Search results for: disintegration time

Authors: Simin Asadollahi, Amir H. Soruri, Ali Moghimi

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Nowadays, salad oils are used in many countries around the world. Therefore, it is of great importance to ensure the safety of these food products which are usually packaged in Polyethylene terephthalate (PET) bottles and come on the market. This study investigated the effects of storage time and temperature on the migration rate of phthalate compounds from PET bottle to salad oil. In more detail, migration rate of bis (2-ethylhexyl) phthalate from bottles to salad oil samples was measured in 1st, the 30th, and the 60th days of storage at a temperature of either 20 or 40 °C. At both storage temperatures, an increase in the storage time led to a statistically significant increase in the migration rate of phthalate compounds (p<.01). Regarding this, the highest migration rate occurred after 60 days of storage in to the samples. Furthermore, it was revealed bis (2-ethylhexyl) phthalate had a higher migration rate at 40 °C than at 20 °C which showed that an increase in the storage temperature would lead to an increase in the migration rate. The highest migration rate occurred in relation to salad oil stored at 40 °C and after 60 days of storage.

Keywords: salad oil, migration rate, polyethylene terephthalate, bis (2-ethylhexyl) phthalate

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Authors: Tiantian Li, Lusheng Wang, Zhaohui Zhan, Daming Zhu

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In this paper, we propose two string problems, and study algorithms and complexity of various versions for those problems. Let S = {s₁, s₂, . . . , sₘ} be a set of m strings. A common substring of S is a substring appearing in every string in S. Given a set of m strings S = {s₁, s₂, . . . , sₘ} and a positive integer k, we want to find a set C of k common substrings of S such that the k common substrings in C appear in the same order and have no overlap among the m input strings in S, and the total length of the k common substring in C is maximized. This problem is referred to as the longest total length of k common substrings from m input strings (LCSS(k, m) for short). The other problem we study here is called the longest total length of a set of common substrings with length more than l from m input string (LSCSS(l, m) for short). Given a set of m strings S = {s₁, s₂, . . . , sₘ} and a positive integer l, for LSCSS(l, m), we want to find a set of common substrings of S, each is of length more than l, such that the total length of all the common substrings is maximized. We show that both problems are NP-hard when k and m are variables. We propose dynamic programming algorithms with time complexity O(k n₁n₂) and O(n₁n₂) to solve LCSS(k, 2) and LSCSS(l, 2), respectively, where n1 and n₂ are the lengths of the two input strings. We then design an algorithm for LSCSS(l, m) when every length > l common substring appears once in each of the m − 1 input strings. The running time is O(n₁²m), where n1 is the length of the input string with no restriction on length > l common substrings. Finally, we propose a fixed parameter algorithm for LSCSS(l, m), where each length > l common substring appears m − 1 + c times among the m − 1 input strings (other than s1). In other words, each length > l common substring may repeatedly appear at most c times among the m − 1 input strings {s₂, s₃, . . . , sₘ}. The running time of the proposed algorithm is O((n12ᶜ)²m), where n₁ is the input string with no restriction on repeats. The LSCSS(l, m) is proposed to handle whole chromosome sequence alignment for different strains of the same species, where more than 98% of letters in core regions are identical.

Keywords: dynamic programming, algorithm, common substrings, string

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Authors: Mahdy Elhusseiny, Richard Gearhart, Mariam Alyammahi

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In this study we analyse the impact of a number of major macroeconomic variables on industry-specific excess rates of return. In later specifications, we include time and recession fixed effects, to potentially capture time-specific trends that may have been changing over our panel. We have a number of results that bear mentioning. Seasonal and temporal factors found to have very large role in sector-specific excess returns. Increases in M1(money supply) decreases bank, insurance, real estate, and telecommunications, while increases industrial and transportation excess returns. The results indicate that the market return increases every sector-specific rate of return. The 2007 to 2009 recession significantly reduced excess returns in the bank, real estate, and transportation sectors.

