Search results for: optimal porosity

Authors: Anne Schattel, Mitja Echim, Christof Büskens

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Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Bezhan Ghvaberidze

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A multiple criteria optimization approach for the solution of the Fuzzy Vehicle Routing Problem (FVRP) is proposed. For the possibility environment the levels of movements between customers are calculated by the constructed simulation interactive algorithm. The first criterion of the bi-criteria optimization problem - minimization of the expectation of total fuzzy travel time on closed routes is constructed for the FVRP. A new, second criterion – maximization of feasibility of movement on the closed routes is constructed by the Choquet finite averaging operator. The FVRP is reduced to the bi-criteria partitioning problem for the so called “promising” routes which were selected from the all admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in the real-time computing. For the numerical solution of the bi-criteria partitioning problem the -constraint approach is used. An exact algorithm is implemented based on D. Knuth’s Dancing Links technique and the algorithm DLX. The Main objective was to present the new approach for FVRP, when there are some difficulties while moving on the roads. This approach is called FVRP for extreme conditions (FVRP-EC) on the roads. Also, the aim of this paper was to construct the solving model of the constructed FVRP. Results are illustrated on the numerical example where all Pareto-optimal solutions are found. Also, an approach for more complex model FVRP with time windows was developed. A numerical example is presented in which optimal routes are constructed for extreme conditions on the roads.

Keywords: combinatorial optimization, Fuzzy Vehicle routing problem, multiple objective programming, possibility theory

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

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This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

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Authors: Emiliano Matta

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Passive resonant vibration absorbers are among the most widely used dynamic control systems in civil engineering. They typically consist in a single-degree-of-freedom mechanical appendage of the main structure, tuned to one structural target mode through frequency and damping optimization. One classical scheme is the pendulum absorber, whose mass is constrained to move along a curved trajectory and is damped by viscous dashpots. Even though the principle is well known, the search for improved arrangements is still under way. In recent years this investigation inspired a type of bidirectional pendulum absorber (BPA), consisting of a mass constrained to move along an optimal three-dimensional (3D) concave surface. For such a BPA, the surface principal curvatures are designed to ensure a bidirectional tuning of the absorber to both principal modes of the main structure, while damping is produced either by horizontal viscous dashpots or by vertical friction dashpots, connecting the BPA to the main structure. In this paper, a variant of BPA is proposed, where damping originates from the variable tangential friction force which develops between the pendulum mass and the 3D surface as a result of a spatially-varying friction coefficient pattern. Namely, a friction coefficient is proposed that varies along the pendulum surface in proportion to the modulus of the 3D surface gradient. With such an assumption, the dissipative model of the absorber can be proven to be nonlinear homogeneous in the small displacement domain. The resulting homogeneous BPA (HBPA) has a fundamental advantage over conventional friction-type absorbers, because its equivalent damping ratio results independent on the amplitude of oscillations, and therefore its optimal performance does not depend on the excitation level. On the other hand, the HBPA is more compact than viscously damped BPAs because it does not need the installation of dampers. This paper presents the analytical model of the HBPA and an optimal methodology for its design. Numerical simulations of single- and multi-story building structures under wind and earthquake loads are presented to compare the HBPA with classical viscously damped BPAs. It is shown that the HBPA is a promising alternative to existing BPA types and that homogeneous tangential friction is an effective means to realize systems provided with amplitude-independent damping.

Keywords: amplitude-independent damping, homogeneous friction, pendulum nonlinear dynamics, structural control, vibration resonant absorbers

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Authors: Adam Patterson

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This study analyzes the self-reported experiences of virtual reality users to develop insight into an optimal learning path for education within virtual reality. This research uses a sample of 1000 observations to statistically define factors influencing (i) immersion level and (ii) motion sickness rating for virtual reality experience respondents of college age. This paper recommends an efficient duration for each virtual reality session, to minimize sickness and maximize engagement, utilizing modern machine learning methods such as association rules. The goal of this research, in augmentation with previous literature, is to inform logistical decisions relating to implementation of pilot instruction for virtual reality at the collegiate level. Future research will include a Randomized Control Trial (RCT) to quantify the effect of virtual reality education on student learning outcomes and engagement measures. Current research aims to maximize the treatment effect within the RCT by optimizing the learning benefits of virtual reality. Results suggest significant gender heterogeneity amongst likelihood of reporting motion sickness. Females are 1.7 times more likely, than males, to report high levels of motion sickness resulting from a virtual reality experience. Regarding duration, respondents were 1.29 times more likely to select the lowest level of motion sickness after an engagement lasting between 24.3 and 42 minutes. Conversely, respondents between 42 to 60 minutes were 1.2 times more likely to select the higher levels of motion sickness.

