Search results for: optimal reaction network

Authors: Viktor Müller, Ulman Lindenberger

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Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.

Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling

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Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

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In order to effectively detect aerial targets over long distances, an optimal matching design method of space-based optical payload is proposed. Firstly, main factors affecting optical detectability of small targets under complex environment are analyzed based on the full link of a detection system, including band center, band width and spatial resolution. Then a performance characterization model representing the relationship between image signal-to-noise ratio (SCR) and the above influencing factors is established to describe a detection system. Finally, an optimal matching design example is demonstrated for a typical aerial target by simulating and analyzing its SCR under different scene clutter coupling with multi-scale characteristics, and the optimized detection band and spatial resolution are presented. The method can provide theoretical basis and scientific guidance for space-based detection system design, payload specification demonstration and information processing algorithm optimization.

Keywords: space-based detection, aerial targets, optical system design, detectability characterization

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Authors: Ali Heydarimoghim

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In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

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Authors: P. R. Dushantha Chaminda, Peng Kai

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In this review paper, we enclose the thought of wireless ad hoc networks and particularly mobile ad hoc network (MANET), their field of study, intention, concern, benefit and disadvantages, modifications, with relation of AODV routing protocol. Mobile computing is developing speedily with progression in wireless communications and wireless networking protocols. Making communication easy, we function most wireless network devices and sensor networks, movable, battery-powered, thus control on a highly constrained energy budget. However, progress in battery technology presents that only little improvements in battery volume can be expected in the near future. Moreover, recharging or substitution batteries is costly or unworkable, it is preferable to support energy waste level of devices low.

Keywords: wireless ad hoc network, energy efficient routing protocols, AODV, EOAODV, AODVEA, AODVM, AOMDV, FF-AOMDV, AOMR-LM

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Authors: Adesola O. Orimoloye, Edward Gobina

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Membrane separation technology is still considered as an emerging technology in the mining sector and does not yet have the widespread acceptance that it has in other industrial sectors. Underground Coal Gasification (UCG), wherein coal is converted to gas in-situ, is a safer alternative to mining method that retains all pollutants underground making the process environmentally friendly. In-situ combustion of coal for power generation allows access to more of the physical global coal resource than would be included in current economically recoverable reserve estimates. Where mining is no longer taking place, for economic or geological reasons, controlled gasification permits exploitation of the deposit (again a reaction of coal to form a synthesis gas) of coal seams in situ. The oxygen supply stage is one of the most expensive parts of any gasification project but the use of membranes is a potentially attractive approach for producing oxygen-enriched air. In this study, a variety of cost-effective membrane materials that gives an optimal amount of oxygen concentrations in the range of interest was designed and tested at diverse operating conditions. Oxygen-enriched atmosphere improves the combustion temperature but a decline is observed if oxygen concentration exceeds optimum. Experimental result also reveals the preparatory method, apparatus and performance of the fabricated membrane.

Keywords: membranes, oxygen-enrichment, gasification, coal

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Emine Teke, Soner Kuşlu, Sabri Çolak, Turan Çalban

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The aim of the present study was to investigate the dissolution kinetics of ulexite in sodium dihydrogen phosphate in a mechanical agitation system and also to declare an alternative reactant to produce the boric acid. Reaction temperature, concentration of sodium dihydrogen phosphate, stirring speed, solid-liquid ratio, and ulexite particle size were selected as parameters. The experimental results were successfully correlated by using linear regression and a statistical program. Dissolution curves were evaluated in order to test the shrinking core models for solid-fluid systems. It was observed that increase in the reaction temperature and decrease in the solid/liquid ratio causes an increase in the dissolution rate of ulexite. The activation energy was found to be 36.4 kJ/mol. The leaching of ulexite was controlled by diffusion through the ash (or product) layer.

Keywords: ulexite, sodium dihydrogen phosphate, leaching kinetics, boron

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Authors: Yossiri Ariyakul, Piyakiat Insom, Poonyawat Sangiamkulthavorn, Takamichi Nakamoto

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In this paper, the method of optimization algorithm for sensor network comprised of movable sensor nodes which can be used for odor source localization was proposed. A sensor node is composed of an odor sensor, an anemometer, and a wireless communication module. The odor intensity measured from the sensor nodes are sent to the processor to perform the localization based on optimization algorithm by which the odor source localization map is obtained as a result. The map can represent the exact position of the odor source or show the direction toward it remotely. The proposed method was experimentally validated by creating the odor source localization map using three, four, and five sensor nodes in which the accuracy to predict the position of the odor source can be observed.