Keywords: macroeconomic factors, industry returns, fixed effects, temporal factors

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Authors: Samira Khalil, Adib Saad, Malek Ali

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The aim of this research is to determine fish species belonging to the order Pleuronectiforme fish found in Syrian marine water confirm or deny the continuity of the previously registered species, and record the unregistered species that appeared during this research for the first time. The research was carried out in the Laboratory of Marine Sciences, Faculty of Agriculture (Tishreen University); fish samples were collected periodically (bi-monthly) from fishermen in landing areas along the Syrian coast caught from depths (3m to 700m), using various mediums. An appropriate hand is available to fishermen on the Syrian coast (cliff bottom, fixed nets, enclosure nets, shelf nest, and manual disposal network; 451 individuals were captured and studied during the research period. During this study, it was found that the Syrian water includes 15 species, including one species recorded for the first time. On the eastern coast of the Mediterranean, it is Pegusa impar.

Keywords: pleuronectiformes, Syrian coast, flatfish, mediterranean

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Authors: Eirini Arvanitaki

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The popular romance novel has the ability to withstand the test of time by carefully adjusting its contents to the twenty-first century and modern society. At the same time, it manages to preserve unaltered its traditional foundations (heteronormativity, heterosexual love, monogamy). This paper focuses on the projection of the hero’s masculinity in a selection of post-millennial popular romance narratives and attempts to discover if, and to what extent, this projection reinforces or challenges patriarchal ideas about gender. In the majority of these narratives, the hero is often presented as a hegemonic alpha male. However, hegemonic masculinity is not a fixed concept. Rather, it is subject to continuous change, which allows for the emergence of various dominant masculinities. With this in mind, and through a close textual analysis approach and a gender reading of romance narratives, the paper suggests that to a certain extent, the romance hero could be described as a platform onto which different forms of dominant masculinity are displayed and highlights that these masculinities do not necessarily clash, depend on, or function as a prerequisite for each other.

Keywords: gender, literary projections, masculinity, twenty-first century popular romance narratives

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Authors: Lei Qi, Rongxin Yan, Lichen Sun

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With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.

Keywords: acoustic sensor array, spacecraft, damage assessment, leakage location

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Authors: Fatih Tarlak

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Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

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Authors: Jorge Gonzalez-Camus

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In this work is proved the existence of at least one minimal and maximal mild solutions to the Cauchy problem, for fractional evolution equation of neutral type, involving a general kernel. An operator A generating a resolvent family and integral resolvent family on a Banach space X and a kernel belonging to a large class appears in the equation, which covers many relevant cases from physics applications, in particular, the important case of time - fractional evolution equations of neutral type. The main tool used in this work was the Kuratowski measure of noncompactness and fixed point theorems, specifically Darbo-type, and an iterative method of lower and upper solutions, based in an order in X induced by a normal cone P. Initially, the equation is a Cauchy problem, involving a fractional derivate in Caputo sense. Then, is formulated the equivalent integral version, and defining a convenient functional, using the theory of resolvent families, and verifying the hypothesis of the fixed point theorem of Darbo type, give us the existence of mild solution for the initial problem. Furthermore, the existence of minimal and maximal mild solutions was proved through in an iterative method of lower and upper solutions, using the Azcoli-Arzela Theorem, and the Gronwall’s inequality. Finally, we recovered the case derivate in Caputo sense.

Keywords: fractional evolution equations, Volterra integral equations, minimal and maximal mild solutions, neutral type equations, non-local in time equations

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Authors: Chanhoe Kang, Changhyun Lee, Seock-Hee Jun, Yeong-Tae Oh