Keywords: applications and integration of e-education, practices and cases in e-education, systems and technologies in e-education, technology adoption and diffusion of e-learning

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Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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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: M. Saidi, F. Ait Medjber, B. Safi, M. Samar

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This work is focused on the study of valuation of recycled concrete aggregates, by measuring certain properties of concrete in the fresh and hardened state. In this study, rheological tests and physic-mechanical characterization on concretes and mortars were conducted with recycled concrete whose geometric properties were identified aggregates. Mortars were elaborated with recycled fine aggregate (0/5mm) and concretes were manufactured using recycled coarse aggregates (5/12.5 mm and 12.5/20 mm). First, a study of the mortars was conducted to determine the effectiveness of adjuvant polycarboxylate superplasticizer on the workability of these and their action deflocculating of the fine recycled sand. The rheological behavior of mortars based on fine aggregate recycled was characterized. The results confirm that the mortars composed of different fractions of recycled sand (0/5) have a better mechanical properties (compressive and flexural strength) compared to normal mortar. Also, the mechanical strengths of concretes made with recycled aggregates (5/12.5 mm and 12.5/20 mm), are comparable to those of conventional concrete with conventional aggregates, provided that the implementation can be improved by the addition of a superplasticizer.

Keywords: demolition wastes, recycled coarse aggregate, concrete, workability, mechanical strength, porosity/water absorption

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Authors: Seolah Lee, Yoohyk Jang, Soyoung Lee, Kon Chu, Sang Kun Lee

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Objective: The International League Against Epilepsy (ILAE) currently suggests a topiramate serum level range of 5-20 mg/L. However, numerous institutions have observed substantial drug response at lower levels. This study aims to investigate the correlation between topiramate serum levels, drug responsiveness, and adverse events to establish a more accurate and tailored therapeutic range. Methods: We retrospectively analyzed topiramate serum samples collected between January 2017 and January 2022 at Seoul National University Hospital. Clinical data, including serum levels, antiseizure regimens, seizure frequency, and adverse events, were collected. Patient responses were categorized as "insufficient" (reduction in seizure frequency <50%) or "sufficient" (reduction ≥ 50%). Within the "sufficient" group, further subdivisions included seizure-free and tolerable seizure subgroups. A population pharmacokinetic model estimated serum levels from spot measurements. ROC curve analysis determined the optimal serum level cut-off. Results: A total of 389 epilepsy patients, with 555 samples, were reviewed, having a mean dose of 178.4±117.9 mg/day and a serum level of 3.9±2.8 mg/L. Out of the samples, only 5.6% (n=31) exhibited insufficient response, with a mean serum level of 3.6±2.5 mg/L. In contrast, 94.4% (n=524) of samples demonstrated sufficient response, with a mean serum level of 4.0±2.8 mg/L. This difference was not statistically significant (p = 0.45). Among the 78 reported adverse events, logistic regression analysis identified a significant association between ataxia and serum concentration (p = 0.04), with an optimal cut-off value of 6.5 mg/L. In the subgroup of patients receiving monotherapy, those in the tolerable seizure group exhibited a significantly higher serum level compared to the seizure-free group (4.8±2.0 mg/L vs 3.4±2.3 mg/L, p < 0.01). Notably, patients in the tolerable seizure group displayed a higher likelihood of progressing into drug-resistant epilepsy during follow-up visits compared to the seizure-free group. Significance: This study proposed an optimal therapeutic concentration for topiramate based on the patient's responsiveness to the drug and the incidence of adverse effects. We employed a population pharmacokinetic model and analyzed topiramate serum levels to recommend a serum level below 6.5 mg/L to mitigate the risk of ataxia-related side effects. Our findings also indicated that topiramate dose elevation is unnecessary for suboptimal responders, as the drug's effectiveness plateaus at minimal doses.

