Search results for: allocation optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3702

Search results for: allocation optimization

1302 Coordination Behavior, Theoretical Studies, and Biological Activity of Some Transition Metal Complexes with Oxime Ligands

Authors: Noura Kichou, Manel Tafergguenit, Nabila Ghechtouli, Zakia Hank

Abstract:

The aim of this work is to synthesize, characterize and evaluate the biological activity of two Ligands : glyoxime and dimethylglyoxime, and their metal Ni(II) chelates. The newly chelates were characterized by elemental analysis, IR, EPR, nuclear magnetic resonances (1H and 13C), and biological activity. The antibacterial and antifungal activities of the ligands and its metal complexes were screened against bacterial species (Staphylococcus aureus, Bacillus subtilis, and Escherichia coli) and fungi (Candida albicans). Ampicillin and amphotericin were used as references for antibacterial and antifungal studies. The activity data show that the metal complexes have a promising biological activity comparable with parent free ligand against bacterial and fungal species. A structural, energetic, and electronic theoretical study was carried out using the DFT method, with the functional B3LYP and the gaussian program 09. A complete optimization of geometries was made, followed by a calculation of the frequencies of the normal modes of vibration. The UV spectrum was also interpreted. The theoretical results were compared with the experimental data.

Keywords: glyoxime, dimetylglyoxime, nickel, antibacterial activity

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1301 Coordination Behavior, Theoretical studies and Biological Activity of Some Transition Metal Complexes with Oxime Ligands

Authors: Noura Kichou, Manel Tafergguenit, Nabila Ghechtouli, Zakia Hank

Abstract:

The aim of this work is to synthesize, characterize and evaluate the biological activity of two Ligands: glyoxime and dimethylglyoxime, and their metal Ni(II) chelates. The newly chelates were characterized by elemental analysis, IR, EPR, nuclear magnetic resonances (1H and 13C), and biological activity. The antibacterial and antifungal activities of the ligands and its metal complexes were screened against bacterial species (Staphylococcus aureus, Bacillus subtilis, and Escherichia coli) and fungi (Candida albicans). Ampicillin and amphotericin were used as references for antibacterial and antifungal studies. The activity data show that the metal complexes have a promising biological activity comparable with parent free ligand against bacterial and fungal species. A structural, energetic, and electronic theoretical study was carried out using the DFT method, with the functional B3LYP and the gaussian program 09. A complete optimization of geometries was made, followed by a calculation of the frequencies of the normal modes of vibration. The UV spectrum was also interpreted. The theoretical results were compared with the experimental data.

Keywords: glyoxime, dimetylglyoxime, nickel, antibacterial activity

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1300 Optimal Placement of Phasor Measurement Units (PMU) Using Mixed Integer Programming (MIP) for Complete Observability in Power System Network

Authors: Harshith Gowda K. S, Tejaskumar N, Shubhanga R. B, Gowtham N, Deekshith Gowda H. S

Abstract:

Phasor measurement units (PMU) are playing an important role in the current power system for state estimation. It is necessary to have complete observability of the power system while minimizing the cost. For this purpose, the optimal location of the phasor measurement units in the power system is essential. In a bus system, zero injection buses need to be evaluated to minimize the number of PMUs. In this paper, the optimization problem is formulated using mixed integer programming to obtain the optimal location of the PMUs with increased observability. The formulation consists of with and without zero injection bus as constraints. The formulated problem is simulated using a CPLEX solver in the GAMS software package. The proposed method is tested on IEEE 30, IEEE 39, IEEE 57, and IEEE 118 bus systems. The results obtained show that the number of PMUs required is minimal with increased observability.

Keywords: PMU, observability, mixed integer programming (MIP), zero injection buses (ZIB)

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1299 Development of Computational Approach for Calculation of Hydrogen Solubility in Hydrocarbons for Treatment of Petroleum

Authors: Abdulrahman Sumayli, Saad M. AlShahrani

Abstract:

For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectively

Keywords: temperature, pressure variations, machine learning, oil treatment

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1298 Simulation of the Reactive Rotational Molding Using Smoothed Particle Hydrodynamics

Authors: A. Hamidi, S. Khelladi, L. Illoul, A. Tcharkhtchi

Abstract:

