Search results for: computational fluid dynamics.

Authors: Adolfo Martucci, Iulian Mihai

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By means of the expansion through a Conical Nozzle and the low pressure inside the Test Chamber, a large hypersonic stable flow takes place for a duration of up to 30 minutes. Downstream the Test Chamber, the diffuser has the function of reducing the flow velocity to subsonic values, and as a consequence, the temperature increases again. In order to cool down the flow, a heat exchanger is present at the end of the diffuser. The Vacuum System generates the necessary vacuum conditions for the correct hypersonic flow generation, and the DeNOx system, which follows the Vacuum System, reduces the nitrogen oxide concentrations created inside the plasma flow behind the limits imposed by Italian law. This very large, powerful, and complex facility allows researchers and engineers to reproduce entire re-entry trajectories of space vehicles into the atmosphere. One of the most important parameters for a hypersonic flowfield representative of re-entry conditions is the specific total enthalpy. This is the whole energy content of the fluid, and it represents how severe could be the conditions around a spacecraft re-entering from a space mission or, in our case, inside a hypersonic wind tunnel. It is possible to reach very high values of enthalpy (up to 45 MJ/kg) that, together with the large allowable size of the models, represent huge possibilities for making on-ground experiments regarding the atmospheric re-entry field. The maximum nozzle exit section diameter is 1950 mm, where values of Mach number very much higher than 1 can be reached. The specific total enthalpy is evaluated by means of a number of measurements, each of them concurring with its value and its uncertainty. The scope of the present paper is the evaluation of the sensibility of the uncertainty of the specific total enthalpy versus all the parameters and measurements involved. The sensors that, if improved, could give the highest advantages have so been individuated. Several simulations in Python with the METAS library and by means of Monte Carlo simulations are presented together with the obtained results and discussions about them.

Keywords: hypersonic, uncertainty, enthalpy, simulations

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Authors: Shobhit Mittal

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Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget

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Authors: T. Marinaci, C. Venuleo

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Different conceptualizations of disease affect patient care. This study aims to address this gap. It explores how health professionals conceptualize gambling problem, addiction and the goals of recovery process. In-depth, semi-structured, open-ended interviews were conducted with Italian psychologists, psychiatrists, general practitioners, and support staff (N= 114), working within health centres for the treatment of addiction (public health services or therapeutic communities) or medical offices. A Lexical Correspondence Analysis (LCA) was applied to the verbatim transcripts. LCA allowed to identify two main factorial dimensions, which organize similarity and dissimilarity in the discourses of the interviewed. The first dimension labelled 'Models of relationship with the problem', concerns two different models of relationship with the health problem: one related to the request for help and the process of taking charge and the other related to the identification of the psychopathology underlying the disorder. The second dimension, labelled 'Organisers of the intervention' reflects the dialectic between two ways to address the problem. On the one hand, they are the gambling dynamics and its immediate life-consequences to organize the intervention (whatever the request of the user is); on the other hand, they are the procedures and the tools which characterize the health service to organize the way the professionals deal with the user’ s problem (whatever it is and despite the specify of the user’s request). The results highlight how, despite the differences, the respondents share a central assumption: understanding gambling problem implies the reference to the gambler’s identity, more than, for instance, to the relational, social, cultural or political context where the gambler lives. A passive stance is attributed to the user, who does not play any role in the definition of the goal of the intervention. The results will be discussed to highlight the relationship between professional models and users’ ways to understand and deal with the problems related to gambling.

Keywords: cultural models, health professionals, intervention models, problem gambling

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.

Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing

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Authors: Ahmadreza Ebadati, Asaad Y. Shamseldin, Amin Ghadirian

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Seawall geometry plays a crucial role in mitigating wave impacts, though detailed exploration of its manipulation is limited. This study delves into the effects of varying cross-shore seawall geometry on the dynamics of wave impacts, with a particular focus on vertical seawalls. Inspired by foundational insights linking seawall shape to hydraulic efficiency, this investigation centres on how alterations in seawall geometry can influence wave energy dissipation and subsequent wave impacts. The study investigates the 2D interaction of regular waves with a period of 2.1s with a vertical seawall and berm featuring small-scale cross-shore protrusions and recesses. Utilising OpenFOAM® simulations and a k-ω SST turbulence model, this investigation compares results to a base case simulation, which is partially calibrated with experimental data from a flume study. The analysis evaluates various geometric modifications, specifically interchanged protrusions and recesses at different heights and orientations along the seawall. Findings suggest that specific configurations, such as interchanged protrusions and recesses, can mitigate initial impact forces, while certain arrangements may intensify subsequent impacts. Key insights include the identification of geometry configurations that can effectively reduce the force impulse of slamming waves on coastal structures and potentially decrease the frequency and cost of seawall maintenance. This research contributes to the field by advancing the understanding of how seawall geometry influences wave forces and by providing actionable insights for the design of more resilient seawall structures. Further exploration of seawall geometry variation is recommended, advocating additional case studies to optimise designs tailored to specific coastal environments.

Keywords: seawall geometry, wave impact loads, numerical simulation, coastal engineering, wave-structure interaction

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Authors: E. M. Rifqi Wilda Pradana, Bagus Bayu Prabowo, Meida Riski Pujiyati, Efraim Maykhel Hagana Ginting, Virgiawan Arya Hangga Reksa

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The VLF (Very Low Frequency) method is an electromagnetic method that uses low frequencies between 10-30 KHz which results in a fairly deep penetration. In this study, the VLF method was used for zonation of disaster-prone areas by identifying geological structures in the form of faults. Data acquisition was carried out in Trimulyo Region, Jetis District, Bantul Regency, Special Region of Yogyakarta, Indonesia with 8 measurement paths. This study uses wave transmitters from Japan and Australia to obtain Tilt and Elipt values that can be used to create RAE (Rapat Arus Ekuivalen or Current Density) sections that can be used to identify areas that are easily crossed by electric current. This section will indicate the existence of a geological structure in the form of faults in the study area which is characterized by a high RAE value. In data processing of VLF method, it is obtained Tilt vs Elliptical graph and Moving Average (MA) Tilt vs Moving Average (MA) Elipt graph of each path that shows a fluctuating pattern and does not show any intersection at all. Data processing uses Matlab software and obtained areas with low RAE values that are 0%-6% which shows medium with low conductivity and high resistivity and can be interpreted as sandstone, claystone, and tuff lithology which is part of the Semilir Formation. Whereas a high RAE value of 10% -16% which shows a medium with high conductivity and low resistivity can be interpreted as a fault zone filled with fluid. The existence of the fault zone is strengthened by the discovery of a normal fault on the surface with strike N550W and dip 630E at coordinates X= 433256 and Y= 9127722 so that the activities of residents in the zone such as housing, mining activities and other activities can be avoided to reduce the risk of natural disasters.

Keywords: current density, faults, very low frequency, zonation

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Authors: Omnia M.Kandil, Noha M. F. Hassan, Doaa Sedky, Hatem A. Shalaby, Heba M. Ashry, Nadia M. T. Abu El Ezz, Sahar M. Kandeel, Mohamed S. Abdelfattah Ying L, Ebtesam M. Al-Olayan

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The cestode, Taenia saginata is a zoonotic tapeworm that it’s larval stage which known as Cysticercus bovis cause cyst formation in cattle’s organs such as heart, lung, liver, tongue, esophagus and diaphragm muscle, despite the infected cattle may show no clinical signs. In view of considerable interest in developing cysticidal drugs including those from medicinal plants, because of their consideration as eco-friendly and biodegradable as well as having multiple bioactive compounds that may translate to multiple mechanisms in killing the parasites. This study was achieved to evaluate, for the first time, the efficacy of methanolic extract of Balanites aegyptiaca fruits and Moringa oleifera seeds against metacestode larval stage of the cestode Taenia saginata in BALB/c mice compared with commonly used anthelmintic albendazole and assigning the level of tumor necrosis factor (TNF-α) to monitor immune and inflammatory response of experimentally infected animals. The results revealed a marked decrease in the numbers of cysticerci found in all treated mice groups and up to 88% reduction was achieved in the B. aegyptiaca treated group; higher than that was recorded in both M. oleifera (72.23%) and albendazole treated ones (80.56%). The cysts of the treated groups were smaller of the control one. Besides, the mean concentration of TNF-α following treatment with Balanites and Moringa extracts, was higher but not significant difference than that in the untreated infected control one (P<0.05), evidence for inflammation and cyst damage. It can be concluded that the in vivo efficacy of M. oleifera extract was comparable to a commercial anthelmintic, and the B. aegyptiaca extract was superior in the reduction of cysticerci numbers.

