Search results for: numerical model

Authors: Shubham Mandliya, Pooja Pandey, H. N. Mishra

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Amla (Phyllanthus emblica), a plant of Euphorbiaceous is widely distributed in subtropical and tropical areas of China, India, Indonesia, and Malaysia. Amla is very high in vitamin C content. Spray drying of fruit juices represents another alternative way to improve the physicochemical stability and increase their shelf life. Samples of amla powder were produced using the spray drying method to investigate the effect of inlet temperatures and maltodextrin levels. The spray dryer model used was a laboratory scale dryer and samples were run at different temperatures and concentrations. The response surface methodology (RSM) was used to optimize the spray-drying process for the development of amla powder. The resultant powders were then analyzed for vitamin C, moisture, solubility and dispersibility. The spray dried amla powder contains higher amounts of vitamin C when compared to commercial fruit juice powders. SEM analysis revealed that lower maltodextrin levels and higher inlet air temperatures resulted in smaller but smoother particles. At lower temperature, vitamin C content is high as compared to higher temperature. Spray drying is an effective as well as an economic method which can be commercially used for making powder rather than by tray or solar drying as more fraction is retained with less cost.

Keywords: Amla powder, physiochemical properties, response surface methodology, spray drying

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Authors: Karchung, S. Ruangsinchaiwanich

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This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Keunock Lew, Seungryul Ma

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The paper analyzes risk and expected return of lenders who provide mortgage loans to households in the shared mortgage program of Korea. In 2013, the Korean government introduced the mortgage program to help low income householders to convert their renting into purchasing houses. The financial source for the mortgage program is the Urban Housing Fund set up by the Korean government. Through the program, low income households can borrow money from lenders to buy a house at a very low interest rate (e.g. 1 % per year) for a long time. The motivation of adopting this mortgage program by the Korean government is that the cost of renting houses has been rapidly increased especially in large urban areas during the past decade, which became financial difficulties to low income households who do not have their own houses. As the analysis methodology, the paper uses a spread sheet model for projecting cash flows of the mortgage product over the period of loan contract. It also employs Monte Carlo simulation method to analyze the risk and expected yield of the lenders with assumption that the future housing price and market rate of interest follow a stochastic process. The study results will give valuable implications to the Korean government and lenders who want to stabilize the mortgage program and innovate the related loan products.

Keywords: expected return, Monte Carlo simulation, risk, shared mortgage program

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Authors: D. C. Soares, J. T. S. Santos, D. G. Costa, A. K. S. Abud, T. P. Nunes, A. V. D. Figueiredo, A. M. de Oliveira Junior

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Mangabeira (Hancornia speciosa Gomes), a native plant in Brazil, is found growing spontaneously in various regions of the country. The high perishability of tropical fruits such as mangaba, causes it to be necessary to use technologies that promote conservation, aiming to increase the shelf life of this fruit and add value. The objective of this study was to compare the mangabas lyophilisation curves behaviours with different sizes and maturation stages. The fruits were freeze-dried for a period of approximately 45 hours at lyophilizer Liotop brand, model L -108. It has been considered large the fruits between 38 and 58 mm diameter and small, between 23 and 28 mm diameter and the two states of maturation, intermediate and mature. Large size mangabas drying curves in both states of maturation were linear behaviour at all process, while the kinetic drying curves related to small fruits, independent of maturation state, had a typical behaviour of drying, with all the well-defined steps. With these results it was noted that the time of lyophilisation was suitable for small mangabas, a fact that did not happen with the larger one. This may indicate that the large mangabas require a longer time to freeze until reaches the equilibrium level, as it happens with the small fruits, going to have constant moisture at the end of the process. For both types of fruit were analysed water activity, acidity, protein, lipid, and vitamin C before and after the process.

