Search results for: data transfer optimization

Authors: Aastha Paliwal, H. N. Chanakya, S. Dasappa

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Lignocellulose, as an alternate feedstock for biogas production, has been an active area of research. However, lignocellulose poses a lot of operational difficulties- widespread variation in the structural organization of lignocellulosic matrix, amenability to degradation, low bulk density, to name a few. Amongst these, the low bulk density of the lignocellulosic feedstock is crucial to the process operation and optimization. Low bulk densities render the feedstock floating in conventional liquid/wet digesters. Low bulk densities also restrict the maximum achievable organic loading rate in the reactor, decreasing the power density of the reactor. However, during digestion, lignocellulose undergoes very high compaction (up to 26 times feeding density). This first reduces the achievable OLR (because of low feeding density) and compaction during digestion, then renders the reactor space underutilized and also imposes significant mass transfer limitations. The objective of this paper was to understand the effects of compacting lignocellulose on mass transfer and the influence of loss of different components on the bulk density and hence structural integrity of the digesting lignocellulosic feedstock. 10 different lignocellulosic feedstocks (monocots and dicots) were digested anaerobically in a fed-batch, leach bed reactor -solid-state stratified bed reactor (SSBR). Percolation rates of the recycled bio-digester liquid (BDL) were also measured during the reactor run period to understand the implication of compaction on mass transfer. After 95 ds, in a destructive sampling, lignocellulosic feedstocks digested at different SRT were investigated to quantitate the weekly changes in bulk density and lignocellulosic composition. Further, percolation rate data was also compared to bulk density data. Results from the study indicate loss of hemicellulose (r²=0.76), hot water extractives (r²=0.68), and oxalate extractives (r²=0.64) had dominant influence on changing the structural integrity of the studied lignocellulose during anaerobic digestion. Further, feeding bulk density of the lignocellulose can be maintained between 300-400kg/m³ to achieve higher OLR, and bulk density of 440-500kg/m³ incurs significant mass transfer limitation for high compacting beds of dicots.

Keywords: anaerobic digestion, bulk density, feed compaction, lignocellulose, lignocellulosic matrix, cellulose, hemicellulose, lignin, extractives, mass transfer

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Authors: Elaheh Vaezpour

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Data sensing in wireless sensor networks is done by query deceleration the network by the users. In many applications of the wireless sensor networks, many users send queries to the network simultaneously. If the queries are processed separately, the network’s energy consumption will increase significantly. Therefore, it is very important to aggregate the queries before sending them to the network. In this paper, we propose a multiple query optimization framework based on sensors physical and temporal correlation. In the proposed method, queries are merged and sent to network by considering correlation among the sensors in order to reduce the communication cost between the sensors and the base station.

Keywords: wireless sensor networks, multiple query optimization, data correlation, reducing energy consumption

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Authors: Romisaa Ali

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The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

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Authors: Assaad Ghazouani, Hedia Teraoui

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The purpose of this article is to try to see if the FDI actually contributes to technology transfer in Tunisia or are there other sources that can guarantee this transfer? The answer to this problem was gradual as we followed an approach using economic theory, the reality of Tunisia and econometric and statistical tools. We examined the relationship between technology transfer and FDI in Tunisia over a period of 40 years from 1970 to 2010. We estimated in two stages: first, a growth equation, then we have learned from this regression residue (proxy technology), secondly, we regressed on European FDI, exports of manufactures, imports of goods from the European Union in addition to other variables to test the robustness of the results and describing the level of infrastructure in the country. It follows from our study that technology transfer does not originate primarily and exclusively in the FDI and the latter is econometrically weakly with technology transfer and spill over effect of FDI does not seem to occur according to our results. However, the relationship between technology transfer and imports is negative and significant. Although this result is cons-intuitive, is recurrent in the literature of panel data. It has also given rise to intense debate on the microeconomic modelling as well as on the empirical applications. Technology transfer through trade or foreign investment has become a catalyst for growth recognized by numerous empirical studies in particular. However, the relationship technology transfer FDI is more complex than it appears. This complexity is due, primarily, but not exclusively to the close link between FDI and the characteristics of the host country. This is essentially the host's responsibility to establish general conditions, transparent and conducive to investment, and to strengthen human and institutional capacity necessary for foreign capital flows that can have real effects on growth.

