Search results for: kinetic and mechanistic approaches

Authors: Soumyadip Banerjee, Tanmoy Maity

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The recovery of power from waste air generated by mine ventilation fans presents a promising avenue for enhancing energy efficiency in mining operations. This abstract explores the feasibility and benefits of utilizing turbine generators to capture the kinetic energy present in waste air and convert it into electrical power. By integrating turbine generator systems into mine ventilation infrastructures, the potential to harness and utilize the previously untapped energy within the waste air stream is realized. This study examines the principles underlying turbine generator technology and its application within the context of mine ventilation systems. The process involves directing waste air from ventilation fans through specially designed turbines, where the kinetic energy of the moving air is converted into rotational motion. This mechanical energy is then transferred to connected generators, which convert it into electrical power. The recovered electricity can be employed for various on-site applications, including powering mining equipment, lighting, and control systems. The benefits of power recovery from waste air using turbine generators are manifold. Improved energy efficiency within the mining environment results in reduced dependence on external power sources and associated cost savings. Additionally, this approach contributes to environmental sustainability by utilizing a previously wasted resource for power generation. Resource conservation is further enhanced, aligning with modern principles of sustainable mining practices. However, successful implementation requires careful consideration of factors such as waste air characteristics, turbine design, generator efficiency, and integration into existing mine infrastructure. Maintenance and monitoring protocols are necessary to ensure consistent performance and longevity of the turbine generator systems. While there is an initial investment associated with equipment procurement, installation, and integration, the long-term benefits of reduced energy costs and environmental impact make this approach economically viable. In conclusion, the recovery of power from waste air from mine ventilation fans using turbine generators offers a tangible solution to enhance energy efficiency and sustainability within mining operations. By capturing and converting the kinetic energy of waste air into usable electrical power, mines can optimize resource utilization, reduce operational costs, and contribute to a greener future for the mining industry.

Keywords: waste to energy, wind power generation, exhaust air, power recovery

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: AnjalI A. Prasad

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Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms.

Keywords: BERT, CNN, LSTM, RNN

Procedia PDF Downloads 189

Authors: Eleni Volonaki

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In Athenian forensic speeches, the argumentation on punishment of the wrongdoers constitutes a fundamental ideal of exacting justice in court. The present paper explores the variation of approaches to punishment as a means of reformation, revenge, correction, education, example, chance to restoration of justice. As it will be shown, all these approaches reflect the social and political ideology of Athenian justice in the classical period and enhances the role of the courts and the importance of rhetoric in the process of decision-making. Punishment entails a wide range of penalties but also of ideological principles related to the Athenian constitution of democracy.

Keywords: punishment, athenian forensic speeches, justice, athenian democracy

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Authors: Benaliouche Hana, Abdessemed Djamal, Meniai Abdessalem, Lesage Geoffroy, Heran Marc

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This paper presents a dynamic mathematical model of activated sludge which is able to predict the formation and degradation kinetics of SMP (Soluble microbial products) in membrane bioreactor systems. The model is based on a calibrated version of ASM1 with the theory of production and degradation of SMP. The model was calibrated on the experimental data from MBR (Mathematical modeling Membrane bioreactor) pilot plant. Analytical expressions have been developed, describing the concentrations of the main state variables present in the sludge matrix, with the inclusion of only six additional linear differential equations. The objective is to present a new dynamic mathematical model of activated sludge capable of predicting the formation and degradation kinetics of SMP (UAP and BAP) from the submerged membrane bioreactor (BRMI), operating at low organic load (C / N = 3.5), for two sludge retention times (SRT) fixed at 40 days and 60 days, to study their impact on membrane fouling, The modeling study was carried out under the steady-state condition. Analytical expressions were then validated by comparing their results with those obtained by simulations using GPS-X-Hydromantis software. These equations made it possible, by means of modeling approaches (ASM1), to identify the operating and kinetic parameters and help to predict membrane fouling.