Keywords: topiramate, therapeutic range, low dos, antiseizure effect

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Authors: Akram Sadat Jafari Roodbandi, Parisa Kahani, Fatollah Rahimi Bafrani, Ali Dehghan, Nava Seyedi, Vafa Feyzi, Zohreh Forozanfar

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Introduction: Movement function is considered as the ability to produce and maintain balance, stability, and movement throughout the movement chain. Having a score of 14 and above on 7 sub-tests in the functional movement screening (FMS) test shows agility and optimal movement performance. On the other hand, the person's body is an important factor in physical fitness and optimal movement performance. The aim of this study was to identify effective anthropometric dimensions in increasing motor function. Methods: This study was a descriptive-analytical and cross-sectional study using simple random sampling. FMS test and 25 anthropometric dimensions and subcutaneous in five body regions measured in 139 healthy students of Bam University of Medical Sciences. Data analysis was performed using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: 139 students were enrolled in the study, 51.1% (71 subjects) and the rest were female. The mean and standard deviation of age, weight, height, and arm subcutaneous fat were 21.5 ± 1.45, 12.6 ± 64.3, 168.7 ± 9.8, 15.3 ± 7, respectively. 17 subjects (12.2%) of the participants in the study have a score of less than 14, and the rest were above 14. Using regression analysis, it was found that exercise and arm subcutaneous fat are predictive variables associated with obtaining a high score in the FMS test. Conclusion: Exercise and weight loss are effective factors for increasing the movement performance of individuals, and this factor is independent of the size of other physical dimensions.

Keywords: functional movement, screening test, anthropometry, ergonomics

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Authors: Adel Nikfarjam, Hamed Tayebi, Sadoullah Ebrahimnejad

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This paper considers a two-echelon inventory system with a number of warehouses and a single retailer. The retailer replenishes its required items from warehouses, and assembles them into a single final product. We assume that each warehouse supplies only one kind of the raw material for the retailer. The demand process of the final product is assumed to be Poissson, and unsatisfied demand of the final product will be lost. The retailer applies one-for-one-period ordering policy which is also known as (1, T) ordering policy. In this policy the retailer orders to each warehouse a fixed quantity of each item at fixed time intervals, which the fixed quantity is equal to the utilization of the item in the final product. Since, this policy eliminates all demand uncertainties at the upstream echelon, the standard lot sizing model can be applied at all warehouses. In this paper, we calculate the total cost function of the inventory system. Then, based on this function, we present a procedure to obtain the optimal time interval between two consecutive order placements from retailer to the warehouses, and the optimal order quantities of warehouses (assuming that there are positive ordering costs at warehouses). Finally, we present some numerical examples, and conduct numerical sensitivity analysis for cost parameters.

Keywords: two-echelon supply chain, multi-vendor-single-buyer inventory system, lost sales, Poisson demand, one-for-one-period policy, lot sizing model

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Authors: Neda Sinaei, Davood Zare, Mehrdad Azin

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Polyhydroxyalkanoates (PHAs) are biocompatible and biodegradable polymers produced by a wide range of bacterial strains. These biopolymers are significantly studied for drug delivery and tissue engineering applications because of their fascinating physicochemical properties. Polyhydroxybutyrate (PHB) scaffold that has been extracted from a novel bacteria using oil wastewater was selected to study. Some physical parameters affecting scaffold properties such as PHB concentration, solvent evaporation speed, and ultrasonic time were investigated. Scanning electron microscopy was used to evaluate the porosity. Afterward, the biocompatibility of PHB scaffold was assessed. Initial results showed the highly porous PHB scaffold structure with a variety of pore sizes. Subsequent results indicated that more unique pore sizes can be obtained by optimizing physical factors. It would be noticed that the morphology of the pore structure was accordingly affected by ultrasonic time. Hence, In vitro cell viability tests on the PHB scaffold using human foreskin fibroblasts revealed strong cell attachment and proliferation supports. Therefore, it can be concluded that the cost-effective PHB scaffold has the potential using as a biomaterial cell adhesion substrate in therapeutic applications.