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Offshore floating structure under the various environmental conditions maintains a fixed position by mooring system. Environmental conditions, vessel motions and mooring loads are applied to mooring lines as the dynamic tension. Because global responses of mooring system in deep water are specified as wave frequency and low frequency response, they should be calculated from the time-domain analysis due to non-linear dynamic characteristics. To take into account all mooring loads, environmental conditions, added mass and damping terms at each time step, a lot of computation time and capacities are required. Thus, under the premise that reliable fatigue damage could be derived through reasonable analysis method, it is necessary to reduce the analysis cases through the sensitivity studies and appropriate assumptions. In this paper, effects in fatigue are studied for spread mooring system connected with oil FPSO which is positioned in deep water of West Africa offshore. The target FPSO with two Mbbls storage has 16 spread mooring lines (4 bundles x 4 lines). The various sensitivity studies are performed for environmental loads, type of responses, vessel offsets, mooring position, loading conditions and riser behavior. Each parameter applied to the sensitivity studies is investigated from the effects of fatigue damage through fatigue analysis. Based on the sensitivity studies, the following results are presented: Wave loads are more dominant in terms of fatigue than other environment conditions. Wave frequency response causes the higher fatigue damage than low frequency response. The larger vessel offset increases the mean tension and so it results in the increased fatigue damage. The external line of each bundle shows the highest fatigue damage by the governed vessel pitch motion due to swell wave conditions. Among three kinds of loading conditions, ballast condition has the highest fatigue damage due to higher tension. The riser damping occurred by riser behavior tends to reduce the fatigue damage. The various analysis results obtained from these sensitivity studies can be used for a simplified fatigue analysis of spread mooring line as the reference.

Keywords: mooring system, fatigue analysis, time domain, non-linear dynamic characteristics

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Authors: Kumaresh Selvakumar, Man Young Kim

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Selective catalytic reduction (SCR) converts the nitrogen oxides with the aid of a catalyst by adding aqueous urea into the exhaust stream. In this work, the urea water droplets are sprayed over the exhaust gases by treating with Lagrangian particle tracking. The evaporation of ammonia from a single droplet of urea water solution is investigated computationally by convection-diffusion controlled model. The conversion to ammonia due to thermolysis of urea water droplets is measured downstream at different sections using finite rate/eddy dissipation model. In this paper, the mixer installed at the upstream enhances the distribution of ammonia over the entire domain which is calculated for different time steps. Calculations are made within the respective duration such that the complete decomposition of urea is possible at a much shorter residence time.

Keywords: convection-diffusion controlled model, lagrangian particle tracking, selective catalytic reduction, thermolysis

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Authors: Takashi Shimizu, Tomoaki Hashimoto

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Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.

Keywords: model predictive control, optimal control, process control, crystal growth

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Authors: Kwan U. Kim, Jin Sim, Ryong Jin Jang, Sung Duk Kim

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It is Leverrier that discovered the precession of the perihelion in the planetary orbits for the first time in the world, while it is Einstein that explained the astronomical phenomenom for the first time in the world. The amount of the precession of the perihelion for Einstein’s theory of gravitation has been explained by means of the inverse fourth power force(inverse third power potential) introduced totheory of gravitation through Schwarzschild metric However, the methodology has a serious shortcoming that it is impossible to explain the cause for the precession of the perihelion in the planetary orbits. According to our study, without taking the cause for the precession of the perihelion, 6 methods can explain the amount of the precession of the perihelion discovered by Leverrier. Therefore, the problem of what caused the perihelion to precess in the planetary orbits must be solved for physics because it is a profound scientific and technological problem for a basic experiment in construction of relativistic theory of gravitation. The scientific solution to the problem proved that Einstein’s explanation for the planetary orbits is a magic made by the numerical expressions obtained from fictitious gravitation introduced to theory of gravitation and wrong definition of proper time The problem of the precession of the perihelion seems solved already by means of general theory of relativity, but, in essence, the cause for the astronomical phenomenon has not been successfully explained for astronomy yet. The right solution to the problem comes from generalized theory of gravitation. Therefore, in this paper, it has been shown that by means of Schwarzschild field and the physical quantities of relativistic Lagrangian redflected in it, fictitious gravitation is not the main factor which can cause the perihelion to precess in the planetary orbits. In addition to it, it has been shown that the main factor which can cause the perihelion to precess in the planetary orbits is the inverse third power force existing really in the relativistic region in the Solar system.