Keywords: Activated Sludge Model No. 1 (ASM1), mathematical modeling membrane bioreactor, soluble microbial products, UAP, BAP, Modeling SMP, MBR, heterotrophic biomass

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Authors: Akunna Agunwah, Kevin Gallimore, Kathryn Kinnmond

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Entrepreneurship and project management are widely associated and seen as a vehicle for economic growth, but are studied separately. A few authors have considered the interconnectivity existing between these two fields, but relatively little empirical data currently exist in the literature. The purpose of the present empirical study is to explore whether successful entrepreneurs utilise project management approaches in enhancing enterprise growth by understanding the working practices and experiences of the entrepreneurs’ using the Theory of Planned Behaviour (TPB) as a lens. In order to understand those experiences, ten successful entrepreneurs in various business sectors in the North West of England were interviewed through a face-to-face semi-structured interview method. The collected audio tape-recorded data was transcribed and analysed using the deductive thematic technique (qualitative approach). The themes were viewed through the lens of Theory of Planned Behaviour to identify the three intentional antecedents (attitude, subjective norms, and perceived behavioural control) and to understand how they relate to the project management approaches (Planning, execution, and monitoring). The findings are twofold, the first evidence of the three intentional antecedents, which make up Theory of Planned Behaviour was present. Secondly, the analysis of project management approaches themes (planning, execution, and monitoring) using the lens of the theory of planned behaviour shows evidence of the three intentional antecedents. There were more than one intentional antecedents found in a particular project management theme, which indicates that the entrepreneur does utilise these approaches without categorising them into definite themes. However, the entrepreneur utilised these intentional antecedents as processes to enhanced business growth. In conclusion, the work presented here showed a way of understanding the interconnectivity between entrepreneurship and project management towards enhancing enterprise growth by examining the working practices and experiences of the successful entrepreneurs in the North-West England.

Keywords: business growth, entrepreneurship, project management approaches, theory of planned behaviour

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Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: Revanth Rallapalli

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Manually dispensing powders can be difficult as it requires gradually pouring and checking the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and are user-dependent and difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various new powder dispensing mechanisms are being designed to overcome these challenges. A battery-operated screw conveyor mechanism is being innovated to overcome the above problems faced. These inventions are numerically evaluated at the concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices saving time and money by reducing the number of prototypes and testing. This paper describes a simulation of powder dispensation from the trocar’s end by considering the powder as secondary flow in the air, is simulated by using the technique called Dense Discrete Phase Model incorporated with Kinetic Theory of Granular Flow (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation of powder from the inlet side to the trocar’s end side is done by rotation of the screw conveyor. The performance is calculated for a 1-sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: multiphase flow, screw conveyor, transient, dense discrete phase model (DDPM), kinetic theory of granular flow (KTGF)

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Authors: Nabila Mohamed, Santiago Aparicio, Bahman Tohidi, Mert Atilhan

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Qatar's one of the biggest problem in processing its natural resource, which is natural gas, is the often occurring blockage in the pipelines caused due to uncontrolled gas hydrate formation in the pipelines. Several millions of dollars are being spent at the process site to dehydrate the blockage safely by using chemical inhibitors. We aim to establish national database, which addresses the physical conditions that promotes Qatari natural gas to form gas hydrates in the pipelines. Moreover, we aim to design and test novel hydrate inhibitors that are suitable for Qatari natural gas and its processing facilities. From these perspectives we are aiming to provide more effective and sustainable reservoir utilization and processing of Qatari natural gas. In this work, we present the initial findings of a QNRF funded project, which deals with the natural gas hydrate formation characteristics of Qatari type gas in both experimental (PVTx) and computational (molecular simulations) methods. We present the data from the two fully automated apparatus: a gas hydrate autoclave and a rocking cell. Hydrate equilibrium curves including growth/dissociation conditions for multi-component systems for several gas mixtures that represent Qatari type natural gas with and without the presence of well known kinetic and thermodynamic hydrate inhibitors. Ionic liquids were designed and used for testing their inhibition performance and their DFT and molecular modeling simulation results were also obtained and compared with the experimental results. Results showed significant performance of ionic liquids with up to 0.5 % in volume with up to 2 to 4 0C inhibition at high pressures.