Keywords: technology transfer, foreign direct investment, economics, finance

Procedia PDF Downloads 295

Authors: Anders Schou Simonsen, Kim Sorensen, Thomas Condra

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Wet scrubbers are used for flue gas desulfurization by injecting water directly into the flue gas stream from a set of sprayers. The water droplets will flow freely inside the scrubber, and flow down along the scrubber walls as a thin wall film while reacting with the gas phase to remove SO₂. This complex multiphase phenomenon can be divided into three main contributions: the continuous gas phase, the liquid droplet phase, and the liquid wall film phase. This study proposes a complete model, where all three main contributions are taken into account and resolved using OpenFOAM for the continuous gas phase, and MATLAB for the liquid droplet and wall film phases. The 3D continuous gas phase is composed of five species: CO₂, H₂O, O₂, SO₂, and N₂, which are resolved along with momentum, energy, and turbulence. Source terms are present for four species, energy and momentum, which are affecting the steady-state solution. The liquid droplet phase experiences breakup, collisions, dynamics, internal chemistry, evaporation and condensation, species mass transfer, energy transfer and wall film interactions. Numerous sub-models have been implemented and coupled to realise the above-mentioned phenomena. The liquid wall film experiences impingement, acceleration, atomization, separation, internal chemistry, evaporation and condensation, species mass transfer, and energy transfer, which have all been resolved using numerous sub-models as well. The continuous gas phase has been coupled with the liquid phases using source terms by an approach, where the two software packages are couples using a link-structure. The complete CFD model has been verified using 16 experimental tests from an existing scrubber installation, where a gradient-based pattern search optimization algorithm has been used to tune numerous model parameters to match the experimental results. The CFD model needed to be fast for evaluation in order to apply this optimization routine, where approximately 1000 simulations were needed. The results show that the complex multiphase phenomena governing wet scrubbers can be resolved in a single model. The optimization routine was able to tune the model to accurately predict the performance of an existing installation. Furthermore, the study shows that a coupling between OpenFOAM and MATLAB is realizable, where the data and source term exchange increases the computational requirements by approximately 5%. This allows for exploiting the benefits of both software programs.

Keywords: desulfurization, discrete phase, scrubber, wall film

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Authors: Sait Ali Uymaz, Gülay Tezel

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This paper presents the comparison results on the performance of the Cuckoo Search (CS) algorithm for constrained optimization problems. For constraint handling, CS algorithm uses penalty method. CS algorithm is tested on thirteen well-known test problems and the results obtained are compared to Particle Swarm Optimization (PSO) algorithm. Mean, best, median and worst values were employed for the analyses of performance.

Keywords: cuckoo search, particle swarm optimization, constrained optimization problems, penalty method

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Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability

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Authors: Kang Zijian, Zhang Tingyu, Burra Venkata Durga Kumar

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This article investigates the challenges in memory migration during the live migration of virtual machines. We found three challenges probably existing in pre-copy technology. One of the main challenges is the challenge of downtime migration. Decrease the downtime could promise the normal work for a virtual machine. Although pre-copy technology is greatly decreasing the downtime, we still need to shut down the machine in order to finish the last round of data transfer. This paper provides an optimization scheme for the problems existing in pro-copy technology, mainly the optimization of the dirty page migration mechanism. The typical pre-copy technology copy n-1th’s dirty pages in nth turn. However, our idea is to create a double iteration method to solve this problem.

Keywords: virtual machine, pre-copy technology, memory migration process, downtime, dirty pages migration method

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Authors: S. Ali Ashrafizadeh, M. Amidpour, N. Hedayat

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Driving forces along with transfer coefficient affect on heat transfer rate, on the other hand, with regard to the relation of these forces with irriversibilities they are effective on exergy losses. Therefore, the driving forces can be used as a relation between heat transfer rate, transfer coefficients and exergy losses. In this paper, first, the relation of the exergetic efficiency and resistant forces is obtained, next the relation between exergy efficiency, relative driving force, heat transfer rate and heat resistances is considered. In all cases, results are argued graphically. Finally, a case study inspected by obtained results.

