Search results for: optimal formulation
3713 Single Machine Scheduling Problem to Minimize the Number of Tardy Jobs
Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek
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Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution.Keywords: single machine scheduling, number of tardy jobs, heuristi, lower and upper bounds
Procedia PDF Downloads 5553712 Development of a Dairy Drink Made of Cocoa, Coffee and Orange By-Products with Antioxidant Activity
Authors: Gianella Franco, Karen Suarez, María Quijano, Patricia Manzano
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Agro-industries generate large amounts of waste, which are mostly untapped. This research was carried out to use cocoa, coffee and orange industrial by-products to develop a dairy drink. The product was prepared by making a 10% aqueous extract of the mixture of cocoa and coffee beans shells and orange peel. Extreme Vertices Mixture Design was applied to vary the proportions of the ingredients of the aqueous extract, getting 13 formulations. Each formulation was mixed with skim milk and pasteurized. The attributes of taste, smell, color and appearance were evaluated by a semi-trained panel by multiple comparisons test, comparing the formulations against a standard marked as "R", which consisted of a coffee commercial drink. The formulations with the highest scores were selected to maximize the Total Polyphenol Content (TPC) through a process of linear optimization resulting in the formulation 80.5%: 18.37%: 1.13% of cocoa bean shell, coffee bean shell and orange peel, respectively. The Total Polyphenol Content was 4.99 ± 0.34 mg GAE/g of drink, DPPH radical scavenging activity (%) was 80.14 ± 0.05 and caffeine concentration of 114.78 mg / L, while the coffee commercial drink presented 3.93 ± 0.84 mg GAE / g drink, 55.54 ± 0.03 % and 47.44 mg / L of TPC, DPPH radical scavenging activity and caffeine content, respectively. The results show that it is possible to prepare an antioxidant - rich drink with good sensorial attributes made of industrial by-products.Keywords: DPPH, polyphenols, waste, food science
Procedia PDF Downloads 4683711 Blast Resistance Enhancement of Structures Subjected to Improvised Explosive Devices Attack: A Numerical Study
Authors: Michael I. Okereke, Ambrose I. Akpoyomare
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This paper presents a numerical study of the impact mechanic of metallic and sandwich structures incorporate with blast resistance enhancements. The study focuses on structures that have been exposed to improvised explosives devices (IEDs) attacks. The results show numerical conclusions on mechanisms to ensure blast resistance enhancement for the applications studied in this work. The work has identified optimal panel configuration both in geometry and configurations to ensure optimal blast resistance response to such IEDs discharges. Findings from this work will drive improvements in especially military and civilian vehicles in countries where blast attacks on vehicular occupants are quite rampant like Pakistan and Afghanistan.Keywords: blast resistance, blast enhancement, explosives, material behavior
Procedia PDF Downloads 3733710 A Modified Refined Higher Order Zigzag Theory for Stress Analysis of Hybrid Composite Laminates
Authors: Dhiraj Biswas, Chaitali Ray
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A modified refined higher order zigzag theory has been developed in this paper in order to compute the accurate interlaminar stresses within hybrid laminates. Warping has significant effect on the mechanical behaviour of the laminates. To the best of author(s)’ knowledge the stress analysis of hybrid laminates is not reported in the published literature. The present paper aims to develop a new C0 continuous element based on the refined higher order zigzag theories considering warping effect in the formulation of hybrid laminates. The eight noded isoparametric plate bending element is used for the flexural analysis of laminated composite plates to study the performance of the proposed model. The transverse shear stresses are computed by using the differential equations of stress equilibrium in a simplified manner. A computer code has been developed using MATLAB software package. Several numerical examples are solved to assess the performance of the present finite element model based on the proposed higher order zigzag theory by comparing the present results with three-dimensional elasticity solutions. The present formulation is validated by comparing the results obtained from the relevant literature. An extensive parametric study has been carried out on the hybrid laminates with varying percentage of materials and angle of orientation of fibre content.Keywords: hybrid laminate, Interlaminar stress, refined higher order zigzag theory, warping effect