Keywords: inverse third power force, precession of the perihelion, fictitious gravitation, planetary orbits

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Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

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Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

Procedia PDF Downloads 127

Authors: Anupam Sibal

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Apollo Quality Program(AQP) was launched across the Apollo Group of Hospitals to address the four patient safety areas; Safety during Clinical Handovers, Medication Safety, Surgical Safety and the six International Patient Safety Goals(IPSGs) of JCI. A measurable, online, quality dashboard covering 20 process and outcome parameters was devised for monthly monitoring. The expected outcomes were also defined and categorized into green, yellow and red ranges. An audit methodology was also devised to check the processes for the measurable dashboard. Documented clinical handovers were introduced for the first time at many locations for in-house patient transfer, nursing-handover, and physician-handover. Prototype forms using the SBAR format were made. Patient-identifiers, read-back for verbal orders, safety of high-alert medications, site marking and time-outs and falls risk-assessment were introduced for all hospitals irrespective of accreditation status. Measurement of Surgical-Site-Infection (SSI) for 30 days postoperatively, was done. All hospitals now tracked the time of administration of antimicrobial prophylaxis before surgery. Situations with high risk of retention of foreign body were delineated and precautionary measures instituted. Audit of medications prescribed in the discharge summaries was made uniform. Formularies, prescription-audits and other means for reduction of medication errors were implemented. There is a marked increase in the compliance to processes and patient safety outcomes. Compliance to read-back for verbal orders rose from 86.83% in April’11 to 96.95% in June’15, to policy for high alert medications from 87.83% to 98.82%, to use of measures to prevent wrong-site, wrong-patient, wrong procedure surgery from 85.75% to 97.66%, to hand-washing from 69.18% to 92.54%, to antimicrobial prophylaxis within one hour before incision from 79.43% to 93.46%. Percentage of patients excluded from SSI calculation due to lack of follow-up for the requisite time frame decreased from 21.25% to 10.25%. The average AQP scores for all Apollo Hospitals improved from 62 in April’11 to 87.7 in Jun’15.

Keywords: clinical handovers, international patient safety goals, medication safety, surgical safety

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Authors: M. Brahim, I. Bahri, Y. Bernard

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Traveling Wave Ultrasonic Motor (TWUM) is a compact, precise, and silent actuator generating high torque at low speed without gears. Moreover, the TWUM has a high holding torque without supply, which makes this motor as an attractive solution for holding position of robotic arms. However, their nonlinear dynamics, and the presence of load-dependent dead zones often limit their use. Those issues can be overcome in closed loop with effective and precise controllers. In this paper, robust H-infinity (H∞) and discrete time RST position controllers are presented. The H∞ controller is designed in continuous time with additional weighting filters to ensure the robustness in the case of uncertain motor model and external disturbances. Robust RST controller based on the pole placement method is also designed and compared to the H∞. Simulink model of TWUM is used to validate the stability and the robustness of the two proposed controllers.

Keywords: piezoelectric motors, position control, H∞, RST, stability criteria, robustness

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Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

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Authors: S. Agheb, G. Ledwich, G.Walker, Z.Tong

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Frequency control has become more of concern for reliable operation of interconnected power systems due to the integration of low inertia renewable energy sources to the grid and their volatility. Also, in case of a sudden fault, the system has less time to recover before widespread blackouts. Electric Vehicles (EV)s have the potential to cooperate in the Emergency Frequency Regulation (EFR) by a nonlinear control of the power system in case of large disturbances. The time is not adequate to communicate with each individual EV on emergency cases, and thus, an aggregate model is necessary for a quick response to prevent from much frequency deviation and the occurrence of any blackout. In this work, an aggregate of EVs is modelled as a big virtual battery in each area considering various aspects of uncertainty such as the number of connected EVs and their initial State of Charge (SOC) as stochastic variables. A control law was proposed and applied to the aggregate model using Lyapunov energy function to maximize the rate of reduction of total kinetic energy in a two-area network after the occurrence of a fault. The control methods are primarily based on the charging/ discharging control of available EVs as shunt capacity in the distribution system. Three different cases were studied considering the locational aspect of the model with the virtual EV either in the center of the two areas or in the corners. The simulation results showed that EVs could help the generator lose its kinetic energy in a short time after a contingency. Earlier estimation of possible contributions of EVs can help the supervisory control level to transmit a prompt control signal to the subsystems such as the aggregator agents and the grid. Thus, the percentage of EVs contribution for EFR will be characterized in the future as the goal of this study.

