Search results for: dispersed particle swarm optimization (DPSO)

Authors: Meimei Zheng

Abstract:

Product personalization could not only bring new profits to companies but also provide the direction of long-term development for companies. However, the characteristics of personalized product cause some new problems. This paper investigates how companies make decisions on the supply of personalized products when facing different customer attitudes to personalized product and service, constraints due to limited capacity and updates of personalized demand information. This study will provide optimal decisions for companies to develop personalized markets, resulting in promoting business transformation and improving business competitiveness.

Keywords: demand forecast updating, limited capacity, personalized products, optimization

Procedia PDF Downloads 266

Authors: Ilkay Turk Cakir, Murat Altinli, Zekeriya Uysal, Abdulkadir Senol, Olcay Bolukbasi Yalcinkaya, Ali Yilmaz

Abstract:

The Higgs boson was discovered by the ATLAS and CMS experimental groups in 2012 at the Large Hadron Collider (LHC). Production and decay properties of the Higgs boson, Standard Model (SM) couplings, and limits on effective scale of the Higgs boson’s couplings with other bosons are investigated at particle colliders. Deviations from SM estimates are parametrized by effective Lagrangian terms to investigate Higgs couplings. This is a model-independent method for describing the new physics. In this study, sensitivity to neutral gauge boson anomalous couplings with the Higgs boson is investigated using the parameters of the Large Hadron electron Collider (LHeC) and the Future Circular electron-hadron Collider (FCC-eh) with a model-independent approach. By using MadGraph5_aMC@NLO multi-purpose event generator with the parameters of LHeC and FCC-eh, the bounds on the anomalous Hγγ, HγZ and HZZ couplings in e− p → e− q H process are obtained. Detector simulations are also taken into account in the calculations.

Keywords: anomalos couplings, FCC-eh, Higgs, Z boson

Procedia PDF Downloads 214

Authors: Paul C. Njoku, Archana Swati Njoku

Abstract:

The study deals with the development of a mathematical model to characterize the oil production in Nigeria. This is calculated by initiating the dynamics of oil production in million barrels revenue plan cost of oil production in million nairas and unit cost of production from 1974-1982 in the contest of the federal Republic of Nigeria. This country export oil to other countries as well as importing specialized crude. The transport network from origin/destination tij to pairs is taking into account simulation runs, optimization have been considered in this study.

Keywords: mathematical oil model development dynamics, Nigeria, characterization barrels, dynamics of oil production

Procedia PDF Downloads 390

Authors: Naci Kalkan, Ihsan Dagtekin

Abstract:

Passive design responds to improve indoor thermal comfort and minimize the energy consumption. The present research analyzed the how efficiently passive solar technologies generate heating and cooling and provide the system integration for domestic applications. In addition to this, the aim of this study is to increase the efficiency of solar systems system with integration some innovation and optimization. As a result, outputs of the project might start a new sector to provide environmentally friendly and cheap cooling for domestic use.

Keywords: passive solar systems, heating, cooling, thermal comfort, ventilation systems

Procedia PDF Downloads 304

Authors: Z. Babic, I. Veza, A. Balic, M. Crnjac

Abstract:

The linear programming model is sometimes difficult to apply in real business situations due to its assumption of proportionality. This paper shows an example of how to use De Novo programming approach instead of linear programming. In the De Novo programming, resources are not fixed like in linear programming but resource quantities depend only on available budget. Budget is a new, important element of the De Novo approach. Two different production situations are presented: increasing costs and quantity discounts of raw materials. The focus of this paper is on advantages of the De Novo approach in the optimization of production plan for production company which produces souvenirs made from famous stone from the island of Brac, one of the greatest islands from Croatia.

Keywords: business process, De Novo programming, optimizing, production

Procedia PDF Downloads 225

Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

Abstract:

We consider a linear programming model to help farmers to decide if it is convinient to choose among three kinds of export fruits for their future investment. We consider area, investment, water, productivitiy minimal unit, and harvest restrictions and a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability and initia investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market.