Keywords: odor sensor, odor source localization, optimization, sensor network

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Authors: Meimei Zheng

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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

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Authors: Vemula Amalakrishna, S. Pushpavanam

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Change and motion characterize and persistently reshape the world around us, on scales from molecular to global. The subtle interplay between change (Reaction) and motion (Diffusion) gives rise to an astonishing intricate spatial or temporal pattern. These pattern formation in nature has been intellectually appealing for many scientists since antiquity. Periodic precipitation patterns, also known as Liesegang patterns (LP), are one of the stimulating examples of such self-assembling reaction-diffusion (RD) systems. LP formation has a great potential in micro and nanotechnology. So far, the research on LPs has been concentrated mostly on how these patterns are forming, retrieving information to build a universal mathematical model for them. Researchers have developed various theoretical models to comprehensively construct the geometrical diversity of LPs. To the best of our knowledge, simulation studies of LPs assume an arbitrary value of RD parameters to explain experimental observation qualitatively. In this work, existing models were studied to understand the mechanism behind this phenomenon and challenges pertaining to models were understood and explained. These models are not computationally effective due to the presence of discontinuous precipitation rate in RD equations. To overcome the computational challenges, smoothened Heaviside functions have been introduced, which downsizes the computational time as well. Experiments were performed using a conventional LP system (AgNO₃-K₂Cr₂O₇) to understand the effects of different gels and temperatures on formed LPs. The model is extended for real parameter values to compare the simulated results with experimental data for both 1-D (Cartesian test tubes) and 2-D(cylindrical and Petri dish).

Keywords: reaction-diffusion, spatio-temporal patterns, nucleation and growth, supersaturation

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Jarek Krajewski, Andre Wittenborn, Martin Sauerland

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This abstract describes a promising approach for estimating post-traumatic stress disorder (PTSD) based on prosodic speech characteristics. It illustrates the validity of this method by briefly discussing results from an Arabic refugee sample (N= 47, 32 m, 15 f). A well-established standardized self-report scale “Reaction of Adolescents to Traumatic Stress” (RATS) was used to determine the ground truth level of PTSD. The speech material was prompted by telling about autobiographical related sadness inducing experiences (sampling rate 16 kHz, 8 bit resolution). In order to investigate PTSD-induced speech changes, a self-developed set of 136 prosodic speech features was extracted from the .wav files. This set was adapted to capture traumatization related speech phenomena. An artificial neural network (ANN) machine learning model was applied to determine the PTSD level and reached a correlation of r = .37. These results indicate that our classifiers can achieve similar results to those seen in speech-based stress research.

Keywords: speech prosody, PTSD, machine learning, feature extraction

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Authors: R. H. Hwang, J. H. Park, K. B. Yi

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Nitrous oxide (N2O) is now distinguished as an environmental pollutant. N2O is one of the representative greenhouse gases and N2O is produced by both natural and anthropogenic sources. So, it is very important to reduce N2O. N2O abatement processes are various processes such as HC-SCR, NH3-SCR and decomposition process. Among them, decomposition process is advantageous because it does not use a reducing agent. N2O decomposition is a reaction in which N2O is decomposed into N2 and O2. There are noble metals, transition metal ion-exchanged zeolites, pure and mixed oxides for N2O decomposition catalyst. Among the various catalysts, cobalt-based catalysts derived from hydrotalcites gathered much attention because spinel catalysts having large surface areas and high thermal stabilities. In this study, the effect of promoter and K addition on the activity was compared and analyzed. Co3O4 catalysts for N2O decomposition were prepared by co- precipitation method. Ce and Zr were added during the preparation of the catalyst as promoter with the molar ratio (Ce or Zr) / Co = 0.05. In addition, 1 wt% K2CO3 was doped to the prepared catalyst with impregnation method to investigate the effect of K on the catalyst performance. Characterizations of catalysts were carried out with SEM, BET, XRD, XPS and H2-TPR. The catalytic activity tests were carried out at a GHSV of 45,000 h-1 and a temperature range of 250 ~ 375 ℃. The Co3O4 catalysts showed a spinel crystal phase, and the addition of the promoter increased the specific surface area and reduced the particle and crystal size. It was exhibited that the doping of K improves the catalytic activity by increasing the concentration of Co2+ in the catalyst which is an active site for catalytic reaction. As a result, the K-doped catalyst showed higher activity than the promoter added. Also, it was found through experiments that Co2+ concentration and reduction temperature greatly affect the reactivity.

