Half-duplex energy harvesting relay network over different fading environment: System performance with effect of hardware impairment

In this paper, we introduce a half-duplex (HD) energy harvesting (EH) relay network over the different fading environment with the effect of hardware impairment (HI). The model system was investigated with the amplify-and-forward (AF) and the power splitting (PS) protocols. The system performance analysis in term of the outage probability (OP), achievable throughput (AT), and bit error rate (BER) were demonstrated with the closed-form expressions. In addition, the power splitting (PS) factor was investigated. We verified the analytical analysis by Monte Carlo simulation with all primary parameters. From the results, we can state that the analytical and simulation results match well with each other.Web of Science911art. no. Unsp 228

A note on dissipative particle dynamics (DPD) modelling of simple fluids

In this paper, we show that a Dissipative Particle Dynamics (DPD) model of a viscous Newtonian fluid may actually produce a linear viscoelastic fluid. We demonstrate that a single set of DPD particles can be used to model a linear viscoelastic fluid with its physical parameters, namely the dynamical viscosity and the relaxation time in its memory kernel, determined from the DPD system at equilibrium. The emphasis of this study is placed on (i) the estimation of the linear viscoelastic effect from the standard parameter choice; and (ii) the investigation of the dependence of the DPD transport properties on the length and time scales, which are introduced from the physical phenomenon under examination. Transverse-current auto-correlation functions (TCAF) in Fourier space are employed to study the effects of the length scale, while analytic expressions of the shear stress in a simple small amplitude oscillatory shear flow are utilised to study the effects of the time scale. A direct mechanism for imposing the particle diffusion time and fluid viscosity in the hydrodynamic limit on the DPD system is also proposed

Experimental results of gaslift process

In the paper, the investigation results of periodical gas-lift flows in vertical pipes using experiment method are presented. The experiment facilities consist of flow measurement equipment, gas and fluid supplier facilities, tubing system. To study the influence of medium physical and dynamical characteristics on the process efficiency, two liquid-gas systems are used, namely, water-air and spindle oil-air. The objects of investigation are to obtain data from tests conducted in some conduits and to analyse the influence of system physical, geometrical and etc. parameters such as: initial liquid height in the conduits, gas injected volume, conduit diameter, conduit configuration and etc. on the considered process

Factors affecting green food purchase intention in Ho Chi Minh City

This study adopts Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) to measure factors affecting green food purchase intention in Ho Chi Minh city (HCMC). The survey data was collected from 197 students during the period of 1st to 20th September, 2017. Testing the conceptual model by Structural Equation Modeling (SEM), we find that perceived usefulness of green food and perceived ease of purchase impact on attitudes towards green food purchase. We also find that subjective norm, perceived usefulness of green food, attitudes towards green food purchase are positively associated with green food purchase intention. From the research findings, some recommendations are proposed accordingly

Hydrothermal Synthesis and Optical Properties of Undoped and Eu3+\text{Eu}^{3+}-doped Zinc Stannate Nanocrystals

Abstract. In this work we report a hydrothermal approach for synthesis of zinc stannate (Zn2SnO4)nanocrystals. Our research focused on the effect of the molar ratio of initial chemicals, reaction temperature and reaction duration on the phase composition and the fluorescence properties.Structural and optical properties of the final products were investigated in detail. X-ray diffractionanalysis indicated that the Zn2SnO4 nanocrystals possess face-centered cubic crystal structure.Raman scattering spectra exhibit two characteristic vibrational modes of Zn2SnO4 crystals. Optical band gap of Eu3+-doped Zn2SnO4 nanocrystals obviously depends on Eu3+content. Theroom-temperature emission spectra of the undoped Zn2SnO4 nanocrystals show two broad bands,while the photoluminescence spectra of Eu3+-doped Zn2SnO4 nanocrystals exhibit the emissionpeaks related to the radiative intra-configurational f-f tr ansitions of Eu3+ions. The absorptiontransitions within Eu3+ions were observed both in the photoluminescence excitation spectra andin the diffuse reflection spectra

Some initial experimental results on the conditions of free water layer formation in horizontal pipes

This paper presents an experimental facility conducted in Hanoi Institute of Mechanics to investigate multiphase How pattern in the pipes. First and foremost, it is used to define the conditions of water layer formation in the horizontal pipe.Experimental results have been obtained in stainless steel pipes of three different diameters (24.6mm; 30.8mm and 40.5mm) with white spindle oil N° 10 and water. They have been shown in the form of water layer maps