Keywords: emergency frequency regulation, electric vehicle, EV, aggregation, Lyapunov energy function

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Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

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A packet loss probability (PLP) estimation filter with finite memory structure is proposed to estimate the packet rate mean and variance of the input traffic process in real-time while removing undesired system and measurement noises. The proposed PLP estimation filter is developed under a weighted least square criterion using only the finite traffic measurements on the most recent window. The proposed PLP estimation filter is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. A guideline for choosing appropriate window length is described since it can affect significantly the estimation performance. Using computer simulations, the proposed PLP estimation filter is shown to be superior to the Kalman filter for the temporarily uncertain system. One possible explanation for this is that the proposed PLP estimation filter can have greater convergence time of a filtered estimate as the window length M decreases.

Keywords: packet loss probability estimation, finite memory filter, infinite memory filter, Kalman filter

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Authors: Guesh Simretab Gebremedhin, Saumya Rajan Jena

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In this work, a septic B-spline scheme has been used to simplify the process of solving an approximate solution of the generalized Rosenau-regularized long-wave equation (GR-RLWE) with initial boundary conditions. The resulting system of first-order ODEs has dealt with Butcher’s fifth order Runge-Kutta (BFRK) approach without using finite difference techniques for discretizing the time-dependent variables at each time level. Here, no transformation or any kind of linearization technique is employed to tackle the nonlinearity of the equation. Two test problems have been selected for numerical justifications and comparisons with other researchers on the basis of efficiency, accuracy, and results of the two invariants Mᵢ (mass) and Eᵢ (energy) of some motion that has been used to test the conservative properties of the proposed scheme.

Keywords: septic B-spline scheme, Butcher's fifth order Runge-Kutta approach, error norms, generalized Rosenau-RLW equation

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Authors: Rana S. Alghamdi

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Play in early childhood education has been stifled across the world due to an overemphasis on academic achievement and a reduced focus on physical play and motor development. In Saudi Arabia, teachers reticent to allocate more time to play for fear of retribution from parents and administrators that children are losing academic seat time. This practice has proven to be detrimental to the social, emotional, physical, and cognitive development of children. Teachers are pressured to prioritize Arabic, math, and science while providing minimal time for physical activities. Administrators tend to push for an ever-increasing emphasis on academia in order to achieve higher test scores. However, young children often find it difficult to concentrate if they are not able to get out energy through physical play. Furthermore, many youth educators are not qualified to oversee physical activities, and many facilities are unprepared for safe, outdoor play. This results in children getting little to no outdoor activity. They are stuck in a strict academic regimen that may dampen the creativity and imagination easily fostered through cooperative play. For a stronger educational system and more well-rounded students, Saudi schools should enact policies that extend the number of required hours dedicated to outdoor and physical play. They should also offer training for unqualified teachers. This training should focus on the benefits of physical play and instruct them on how to facilitate these activities safely and effectively. School administrators must focus on providing adequate equipment and safe environments for the purpose of outdoor play and education. In doing so, they will be setting their students up for a successful future and improving their abilities in all aspects of education.

