19672 research outputs found
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Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation
No full textSolar energy plays a vital role in the field of sustainable energy by providing clean, efficient and reliable alternative source of energy. Where, the output of solar energy systems is highly dependent on the solar radiation. Thus, accurate prediction of solar radiation is considered as a very important factor for such applications. In this paper, standalone adaptive neuro-fuzzy inference system and hybrid models have been developed to predict monthly global solar radiation from different meteorological parameters such as sunshine duration S(h), and air temperature. The proposed hybrid models include particle swarm optimization, genetic algorithm and differential evolution. To evaluate the capability and efficiency of the proposed models, several statistical indicators such as; root mean square error, co-efficient of determination and mean absolute bias error are used. All prediction models’ results showed good agreements with measured datasets. The performance evaluation over different statistical indicators showed high correlation for all developed modules. Whereas, hybrid particle swarm optimization has achieved the best statistical indicators over all models in training and testing models. A detailed comparison with other studies is carried out to validate the prediction accuracy and suitability of the proposed models. The results showed that the developed hybrid models have the most reliable and accurate estimation capability and deemed to be the efficient methods for predicting global solar radiation for various applications
Pyrolysis analyses and bulk kinetic models of the Late Cretaceous oil shales in Jordan and their implications for early mature sulphur-rich oil generation potential
No full textIn this study, oil shale samples were collected from Late Cretaceous Muwaqaar Chalk Marl Formation (MCM) in Jordan to study their petrologic and organic geochemical properties. Pyrolysis and bulk kinetic techniques were performed on the Late Cretaceous oil shales. The results of this study were used to characterize the different organofacie types in the Late Cretaceous oil shales and their effect on the petroleum type generated during thermal maturation and the temperature of petroleum generation. On the basis of the geochemical results, the analysed Late Cretaceous oil shales contain predominantly Type II and rarely Type I kerogens. These kerogens are consistent with the high dominate of sapropel organic matter (i.e., alginite and amorphous organic matter). A good correlation is noted between increasing abundance of organic matter and the kerogen type that was derived from an open pyrolysis–gas chromatography (Py–GC). The Py–GC data indicate the analysed oil shale samples contain heterogeneous organic matter of the kerogen Type II-S. It is interesting to know that this sulphur-rich kerogen (Type II-S) can generate high sulphur oils at low maturity ranges. This is consistent with the predicted temperature petroleum generation from bulk kinetic models. The bulk kinetic models in this study indicate that the main phase of petroleum formation from the thermally immature Late Cretaceous oil shales occur between 122 and 148 °C. These temperature values of the petroleum generation are generally consistent with the kerogen type II-S and further indicate that the analysed oil shale samples can generate sulfur-rich oils at early stage of kerogen cracking
Linear and nonlinear causal relationship between energy consumption and economic growth in China: New evidence based on wavelet analysis
No full textThe energy-growth nexus has important policy implications for economic development. The results from many past studies that investigated the causality direction of this nexus can lead to misleading policy guidance. Using data on China from 1953 to 2013, this study shows that an application of causality test on the time series of energy consumption and national output has masked a lot of information. The Toda-Yamamoto test with bootstrapped critical values and the newly proposed non-linear causality test reveal no causal relationship. However, a further application of these tests using series in different time-frequency domain obtained from wavelet decomposition indicates that while energy consumption Granger causes economic growth in the short run, the reverse is true in the medium term. A bidirectional causal relationship is found for the long run. This approach has proven to be superior in unveiling information on the energy-growth nexus that are useful for policy planning over different time horizons
Formation and characterization of intermetallic compounds in electroplated cobalt–tin multilayers