Keywords: heat transfer, exergy losses, exergetic efficiency, driving forces

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Authors: Evln Ranga Charyulu, S. P. Venu Madhavarao, S. Udaya kumar, S. V. S. S. N. V. G. Krishna Murthy

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With the advent of new nanometer process technologies, it is possible to integrate billion transistors on a single substrate. When more and more functionality included there is the possibility of multi-million transistors switching simultaneously consuming more power and dissipating more power along with more leakage of current into the substrate of porous silicon or germanium material. These results in substrate heating and thermal noise generation coupled to signals of interest. The heating process is represented by coupled nonlinear partial differential equations in porous silicon and germanium. By identifying heat sources and heat fluxes may results in designing of ultra-low power circuits. The PDEs are solved by finite difference scheme assuming that boundary layer equations in porous silicon and germanium. Local heat fluxes along the vertical isothermal surface immersed in porous SI/Ge are considered. The parameters considered for optimization are thermal diffusivity, thermal expansion coefficient, thermal diffusion ratio, permeability, specific heat at constant temperatures, Rayleigh number, amplitude of wavy surface, mass expansion coefficient. The diffusion of heat was caused by the concentration gradient. Thermal physical properties are homogeneous and isotropic. By using L8, TAGUCHI method the parameters are optimized.

Keywords: heat transfer, pde, taguchi optimization, SI/Ge

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Authors: Bandar Ali Al-Asbahi, Mohammad Hafizuddin Haji Jumali

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Forster energy transfer between poly (9,9'-di-n-octylfluorenyl-2,7-diyl) (PFO)/TiO2 nanoparticles (NPs) as a donor and Fluorol 7GA as an acceptor has been studied. The energy transfer parameters were calculated by using mathematical models. The dominant mechanism responsible for the energy transfer between the donor and acceptor molecules was Forster-type, as evidenced by large values of quenching rate constant, energy transfer rate constant and critical distance of energy transfer. Moreover, these composites which were used as an emissive layer in organic light emitting diodes, were investigated in terms of current density–voltage and electroluminescence spectra.

Keywords: energy transfer parameters, forster-type, electroluminescence, organic light emitting diodes

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Authors: Shu-Bo Yang, Wei Wu, Yuan-Heng Liu

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This research aims to design a heat-exchanger type of methanol reformer coupled with a preheating design in gPROMS® environment. The endothermic methanol steam reforming reaction (MSR) and the exothermic preferential oxidation reaction (PROX) occur in the inner tube and the outer tube of the reformer, respectively. The effective heat transfer manner between the inner and outer tubes is investigated. It is verified that the countercurrent-flow type reformer provides the higher hydrogen yield than the cocurrent-flow type. Since the hot spot temperature appears in the outer tube, an improved scheme is proposed to suppress the hot spot temperature by splitting the excess air flowing into two sites. Finally, an optimization algorithm for maximizing the hydrogen yield is employed to determine optimal operating conditions.

Keywords: methanol reformer, methanol steam reforming, optimization, simulation

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Authors: Kuen Ming Shu, Ren Kai Ho

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Ultrasonic horn has the functions of amplifying amplitude and reducing resonant impedance in ultrasonic system. Its primary function is to amplify deformation or velocity during vibration and focus ultrasonic energy on the small area. It is a crucial component in design of ultrasonic vibration system. There are five common design methods for ultrasonic horns: analytical method, equivalent circuit method, equal mechanical impedance, transfer matrix method, finite element method. In addition, the general optimization design process is to change the geometric parameters to improve a single performance. Therefore, in the general optimization design process, we couldn't find the relation of parameter and objective. However, a good optimization design must be able to establish the relationship between input parameters and output parameters so that the designer can choose between parameters according to different performance objectives and obtain the results of the optimization design. In this study, an ultrasonic horn provided by Maxwide Ultrasonic co., Ltd. was used as the contrast of optimized ultrasonic horn. The ANSYS finite element analysis (FEA) software was used to simulate the distribution of the horn amplitudes and the natural frequency value. The results showed that the frequency for the simulation values and actual measurement values were similar, verifying the accuracy of the simulation values. The ANSYS DesignXplorer was used to perform Response Surface optimization, which could shows the relation of parameter and objective. Therefore, this method can be used to substitute the traditional experience method or the trial-and-error method for design to reduce material costs and design cycles.