Keywords: Balanites aeggyptica, Moringa oleifera, cysticercosis, BALB/C mice

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Authors: Debashree Ghosh, Preethi Sridhar, Shloka Atul Dhavle

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The judicious and economic consumption of energy for sustainable growth and development is nowadays a thing of primary importance; Phase Change Materials (PCM) provide an ingenious option of storing energy in the form of Latent Heat. Energy storing mechanism incorporating phase change material increases the efficiency of the process by minimizing the difference between supply and demand; PCM heat exchangers are used to storing the heat or non-convectional energy within the PCM as the heat of fusion. The experimental study evaluates the effect of thermo-physical properties, variation in inlet temperature, and flow rate on charging period of a coiled heat exchanger. Secondly, a numerical study is performed on a PCM double pipe heat exchanger packed with two different PCMs, namely, RT50 and Fatty Acid, in the annular region. In this work, the simulation of charging of paraffin wax (RT50) using water as high-temperature fluid (HTF) is performed. Commercial software Ansys-Fluent 15 is used for simulation, and hence charging of PCM is studied. In the Enthalpy-porosity model, a single momentum equation is applicable to describe the motion of both solid and liquid phases. The details of the progress of phase change with time are presented through the contours of melt-fraction, temperature. The velocity contour is shown to describe the motion of the liquid phase. The experimental study revealed that paraffin wax melts with almost the same temperature variation at the two Intermediate positions. Fatty acid, on the other hand, melts faster owing to greater thermal conductivity and low melting temperature. It was also observed that an increase in flow rate leads to a reduction in the charging period. The numerical study also supports some of the observations found in the experimental study like the significant dependence of driving force on the process of melting. The numerical study also clarifies the melting pattern of the PCM, which cannot be observed in the experimental study.

Keywords: latent heat storage, charging period, discharging period, coiled heat exchanger

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Authors: N. Harun, E. E. Masiren, W. H. W. Ibrahim, F. Adam

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Amine absorption process is an approach for mitigation of CO2 from flue gas that produces from power plant. This process is the most common system used in chemical and oil industries for gas purification to remove acid gases. On the challenges of this process is high energy requirement for solvent regeneration to release CO2. In the past few years, mixed alkanolamines have received increasing attention. In most cases, the mixtures contain N-methyldiethanolamine (MDEA) as the base amine with the addition of one or two more reactive amines such as PZ. The reason for the application of such blend amine is to take advantage of high reaction rate of CO2 with the activator combined with the advantages of the low heat of regeneration of MDEA. Several experimental and simulation studies have been undertaken to understand this process using blend MDEA/PZ solvent. Despite those studies, the mechanism of CO2 absorption into the aqueous MDEA is not well understood and available knowledge within the open literature is limited. The aim of this study is to investigate the intermolecular interaction of the blend MDEA/PZ using Molecular Dynamics (MD) simulation. MD simulation was run under condition 313K and 1 atm using NVE ensemble at 200ps and NVT ensemble at 1ns. The results were interpreted in term of Radial Distribution Function (RDF) analysis through two system of interest i.e binary and tertiary. The binary system will explain the interaction between amine and water molecule while tertiary system used to determine the interaction between the amine and CO2 molecule. For the binary system, it was observed that the –OH group of MDEA is more attracted to water molecule compared to –NH group of MDEA. The –OH group of MDEA can form the hydrogen bond with water that will assist the solubility of MDEA in water. The intermolecular interaction probability of –OH and –NH group of MDEA with CO2 in blended MDEA/PZ is higher than using single MDEA. This findings show that PZ molecule act as an activator to promote the intermolecular interaction between MDEA and CO2.Thus, blend of MDEA with PZ is expecting to increase the absorption rate of CO2 and reduce the heat regeneration requirement.