No full textIntermetallic compounds (IMC) form during the metallurgical bonding processes when the interfaces involve solid metal and molten solder. Cobalt (Co) is a promising candidate to be used as under bump metallization (UBM) material, tin (Sn)-based solder alloying element, and transient liquid phase bonding base metal. This work aims at studying the intermixing reaction in Co–Sn system from electroplated Co and Sn multilayers. Co–Sn couples were sequentially electroplated and reflowed at 400 °C for 1 and 4 h. The microstructure and composition of the phases formed at different reflow duration were characterized by field emission scanning electron microscopy (FESEM) coupled with energy dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD). Mechanical properties of the IMC layers formed in the samples were characterized using the nanoindentation technique under quasi-static and continuous measurement modes. FESEM/EDX and XRD analysis showed a mixture of CoSn+CoSn2 phases was formed in the 1 h reflow sample. As reflow time was increased to 4 h, only CoSn phase was found. Pure CoSn phase exhibits high nanohardness of 9.51 GPa while the region with CoSn+CoSn2 phases gives nanohardness value of 6.83 GPa
Enhanced structural properties of In2O3 nanoparticles at lower calcination temperature synthesised by co-precipitation method
No full textIndium oxide nanoparticles (In2O3 NPs) were formed by calcining the optimised as-prepared indium hydroxide (In(OH)3) NPs. The as-prepared In(OH)3 NPs were synthesised at optimal pH 10 through co-precipitation method at various calcination temperatures (200, 300, 400, 500, 600°C) for 2 h. Characterisation of the samples was performed by thermogravimetric (TGA and differential thermal, DTA) analysis, high-resolution transmission electron microscope (HRTEM), X-ray diffractometer (XRD), Fourier transform infrared spectroscopy, and Raman spectroscopy. The complete conversion to In2O3 NPs was reached at 300°C. Besides, the crystallite size of In2O3 NPs calculated by William-Hall equation had the same trend with the values obtained from Scherrer equation. The HRTEM images also showed that the size of In2O3 NPs was within the range of 15-28 nm. Clearly, their work confirmed that the smallest In2O3 NPs (15 nm) with homogenous particle distribution were formed at a lower calcination temperature of 300°C
Do consumers want mobile commerce? A closer look at M-shopping and technology adoption in Malaysia
No full textPurpose: Mobile shopping is expected to emerge as a new way of shopping as the Asia Pacific region moves towards the digital era. It is important to understand factors that influence consumers’ intentions to adopt this new shopping channel, especially in developing countries such as Malaysia where it has the fastest growing mobile penetration rate in the world. The purpose of this paper is to integrate the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB), and includes additional variables such as personal innovativeness (PI) and trust. Design/methodology/approach: Empirical data from 453 consumers were tested against a proposed model using partial least squares structural equation modelling. Findings: Findings suggest that most of the constructs in the model (i.e. trust, perceived ease of use, perceived usefulness, attitudes, PI and perceived behavioural control) influence a shopper’s intentions towards adopting mobile shopping. For example, consumers’ attitudes towards M-shopping adoption is higher if a system is not complex and easy to use; if consumers can easily pull out their mobile devices from their pockets to browse or shop by using just one finger, without a complicated process, they tend to use M-shopping channels. In addition, when mobile technology is user-friendly and free from mental effort, it creates positive perceptions that the system is useful, developing stronger intentions for consumers to adopt this alternative. Originality/value: Since M-shopping is a personalised activity that involves money transactions, consumers are more cautious with adoption intentions, and do not follow social norms blindly. Thus, the empirical evidence from Malaysian consumers contributes to literature with insights into their specific m-shopping behaviour in this emerging market. In addition, from a theoretical perspective, the research model in this study integrates both TAM and TPB to provide a holistic view of consumers’ M-shopping adoption intentions in an emerging market, incorporating user-centric factors (i.e. trust and PI). An important finding which differs from other studies is that the relationship between subjective norms and behavioural intention to use M-shopping was not significant, which is contrary to the findings of previous studies. Moreover, attitude was found to mediate the effect of PEOU and PU on consumer’s intention towards mobile shopping adoption. The validated instrument would serve as a useful guideline for researchers during development and refinement of studies on M-shopping
Thermal conductivity optimization and entropy generation analysis of titanium dioxide nanofluid in evacuated tube solar collector