Keywords: gas hydrates, natural gas, ionic liquids, inhibition, thermodynamic inhibitors, kinetic inhibitors

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Authors: Barenten Suciu

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In this work, effects of the friction and truncation on the dynamics of a double-cone gravitational motor, self-propelled on a straight V-shaped horizontal rail, are evaluated. Such mechanism has a variable radius of contact, and, on one hand, it is similar to a pulley mechanism that changes the potential energy into the kinetic energy of rotation, but on the other hand, it is similar to a pendulum mechanism that converts the potential energy of the suspended body into the kinetic energy of translation along a circular path. Movies of the self- propelled double-cones, made of S45C carbon steel and wood, along rails made of aluminum alloy, were shot for various opening angles of the rails. Kinematical features of the double-cones were estimated through the slow-motion processing of the recorded movies. Then, a kinematical model is derived under assumption that the distance traveled by the contact points on the rectilinear rails is identical with the distance traveled by the contact points on the truncated conical surface. Additionally, a dynamic model, for this particular contact problem, was proposed and validated against the experimental results. Based on such model, the traction force and the traction torque acting on the double-cone are identified. One proved that the rolling traction force is always smaller than the sliding friction force; i.e., the double-cone is rolling without slipping. Results obtained in this work can be used to achieve the proper design of such gravitational motor.

Keywords: Truncated double-cone, friction, rolling and sliding, dynamic model, gravitational motor

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Authors: Mehdi Razeghi

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Background: The purpose of this case series was to quantify gait to study muscular dystrophy disease. In this research, the quantitative differences between normal and waddling gaits were assessed by force plate analysis. Methods: Nineteen myopathy patients and twenty normal subjects serving as the control group participated in this research. In this study, quantitative analyses of gait have been used to investigate the differences between the mobility of normal subjects and myopathy patients. This study was carried out at the Iranian Muscular Dystrophy Association in Boali Hospital, Tehran, Iran, from October 2015 to July 2020. Patient data were collected from Iranian Muscular Dystrophy Association members. individuals signed an informed consent form approved by the ethics committee of the Azad University. All of the gait tests were performed using a Kistler force platform. Participants walked at a self-selected speed, barefoot, independently, and without assistive devices. Results: Our findings indicate that there were no significant differences between the patients and the control group in the anterior-posterior components of the ground reaction forces; however, there were considerable differences in the force components between the groups in the medial-lateral and vertical directions of the ground reaction force. In addition, there were significant differences in the time parameters between the groups in the vertical and medial-lateral directions.

Keywords: biomechanics, force plate analysis, gait disorder, ground reaction force, kinetic analysis, myopathy disease, rehabilitation engineering

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Authors: R. Pravin Kumar, L. Roopa

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Enzymes are molecular machines used in various industries such as pharmaceuticals, cosmetics, food and animal feed, paper and leather processing, biofuel, and etc. Nevertheless, this has been possible only by the breath-taking efforts of the chemists and biologists to evolve/engineer these mysterious biomolecules to work the needful. Main agenda of this enzyme engineering project is to derive screening and selection tools to obtain focused libraries of enzyme variants with desired qualities. The methodologies for this research include the well-established directed evolution, rational redesign and relatively less established yet much faster and accurate insilico methods. This concept was initiated as a Receptor Rependent-4Dimensional Quantitative Structure Activity Relationship (RD-4D-QSAR) to predict kinetic properties of enzymes and extended here to study transaminase by a 7D QSAR approach. Induced-fit scenarios were explored using Quantum Mechanics/Molecular Mechanics (QM/MM) simulations which were then placed in a grid that stores interactions energies derived from QM parameters (QMgrid). In this study, the mutated enzymes were immersed completely inside the QMgrid and this was combined with solvation models to predict descriptors. After statistical screening of descriptors, QSAR models showed > 90% specificity and > 85% sensitivity towards the experimental activity. Mapping descriptors on the enzyme structure revealed hotspots important to enhance the enantioselectivity of the enzyme.

Keywords: QMgrid, QM/MM simulations, RD-4D-QSAR, transaminase

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Jignasha Derasari, Patel Krishna M, Modi Jignasa G.