Keywords: amine absorption process, blend MDEA/PZ, CO2 capture, molecular dynamic simulation, radial distribution function

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Authors: Kawsar Ahmed, Hong Wang

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The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy.

Keywords: causal mediation analysis, directed acyclic graphs, tobacco price policy, sensitivity analysis, pathway estimation

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Authors: A. C. Kumbharkhane

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Time domain dielectric relaxation microwave spectroscopy (TDRMS) is a term used to describe a technique of observing the time dependant response of a sample after application of time dependant electromagnetic field. A TDRMS probes the interaction of a macroscopic sample with a time dependent electrical field. The resulting complex permittivity spectrum, characterizes amplitude (voltage) and time scale of the charge-density fluctuations within the sample. These fluctuations may arise from the reorientation of the permanent dipole moments of individual molecules or from the rotation of dipolar moieties in flexible molecules, like polymers. The time scale of these fluctuations depends on the sample and its relative relaxation mechanism. Relaxation times range from some picoseconds in low viscosity liquids to hours in glasses, Therefore the TDRS technique covers an extensive dynamical process. The corresponding frequencies range from 10-4 Hz to 1012 Hz. This inherent ability to monitor the cooperative motion of molecular ensemble distinguishes dielectric relaxation from methods like NMR or Raman spectroscopy, which yield information on the motions of individual molecules. Recently, we have developed and established the TDR technique in laboratory that provides information regarding dielectric permittivity in the frequency range 10 MHz to 30 GHz. The TDR method involves the generation of step pulse with rise time of 20 pico-seconds in a coaxial line system and monitoring the change in pulse shape after reflection from the sample placed at the end of the coaxial line. There is a great interest to study the dielectric relaxation behaviour in liquid systems to understand the role of hydrogen bond in liquid system. The intermolecular interaction through hydrogen bonds in molecular liquids results in peculiar dynamical properties. The dynamics of hydrogen-bonded liquids have been studied. The theoretical model to explain the experimental results will be discussed.

Keywords: microwave, time domain reflectometry (TDR), dielectric measurement, relaxation time

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Authors: Yaara Oppenheimer-Shaanan, Nimrod Nachmias, Marina Campos Rocha, Neta Schlezinger, Noam Dotan, Asaf Levy

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Fusarium oxysporum, a fungus that attacks a broad range of plants and can cause infections in humans, operates across different kingdoms. This pathogen encounters varied conditions, such as temperature, pH, and nutrient availability, in plant and human hosts. The Fusarium oxysporum species complex, pervasive in soils globally, can affect numerous plants, including key crops like tomatoes and bananas. Controlling Fusarium infections can involve biocontrol agents that hinder the growth of harmful strains. Our research developed a computational method to identify toxin domains within a vast number of microbial genomes, leading to the discovery of nine distinct toxins capable of killing bacteria and fungi, including Fusarium. These toxins appear to function as enzymes, causing significant damage to cellular structures, membranes and DNA. We explored biological control using bacteria that produce polymorphic toxins, finding that certain bacteria, non-pathogenic to plants, offer a safe biological alternative for Fusarium management, as they did not harm macrophage cells or C. elegans. Additionally, we elucidated the 3D structures of two toxins with their protective immunity proteins, revealing their function as unique DNases. These potent toxins are likely instrumental in microbial competition within plant ecosystems and could serve as biocontrol agents to mitigate Fusarium wilt and related diseases.