No full textTitanium dioxide (TiO2) nanofluid is produced by dispersing a small amount of TiO2 nanoparticles in distilled water. The high thermal conductivity of the TiO2 nanofluid can improve the performance of evacuated tube solar thermal collector (ETSC). The main objectives of this study are to evaluate the thermal efficiency and perform entropy analysis of an ETSC in which TiO2 nanofluid is used as the working fluid. Response surface methodology is used to determine the optimum thermal conductivity of the TiO2 nanofluid. The following factors are varied for the optimization process: (1) volumetric concentration of nanoparticles, (2) amount of surfactant, and (3) sonication time. The optimum factors are as follows: (1) volumetric concentration of TiO2 nanoparticles: 0.50 vol%, (2) surfactant-to-nanoparticle ratio: 1:1, and (3) sonication time: 10.0 min. Excessive amounts of polyvinylpyrrolidone (PVP) surfactant significantly reduce the thermal conductivity of the TiO2 nanofluid. The thermal conductivity of the TiO2 nanofluid increases by 7.28% when it is prepared under optimum conditions. The TiO2 nanofluid with the optimum thermal conductivity is used as the working fluid in the ETSC. It is found that thermal efficiency of the ETSC increases with an increase in the mass flow rate of water and TiO2 nanofluid. The results show that the entropy generation decreases by 1.23% whereas the thermal efficiency increases by 16.5% when the optimum TiO2 nanofluid is used in the ETSC compared with those for distilled water at a mass flow rate of 0.033 kg/s. The heat transfer capability increases by using TiO2 nanofluid with high thermal conductivity as well as high mass flow rate. In conclusion, the performance of the ETSC can be enhanced by using stable nanofluid as the heat transfer fluid because of its high thermal conductivity
Spectroscopic studies on the interaction of green synthesized-gold nanoparticles with human serum albumin
No full textThe interaction of gold nanoparticles, synthesized using Curcuma mangga extract (CM-AuNPs) with human serum albumin (HSA) was investigated with the help of fluorescence, UV absorption and circular dichroism (CD) spectroscopy. In view of the positive correlation of Stern-Volmer constant with temperature, quenching of protein fluorescence observed upon addition of CM-AuNPs seems to occur through collisional mechanism. The quenching mechanism was further substantiated by UV absorption spectral results, where no significant change in the absorption spectrum of HSA was observed upon addition of CM-AuNPs. Analysis of the fluorescence quenching titration data revealed moderate binding affinity (Ka = 0.97 × 104 M−1 at 298 K) between CM-AuNP and HSA. The complexation between CM-AuNP and HSA was predicted to be stabilized by hydrophobic forces, as reflected from the thermodynamic data (ΔH = +35.5 kJ mol−1 and ΔS = +195.62 J mol−1 K−1). Three-dimensional fluorescence spectral analysis demonstrated perturbation of microenvironment around Trp and Tyr residues in HSA upon CM-AuNPs addition. While interaction between CM-AuNP and HSA produced significant tertiary structural change in the protein, secondary structures remained unaltered, as elucidated by near-UV and far-UV CD spectral analyses, respectively. ANS displacement experiments suggested Sudlow's Site II, located in subdomain IIIA, as the preferred binding site of CM-AuNP on HSA
Erythrocyte-binding assays reveal higher binding of Plasmodium knowlesi Duffy binding protein to human Fya+/b+ erythrocytes than to Fya+/b- erythrocytes
No full textBACKGROUND: The merozoite of the zoonotic Plasmodium knowlesi invades human erythrocytes via the binding of its Duffy binding protein (PkDBPαII) to the Duffy antigen on the eythrocytes. The Duffy antigen has two immunologically distinct forms, Fya and Fyb. In this study, the erythrocyte-binding assay was used to quantitatively determine and compare the binding level of PkDBPαII to Fya+/b+ and Fya+/b- human erythrocytes. RESULTS: In the erythrocyte-binding assay, binding level was determined by scoring the number of rosettes that were formed by erythrocytes surrounding transfected mammalian COS-7 cells which expressed PkDBPαII. The assay result revealed a significant difference in the binding level. The number of rosettes scored for Fya+/b+ was 1.64-fold higher than that of Fya+/b- (155.50 ± 34.32 and 94.75 ± 23.16 rosettes, respectively; t(6) = -2.935, P = 0.026). CONCLUSIONS: The erythrocyte-binding assay provided a simple approach to quantitatively determine the binding level of PkDBPαII to the erythrocyte Duffy antigen. Using this assay, PkDBPαII was found to display higher binding to Fya+/b+ erythrocytes than to Fya+/b- erythrocytes
BTPC-Based DES-Functionalized CNTs for As3+ Removal from Water: NARX Neural Network Approach
No full textIn this study, a novel adsorbent process was developed using a deep eutectic solvent (DES) system based on benzyltriphenylphosphonium chloride (BTPC) as a functionalization agent of carbon nanotubes (CNTs) for arsenic ion removal from water. The nonlinear autoregressive network with exogenous inputs (NARX) neural network strategy was used for the modeling and predicting the adsorption capacity of functionalized carbon nanotubes. The developed adsorbent was characterized using zeta potential, Fourier transform infrared (FTIR), and Raman spectroscopy. The effects of operational parameters such as initial concentration, adsorbent dosage, pH, and contact time are studied to investigate the optimum conditions for maximum arsenic removal. Three kinetic models were used to identify the adsorption rate and mechanism, and the pseudo-second order best described the adsorption kinetics. Four statistical indicators were used to determine the efficiency and accuracy of the NARX model, with a minimum value of mean square error, 6.37×10-4. In addition, a sensitivity study of the parameters involved in the experimental work was performed. The NARX model prediction was consolidated with the experimental result and proved its efficiency at predicting arsenic removal from water with a correlation coefficient R2 of 0.9818