Search results for: teaching-learning based optimization

Authors: Rihab Hamdi, Amel Hadri Hamida, Fatiha Khelili, Sakina Zerouali, Ouafae Bennis

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This paper features a comparative study performance of sliding mode controller (SMC) for closed-loop voltage control of direct current to direct current (DC-DC) three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM) with SMC based on hysteresis modulation (HM) where an adaptive feedforward technique is adopted. On one hand, for the PWM-based SM, the approach is to incorporate a fixed-frequency PWM scheme which is effectively a variant of SM control. On the other hand, for the HM-based SM, oncoming an adaptive feedforward control that makes the hysteresis band variable in the hysteresis modulator of the SM controller in the aim to restrict the switching frequency variation in the case of any change of the line input voltage or output load variation are introduced. The results obtained under load change, input change and reference change clearly demonstrates a similar dynamic response of both proposed techniques, their effectiveness is fast and smooth tracking of the desired output voltage. The PWM-based SM technique has greatly improved the dynamic behavior with a bit advantageous compared to the HM-based SM technique, as well as provide stability in any operating conditions. Simulation studies in MATLAB/Simulink environment have been performed to verify the concept.

Keywords: DC-DC converter, hysteresis modulation, parallel multi-cells converter, pulse-width modulation, robustness, sliding mode control

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Authors: Soheila Sadeghi

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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: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

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Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

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Authors: Kriangkrai Aranyarat

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The effect of N2 pretreatment on the catalytic activity of tungsten-based catalysts was investigated in the metathesis of ethylene and trans-2-butene at 450oC and atmospheric pressure. The presence of tungsten active species was confirmed by UV-Vis and Raman spectroscopy. Compared to the WO3-based catalysts treated in air, higher amount of WO42- tetrahedral species and lower amount of WO3 crystalline species were observed on the N2-treated ones. These contribute to the higher conversion of 2-butene and propylene selectivity during 10 h time-on-stream. Moreover, N2 treatment led to lower amount of coke formation as revealed by TPO of the spent catalysts.

Keywords: metathesis, pretreatment, propylene, tungsten

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Authors: E. Kharaishvili

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The paper shows the necessity of farm diversification in accordance with the current trends in agricultural sector of Georgia. The possibilities for the diversification and the corresponding economic policy are suggested. The causes that hinder diversification of farms are revealed, possibilities of diversification are suggested and the ability of increasing employment through diversification is proved. Index of harvest diversification is calculated based on the areas used for cereals and legumes, potatoes and vegetables and other food crops. Crop and livestock production indexes are analyzed, correlation between crop capacity index and value-added per one worker and one ha is studied. Based on the research farm diversification strategies and priorities of corresponding economic policy are presented. Based on the conclusions relevant recommendations are suggested.

Keywords: farm diversification, diversification index, agricultural development policy

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Authors: Hamid Rostami, Ali Fallah Yeznabad, Mohammad H. Baziar

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The energy-based method for evaluating seismic soil liquefaction has two main sections. First is the demand energy, which is dissipated energy of earthquake at a site, and second is the capacity energy as a representation of soil resistance against liquefaction hazard. In this study, using a statistical analysis of recorded data by 14 down-hole array sites in California, an empirical equation was developed to estimate the demand energy at sites. Because determination of capacity energy at a site needs to calculate several site calibration factors, which are obtained by experimental tests, in this study the standard penetration test (SPT) N-value was assumed as an alternative to the capacity energy at a site. Based on this assumption, the empirical equation was employed to calculate the demand energy for 193 liquefied and no-liquefied sites and then these amounts were plotted versus the corresponding SPT numbers for all sites. Subsequently, a discrimination analysis was employed to determine the equations of several boundary curves for various liquefaction likelihoods. Finally, a comparison was made between the probabilistic model and the commonly used stress method. As a conclusion, the results clearly showed that energy-based method can be more reliable than conventional stress-based method in evaluation of liquefaction occurrence.

