Search results for: optimization methods

Authors: Thiago Ribeiro De Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite Asano

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The area of the electricity sector that deals with energy needs by the hydropower and thermoelectric in a coordinated way is called Planning Operating Hydrothermal Power Systems. The aim of this area is to find a political operative to provide electrical power to the system in a specified period with minimization of operating cost. This article proposes a computational tool for solving the planning problem. In addition, this article will be introducing a methodology to find new transfer points between reservoirs increasing energy production in hydroelectric power plants cascade systems. The computational tool proposed in this article applies: i) genetic algorithms to optimize the water transfer and operation of hydroelectric plants systems; and ii) Ant Colony algorithm to find the trajectory with the least energy pumping for the construction of pipes transfer between reservoirs considering the topography of the region. The computational tool has a database consisting of 35 hydropower plants and 41 reservoirs, which are part of the southeastern Brazilian system, which has been implemented in an individualized way.

Keywords: ant colony system, genetic algorithms, hydroelectric, hydrothermal systems, optimization, water transfer between rivers

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Authors: Kexin Chen

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As an important method of transportation to solve the demand and supply contradiction generated in the rapid urbanization process, urban rail traffic system has been rapidly developed over the past ten years in China. During the rapid development, the space of urban rail Transit has encountered many problems, such as space simplification, sensory experience dullness, and poor regional identification, etc. This paper, focus on the study of the negative space of subway station and spatial softening, by comparing and learning from foreign cases. The article sorts out cases at home and abroad, make a comparative study of the cases, analysis more diversified setting of public art, and sets forth propositions on the domestic type of public art in the space of urban rail transit for reference, then shows the relationship of the spatial attribute in the space of urban rail transit and public art form. In this foundation, it aims to characterize more diverse setting ways for public art; then suggests the three public art forms corresponding properties, such as static presenting mode, dynamic image mode, and spatial softening mode; finds out the method of urban public art to optimize negative space.

Keywords: diversification, negative space, optimization strategy, public art planning

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Authors: A. Rostampouryasouri, A. Maghoul, S. Tahersima

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The rapid growth of urbanization and the subsequent increase in population in cities have resulted in the destruction of the environment to cater to the needs of citizens. The industrialization of urban life has led to the production of pollutants, which has significantly contributed to the rise of air pollution. Infrastructure can have both positive and negative effects on air pollution. The effects of infrastructure on air pollution are complex and depend on various factors such as the type of infrastructure, location, and context. This study examines the effects of infrastructure on air pollution, drawing on a range of empirical evidence from Iran and China. Our paper focus for analyzing the data is on the following concepts: 1. Urban design and planning principles and practices 2. Infrastructure efficiency and optimization strategies 3. Public transportation systems and their environmental impact 4. GHG emissions reduction strategies in urban areas 5. Case studies and best practices in sustainable urban development This paper employs a mixed methodology approach with a focus on developmental and applicative purposes. The mixed methods approach combines both quantitative and qualitative research methods to provide a more comprehensive understanding of the research topic. A group of 20 architectural specialists and experts who are proficient in the field of research, design, and implementation of green architecture projects were interviewed in a systematic and purposeful manner. The research method was based on content analysis using MAXQDA2020 software. The findings suggest that policymakers and urban planners should consider the potential impacts of infrastructure on air pollution and take measures to mitigate negative effects while maximizing positive ones. This includes adopting a nature-based approach to urban planning and infrastructure development, investing in information infrastructure, and promoting modern logistic transport infrastructure.

Keywords: GHG emissions, infrastructure efficiency, urban development, urban design

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Authors: Angga S. Fajar, Y. Takahashi, J. Kiyono, S. Sawada

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The structural system concept of RC pier accompanied with multi sliding friction damping mechanism was developed based on numerical analysis approach. However in the implementation, to make design for such kind of this structural system consumes a lot of effort in case high of complexity. During making design, the special behaviors of this structural system should be considered including flexible small deformation, sufficient elastic deformation capacity, sufficient lateral force resistance, and sufficient energy dissipation. The confinement distribution of friction devices has significant influence to its. Optimization and prediction with multi function regression of this structural system expected capable of providing easier and simpler design method. The confinement distribution of friction devices is optimized with SNOPT in Opensees, while some design variables of the structure are predicted using multi function regression of ANN. Based on the optimization and prediction this structural system is able to be designed easily and simply.