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Chemical stability of pharmaceutical molecules is a matter of great concern as it affects the safety and efficacy of the drug product.Stability testing data provides the basis to understand how the quality of a drug substance and drug product changes with time under the influence of various environmental factors. Besides this, it also helps in selecting proper formulation and package as well as providing proper storage conditions and shelf life, which is essential for regulatory documentation. The ICH guideline states that stress testing is intended to identify the likely degradation products which further help in determination of the intrinsic stability of the molecule and establishing degradation pathways, and to validate the stability indicating procedures. A simple, accurate and precise stability indicating RP- HPLC method was developed and validated for simultaneous estimation of Amiloride Hydrochloride and Furosemide in tablet dosage form. Separation was achieved on an Phenomenexluna ODS C18 (250 mm × 4.6 mm i.d., 5 µm particle size) by using a mobile phase consisting of Ortho phosphoric acid: Acetonitrile (50:50 %v/v) at a flow rate of 1.0 ml/min (pH 3.5 adjusted with 0.1 % TEA in Water) isocratic pump mode, Injection volume 20 µl and wavelength of detection was kept at 283 nm. Retention time for Amiloride Hydrochloride and Furosemide was 1.810 min and 4.269 min respectively. Linearity of the proposed method was obtained in the range of 40-60 µg/ml and 320-480 µg/ml and Correlation coefficient was 0.999 and 0.998 for Amiloride hydrochloride and Furosemide, respectively. Forced degradation study was carried out on combined dosage form with various stress conditions like hydrolysis (acid and base hydrolysis), oxidative and thermal conditions as per ICH guideline Q2 (R1). The RP- HPLC method has shown an adequate separation for Amiloride hydrochloride and Furosemide from its degradation products. Proposed method was validated as per ICH guidelines for specificity, linearity, accuracy; precision and robustness for estimation of Amiloride hydrochloride and Furosemide in commercially available tablet dosage form and results were found to be satisfactory and significant. The developed and validated stability indicating RP-HPLC method can be used successfully for marketed formulations. Forced degradation studies help in generating degradants in much shorter span of time, mostly a few weeks can be used to develop the stability indicating method which can be applied later for the analysis of samples generated from accelerated and long term stability studies. Further, kinetic study was also performed for different forced degradation parameters of the same combination, which help in determining order of reaction.

Keywords: amiloride hydrochloride, furosemide, kinetic study, stability indicating RP-HPLC method validation

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Authors: Mohamed Sharof Mostafa, Atefeh Ahmadi

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Most of traditional single modality psychotherapy and counselling approaches to clients’ problems are based on the application of one therapy in all sessions. Modern developments in these sciences focus on eclectic and integrative interventions to consider all dimensions of an issue and all characteristics of the clients. This paper presents and overview eclectic therapy and its pros and cons. In addition, multiple intelligence theory and its application in eclectic therapy approaches are mentioned.

Keywords: eclectic therapy, client, multiple intelligence theory, dimensions

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Authors: Sonia Arradaza-Pajaron

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Speaking English, as a medium of instruction among students who are non-native English speakers poses a real challenge to achieve proficiency, especially so if it is a requirement in most communicative classroom instruction. It becomes a real burden among students whose English language orientation is not well facilitated and encouraged by teachers among national high schools. This study, which utilized a descriptive-correlational research, examined the relationship between the select communicative approaches commonly utilized in classroom instruction to the level of speaking skills among the identified high school students. Survey questionnaires, interview, and observations sheets were researcher instruments used to generate salient information. Data were analyzed and treated statistically utilizing weighted mean speaking skills levels and Pearson r to determine the relationship between the two identified variables of the study. Findings revealed that the level of English speaking skills of the high school students is just average. Further, among the identified speaking sub-skills, namely, grammar, pronunciation and fluency, the students were considered above average level. There was also a clear relationship of some communicative approaches to the respondents’ speaking skills. Most notable among the select approaches is that of role-playing, compared to storytelling, informal debate, brainstorming, oral reporting, and others. It may be because role-playing is the most commonly used approach in the classroom. This implies that when these high school students are given enough time and autonomy on how they could express their ideas or comprehension of some lessons, they are shown to have a spontaneous manner of expression, through the maximization of the second language. It can be concluded further that high school students have the capacity to express ideas even in the second language, only if they are encouraged and well-facilitated by teachers. Also, when a better communicative approach is identified and better implemented, thus, will level up students’ classroom engagement.