Keywords: energy demand, liquefaction, probabilistic analysis, SPT number

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Authors: Nibedita Pani, Vishnu Tejani, T. S. Anantha Singh

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Water pollution resulting from discharge of partial/not treated textile wastewater containing high carbon and nitrogen pollutants pose a huge threat to the environment, ecosystem, and human health. It is essential to remove carbon- and nitrogen-based organic pollutants more effectively from industrial wastewater before discharging. The present study focuses on removal of carbon-based pollutant in particular COD (chemical oxygen demand) and nitrogen-based pollutants, in particular, ammoniacal nitrogen by Fenton oxidation process using Fe²⁺ and H₂O₂ as reagents. The study was carried out with high strength wastewater containing initial COD 5632 mg/L and NH⁴⁺-N 1372 mg/L. The major operating condition like pH was varied between 1.0 to 4.0. The maximum degradation was obtained at pH 3.0 taking the molar ratio of Fe²⁺/H₂O₂ as 1:1. At this pH, the removal efficiencies of COD and ammoniacal nitrogen were found to be 77.27% and 74.9%, respectively. The Fenton process can be the best alternative for the simultaneous removal of COD and NH4+-N from industrial wastewater.

Keywords: ammoniacal nitrogen, COD, Fenton oxidation, industrial wastewater

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Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

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Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular, compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins, which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed, and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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Authors: Rahma Amri, Narjès Bellamine Ben Saoud

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Sustainable development or sustainability is one of the most urgent issues in actual debate in almost domains. Particularly the significant way the software pervades our live should make it in the center of sustainability concerns. The social aspects of sustainability haven’t been well studied in the context of software systems and still immature research field that needs more interest among researchers’ community. This paper presents a Goal-Question-Metric based approach to assess social sustainability of software systems. The approach is based on a generic social sustainability model taken from Social sciences.

Keywords: software assessment approach, social sustainability, goal-question-metric paradigm, software project metrics

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Ling-Lang Huang

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Research Background: Historically, the evolution of medicine has not only aimed to extend life but has also inadvertently introduced suffering in the process of maintaining life, presenting a contemporary challenge. We must carefully assess the conflict between the length of life and the quality of living. Evidence-Based Medicine (EBM) exists primarily to ensure the quality of cures. However, EBM alone does not fulfill our ultimate medical goals; we must also evaluate Value-Based Medicine (VBM) to find the best treatment for patients. Research Methodology: We can attempt to integrate EBM with VBM. Within the five steps of EBM, the first three steps (Ask—Acquire—Appraise) focus on the physical aspect of humans. However, in the fourth and fifth steps (Apply—Assess), the focus shifts from the physical to applying evidence-based treatment to the patient and assessing its effectiveness, considering a holistic approach to the individual. To consider VBM for patients, we can divide the process into three steps: The first step is "awareness," recognizing that each patient inhabits a different life-world and possesses unique differences. The second step is "integration," akin to the hermeneutic concept of the Fusion of Horizons. This means being aware of differences and also understanding the origins of these patient differences. The third step is "respect," which involves setting aside our adherence to medical objectivity and scientific rigor to respect the ultimate healthcare decisions made by individuals regarding their lives. Discussion and Conclusion: After completing these three steps of VBM, we can return to the fifth step of EBM: Assess. Our assessment can now transcend the physical treatment focus of the initial steps to align with a holistic care philosophy.

Keywords: shared decision-making, evidence-based medicine, values-based medicine, holistic healthcare

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Authors: Yu-Ping Chiu, Dung-Ying Lin

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Traditional staff scheduling methods, relying on employee experience, often lead to inefficiencies and resource waste. The challenges of transferring scheduling expertise and adapting to changing labor regulations further complicate this process. Manual approaches become increasingly impractical as companies accumulate complex scheduling rules over time. This study proposes an algorithmic optimization approach to address these issues, aiming to expedite scheduling while ensuring strict compliance with labor regulations and company policies. The method focuses on generating optimal schedules that minimize weighted company objectives within a compressed timeframe. Recognizing the limitations of conventional commercial software in modeling and solving complex real-world scheduling problems efficiently, this research employs Tabu Search with both long-term and short-term memory structures. The study will present numerical results and managerial insights to demonstrate the effectiveness of this approach in achieving intelligent and efficient staff scheduling.