Energy harvesting-based spectrum access with incremental cooperation, relay selection and hardware noises

In this paper, we propose an energy harvesting (EH)-based spectrum access model in cognitive radio (CR) network. In the proposed scheme, one of available secondary transmitters (STs) helps a primary transmitter (PT) forward primary signals to a primary receiver (PR). Via the cooperation, the selected ST finds opportunities to access licensed bands to transmit secondary signals to its intended secondary receiver (SR). Secondary users are assumed to be mobile, hence, optimization of energy consumption for these users is interested. The EH STs have to harvest energy from the PT's radio-frequency (RF) signals to serve the PTPR communication as well as to transmit their signals. The proposed scheme employs incremental relaying technique in which the PR only requires the assistance from the STs when the transmission between PT and PR is not successful. Moreover, we also investigate impact of hardware impairments on performance of the primary and secondary networks. For performance evaluation, we derive exact and lower-bound expressions of outage probability (OP) over Rayleigh fading channel. Monte-Carlo simulations are performed to verify the theoretical results. The results present that the outage performance of both networks can be enhanced by increasing the number of the ST-SR pairs. In addition, the outage performance of both primary and secondary networks is severely degraded with the increasing of hardware impairment level. It is also shown that fraction of time used for EH and positions of the secondary users significantly impact on the system performance.Web of Science26125024

Exploring Value Co-Destruction Process in Customer Interactions with AI-Powered Mobile Applications

Background: Mobile applications have emerged as important touchpoints for addressing service requests and optimizing human resources. Within the service industry, the integration of artificial intelligence (AI) into these applications has enabled the inference of product demand, provision of personalized service offers, and enhancement of overall firm value. Customers now engage with these apps to stay informed, seek guidance, and make purchases. It is important to recognize that the interactive and human-like qualities of AI can either foster the co-creation of value with customers or potentially lead to the co-destruction of customer value. Although prior research has examined the process of value co-creation, the present study aims to investigate the underlying factors contributing to the value co-destruction process, specifically within AI-powered mobile applications. Method: Our research employs topic modelling and content analysis to examine the value co-destruction process that occurs when customers engage with AI apps. We analyze 7,608 negative reviews obtained from eleven AI apps available on Google Play and App Store AI apps. Results: Our findings reveal six distinct types of value - utilitarian, hedonic, symbolic, social, epistemic, and economic value - that can be co-destroyed during the process. System failure, self-threat and privacy violation are some contributing factors to this value co-destruction process. These values change over time and vary depending on the type of app. Conclusion: Theoretically, our findings extend the concept of value co-destruction in the context of AI apps. We also offer practical recommendations for designing an AI app in a more service-friendly way

Combined analysis of acoustic emission and vibration signals in monitoring tool wear, surface quality and chip formation when turning SCM440 steel using MQL

With modern production, Minimum Quantity Lubricant (MQL) technology has emerged as an alternative to conventional liquid cooling. The MQLs is an environmentally friendly lubricant method with low cost while meeting the requirements of machining conditions. In this study, the experimental and analytical results show that the obtained acoustic emission (AE) and vibration signal components can effectively monitor various circumstances in the SCM440 steel turning process with MQL, such as surface quality and chip formation as cutting tool conditions. The AE signals showed a significant response to the tool wear processes. In contrast, the vibration signal showed an excellent ability to reflect the surface roughness during turning with MQL. The chip formation process through the cutting mode parameters (cutting speed, feed and depth of cut) was detected through analysis amplitude of the vibration components Ax, Ay and Az and the AE signal. Finally, Gaussian process regression and adaptive neuro-fuzzy inference systems (GPR-ANFIS) algorithms were combined to predict the surface quality and tool wear parameters of the MQL turning process. Tool condition monitoring devices assist the operator in monitoring tool wear and surface quality limits, stopping the machine in case of imminent tool breakage or lower surface quality. With the unique combination of AE and vibration analysis model and the training and testing samples established by the experimental data, the corresponding average prediction accuracy is 97.57 %. The highest prediction error is not more than 3.8 %, with a confidence percentage of 98 %. The proposed model can be used in industry to predict surface roughness and wear of the tools directly during turnin