Sorption of Mo(VI) on zirconium molybdosilicate gel and potential application as a <Superscript>99</Superscript>Mo/<Superscript>99<Emphasis Type="Italic">m</Emphasis> </Superscript>Tc generator

Sorption of Mo(VI) from aqueous nitrate solutions onto zirconium molybdosilicate (ZrMoSi) gel was studied using ⁹⁹Mo radiotracer. The acid–base titration curve showed that the prepared ZrMoSi gel was an amphoteric material with the point of zero charge (PZC) at pH 2.5. The highest distribution coefficient (600 mL g^–1) of ⁹⁹Mo(VI) on ZrMoSi from nitrate media was achieved at pH 2.1. The sorption kinetics of ⁹⁹Mo(VI) onto ZrMoSi obeyed the pseudo-second-order model. The breakthrough sorption capacity of ZrMoSi gel was found to be 4.25 × 10^–2 [mmol Mo(VI)] g^–1. The prepared ⁹⁹Mo/^99mTc chromatographic column generator showed a good performance: The ^99mTc elution yield was 87.7%, pH of the eluate ranged from 5.6 to 7.2, and the radionuclidic purity of the eluted ^99mTc was >99.99% with a radiochemical purity of 98.31% (as ^99mTcO₄^–).     

Experimental and numerical results of dynamics behavior of a nonlinear piezoelectric beam

This article presents a numerical formulation and experimental implementation for the dynamics behavior verification of the nonlinear piezoelectric beam through harmonic excitation. The nonlinear piezoelectric beam dynamic analysis program is developed with MATLAB software. To verify the nonlinear piezoelectric beam dynamic analysis results, the experimental results are used for the vibration analysis of a piezoelectric beam to the harmonic excitation of the base of the beam. Then, the piezoelectric effect on the output voltage, velocity, acceleration values, and the time response are obtained. Afterwards, the effects of the excitation velocity and the position of concentrated mass on the output voltage are verified.     

SENTIMENT ASSESSMENT OF TEXT BY ANALYZING LINGUISTIC FEATURES AND CONTEXTUAL VALENCE ASSIGNMENT

Text is not only an important medium to describe facts and events, but also to effectively communicate information about the writer's positive or negative sentiment underlying an opinion, or to express an affective or emotional state, such as happiness, fearfulness, surpriseness, and so on. We consider sentiment assessment and emotion sensing from text as two different problems, whereby sentiment assessment is the task that we want to solve first. Thus, this article presents an approach to sentiment assessment, i.e., the recognition of negative or positive valence of a sentence. For the purpose of sentiment recognition from text, we perform semantic dependency analysis on the semantic verb frames of each sentence, and then apply a set of rules to each dependency relation to calculate the contextual valence of the whole sentence. By employing a domain-independent, rule-based approach our system is able to automatically identify sentence-level sentiment. A linguistic tool called “SenseNet” has been developed to recognize sentiments in text, and to visualize the detected sentiments. We conducted several experiments with a variety of datasets containing data from different domains. The obtained results indicate significant performance gains over existing state-of-the-art approaches.     

Self-Adjustable Neural Network for speech recognition

Neural networks with fixed input length are not able to train and test data with variable lengths in one network size. This issue is very crucial when the neural networks need to deal with signals of variable lengths, such as speech. Though various methods have been proposed in segmentation and feature extraction to deal with variable lengths of the data, the size of the input data to the neural networks still has to be fixed. A novel Self-Adjustable Neural Network (SANN) is presented in this paper, to enable the network to adjust itself according to different data input sizes. The proposed method is applied to the speech recognition of Malay vowels and TIMIT isolated words. SANN is benchmarked against the standard and state-of-the-art recogniser, Hidden Markov Model (HMM). The results showed that SANN was better than HMM in recognizing the Malay vowels. However, HMM outperformed SANN in recognising the TIMIT isolated words.     

Trust region methods for solving the optimal output feedback design problem

We consider the problem of designing feedback control laws when a complete set of state variables is not available. For linear autonomous control systems with quadratic performance criterion, the design problem consists of choosing an appropriate static output feedback (SOF) gain matrix according to a certain objective function. The corresponding non-linear matrix optimization problem can be interpreted as an equality constrained minimization problem. For solving this problem, we propose a constrained trust region (CTR) algorithm, which presents a new and efficient numerical approach for this problem class. On the other hand, based on the formulation used in the past, the SOF problem can be also interpreted as an unconstrained programming problem. Thus, based on this interpretation, we also develop an unconstrained trust region (UTR) method. Finally, several numerical examples for optimal SOF problems demonstrate the applicability of the considered algorithm.     

