Thermal analysis of a ceramic coating diesel engine piston using 3-D finite element method

In this study, firstly, thermal analyses are investigated on a conventional (uncoated) diesel piston, made of aluminum silicon alloy and steel. Secondly, thermal analyses are performed on pistons, coated with MgO-ZrO₂ material by means of using a commercial code, namely ANSYS. Finally, the results of four different pistons are compared with each other. The effects of coatings on the thermal behaviors of the pistons are investigated. It has been shown that the maximum surface temperature of the coated piston with material which has low thermal conductivity is improved approximately 48% for the AlSi alloy and 35% for the steel.     

Fractionation of transgenic corn for recovery of recombinant enzymes

Two germ-separation methods, dry-milling and density separation by flotation, were evaluated for recovering recombinant β-glucuronidase (rGUS) that accumulated primarily in the germ of transgenic corn. The dry-milling process consisted of (i) seed tempering, (ii) degerming with a horizontal-drum degermer/dehuller, (iii) particle size fractionation with standard sieves, (iv) germ and endosperm separation by roller milling and sifting, and (v) removal of hulls by aspiration. Sieves nos. 5, 6, and 7 retained the majority of germ, and subfractions from these sieves were pooled as a germ-rich fraction. Mass balances showed that the germ-rich fraction, which constituted 17% of the total dry-milled corn weight, contained 49% of rGUS activity and 64% of the total recoverable oil. Germ fractionation by flotation was tested as a proof-of-concept method aimed at separating corn fractions based on their difference in specific gravity (sp gr). The process consisted of impact-grinding of corn kernels followed by density separation using 1.15 or 1.3 specific gravity sodium nitrate solution. The oil-containing germ fraction floated, whereas the heavier endosperm fraction sedimented. The flotation method was simpler and resulted in higher enzyme recovery, that is, the germ-rich fraction was 20% (w/w) of the initial corn weight, and accounted for 80% of rGUS activity and 77% of total oil. The sodium nitrate solution did not have an adverse effect on the enzyme activity.     

A Model for Cross-Domain Opinion Target Extraction in Sentiment Analysis

Opinion target extraction is one of the core tasks in sentiment analysis on text data. In recent years, dependency parser–based approaches have been commonly studied for opinion target extraction. However, dependency parsers are limited by language and grammatical constraints. Therefore, in this work, a sequential pattern-based rule mining model, which does not have such constraints, is proposed for cross-domain opinion target extraction from product reviews in unknown domains. Thus, knowing the domain of reviews while extracting opinion targets becomes no longer a requirement. The proposed model also reveals the difference between the concepts of opinion target and aspect, which are commonly confused in the literature. The model consists of two stages. In the first stage, the aspects of reviews are extracted from the target domain using the rules automatically generated from source domains. The aspects are also transferred from the source domains to a target domain. Moreover, aspect pruning is applied to further improve the performance of aspect extraction. In the second stage, the opinion target is extracted among the aspects extracted at the former stage using the rules automatically generated for opinion target extraction. The proposed model was evaluated on several benchmark datasets in different domains and compared against the literature. The experimental results revealed that the opinion targets of the reviews in unknown domains can be extracted with higher accuracy than those of the previous works.     

Noise analysis of robot manipulator using neural networks

Due to a lot of robot manipulators application in industry, low noise degree is very important criteria for robot manipulator's joints. In this paper, joint noise problem of a robot manipulator with five joints is investigated both theoretically and experimentally. The investigation is consisted of two steps. First step is to analyze the noise of joints using a hardware and software. The hardware is a part of noise sensors. The second step; according to experimental results, some neural networks are employed for finding robust neural noise analyzer. Five types of neural networks are used to compare each other. From the results, it is noted that the proposed RBFNN gives the best results for analyzing joint noise of the robot manipulator.     