Keywords: communicative approaches, comprehension, role playing, speaking skills

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: K. G. R. M. Jayathilake, S. Rudra

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Wood degradation in hot compressed water is modeled with a Computational Fluid Dynamics (CFD) code using cellulose, xylan, and lignin as model compounds. Model compounds are reacted under catalyst-free conditions in a temperature range from 250 to 370 °C. Using a simplified reaction scheme where water soluble products, methanol soluble products, char like compounds and gas are generated through intermediates with each model compound. A modified multistage shrinking core model is developed to simulate particle degradation. In the modified shrinking core model, each model compound is hydrolyzed in separate stages. Cellulose is decomposed to glucose/oligomers before producing degradation products. Xylan is decomposed through xylose and then to degradation products where lignin is decomposed into soluble products before producing the total guaiacol, organic carbon (TOC) and then char and gas. Hydrolysis of each model compound is used as the main reaction of the process. Diffusion of water monomers to the particle surface to initiate hydrolysis and dissolution of the products in water is given importance during the modeling process. In the developed model the temperature variation depends on the Arrhenius relationship. Kinetic parameters from the literature are used for the mathematical model. Meanwhile, limited initial fast reaction kinetic data limit the development of more accurate CFD models. Liquefaction results of the CFD model are analyzed and validated using the experimental data available in the literature where it shows reasonable agreement.

Keywords: computational fluid dynamics, liquefaction, shrinking-core, wood

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Authors: Ratna Sen

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As due to very high temperature of Plasma it is very difficult to confine it for sufficient time so that nuclear fusion reactions to take place, As we know Plasma escapes faster than the binary collision rates. We studied the ball analogy and the ‘energy principle’ and calculated the total potential energy for the whole Plasma. If δ ⃗w is negative, that is decrease in potential energy then the plasma will be unstable. We also discussed different approaches of stability analysis such as Nyquist Method, MHD approximation and Vlasov approach of plasma stability. So that by using magnetic field configurations we can able to create a stable Plasma in Tokamak for generating energy for future generations.

Keywords: jello, magnetic field configuration, MHD approximation, energy principle

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Authors: Aina Barcelona, Carolyn Oldham, Jordi Colomer, Teresa Serra

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The loss of seagrass meadows worldwide is being tackled by formulating coastal restoration strategies. Seagrass loss results in a network of vegetated patches which are barely interconnected, and consequently, the ecological services they provide may be highly compromised. Hence, there is a need to optimize coastal management efforts in order to implement successful restoration strategies, not only through modifying the architecture of the canopies but also by gathering together information on the hydrodynamic conditions of the seabeds. To obtain information on the hydrodynamics within the patches of vegetation, this study deals with the scale analysis of the minimum lengths of patch management strategies that can be effectively used on. To this aim, a set of laboratory experiments were conducted in a laboratory flume where the plant densities, patch lengths, and hydrodynamic conditions were varied to discern the vegetated patch lengths that can provide optimal ecosystem services for canopy development. Two possible patch behaviours based on the turbulent kinetic energy (TKE) production were determined: one where plants do not interact with the flow and the other where plants interact with waves and produce TKE. Furthermore, this study determines the minimum patch lengths that can provide successful management restoration. A canopy will produce TKE, depending on its density, the length of the vegetated patch, and the wave velocities. Therefore, a vegetated patch will produce plant-wave interaction under high wave velocities when it presents large lengths and high canopy densities.

Keywords: seagrass, minimum patch size, turbulent kinetic energy, oscillatory flow

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Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

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Authors: Masood Otarod, Ronald M. Supkowski