Procedia PDF Downloads 2243709 Optimization of Flexible Job Shop Scheduling Problem with Sequence-Dependent Setup Times Using Genetic Algorithm Approach
Authors: Sanjay Kumar Parjapati, Ajai Jain
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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times
Procedia PDF Downloads 3333708 Realization of Hybrid Beams Inertial Amplifier
Authors: Somya Ranjan Patro, Abhigna Bhatt, Arnab Banerjee
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Inertial amplifier has recently gained increasing attention as a new mechanism for vibration control of structures. Currently, theoretical investigations are undertaken by researchers to reveal its fundamentals and to understand its underline principles in altering the structural response of structures against dynamic loadings. This paper investigates experimental and analytical studies on the dynamic characteristics of hybrid beam inertial amplifier (HBIA). The analytical formulation of the HBIA has been derived by implementing the spectral element method and rigid body dynamics. This formulation gives the relation between dynamic force and the response of the structure in the frequency domain. Further, for validation of the proposed HBIA, the experiments have been performed. The experimental setup consists of a 3D printed HBIA of polylactic acid (PLA) material screwed at the base plate of the shaker system. Two numbers of accelerometers are used to study the response, one at the base plate of the shaker second one placed at the top of the inertial amplifier. A force transducer is also placed in between the base plate and the inertial amplifier to calculate the total amount of load transferred from the base plate to the inertial amplifier. The obtained time domain response from the accelerometers have been converted into the frequency domain using the Fast Fourier Transform (FFT) algorithm. The experimental transmittance values are successfully validated with the analytical results, providing us essential confidence in our proposed methodology.Keywords: inertial amplifier, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers
Procedia PDF Downloads 1033707 Optimal Number of Reconfigurable Robots in a Transport System
Authors: Mari Chaikovskaia, Jean-Philippe Gayon, Alain Quilliot
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We consider a fleet of elementary robots that can be connected in different ways to transport loads of different types. For instance, a single robot can transport a small load, and the association of two robots can either transport a large load or two small loads. We seek to determine the optimal number of robots to transport a set of loads in a given time interval, with or without reconfiguration. We show that the problem with reconfiguration is strongly NP-hard by a reduction to the bin-packing problem. Then, we study a special case with unit capacities and derive simple formulas for the minimum number of robots, up to 3 types of loads. For this special case, we compare the minimum number of robots with or without reconfiguration and show that the gain is limited in absolute value but may be significant for small fleets.Keywords: fleet sizing, reconfigurability, robots, transportation
Procedia PDF Downloads 873706 An Optimal Bayesian Maintenance Policy for a Partially Observable System Subject to Two Failure Modes
Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari
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In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control
Procedia PDF Downloads 4573705 Evaluation of Immunostimulant Potential of Proteoliposomes Derived from Vibrio anguillarum Administered by Immersion in Zebrafish (Danio rerio)
Authors: M. Caruffo, P. Navarrete, C. G. Feijoo, L. Sáenz
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Disease prevention through the use of vaccines has been crucial to achieve the current level of production in the salmon industry. However, vaccines have been developed based largely on inactivated bacterial formulations, using the whole pathogen. These formulations have demonstrated excellent efficacy against extracellular bacterial pathogens. However diseases with the greatest economic impacts correspond to intracellular bacterial and viral pathogens, vaccines based on these types of agents have shown a discrete effectiveness. It is for these reasons that the development of subunit vaccines based on defined antigens offers a promising solution. The main problem is that subunit vaccines offer a low immunogenicity, since they lack immunostimulatory elements, so that the development of new adjuvants platforms becomes an important challenge for this type of formulations. We evaluate the effect of a formulation based on proteoliposomes of Vibrio anguillarum administered by immersion as a new adjuvant strategy, allowing efficient stimulation of the innate immune system. Proteoliposomes physicochemical properties were evaluated in its ability to produce an inflammatory process. Using zebrafish (Danio rerio) larvae as a model species and the transgenic line (Tg(mpx: GFP)i114) allowed us to track the neutrophil migration in real time. Additionally we evaluated the gene expression of some molecular markers involved in the development of the innate immune response characterizing the adjuvant capacity of the formulation.Keywords: adjuvants, vaccine development, zebrafish, innate immunity