Keywords: Co₃O4, K-doped, N₂O decomposition, promoter

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Venugopal Kummamuru

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Corporate Governance (CG) is of utmost importance for running a company ethically. It is essential for the growth and success of the corporation. It is intended to increase the accountability of an organization to the larger context of the business environment. The general principles of CG include and are related to Shareholder recognition, Stakeholder interests, and focus on Corporate Social Responsibility (CSR), Clear Board responsibilities, Ethical behavior, and Business transparency. Network Marketing Organizations (NMOs) focus on marketing through direct-sales using people who are associated with the organization but are not their employees. This paper tries to study the importance of Ethics and CSR in an NMO and suggest a basic guideline for CG in NMO(s). This paper could be used as a basis or starting point for conducting an in-depth research to understand the difference in CG practices between NMO(s) and other organizations and define a standard set of guidelines for CG practice.

Keywords: corporate governance, corporate responsibility, direct selling, network marketing

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Authors: Tomoaki Hashimoto

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Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: optimal control, stochastic systems, random dither, quantization

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Authors: Sun Lim, Kyun Jung

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In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.

Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic

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Authors: Hyun-Jong Choi, Minjun Kwak, Doo-Won Seo, Sang-Kuk Woo, Sun-Dong Kim

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Solid Oxide Cell(SOC) systems can contribute to the transition to the hydrogen society by utilized as a power and hydrogen generator by the electrochemical reaction with high efficiency at high operation temperature (>750 ℃). La1-xSrxCo1-yFeyO3, which is an air electrode, is occurred stability degradations due to reaction and delamination with yittria stabilized zirconia(YSZ) electrolyte in a water electrolysis mode. To complement this phenomenon SOCs need gadolinium doped ceria(GDC) buffer layer between electrolyte and air electrode. However, GDC buffer layer requires a high sintering temperature and it causes a reaction with YSZ electrolyte. This study carried out low temperature sintering of GDC layer by applying Cu-oxide as a sintering aid. The effect of a copper additive as a sintering aid to lower the sintering temperature for the construction of solid oxide fuel cells (SOFCs) was investigated. GDC buffer layer with 0.25-10 mol% CuO sintering aid was prepared by reacting GDC power and copper nitrate solution followed by heating at 600 ℃. The sintering of CuO-added GDC powder was optimized by investigating linear shrinkage, microstructure, grain size, ionic conductivity, and activation energy of CuO-GDC electrolytes at temperatures ranging from 1100 to 1400 ℃. The sintering temperature of the CuO-GDC electrolyte decreases from 1400 ℃ to 1100 ℃ by adding the CuO sintering aid. The ionic conductivity of the CuO-GDC electrolyte shows a maximum value at 0.5 mol% of CuO. However, the addition of CuO has no significant effects on the activation energy of GDC electrolyte. GDC-LSCF layers were co-sintering at 1050 and 1100 ℃ and button cell tests were carried out at 750 ℃.