Keywords: RC Pier, multi sliding friction device, optimal design, flexible small deformation

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Authors: Basil Manos, Thomas Bournaris, Christina Moulogianni

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The European agricultural policy supports all member states to apply agricultural development plans for the development of their agricultural sectors. A specific measure of the agricultural development plans refers to young people in order to enter into the agricultural sector. This measure helps the participating young farmers in achieving maximum efficiency, using methods and environmentally friendly practices, by altering their farm plans. This study applies a Multicriteria Mathematical Programming (MCDA) model for the young farmers to find farm plans that achieve the maximum gross margin and the minimum environmental impacts (less use of fertilizers and irrigation water). The analysis was made in the region of Central Macedonia, Greece, among young farmers who have participated in the “Setting up Young Farmers” measure during 2007-2010. The analysis includes the implementation of the MCDA model for the farm plans optimization and the comparison of selected environmental indicators with those of the existent situation.

Keywords: multicriteria, optimum farm plans, environmental impacts, sustainable management

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Authors: Fazl Ullah, Rahmat Ullah

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This paper shows a comprehensive learning focused on the optimization of gas production in shale gas reservoirs through hydraulic fracturing. Shale gas has emerged as an important unconventional vigor resource, necessitating innovative techniques to enhance its extraction. The key objective of this study is to examine the influence of fracture parameters on reservoir productivity and formulate strategies for production optimization. A sophisticated model integrating gas flow dynamics and real stress considerations is developed for hydraulic fracturing in multi-stage shale gas reservoirs. This model encompasses distinct zones: a single-porosity medium region, a dual-porosity average region, and a hydraulic fracture region. The apparent permeability of the matrix and fracture system is modeled using principles like effective stress mechanics, porous elastic medium theory, fractal dimension evolution, and fluid transport apparatuses. The developed model is then validated using field data from the Barnett and Marcellus formations, enhancing its reliability and accuracy. By solving the partial differential equation by means of COMSOL software, the research yields valuable insights into optimal fracture parameters. The findings reveal the influence of fracture length, diversion capacity, and width on gas production. For reservoirs with higher permeability, extending hydraulic fracture lengths proves beneficial, while complex fracture geometries offer potential for low-permeability reservoirs. Overall, this study contributes to a deeper understanding of hydraulic cracking dynamics in shale gas reservoirs and provides essential guidance for optimizing gas production. The research findings are instrumental for energy industry professionals, researchers, and policymakers alike, shaping the future of sustainable energy extraction from unconventional resources.

Keywords: fluid-solid coupling, apparent permeability, shale gas reservoir, fracture property, numerical simulation

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Samuel Quashie

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Ph.D. Construction Management methodology and mixed methods are organized to guide the researcher to assemble and assess data in the research activities. Construction management research is close to business management and social science research. It also contributes to researching the phenomenon and answering the research question, generating an integrated management system for post-disaster reconstruction in construction and related industries. Research methodology and methods drive the research to achieve the goal or goals, contribute to knowledge, or increase knowledge. This statement means the research methodology, mixed methods, aim, objectives, and processes address the research question, facilitate its achievement and foundation to conduct the study. Mixed methods use project-based case studies, interviews, observations, literature and archival document reviews, research questionnaires, and surveys, and evaluation of integrated systems used in the construction industry and related industries to address the research work. The research mixed methods (qualitative, quantitative) define the research topic and establish a more in-depth study. The research methodology is action research, which involves the collaboration of participants and service users to collect and evaluate data, studying the phenomenon, research question(s) to improve the situation in post-disaster reconstruction phase management.