Procedia PDF Downloads 5563704 Deep Reinforcement Learning Approach for Optimal Control of Industrial Smart Grids
Authors: Niklas Panten, Eberhard Abele
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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control
Procedia PDF Downloads 1963703 A New Bound on the Average Information Ratio of Perfect Secret-Sharing Schemes for Access Structures Based on Bipartite Graphs of Larger Girth
Authors: Hui-Chuan Lu
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In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.Keywords: secret-sharing scheme, average information ratio, star covering, deduction, core cluster
Procedia PDF Downloads 3623702 Formulation and in Vitro Evaluation of Cubosomes Containing CeO₂ Nanoparticles Loaded with Glatiramer Acetate Drug
Authors: Akbar Esmaeili, Zahra Salarieh
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Cerium oxide nanoparticles (nano-series) are used as catalysts in industrial applications due to their free radical scavenging properties. Given that free radicals play an essential role in the pathology of many neurological diseases, we investigated the use of nanocrystals as a potential therapeutic agent for oxidative damage. This project synthesized nano-series from a new and environmentally friendly bio-pathway. Investigation of cerium nitrate in culture medium containing inoculated Lactobacillus acidophilus strain before incubation produces nano-series. Loaded with glatiramer acetate (GA) was formed by coating carboxymethylcellulose (CMC) and CeO2. FE-SEM analysis showed nano-series in the 9-11 nm range, spherical shape, and uniform particle size distribution. Cubic nanoparticles containing anti-multiple sclerosis (anti-Ms) treatment called GA were used. Glycerol monostearate (GMS) was used as a fat base, and evening primrose extract was used as an anti-inflammatory in cubosomes. Design-Expert® software was used to study the effects of different formulation factors on the properties of GAloaded cubic dispersions. Thirty GA-labeled cubic dispersions were prepared with GA-labeled carboxymethylcellulose and evaluated in vitro. The results showed an average nano-series size of 89.02 and a zeta potential of -49.9. Cubosomes containing GA-CMC/CeO2 showed a stable release profile for 180 min. The results showed that cubosomes containing GA-CMC/CeO2 could be a promising drug carrier with normal release behavior.Keywords: ciochemistry, biotechnology, molecular, biology
Procedia PDF Downloads 533701 Stability-Indicating High-Performance Thin-Layer Chromatography Method for Estimation of Naftopidil
Authors: P. S. Jain, K. D. Bobade, S. J. Surana
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A simple, selective, precise and Stability-indicating High-performance thin-layer chromatographic method for analysis of Naftopidil both in a bulk and in pharmaceutical formulation has been developed and validated. The method employed, HPTLC aluminium plates precoated with silica gel as the stationary phase. The solvent system consisted of hexane: ethyl acetate: glacial acetic acid (4:4:2 v/v). The system was found to give compact spot for Naftopidil (Rf value of 0.43±0.02). Densitometric analysis of Naftopidil was carried out in the absorbance mode at 253 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.999±0.0001 with respect to peak area in the concentration range 200-1200 ng per spot. The method was validated for precision, recovery and robustness. The limits of detection and quantification were 20.35 and 61.68 ng per spot, respectively. Naftopidil was subjected to acid and alkali hydrolysis, oxidation and thermal degradation. The drug undergoes degradation under acidic, basic, oxidation and thermal conditions. This indicates that the drug is susceptible to acid, base, oxidation and thermal conditions. The degraded product was well resolved from the pure drug with significantly different Rf value. Statistical analysis proves that the method is repeatable, selective and accurate for the estimation of investigated drug. The proposed developed HPTLC method can be applied for identification and quantitative determination of Naftopidil in bulk drug and pharmaceutical formulation.Keywords: naftopidil, HPTLC, validation, stability, degradation
Procedia PDF Downloads 4003700 Optimal Simultaneous Sizing and Siting of DGs and Smart Meters Considering Voltage Profile Improvement in Active Distribution Networks