Reactive rotational molding (RRM) is a process to manufacture hollow plastic parts with reactive material has several advantages compared to conventional roto molding of thermoplastic powders: process cycle time is shorter; raw material is less expensive because polymerization occurs during processing and high-performance polymers may be used such as thermosets, thermoplastics or blends. However, several phenomena occur during this process which makes the optimization of the process quite complex. In this study, we have used a mixture of isocyanate and polyol as a reactive system. The chemical transformation of this system to polyurethane has been studied by thermal analysis and rheology tests. Thanks to these results of the curing process and rheological measurements, the kinetic and rheokinetik of polyurethane was identified. Smoothed Particle Hydrodynamics, a Lagrangian meshless method, was chosen to simulate reactive fluid flow in 2 and 3D configurations of the polyurethane during the process taking into account the chemical, and chemiorehological results obtained experimentally in this study.

Keywords: reactive rotational molding, simulation, smoothed particle hydrodynamics, surface tension, rheology, free surface flows, viscoelastic, interpolation

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1297 Efficient Reconstruction of DNA Distance Matrices Using an Inverse Problem Approach

Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

Abstract:

We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

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1296 Design of a Solar Water Heating System with Thermal Storage for a Three-Bedroom House in Newfoundland

Authors: Ahmed Aisa, Tariq Iqbal

Abstract:

This letter talks about the ready-to-use design of a solar water heating system because, in Canada, the average consumption of hot water per person is approximately 50 to 75 L per day and the average Canadian household uses 225 L. Therefore, this paper will demonstrate the method of designing a solar water heating system with thermal storage. It highlights the renewable hybrid power system, allowing you to obtain a reliable, independent system with the optimization of the ingredient size and at an improved capital cost. The system can provide hot water for a big building. The main power for the system comes from solar panels. Solar Advisory Model (SAM) and HOMER are used. HOMER and SAM are design models that calculate the consumption of hot water and cost for a house. Some results, obtained through simulation, were for monthly energy production, annual energy production, after tax cash flow, the lifetime of the system and monthly energy usage represented by three types of energy. These are system energy, electricity load electricity and net metering credit.

Keywords: water heating, thermal storage, capital cost solar, consumption

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1295 Modeling and Simulation of a Hybrid System Solar Panel and Wind Turbine in the Quingeo Heritage Center in Ecuador

Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

Abstract:

In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

Procedia PDF Downloads 250
1294 A General Iterative Nonlinear Programming Method to Synthesize Heat Exchanger Network

Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

Abstract:

The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

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1293 The Optimization of Immobilization Conditions for Biohydrogen Production from Palm Industry Wastewater

Authors: A. W. Zularisam, Sveta Thakur, Lakhveer Singh, Mimi Sakinah Abdul Munaim

Abstract:

Clostridium sp. LS2 was immobilised by entrapment in polyethylene glycol (PEG) gel beads to improve the biohydrogen production rate from palm oil mill effluent (POME). We sought to explore and optimise the hydrogen production capability of the immobilised cells by studying the conditions for cell immobilisation, including PEG concentration, cell loading and curing times, as well as the effects of temperature and K2HPO4 (500–2000 mg/L), NiCl2 (0.1–5.0 mg/L), FeCl2 (100–400 mg/L) MgSO4 (50–200 mg/L) concentrations on hydrogen production rate. The results showed that by optimising the PEG concentration (10% w/v), initial biomass (2.2 g dry weight), curing time (80 min) and temperature (37 °C), as well as the concentrations of K2HPO4 (2000 mg/L), NiCl2 (1 mg/L), FeCl2 (300 mg/L) and MgSO4 (100 mg/L), a maximum hydrogen production rate of 7.3 L/L-POME/day and a yield of 0.31 L H2/g chemical oxygen demand were obtained during continuous operation. We believe that this process may be potentially expanded for sustained and large-scale hydrogen production.

Keywords: hydrogen, polyethylene glycol, immobilised cell, fermentation, palm oil mill effluent

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1292 Synthesis of Ce Impregnated on Functionalized Graphene Oxide Nanosheets for Transesterification of Propylene Carbonate and Ethanol to Produce Diethyl Carbonate

Authors: Kumar N., Verma S., Park J., Srivastava V. C.