Keywords: freeze dryer, mangaba, conservation, chemical characteristics

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Authors: Karl-Erich Lindenschmidt, Apurba Das, Joel Trudell, Keanne Russell

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In this presentation, we explore options for mitigating ice-jam flooding along the Athabasca River in western Canada. Not only flood hazard, expressed in this case as the probability of flood depths and extents being exceeded, but also flood risk, in which annual expected damages are calculated. Flood risk is calculated, which allows a cost-benefit analysis to be made so that decisions on the best mitigation options are not based solely on flood hazard but also on the costs related to flood damages and the benefits of mitigation. The river ice model is used to simulate extreme ice-jam flood events with which scenarios are run to determine flood exposure and damages in flood-prone areas along the river. We will concentrate on three mitigation options – the placement of a dike, artificial breakage of the ice cover along the river, the installation of an ice-control structure, and the construction of a reservoir. However, any mitigation option is not totally failsafe. For example, dikes can still be overtopped and breached, and ice jams may still occur in areas of the river where ice covers have been artificially broken up. Hence, for all options, it is recommended that zoning of building developments away from greater flood hazard areas be upheld. Flood mitigation can have a negative effect of giving inhabitants a false sense of security that flooding may not happen again, leading to zoning policies being relaxed. (Text adapted from Lindenschmidt [2022] "Ice Destabilization Study - Phase 2", submitted to the Regional Municipality of Wood Buffalo, Alberta, Canada)

Keywords: ice jam, flood hazard, flood risk river ice modelling, flood risk

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: F. Al-Mufadi, F. Djavanroodi

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During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of standard deviation (S. D.) and inhomogeneity index (Ci) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 20° and 20 mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67 HV from 21 HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.

Keywords: SPD, ECAP, FEM, pure Al, mechanical properties

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Authors: Laura Jenkins, Tim Eschle, Joanne Ciafone, Colin Hamilton

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An original working memory model suggested the separation of visual and verbal systems in working memory architecture, in which only visual working memory components were used during visual working memory tasks. It was later suggested that the visuo spatial sketch pad was the only memory component at use during visual working memory tasks, and components such as the phonological loop were not considered. In more recent years, a contrasting approach has been developed with the use of an executive resource to incorporate both visual and verbal representations in visual working memory paradigms. This was supported using research demonstrating the use of verbal representations and an executive resource in a visual matrix patterns task. The aim of the current research is to investigate the working memory architecture during both a quantitative and a qualitative visual working memory task. A dual task method will be used. Three secondary tasks will be used which are designed to hit specific components within the working memory architecture – Dynamic Visual Noise (visual components), Visual Attention (spatial components) and Verbal Attention (verbal components). A comparison of the visual working memory tasks will be made to discover if verbal representations are at use, as the previous literature suggested. This direct comparison has not been made so far in the literature. Considerations will be made as to whether a domain specific approach should be employed when discussing visual working memory tasks, or whether a more domain general approach could be used instead.

Keywords: semantic organisation, visual memory, change detection

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Authors: Kaleb Shiferaw, Berhanu Geberemedhin, Dereje Legesse

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Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However, only a few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit for the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services.

Keywords: livestock production, credit access, credit allocation, household decision, double sample selection

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Authors: Malik D. Halidu, Cathrine F. Moe, Tommy Haugan

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Purpose: The demand for effective school-based interventions in shaping adolescents' unmet mental health needs is growing. Grounding in the functional contextualism approach, this study investigates the role of school satisfaction (SS) in serving as a buffer to school absenteeism (SAB) among adolescents experiencing social anxiety (SA). Methods: A unique and large population-based sample of adolescents (upper secondary school pupils; n= 1864) from the Young-HUNT 3 survey dataset merged with the national educational registry from Norway. Moderation regression analysis was performed using Stata 17. Results: We find a statistically significant moderating role of school satisfaction on the relationship between social anxiety and school absenteeism (β=-0.109,p<0.01) among upper secondary school pupils. Among socially anxious adolescents associated with a higher perceived quality of school life, it functions as a buffer by reducing the positive relationship between SA and SAB. But, there was no statistically significant difference between social anxiety and school absenteeism for adolescents with low school satisfaction. Conclusion: Overall, the study's hypothesis model was statistically supported and contributes to the discourse that school satisfaction as a target of school-based interventions can effectively improve school outcomes (e.g., reduced absenteeism) among socially anxious pupils.