Authors: T. Sattarpour, D. Nazarpour
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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)
Procedia PDF Downloads 3033699 Optimal Hybrid Linear and Nonlinear Control for a Quadcopter Drone
Authors: Xinhuang Wu, Yousef Sardahi
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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones
Procedia PDF Downloads 733698 An Efficient Robot Navigation Model in a Multi-Target Domain amidst Static and Dynamic Obstacles
Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi
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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles
Procedia PDF Downloads 2813697 Effect of Additives on Post-hydrogen Decompression Microstructure and Mechanical Behaviour of PA11 Involved in Type-IV Hydrogen Tank Liners
Authors: Mitia Ramarosaona, Sylvie Castagnet, Damien Halm, Henri-Alexandre Cayzac, Nicolas Dufaure, Philippe Papin
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In light of the ongoing energy transition, 'Infrastructure developments' for hydrogen transportation and storage raise studies on the materials employed for hyperbaric vessels. Type IV tanks represent the most mature choice for gaseous hydrogen storage at high pressure – 70MPa. These tanks are made of a composite shell and an internal hydrogen-exposed polymer liner. High pressure conditions lead to severe mechanical loading requiring high resistance. Liner is in contact with hydrogen and undergoes compression – decompression cycles during system filling and emptying. Stresses induced by this loading, coupled with hydrogen diffusion, were found to cause microstructural changes and degradation of mechanical behaviour after decompression phase in some studies on HDPE. These phenomena are similar to those observed in elastomeric components like sealing rings, which can affect permeability and lead to their failure. They may lead to a hydrogen leak, compromising security and tightness of the tank. While these phenomena have been identified in elastomers, they remain less addressed in thermoplastics and consequences post-decompression damages on mechanical behaviour and to the best of author's knowledge was not studied either. Different additives are also included in liner formulation to improve its behaviour. This study aimed to better understand damage micro-mechanisms in PA11s exposed to hydrogen compression-decompression cycles and understand if additives influence their resistance. Samples of pure, plasticized and impact-modified PA11s are exposed to 1, 3 and 8 pressure cycles including hydrogen saturation at 70MPa followed by severe 15-second decompression. After hydrogen exposure and significantly later than full desorption, the residual mechanical behaviour is characterized through impact and monotonic tensile tests, on plain and notched samples. Several techniques of microstructure and micro-nano damage characterization are carried out to assess whether changes in macroscopic properties are driven by microstructural changes in the crystalline structure (SAXS-WAXS acquisitions and SEM micrographs). Thanks to WAXS acquisition and microscopic observation, the effects due to additives and pressure consequences can be decorrelated. Pure PA11 and PA11 with a low percentage of additives show an increase in stress level at the first yielding point after hydrogen cycles. The amplitude of the stress increase is more important in formulation with additives because of changes in PA11 matrix behavior and environment created by additives actions. Plasticizer modifies chain mobility leading to microstructure changes while other additives, more ductile than PA11, is able to cavitate inside PA11 matrix when undergoing decompression. On plasticized formulation, plasticizer migration are suspected to enhance impact of hydrogen cycling on mechanical behaviour. Compared to the literature on HDPE and elastomers, no damages like cavitation or cracking could be evidenced from SAXS experiments on every PA11 formulation tested. In perspectives, on all formulation, experimental work is underway to confirm influence of residual pressure level after decompression on post-decompression damages level, the aim is to better understand the factors affecting the mechanical behavior of thermoplastics subject to mechanical solicitation from decompression in hydrogen tank liners, not mechanical behaviour of liner in hydrogen tanks directly.Keywords: additives, hydrogen tank liner, microstructural analysis, PA11
Procedia PDF Downloads 473696 Pharmacokinetic and Tissue Distribution of Etoposide Loaded Modified Glycol Chitosan Nanoparticles
Authors: Akhtar Aman, Abida Raza, Shumaila Bashir, Mehboob Alam