Keywords: early childhood education, play, outdoor, Saudi Arabia

Procedia PDF Downloads 151

Authors: Sumeet Kumar, C. V. Krishnamurthy, Krishnan Balasubramaniam

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Normal spectral emissivity of Al 6061 alloys with different surface finishes was experimentally measured at 833°K. Four different samples were prepared by polishing the surfaces of the alloy by 80, 220, 600 grit sizes of SiC abrasive papers and diamond paste. The samples were heated in air for 6 h at 833°K, and the emissivity was measured during the process from pyrometers operating at wavelengths of 3.9, 5.14 and 7.8 μm. The results indicated that the emissivity was increasing with heating time and the rate of increase was rapid during the initial stage of heating in comparison with the later stage. This appears to be because of the parabolic rate law followed by the process of oxidation. Further, it is found that the increase in emissivity with heating time was higher for rough surfaces than that for polished surfaces. Both the results were analyzed at all the three wavelengths, and qualitatively similar results were obtained for all of them. In this way emissivity of the alloy can be increased by roughening the surfaces and heating it at high temperature until the surfaces are oxidized.

Keywords: aluminum alloy, high temperature, normal spectral emissivity, surface roughness

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Authors: M. Dagim Yoseph, M. K. Savage, A. D. Jolly, C. J. Ebinger

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Whakaari/White Island has been the most active New Zealand volcano in the 21st century, producing small phreatic and phreatomagmatic eruptions, which are hard to predict. The most recent eruption occurred in 2019, tragically claiming the lives of 22 individuals and causing numerous injuries. We employed shear-wave splitting analyses to investigate variations in anisotropy between 2018 and 2020, during quiescence, unrest, and the eruption. We examined spatial and temporal variations in 3499 shear-wave splitting and 2656 V_p/V_s ratio measurements. Comparing shear-wave splitting parameters from similar earthquake paths across different times indicates that the observed temporal changes are unlikely to result from variations in earthquake paths through media with spatial variability. Instead, these changes may stem from variations in anisotropy over time, likely caused by changes in crack alignment due to stress or varying fluid content.

Keywords: background seismic waves, fast orientations, seismic anisotropy, V_p/V_s ratio

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Authors: Kyoungwoo Park, Gil Dong Kim, Seong Joon Moon, Ho Kil Lee

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The Urea-SCR is one of the most efficient technologies to reduce NOx emissions in diesel engines. In the present work, the computational prediction of internal flow and spray characteristics in the Urea-SCR system was carried out by using 3D-CFD simulation to evaluate NH3 uniformity index (NH3 UI) and its activation time according to the official New European Driving Cycle (NEDC). The number of nozzle and its diameter, two types of injection directions, and penetration length were chosen as the design variables. The optimal solutions were obtained by coupling the CFD analysis with Taguchi method. The L16 orthogonal array and small-the-better characteristics of the Taguchi method were used, and the optimal values were confirmed to be valid with 95% confidence and 5% significance level through analysis of variance (ANOVA). The results show that the optimal solutions for the NH3 UI and activation time (NH3 UI 0.22) are obtained by 0.41 and 0,125 second, respectively, and their values are improved by 85.0% and 10.7%, respectively, compared with those of the base model.

Keywords: computational fluid dynamics, NH3 uniformity index, optimization, Taguchi method, Urea-SCR system, UWS injector

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Authors: Sergio Tovar-Pérez, Sebastian Töpfer, Markus Gräfe

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The work proposes a technique that decreases the detection acquisition time of quantum holography schemes down to one-third; this allows the possibility to image moving objects. Since its invention, quantum holography with undetected photon schemes has gained interest in the scientific community. This is mainly due to its ability to tailor the detected wavelengths according to the needs of the scheme implementation. Yet this wavelength flexibility grants the scheme a wide range of possible applications; an important matter was yet to be addressed. Since the scheme uses digital phase-shifting techniques to retrieve the information of the object out of the interference pattern, it is necessary to acquire a set of at least four images of the interference pattern along with well-defined phase steps to recover the full object information. Hence, the imaging method requires larger acquisition times to produce well-resolved images. As a consequence, the measurement of moving objects remains out of the reach of the imaging scheme. This work presents the use and implementation of a spatial light modulator along with a digital holographic technique called quasi-parallel phase-shifting. This technique uses the spatial light modulator to build a structured phase image consisting of a chessboard pattern containing the different phase steps for digitally calculating the object information. Depending on the reduction in the number of needed frames, the acquisition time reduces by a significant factor. This technique opens the door to the implementation of the scheme for moving objects. In particular, the application of this scheme in imaging alive specimens comes one step closer.

