Investigation on Thrust Force Conversion Method of Oscillating Caudal Fin Based on Wake Vortex Field Structure

The wake field of the flexible oscillating caudal fin is investigated using the Digital Particle Image Velocity (DPIV) system. The distributions of the vorticity with different Strouhal numbers are presented, and a self-developed program is used for calculating the velocity circulation of the vortex ring. Quantitative analysis of the wake field such as velocity circulation of the vortex ring, vortex radius, and the center-to-center spacing of vortex pair is presented. A three-dimensional vortex ring chain model of oscillating caudal fin is introduced. A conversion model between velocity circulation and dynamic moment of the vortex ring is presented according to the vortex dynamics theory, and a self-developed program is used for the calculation, in which the conversion of the thrust force based on wake field of oscillating caudal fin is carried out. Comparisons of the results of the two kinds flexible caudal fins thrust force conversion with the result of tricomponent balance system have been done in this paper. The relative errors are 5.86% and 3.44%, respectively. It is shown that the thrust force conversion model of flexible oscillating caudal fin is accurate and reliable, and the method presented in the paper provides an effective model for the quantitative conversion between the flow field and the thrust force of the caudal fin.

Segmentation of Tomato Growing Truss a Depth Image Conversion Model Based on CycleGAN

Background: The truss on tomato plants is a group or cluster of smaller stems where flowers and fruit develop, while a growing truss is the most extended part of the stem. Because the state of the growing truss reacts sensitively to the surrounding environment, it is essential to control the growth in the early stages. With the recent development of IT and artificial intelligence technology in agriculture, a previous study developed a real-time acquisition and evaluation method for images using robots. Further, we used image processing to locate the growing truss and flowering rooms to extract growth information such as the height of the flower room and hard crab. Among the different vision algorithms, the CycleGAN algorithm was used to generate and transform unpaired images using generatively learning images. In this study, we developed a robot-based system for simultaneously acquiring RGB and depth images of the tomato growing truss and flower room groups.Results: The segmentation performance for approximately 35 samples was compared through the false negative (FN) and false positive (FP) indicators. For the depth camera image, we obtained FN as 17.55±3.01% and FP as 17.76±3.55%. Similarly, for CycleGAN, we obtained FN as approximately 19.24±1.45% and FP as 18.24±1.54%. As a result of image processing through depth image, IoU was 63.56 ± 8.44%, and when segmentation was performed through CycelGAN, IoU was 69.25 ± 4.42%, indicating that CycleGAN is advantageous in extracting the desired growing truss. Conclusions: The scannability was confirmed when the image scanning robot drove in a straight line through the plantation in the tomato greenhouse, which confirmed the on-site possibility of the image extraction technique using CycleGAN. In the future, the proposed approach is expected to be used in vision technology to scan the tomato growth indicators in greenhouses using an unmanned robot platform.

Environmental Critical Aspects of The Conversion of Biomass to Biogas for Sustainable Energy in Indonesia

Renewable energy will become the foundation for meeting the world's energy needs in the future. However, Indonesia has not done much research on the development and application of technology for sustainable energy. Indonesia has potential energy sources. However, biomass conversion into other forms of energy, such as biogas, will hurt the environment. The development of biomass-based bioenergy is one of the best solution for meeting Indonesia's current and future energy needs. Biogas is biomass-based bioenergy, which is the potential for future energy sources. Minimizing the environment's degradation is a significant aspect of preparing the biomass to biogas conversion model. Furthermore, the production of biogas with automatic monitoring and control will minimize new waste formation. Indonesian government regulatory support and total community participation will increase converting biomass into biogas as renewable energy into electrical energy. The paper analyzes the environmental impact of biomass conversion into biogas and proposed an environmentally friendly conversion model.

The Transition in Household Energy Use for Cooking in India: Evidence from a Longitudinal Survey

This article seeks to assess the transition in household energy use for cooking in India based on data from two rounds of the India Human Development Survey in 2004–2005 and 2011–2012. In this study, we have used the multinomial logistic regression and Multiple Classification Analysis conversion model to assess the transition in household energy use according to the socio-economic characteristics of households. Our findings suggest that although the transition from solid fuel to clean fuel is universal across households, it is greater among the socio-economically better-off households than their poorer counterparts. The use of solid fuel for cooking was more prevalent among the socio-economically disadvantaged households than among their socio-economically better-off counterparts in both 2004–2005 and 2011–2012. Convergence in clean cooking fuel use across the households can be possible only when socio-economically disadvantaged households progress faster than their already better-off counterparts. JEL Codes: B5, C23, D31, I3, Q5

Modelling the Kinetics of Color and Texture Changes of Dabai (Canarium odontophyllum Miq.) during Blanching