Keywords: mixed integer problem, fruit production, support decision model, fruit tree farms

Procedia PDF Downloads 460

Authors: Mohammad Abu-Shaira, Weishi Shi

Abstract:

Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

Procedia PDF Downloads 21

Authors: Mostafa Rezaee Saraji, Ali Keshavarz Panahi

Abstract:

In this work, the processing steps for producing alumina parts using powder injection molding (PIM) technique and nano-powder were investigated and the thermal conductivity and flexural strength of samples were determined as a function of sintering temperature and holding time. In the first step, the feedstock with 58 vol. % of alumina nano-powder with average particle size of 100nm was prepared using Extrumixing method to obtain appropriate homogeneity. This feedstock was injection molded into the two cavity mold with rectangular shape. After injection molding step, thermal and solvent debinding methods were used for debinding of molded samples and then these debinded samples were sintered in different sintering temperatures and holding times. From the results, it was found that the flexural strength and thermal conductivity of samples increased by increasing sintering temperature and holding time; in sintering temperature of 1600ºC and holding time of 5h, the flexural strength and thermal conductivity of sintered samples reached to maximum values of 488MPa and 40.8 W/mK, respectively.

Keywords: alumina nano-powder, thermal conductivity, flexural strength, powder injection molding

Procedia PDF Downloads 332

Authors: J. Satya Eswari, J. Sekhar Babub, Meena Murmu, Govardhan Bhat

Abstract:

Electrical Discharge Machining (EDM) is an unconventional manufacturing process based on removal of material from a part by means of a series of repeated electrical sparks created by electric pulse generators at short intervals between a electrode tool and the part to be machined emmersed in dielectric fluid. In this paper, a study will be performed on the influence of the factors of peak current, pulse on time, interval time and power supply voltage. The output responses measured were material removal rate (MRR) and surface roughness. Finally, the parameters were optimized for maximum MRR with the desired surface roughness. RSM involves establishing mathematical relations between the design variables and the resulting responses and optimizing the process conditions. RSM is not free from problems when it is applied to multi-factor and multi-response situations. Design of experiments (DOE) technique to select the optimum machining conditions for machining AISI 4140 using EDM. The purpose of this paper is to determine the optimal factors of the electro-discharge machining (EDM) process investigate feasibility of design of experiment techniques. The work pieces used were rectangular plates of AISI 4140 grade steel alloy. The study of optimized settings of key machining factors like pulse on time, gap voltage, flushing pressure, input current and duty cycle on the material removal, surface roughness is been carried out using central composite design. The objective is to maximize the Material removal rate (MRR). Central composite design data is used to develop second order polynomial models with interaction terms. The insignificant coefficients’ are eliminated with these models by using student t test and F test for the goodness of fit. CCD is first used to establish the determine the optimal factors of the electro-discharge machining (EDM) for maximizing the MRR. The responses are further treated through a objective function to establish the same set of key machining factors to satisfy the optimization problem of the electro-discharge machining (EDM) process. The results demonstrate the better performance of CCD data based RSM for optimizing the electro-discharge machining (EDM) process.

Keywords: electric discharge machining (EDM), modeling, optimization, CCRD

Procedia PDF Downloads 344

Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

Abstract:

The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

Procedia PDF Downloads 64

Authors: I .Ait El Harch, K. Outaaoui, Y. El Foutayeni

Abstract:

This study aims to deepen the understanding and optimize fishing activity in Morocco by holistically integrating biological and economic aspects. We develop a biological equilibrium model in which these competing species present their natural growth by logistic equations, taking into account density and competition between them. The integration of human intervention adds a realistic dimension to our model. A company specifically targets the three species, thus influencing population dynamics according to their fishing activities. The aim of this work is to determine the fishing effort that maximizes the company’s profit, taking into account the constraints associated with conserving ecosystem equilibrium.