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The development of efficient delivery systems remains a major concern in cancer chemotherapy as many efficacious anticancer drugs are hydrophobic and difficult to formulate. Nanomedicines based on drug-loaded amphiphilic glycol chitosan micelles offer potential advantages for the formulation of drugs such as etoposide that may improve the pharmacokinetics and reduce the formulation-related adverse effects observed with current formulations. Amphiphilic derivatives of glycol chitosan were synthesized by chemical grafting of palmitic acid N-hydroxysuccinimide and quaternization to glycol chitosan backbone. To this end, a 7.9 kDa glycol chitosan was modified by palmitoylation and quaternization, yielding a 13 kDa amphiphilic polymer. Micelles prepared from this amphiphilic polymer had a size of 162nm and were able to encapsulate up to 3 mg/ml etoposide. Pharmacokinetic results indicated that the GCPQ micelles transformed the biodistribution pattern and increased etoposide concentration in the brain significantly compared to free drugs after intravenous administration. AUC 0.5-24h showed statistically significant difference in ETP-GCPQ vs. Commercial preparation in liver (25 vs.70, p<0.001), spleen (27 vs.36, p<0.05), lungs (42 vs.136,p<0.001),kidneys(25 vs.70,p< 0.05),and brain(19 vs.9,p<0.001). ETP-GCPQ crossed the blood-brain barrier, and 4, 3.5, 2.6, 1.8, 1.7, 1.5, and 2.5 fold higher levels of etoposide were observed at 0.5, 1, 2, 4, 6, 12, and 24hrs; respectively suggesting these systems could deliver hydrophobic anticancer drugs such as etoposide to tumors but also increased their transport through the biological barriers, thus making it a good delivery systemKeywords: glycol chitosan, micelles, pharmacokinetics, tissue distribution
Procedia PDF Downloads 1053695 Computer-Assisted Management of Building Climate and Microgrid with Model Predictive Control
Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak
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With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.Keywords: price-optimal building climate control, Microgrid power flow optimisation, hierarchical model predictive control, energy efficient buildings, energy market participation
Procedia PDF Downloads 4663694 Inventory Decisions for Perishable Products with Age and Stock Dependent Demand Rate
Authors: Maher Agi, Hardik Soni
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This paper presents a deterministic model for optimized control of the inventory of a perishable product subject to both physical deterioration and degradation of its freshness condition. The demand for the product depends on its current inventory level and freshness condition. Our model allows for any positive amount of end of cycle inventory. Some useful conditions that characterize the optimal solution of the model are derived and an algorithm is presented for finding the optimal values of the price, the inventory cycle, the end of cycle inventory level and the order quantity. Numerical examples are then given. Our work shows how the product freshness in conjunction with the inventory deterioration affects the inventory management decisions.Keywords: inventory management, lot sizing, perishable products, deteriorating inventory, age-dependent demand, stock-dependent demand
Procedia PDF Downloads 2353693 Intelligent Minimal Allocation of Capacitors in Distribution Networks Using Genetic Algorithm
Authors: S. Neelima, P. S. Subramanyam
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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction
Procedia PDF Downloads 3923692 Nitrogen, Phosphorus, Potassium (NPK) Hydroxyapatite Nano-Hybrid Slow Release Fertilizer
Authors: Tinomuvonga Manenji Zhou, Eubert Mahofa, Tatenda Crispen Madzokere
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The nanostructured formulation can increase fertilizer efficacy and uptake ratio of the soil nutrients in agriculture production and save fertilizer resources. Controlled release modes have properties of both release rate and release pattern of nutrients, for fertilizers that are soluble in water might be correctly controlled. Nanoparticles can reduce the rate at which fertilizer nutrients are in the soil by leaching. A slow release NPK-hydroxyapatite nano hybrid fertilizer was synthesized using exfoliated bentonite as filler material. A simple, scalable method was used to synthesize the nitrogen-phosphorus hydroxyapatite nano fertilizer, where calcium hydroxide, phosphoric acid, and urea were used as precursor material, followed by the incorporation of potassium through a liquid grinding method. The product obtained was an NPK-hydroxyapatite nano hybrid fertilizer. A quantitative analysis was done to determine the percentage of nitrogen, phosphorus, and potassium in the hybrid fertilizer. AAS was used to determine the percentage of potassium in the fertilizer. An accelerated water test was conducted to compare the nutrient release behavior of nutrients between the synthesized NPK-hydroxyapatite nano hybrid fertilizer and commercial NPK fertilizer. The rate of release of Nitrogen, phosphorus, and potassium was significantly lower in the synthesized NPK hydroxyapatite nano hybrid fertilizer than in the convectional NPK fertilizer. The synthesized fertilizer was characterized using XRD. NPK hydroxyapatite nano hybrid fertilizer encapsulated in exfoliated bentonite thus prepared can be used as an environmentally friendly fertilizer formulation which could be extended to solve one of the major problems faced in the global fertilization of low nitrogen, phosphorus, and potassium use efficiency in agriculture.Keywords: NPK hydroxyapatite nano hybrid fertilizer, bentonite, encapsulation, low release