Abstract:

Organic carbonates have the potential to be used as fuels and because of this, their production through non-phosgene routes is a thrust area of research. Di-ethyl carbonate (DEC) synthesis from propylene carbonate (PC) in the presence of alcohol is a green route. In this study, the use of reduced graphene oxide (rGO) based metal oxide catalysts [rGO-MO, where M = Ce] with different amounts of graphene oxide (0.2%, 0.5%, 1%, and 2%) has been investigated for the synthesis of DEC by using PC and ethanol as reactants. The GO sheets were synthesized by an electrochemical process and the catalysts were synthesized using an in-situ method. A theoretical study of the thermodynamics of the reaction was done, which revealed that the reaction is mildly endothermic. The theoretical value of optimum temperature was found to be 420 K. The synthesized catalysts were characterized for their morphological, structural and textural properties using field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), N2 adsorption/desorption, thermogravimetric analysis (TGA), and Raman spectroscopy. Optimization studies were carried out to study the effect of different reaction conditions like temperature (140 °C to 180 °C) and catalyst dosage (0.102 g to 0.255 g) on the yield of DEC. Amongst the various synthesized catalysts, 1% rGO-CeO2 gave the maximum yield of DEC.

Keywords: GO, DEC, propylene carbonate, transesterification, thermodynamics

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1291 Toward a Characteristic Optimal Power Flow Model for Temporal Constraints

Authors: Zongjie Wang, Zhizhong Guo

Abstract:

While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model.

Keywords: optimal power flow, time period, security, economy

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1290 Simulation of Photocatalytic Degradation of Rhodamine B in Annular Photocatalytic Reactor

Authors: Jatinder Kumar, Ajay Bansal

Abstract:

Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

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1289 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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1288 Optimization of Production Scheduling through the Lean and Simulation Integration in Automotive Company

Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Due to the competitive market in which companies are currently engaged, the constant changes require companies to react quickly regarding the variability of demand and process. The changes are caused by customers, or by demand fluctuations or variations of products, or the need to serve customers within agreed delivery taking into account the continuous search for quality and competitive prices in products. These changes end up influencing directly or indirectly the activities of the Planning and Production Control (PPC), which does business in strategic, tactical and operational levels of production systems. One area of concern for organizations is in the short term (operational level), because this planning stage any error or divergence will cause waste and impact on the delivery of products on time to customers. Thus, this study aims to optimize the efficiency of production scheduling, using different sequencing strategies in an automotive company. Seeking to aim the proposed objective, we used the computer simulation in conjunction with lean manufacturing to build and validate the current model, and subsequently the creation of future scenarios.

Keywords: computational simulation, lean manufacturing, production scheduling, sequencing strategies

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1287 Study, Design, Simulation and Fabrication of Microwave Slot Antenna

Authors: Khaled A. Madi, Rema A. Mousbahi, Mostafa B. Abuitbel, Abdualhakim O. Nagi

Abstract:

Antenna perhaps is the most important part of any communication system, it determines the overall efficiency and the direction of radiation of the system. Antennas vary in shape and size on a very wide range. For fast moving vehicles, the antenna should offer as litter aerodynamic resistance as possible. Slot antenna is best suited for this purpose. It offers very little aerodynamic resistance, compact, easy to feed and fabricate. This work presented in this paper deals with the investigation of a half wave slot antenna. The antenna has been studied, analyzed, designed, simulated, fabrication, and tested at the X-band. The field of antenna study is an extremely vast one, and to grasp the fundamentals, two pronged approaches have been used, and the focus was on the fabrication and testing of a slot waveguide directional antenna. Focuses on the design and simulation of slot antennas with an emphasis on optimization of a 9.1 GHz a rectangular waveguide have been used to feed slot antenna. A microwave fed slot antenna used in the communication lab was also simulated. The results have been presented and compared with the expected values, where a good agreement was achieved between the simulation and experimental results.