Keywords: social anxiety, school satisfaction, school absenteeism, Norwegian adolescent

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Authors: Valean Maria

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Construction and demolition waste management is a timely topic, due to the urgency of its transition to sustainability. This sector is responsible for over a third of the waste generated in the E.U., while the legislation requires a proportion of at least 70% preparation for reuse and recycle, excluding backfilling. To this end, the E.U. Commission has provided the Level(s) methodology, allowing for the standardized planning and reporting of waste quantities across all levels of the construction process, from the architecture, to the demolition, from the estimation stage, to the actual measurements at the end of the operations. We applied Level(s) for the first time to the Romanian context, a developing E.U. country in which illegal dumping of contruction waste in nature and landfills, are still common practice. We performed the desk study of the buildings’ documents, followed by field studies of the sites, and finally the insertion and calculation of statistical data of the construction and demolition waste. We learned that Romania is far from the E.U. average in terms of the initial estimations of waste, with some numbers being higher, others lower, and that the price of evacuation to landfills is significantly lower in the developing country, a possible barrier to adopting the new regulations. Finally, we found that concrete is the predominant type waste, in terms of quantity as well as cost of disposal. Further directions of research are provided, such as mapping out all of the alternative facilities in the region and the calculation of the financial costs and of the CO2 footprint, for preparing and delivering waste sustainably, for a more sound and locally adapted model of waste management.

Keywords: construction, waste, management, levels, EU

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Authors: Didem Güven, Oytun Hanhan, Elif Ceren Aksoy, Emine Ubay Çokgör

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This paper presents a biological treatability study ofpaintshopwastewaterof a bus factory by an anoxic/aerobic sequencing batch reactor.A lab scale 14L SBR system was implementedto investigate carbon and nitrogen removal performance frompaint shop waste streams combined with domestic and process wastewater of a bus production factory in Istanbul (Turkey).The wastewater collected from decanters of the paint boots and pre-treatmentplant was usedforthefeeding of SBR. The reactor was operated with a total hydraulic retention time of 24 hrs, and a total sludge age of 18.7 days. Initially the efficiency and stability of the reactor were studied when fed with main wastewater stream to simulate the current wastewater treatment plant. Removal efficiency of 57% nitrogen and 90% COD were obtained. Once the paint shop wastewater was introduced to mainstream feeding with a ratio of 1:5, nitrification completely, carbon removal were partially inhibited. SBR system was successful to handle even at very high COD concentrations of paint shop wastewater after feeding of 2 months, with an average effluent COD of 100 mg/L. For the determination of kinetic parameters, respirometric analysis was also conducted with/without paint shop wastewater addition. Model simulation indicated lower maximum specific growth and hydrolysis rates when paint shop wastewater was mixed with the mainstream wastewater of the factory.

Keywords: biological treatability, nitrogen removal, paint shop wastewater, sequencing batch reactor

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Authors: Nancy Bartekian, Kaelan Vazquez, Christine Reyna

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Immigrants coming into the United States of America may justify the American system (political, economic, healthcare, criminal justice) and see it as functional. This may be explained because they may come from countries that are even more unstable than the U.S. and/or come here to benefit from the promise of the “American dream” -a narrative that they might be more likely to believe in if they were willing to undergo the costly and sometimes dangerous process to immigrate. Conversely, native-born Americans, as well as immigrants who may have lived in America for a longer period of time, would have more experiences with the various broken systems in America that are dysfunctional, fail to provide adequate services equitably, and/or are steeped in systemic racism and other biases that disadvantage lower-status groups. Thus, our research expects that system justification would decrease, and condemnation would increase with more time spent in the U.S. for immigrant groups. We predict that a) those not born in the U.S. will be more likely to justify the system, b) they will also be less likely to condemn the system, and c) the longer an immigrant has been in the U.S. the less likely they will to justify, and more they will to condemn the system. We will use a mixed-model multivariate analysis of covariance (MANCOVA) and control for race, income, and education. We will also run linear regression models to test if there is a relationship between the length of time in the United States and a decrease in system justification, and length of time and an increase in system condemnation for those not born in the U.S. We will also conduct exploratory analyses to see if the predicted patterns are more likely within certain systems over other systems (political, economic, healthcare, criminal justice).

