Robust global motion estimation oriented to video object segmentation.

Most global motion estimation (GME) methods are oriented to video coding while video object segmentation methods either assume no global motion (GM) or directly adopt a coding-oriented method to compensate for GM. This paper proposes a hierarchical differential GME method oriented to video object segmentation. A scheme which combines three-step search and motion parameters prediction is proposed for initial estimation to increase efficiency. A robust estimator that uses object information to reject outliers introduced by local motion is also proposed. For the first frame, when the object information is unavailable, a robust estimator is proposed which rejects outliers by examining their distribution in local neighborhoods of the error between the current and the motion-compensated previous frame. Subjective and objective results show that the proposed method is more robust, more oriented to video object segmentation, and faster than the referenced methods.     

Three‐dimensional computational comparison of mini pinned heat sinks using different nanofluids: Part one—the hydraulic‐thermal characteristics

The hydraulic‐thermal characteristics of 3D pinned heat sink designs have been numerically compared as the first part of a three‐part investigation. Five different pin geometries (circular, square, triangular, strip, and elliptic pins) and an unpinned heat sink with three types of nanofluids (Al₂O₃–H₂O, SiO₂–H₂O, and CuO–H₂O) are considered for laminar forced convection. The range of Reynolds number is from 100 to 1000, and volume fractions vary between 0% and 5%. The finite volume method is employed to solve the Navier–Stokes and energy equations by employing a SIMPLE algorithm for a computational solution. Three parameters are presented—the Nusselt number, the bottom temperature, and the hydrothermal performance of the heat sink with pressure drop data. The findings indicated that the overall hydrothermal performance of elliptic‐pinned (EP) heat sinks produces the most substantial value of 3.10 for pure water. For different nanofluids, the SiO₂–water nanofluids with EPs have the most significant hydrothermal performance. Also, this factor is enhanced with an increase in nanofluid concentration up to nearly 3.34 for 5% of SiO₂–water. Consequently, applying the elliptic‐pinned heat sinks is recommended with pure water for considering an increase in the pressure drop, with 5% of SiO₂–water nanofluids, regardless of an enlargement of pressure drop for heat‐dissipation applications.     

Simultaneously achievement of high recoverable energy density and efficiency in sodium niobate-based ceramics

Journal of Materials Science: Materials in Electronics - Single lead-free Na0.73Bi0.09(Nb1???xTax)O3 (x?=?0, 0.10, 0.20, 0.30, and 0.40) ceramic phases were processed...     

Use of solution crystallization analysis by laser light scattering for studying the solution crystallization of various Ziegler–Natta‐catalysed polypropylenes

Solution crystallization analysis by laser light scattering (SCALLS) involves the observation of the scattering of diode mercury laser lamp light after it passes through a polymer solution. An increase in turbidity occurs when the hot polymer solution is cooled and the polymer starts to crystallize out of solution. This causes a decrease in the amount of laser light that can pass through the solution and an increase in the amount of scattered light. The reverse of this process leads to the turbidity decreasing with an increase in temperature. According to this concept, it is possible to follow the solution crystallization of various polypropylenes under controlled cooling. In this study, SCALLS was able to differentiate between different isotactic and syndiotactic polypropylenes with similar chemical structures, but different tacticity and molecular weights. Furthermore, SCALLS provided good crystallization information that is similar to that from crystallization analysis fractionation and temperature rising elution fractionation. In addition, SCALLS can be used as a quantitative tool for the measurement of weight fractions during dissolution. © 2014 Society of Chemical Industry     

Heifers with positive genetic merit for fertility traits reach puberty earlier and have a greater pregnancy rate than heifers with negative genetic merit for fertility traits

This study investigated the hypothesis that dairy heifers divergent in genetic merit for fertility traits differ in the age of puberty and reproductive performance. New Zealand's fertility breeding value (FertBV) is the proportion of a sire's daughters expected to calve in the first 42 d of the seasonal calving period. We used the New Zealand national dairy database to identify and select Holstein-Friesian dams with either positive (POS, +5 FertBV, n = 1,334) or negative FertBV (NEG, ?5% FertBV, n = 1,662) for insemination with semen from POS or NEG FertBV sires, respectively. The resulting POS and NEG heifers were predicted to have a difference in average FertBV of 10 percentage points. We enrolled 640 heifer calves (POS, n = 324; NEG, n = 316) at 9 d ± 5.4 d (± standard deviation; SD) for the POS calves and 8 d ± 4.4 d old for the NEG calves. Of these, 275 POS and 248 NEG heifers were DNA parent verified and retained for further study. The average FertBV was +5.0% (SD = 0.74) and ?5.1% (SD = 1.36) for POS and NEG groups, respectively. Heifers were reared at 2 successive facilities as follows: (1) calf rearing (enrollment to ～13 wk of age) and (2) grazier, after 13 wk until 22 mo of age. All heifers wore a collar with an activity sensor to monitor estrus events starting at 8 mo of age, and we collected weekly blood samples when individual heifers reached 190 kg of body weight (BW) to measure plasma progesterone concentrations. Puberty was characterized by plasma progesterone concentrations >1 ng/mL in at least 2 of 3 successive weeks. Date of puberty was defined when the first of these samples was >1 ng/mL. Heifers were seasonally bred for 98 d starting at ～14 mo of age. Transrectal ultrasound was used to confirm pregnancy and combined with activity data to estimate breeding and pregnancy dates. We measured BW every 2 wk, and body condition and stature at 6, 9, 12, and 15 mo of age. The significant FertBV by day interaction for BW was such that the NEG heifers had increasingly greater BW with age. This difference was mirrored with the significant FertBV by month interaction for average daily gain, with the NEG heifers having a greater average daily gain between 9 and 18 mo of age. There was no difference in heifer stature between the POS and NEG heifers. The POS heifers were younger and lighter at puberty, and were at a lesser mature BW, compared with the NEG heifers. As a result, 94 ± 1.6% of the POS and 82 ± 3.2% of the NEG heifers had reached puberty at the start of breeding. The POS heifers were 20% and 11% more likely to be pregnant after 21 d and 42 d of breeding than NEG heifers (relative risk = 1.20, 95% confidence interval of 1.03–1.34; relative risk = 1.11, 95% confidence interval of 1.01–1.16). Results from this experiment support an association between extremes in genetic merit for fertility base on cow traits and heifer reproduction. Our results indicate that heifer puberty and pregnancy rates are affected by genetic merit for fertility traits, and these may be useful phenotypes for genetic selection.     