Keywords: microwave, slot antenna, simulation, fabrication

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1286 Optimization of Multiplier Extraction Digital Filter On FPGA

Authors: Shiksha Jain, Ramesh Mishra

Abstract:

One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

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1285 Application of Alumina-Aerogel in Post-Combustion CO₂ Capture: Optimization by Response Surface Methodology

Authors: S. Toufigh Bararpour, Davood Karami, Nader Mahinpey

Abstract:

Dependence of global economics on fossil fuels has led to a large growth in the emission of greenhouse gases (GHGs). Among the various GHGs, carbon dioxide is the main contributor to the greenhouse effect due to its huge emission amount. To mitigate the threatening effect of CO₂, carbon capture and sequestration (CCS) technologies have been studied widely in recent years. For the combustion processes, three main CO₂ capture techniques have been proposed such as post-combustion, pre-combustion and oxyfuel combustion. Post-combustion is the most commonly used CO₂ capture process as it can be readily retrofit into the existing power plants. Multiple advantages have been reported for the post-combustion by solid sorbents such as high CO₂ selectivity, high adsorption capacity, and low required regeneration energy. Chemical adsorption of CO₂ over alkali-metal-based solid sorbents such as K₂CO₃ is a promising method for the selective capture of diluted CO₂ from the huge amount of nitrogen existing in the flue gas. To improve the CO₂ capture performance, K₂CO₃ is supported by a stable and porous material. Al₂O₃ has been employed commonly as the support and enhanced the cyclic CO₂ capture efficiency of K₂CO₃. Different phases of alumina can be obtained by setting the calcination temperature of boehmite at 300, 600 (γ-alumina), 950 (δ-alumina) and 1200 °C (α-alumina). By increasing the calcination temperature, the regeneration capacity of alumina increases, while the surface area reduces. However, sorbents with lower surface areas have lower CO₂ capture capacity as well (except for the sorbents prepared by hydrophilic support materials). To resolve this issue, a highly efficient alumina-aerogel support was synthesized with a BET surface area of over 2000 m²/g and then calcined at a high temperature. The synthesized alumina-aerogel was impregnated on K₂CO₃ based on 50 wt% support/K₂CO₃, which resulted in the preparation of a sorbent with remarkable CO₂ capture performance. The effect of synthesis conditions such as types of alcohols, solvent-to-co-solvent ratios, and aging times was investigated on the performance of the support. The best support was synthesized using methanol as the solvent, after five days of aging time, and at a solvent-to-co-solvent (methanol-to-toluene) ratio (v/v) of 1/5. Response surface methodology was used to investigate the effect of operating parameters such as carbonation temperature and H₂O-to-CO₂ flowrate ratio on the CO₂ capture capacity. The maximum CO₂ capture capacity, at the optimum amounts of operating parameters, was 7.2 mmol CO₂ per gram K₂CO₃. Cyclic behavior of the sorbent was examined over 20 carbonation and regenerations cycles. The alumina-aerogel-supported K₂CO₃ showed a great performance compared to unsupported K₂CO₃ and γ-alumina-supported K₂CO₃. Fundamental performance analyses and long-term thermal and chemical stability test will be performed on the sorbent in the future. The applicability of the sorbent for a bench-scale process will be evaluated, and a corresponding process model will be established. The fundamental material knowledge and respective process development will be delivered to industrial partners for the design of a pilot-scale testing unit, thereby facilitating the industrial application of alumina-aerogel.

Keywords: alumina-aerogel, CO₂ capture, K₂CO₃, optimization

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1284 Smart Mobility Planning Applications in Meeting the Needs of the Urbanization Growth

Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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1283 Aiming at Optimization of Tracking Technology through Seasonally Tilted Sun Trackers: An Indian Perspective

Authors: Sanjoy Mukherjee

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Discussions on concepts of Single Axis Tracker (SAT) are becoming more and more apt for developing countries like India not just as an advancement in racking technology but due to the utmost necessity of reaching at the lowest Levelized Cost of Energy (LCOE) targets. With this increasing competition and significant fall in feed-in tariffs of solar PV projects, developers are under constant pressure to secure investment for their projects and eventually earn profits from them. Moreover, being the second largest populated country, India suffers from scarcity of land because of higher average population density. So, to mitigate the risk of this dual edged sword with reducing trend of unit (kWh) cost at one side and utilization of land on the other, tracking evolved as the call of the hour. Therefore, the prime objectives of this paper are not only to showcase how STT proves to be an effective mechanism to get more gain in Global Incidence in collector plane (Ginc) with respect to traditional mounting systems but also to introduce Seasonally Tilted Tracker (STT) technology as a possible option for high latitude locations.