Keywords: immigration, system justification, system condemnation, system qualification

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Authors: U. Yerlikaya, R. T. Balkan

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In this research, a method is developed to obtain high-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-dimensional (D) workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. The number of dimensions of the configuration space comes from the degree of freedoms of the system of interest. The method can be applied in two ways. In the first way, the point clouds of all the bodies of the system and interaction of them are used. The second way is performed via using the clearance function of simulation software where the minimum distances between surfaces of bodies are simultaneously measured. A double-turret system is held in the scope of this study. The 4-D configuration space of a double-turret system is obtained in these two ways. As a result, the difference between these two methods is around 1%, depending on the density of the point cloud. The disparity between the two forms steadily decreases as the point cloud density increases. At the end of the study, in order to verify 4-D configuration space obtained, 4-D path planning problem was realized as 2-D + 2-D and a sample path planning is carried out with using A* algorithm. Then, the accuracy of the configuration space is proved using the obtained paths on the simulation model of the double-turret system.

Keywords: A* algorithm, autonomous turrets, high-dimensional C-space, manifold C-space, point clouds

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Authors: M. D. Antoine

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When a child is diagnosed with an illness, condition, or developmental disorder, the process involved in understanding and accepting this diagnosis can be a very stressful and isolating experience for parents and families. The healthcare providers’ ability to effectively communicate in such situations represents a vital lifeline for parents. In this context, communication becomes a crucial element not only for getting through the period of grief but also for the future. We mobilized the five stages of grief model to summarize existing literature regarding the ways in which the experience ofan autism spectrum disorder diagnosis disclosurealigns with the experience of grief to explore how this can inform best practices for effective communication with parents through the diagnosis disclosure. Fifteen publications met inclusion criteria. Findings from the scoping review of empirical studies show that parents/families experience grief-like emotions during the diagnosis disclosure. However, grief is not an outcome of the encounter itself. In fact, the experience of the encounter can help mitigate the grief experience. The way parents/families receive and react to the ‘news’ depends on their preparedness, knowledge, and the support received through the experience. Individual communication skills, as well as policies and regulations, should be examined to alleviate adverse reactions in this context. These findings highlight the importance of further research into effective parent-provider communication strategies and their place in supporting quality autism care.

Keywords: autism spectrum disorder, autism spectrum disorder diagnosis, diagnosis disclosure, parent-provider communication, parental grief

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Authors: Abhiyan Paudel, Maheshwaran M Pillai

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This paper deals with the optimization and comparison of slender delta wing and blended wing body. The objective is to study the difference between the two wing types and analyze the various aerodynamic characteristics of both of these types.The blended-wing body is an aircraft configuration that has the potential to be more efficient than conventional large transport aircraft configurations with the same capability. The purported advantages of the BWB approach are efficient high-lift wings and a wide airfoil-shaped body. Similarly, symmetric separation vortices over slender delta wing may become asymmetric as the angle of attack is increased beyond a certain value, causing asymmetric forces even at symmetric flight conditions. The transition of the vortex pattern from being symmetric to asymmetric over symmetric bodies under symmetric flow conditions is a fascinating fluid dynamics problem and of major importance for the performance and control of high-maneuverability flight vehicles that favor the use of slender bodies. With the use of Star CCM, we analyze both the fluid properties. The CL, CD and CM were investigated in steady state CFD of BWB at Mach 0.3 and through wind tunnel experiments on 1/6th model of BWB at Mach 0.1. From CFD analysis pressure variation, Mach number contours and turbulence area was observed.