The Robust Regression Methods for Estimating of Finite Population Mean Based on SRSWOR in Case of Outliers

The ordinary least square (OLS) method is commonly used in regression analysis. But in the presence of outlier in the data, its results are unreliable. Hence, the robust regression methods have been suggested for a long time as alternatives to the OLS to solve the outliers problem. In the present study, new ratio type estimators of finite population mean are suggested using simple random sampling without replacement (SRSWOR) utilizing the supplementary information in Bowley’s coefficient of skewness with quartiles. For these proposed estimators, we have used the OLS, Huber-M, Mallows GM-estimate, Schweppe GM-estimate, and SIS GM-estimate methods for estimating the population parameters. Theoretically, the mean square error (MSE) equations of various estimators are obtained and compared with the OLS competitor. Simulations for skewed distributions as the Gamma distribution support the results, and an application of real data set containing outliers is considered for illustration.     

Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution

In this paper, we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans (ASPs) where the life test is assumed to be truncated at a pre-assigned time. For the new suggested ASPs, the tables of the minimum samples sizes needed to assert a specific mean life of the test units are obtained. In addition, the values of the corresponding operating characteristic function and the associated producer’s risks are calculated. Analyses of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans; one data set contains the first failure of 20 small electric carts, and the other data set contains the failure times of the air conditioning system of an airplane. Comparisons are made between the proposed acceptance sampling plans and some existing acceptance sampling plans considered in this study based on the minimum sample sizes. It is observed that the samples sizes based on the proposed acceptance sampling plans are less than their competitors considered in this study. The suggested acceptance sampling plans are recommended for practitioners in the field.     

Deep Multimodal Fusion: A Hybrid Approach

We propose a novel hybrid model that exploits the strength of discriminative classifiers along with the representation power of generative models. Our focus is on detecting multimodal events in time varying sequences as well as generating missing data in any of the modalities. Discriminative classifiers have been shown to achieve higher performances than the corresponding generative likelihood-based classifiers. On the other hand, generative models learn a rich informative space which allows for data generation and joint feature representation that discriminative models lack. We propose a new model that jointly optimizes the representation space using a hybrid energy function. We employ a Restricted Boltzmann Machines (RBMs) based model to learn a shared representation across multiple modalities with time varying data. The Conditional RBMs (CRBMs) is an extension of the RBM model that takes into account short term temporal phenomena. The hybrid model involves augmenting CRBMs with a discriminative component for classification. For these purposes we propose a novel Multimodal Discriminative CRBMs (MMDCRBMs) model. First, we train the MMDCRBMs model using labeled data by training each modality, followed by training a fusion layer. Second, we exploit the generative capability of MMDCRBMs to activate the trained model so as to generate the lower-level data corresponding to the specific label that closely matches the actual input data. We evaluate our approach on ChaLearn dataset, audio-mocap, as well as the Tower Game dataset, mocap-mocap as well as three multimodal toy datasets. We report classification accuracy, generation accuracy, and localization accuracy and demonstrate its superiority compared to the state-of-the-art methods.     

Improving PAPR performance of filtered OFDM for 5G communications using PTS

The filtered orthogonal frequency division multiplexing (F-OFDM) system has been recommended as a waveform candidate for fifth-generation (5G) communications. The suppression of out-of-band emission (OOBE) and asynchronous transmission are the distinctive features of the filtering-based waveform frameworks. Meanwhile, the high peak-to-average power ratio (PAPR) is still a challenge for the new waveform candidates. Partial transmit sequence (PTS) is an effective technique for mitigating the trend of high PAPR in multicarrier systems. In this study, the PTS technique is employed to reduce the high PAPR value of an F-OFDM system. Then, this system is compared with the OFDM system. In addition, the other related parameters such as frequency localization, bit error rate (BER), and computational complexity are evaluated and analyzed for both systems with and without PTS. The simulation results indicate that the F-OFDM based on PTS achieves higher levels of PAPR, BER, and OOBE performances compared with OFDM. Moreover, the BER performance of F-OFDM is uninfluenced by the use of the PTS technique.     

Synthesis of new 5-thiazolyl azo-disperse dyes for dyeing polyester fabrics

Diazotized aryl amines were coupled with 2-aminothiazoles 1 and 2 to give the corresponding thiazolylazo dyes 3 and 4, respectively. 2-Amino-5-arylazothiazoles 5 reacted with chloroacetyl chloride to afford the chloro-acetamide derivatives 6 which further reacted with 2-mercaptobenzothiazole to furnish a new series of 5-arylazothiazolyl dyes 7. The azo structure of the dyes (rather than the tautomeric hydrazo structure) was assessed by ab initio DFT calculations at the B3LYP/6-31G* level. These dyes were applied to polyester fabric as disperse dyes and their fastness properties were evaluated.