Keywords: intelligent memory structures, mixed integer programming, meta-heuristics, staff scheduling problem, tabu search

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Authors: Mujahid S. Alharbi

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The construction of process plants in oil and gas-producing countries, such as Saudi Arabia, necessitates substantial investment in design and building. Each new plant, while unique, includes common building types, suggesting an opportunity for design standardization. This study investigates the adoption of standardized Issue For Construction (IFC) packages for non-process buildings in Saudi Aramco. A SWOT analysis presents the strengths, weaknesses, opportunities, and threats of this approach. The approach's benefits are illustrated using the Hawiyah Unayzah Gas Reservoir Storage Program (HUGRSP) as a case study. Standardization not only offers significant cost savings and operational efficiencies but also expedites project timelines, reduces the potential for change orders, and fosters local economic growth by allocating building tasks to local contractors. Standardization also improves project management by easing interface constraints between different contractors and promoting adaptability to future industry changes. This research underscores the standardization of non-process buildings as a powerful strategy for cost optimization, efficiency enhancement, and local economic development in process plant construction within the oil and gas sector.

Keywords: building, construction, management, project, standardization

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases

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Authors: Saud Al Mahdi

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Traditionally,portfolio managers have been discouraged from timing the market. This means, for example, that equity managers have been forced to adhere strictly to a benchmark with static or relatively stable components, such as the SP 500 or the Russell 3000. This means that the portfolio’s exposures to all risk factors should mimic as closely as possible the corresponding exposures of the benchmark. The main risk factor, of course, is the market itself. Effectively, a long-only portfolio would be constrained to have a beta 1. More recently, however, managers have been given greater discretion to adjust their portfolio’s risk exposures (in particular, the beta of their portfolio) dynamically to match the manager’s beliefs about future performance of the risk factors themselves. This freedom translates into the manager’s ability to adjust the portfolio’s beta dynamically. These strategies have come to be known as smart beta strategies. Adjusting beta dynamically amounts to attempting to "time" the market; that is, to increase exposure when one anticipates that the market will rise, and to decrease it when one anticipates that the market will fall. Traditionally, market timing has been believed to be impossible to perform effectively and consistently. Moreover, if a majority of market participants do it, their combined actions could destabilize the market. The aim of this project is to investigate so-called smart beta strategies to determine if they really can add value, or if they are merely marketing gimmicks used to sell dubious investment strategies.

Keywords: beta, alpha, active portfolio management, trading strategies

Procedia PDF Downloads 356

Authors: Riddhiman Sherlekar, Umang Paladia, Rachit Desai, Yash Patel

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A number of surfactants which exhibit ultra-low interfacial tension and an excellent microemulsion phase behavior with crude oils of low to medium gravity are not sufficiently soluble at optimum salinity to produce stable aqueous solutions. Such solutions often show phase separation after a few days at reservoir temperature, which does not suffice the purpose and the time is short when compared to the residence time in a reservoir for a surfactant flood. The addition of polymer often exacerbates the problem although the poor stability of the surfactant at high salinity remains a pivotal issue. Surfactants such as SDS, Ctab with large hydrophobes produce lowest IFT, but are often not sufficiently water soluble at desired salinity. Hydrophilic co-solvents and/or co-surfactants are needed to make the surfactant-polymer solution stable at the desired salinity. This study focuses on contrasting the effect of addition of a co-solvent in stability of a surfactant –oil emulsion. The idea is to use a co-surfactant to increase stability of an emulsion. Stability of the emulsion is enhanced because of creation of micro-emulsion which is verified both visually and with the help of particle size analyzer at varying concentration of salinity, surfactant and co-surfactant. A lab-experimental method description is provided and the method is described in detail to permit readers to emulate all results. The stability of the oil-water emulsion is visualized with respect to time, temperature, salinity of the brine and concentration of the surfactant. Nonionic surfactant TX-100 when used as a co-surfactant increases the stability of the oil-water emulsion. The stability of the prepared emulsion is checked by observing the particle size distribution. For stable emulsion in volume% vs particle size curve, the peak should be obtained for particle size of 5-50 nm while for the unstable emulsion a bigger sized particles are observed. The UV-Visible spectroscopy is also used to visualize the fraction of oil that plays important role in the formation of micelles in stable emulsion. This is important as the study will help us to decide applicability of the surfactant based EOR method for a reservoir that contains a specific type of crude. The use of nonionic surfactant as a co-surfactant would also increase the efficiency of surfactant EOR. With the decline in oil discoveries during the last decades it is believed that EOR technologies will play a key role to meet the energy demand in years to come. Taking this into consideration, the work focuses on the optimization of the secondary recovery(Water flooding) with the help of surfactant and/or co-surfactants by creating desired conditions in the reservoir.