Keywords: bioeconomical modeling, optimization techniques, linear complementarity problem LCP, biological equilibrium, maximizing profits

Procedia PDF Downloads 31

Authors: Sarah Triller, Ferdi Schüth

Abstract:

The challenges encountered in upscaling the mechanochemical synthesis of high surface area α-alumina are investigated in this study. After lab-scale experiments in shaker mills and planetary ball mills, the optimization of reaction parameters of the conversion in the smallest vessel of a scalable mill, named Simoloyer, was developed. Furthermore, the future perspectives by scaling up the conversion in several steps are described. Since abrasion from the steel equipment can be problematic, the process was transferred to a ceramically lined mill, which solved the contamination problem. The recovered alpha-alumina shows a high specific surface area in all investigated scales.

Keywords: mechanochemistry, scale-up, ball milling, ceramic lining

Procedia PDF Downloads 71

Authors: Kai Jin, Hua Li, Qing Song

Abstract:

Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

Procedia PDF Downloads 520

Authors: Jian Wang, Lu Yang, Jiong Peng

Abstract:

Internal circulation two-platen clamping system for injection molding machine (IMM) has many potential advantages on energy-saving. In order to estimate its properties, experiments in this paper were carried out. Displacement and pressure of the components were measured. In comparison, the model of hydraulic clamping system was established by using AMESim. The related parameters as well as the energy consumption could be calculated. According to the analysis, the hydraulic system was optimized in order to reduce the energy consumption.

Keywords: AMESim, energy-saving, injection molding machine, internal circulation

Procedia PDF Downloads 555

Authors: Iyai Davies, Olivier L. C. Haas

Abstract:

In this paper, the problem of stability and stabilization for neutral delay-differential systems with infinite delay is investigated. Using Lyapunov method, new delay-independent sufficient condition for the stability of neutral systems with infinite delay is obtained in terms of linear matrix inequality (LMI). Memory-less state feedback controllers are then designed for the stabilization of the system using the feasible solution of the resulting LMI, which are easily solved using any optimization algorithms. Numerical examples are given to illustrate the results of the proposed methods.

Keywords: infinite delays, Lyapunov method, linear matrix inequality, neutral systems, stability

Procedia PDF Downloads 433

Authors: Reza Hedayati, Meysam Jahanbakhshi

Abstract:

Elastic energy absorbers which consist of a ring-liked plate and springs can be a good choice for increasing the impact duration during an accident. In the current project, an energy absorber system is optimized using four optimizing methods Kuhn-Tucker, Sequential Linear Programming (SLP), Concurrent Subspace Design (CSD), and Pshenichny-Lim-Belegundu-Arora (PLBA). Time solution, convergence, Programming Length and accuracy of the results were considered to find the best solution algorithm. Results showed the superiority of PLBA over the other algorithms.

Keywords: Concurrent Subspace Design (CSD), Kuhn-Tucker, Pshenichny-Lim-Belegundu-Arora (PLBA), Sequential Linear Programming (SLP)

Procedia PDF Downloads 401

Authors: Nadim Zgheib, Sivaramakrishnan Balachandar

Abstract:

We present results on the initial formation of ripples from an initially flattened erodible bed. We use direct numerical simulations (DNS) of turbulent open channel flow over a fixed sinusoidal bed coupled with hydrodynamic stability analysis. We use the direct forcing immersed boundary method to account for the presence of the sediment bed. The resolved flow provides the bed shear stress and consequently the sediment transport rate, which is needed in the stability analysis of the Exner equation. The approach is different from traditional linear stability analysis in the sense that the phase lag between the bed topology, and the sediment flux is obtained from the DNS. We ran 11 simulations at a fixed shear Reynolds number of 180, but for different sediment bed wavelengths. The analysis allows us to sweep a large range of physical and modelling parameters to predict their effects on linear growth. The Froude number appears to be the critical controlling parameter in the early linear development of ripples, in contrast with the dominant role of particle Reynolds number during the equilibrium stage.

Keywords: direct numerical simulation, immersed boundary method, sediment-bed interactions, turbulent multiphase flow, linear stability analysis

Procedia PDF Downloads 191

Authors: Piotr Jerzy Rugor, Julia Wajoras

Abstract:

The presented work regards a single-stage aerodynamically controlled solid propulsion rocket. Steering a rocket to fly along a predetermined trajectory can be beneficial for minimizing aerodynamic losses and achieved by implementing an active control system on board. In this particular case, a canard configuration has been chosen, although other methods of control have been considered and preemptively analyzed, including non-aerodynamic ones. The objective of this work is to create a system capable of guiding the rocket, focusing on roll stabilization. The paper describes initial analysis of the problem, covers the main challenges of missile guidance and presents data acquired during the experimental study.