Procedia PDF Downloads 973691 Off-Policy Q-learning Technique for Intrusion Response in Network Security
Authors: Zheni S. Stefanova, Kandethody M. Ramachandran
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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.Keywords: cyber security, intrusion prevention, optimal policy, Q-learning
Procedia PDF Downloads 2393690 Enhancement of Tribological Behavior for Diesel Engine Piston of Solid Skirt by an Optimal Choice of Interface Material
Authors: M. Amara, M. Tahar Abbes, A. Dokkiche, M. Benbrike
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Shear stresses generate frictional forces thus lead to the reduction of engine performance due to the power losses. This friction can also cause damage to the piston material. Thus, the choice of an optimal material for the piston is necessary to improve the elastohydrodynamical contacts of the piston. In this study, to achieve this objective, an elastohydrodynamical lubrication model that satisfies the best tribological behavior of the piston with the optimum choice of material is developed. Several aluminum alloys composed of different components are studied in this simulation. An application is made on the piston 60 x 120 mm Diesel engine type F8L413 currently mounted on Deutz trucks TB230 by using different aluminum alloys where alloys based on aluminum-silicon have better tribological performance.Keywords: EHD lubricated contacts, friction, properties of materials, tribological performance
Procedia PDF Downloads 2723689 Simulation Data Summarization Based on Spatial Histograms
Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura
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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.Keywords: simulation data, data summarization, spatial histograms, exploration, visualization
Procedia PDF Downloads 1773688 Pressure-Controlled Dynamic Equations of the PFC Model: A Mathematical Formulation
Authors: Jatupon Em-Udom, Nirand Pisutha-Arnond
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The phase-field-crystal, PFC, approach is a density-functional-type material model with an atomic resolution on a diffusive timescale. Spatially, the model incorporates periodic nature of crystal lattices and can naturally exhibit elasticity, plasticity and crystal defects such as grain boundaries and dislocations. Temporally, the model operates on a diffusive timescale which bypasses the need to resolve prohibitively small atomic-vibration time steps. The PFC model has been used to study many material phenomena such as grain growth, elastic and plastic deformations and solid-solid phase transformations. In this study, the pressure-controlled dynamic equation for the PFC model was developed to simulate a single-component system under externally applied pressure; these coupled equations are important for studies of deformable systems such as those under constant pressure. The formulation is based on the non-equilibrium thermodynamics and the thermodynamics of crystalline solids. To obtain the equations, the entropy variation around the equilibrium point was derived. Then the resulting driving forces and flux around the equilibrium were obtained and rewritten as conventional thermodynamic quantities. These dynamics equations are different from the recently-proposed equations; the equations in this study should provide more rigorous descriptions of the system dynamics under externally applied pressure.Keywords: driving forces and flux, evolution equation, non equilibrium thermodynamics, Onsager’s reciprocal relation, phase field crystal model, thermodynamics of single-component solid
Procedia PDF Downloads 3053687 Enhanced Photoelectrochemical performance of TiO₂ Nanorods: The Critical Role of Hydrothermal Reaction Time
Authors: Srijitra Khanpakdee, Teera Butburee, Jung-Ho Yun, Miaoqiang Lyu, Supphasin Thaweesak, Piangjai Peerakiatkhajohn