Keywords: co-surfactant, enhanced oil recovery, micro-emulsion, surfactant flooding

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Authors: Golovchun Aleftina, Dabyltayeva Raikhan

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Nowadays, in the world of widely developing cross-cultural interactions and rapidly changing demands of the global labor market, foreign language teaching and learning has taken a special role not only in school education but also in everyday life. Cognitive Lingua-Cultural Methodology of Foreign Language Teaching originated in Kazakhstan brings a communicative approach to the forefront in foreign language teaching that gives raise a variety of techniques to make the language learning a real communication. One of these techniques is Computer Assisted Language Learning. In our article, we aim to: demonstrate what learning benefits students are likely to get by teachers having implemented computer-based technologies into foreign language teaching process; prove that technology-based classroom serves as the best tool for interactive and efficient language learning; give examples of classroom sufficient organization with computer-based activities.

Keywords: computer assisted language learning, learning benefits, foreign language teaching process, implementation, communicative approach

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Authors: Robert Jesiolowski, Monique Jesiolowski

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Today more than ever before, we have access to new technologies which provide unforeseen opportunities for educators to pursue in online education. It starts with an idea, but that needs to be coupled with the right team of experts willing to take big risks and put in the hard work to build something different. An instructional design team was empowered to reimagine an Introduction to Sociology university course as a Game-Based Learning (GBL) experience utilizing cutting edge Virtual Reality (VR) technology. The result was a collaborative process that resulted in a type of learning based in Game theory, Method of Loci, and VR Immersion Simulations to promote deeper retention of core concepts. The team deconstructed the way that university courses operated, in order to rebuild the educational process in a whole learner-centric manner. In addition to a review of the build process, this paper will explore the results of in-course surveys completed by student participants.

Keywords: higher education, innovation, virtual reality, game-based learning, loci method

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Authors: M. Ahmed Eldesouky, S. Nasr, A. Beltagy

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Groundwater is generally considered as the best source for aquaculture as it is well protected from contamination. The most common problem limiting the use of groundwater in Egypt is its high iron, manganese and ammonia content. This problem is often overcome by applying the treatment before use. Aeration in many cases is not enough to oxidize iron and manganese in complex forms with organics. Most of the treatment we use potassium permanganate as an oxidizer followed by a pressurized closed green sand filter. The aim of present study is to investigate the optimum characteristics of groundwater to give lowest iron, manganese and ammonia, maximum production and quality of fish in aquaculture in El-Max Research Station. The major design goal of the system was determined the optimum time for harvesting the treated water, pH, and Glauconite weight to use it for aquaculture process in the research site and achieve the Egyptian law (48/1982) and EPA level required for aquaculture. The water characteristics are [Fe = 0.116 mg/L, Mn = 1.36 mg/L,TN = 0.44 mg/L , TP = 0.07 mg/L , Ammonia = 0.386 mg/L] by using the glauconite filter we obtained high efficiency for removal for [(Fe, Mn and Ammonia] ,but in the Lab we obtained result for (Fe, 43-97), ( Mn,92-99 ), and ( Ammonia, 66-88 )]. We summarized the results to show the optimum time, pH, Glauconite weight, and the best model for design in the region.

Keywords: aquaculture, ammonia in groundwater, groundwater, iron and manganese in water, groundwater treatment

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Authors: Atabak Rahimzadeh Ilkhch

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Friction stir processing (FSP) has promised for application of thermo-mechanical processing techniques where aims to change the micro structural and mechanical properties of materials in order to obtain high performance and reducing the production time and cost. There are lots of studies focused on the microstructure of friction stir welded aluminum alloys. The main focus of this research is on the grain size obtained in the weld zone. Moreover in second part focused on temperature distribution effect over the entire weld zone and its effects on the microstructure. Also, there is a need to have more efforts on investigating to obtain the optimal value of effective parameters such as rotational speed on microstructure and to use the optimum tool designing method. the final results of this study will be present the variation of structural and mechanical properties of materials in the base of applying Friction stir processing and effect of (FSP) processing and tensile testing on surface quality. in the hand, this research addresses the FSP f AA-7020 aluminum and variation f ration of rotation and translational speeds.