Keywords: quasi-parallel phase shifting, quantum imaging, quantum holography, quantum metrology

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Authors: R. Velvarska, A. Vrablik, M. Fiedlerova, R. Cerny

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Near-infrared spectrometry (NIR) was tested as a rapid and alternative tool for determination of biodiesel oxidation stability. A PetroOxy method is standardly used for the determination, but this method is hazardous due to the possibility of explosion and ignition of flammable fuels. The second disadvantage is time consuming. The near-infrared spectrometry served for the development of the calibration model which was composed of 133 real samples (calibration standards). The reference values of these standards were obtained by PetroOxy method. Many chemometric diagnostics were used for the development of the final NIR model with the aim to have accurate prediction of the oxidation stability. The final NIR model was validated by 30 validation standards. The repeatability was determined as well with the acceptable residual standard deviation (8.59 %). The NIR spectrometry has proved to be an accurate alternative method for the determination of biodiesel oxidation stability with advantages as the time and cost saving, non-destructive character of analyzing and the possibility of online monitoring in safe mode.

Keywords: biodiesel, fatty acid methyl ester, NIR, oxidation stability

Procedia PDF Downloads 175

Authors: M. S. Stepanova, V. V. Zakharov, P. D. Khavlyuk, I. D. Skurlov, A. Y. Dubovik, A. L. Rogach

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Carbon dots are small carbon-based spherical nanoparticles, which are typically less than 10 nm in size that can be modified with surface passivation and heteroatoms doping. The light-absorbing ability of carbon dots has attracted a significant amount of attention in photoluminescence for bioimaging and fluorescence sensing applications owing to their advantages, such as tunable fluorescence emission, photo- and thermostability and low toxicity. In this study, carbon dots were synthesized by the solvothermal method from citric acid and ethylenediamine dissolved in water. The solution was heated for 5 hours at 200°C and then cooled down to room temperature. The carbon dots films were obtained by evaporation from a high-concentration aqueous solution. The increase of both luminescence intensity and light transmission was obtained as a result of a 405 nm laser exposure to a part of the carbon dots film, which was detected using a confocal laser scanning microscope (LSM 710, Zeiss). Blueshift up to 35 nm of the luminescence spectrum is observed as luminescence intensity, which is increased more than twofold. The exact value of the shift depends on the time of the laser exposure. This shift can be caused by the modification of surface groups at the carbon dots, which are responsible for long-wavelength luminescence. In addition, a shift of the absorption peak by 10 nm and a decrease in the optical density at the wavelength of 350 nm is detected, which is responsible for the absorption of surface groups. The obtained sample was also studied with time-resolved confocal fluorescence microscope (MicroTime 100, PicoQuant), which made it possible to receive a time-resolved photoluminescence image and construct emission decays of the laser-exposed and non-exposed areas. 5 MHz pulse rate impulse laser has been used as a photoluminescence excitation source. Photoluminescence decay was approximated by two exhibitors. The laser-exposed area has the amplitude of the first-lifetime component (A1) twice as much as before, with increasing τ1. At the same time, the second-lifetime component (A2) decreases. These changes evidence a modification of the surface groups of carbon dots. The detected effect can be used to create thermostable fluorescent marks, the physical size of which is bounded by the diffraction limit of the optics (~ 200-300 nm) used for exposure and to improve the optical properties of carbon dots or in the field of optical encryption. Acknowledgements: This work was supported by the Ministry of Science and Higher Education of Russian Federation, goszadanie no. 2019-1080 and financially supported by Government of Russian Federation, Grant 08-08.