Keywords: methodology, Ph.D. research, post-disaster reconstruction, mixed-methods qualitative and quantitative

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Authors: Zelikha Labbani

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Many biotechnology methods have been used in plant breeding programs. The in vitro isolated microspore culture is the one of these methods. For durum wheat, the use of this technology has been limited for a long time due to the low number of embryos produced and also most regeneration plants are albina. The objective of this paper is to show that using isolated microspores culture on durum wheat is possible due to the development of the new methods using the new pretreatment of the microspores before their isolation and cultivation.

Keywords: isolated microspore culture, pretreatments, in vitro embryogenesis, plant breeding program

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Authors: Samson Olusegun Apantaku, Adetayo K. Aromolaran, Giyatt Hammed

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The study assessed the use of participatory research methods among Federal University of Agriculture Abeokuta, Nigeria (FUNAAB) researchers. Simple random sampling technique was used to select one hundred and twenty respondents from the study area. Data were collected using a questionnaire. Data collected were subjected to descriptive and inferential statistical analyses. Results showed that 75.8% of the respondents were males while only 21.3% were female. The mean age of the respondents was 38.8 years and most (77.5%) of them were married. 15% of the respondents were in professorial cadre, 21.7% and 20% of the respondents were senior lecturers/fellow and lecturer/research fellow I&II respectively. The results further revealed that 93.3% of the respondents were aware of participatory research methods and 82.5% of the respondents have utilized it before. The average period of usage was 2.7 years and participation by consultation (86.7%) and interactive participation (76.7%) were mostly used. Most (94.2%) indicated that fund was the major hindrance to the use of participatory research methods. The result of correlation analysis showed that there was significant relationship between the years of research experience, designation post (status) of the respondents and usage of participatory research methods (r = 0.034, 0.031, p < 0.05). The study concluded that most of the researchers were aware of and used participatory research methods, which could influence the quality of their research or make it acceptable to the end users. It was recommended that more funds should be made available and accessible for participatory research. All researchers should be trained and encouraged to make use of participatory research methods in their research activities so as to achieve effective research and capacity building that could enhance adoption of technologies and increase agricultural production in the country. Farmers’ capacity to participate in agricultural research should also be enhanced.

Keywords: participatory research, participatory research methods, awareness, utilization

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Authors: Swapnila V. Vanshiv, Hemant P. Joshi, Atul B. Aware

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Current study illustrates the formulation of floating microspheres for purpose of gastroretention of Dipyridamole which shows pH dependent solubility, with the highest solubility in acidic pH. The formulation involved hollow microsphere preparation by using solvent evaporation technique. Concentrations of rate controlling polymer, hydrophilic polymer, internal phase ratio, stirring speed were optimized to get desired responses, namely release of Dipyridamole, buoyancy of microspheres, entrapment efficiency of microspheres. In the formulation, the floating microspheres were prepared by using ethyl cellulose as release retardant and HPMC as a low density hydrophilic swellable polymer. Formulated microspheres were evaluated for their physical properties such as particle size and surface morphology by optical microscopy and SEM. Entrapment efficiency, floating behavior and drug release study as well the formulation was evaluated for in vivo gastroretention in rabbits using gamma scintigraphy. Formulation showed 75% drug release up to 10 hr with entrapment efficiency of 91% and 88% buoyancy till 10 hr. Gamma scintigraphic studies revealed that the optimized system was retained in the gastric region (stomach) for a prolonged period i.e. more than 5 hr.

Keywords: Dipyridamole microspheres, gastroretention, HPMC, optimization method

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Authors: Hossein Keshavarz, Alejandro Ramirez-Serrano

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Energy efficiency and locomotion speed are two key parameters for legged robots; thus, finding ways to improve them are important. This paper proposes a locomotion framework to analyze the energy usage and speed of quadruped robots via a Genetic Algorithm (GA) optimization process. For this, a quadruped robot platform with joint redundancy in its hind legs that we believe will help multi-legged robots improve their speed and energy consumption is used. ContinuO, the quadruped robot of interest, has 14 active degrees of freedom (DoFs), including three DoFs for each front leg, and unlike previously developed quadruped robots, four DoFs for each hind leg. ContinuO aims to realize a cost-effective quadruped robot for real-world scenarios with high speeds and the ability to overcome large obstructions. The proposed framework is used to locomote the robot and analyze its energy consumed at diverse stride lengths and locomotion speeds. The analysis is performed by comparing the obtained results in two modes, with and without the joint redundancy on the robot’s hind legs.