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This abstract discusses a method that reduces the general dispersion model in cylindrical coordinates to a second order linear ordinary differential equation with constant coefficients so that it can be utilized to conduct kinetic studies in packed bed tubular catalytic reactors at a broad range of Reynolds numbers. The model was tested by 13CO isotope transient tracing of the CO adsorption of Boudouard reaction in a differential reactor at an average Reynolds number of 0.2 over Pd-Al2O3 catalyst. Detailed experimental results have provided evidence for the validity of the theoretical framing of the model and the estimated parameters are consistent with the literature. The solution of the general dispersion model requires the knowledge of the radial distribution of axial velocity. This is not always known. Hence, up until now, the implementation of the dispersion model has been largely restricted to the plug-flow regime. But, ideal plug-flow is impossible to achieve and flow regimes approximating plug-flow leave much room for debate as to the validity of the results. The reduction of the general dispersion model transpires as a result of the application of a factorization theorem. Factorization theorem is derived from the observation that a cross section of a catalytic bed consists of a solid phase across which the reaction takes place and a void or porous phase across which no significant measure of reaction occurs. The disparity in flow and the heterogeneity of the catalytic bed cause the concentration of reacting compounds to fluctuate radially. These variabilities signify the existence of radial positions at which the radial gradient of concentration is zero. Succinctly, factorization theorem states that a concentration function of axial and radial coordinates in a catalytic bed is factorable as the product of the mean radial cup-mixing function and a contingent dimensionless function. The concentration of adsorbed compounds are also factorable since they are piecewise continuous functions and suffer the same variability but in the reverse order of the concentration of mobile phase compounds. Factorability is a property of packed beds which transforms the general dispersion model to an equation in terms of the measurable mean radial cup-mixing concentration of the mobile phase compounds and mean cross-sectional concentration of adsorbed species. The reduced model does not require the knowledge of the radial distribution of the axial velocity. Instead, it is characterized by new transport parameters so denoted by Ωc, Ωa, Ωc, and which are respectively denominated convection coefficient cofactor, axial dispersion coefficient cofactor, and radial dispersion coefficient cofactor. These cofactors adjust the dispersion equation as compensation for the unavailability of the radial distribution of the axial velocity. Together with the rest of the kinetic parameters they can be determined from experimental data via an optimization procedure. Our data showed that the estimated parameters Ωc, Ωa Ωr, are monotonically correlated with the Reynolds number. This is expected to be the case based on the theoretical construct of the model. Computer generated simulations of methanation reaction on nickel provide additional support for the utility of the newly conceptualized dispersion model.

Keywords: factorization, general dispersion model, isotope transient kinetic, partial differential equations

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Authors: Fatima Zahra Mahjoubi, Abderrahim Khalidi, Mohamed Abdennouri, Omar Cherkaoui, Noureddine Barka

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Industrial effluents are one of the major causes of environmental pollution, especially effluents discharged from various dyestuff manufactures, plastic, and paper making industries. These effluents can give rise to certain hazards and environmental problems for their highly colored suspended organic solid. Dye effluents are not only aesthetic pollutants, but coloration of water by the dyes may affect photochemical activities in aquatic systems by reducing light penetration. It has been also reported that several commonly used dyes are carcinogenic and mutagenic for aquatic organisms. Therefore, removing dyes from effluents is of significant importance. Many adsorbent materials have been prepared in the removal of dyes from wastewater, including anionic clay or layered double hydroxyde. The zinc/aluminium (Zn-AlNO₃), magnesium/aluminium (Mg-AlNO₃) and nickel/aluminium (Ni-AlNO₃) layered double hydroxides (LDHs) were successfully synthesized via coprecipitation method. Samples were characterized by XRD, FTIR, TGA/DTA, TEM and pHPZC analysis. XRD patterns showed a basal spacing increase in the order of Zn-AlNO₃ (8.85Å)> Mg-AlNO₃ (7.95Å)> Ni-AlNO₃ (7.82Å). FTIR spectrum confirmed the presence of nitrate anions in the LDHs interlayer. The TEM images indicated that the Zn-AlNO3 presents circular to shaped particles with an average particle size of approximately 30 to 40 nm. Small plates assigned to sheets with hexagonal form were observed in the case of Mg-AlNO₃. Ni-AlNO₃ display nanostructured sphere in diameter between 5 and 10 nm. The LDHs were used as adsorbents for the removal of methyl orange (MO), as a model dye and for the treatment of an effluent generated by a textile factory. Adsorption experiments for MO were carried out as function of solution pH, contact time and initial dye concentration. Maximum adsorption was occurred at acidic solution pH. Kinetic data were tested using pseudo-first-order and pseudo-second-order kinetic models. The best fit was obtained with the pseudo-second-order kinetic model. Equilibrium data were correlated to Langmuir and Freundlich isotherm models. The best conditions for color and COD removal from textile effluent sample were obtained at lower values of pH. Total color removal was obtained with Mg-AlNO₃ and Ni-AlNO₃ LDHs. Reduction of COD to limits authorized by Moroccan standards was obtained with 0.5g/l LDHs dose.

