecting parallel data for the pair. 2. Training an existing SMT system on the data. 3. Evaluating the performance of the system and analyzing the errors it does. Estimating how much the accuracy of translation is affected by the problems mentioned above, and possibly what are the other types of error causes that dominate the output. 4. Implementing preprocessing and/or other techniques aimed at minimizing the found classes of errors. Evaluating..