Keywords: Co-Sintering, GDC-LSCF, Sintering Aid, solid Oxide Cells

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Authors: Shalini Arora, Sri Sivakumar

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The deep removal of high molecular weight sulphur compounds (e.g., 4,6, dimethyl dibenzothiophene) is challenging due to their steric hindrance. Hydrogenation desulfurization (HYD) pathway is the main pathway to remove these sulfur compounds, and it is mainly governed by the number of type 2 sites. The formation of type 2 sites can be enhanced by modulating the pore structure and the interaction between the active metal and support. To this end, we report the enhanced HDS catalytic activity of ultrasmall NiMo supported on amorphous alumina (A-Al₂O₃) catalysts by one pot colloidal synthesis method followed by calcination and sulfidation. The amorphous alumina (A-Al₂O₃) was chosen as the support due to its lower surface energy, better physicochemical properties, and enhanced acidic sites (due to the dominance of tetra and penta coordinated [Al] sites) than crystalline alumina phase. At 20% metal oxide composition, NiMo supported on A-Al₂O₃ catalyst showed 1.4 and 1.2 times more reaction rate constant and turn over frequency (TOF) respectively than the conventional catalyst (wet impregnated NiMo catalysts) for HDS reaction of dibenzothiophene reactant molecule. A-Al₂O₃ supported catalysts represented enhanced type 2 sites formation (because this catalystpossesses higher sulfidation degree (80%) and NiMoS sites (19.3 x 10¹⁷ sites/mg) with desired optimum stacking degree (2.5) than wet impregnated catalyst at same metal oxide composition 20%) along with higher active metal dispersion, Mo edge site fraction. The experimental observations were also supported by DFT simulations. Lower heat of adsorption (< 4.2 ev for MoS2 interaction and < 3.15 ev for Ni doped MoS2 interaction) values for A-Al₂O₃ confirmed the presence of weaker metal-support interaction in A-Al₂O₃ in contrast to crystalline ℽ-Al₂O3. The weak metal-support interaction for prepared catalysts clearly suggests the higher formation of type 2 sites which leads to higher catalytic activity for HDS reaction.

Keywords: amorphous alumina, colloidal, desulfurization, metal-support interaction

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Authors: Chun-Wei Yeh, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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Reducing greenhouse gases or converting them into fuels and chemicals with added value is vital for the environment. Given the enhanced techniques for hydrocarbon extraction in this context, the catalytic conversion of methane to methanol is particularly intriguing for future applications as vehicle fuels and/or bulk chemicals. Metal-organic frameworks (MOFs) have received much attention recently for the oxidation of methane to methanol. In addition, biomimetic material, particulate methane monooxygenase (pMMO), has been reported to convert methane using copper oxide clusters as active sites. Inspired by these, in this study, we considered the well-known MIL-53(Al) MOF as support for copper oxide clusters (Cu2Ox, Cu3Ox) to investigate their reactivity towards methane oxidation using Density Functional Theory (DFT) calculations. The copper oxide clusters (Cu2O2, Cu3O2) are modeled by oxidizing copper clusters (Cu2, Cu3) with two oxidizers, O2 and N2O. The initial C-H bond activation barriers on Cu2O2/MIL-53(Al) and Cu3O2/MIL-53(Al) catalysts are 0.70 eV and 0.64 eV, respectively, and are the rate-determining steps in the overall methane conversion to methanol reactions. The desorption energy of the methanol over the Cu2O/MIL-53(Al) and Cu3O/MIL-53(Al) is 0.71eV and 0.75 eV, respectively. Furthermore, to explore the prospect of catalyst reusability, we considered the different oxidants and proposed the different reaction pathways for completing the reaction cycle and regenerating the active copper oxide clusters. To know the reason for the difference between bi-copper and tri-cooper systems, we also did an electronic analysis. Finally, we calculate the Microkinetic Simulation. The result shows that the reaction can happen at room temperature.

Keywords: DFT study, copper oxide cluster, MOFs, methane conversion

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Authors: Waseim Ragab Azzam Ahmed Mohamed Nasr, Aalaa Ibrahim Khater

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Torsional loads from offshore wind turbines, waves, wind, earthquakes, ship collisions in the maritime environment, and electrical transmission towers might affect the pile foundations. Torsional loads can also be caused by the axial load from the sustaining structures. The paper introduces the finned pile, an alternative method of pile modification. The effects of torsional loads were investigated through a series of experimental tests aimed at improving the torsional capacity of a single pile in the sand (where sand was utilized in a state of medium density (Dr = 50%), with or without fins. In these tests, the fins' length, width, form, and number were varied to see how these attributes affected the maximum torsional capacity of the piles. We have noticed the torsion-rotation reaction. The findings demonstrated that the fins improve the maximum torsional capacity of the piles. It was demonstrated that a length of 0.6 times the embedded pile's length and a width equivalent to the pile's diameter constitute the optimal fin geometry. For the conventional pile and the finned pile, the maximum torsional capacities were determined to be 4.12 N.m. and 7.36 N.m., respectively. When subjected to torsional loads, the fins' presence enhanced the piles' maximum torsional capacity by almost 79%.