Keywords: chemical oxygen demand, color removal, layered double hydroxides, textile wastewater treatment

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

Abstract:

In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

Procedia PDF Downloads 76

Authors: Jay Xiong, Li Lin

Abstract:

Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

Procedia PDF Downloads 379

Authors: Parvin Malhami

Abstract:

The purpose of the present study was to investigate the effects of two functional and functional stretching methods of the leg muscles on a selection of kinematical and kinetic indicators among women with ankle instability. Twenty-four persons were targeted and randomly divided into the functional exercise (8 persons), extra-functional exercise (8 persons) and control (8 persons) groups on the basis of inclusion and exclusion criteria. The experimental groups received stretching for eight weeks, 3 sessions each week, and the control group merely performed its daily activities. Then, in order to measure the pre -test and post -test variables, the dorsi flexion, Plantar flexion and ground reaction force were investigated and measured. Data were analyzed using paired T-test and independent T-tests at a significant level of 0.05. All statistical analyses were conducted using SPSS 25 software. The results of the T-test showed the significant effect of eight weeks of functional and Extra functional exercises on dorsi Flexion, Plantar Flexion and ground reaction force. (P≤ 0/001). The results of this study showed that the implementation of the functional and Extra-functional exercise protocol had an impact on the amount of Ankle dorsi Flexion and the Plantar felxion of women with an ankle instability. It was also found that muscle flexibility following the stretch ability of the gastrocnemius muscles facilitates the walking of the wrist installation by affecting the amount of wrist flexion, so these people are recommended to use the functional and extra-functional exercise protocol.

Keywords: functional stretching, extra functional stretching, dorsi flexion, plantar flexion

Procedia PDF Downloads 54

Authors: Laroussi Chaabane, Emmanuel Beyou, Amel El Ghali, Mohammed Hassen V. Baouab

Abstract:

The functionalization of graphene oxide sheets by ethylenediamine (EDA) was accomplished followed by the grafting of bis(2-pyridylmethyl)amino group (BPED) onto the activated graphene oxide sheets in the presence of chloroacetylchloride (CAC) produced the martial [(Go-EDA-CAC)-BPED]. The physic-chemical properties of [(Go-EDA-CAC)-BPED] composites were investigated by Fourier transform infrared (FT-IR), X-ray photoelectron spectroscopy (XPs), Scanning electron microscopy (SEM) and Thermogravimetric analysis (TGA). Moreover, [(Go-EDA-CAC)-BPED] was used for removing M(II) (where M=Cu, Ni and Co) ions from aqueous solutions using a batch process. The effect of pH, contact time and temperature were investigated. More importantly, the [(Go-EDA-CAC)-BPED] adsorbent exhibited remarkable performance in capturing heavy metal ions from water. The maximum adsorption capacity values of Cu(II), Ni(II) and Co(II) on the [(GO-EDA-CAC)-BPED] at the pH of 7 is 3.05 mmol.g⁻¹, 3.25 mmol.g⁻¹ and 3.05 mmol.g⁻¹ respectively. To examine the underlying mechanism of the adsorption process, pseudo-first, pseudo-second-order, and intraparticle diffusion models were fitted to experimental kinetic data. Results showed that the pseudo-second-order equation was appropriate to describe the three metal ions adsorption by [(Go-EDA-CAC)-BPED]. Adsorption data were further analyzed by the Langmuir, Freundlich, and Jossensadsorption approaches. Additionally, the adsorption properties of the [(Go-EDA-CAC)-BPED], their reusability (more than 10 cycles) and durability in the aqueous solutions open the path to removal of metal ions (Cu(II), Ni(II) and Co(II) from water solution. Based on the results obtained, we conclude that [(Go-EDA-CAC)-BPED] can be an effective and potential adsorbent for removing metal ions from an aqueous solution.

Keywords: graphene oxide, bis(2-pyridylmethyl)amino, adsorption kinetics, isotherms

Procedia PDF Downloads 117

Authors: C. Benoudjafer, M. N. Tandjaoui, C. Benachaiba

Abstract:

The use of kinetic energy of the wind is in full rise in the world and it starts to be known in our country but timidly. One or more aero generators can be installed to produce for example electricity on isolated places or not connected to the electrical supply network. To use the wind as energy source, it is necessary to know first the energy needs for the population and study the wind intensity, speed, frequency and direction.

Keywords: Algeria, renewable energies, wind, wind power, aero-generators, wind energetic potential

Procedia PDF Downloads 408

Authors: M. Rodionov, N. Sharapova, Z. Dedovets

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The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.

Keywords: education, methodological approaches, teacher, secondary school

Procedia PDF Downloads 153