Keywords: tracking system, grid connected solar PV plant, CAPEX reduction, levelized cost of energy

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1282 Adopting the Community Health Workers Master List Registry for Community Health Workforce in Kenya

Authors: Gikunda Aloise, Mjema Saida, Barasa Herbert, Wanyungu John, Kimani Maureen

Abstract:

Background: Community Health Workforce (CHW) is health care providers at the community level (Level 1) and serves as a bridge between the community and the formal healthcare system. This human resource has enormous potential to extend healthcare services and ensures that the vulnerable, marginalized, and hard-to-reach populations have access to quality healthcare services at the community and primary health facility levels. However, these cadres are neither recognized, remunerated, nor in most instances, registered in a master list. Management and supervision of CHWs is not easy if their individual demographics, training capacity and incentives is not well documented through a centralized registry. Description: In February 2022, Amref supported the Kenya Ministry of Health in developing a community health workforce database called Community Health Workers Master List Registry (CHWML), which is hosted in Kenya Health Information System (KHIS) tracker. CHW registration exercise was through a sensitization meeting conducted by the County Community Health Focal Person for the Sub-County Community Health Focal Person and Community Health Assistants who uploaded information on individual demographics, training undertaken and incentives received by CHVs. Care was taken to ensure compliance with Kenyan laws on the availability and use of personal data as prescribed by the Data Protection Act, 2019 (DPA). Results and lessons learnt: By June 2022, 80,825 CHWs had been registered in the system; 78,174 (96%) CHVs and 2,636 (4%) CHAs. 25,235 (31%) are male, 55,505 (68%) are female & 85 (1%) are transgender. 39,979. (49%) had secondary education and 2500 (3%) had no formal education. Only 27 641 (34%) received a monthly stipend. 68,436 CHVs (85%) had undergone basic training. However, there is a need to validate the data to align with the current situation in the counties. Conclusions/Next steps: The use of CHWML will unlock opportunities for building more resilient and sustainable health systems and inform financial planning, resource allocation, capacity development, and quality service delivery. The MOH will update the CHWML guidelines in adherence to the data protection act which will inform standard procedures for maintaining, updating the registry and integrate Community Health Workforce registry with the HRH system.

Keywords: community health registry, community health volunteers (CHVs), community health workers masters list (CHWML), data protection act

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1281 Barriers to Participation in Sport for Children without Disability: A Systematic Review

Authors: S. Somerset, D. J. Hoare

Abstract:

Participation in sport is linked to better mental and physical health in children and adults. Studies have shown children who participate in sports benefit from improved social skills, self-confidence, communication skills and a better quality of life. Children who participate in sports from a young age are also more likely to continue to have active lifestyles during adulthood. This is an important consideration with a nation where physical activity levels are declining and the incidences of obesity are rising. Getting children active and keeping them active can provide long term health benefits to the individual but also a potential reduction in health costs in the future. This systematic review aims to identify the barriers to participation in sport for children aged up to 18 years and encompasses both qualitative and quantitative studies. The bibliographic databases, EMBASE, Medline, CINAHL and SportDiscus were searched. Additional hand searches were carried out on review articles found in the searches to identify any studies that may have been missed. Studies involving children up to 18 years without additional needs focusing on barriers to participation in sport were included. Randomised control trials, policy guidelines, studies with sport as an intervention, studies focusing on the female athlete triad, tobacco abuse, alcohol abuse, drug abuse, pre exercise testing, and cardiovascular disease were excluded. Abstract review, full paper review and quality appraisal were conducted by two researchers. A consensus meeting took place to resolve any differences at the abstract, full text and data extraction / quality appraisal stages. The CASP qualitative studies appraisal tool and the CASP cohort studies tool (excluding question 3 and 4 which refer to interventions) were used for quality appraisal in this review. The review identified several salient barriers to participation in sport for children. These barriers ranged from the uniform worn during school physical education lessons to the weather during participation in sport. The most commonly identified barriers in the review include parental support, time allocation, location of the activity and the cost of the activity. Therefore, it would be beneficial for a greater provision to be made within the school environment for children to participate sport. This can reduce the cost and time commitment required from parents to encourage participation. This would help to increase activity levels of children, which ultimately can only be a good thing.