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The synthesis of titanium dioxide (TiO₂) nanorods (NRs) on fluorine-doped tin oxide (FTO) glass via hydrothermal methods was investigated to determine the optimal reaction time for enhanced photocatalytic and optical performance. Reaction times of 4, 6, and 8 hours were studied. Characterization through SEM, UV-vis, XRD, FTIR, Raman spectroscopy and photoelectrochemical (PEC) techniques revealed significant differences in the properties of the TiO₂ NRs based on the reaction duration. XRD and Raman spectroscopy analysis confirmed the formation of the rutile phase of TiO₂. As photoanodes in PEC cells, TiO₂ NRs synthesized for 4 hours exhibited the best photocatalytic activity, with the highest photocurrent density and superior charge transport properties, attributed to their densely packed vertical structure. Longer reaction times resulted in less optimal morphological and photoelectrochemical characteristics. The bandgap of the TiO₂ NRs remained consistent around 3.06 eV, with only slight variations observed. This study highlights the critical role of reaction time in hydrothermal synthesis, identifying 4 hours as the optimal duration for producing TiO₂ NRs with superior photoelectrochemical performance. These findings provide valuable insights for optimizing TiO₂-based materials for solar energy conversion and renewable energy applications.Keywords: titanium dioxide, nanorods, hydrothermal, photocatalytic, photoelectrochemical
Procedia PDF Downloads 443686 Surfactant-Assisted Aqueous Extraction of Residual Oil from Palm-Pressed Mesocarp Fibre
Authors: Rabitah Zakaria, Chan M. Luan, Nor Hakimah Ramly
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The extraction of vegetable oil using aqueous extraction process assisted by ionic extended surfactant has been investigated as an alternative to hexane extraction. However, the ionic extended surfactant has not been commercialised and its safety with respect to food processing is uncertain. Hence, food-grade non-ionic surfactants (Tween 20, Span 20, and Span 80) were proposed for the extraction of residual oil from palm-pressed mesocarp fibre. Palm-pressed mesocarp fibre contains a significant amount of residual oil ( 5-10 wt %) and its recovery is beneficial as the oil contains much higher content of vitamin E, carotenoids, and sterols compared to crude palm oil. In this study, the formulation of food-grade surfactants using a combination of high hydrophilic-lipophilic balance (HLB) surfactants and low HLB surfactants to produce micro-emulsion with very low interfacial tension (IFT) was investigated. The suitable surfactant formulation was used in the oil extraction process and the efficiency of the extraction was correlated with the IFT, droplet size and viscosity. It was found that a ternary surfactant mixture with a HLB value of 15 (82% Tween 20, 12% Span 20 and 6% Span 80) was able to produce micro-emulsion with very low IFT compared to other HLB combinations. Results suggested that the IFT and droplet size highly affect the oil recovery efficiency. Finally, optimization of the operating parameters shows that the highest extraction efficiency of 78% was achieved at 1:31 solid to liquid ratio, 2 wt % surfactant solution, temperature of 50˚C, and 50 minutes contact time.Keywords: food-grade surfactants, aqueous extraction of residual oil, palm-pressed mesocarp fibre, interfacial tension
Procedia PDF Downloads 3913685 Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System
Authors: S. Gherbi, F. Bouchareb
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This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method.Keywords: delayed systems, fuzzy immune PID, optimization, Smith predictor
Procedia PDF Downloads 4353684 DG Allocation to Reduce Production Cost by Reducing Losses in Radial Distribution Systems Using Fuzzy
Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao
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Electrical energy is vital in every aspect of day-to-day life. Keen interest is taken on all possible sources of energy from which it can be generated and this led to the encouragement of generating electrical power using renewable energy resources such as solar, tidal waves and wind energy. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss and reduction in operational cost, etc. To reduce production cost, it is important to minimize the losses by determining the location and size of local generators to be placed in the radial distribution systems. In this paper, reduction of production cost by optimal size of DG unit operated at optimal power factor is dealt. The optimal size of the DG unit is calculated analytically using approximate reasoning suitable nodes and DG placement to minimize production cost with minimum loss is determined by fuzzy technique. Total Cost of Power generation is compared with and without DG unit for 1 year duration. The suggested method is programmed under MATLAB software and is tested on IEEE 33 bus system and the results are presented.Keywords: distributed generation, operational cost, exact loss formula, optimum size, optimum location
Procedia PDF Downloads 485