Keywords: genetic algorithm optimization, locomotion path planning, quadruped robots, redundant legs

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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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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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: Carlos Gonzalez

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This paper describes a system to optimize the use of the internet by clients requiring downloading of videos at peak hours. The system consists of a web server belonging to a provider of video contents, a provider of internet communications and a software application running on a client’s computer. The client using the application software will communicate to the video provider a list of the client’s future video demands. The video provider calculates which videos are going to be more in demand for download in the immediate future, and proceeds to request the internet provider the most optimal hours to do the downloading. The times of the downloading will be sent to the application software, which will use the information of pre-established hours negotiated between the video provider and the internet provider to download those videos. The videos will be saved in a special protected section of the user’s hard disk, which will only be accessed by the application software in the client’s computer. When the client is ready to see a video, the application will search the list of current existent videos in the area of the hard disk; if it does exist, it will use this video directly without the need for internet access. We found that the best way to optimize the download traffic of videos is by negotiation between the internet communication provider and the video content provider.

Keywords: internet optimization, video download, future demands, secure storage

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: María Rojo Granados

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This work presents an empirical investigation of the performance of pink and purple petunia petals and orange and red geranium petals on a linen fabric using the Eco Print technique. This theoretical and practical approach represents an advance in the textile world towards sustainable dyeing and printing methods. It is understood that the possibility of mass printing or dyeing through these methods in fashion is complex, but it can be an approach toward a more sustainable industry. The research consists of twenty-two empirical tests where different processes and methods are applied and explained at different temperatures and using different mordants. The test results allow the selection of which printing and dyeing methods can be applied to the fashion industry in an environmentally consistent way.

Keywords: dyeing, empirical tests, petals, performance, printing, sustainably

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Authors: F. L. Motta, M. H. A. Santana

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Humic Acids (HA) were produced by a Trichoderma viride strain under submerged fermentation in a medium based on the oil palm Empty Fruit Bunch (EFB) and the main variables of the process were optimized by using response surface methodology. A temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the variables that maximize the HA production, within the physicochemical and biological limits of the process. The optimized conditions led to an experimental HA concentration of 428.4±17.5 mg/L, which validated the prediction from the statistical model of 412.0mg/L. This optimization increased about 7–fold the HA production previously reported in the literature. Additionally, the time profiles of HA production and fungal growth confirmed our previous findings that HA production preferably occurs during fungal sporulation. The present study demonstrated that T. viride successfully produced HA via the submerged fermentation of EFB and the process parameters were successfully optimized using a statistics-based response surface model. To the best of our knowledge, the present work is the first report on the optimization of HA production from EFB by a biotechnological process, whose feasibility was only pointed out in previous works.

Keywords: empty fruit bunch, humic acids, submerged fermentation, Trichoderma viride

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Authors: Ian Marc G. Cabugsa, Kim Ryan Won, Kareem Mamac, Manuel Dee, Merlita Garcia

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An optimized cacao fermentation technique was developed for the cacao farmers of Davao City Philippines. Cacao samples with weights ranging from 150-250 kilograms were collected from various cacao farms in Davao City and Zamboanga City Philippines. Different fermentation techniques were used starting with design of the sweat box, prefermentation conditionings, number of days for fermentation and number of turns. As the beans are being fermented, its temperature was regularly monitored using a digital thermometer. The resultant cacao beans were assessed using physical and chemical means. For the physical assessment, the bean cut test, bean count tests, and sensory test were used. Quantification of theobromine, caffeine, and antioxidants in the form of equivalent quercetin was used for chemical assessment. Both the theobromine and caffeine were analyzed using HPLC method while the antioxidant was analyzed spectrometrically. To come up with the best fermentation procedure, the different assessment were given priority coefficients wherein the physical tests – taste test, cut, and bean count tests were given priority over the results of the chemical test. The result of the study was an optimized fermentation protocol that is readily adaptable and transferable to any cacao cooperatives or groups in Mindanao or even Philippines as a whole.