Keywords: clean sand, finned piles, model tests, torsional load

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Authors: Artiya Sopharak, Tosaphol Ratniyomchai, Thanatchai Kulworawanichpong

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This paper presents an energy-saving study of Mass Rapid Transit (MRT) using an optimal train coasting operation. For the dynamic train movement with four modes of operation, including accelerating mode, constant speed or cruising mode, coasting mode, and braking mode are considered in this study. The acceleration rate, the deceleration rate, and the starting coasting point are taken into account the optimal train speed profile during coasting mode with considering the energy saving and acceptable travel time comparison to the based case with no coasting operation. In this study, the mathematical method as a Quadratic Search Method (QDS) is conducted to carry out the optimization problem. A single train of MRT services between two stations with a distance of 2 km and a maximum speed of 80 km/h is taken to be the case study. Regarding the coasting mode operation, the results show that the longer distance of costing mode, the less energy consumption in cruising mode and the less braking energy. On the other hand, the shorter distance of coasting mode, the more energy consumption in cruising mode and the more braking energy.

Keywords: energy saving, coasting mode, mass rapid transit, quadratic search method

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Authors: Dharminer Singh, Sanjeev Yadav, Pravakar Mohanty

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In this work, gasification of groundnut shell was carried out in an air bubbling fluidized bed gasifier. Atmospheric air used as gasification agent in the gasifier. The groundnut shell used for gasification was in powder form and the locally available river sand was used as bed material. Conventional charcoal was used for heating sand bed. Two cyclones were used for proper segregation of char particles and for proper cleaning and cooling the product gas. Experiments were performed on different equivalence ratio (ER) 0.3 - 0.33 by varying feeding rate 36 - 32.8 kg/h of biomass and by keeping the air flow rate constant at bed temperature between 700 °C – 800 °C. Performance of gasifier was evaluated on the basis of different parameters such as cold gas efficiency, carbon conversion efficiency (CCE), Tar and Suspended particles matter (SPM) generation, gas yield, and Higher heating value (HHV) of gas. The optimal ER value for gasification of groundnut shell (GNS) powder in an air bubbling fluidized bed gasifier was found to be 0.31. Cold gas efficiency and CCE value at optimal ER was found to be 63.7 %, and 91 %, respectively. Concentration of Tar and SPM, HHV of gas, and gas yield at optimal ER was found to be 11.88 g/Nm3, 2.38 MJ/Nm3, and 2.01m3/kg, respectively. In the product gas, concentrations of CO, CO2, CH4 and H2 were found to be 12.94%, 13.5%, 5.74% and 13.77%, respectively. At ER 0.31, it was observed that bed temperature of gasifier was in steady state for long time at 714 °C with 5 – 10 °C fluctuation.

Keywords: air bubbling fluidized bed gasifier, groundnut shell powder, equivalence ratio (ER), cold gas efficiency, carbon conversion efficiency (CCE), high heating value (HHV)

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Fatin Fadhilah Hasib, Dewi Nuraini, Nisful Laila, Muhammad Madyan

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A big political event such as Cabinet reshuffle mostly can affect the stock price positively or negatively, depend on the perception of each investor and potential investor. This study aims to analyze the movement of the market and trading activities which respect to an event using event study method. This method is used to measure the movement of the stock exchange in which abnormal return can be obtained by investor related to the event. This study examines the differences of reaction on abnormal return and trading volume activity from the companies listed in the Jakarta Islamic Index (JII), before and after the announcement of the Cabinet Work Volume II on 27 July 2016. The study was conducted in observation of 21 days in total which consists of 10 days before the event and 10 days after the event. The method used in this study is event study with market adjusted model method that observes market reaction to the information of an announcement or publicity events. The Results from the study showed that there is no significant negative nor positive reaction at the abnormal return and abnormal trading before and after the announcement of the cabinet reshuffle. It is indicated by the results of statistical tests whose value not exceeds the level of significance. Stock exchange of the JII just reflects from the previous stock prices without reflecting the information regarding to the Cabinet reshuffle event. It can be concluded that the capital market is efficient with a weak form.