Keywords: microbial toxins, antifungal, Fusarium oxysporum, bacterial-fungal intreactions

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Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

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The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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Authors: Malgorzata Krysiak, Anna Wegrzyn, Maciej Garstka, Radoslaw Mazur

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Under constantly fluctuating environmental conditions, the thylakoid membrane protein network evolved the ability to dynamically respond to changing biotic and abiotic factors. One of the most important protective mechanism is rearrangement of the chlorophyll-protein (CP) complexes, induced by protein phosphorylation. In a temperate climate, low temperature is one of the abiotic stresses that heavily affect plant growth and productivity. The aim of this study was to determine the role of LHCII antenna complex phosphorylation in the dark-chilling response. The study included an experimental model based on dark-chilling at 4 °C of detached chilling sensitive (CS) runner bean (Phaseolus coccineus L.) and chilling tolerant (CT) garden pea (Pisum sativum L.) leaves. This model is well described in the literature as used for the analysis of chilling impact without any additional effects caused by light. We examined changes in thylakoid membrane protein phosphorylation, interactions between phosphorylated LHCII (P-LHCII) and CP complexes, and their impact on the dynamics of photosystem II (PSII) under dark-chilling conditions. Our results showed that the dark-chilling treatment of CS bean leaves induced a substantial increase of phosphorylation of LHCII proteins, as well as changes in CP complexes composition and their interaction with P-LHCII. The PSII photochemical efficiency measurements showed that in bean, PSII is overloaded with light energy, which is not compensated by CP complexes rearrangements. On the contrary, no significant changes in PSII photochemical efficiency, phosphorylation pattern and CP complexes interactions were observed in CT pea. In conclusion, our results indicate that different responses of the LHCII phosphorylation to chilling stress take place in CT and CS plants, and that kinetics of LHCII phosphorylation and interactions of P-LHCII with photosynthetic complexes may be crucial to chilling stress response. Acknowledgments: presented work was financed by the National Science Centre, Poland grant No.: 2016/23/D/NZ3/01276

Keywords: LHCII, phosphorylation, chilling stress, pea, runner bean

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Authors: Robert Prohaska, Arnaud Konan, Kenneth Kelly, Adam Ragatz, Adam Duran

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In an effort to evaluate the in-use performance of electrified Power Take-off (PTO) usage on bucket utility trucks operating under real-world conditions, data from 20 medium- and heavy-duty vehicles operating in California, USA were collected, compiled, and analyzed by the National Renewable Energy Laboratory's (NREL) Fleet Test and Evaluation team. In this paper, duty-cycle statistical analyses of class 5, medium-duty quick response trucks and class 8, heavy-duty material handler trucks are performed to examine and characterize vehicle dynamics trends and relationships based on collected in-use field data. With more than 100,000 kilometers of driving data collected over 880+ operating days, researchers have developed a robust methodology for identifying PTO operation from in-field vehicle data. Researchers apply this unique methodology to evaluate the performance and utilization of the conventional and electric PTO systems. Researchers also created custom representative drive-cycles for each vehicle configuration and performed modeling and simulation activities to evaluate the potential fuel and emissions savings for hybridization of the tractive driveline on these vehicles. The results of these analyses statistically and objectively define the vehicle dynamic and kinematic requirements for each vehicle configuration as well as show the potential for further system optimization through driveline hybridization. Results are presented in both graphical and tabular formats illustrating a number of key relationships between parameters observed within the data set that relates specifically to medium- and heavy-duty utility vehicles operating under real-world conditions.

Keywords: drive cycle, heavy-duty (HD), hybrid, medium-duty (MD), PTO, utility

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Authors: K. R. Sreenivas, Shaurya Kaushal

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After sunset, under calm & clear-sky nocturnal conditions, the air layer near the surface containing aerosols cools through radiative processes to the upper atmosphere. Due to this cooling, surface air-layer temperature can fall 2-6 degrees C lower than the ground-surface temperature. This unstable convection layer, on the top, is capped by a stable inversion-boundary layer. Radiative divergence, along with the convection within the surface layer, governs the vertical transport of heat and moisture. Micro-physics in this layer have implications for the occurrence and growth of the fog layer. This particular configuration, featuring a convective mixed layer beneath a stably stratified inversion layer, exemplifies a classic case of penetrative convection. In this study, we conduct numerical simulations of the penetrative convection phenomenon within the nocturnal atmospheric surface layer and elucidate its relevance to the dynamics of fog layers. We employ field and laboratory measurements of aerosol number density to model the strength of the radiative cooling. Our analysis encompasses horizontally averaged, vertical profiles of temperature, density, and heat flux. The energetic incursion of the air from the mixed layer into the stable inversion layer across the interface results in entrainment and the growth of the mixed layer, modeling of which is the key focus of our investigation. In our research, we ascertain the appropriate length scale to employ in the Richardson number correlation, which allows us to estimate the entrainment rate and model the growth of the mixed layer. Our analysis of the mixed layer and the entrainment zone reveals a close alignment with previously reported laboratory experiments on penetrative convection. Additionally, we demonstrate how aerosol number density influences the growth or decay of the mixed layer. Furthermore, our study suggests that the presence of fog near the ground surface can induce extensive vertical mixing, a phenomenon observed in field experiments.