Verification of two machine learning approaches for cloud masking based on reflectance of channel IR3.9 using Meteosat Second Generation over Middle East maritime

ABSTRACT

Most cold channels of Meteosat Second Generation (MSG) satellites can distinguish between the sea and ice cloud tops, except for the IR3.9 channel because of the close reflectance and radiance values of the IR3.9 channel for maritime, low-level cloud and ice cloud tops. In this article, we introduce and evaluate two machine learning methods for cloud masking of Spinning Enhanced Visible and Infrared Imager (SEVIRI) images in the day and night that use the reflectance value of the IR3.9 channel. We reached a good correlation by comparing the results of the modelled cloud masking of Meteosat satellite images with MODIS (Moderate Resolution Imaging Spectroradiometer) and CLM (Cloud Mask product of EUMETSAT) images in a way that the coefficient of determination (R²) value was 92.34%, 89.91% and 83.69%, 78.23% in the cold season and 90.17%, 87.09% and 80.37%, 76.48% in the warm season, respectively, using the CHAID (chi-squared automatic interaction detection) decision tree and RBF (radial basis function) neural network approaches.     

Corresponding regions for shadow restoration in satellite high-resolution images

ABSTRACT

High spatial resolution images available by satellites such as Ikonos, Quickbird, and WorldView-2 provide more information for remote sensing applications, such as object detection, classification, change detection, and object mapping. The presence of shadow reduces the amount of information that can be extracted and consequently makes these applications more difficult or even impossible. In this article, a shadow restoration approach for high-resolution satellite images is proposed. The approach detects the shadow area and segments the image into regions according to the land surface type. Then, shadow restoration is carried out for each region based on the degree of correspondence between shadow and neighbouring non-shadow regions. The proposed approach is applied to study areas from Ikonos and WorldView-2 satellite images. A comparison to the standard approaches for shadow restoration is performed, and an accuracy assessment is carried out by visual inspection and land-cover classification. The results show that the enhanced shadow regions using the proposed approach have better appearances and are highly compatible with their surrounding non-shadow regions. In addition, the overall accuracy is higher than those of the standard approaches.     

Development of multilayer perceptron artificial neural network (MLP-ANN) and least square support vector machine (LSSVM) models to predict Nusselt number and pressure drop of TiO2/water nanofluid flows through non-straight pathways

Abstract

In this study, Multilayer Perceptron Artificial Neural Network (MLP-ANN) model and Least Square Support Vector Machine (LSSVM), were developed to predict the thermal performance and pressure loss of nanofluid flow through coils as non-straight pathways. There different coils with various curvature ratios and coil pitches were constructed and used. Stable TiO₂ (50?nm)/water nanofluid in different concentrations from 0.0 to 2.0% were prepared using appropriate method. As it is expected, considerable enhancement of heat transfer was achieved by application of nanofluids instead of water in system. Volume concentration of nanofluid, Prandtl number (ranging from 4.82 to 9.11) and Helical number (106.80 to 1282.87) were introduced to the developed models to obtain Nusselt number (9.89 to 53.30) and pressure drop (291.35 to 18784?kPa) as the output data of the models. According to the output results of developed models, MLP-ANN model was able to predict both Nusselt number and pressure drop of nanofluid flow more precisely in comparison to LSSVM model. The developed MLP model of this study exceeded LSSVM model to high correlation coefficient value of 0.97.     

Improved Incompressible Smoothed Particle Hydrodynamics method for simulating flow around bluff bodies

In this article, we present numerical solutions for flow over an airfoil and a square obstacle using Incompressible Smoothed Particle Hydrodynamics (ISPH) method with an improved solid boundary treatment approach, referred to as the Multiple Boundary Tangents (MBT) method. It was shown that the MBT boundary treatment technique is very effective for tackling boundaries of complex shapes. Also, we have proposed the usage of the repulsive component of the Lennard-Jones Potential (LJP) in the advection equation to repair particle fractures occurring in the SPH method due to the tendency of SPH particles to follow the stream line trajectory. This approach is named as the artificial particle displacement method. Numerical results suggest that the improved ISPH method which is consisting of the MBT method, artificial particle displacement and the corrective SPH discretization scheme enables one to obtain very stable and robust SPH simulations. The square obstacle and NACA airfoil geometry with the angle of attacks between 0° and 15° were simulated in a laminar flow field with relatively high Reynolds numbers. We illustrated that the improved ISPH method is able to capture the complex physics of bluff-body flows naturally such as the flow separation, wake formation at the trailing edge, and the vortex shedding. The SPH results are validated with a mesh-dependent Finite Element Method (FEM) and excellent agreements among the results were observed.