Keywords: Coefficient of Lift, Coefficient of Drag, CFD=Computational Fluid Dynamics, BWB=Blended Wing Body, slender delta wing

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Authors: Hamze Torabian, Mohammad Mehrabioun Mohammadi

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Like many other industries, the payment industry has been affected by digital transformation. The importance of digital transformation in the payment industry is very crucial. Because the payment industry is considered a leading industry in digital and emerging technologies, and the digitalization of other industries such as retail, health, and telecommunication, it also depends on the growth rate of digitalized payment systems. One of the technological innovations in service management is Field Service Management (FSM). Despite the widespread use of FSM in various industries such as petrochemical, health, maintenance, etc., this technology can also be recruited in the payment industry, transforming the payment industry into a more agile and efficient one. Accordingly, the present study pays close attention to the application of FSM in the payment industry. Given the importance of merchants' bargaining power in the payment industry, this study aims to use FSM in the digital transformation initiative with a targeted focus on providing real-time services to merchants. The research method consists of three parts. Firstly, conducting the review of past research, applications of FSM in the payment industry are considered. In the next step, merchants' benefits such as emotional, functional, economic, and social benefits in using FSM are identified using in-depth interviews and content analysis methods. The related business model in helping the payment industry transforming into a more agile and efficient industry is considered in the following step. The results revealed the 10 main pillars required to realize the digital transformation of payment systems using FSM.

Keywords: digital transformation, field service management, merchant support systems, payment industry

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Authors: Hae-Jun Lee, Ji-Sun Shin, Kyung-Tae Lee

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Potentilla species (Rosasease) have been used in traditional medicine to treat different ailment, disease or malady. In this study, we investigated the anti-inflammatory effects of ethanol extracts of NUTT (EPP) in lipopolysaccharide (LPS)-induced Raw 264.7 macrophages and septic mice. EPP suppressed LPS-induced nitric oxide (NO) and prostaglandin E2 (PGE2) production in LPS-induced Raw 264.7 macrophages. Consistent with these observations, EPP reduced the expressions of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) by downregulation of their promoter activities. EPP inhibited tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) at production and mRNA levels. Molecularly, EPP attenuated the LPS-induced transcriptional activity, and DNA-binding activity of nuclear factor-κB (NF-κB), and this was associated with a decrease of translocation and phosphorylation of p65 NF-κB by inhibiting the inhibitory κB-α (IκB-α) degradation and IκB kinase-α/β (IKK-α/β) phosphorylation. Furthermore, EPP suppressed the LPS-induced activation of activator protein-1 (AP-1) by reducing the expression of c-Fos and c-Jun in nuclear. EPP also reduced the phosphorylation of mitogen-activated protein kinase (MAPK), such as p38 MAPK and c-Jun N-terminal kinase/stress-activated protein kinase (JNK). In a sepsis model, pretreatment with EPP reduced the LPS-induced lethality. Collectively, these results suggest that the anti-inflammatory effects of EPP were associated with the suppression of NF-κB and AP-1 activation, and support its possible therapeutic role for the treatment of sepsis.

Keywords: anti-inflammation, activator protein-1, nuclear factor κB, Potentilla paradoxa Nutt

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Authors: Masoud Mohammadpour, Nima Yazdian, Radovan Kovacevic

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The Oil and Gas industries are vigorously looking for new ways to increase the efficiency of their pipeline constructions. Besides the other approaches, implementing of new welding methods for joining pipes can be the best candidate on this regard. Hybrid Laser Arc Welding (HLAW) with the capabilities of high welding speed, deep penetration, and excellent gap bridging ability can be a possible alternative method in pipeline girth welding. This paper investigates the feasibility of applying the HLAW to join ASTM A106-B as the mostly used piping material for transporting high-temperature and high-pressure fluids and gases. The experiments were carried out on six-inch diameter pipes with the wall thickness of 10mm. AWS ER 70 S6 filler wire with diameter of 1.2mm was employed. Relating to this welding procedure, characterization of welded samples such as hardness, tensile testing and Charpy V-notch testing were performed and the results will be reported in this paper. In order to have better understanding about the thermal history and the microstructural alterations caused by the welding heat cycle, a comprehensive Finite Element (FE) model was also conducted. The obtained results have shown that the Gas Metal Arc Welding (GMAW) procedure with the minimum number of 5 passes to complete the wall thickness, was reduced to only single pass by using the HLAW process with the welding time less than 15s.