Keywords: friction stir processing, AA-7020, thermo-mechanical, microstructure, temperature

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Authors: Shuo Liu, Dan Liu

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In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

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Authors: Brad Curabba

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Utilising active, process-based learning methods to improve critical thinking and writing skills of second language (L2) writers brings unique challenges. To comprehensively satisfy different learners' needs, when commenting on student work, instructors can embed multiple feedback methods so that the capstone of their abilities as writers can be achieved. This research project assesses faculty and student perceptions regarding the effectiveness of various feedback practices used in process-based writing classrooms with L2 students at the American University of Sharjah (AUS). In addition, the research explores the challenges encountered by faculty during the provision of feedback practices. The quantitative research findings are based on two concurrent electronically distributed anonymous surveys; one aimed at students who have just completed a process-based writing course, and the other at instructors who delivered these courses. The student sample is drawn from multiple sections of Academic Writing I and II, and the faculty survey was distributed among the Department of Writing Studies (DWS) faculty. Our findings strongly suggest that all methods of feedback are deemed equally important by both students and faculty. Students, in particular, find process writing and its feedback practices to have greatly contributed to their writing proficiency.

Keywords: process writing, feedback, formative feedback, composition, reflection

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Authors: Mehrshad Khosraviani, Sepehr Najjarpour

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Considering the usage of graph-based approaches in systems and synthetic biology, and the various types of ‎the graphs employed by them, a comprehensive graph library based ‎on the three-tier architecture (3TA) was previously introduced for full representation of the biological systems. Although proposing a 3TA-based graph library, three following reasons motivated us to redesign the graph ‎library based on the service-oriented architecture (SOA): (1) Maintaining the accuracy of the data related to an input graph (including its edges, its ‎vertices, its topology, etc.) without involving the end user:‎ Since, in the case of using 3TA, the library files are available to the end users, they may ‎be utilized incorrectly, and consequently, the invalid graph data will be provided to the ‎computer algorithms. However, considering the usage of the SOA, the operation of the ‎graph registration is specified as a service by encapsulation of the library files. In other words, overall control operations needed for registration of the valid data will be the ‎responsibility of the services. (2) Partitioning of the library product into some different parts: Considering 3TA, a whole library product was provided in general. While here, the product ‎can be divided into smaller ones, such as an AND/OR graph drawing service, and each ‎one can be provided individually. As a result, the end user will be able to select any ‎parts of the library product, instead of all features, to add it to a project. (3) Reduction of the complexities: While using 3TA, several other libraries must be needed to add for connecting to the ‎database, responsibility of the provision of the needed library resources in the SOA-‎based graph library is entrusted with the services by themselves. Therefore, the end user ‎who wants to use the graph library is not involved with its complexity. In the end, in order to ‎make ‎the library easier to control in the system, and to restrict the end user from accessing the files, ‎it was preferred to use the service-oriented ‎architecture ‎‎(SOA) over the three-tier architecture (3TA) and to redevelop the previously proposed graph library based on it‎.

Keywords: Bio-Design Automation, Biological System, Graph Library, Service-Oriented Architecture, Systems and Synthetic Biology

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Authors: Young Min Kim, Deokyeong Choe, Chul Soo Shin

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Monascus pigments, commonly used as a natural colorant in Asia, have many biological activities, such as cholesterol level control, anti-obesity, anti-cancer, and anti-oxidant, that have recently been elucidated. Especially, amino acid derivatives of Monascus pigments are receiving much attention because they have higher biological activities than original Monascus pigments. Previously, there have been two ways to produce amino acid derivatives: one-step production and two-step production. However, the one-step production has low purity, and the two-step production—precursor(orange pigments) fermentation and derivatives synthesis—has low productivity and growth rate during its precursor fermentation step. In this study, it was verified that pH is a key factor that affects the stability of orange pigments and the growth rate of Monascus. With an optimal pH profile obtained by pH-stat fermentation, we designed a process of precursor(orange pigments) fermentation that is a pH-controlled fed-batch fermentation. The final concentration of orange pigments in this process increased to 5.5g/L which is about 30% higher than the concentration produced from the previously used precursor fermentation step.