Keywords: inversion layer, penetrative convection, radiative cooling, fog occurrence

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Marianna Ciaccia, Gennaro Agrimi, Isabella Pisano, Maurizio Bettiga, Silvia Rapacioli, Giulia Mensa, Monica Marzagalli

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Objective: Untargeted metabolomic analysis of extracellular metabolites is a powerful approach that focuses on comprehensively profiling in the extracellular space. In this study, we applied extracellular metabolomic analysis to investigate the metabolism of two probiotic microorganisms with health benefits that extend far beyond the digestive tract and the immune system. Methods: Analytical techniques employed in extracellular metabolomic analysis encompass various technologies, including mass spectrometry (MS), which enables the identification of metabolites present in the fermentation media, as well as the comparison of metabolic profiles under different experimental conditions. Multivariate statistical analysis techniques like principal component analysis (PCA) or partial least squares-discriminant analysis (PLS-DA) play a crucial role in uncovering metabolic signatures and understanding the dynamics of metabolic networks. Results: Different types of supernatants from fermentation processes, such as dairy-free, not dairy-free media and media with no cells or pasteurized, were subjected to metabolite profiling, which contained a complex mixture of metabolites, including substrates, intermediates, and end-products. This profiling provided insights into the metabolic activity of the microorganisms. The integration of advanced software tools has facilitated the identification and characterization of metabolites in different fermentation conditions and microorganism strains. Conclusions: In conclusion, untargeted extracellular metabolomic analysis, combined with software tools, allowed the study of the metabolites consumed and produced during the fermentation processes of probiotic microorganisms. Ongoing advancements in data analysis methods will further enhance the application of extracellular metabolomic analysis in fermentation research, leading to improved bioproduction and the advancement of sustainable manufacturing processes.

Keywords: biotechnology, metabolomics, lactic bacteria, probiotics, postbiotics

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Authors: Atousa Ataieyan, Salvador A. Gomez-Lopera, Gennaro Sepede

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Today, due to the growing urban population and consequently, the increasing water demand in cities, the amount of contaminants entering the water resources is increasing. This can impose harmful effects on the quality of the downstream water. Therefore, predicting the concentration of discharged pollutants at different times and distances of the interested area is of high importance in order to carry out preventative and controlling measures, as well as to avoid consuming the contaminated water. In this paper, the concentration distribution of an injected conservative pollutant in a square reservoir containing four symmetric blocks and three sources using Finite Volume Method (FVM) is simulated. For this purpose, after estimating the flow velocity, classical Advection-Diffusion Equation (ADE) has been discretized over the studying domain by Backward Time- Backward Space (BTBS) scheme. Then, the discretized equations for each node have been derived according to the initial condition, boundary conditions and point contaminant sources. Finally, taking into account the appropriate time step and space step, a computational code was set up in MATLAB. Contaminant concentration was then obtained at different times and distances. Simulation results show how using BTBS differentiating scheme and FVM as a numerical method for solving the partial differential equation of transport is an appropriate approach in the case of two-dimensional contaminant transfer in an advective-diffusive flow.