Keywords: barrier, children, participation, sport

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1280 Enzymatic Synthesis of Olive-Based Ferulate Esters: Optimization by Response Surface Methodology

Authors: S. Mat Radzi, N. J. Abd Rahman, H. Mohd Noor, N. Ariffin

Abstract:

Ferulic acid has widespread industrial potential by virtue of its antioxidant properties. However, it is partially soluble in aqueous media, limiting their usefulness in oil-based processes in food, cosmetic, pharmaceutical, and material industry. Therefore, modification of ferulic acid should be made by producing of more lipophilic derivatives. In this study, a preliminary investigation of lipase-catalyzed trans-esterification reaction of ethyl ferulate and olive oil was investigated. The reaction was catalyzed by immobilized lipase from Candida antarctica (Novozym 435), to produce ferulate ester, a sunscreen agent. A statistical approach of Response surface methodology (RSM) was used to evaluate the interactive effects of reaction temperature (40-80°C), reaction time (4-12 hours), and amount of enzyme (0.1-0.5 g). The optimum conditions derived via RSM were reaction temperature 60°C, reaction time 2.34 hours, and amount of enzyme 0.3 g. The actual experimental yield was 59.6% ferulate ester under optimum condition, which compared well to the maximum predicted value of 58.0%.

Keywords: ferulic acid, enzymatic synthesis, esters, RSM

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1279 Water Supply and Demand Analysis for Ranchi City under Climate Change Using Water Evaluation and Planning System Model

Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

Abstract:

There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

Procedia PDF Downloads 408
1278 Micromechanics of Stress Transfer across the Interface Fiber-Matrix Bonding

Authors: Fatiha Teklal, Bachir Kacimi, Arezki Djebbar

Abstract:

The study and application of composite materials are a truly interdisciplinary endeavor that has been enriched by contributions from chemistry, physics, materials science, mechanics and manufacturing engineering. The understanding of the interface (or interphase) in composites is the central point of this interdisciplinary effort. From the early development of composite materials of various nature, the optimization of the interface has been of major importance. Even more important, the ideas linking the properties of composites to the interface structure are still emerging. In our study, we need a direct characterization of the interface; the micromechanical tests we are addressing seem to meet this objective and we chose to use two complementary tests simultaneously. The microindentation test that can be applied to real composites and the drop test, preferred to the pull-out because of the theoretical possibility of studying systems with high adhesion (which is a priori the case with our systems). These two tests are complementary because of the principle of the model specimen used for both the first "compression indentation" and the second whose fiber is subjected to tensile stress called the drop test. Comparing the results obtained by the two methods can therefore be rewarding.

Keywords: Fiber, Interface, Matrix, Micromechanics, Pull-out

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1277 Extraction of Colorant and Dyeing of Gamma Irradiated Viscose Using Cordyline terminalis Leaves Extract

Authors: Urvah-Til-Vusqa, Unsa Noreen, Ayesha Hussain, Abdul Hafeez, Rafia Asghar, Sidrat Nasir

Abstract:

Natural dyes offer an alternative better application in textiles than synthetic ones. The present study will be aimed to employ natural dye extracted from Cordyline terminalis plant and its application into viscose under the influence of gamma radiations. The colorant extraction will be done by boiling dracaena leaves powder in aqueous, alkaline and ethyl acetate mediums. Both dye powder and fabric will be treated with different doses (5-20 kGy) of gamma radiations. The antioxidant, antimicrobial and hemolytic activities of the extracts will also be determined. Different tests of fabric characterization (before and after radiations treatment) will be employed. Dyeing variables just as time, temperature and M: L will be applied for optimization. Standard methods for ISO to evaluate color fastness to light, washing and rubbing will be employed for improvement of color strength 1.5-15.5% of Al, Fe, Cr, and Cu as mordants will be employed through pre, post and meta mordanting. Color depth % & L*, a*, b* and L*, C*, h values will be recorded using spectra flash SF650.