Keywords: abnormal return, abnormal trading volume activity, event study, political event

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Reena D. Souza, Tripti Vats, Prem F. Siril

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Esterification of free fatty acid (oleic acid) and transesterification of waste cooking oil (WCO) with ethanol over graphene oxide (GO), GO-Fe2O3, sulfonated GO (GO-SO3H), and Fe2O3/GO-SO3H catalysts were examined in the present study. Iron oxide supported graphene-based acid catalyst (Fe2O3/GO-SO3H) exhibited highest catalytic activity. GO was prepared by modified Hummer’s process. The GO-Fe2O3 nanocomposites were prepared by the addition of NaOH to a solution containing GO and FeCl3. Sulfonation was done using concentrated sulfuric acid. Transmissionelectron microscopy (TEM) and atomic force microscopy (AFM) imaging revealed the presence of Fe2O3 particles having size in the range of 50-200 nm. Crystal structure was analyzed by XRD and defect states of graphene were characterized using Raman spectroscopy. The effects of the reaction variables such as catalyst loading, ethanol to acid ratio, reaction time and temperature on the conversion of fatty acids were studied. The optimum conditions for the esterification process were molar ratio of alcohol to oleic acid at 12:1 with 5 wt% of Fe2O3/GO-SO3H at 1000C with a reaction time of 4h yielding 99% of ethyl oleate. This is because metal oxide supported solid acid catalysts have advantages of having both strong Brønsted as well as Lewis acid properties. The biodiesel obtained by transesterification of WCO was characterized by 1H NMR and Gas Chromatography techniques. XRD patterns of the recycled catalyst evidenced that the catalyst structure was unchanged up to the 5th cycle, which indicated the long life of the catalyst.

Keywords: Fe₂O₃/GO-SO₃H, Graphene Oxide, GO-Fe₂O₃, GO-SO₃H, WCO

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Authors: Yenny Paola Morales Cortés, Fabián Rico Rodríguez, Juan Carlos Serrato Bermúdez, Carlos Arturo Martínez Riascos

Abstract:

Numerous benefits of galactooligosaccharides (GOS) as prebiotics have motivated the study of enzymatic processes for their production. These processes have special complexities due to several factors that make difficult high productivity, such as enzyme type, reaction medium pH, substrate concentrations and presence of inhibitors, among others. In the present work the production of galactooligosaccharides (with different degrees of polymerization: two, three and four) from lactose was studied. The study considers the formulation of a mathematical model that predicts the production of GOS from lactose using the enzyme β-galactosidase. The effect of pH in the reaction was studied. For that, phosphate buffer was used and with this was evaluated three pH values (6.0.6.5 and 7.0). Thus it was observed that at pH 6.0 the enzymatic activity insignificant. On the other hand, at pH 7.0 the enzymatic activity was approximately 27 times greater than at 6.5. The last result differs from previously reported results. Therefore, pH 7.0 was chosen as working pH. Additionally, the enzyme concentration was analyzed, which allowed observing that the effect of the concentration depends on the pH and the concentration was set for the following studies in 0.272 mM. Afterwards, experiments were performed varying the lactose concentration to evaluate its effects on the process and to generate the data for the adjustment of the mathematical model parameters. The mathematical model considers the reactions of lactose hydrolysis and transgalactosylation for the production of disaccharides and trisaccharides, with their inverse reactions. The production of tetrasaccharides was negligible and, because of that, it was not included in the model. The reaction was monitored by HPLC and for the quantitative analysis of the experimental data the Matlab programming language was used, including solvers for differential equations systems integration (ode15s) and nonlinear problems optimization (fminunc). The results confirm that the transgalactosylation and hydrolysis reactions are reversible, additionally inhibition by glucose and galactose is observed on the production of GOS. In relation to the production process of galactooligosaccharides, the results show that it is necessary to have high initial concentrations of lactose considering that favors the transgalactosylation reaction, while low concentrations favor hydrolysis reactions.