Keywords: horn, natural frequency, response surface optimization, ultrasonic vibration

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Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

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Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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Authors: M. Moody, R. Mahmoodi, A. R. Zolfaghari, A. Aminottojari

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In this study, flow inside the shell side of a shell-and-tube heat exchanger is simulated numerically for laminar and turbulent flows in both steady state and transient mode. Governing equations of fluid flow are discrete using finite volume method and central difference scheme and solved with simple algorithm which is staggered grid by using MATLAB programming language. The heat transfer coefficient is obtained using velocity field from equation Dittus-Bolter. In comparison with, heat exchanger is simulated with ANSYS CFX software and experimental data measured in the THTL test loop. Numerical results obtained from the study show good agreement with experimental data and ANSYS CFX results. In addition, by deliberation the effect of the baffle spacing and the baffle cut on the heat transfer rate for turbulent flow, it is illustrated that the heat transfer rate depends on the baffle spacing and the baffle cut directly. In other word in spied of large turbulence, if these two parameters are not selected properly in the heat exchanger, the heat transfer rate can reduce.

Keywords: shell-and-tube heat exchanger, flow and heat transfer, laminar and turbulence flow, turbulence model, baffle spacing, baffle cut

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Authors: Yasser Rammah, Wolf-Christian Mueller

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Nonlinear triad interactions in incompressible three-dimensional magnetohydrodynamic (3D-MHD) turbulence are studied by analyzing data from high-resolution direct numerical simulations of decaying isotropic (5123 grid points) and forced anisotropic (10242 x256 grid points) turbulence. An accurate numerical approach toward analyzing nonlinear turbulent energy transfer function and triad interactions is presented. It involves the direct numerical examination of every wavenumber triad that is associated with the nonlinear terms in the differential equations of MHD in the inertial range of turbulence. The technique allows us to compute the spectral energy transfer and energy fluxes, as well as the spectral locality property of energy transfer function. To this end, the geometrical shape of each underlying wavenumber triad that contributes to the statistical transfer density function is examined to infer the locality of the energy transfer. Results show that the total energy transfer is local via nonlocal triad interactions in decaying macroscopically isotropic MHD turbulence. In anisotropic MHD, turbulence subject to a strong mean magnetic field the nonlinear transfer is generally weaker and exhibits a moderate increase of nonlocality in both perpendicular and parallel directions compared to the isotropic case. These results support the recent mathematical findings, which also claim the locality of nonlinear energy transfer in MHD turbulence.

Keywords: magnetohydrodynamic (MHD) turbulence, transfer density function, locality function, direct numerical simulation (DNS)

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Authors: Takahiro Hino, Michiharu Maeda

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Particle swarm optimization (PSO) is an optimization approach that achieves the social model of bird flocking and fish schooling. PSO works in continuous space and can solve continuous optimization problem with high quality. Set-based particle swarm optimization (SPSO) functions in discrete space by using a set. SPSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In this paper, we present an algorithm of SPSO with status memory to decide the position based on the previous position for solving traveling salesman problem (TSP). In order to show the effectiveness of our approach. We examine SPSOSM for TSP compared to the existing algorithms.

Keywords: combinatorial optimization problems, particle swarm optimization, set-based particle swarm optimization, traveling salesman problem

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Authors: Neha Asthana, Vishal Krishna Prasad

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Collaborative planning and forecasting are the innovative and systematic approaches towards productive integration and assimilation of data synergized into information. The changing and variable market dynamics have persuaded global business chains to incorporate collaborative planning and forecasting as an imperative tool. Thus, it is essential for the supply chains to constantly improvise, update its nature, and mould as per changing global environment.

Keywords: information transfer, forecasting, optimization, supply chain management

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Authors: Abir Derouiche, Abdesslem Layeb

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Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics.