Keywords: Polyhydroxybutyrate, biocompatible, scaffold, porous, tissue engineering

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Authors: Samia Rabet, Rachida Chemini, Gerhard Schäfer, Farid Aiouache

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The textile industry generates large quantities of wastewater, which poses significant environmental problems due to its complex composition and high levels of pollutants loaded principally with heavy metals, large amounts of COD, and dye. Separation treatment methods are often known for their effectiveness in removing contaminants whereas membrane separation techniques are a promising process for the treatment of textile effluent due to their versatility, efficiency, and low energy requirements. This study focuses on the modeling and simulation of membrane separation technologies with a cross-flow filtration process for textile effluent treatment. It aims to explore the application of mathematical models and computational simulations using ASPEN Plus Software in the prediction of a complex and real effluent separation. The results demonstrate the effectiveness of modeling and simulation techniques in predicting pollutant removal efficiencies with a global deviation percentage of 1.83% between experimental and simulated results; membrane fouling behavior, and overall process performance (hydraulic resistance, membrane porosity) were also estimated and indicating that the membrane losses 10% of its efficiency after 40 min of working.

Keywords: membrane separation, ultrafiltration, textile effluent, modeling, simulation

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Authors: Saneeya Qureshi

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This paper reports doctoral research into the impact of Special Educational Needs Coordinators (SENCOs) on teachers in England, UK. Since 1994, it has been compulsory for all mainstream schools in the UK to have a SENCO who co-ordinates assessment and provision for supporting pupils with Special Educational Needs (SEN), helping teachers to develop and implement optimal SEN planning and resources. SENCOs’ roles have evolved as various policies continually redefined SEN provision, impacting their positioning within the school hierarchical structure. SENCOs in England are increasingly recognised as key members of school senior management teams. In this paper, It will be argued that despite issues around the transformative ‘professionalisation’ of their role, and subsequent conflict around boundaries and power relations, SENCOs enhance teachers’ abilities in terms of delivering optimal SEN provision. There is a significant international dimension to the issue: a similar role in respect of SEN management already exists in countries such as Ireland, Finland and Singapore, whilst in other countries, such as Italy and India, the introduction of a role similar to that of a SENCO is currently under discussion. The research question addressed is: do SENCOs enhance teachers’ abilities to be effective teachers of children with Special Educational Needs? The theoretical framework of the project is that of interpretivism, as it is acknowledged that there are contexts and realities are social constructions. The study applied a mixed method approach consisting of two phases. The first phase involved a purposive survey (n=42) of 223 primary school SENCOs, which enabled a deeper insight into SENCOs’ perceptions of their roles in relation to teachers. The second phase consisted of semi-structured interviews (n=36) of SENCOs, teachers and head teachers, in addition to school SEN-related documentation scrutiny. ‘Trustworthiness’ was accomplished through data and methodological triangulation, in addition to a rigorous process of coding and thematic analysis. The research was informed by an Ethical Code as per national guidelines. Research findings point to the evolutionary aspect of the SENCO role having engendered a culture of expectations amongst practitioners, as SENCOs transition from being ‘fixers’ to being ‘enablers’ of teachers. Outcomes indicate that SENCOs can empower teaching staff through the dissemination of specialist knowledge. However, there must be resources clearly identified for such dissemination to take place. It is imperative that both SENCOs and teachers alike address the issue of absolution of responsibility that arises when the ownership and accountability for the planning and implementation of SEN provision are not clarified so as to ensure the promotion of a positive school ethos around inclusive practices. Optimal outcomes through effective SEN interventions and teaching practices are positively correlated with the inclusion of teachers in the planning and execution of SEN provisions. An international audience can consider how the key findings are being manifest in a global context, with reference to their own educational settings. Research outcomes can aid the development of specific competencies needed to shape optimal inclusive educational settings in accordance with the official global priorities pertaining to inclusion.