Keywords: β-galactosidase, galactooligosaccharides, inhibition, lactose, Matlab, modeling

Procedia PDF Downloads 358

Authors: Wen-Tsung Ho, Ku-Kuang Chang, Hsin-Yuan Chang

Abstract:

In this study, we consider an economic lot-size batch-shipment scheduling problem (ELBSP) with extended basic period (EBP) and power-of-two (PoT) policies. In this problem, the supplier using a single facility to manufacture multiple products and equally sized batches are then delivered by the supplier to buyers over an infinite planning horizon. Further, the extended basic period (EBP) and power-of-two (PoT) policy are utilized. Relaxing the production schedule converts the ELBSP to an economic lot-size batch-shipment problem (ELBP) with EBP and PoT policies, and a nonlinear integer programming model of the ELBP is constructed. Using the replenishment cycle division and recursive tightening methods, optimal solutions are then solved separately for each product. The sum of these optimal solutions is the lower bound of the ELBSP. A proposed heuristic method with polynomial complexity is then applied to figure out the near-optimal solutions of the ELBSP. Numerical example is presented to confirm the efficacy of the proposed method.

Keywords: economic lot-size scheduling problem, extended basic period, replenishment cycle division, recursive tightening, power-of-two

Procedia PDF Downloads 338

Authors: Binyam Teferi

Abstract:

Numerical and theoretical analysis of mixed convection flow of magneto- hydrodynamics micropolar fluid with stretching capillary in the presence of thermal radiation, chemical reaction, viscous dissipation, and heat generation/ absorption have been studied. The non-linear partial differential equations of momentum, angular velocity, energy, and concentration are converted into ordinary differential equations using similarity transformations which can be solved numerically. The dimensionless governing equations are solved by using Runge Kutta fourth and fifth order along with the shooting method. The effect of physical parameters viz., micropolar parameter, unsteadiness parameter, thermal buoyancy parameter, concentration buoyancy parameter, Hartmann number, spin gradient viscosity parameter, microinertial density parameter, thermal radiation parameter, Prandtl number, Eckert number, heat generation or absorption parameter, Schmidt number and chemical reaction parameter on flow variables viz., the velocity of the micropolar fluid, microrotation, temperature, and concentration has been analyzed and discussed graphically. MATLAB code is used to analyze numerical and theoretical facts. From the simulation study, it can be concluded that an increment of micropolar parameter, Hartmann number, unsteadiness parameter, thermal and concentration buoyancy parameter results in decrement of velocity flow of micropolar fluid; microrotation of micropolar fluid decreases with an increment of micropolar parameter, unsteadiness parameter, microinertial density parameter, and spin gradient viscosity parameter; temperature profile of micropolar fluid decreases with an increment of thermal radiation parameter, Prandtl number, micropolar parameter, unsteadiness parameter, heat absorption, and viscous dissipation parameter; concentration of micropolar fluid decreases as unsteadiness parameter, Schmidt number and chemical reaction parameter increases. Furthermore, computational values of local skin friction coefficient, local wall coupled coefficient, local Nusselt number, and local Sherwood number for different values of parameters have been investigated. In this paper, the following important results are obtained; An increment of micropolar parameter and Hartmann number results in a decrement of velocity flow of micropolar fluid. Microrotation decreases with an increment of the microinertial density parameter. Temperature decreases with an increasing value of the thermal radiation parameter and viscous dissipation parameter. Concentration decreases as the values of Schmidt number and chemical reaction parameter increases. The coefficient of local skin friction is enhanced with an increase in values of both the unsteadiness parameter and micropolar parameter. Increasing values of unsteadiness parameter and micropolar parameter results in an increment of the local couple stress. An increment of values of unsteadiness parameter and thermal radiation parameter results in an increment of the rate of heat transfer. As the values of Schmidt number and unsteadiness parameter increases, Sherwood number decreases.

Keywords: thermal radiation, chemical reaction, viscous dissipation, heat absorption/ generation, similarity transformation

Procedia PDF Downloads 128