Keywords: carbon dots, photoactivation, optical properties, photoluminescence and absorption spectra

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Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Sridevi Devadas

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This study was aimed to examine the combination efficiency of Clorox (5.25% Sodium Hypochlorite) and mercury chloride (HgCl2) as reagent for surface sterilization process of aquatic plant, Cryptocoryne affinis (C. affinis). The treatment applied 10% of the Clorox and 0.1 ppm of mercury chloride. The maximum exposure time for Clorox and mercury chloride was 10 min and 60 sec respectively. After exposed to the treatments protocols (T1-T15) the explants were transferred to culture room under control temperature at 25°C ± 2°C and subjected to 16 hours fluorescence light (2000 lumens) for 30 days. The both sterilizing agents were not applied on control specimens. Upon analysis, the result indicates all of the treatments protocols produced sterile explants at range of minimum 1.5 ± 0.7 (30%) to maximum 5.0 ± 0.0 (100%). Meanwhile, maximum 1.0 ± 0.7 numbers of leaves and 1.4 ± 0.6 numbers of roots have been produced. The optimized exposure time was 0 to 15 min for Clorox and 30 sec for HgCl2 whereby 90% to 100% sterilization was archived at this condition.

Keywords: Cryptocoryne affinis, surface sterilization, tissue culture, clorox, mercury chloride

Procedia PDF Downloads 600

Authors: Ruolan Zhang, Ryo Imai, Naoko Senda, Tomoyuki Sakai

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Enzymes have attracted increasing attentions in industrial manufacturing for their applicability in catalyzing complex chemical reactions under mild conditions. Directed evolution has become a powerful approach to optimize enzymes and exploit their full potentials under the circumstance of insufficient structure-function knowledge. With the incorporation of cell-free synthetic biotechnology, rapid enzyme synthesis can be realized because no cloning procedure such as transfection is needed. Its open environment also enables direct enzyme measurement. These properties of cell-free biotechnology lead to excellent throughput of enzymes generation. However, the capabilities of current screening methods have limitations. Fluorescence-based assay needs applicable fluorescent label, and the reliability of acquired enzymatic activity is influenced by fluorescent label’s binding affinity and photostability. To acquire the natural activity of an enzyme, another method is to combine pre-screening step and high-performance liquid chromatography (HPLC) measurement. But its throughput is limited by necessary time investment. Hundreds of variants are selected from libraries, and their enzymatic activities are then identified one by one by HPLC. The turn-around-time is 30 minutes for one sample by HPLC, which limits the acquirable enzyme improvement within reasonable time. To achieve the real high-throughput enzyme screening, i.e., obtain reliable enzyme improvement within reasonable time, a widely applicable high-throughput measurement of enzymatic reactions is highly demanded. Here, a high-throughput screening method using broadband coherent anti-Stokes Raman spectroscopy (CARS) was proposed. CARS is one of coherent Raman spectroscopy, which can identify label-free chemical components specifically from their inherent molecular vibration. These characteristic vibrational signals are generated from different vibrational modes of chemical bonds. With the broadband CARS, chemicals in one sample can be identified from their signals in one broadband CARS spectrum. Moreover, it can magnify the signal levels to several orders of magnitude greater than spontaneous Raman systems, and therefore has the potential to evaluate chemical's concentration rapidly. As a demonstration of screening with CARS, alcohol dehydrogenase, which converts ethanol and nicotinamide adenine dinucleotide oxidized form (NAD+) to acetaldehyde and nicotinamide adenine dinucleotide reduced form (NADH), was used. The signal of NADH at 1660 cm⁻¹, which is generated from nicotinamide in NADH, was utilized to measure the concentration of it. The evaluation time for CARS signal of NADH was determined to be as short as 0.33 seconds while having a system sensitivity of 2.5 mM. The time course of alcohol dehydrogenase reaction was successfully measured from increasing signal intensity of NADH. This measurement result of CARS was consistent with the result of a conventional method, UV-Vis. CARS is expected to have application in high-throughput enzyme screening and realize more reliable enzyme improvement within reasonable time.

Keywords: Coherent Anti-Stokes Raman Spectroscopy, CARS, directed evolution, enzyme screening, Raman spectroscopy

Procedia PDF Downloads 141