Approximate periodic solutions for the Helmholtz-Duffing equation

Approximate periodic solutions for the Helmholtz-Duffing oscillator are obtained in this paper. He’s Energy Balance Method (HEBM) and He’s Frequency Amplitude Formulation (HFAF) are adopted as the solution methods. Oscillation natural frequencies are analytically analyzed. Error analysis is carried out and accuracy of the solution methods is evaluated.     

Mobile multi-view object image search

High user interaction capability of mobile devices can help improve the accuracy of mobile visual search systems. At query time, it is possible to capture multiple views of an object from different viewing angles and at different scales with the mobile device camera to obtain richer information about the object compared to a single view and hence return more accurate results. Motivated by this, we propose a new multi-view visual query model on multi-view object image databases for mobile visual search. Multi-view images of objects acquired by the mobile clients are processed and local features are sent to a server, which combines the query image representations with early/late fusion methods and returns the query results. We performed a comprehensive analysis of early and late fusion approaches using various similarity functions, on an existing single view and a new multi-view object image database. The experimental results show that multi-view search provides significantly better retrieval accuracy compared to traditional single view search.     

Developing robust vision modules for microsystems applications

In this work, several robust vision modules are developed and implemented for fully automated micromanipulation. These are autofocusing, object and end-effector detection, real-time tracking and optical system calibration modules. An image based visual servoing architecture and a path planning algorithm are also proposed based on the developed vision modules. Experimental results are provided to assess the performance of the proposed visual servoing approach in positioning and trajectory tracking tasks. Proposed path planning algorithm in conjunction with visual servoing imply successful micromanipulation tasks.     

Dielectric properties of sol-gel derived Ta2O5 thin films

The dielectric constant and the dielectric loss of tantalum pentoxide (Ta₂O₅) thin films, produced by sol-gel spin-coated process on Corning glass substrates, have been investigated in the frequency range of 20-10⁵ Hz and the temperature range of 183-403 K, using ohmic Al electrodes. The frequency and temperature dependence of relaxation time has also been determined. The capacitance and loss factor were found to decrease with increasing frequency and increase with increasing temperature. The activation energy values were evaluated and a good agreement between the activation energy values obtained from capacitance and dielectric loss factor measurements were observed.     

Hypergraph Models and Algorithms for Data-Pattern-Based Clustering

In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations in different contexts. Since such contexts might be captured by interesting patterns in the overall data, we represent each transaction as a set of patterns through modifying the conventional pattern semantics. By clustering the patterns in the dataset, we infer a clustering of the transactions represented this way. For this, we propose a novel hypergraph model to represent the relations among the patterns. Instead of a local measure that depends only on common items among patterns, we propose a global measure that is based on the cooccurences of these patterns in the overall data. The success of existing hypergraph partitioning based algorithms in other domains depends on sparsity of the hypergraph and explicit objective metrics. For this, we propose a two-phase clustering approach for the above hypergraph, which is expected to be dense. In the first phase, the vertices of the hypergraph are merged in a multilevel algorithm to obtain large number of high quality clusters. Here, we propose new quality metrics for merging decisions in hypergraph clustering specifically for this domain. In order to enable the use of existing metrics in the second phase, we introduce a vertex-to-cluster affinity concept to devise a method for constructing a sparse hypergraph based on the obtained clustering. The experiments we have performed show the effectiveness of the proposed framework.     

Investigation of Al-O-Al sites in an Na-aluminosilicate glass

This paper reports the presence of Al- O- Al linkages in an aluminosilicate glass where Si/Al = 1 by using 2D¹⁷O triple quantum MAS NMR technique (3Q MASNMR). The experiments were performed at external magnetic fields of 8.4 and 14.4T. Despite¹⁷OMAS NMR spectra of the sample in both fields do not give much information about the different kinds of linkages in the sample, 3Q MAS NMR spectrum shows clear evidence that there are some amounts of Al-O-Al linkages in the sample giving two completely resolved peaks. These two peaks were attributed to the Si-O-Al and Al-O-Al linkages on the basis of their chemical shifts and, quadrupolar coupling constants which are quite sensitive to the local structure.