Dabai (Canarium odontophyllum Miq.) is a fruit that is often eaten by first blanching in hot water to make the flesh creamier and softer, before it is served as a snack or side dish. In this study, Dabai fruit was blanched at different temperatures between 60 and 100 °C, with an increment of 10 °C, for up to 10 min, and the kinetics of quality changes (color and texture) were studied. Kinetic models that were assessed for changes of color and texture were zero-order, first-order, and fractional conversion model. The results showed that L parameter had no change throughout the blanching process, while parameters a*, b*, chroma (C), and total color difference (TCD) resulted as significantly increased as the temperature and duration of blanching increased. However, the change of firmness was not significant due to minor changes of firmness as the temperature and time increased. In terms of kinetic models, zero and fractional-conversion order well described the changes of a* parameter; while zero, first and fractional conversion well described parameters b*, C and TCD. Change of firmness did not fit with zero or first-order. All of the kinetic models obeyed the Arrhenius equation. Thus, the fitted kinetic models can be used to design the blanching process of Dabai fruit.

Online Museums Segmentation with Structured Data: The Case of the Canary Island’s Online Marketplace

This paper’s primary objective is to segment the online marketplace of the Canary Islands’ museums by using different conversion funnel metrics. Little systematic research exists on digital user behaviour, and much less is known about how to segment cultural users with structured data from manually extracted and SEO software sources. With this aim in mind, we built a database with data related to the different phases of the conversion funnel of the museums to segment this online museum marketplace. In the findings, not only do we acknowledge the existence of different segments, but we also provide insight into the user’s digital behaviour by considering different metrics from the different phases of the conversion model process (awareness, consideration, conversion and loyalty). The originality of this paper is multifold. Firstly, it estimates the potential optimisation of these websites to improve the digital marketing implemented by the museum sector of the Canary Islands. Secondly, it sheds light on what benchmarking tactics and statistics procedures can be followed to carry out a non-hierarchical segmentation with standardised and comparable data. Thirdly, it contributes to the literature of digital marketing by eclectically combining the conversion funnel model, benchmarking techniques and non-hierarchical segmentation procedures.

Kalman Filter Photovoltaic Power Prediction Model Based on Forecasting Experience

A Kalman filter photovoltaic (PV) power prediction model based on forecasting experience is proposed to solve the problem that the accuracy of the prediction method based on historical experience is reduced under anomalous situations. This study uses the hourly solar irradiance forecasting model, numerical weather prediction (NWP) data, and the photoelectric conversion model to calculate the ground irradiance and PV power generation, which are used as the forecasting experience data. The dynamic equation of the Kalman filter model is obtained by fitting the forecasting data to make the prediction model with the future situation information properties while solving the modeling difficulties caused by the transcendental equation characteristic of the photoelectric conversion model. In the iterative process of the Kalman filter algorithm, the measured power is used to correct the prediction error and significantly limit the error variability so as to realize the ultra-short-term accurate prediction of PV power and ultimately improve the management of PV energy storage power stations. The comparative analysis through DKASC data simulation verifies that the results show that the proposed model is effective and can achieve better results in predictive accuracy.

E-business Through Social Media: An Instagram Page Attribute-Conversion Model in Context of Fashion Apparel Industry

Instagram is a highly favoured platform for visual businesses, particularly fashion apparel industry. There are increasing number of fashion apparel businesses that are growing without any physical presence, solely on the basis of their online platforms. To explore the role of Instagram in consumer engagement for this sector, this article aims to empirically test an Instagram business page attribute-conversion model to examine how attributes of a business Instagram page can influence the purchase decision of a consumer, and subsequently result in conversion. First, based on focus group interviews, four Instagram page attributes relevant for an online fashion apparel business were identified. These were instant popularity gauge, influencer appeal, visual aesthetic and an interactive forum. The final model was tested among 327 consumers using structural equation modelling (SEM). Further, moderating role of gender was investigated. Results show that having a visually aesthetic and an interactive forum with active participation (followers/comments/likes/views) and collaboration with trusted brands/admired social media influencers should form an important component of Instagram sales conversion strategy for online retail businesses.

Bigdata Assisted Energy Conversion Model for Innovative City Application

Centrally controlled energy conversion schemes in intelligent residential microgrids are a difficult optimization challenge because of their range of processing and power devices accessible. Typical steps to shrink the weight and seriousness of the issues are decreasing modelling precision, adding several weights, or adjusting the measurement accuracy. Nevertheless, because these interventions modify the specialization issue and thus result in various approaches as expected, this article introduces a Bigdata assisted energy conversion model (BD-ECM) and evaluates a decomposition approach to solve the initial problem recursively. Compared to the initial compact version, the decayed approach is tested to demonstrate that all versions differ less than 18.8%. Moreover, both methods contribute to the use of roughly similar structures. The results reveal that because of the existing constraints on computational capital and simulation techniques, condensed development of the common law can only be extended to moderate and limited intelligent grids. However, decentralized approaches can be dealing with sizeable dispersed generation structures. To assess the month’s environmental and strategic advantages as part of the system, researchers extend the decompiled approach to a massive smart grid. The data reveal that prices can be lowered by 14.0% in local energy exchanges and pollution by 23.9% in the situation studied.