Keywords: cultivation process, fed-batch fermentation, monascus pigments, pH stability

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Authors: Henriette van Rensburg, Betty Adcock

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Concern about the lack of knowledge of quality teaching and teacher retention in rural and remote areas of Australia, has caused academics to improve pre-service teachers’ understanding of this problem. The participants in this study were forty students enrolled in an undergraduate educational course (EDO3341 Teaching in rural and remote communities) at the University of Southern Queensland in Toowoomba in 2012. This study involved an innovative case-based teaching approach in order to broaden their generally under-informed understanding of teaching in a rural and remote area. Three themes have been identified through analysing students’ critical reflections: learning expertise, case-based learning support and authentic learning. The outcomes identified the changes in pre-service teachers’ understanding after they have deepened their knowledge of the realities of teaching in rural and remote areas.

Keywords: rural and remote education, case based teaching, innovative education approach, higher education

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Authors: Wieland Hoppe, Nadine Wachter, Stefan Bringezu

Abstract:

Carbon dioxide (CO2) utilization might be a promising way to substitute fossil raw materials like coal, oil or natural gas as carbon source of chemical production. While first life cycle assessments indicate a positive environmental performance of CO2-based process routes, a commercialization of CO2 is limited by several economic obstacles up to now. We, therefore, analyzed the economic performance of the three CO2-based chemicals methane and methanol as basic chemicals and polyoxymethylene as polymer on a cradle-to-gate basis. Our approach is oriented towards life cycle costing. The focus lies on the cost drivers of CO2-based technologies and options to stimulate a CO2-based economy by changing regulative factors. In this way, we analyze various modes of operation and give an outlook for the potentially cost-effective development in the next decades. Biogas, waste gases of a cement plant, and flue gases of a waste incineration plant are considered as CO2-sources. The energy needed to convert CO2 into hydrocarbons via electrolysis is assumed to be supplied by wind power, which is increasingly available in Germany. Economic data originates from both industrial processes and process simulations. The results indicate that CO2-based production technologies are not competitive with conventional production methods under present conditions. This is mainly due to high electricity generation costs and regulative factors like the German Renewable Energy Act (EEG). While the decrease in production costs of CO2-based chemicals might be limited in the next decades, a modification of relevant regulative factors could potentially promote an earlier commercialization.

Keywords: carbon capture and utilization (CCU), economic assessment, life cycle costing (LCC), power-to-X

Procedia PDF Downloads 291

Authors: Mkhize Xolile, Davies Theopheluis

Abstract:

The purpose of the study was to develop a variety of fruit, vegetable and indigenous wild herb (amaranth) based juices, which can increase mineral consumption (of Ca, Fe, K, Mg, Zn). Ten samples of juice varieties were developed. The concentration range for the standards was between 10 and 150 ppm. Standards and samples were analysed using Perkin Elmer Atomic Absorption Spectrophotometer and the AAnalyst 400 model was used. The indigenous herb based juice was the most nutritious than all the other varieties developed. Mg and Fe could contribute significantly in improving cardio vascular health, bone functionality and immunity of elderly.

Keywords: minerals, elderly, juice, hypertension, intervention

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Authors: Aya M. Aboudesouky

Abstract:

Covid-19 has changed and affected the whole world dramatically in a new way that the entire world, even scientists, have not imagined before. The educational institutions around the world have been fighting since Covid-19 hit the world last December to keep the educational process unchanged for all students. E-learning was a must for almost all US universities during the pandemic. It was specifically more challenging to use online case-based learning instead of regular classes among nursing students who take practical education. This study aims to examine the difference in performance and satisfaction between nursing students taking traditional education and those who take virtual case-based education during their practical study. This study enrolls 40 last-year nursing undergraduates from a mid-sized university in Western Pennsylvania. The study uses a convenient sample. Students will be divided into two groups; a control group that is exposed to traditional teaching strategy and a treatment group that is exposed to a case-based teaching strategy. The module designed for this study is a total parenteral nutrition (TPN) module that will be taught for one month. The treatment group (n=20) utilizes the virtual simulation of the CBL method, while the control group (n=20) uses the traditional lecture-based teaching method. Student evaluations are collected after a month by using the survey to attain the students’ learning satisfaction and self-evaluation of the course. The post-test is used to assess the end of the course performance.

Keywords: virtual case-based learning, traditional education, nursing education, Covid-19 crisis, online practical education

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

Abstract:

Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

Procedia PDF Downloads 254