Keywords: inclusion, school professionals, school leadership, special educational needs (SEN), special educational needs coordinators (SENCOs)

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Authors: Yen-Luan Chen

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Maintenance has a great impact on the capacity of production and on the quality of the products, and therefore, it deserves continuous improvement. Maintenance procedure done before a failure is called preventive maintenance (PM). Sequential PM, which specifies that a system should be maintained at a sequence of intervals with unequal lengths, is one of the commonly used PM policies. This article proposes a generalized sequential PM policy for a system subject to shocks with imperfect maintenance and random working time. The shocks arrive according to a non-homogeneous Poisson process (NHPP) with varied intensity function in each maintenance interval. As a shock occurs, the system suffers two types of failures with number-dependent probabilities: type-I (minor) failure, which is rectified by a minimal repair, and type-II (catastrophic) failure, which is removed by a corrective maintenance (CM). The imperfect maintenance is carried out to improve the system failure characteristic due to the altered shock process. The sequential preventive maintenance-last (PML) policy is defined as that the system is maintained before any CM occurs at a planned time Ti or at the completion of a working time in the i-th maintenance interval, whichever occurs last. At the N-th maintenance, the system is replaced rather than maintained. This article first takes up the sequential PML policy with random working time and imperfect maintenance in reliability engineering. The optimal preventive maintenance schedule that minimizes the mean cost rate of a replacement cycle is derived analytically and determined in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.

Keywords: optimization, preventive maintenance, random working time, minimal repair, replacement, reliability

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Authors: V. Jagadeesh, K. Venkata Subbaiah, P. Govinda Rao

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This paper explaining about the significance of information technology tools and software packages in supply chain management (SCM) in order to manage the entire supply chain. Managing materials flow and financial flow and information flow effectively and efficiently with the aid of information technology tools and packages in order to deliver right quantity with right quality of goods at right time by using right methods and technology. Information technology plays a vital role in streamlining the sales forecasting and demand planning and Inventory control and transportation in supply networks and finally deals with production planning and scheduling. It achieves the objectives by streamlining the business process and integrates within the enterprise and its extended enterprise. SCM starts with customer and it involves sequence of activities from customer, retailer, distributor, manufacturer and supplier within the supply chain framework. It is the process of integrating demand planning and supply network planning and production planning and control. Forecasting indicates the direction for planning raw materials in order to meet the production planning requirements. Inventory control and transportation planning allocate the optimal or economic order quantity by utilizing shortest possible routes to deliver the goods to the customer. Production planning and control utilize the optimal resources mix in order to meet the capacity requirement planning. The above operations can be achieved by using appropriate information technology tools and software packages for the supply chain management.

Keywords: supply chain management, information technology, business process, extended enterprise

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Authors: H. Ahmed, A. Schlenkhoff

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Recently, permeable breakwaters have been suggested to overcome the disadvantages of fully protection breakwaters. These protection structures have minor impacts on the coastal environment and neighboring beaches where they provide a more economical protection from waves and currents. For regular waves, a numerical model is used (FLOW-3D, VOF) to investigate the hydraulic performance of a permeable breakwater. The model of permeable breakwater consists of a pair of identical vertical slotted walls with an impermeable upper and lower part, where the draft is a decimal multiple of the total depth. The middle part is permeable with a porosity of 50%. The second barrier is located at distant of 0.5 and 1.5 of the water depth from the first one. The numerical model is validated by comparisons with previous laboratory data and semi-analytical results of the same model. A good agreement between the numerical results and both laboratory data and semi-analytical results has been shown and the results indicate the applicability of the numerical model to reproduce most of the important features of the interaction. Through the numerical investigation, the friction factor of the model is carefully discussed.

Keywords: coastal structures, permeable breakwater, slotted wall, numerical model, energy dissipation coefficient

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Emery A. Coppola Jr., Suna Cinar, Ferenc Szidarovszky

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Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions.