Keywords: active canard control system, rocket design, numerical simulations, flight optimization

Procedia PDF Downloads 196

Authors: Chanunya Fahwan, Supat Chaiyakul

Abstract:

A lactose-free diet is imperative for those with lactose intolerance and experiencing milk intolerance. This entails eliminating milk-based products, which may result in dietary and nutritional challenges and the main problems of Lactose hydrolyzed milk powder during production were the adhesion in the drying chamber and low-yield and low-quality powder. The use of lactose-free milk to produce lactose-free milk powder was studied here. Development of two milk powder formulas from cow's milk and lactose-free cow's milk by using a substitute for maltodextrin, Polydextrose (PDX), Resistant Starch (RS), Cellobiose (CB), and Resistant Maltodextrin (RMD) to improve quality and reduce the glycemic index from maltodextrin, which are carriers that were used in industry at three experimental levels 10%, 15% and 20% the properties of milk powder were studied such as color, moisture content, percentage yield (%yield) and solubility index. The experiment revealed that prebiotic carriers could replace maltodextrin and improve quality, such as solubility and percentage yield, and enriched nutrients, such as dietary fiber. CB, RMD, and PDX are three possible carriers, which are applied to both regular cow's milk formula and lactose-free cow milk.

Keywords: lactose-free milk powder, prebiotic carrier, co-particle, glycemic index

Procedia PDF Downloads 90

Authors: Hassan M. Al-Ahmadi, Hamad Bader Almobayedh

Abstract:

Planning for urban transportation is essential for developing effective and sustainable transportation networks that meet the needs of various communities. Advanced modeling software is required for effective transportation planning, management, and optimization. This paper compares PTV VISUM, Aimsun, TransCAD, and Emme, four industry-leading software tools for transportation planning and modeling. Each software has strengths and limitations, and the project's needs, financial constraints, and level of technical expertise influence the choice of software. Transportation experts can design and improve urban transportation systems that are effective, sustainable, and meet the changing needs of their communities by utilizing these software tools.

Keywords: PTV VISUM, Aimsun, TransCAD, transportation modeling software

Procedia PDF Downloads 37

Authors: Lukas Munster, Pavel Bazant, Ivo Kuritka

Abstract:

Zinc oxide sub-micro particles and metallic silver nano particles (Ag/ZnO) were deposited on micro crystalline cellulose surface by a fast, simple and environmentally friendly one-pot microwave assisted solvo thermal synthesis in an open vessel system equipped with an external reflux cooler. In order to increase the interaction between the surface of cellulose and the precipitated Ag/ZnO particles, oxidized form of cellulose (cellulose dialdehyde, DAC) prepared by periodate oxidation of micro crystalline cellulose was added to the reaction mixture of Ag/ZnO particle precursors and untreated micro crystalline cellulose. The structure and morphology of prepared hybrid powder materials were analysed by X-ray diffraction (XRD), energy dispersive analysis (EDX), scanning electron microscopy (SEM) and nitrogen absorption method (BET). Microscopic analysis of the prepared materials treated by ultra-sonication showed that Ag/ZnO particles deposited on the cellulose/DAC sample exhibit increased adhesion to the surface of the cellulose substrate which can be explained by the DAC adhesive effect in comparison with the material prepared without DAC addition.