Keywords: BTBS differentiating scheme, contaminant concentration, finite volume, mass transfer, water pollution

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Authors: Sabir Khan, Sajjad Hussain, Ademar Wong, Maria Del Pilar Taboada Sotomayor

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The present work aims to develop magnetic molecularly imprinted polymers (MMIPs) for determination of a selected pesticide (ametryne) using high-performance liquid chromatography (HPLC). Computational simulation can assist the choice of the most suitable monomer for the synthesis of polymers. The (MMIPs) were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using 2-vinylpyradine as functional monomer, ethylene-glycol-dimethacrylate (EGDMA) is a cross-linking agent and 2,2-Azobisisobutyronitrile (AIBN) used as radical initiator. Magnetic non-molecularly imprinted polymer (MNIPs) was also prepared under the same conditions without analyte. The MMIPs were characterized by scanning electron microscopy (SEM), Brunauer, Emmett and Teller (BET) and Fourier transform infrared spectroscopy (FTIR). Pseudo first-order and pseudo second order model were applied to study kinetics of adsorption and it was found that adsorption process followed the pseudo-first-order kinetic model. Adsorption equilibrium data was fitted to Freundlich and Langmuir isotherms and the sorption equilibrium process was well described by Langmuir isotherm mode. The selectivity coefficients (α) of MMIPs for ametryne with respect to atrazine, ciprofloxacin and folic acid were 4.28, 12.32 and 14.53 respectively. The spiked recoveries ranged between 91.33 and 106.80% were obtained. The results showed high affinity and selectivity of MMIPs for pesticide ametryne in the food samples.

Keywords: molecularly imprinted polymer, pesticides, magnetic nanoparticles, adsorption

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Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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Authors: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang

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The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.

Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Hsiao-ting Lin

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This paper analyzes the history of Taiwan’s secret program to develop its nuclear weapons during the Cold War. In July 1971, US President Richard Nixon shocked the world when he announced that his national security adviser Henry Kissinger had made a secret trip to China and that he himself had accepted an invitation to travel to Beijing. This huge breakthrough in the US-PRC relationship was followed by Taipei’s loss of political legitimacy and international credibility as a result of its UN debacle in the fall that year. Confronted with the Nixon White House’s opening to the PRC, leaders in Taiwan felt being betrayed and abandoned, and they were obliged to take countermeasures for the sake of national interest and regime survival. Taipei’s endeavor to create an effective nuclear program, including the possible development of nuclear weapons capabilities, fully demonstrates the government’s resolution to pursue its own national policy, even if such a policy was guaranteed to undermine its relations with the United States. With hindsight, Taiwan’s attempt to develop its own nuclear weapons did not succeed in sabotaging the warming of US-PRC relations. Worse, it was forced to come to a full stop when, in early 1988, the US government pressured Taipei to close related facilities and programs on the island. However, Taiwan’s abortive attempt to develop its nuclear capability did influence Washington’s and Beijing’s handling of their new relationship. There did develop recognition of a common American and PRC interest in avoiding a nuclearized Taiwan. From this perspective, Beijing’s interests would best be served by allowing the island to remain under loose and relatively benign American influence. As for the top leaders on Taiwan, such a policy choice demonstrated how they perceived the shifting dynamics of international politics in the 1960s and 1970s and how they struggled to break free and pursue their own independent national policy within the rigid framework of the US-Taiwan alliance during the Cold War.

Keywords: taiwan, richard nixon, nuclear program, chiang Kai-shek, chiang ching-kuo

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Ali M. Al-Shaery

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The purpose of this paper is to address the functions of sustainability dimensions in city information modelling and to present the required sustainability criteria that support establishing a sustainable planning framework for enhancing existing cities and developing future smart cities. The paper is divided into two sections. The first section is based on the examination of a wide and extensive array of cross-disciplinary literature in the last decade and a half to conceptualize the terms ‘sustainable’ and ‘smart city,' and map their associated criteria to city information modelling. The second section is based on analyzing two approaches relating to city information modelling, namely statistical and dynamic approaches, and their suitability in the development of cities’ action plans. The paper argues that the use of statistical approaches to embedding sustainability dimensions in city information modelling have limited value. Despite the popularity of such approaches in addressing other dimensions like utility and service management in development and action plans of the world cities, these approaches are unable to address the dynamics across various city sectors with regards to economic, environmental and social criteria. The paper suggests an integrative dynamic and cross-disciplinary planning approach to embedding sustainability dimensions in city information modelling frameworks. Such an approach will pave the way towards optimal planning and implementation of priority actions of projects and investments. The approach can be used to achieve three main goals: (1) better development and action plans for world cities (2) serve the development of an integrative dynamic and cross-disciplinary framework that incorporates economic, environmental and social sustainability criteria and (3) address areas that require further attention in the development of future sustainable and smart cities. The paper presents an innovative approach for city information modelling and a well-argued, balanced hierarchy of sustainability criteria that can contribute to an area of research which is still in its infancy in terms of development and management.