Keywords: finite element modeling, high-temperature service, hybrid laser/arc welding, welding pipes

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Authors: Boumaraf Malak

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The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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Authors: Zoran Herceg, Višnja Stulić, Tomislava Vukušić, Anet Režek Jambrak

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High voltage electrical discharge is a new technology used for inactivation of pathogen microorganisms. Pathogen yeasts can cause diseases in humans if they are ingested. Nowadays new technologies have become the focus of researching all over the world. Rhodotorula is known as yeast that can cause diseases in humans. The aim of this study was to examine whether the high voltage electrical discharge treatment generated in gas phase has an influence on yeast reduction and recovery of Rhodotorula spp 74 in pure culture. Rhodotorula spp. 74 was treated in 200 mL of model solution. Treatment time (5 and 10 min), frequency (60 and 90 Hz) and injected gas (air or argon 99,99%) were changed. Titanium high voltage needle was used as high voltage electrode (positive polarity) through which air or argon was injected at the gas flow of 0.6 L/min. Experimental design and statistical analyses were obtained by Statgraphics Centurion software (StatPoint Technologies, Inc., VA, USA). The best inactivation rate 1.7 log10 reduction was observed after the 10 min of treatment, frequency of 90 Hz and injected air. Also with a longer treatment time inactivation rate was higher. After the 24 h recovery of treated samples was observed. Therefore the further optimization of method is needed to understand the mechanism of yeasts inactivation and cells recovery after the treatment. Acknowledgements: The authors would like to acknowledge the support by Croatian Science Foundation and research project ‘Application of electrical discharge plasma for preservation of liquid foods’.

Keywords: rhodotorula spp. 74, electrical discharge plasma, inactivation, stress response

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Authors: Joelle Hawa, Michael Gilding

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The role of interest as a driver of action has been an on-going debate in the sociological sciences. This paper shows evidence as to how economic actors frame their environment in terms of interests and goals to take action. It introduces the concept of 'dynamic actor compass', a cognitive tool that is socially contingent and allows economic actors to navigate their environment, evaluate the level of alignment of interests and goals with other players, and decide whether or not they are willing to rely on, collaborate or partner with others in the field. The paper builds on Kaplan’s model of framing contests and integrates Max Weber’s interests, and ideas construct as well as Beckert’s concept of fictional expectations. The author illustrates this conceptual framework in the case of MedTech entrepreneurs’ capital raising activities in Australia. The study adopts a grounded theory methodology, running in-depth interviews with 24 MedTech entrepreneurs in order to examine their decision-making processes and actions to finance their innovation trajectory. The findings show that participants take into account material and ideal interests and goals that they impose adapt or negotiate with other actors in their environment. These interactions affect the way MedTech entrepreneurs perceive other funders in the field, influencing their capital raising strategies.

Keywords: expectations, financing innovation, frames, goals, interest-oriented action, managerial cognition

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Authors: Onur Karaman, Ceren Karaman

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In this study, the adsorption of Methylene Blue (MB), a cationic dye, onto Orange Peel Derived Activated Carbon (OPAC) and chitosan(OPAC/Chitosan composite) composite (a low-cost absorbent) was carried out using a batch system. The composite was characterised using IR spectra, XRD, FESEM and Pore size studies. The effects of initial pH, adsorbent dose rate and initial dye concentration on the initial adsorption rate, capacity and dye removal efficiency were investigated. The Langmuir and Freundlich adsorption models were used to define the adsorption equilibrium of dye-adsorbent system mathematically and it was decided that the Langmuir model was more suitable to describe the adsorption equilibrium for the system. In addition, first order, second order and saturation type kinetic models were applied to kinetic data of adsorption and kinetic constants were calculated. It was concluded that the second order and the saturation type kinetic models defined the adsorption data more accurately. Finally, the evaluated thermodynamic parameters of adsorption show a spontaneous and exothermic behavior. Overall, this study indicates OPAC/Chitosan composite as an effective and low-cost adsorbent for the removal of MB dye from aqueous solutions.