Keywords: microcrystalline cellulose, microwave synthesis, silver nanoparticles, zinc oxide sub-microparticles, cellulose dialdehyde

Procedia PDF Downloads 482

Authors: Vipan Kumar Sohpal, Rajesh Kumar Sharma

Abstract:

Thermo-chemical conversion of non-edible biomass offers an efficient and economically process to provide valuable fuels and prepare chemicals derived from biomass in the context of developing countries. Pyrolysis has advantages over other thermochemical conversion techniques because it can convert biomass directly into solid, liquid and gaseous products by thermal decomposition of biomass in the absence of oxygen. The present paper aims to focus on the slow thermochemical conversion processes for non-edible Jatropha curcus seed cake. The present discussion focuses on the effect of nitrogen gas flow rate on products composition (wt %). In addition, comparative analysis has been performed for different mesh size for product composition. Result shows that, slow pyrolysis experiments of Jatropha curcus seed cake in fixed bed reactor yield the bio-oil 18.42 wt % at a pyrolysis temperature of 500°C, particle size of -6+8 mesh number and nitrogen gas flow rate of 150 ml/min.

Keywords: Jatropha curcus, thermo-chemical, pyrolysis, product composition, yield

Procedia PDF Downloads 438

Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

Abstract:

Elliptic curve discrete logarithm problem (ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard's rho method to evaluate the security of ECDLP on Barreto-Naehrig (BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard's rho method, BN curve, Montgomery multiplication

Procedia PDF Downloads 275

Authors: Andreas D. Jansson

Abstract:

The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.

Keywords: autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation

Procedia PDF Downloads 141

Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

Abstract:

This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

Procedia PDF Downloads 710

Authors: Gulfam Haider, sana danish

Abstract:

Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

Procedia PDF Downloads 133

Authors: Riccardo Loggia, Francesca Pizzimenti, Francesco Lelli, Luigi Martirano

Abstract:

Recent air emission regulations point toward the complete electrification of road vehicles. An increasing number of users are beginning to prefer full electric or hybrid, plug-in vehicle solutions, incentivized by government subsidies and the lower cost of electricity compared to gasoline or diesel. However, it is necessary to optimize charging stations so that they can simultaneously satisfy as many users as possible. The purpose of this paper is to present optimization algorithms that enable simultaneous charging of multiple electric vehicles while ensuring maximum performance in relation to the type of charging station.

Keywords: electric vehicles, charging stations, sharing model, fast charging, car park, power profiles

Procedia PDF Downloads 158

Authors: Shahnaz Mansouri, David Martin, Xiao Dong Chen, Meng Wai Woo

Abstract:

Ultrafine hydrophobic and non-water-soluble drugs can increase the percentage of absorbed compared to their initial dosage. This paper provides a scalable new method of making ultrafine particles of substantially insoluble water compounds specifically, submicron particles of ethanol soluble and water insoluble pharmaceutical materials by steaming an ethanol droplet to prepare a suspension and then followed by immediate drying. This suspension is formed by adding evaporated water molecules as an anti-solvent to the solute of the samples and in early stage of precipitation continued to dry by evaporating both solvent and anti-solvent. This fine particle formation has produced fast dispersion powder in water. The new method is an extension of the antisolvent vapour precipitation technique which exposes a droplet to an antisolvent vapour with reference to the dissolved materials within the droplet. Ultrafine vitamin D3 and ibuprofen particles in the submicron ranges were produced. This work will form the basis for using spray dryers as high-throughput scalable micro-precipitators.

Keywords: single droplet drying, nano size particles, non-water-soluble drugs, precipitators

Procedia PDF Downloads 486

Authors: R. Ouafi, F. Ouafi

Abstract:

We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern.

Keywords: combinatorial optimization, cutting problem, heuristic

Procedia PDF Downloads 542

Authors: Bi Wa, Su-Yeon Kwon, Ik-Joong Kang

Abstract:

Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. In this case, the Mercaptopropionic Acid (MPA) is used to modified chitosan –gold nanoshell, which enhances the absorption between GABA and Chitosan-gold nanoshell. The sulfur end of the MPA is linked to gold which is the surface of the chitosan nanoparticles via the very strong S–Au bond, while a functional group (carboxyl group) attached to GABA. The controlling of particles’ size and the surface morphology are also the important factors during the whole experiment. The particle around 100nm is using to link to MPA, and the range of GABA from 1mM to 30mM was detected by the Raman Scattering to obtain the calibrate curve. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced raman scattering

Procedia PDF Downloads 246