Keywords: information modelling, smart city, sustainable city, sustainability dimensions, sustainability criteria, city development planning

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Authors: Jonghyuk Yoon, Jongil Yoon, Seong-Gyo Chung

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In many kinds of industries which usually need a large amount of power, an axial piston pump has been widely used as a main power source of a hydraulic system. The axial piston pump is a type of positive displacement pump that has several pistons in a circular array within a cylinder block. As the cylinder block and pistons start to rotate, since the exposed ends of the pistons are constrained to follow the surface of the swashed plate, the pistons are driven to reciprocate axially and then a hydraulic power is produced. In the present study, a numerical simulation which has three dimensional full model of the axial piston pump was carried out using a commercial CFD code (Ansys CFX 14.5). In order to take into consideration motion of compression and extension by the reciprocating pistons, the moving boundary conditions were applied as a function of the rotation angle to that region. In addition, this pump using hydraulic oil as working fluid is intentionally designed as a small amount of oil leaks out in order to lubricate moving parts. Since leakage could directly affect the pump efficiency, evaluation of effect of oil-leakage is very important. In order to predict the effect of the oil leakage on the pump efficiency, we considered the leakage between piston-shoe and swash-plate by modeling cylindrical shaped-feature at the end of the cylinder. In order to validate the numerical method used in this study, the numerical results of the flow rate at the discharge port are compared with the experimental data, and good agreement between them was shown. Using the validated numerical method, the effect of the discharge pressure was also investigated. The result of the present study can be useful information of small axial piston pump used in many different manufacturing industries. Acknowledgement: This research was financially supported by the “Next-generation construction machinery component specialization complex development program” through the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT).

Keywords: axial piston pump, CFD, discharge pressure, hydraulic system, moving boundary condition, oil leaks

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Boda Sreenivas, Lyathakula Ravindranath, Kanugula Srishailam, Byru Venkatram Reddy

Abstract:

Extensive research into the optimized structure and molecular properties of 3-Flouro-2-methylbenzoicacid(FMB), 3-Chloro-2-methoxybenzoicacid (CMB), and 3-Bromo-2-methylbenzoicacid (BMB) was carried out using FT-IR, FT-Raman and UV-Visible spectra, as well as theoretically using the DFT approach with B3LYPfunctional in conjunction with 6-311++G(d,p) basis set. The optimized structure was determined by evaluating torsional scans about free rotation bonds. Structure parameters, harmonic vibrational frequencies, potential energy distribution(PED), and infrared and Raman intensities were computed. The computational results from the DFT approach, such asFT-IR, FT-Raman, and UV-Visible spectra, were compared with the experimental results and found good agreement. Observed and calculated frequencies agreed with an rms error of 8.42, 6.60, and 6.95 cm-1 for FMB, CMB, and BMB, respectively. Unambiguous vibrational assignments were made for all fundamentals using PED and eigenvectors. The electronic HOMO-LUMO, H-bonding, and strong conjugative interactions across different molecular entities are discussed using experimental and simulated Ultraviolet-Visible spectra. The title molecules' molecular properties such as dipole moment, mean polarizability, and first-order hyperpolarizability, were calculated to study their non-linear optical (NLO) behavior. The chemical reactivity descriptors and mapped electrostatic surface potential (MESP) were also evaluated. Natural bond orbital (NBO) analysis was used to examine the stability of molecules resulting from hyperconjugative interactions and charge delocalization.

Keywords: ftir/raman spectra, DFT, NLO, homo-lumo, NBO, halogenated benzoic acids

Procedia PDF Downloads 76