Keywords: natural dyes, gamma radiations, Cordyline terminalis, ecofriendly dyes

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1276 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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1275 Optimization of Solar Tracking Systems

Authors: A. Zaher, A. Traore, F. Thiéry, T. Talbert, B. Shaer

Abstract:

In this paper, an intelligent approach is proposed to optimize the orientation of continuous solar tracking systems on cloudy days. Considering the weather case, the direct sunlight is more important than the diffuse radiation in case of clear sky. Thus, the panel is always pointed towards the sun. In case of an overcast sky, the solar beam is close to zero, and the panel is placed horizontally to receive the maximum of diffuse radiation. Under partly covered conditions, the panel must be pointed towards the source that emits the maximum of solar energy and it may be anywhere in the sky dome. Thus, the idea of our approach is to analyze the images, captured by ground-based sky camera system, in order to detect the zone in the sky dome which is considered as the optimal source of energy under cloudy conditions. The proposed approach is implemented using experimental setup developed at PROMES-CNRS laboratory in Perpignan city (France). Under overcast conditions, the results were very satisfactory, and the intelligent approach has provided efficiency gains of up to 9% relative to conventional continuous sun tracking systems.

Keywords: clouds detection, fuzzy inference systems, images processing, sun trackers

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1274 Multiclass Support Vector Machines with Simultaneous Multi-Factors Optimization for Corporate Credit Ratings

Authors: Hyunchul Ahn, William X. S. Wong

Abstract:

Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

Procedia PDF Downloads 278
1273 Chemical and Electrochemical Syntheses of Two Organic Components of Ginger

Authors: Adrienn Kiss, Karoly Zauer, Gyorgy Keglevich, Rita Molnarne Bernath

Abstract:

Ginger (Zingiber officinale) is a perennial plant from Southeast Asia, widely used as a spice, herb, and medicine for many illnesses since its beneficial health effects were observed thousands of years ago. Among the compounds found in ginger, zingerone [4-hydroxy-3- methoxyphenyl-2-butanone] deserves special attention: it has an anti-inflammatory and antispasmodic effect, it can be used in case of diarrheal disease, helps to prevent the formation of blood clots, has antimicrobial properties, and can also play a role in preventing the Alzheimer's disease. Ferulic acid [(E)-3-(4-hydroxy-3-methoxyphenyl)-prop-2-enoic acid] is another cinnamic acid derivative in ginger, which has promising properties. Like many phenolic compounds, ferulic acid is also an antioxidant. Based on the results of animal experiments, it is assumed to have a direct antitumoral effect in lung and liver cancer. It also deactivates free radicals that can damage the cell membrane and the DNA and helps to protect the skin against UV radiation. The aim of this work was to synthesize these two compounds by new methods. A few of the reactions were based on the hydrogenation of dehydrozingerone [4-(4-Hydroxy-3-methoxyphenyl)-3-buten-2-one] to zingerone. Dehydrozingerone can be synthesized by a relatively simple method from acetone and vanillin with good yield (80%, melting point: 41 °C). Hydrogenation can be carried out chemically, for example by the reaction of zinc and acetic acid, or Grignard magnesium and ethyl alcohol. Another way to complete the reduction is the electrochemical pathway. The electrolysis of dehydrozingerone without diaphragm in aqueous media was attempted to produce ferulic acid in the presence of sodium carbonate and potassium iodide using platinum electrodes. The electrolysis of dehydrozingerone in the presence of potassium carbonate and acetic acid to prepare zingerone was carried out similarly. Ferulic acid was expected to be converted to dihydroferulic acid [3-(4-Hydroxy-3-methoxyphenyl)propanoic acid] in potassium hydroxide solution using iron electrodes, separating the anode and cathode space with a Soxhlet paper sheath impregnated with saturated magnesium chloride solution. For this reaction, ferulic acid was synthesized from vanillin and malonic acid in the presence of pyridine and piperidine (yield: 88.7%, melting point: 173°C). Unfortunately, in many cases, the expected transformations did not happen or took place in low conversions, although gas evolution occurred. Thus, a deeper understanding of these experiments and optimization are needed. Since both compounds are found in different plants, they can also be obtained by alkaline extraction or steam distillation from distinct plant parts (ferulic acid from ground bamboo shoots, zingerone from grated ginger root). The products of these reactions are rich in several other organic compounds as well; therefore, their separation must be solved to get the desired pure material. The products of the reactions described above were characterized by infrared spectral data and melting points. The use of these two simple methods may be informative for the formation of the products. In the future, we would like to study the ferulic acid and zingerone content of other plants and extract them efficiently. The optimization of electrochemical reactions and the use of other test methods are also among our plans.

Keywords: ferulic acid, ginger, synthesis, zingerone

Procedia PDF Downloads 160