Keywords: cacao, fermentation, HPLC, optimization, Philippines

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Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

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In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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Authors: Min Sang Lee, Hee Jae Shin, In Pyo Cha, Sun Ho Ko, Hyun Kyung Yoon, Hong Gun Kim, Lee Ku Kwac

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The prepreg process among the CFRP (Carbon Fiber Reinforced Plastic) forming methods is the short term of ‘Pre-impregnation’, which is widely used for aerospace composites that require a high quality property such as a fiber-reinforced woven fabric, in which an epoxy hardening resin is impregnated. the reality is, however, that this process requires continuous researches and developments for its commercialization because the delamination characteristically develops between the layers when a great weight is loaded from outside. to supplement such demerit, three lamination methods among the prepreg lamination methods of CFRP were designed to minimize the delamination between the layers due to external impacts. Further, the newly designed methods and the existing lamination methods were analyzed through a mechanical characteristic test, Interlaminar Shear Strength test. The Interlaminar Shear Strength test result confirmed that the newly proposed three lamination methods, i.e. the Roll, Half and Zigzag laminations, presented more excellent strengths compared to the conventional Ply lamination. The interlaminar shear strength in the roll method with relatively dense fiber distribution was approximately 1.75% higher than that in the existing ply lamination method, and in the half method, it was approximately 0.78% higher.

Keywords: carbon fiber reinforced plastic(CFRP), pre-impregnation, laminating method, interlaminar shear strength (ILSS)

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Authors: Djaafar F., Hadri B., Bachir G.

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We studied mainly the influence of temperature, thickness, molar fraction and the doping of the various layers (emitter, base, BSF and window) on the performances of a photovoltaic solar cell. In a first stage, we optimized the performances of the InGaP/GaAs dual-junction solar cell while varying its operation temperature from 275°K to 375 °K with an increment of 25°C using a virtual wafer fabrication TCAD Silvaco. The optimization at 300°K led to the following result Icc =14.22 mA/cm2, Voc =2.42V, FF =91.32 %, η = 22.76 % which is close with those found in the literature. In a second stage ,we have varied the molar fraction of different layers as well their thickness and the doping of both emitters and bases and we have registered the result of each variation until obtaining an optimal efficiency of the proposed solar cell at 300°K which was of Icc=14.35mA/cm2,Voc=2.47V,FF=91.34,and η =23.33% for In(1-x)Ga(x)P molar fraction( x=0.5).The elimination of a layer BSF on the back face of our cell, enabled us to make a remarkable improvement of the short-circuit current (Icc=14.70 mA/cm2) and a decrease in open circuit voltage Voc and output η which reached 1.46V and 11.97% respectively. Therefore, we could determine the critical parameters of the cell and optimize its various technological parameters to obtain the best performance for a dual junction solar cell. This work opens the way with new prospects in the field of the photovoltaic one. Such structures will thus simplify the manufacturing processes of the cells; will thus reduce the costs while producing high outputs of photovoltaic conversion.

Keywords: modeling, simulation, multijunction, optimization, silvaco ATLAS

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Authors: Fatiha Teklal, Bachir Kacimi, Arezki Djebbar

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

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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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Authors: Bahiru Tsegaye, Chandrajit Balomajumder, Partha Roy