Keywords: Optimization, Metaheuristics, Data Mining, Association rules Mining

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Authors: Kang Hyun Yi

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Wireless power transfer technologies are inductive coupling, magnetic resonance, and capacitive coupling methods, typically. Among them, the capacitive coupling wireless power transfer, also named Capacitive Coupling Wireless Power Transfer (CCWPT), has been researched to overcome the drawbacks of other approaches. The CCWPT has many advantages such as a simple structure, low standing power loss, reduced Electromagnetic Interference (EMI) and the ability to transfer power through metal barriers. In this paper, the CCWPT system with 6.78MHz class D inverter is proposed and analyzed. The proposed system is consisted of the 6.78MHz class D inverter with the LC low pass filter, the capacitor between a transmitter and a receiver and impedance transformers. The system is verified with a prototype for charging mobile devices.

Keywords: wireless power transfer, capacitive coupling power transfer, class D inverter, 6.78MHz

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Authors: James A. Adeyanju, John O. Olajide, Akinbode A. Adedeji

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A predictive mathematical model based on the fundamental principles of mass transfer was developed to simulate the moisture content and oil content during Deep-Fat Frying (DFF) process of dodo. The resulting governing equation, that is, partial differential equation that describes rate of moisture loss and oil uptake was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for the implementation of FDT at different frying conditions and moisture loss as well as oil uptake simulation during DFF of dodo. Plantain samples were sliced into 5 mm thickness and fried at different frying oil temperatures (150, 160 and 170 ⁰C) for periods varying from 2 to 4 min. The comparison between the predicted results and experimental data for the validation of the model showed reasonable agreement. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranging from 0.912 to 0.947 and 0.895 to 0.957, respectively. The predicted results could be further used for the design, control and optimization of deep-fat frying process.

Keywords: frying, moisture loss, modelling, oil uptake

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Authors: M. Hemnath, S. Kannan, R. Kiran, K. Thanigaivelu

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This paper is based on exploring the possible opportunities and applications using Power Line Communication (PLC) for security and surveillance operations. Various research works are done for introducing PLC into onboard vehicle communication and networking (CAN, LIN etc.) and various international standards have been developed. Wireless power transfer (WPT) is also an emerging technology which is studied and tested for recharging purposes. In this work we present a system which embeds the detection and the response into one which eliminates the need for dedicated network for data transmission. Also we check the feasibility for integrating wireless power transfer system into this proposed security system for transmission of power to detection unit wirelessly from the response unit.

Keywords: power line communication, wireless power transfer, surveillance

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Authors: Sperisa Distantina, Rieke Ulfha Noviyanti, Sri Sutriyani, Fadilah Fadilah, Mujtahid Kaavessina

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In this research, carrageenan extracted from seaweed Eucheuma cottonii was mixed with polyvinyl alcohol (PVA) and then crosslinked using glutaraldehyde (GA). The obtained hydrogel films were applied to control the drug release rate of paracetamol. The aim of this research was to develop a mathematical model that can be used to describe the mass transfer rate of paracetamol from the hydrogel film into buffer solution. The effect of weight ratio carrageenan-PVA (5: 0, 1: 0.5, 1: 1, 1: 2, 0: 5) on the parameters of the mathematical model was investigated also. Based on the experimental data, the proposed mathematical model could describe the mass transfer rate of paracetamol. The weight ratio of carrageenan-PVA greatly affected the amount of paracetamol absorbed in the hydrogel film and the mass transfer rate of paracetamol.

Keywords: carrageenan-PVA, crosslinking, glutaraldehyde, hydrogel, paracetamol, mass transfer

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Authors: D. Li

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Optical thin films are used in a wide variety of optical components and there are many software tools programmed for advancing multilayer thin film design. The available software packages for designing the thin film structure may not provide optimum designs. Normally, almost all current software programs obtain their final designs either from optimizing a starting guess or by technique, which may or may not involve a pseudorandom process, that give different answers every time, depending upon the initial conditions. With the increasing power of personal computers, functional methods in optimization and synthesis of optical multilayer systems have been developed such as DGL Optimization, Simulated Annealing, Genetic Algorithms, Needle Optimization, Inductive Optimization and Flip-Flop Optimization. Among these, DGL Optimization has proved its efficiency in optical thin film designs. The application of the DGL optimization technique to the design of optical coating is presented. A DGL optimization technique is provided, and its main features are discussed. Guidelines on the application of the DGL optimization technique to various types of design problems are given. The innovative global optimization strategies used in a software tool, OnlyFilm, to optimize multilayer thin film designs through different filter designs are outlined. OnlyFilm is a powerful, versatile, and user-friendly thin film software on the market, which combines optimization and synthesis design capabilities with powerful analytical tools for optical thin film designers. It is also the only thin film design software that offers a true global optimization function.