Keywords: activated carbon, adsorption, chitosan, methylene blue, orange peel

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Authors: Dai Yizheng, Chen-Yang Zhang

Abstract:

As station-city integration has been widely accepted as a strategy for mixed-use development, a quantitative analysis of the functional characteristics of urban complexes based on station-city integration is urgently needed. Taking 15 railway stations in European, North American, and East Asian cities as the research objects, this study analyzes their functional proportion, functional positioning, and functional correlation with respect to four categories of functional facilities for both railway passenger flow and subway passenger flow. We found that (1) the functional proportion of urban complexes was mainly concentrated in three models: complementary, dominant, and equilibrium. (2) The mathematical model affected by the functional proportion was created to evaluate the functional positioning of an urban complex at three scales: station area, city, and region. (3) The strength of the correlation between the functional area and passenger flow was revealed via data analysis using Pearson’s correlation coefficient. Finally, the findings of this study provide a valuable reference for research on similar topics in other countries that are developing station-city integration.

Keywords: urban complex, station-city integration, mixed-use, function, quantitative analysis

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Authors: Zasha Romero, Roberto Trevino, Lin Wang, Elizabeth Alanis, Jesus Cuellar

Abstract:

Background: There is a strong relationship between low cardiorespiratory fitness (CRF) and high adiposity levels. The purpose of this study was to assess the effects of the Bienestar/Neema Coordinated School Health Program (BN CSHP) on the CRF of preschool children. Methods: This is a randomized cluster trial conducted in preschools of two school districts located along the Texas-Mexico border. Of 48 eligible schools, 28 were randomly selected (intervention, n=14; control, n=14). Family demographics and household health characteristics were collected from parents. CRF, as measured by the Progressive Anaerobic Capacity Endurance Run (PACER) fitness test, was collected from the children. A generalized linear mixed model (GLMM) was used to analyze the data. Results: Family demographics, household health characteristics, and children’s weight, obesity prevalence, and sedentary activity were similar among both treatment groups. After adjusting for covariates, the number of laps run by children in the control group increased by 23% (CI: -5% to 60%) per each data collection period compared with 53% (CI: 7% to 119%) in the intervention group. Conclusions: Children in the BN CSHP, compared to those in the control group, had a significantly higher increase in their CRF. This finding is important because of the health benefits of CRF in children.

Keywords: coordinated school health program, cardiorespiratory fitness, obesity, border health, preschool, physical education, movement

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Authors: Justin Orimisan Ijigbade

Abstract:

The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.

Keywords: climate variability, honeybees production, humidity, rainfall and temperature

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Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

Abstract:

Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

Procedia PDF Downloads 386

Authors: Ghunchq Khan

Abstract:

The increase in greenhouse gas (GHGs) emissions is a main environmental problem. Diverse human activities and inappropriate economic growth have stimulated a trade-off between economic growth and environmental deterioration all over the world. The impact of economic growth on the environment has received attention as global warming and environmental problems have become more serious. The focus of this study is on carbon footprints (production and consumption) and analyses the impact of GDP per capita on carbon footprints. A balanced panel of 99 countries from 2000 to 2016 is estimated by employing autoregressive distributed lags (ARDL) model – mean group (MG) and pooled mean group (PMG) estimators. The empirical results indicate that GDP per capita has a significant and positive impact in the short run but a negative effect in the long run on the carbon footprint of production in high-income countries by controlling trade openness, industry share, biological capacity, and population density. At the same time, GDP per capita has a significant and positive impact in both the short and long run on the carbon footprint of the production of non-high-income countries. The results also indicate that GDP per capita negatively impacts the carbon footprint of consumption for high-income countries; on the other hand, the carbon footprint of consumption increases as GDP per capita grows in non-high-income countries.

Keywords: ARDL, carbon footprint, economic growth, industry share, trade openness

Procedia PDF Downloads 67

Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

Abstract:

The river is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that need to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between the main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of the main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel, and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

Procedia PDF Downloads 144