Keywords: numerical groundwater flow modeling, water management optimization, groundwater overdraft, streamflow depletion

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Authors: L. Nevrivova, K. Lang, M. Kotoucek, D. Vsiansky

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This entry concerned with dense silica microstructure was produced as a part of a project within the Technology Agency of the Czech Republic which is being implemented in cooperation of the biggest producer of refractories the P-D Refractories CZ company with the research organisation Brno University of Technology. The paper is focused on the influence of mixture homogenisation and the influence of grain size of the mineraliser on the resulting utility properties of the material as well as its microstructure. It has a decisive influence on the durability of the material in a building structure. This paper is a continuation of a previously published study dealing with the suitability of various types of mineralising agents in terms of density, strength and mineral composition of silica. The entry describes the influence of the method of mixture homogenisation and the influence of granulometry of the applied Fe-mineralising agent on the resulting silica microstructure. Porosity, density, phase composition and microstructure of the experimentally prepared silica samples were examined and the results were discussed in context with the technology of homogenisation and firing temperature used. The properties of silica brick samples were compared to the sample without any Fe-mineraliser.

Keywords: silica bricks, Fe-mineraliser, mineralogical composition, new developed silica material

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Authors: T. H. N. Nguyen, A. Khodan, M. Amamra, J-V. Vignes, A. Kanaev

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The ultraporous nanofibrous alumina (NOA, Al2O3·nH2O) was synthesized by oxidation of laminated aluminium plates through a liquid mercury-silver layer in a humid atmosphere ~80% at 25°C. The material has an extremely high purity (99%), porosity (90%) and specific area (300 m2/g). The subsequent annealing of raw NOA permits obtaining pure transition phase (γ and θ) nanostructured materials. In this combination, we report on chemical, structural and phase transformations of pure and modified NOA by an impregnation of trimethylethoxysilane (TMES) and tetraethoxysilane (TEOS) during thermal annealing in the temperature range between 20 and 1650°C. The mass density, specific area, average diameter and specific area are analysed. The 3D model of pure NOA monoliths and silica modified NOA is proposed, which successfully describes the evolution of specific area, mass density and phase transformations. Activation energies of the mass transport in two regimes of surface diffusion and bulk sintering were obtained based on this model. We conclude about a common origin of modifications of the NOA morphology, chemical composition and phase transition.

Keywords: nanostructured materials, alumina (Al₂O₃), morphology, phase transitions

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Authors: Qiuhao Chang, Liangliang Huang, Xingru Wu

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In the United States, over 90% of the roads are paved with asphalt. The aging of asphalt is the most serious problem that causes the deterioration of asphalt pavement. Waste cooking oils (WCOs) have been found they can restore the properties of aged asphalt and promote the reuse of aged asphalt pavement. In our previous study, it was found the optimal WCO concentration to restore the aged asphalt sample should be in the range of 10~15 wt% of the aged asphalt sample. After the WCO concentration exceeds 15 wt%, as the WCO concentration increases, some important properties of the asphalt sample can be weakened by the addition of WCO, such as cohesion energy density, surface free energy density, bulk modulus, shear modulus, etc. However, maximizing the utilization of WCO can create environmental and economic benefits. Therefore, in this study, a new idea about using the waste polymer is another additive to restore the WCO modified asphalt that contains a high concentration of WCO (15-25 wt%) is proposed, which has never been reported before. In this way, both waste polymer and WCO can be utilized. The molecular dynamics simulation is used to study the effect of waste polymer on properties of WCO modified asphalt and understand the corresponding mechanism at the molecular level. The radial distribution function, self-diffusion, cohesion energy density, surface free energy density, bulk modulus, shear modulus, adhesion energy between asphalt and aggregate are analyzed to validate the feasibility of combining the waste polymer and WCO to restore the aged asphalt. Finally, the optimal concentration of waste polymer and WCO are determined.