Keywords: optical coatings, optimization, design software, thin film design

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Authors: Rahul Paul, Kedar Nath Das

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The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.

Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques

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Authors: O. Mohamed Amine, A. Khireddine

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Telecoms operators are always looking to meet their share of the other customers, they try to gain optimum utilization of the deployed equipment and network optimization has become essential. This project consists of optimizing UMTS network, and the study area is an urban area situated in the center of Algiers. It was initially questions to become familiar with the different communication systems (3G) and the optimization technique, its main components, and its fundamental characteristics radios were introduced.

Keywords: UMTS, UTRAN, WCDMA, optimization

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Authors: Devatha Kalyan Kumar, R. Poovarasan

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In this paper, we have taken certain important factors and health parameters of diabetes patients especially among children by birth (pediatric congenital) where using the above three metrics methods we are going to assess the importance of each attributes in the dataset and thereby determining the most highly responsible and co-related attribute causing diabetics among young patients. We use cost optimization, control chart and Spearmen methodologies for the real-time application of finding the data efficiency in this diabetes dataset. The Spearmen methodology is the correlation methodologies used in software development process to identify the complexity between the various modules of the software. Identifying the complexity is important because if the complexity is higher, then there is a higher chance of occurrence of the risk in the software. With the use of control; chart mean, variance and standard deviation of data are calculated. With the use of Cost optimization model, we find to optimize the variables. Hence we choose the Spearmen, control chart and cost optimization methods to assess the data efficiency in diabetes datasets.

Keywords: correlation, congenital diabetics, linear relationship, monotonic function, ranking samples, pediatric

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Authors: C. S. Sona, Makrand A. Khanwale, Channamallikarjun S. Mathpati

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New generation nuclear power plants are currently being developed to be highly economical, to be passive safe, to produce hydrogen. An important feature of these reactors will be the use of coolants at temperature higher than that being used in current nuclear reactors. The molten fluoride salt with a eutectic composition of 46.5% LiF - 11.5% NaF - 42% KF (mol %) commonly known as FLiNaK is a leading candidate for heat transfer coolant for these nuclear reactors. CFD simulations were carried out using large eddy simulations to investigate the flow characteristics of molten FLiNaK at 850°C at a Reynolds number of 10,500 in a cylindrical pipe. Simulation results have been validated with the help of mean velocity profile using direct numerical simulation data. Transient velocity information was used to identify and characterise turbulent structures which are important for transfer of heat across solid-fluid interface. A wavelet transform based methodology called wavelet transform modulus maxima was used to identify and characterise the singularities. This analysis was also used for flow visualisation, and also to calculate the heat transfer coefficient using small eddy model. The predicted Nusselt number showed good agreement with the available experimental data.

Keywords: FLiNaK, heat transfer, molten salt, turbulent structures

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Authors: Tao Feng, Fei Xing, Ye Lu, Jun Li Fang

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NDN is a kind of future Internet architecture. Due to the NDN design introduces four privacy challenges,Many research institutions began to care about the privacy issues of naming data network(NDN).In this paper, we are in view of the major NDN’s privacy issues to investigate privacy protection,then put forwards more effectively anonymous transfer policy for NDN.Firstly,based on mutual anonymity communication for MP2P networks,we propose NDN mutual anonymity protocol.Secondly,we add interest package authentication mechanism in the protocol and encrypt the coding coefficient, security of this protocol is improved by this way.Finally, we proof the proposed anonymous transfer protocol security and anonymity.

Keywords: NDN, mutual anonymity, anonymous routing, network coding, authentication mechanism

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Authors: Yue Huang, Yiheng Feng

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Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

Procedia PDF Downloads 61