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The limited supply and related negative environmental consequence of fossil fuels are driving researcher for finding sustainable sources of energy. Lignocellulose biomass like sorghum straw is considered as among cheap, renewable and abundantly available sources of energy. However, lignocellulose biomass conversion to bioenergy like bioethanol is hindered due to the reluctant nature of lignin in the biomass. Therefore, removal of lignin is a vital step for lignocellulose conversion to renewable energy. The aim of this study is to optimize microwave pretreatment conditions using design expert software to remove lignin and to release maximum possible polysaccharides from sorghum straw for efficient hydrolysis and fermentation process. Sodium hydroxide concentration between 0.5-1.5%, v/v, pretreatment time from 5-25 minutes and pretreatment temperature from 120-2000C were considered to depolymerize sorghum straw. The effect of pretreatment was studied by analyzing the compositional changes before and after pretreatments following renewable energy laboratory procedure. Analysis of variance (ANOVA) was used to test the significance of the model used for optimization. About 32.8%-48.27% of hemicellulose solubilization, 53% -82.62% of cellulose release, and 49.25% to 78.29% lignin solubilization were observed during microwave pretreatment. Pretreatment for 10 minutes with alkali concentration of 1.5% and temperature of 1400C released maximum cellulose and lignin. At this optimal condition, maximum of 82.62% of cellulose release and 78.29% of lignin removal was achieved. Sorghum straw at optimal pretreatment condition was subjected to enzymatic hydrolysis and fermentation. The efficiency of hydrolysis was measured by analyzing reducing sugars by 3, 5 dinitrisylicylic acid method. Reducing sugars of about 619 mg/g of sorghum straw were obtained after enzymatic hydrolysis. This study showed a significant amount of lignin removal and cellulose release at optimal condition. This enhances the yield of reducing sugars as well as ethanol yield. The study demonstrates the potential of microwave pretreatments for enhancing bioethanol yield from sorghum straw.

Keywords: cellulose, hydrolysis, lignocellulose, optimization

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Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

Abstract:

Drying technologies for various food processing operations shares an inevitable linkage with energy, cost and environmental sustainability. Hence, solar drying of food grains has become imperative choice to combat duo challenges of meeting high energy demand for drying and to address climate change scenario. But performance and reliability of solar dryers depend hugely on sunshine period, climatic conditions, therefore, offer a limited control over drying conditions and have lower efficiencies. Solar drying technology, supported by Photovoltaic (PV) power plant and hybrid type solar air collector can potentially overpower the disadvantages of solar dryers. For development of such robust hybrid dryers; to ensure quality and shelf-life of paddy grains the optimization of process parameter becomes extremely critical. Investigation of the moisture distribution profile within the grains becomes necessary in order to avoid over drying or under drying of food grains in hybrid solar dryer. Computational simulations based on finite element modeling can serve as potential tool in providing a better insight of moisture migration during drying process. Hence, present work aims at optimizing the process parameters and to develop a 3-dimensional (3D) finite element model (FEM) for predicting moisture profile in paddy during solar drying. COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Furthermore, optimization of process parameters (power level, air velocity and moisture content) was done using response surface methodology in design expert software. 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed and validated with experimental data. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Furthermore, optimized process parameters for drying paddy were found to be 700 W, 2.75 m/s at 13% (wb) with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product. PV-integrated hybrid solar dryers can be employed as potential and cutting edge drying technology alternative for sustainable energy and food security.

Keywords: finite element modeling, moisture migration, paddy grain, process optimization, PV integrated hybrid solar dryer

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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

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Authors: Fabian Velasquez, John Espitia, Henry Hernadez, Sebastian Escobar, Jader Rodriguez

Abstract:

Non-centrifuged cane sugar (NCS) is a concentrated product obtained through the evaporation of water contain from sugarcane juice inopen heat exchangers (OE). The heat supplied to the evaporation stages is obtained from the cane bagasse through the thermochemical process of combustion, where the thermal energy released is transferred to OE by the flue gas. Therefore, the optimization of energy usage becomes essential for the proper design of the production process. For optimize the energy use, it is necessary modeling and simulation of heat transfer between the combustion gases and the juice and to understand the major mechanisms involved in the heat transfer. The main objective of this work was simulated heat transfer phenomena between the flue gas and open heat exchangers using Computational Fluid Dynamics model (CFD). The simulation results were compared to field measured data. Numerical results about temperature profile along the flue gas pipeline at the measurement points are in good accordance with field measurements. Thus, this study could be of special interest in design NCS production process and the optimization of the use of energy.

Keywords: mathematical modeling, design variables, computational fluid dynamics, overall thermal efficiency

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Authors: Aleksandar Hatzivelkos

Abstract:

The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

Procedia PDF Downloads 133