Keywords: reclaim aged asphalt pavement, waste cooking oil, waste polymer, molecular dynamics simulation

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Authors: Carla Idely Palencia-Aguilar

Abstract:

Mining in Colombia represents around 2% of the GDP (USD 8 billion in 2018), with main productions represented by coal, nickel, gold, silver, emeralds, iron, limestone, gypsum, among others. Sand and Gravel had been decreasing its participation of the GDP with a reduction of 33.2 million m3 in 2015, to 27.4 in 2016, 22.7 in 2017 and 15.8 in 2018, with a consumption of approximately 3 tons/inhabitant. However, with the new government policies it is expected to increase in the following years. Mining causes temporary environmental impacts, once restoration and rehabilitation takes place, social, environmental and economic benefits are higher than the initial state. A way to demonstrate how the mining interventions had contributed to improve the characteristics of the region after sand and gravel mining, the NDVI (Normalized Difference Vegetation Index) from MODIS and ASTER were employed. The histograms show not only increments of vegetation in the area (8 times higher), but also topographies similar to the ones before the intervention, according to the application for sustainable development selected: either agriculture, forestry, cattle raising, artificial wetlands or do nothing. The decision was based upon a Multicriteria analysis for optimal land use, with three main variables: geostatistics, evapotranspiration and groundwater characteristics. The use of remote sensing, meteorological stations, piezometers, sunphotometers, geoelectric analysis among others; provide the information required for the multicriteria decision. For cattle raising and agricultural applications (where various crops were implemented), conservation of products were tested by means of nanotechnology. The results showed a duration of 2 years with no chemicals added for preservation and concentration of vitamins of the tested products.

Keywords: ASTER, Geostatistics, MODIS, Multicriteria

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Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo, Jin-O Kim

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Home Energy Management System (HEMS) which makes the residential consumers contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it also represents impacts of the comfort level on the scheduling result.

Keywords: load scheduling, usage pattern, user’s comfort, copula function, branch and bound, electric heater

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Authors: Bilge Demir, Ahmet Durgutlu, Mustafa Acarer

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In this study, the butt welding of the commercial AZ31 magnesium alloy sheets have been carried out by using Tungsten Inert Gas (TIG) welding process with alternative and pulsed current. Welded samples were examined with regards to hardness and microstructure. Despite some recent developments in welding of magnesium alloys, they have some problems such as porosity, hot cracking, oxide formation and so on. Samples of the welded parts have undergone metallographic and mechanical examination. Porosities and homogeneous micron grain oxides were rarely observed. Orientations of the weld microstructure in terms of heat transfer also were rarely observed and equiaxed grain morphology was dominant grain structure as in the base metal. As results, fusion zone and few locations of the HAZ of the welded samples have shown twin’s grains. Hot cracking was not observed for any samples. Weld bead geometry of the welded samples were evaluated as normal according to welding parameters. In the results, conditions of alternative and pulsed current and the samples were compared to each other with regards to microstructure and hardness.

Keywords: AZ31 magnesium alloy, microstructures, micro hardness TIG welding

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Authors: Rafael Alvarenga, Hubert Herbaux, Laurent Linguet

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The uncertainty concerning the power production of intermittent renewable energy is one of the main barriers to the integration of such assets into the power grid. Efforts have thus been made to develop methods to quantify this uncertainty, allowing producers to ensure more reliable and profitable engagements related to their future power delivery. Even though a diversity of probabilistic approaches was proposed in the literature giving promising results, the added value of adopting such methods for scheduling intermittent power plants is still unclear. In this study, the profits obtained by a decision-making model used to optimally schedule an existing PV power plant connected to batteries are compared when the model is fed with deterministic and probabilistic forecasts generated with two of the most recent methods proposed in the literature. Moreover, deterministic forecasts with different accuracy levels were used in the experiments, testing the utility and the capability of probabilistic methods of modeling the progressively increasing uncertainty. Even though probabilistic approaches are unquestionably developed in the recent literature, the results obtained through a study case show that deterministic forecasts still provide the best performance if accurate, ensuring a gain of 14% on final profits compared to the average performance of probabilistic models conditioned to the same forecasts. When the accuracy of deterministic forecasts progressively decreases, probabilistic approaches start to become competitive options until they completely outperform deterministic forecasts when these are very inaccurate, generating 73% more profits in the case considered compared to the deterministic approach.

Keywords: PV power forecasting, uncertainty quantification, optimal scheduling, power systems

Procedia PDF Downloads 87