Search results for: Dirichlet second order boundary problem

Authors: Ilqar Ramazanli

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The matrix completion problem has been studied broadly under many underlying conditions. The problem has been explored under adaptive or non-adaptive, exact or estimation, single-phase or multi-phase, and many other categories. In most of these cases, the observation cost of each entry is uniform and has the same cost across the columns. However, in many real-life scenarios, we could expect elements from distinct columns or distinct positions to have a different cost. In this paper, we explore this generalization under adaptive conditions. We approach the problem under two different cost models. The first one is that entries from different columns have different observation costs, but within the same column, each entry has a uniform cost. The second one is any two entry has different observation cost, despite being the same or different columns. We provide complexity analysis of our algorithms and provide tightness guarantees.

Keywords: matroid optimization, matrix completion, linear algebra, algorithms

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Authors: T. Marinaci, C. Venuleo

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Different conceptualizations of disease affect patient care. This study aims to address this gap. It explores how health professionals conceptualize gambling problem, addiction and the goals of recovery process. In-depth, semi-structured, open-ended interviews were conducted with Italian psychologists, psychiatrists, general practitioners, and support staff (N= 114), working within health centres for the treatment of addiction (public health services or therapeutic communities) or medical offices. A Lexical Correspondence Analysis (LCA) was applied to the verbatim transcripts. LCA allowed to identify two main factorial dimensions, which organize similarity and dissimilarity in the discourses of the interviewed. The first dimension labelled 'Models of relationship with the problem', concerns two different models of relationship with the health problem: one related to the request for help and the process of taking charge and the other related to the identification of the psychopathology underlying the disorder. The second dimension, labelled 'Organisers of the intervention' reflects the dialectic between two ways to address the problem. On the one hand, they are the gambling dynamics and its immediate life-consequences to organize the intervention (whatever the request of the user is); on the other hand, they are the procedures and the tools which characterize the health service to organize the way the professionals deal with the user’ s problem (whatever it is and despite the specify of the user’s request). The results highlight how, despite the differences, the respondents share a central assumption: understanding gambling problem implies the reference to the gambler’s identity, more than, for instance, to the relational, social, cultural or political context where the gambler lives. A passive stance is attributed to the user, who does not play any role in the definition of the goal of the intervention. The results will be discussed to highlight the relationship between professional models and users’ ways to understand and deal with the problems related to gambling.

Keywords: cultural models, health professionals, intervention models, problem gambling

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: mathematics, motivation, secondary school, student, practical problem

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Authors: D. Kaczorek

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Internal insulation of external walls is often problematic due to increased moisture content in the wall and interstitial or surface condensation risk. In this paper, the hygrothermal performance of prefabricated, concrete, large panel, external wall typical for WK70 system, commonly used in Poland in the 70’s, with inside, additional insulation was investigated. Thermal insulation board made out of hygroscopic, natural materials with moisture buffer capacity and extruded polystyrene (EPS) board was used as interior insulation. Experience with this natural insulation is rare in Poland. The analysis was performed using WUFI software. First of all, the impact of various standard boundary conditions on the behavior of the different wall assemblies was tested. The comparison of results showed that the moisture class according to the EN ISO 13788 leads to too high values of total moisture content in the wall since the boundary condition according to the EN 15026 should be usually applied. Then, hygrothermal 1D-simulations were conducted by WUFI Pro for analysis of internally added insulation, and the weak point like the joint of the wall with the concrete ceiling was verified using 2D simulations. Results showed that, in the Warsaw climate and the indoor conditions adopted in accordance with EN 15026, in the tested wall assemblies, regardless of the type of interior insulation, there would not be any problems with moisture - inside the structure and on the interior surface.

Keywords: concrete large panel wall, hygrothermal simulation, internal insulation, moisture related issues

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Authors: Chen Bingru

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This study is intended to describe and analyze the effects of polysyllabic shortening and word or phrase boundary on the duration patterns of spoken utterances by Mandarin learners of English in comparison with native speakers of English. To investigate the relative contribution of these effects, two production experiments were conducted. The study included 11 native British English speakers and 20 Mandarin learners of English who were asked to produce four sets of tokens consisting of a mono-syllabic base form, disyllabic, and trisyllabic words derived from the base by the addition of suffixes, and a set of short sentences with a particular combination of phrase size, stress pattern, and boundary location. The duration of words and segments was measured, and results from the data analysis suggest that the amount of polysyllabic shortening and the effect of word or phrase position are likely to affect a Chinese accent for Mandarin ESL speakers. This study sheds light on research on the duration patterns of language by demonstrating the effect of duration-related factors on the foreign accent of Mandarin ESL speakers. It can also benefit both L2 learners and language teachers by increasing their sensitivity to the duration differences and difficulties experienced by L2 learners of English. An understanding of the amount of polysyllabic shortening and the effect of position in words and phrase on syllable duration can also facilitate L2 teachers to establish priorities for teaching pronunciation to ESL learners.

Keywords: duration patterns, Chinese accent, Mandarin ESL speakers, polysyllabic shortening

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Authors: Jaime Muñoz, José Arcos, Oscar Bautista Federico Méndez

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The influence of a pulsatile electroosmotic flow (PEOF) at the rate of spread, or dispersivity, for a non-reactive solute released in a microcapillary with slippage at the boundary wall (modeled by the Navier-slip condition) is theoretically analyzed. Based on the flow velocity field developed under such conditions, the present study implements an analytical scheme of scaling known as the Theory of Homogenization, in order to obtain a mathematical expression for the dispersivity, valid at a large time scale where the initial transients have vanished and the solute spreads under the Taylor dispersion influence. Our results show the dispersivity is a function of a slip coefficient, the amplitude of the imposed electric field, the Debye length and the angular Reynolds number, highlighting the importance of the latter as an enhancement/detrimental factor on the dispersivity, which allows to promote the PEOF as a strong candidate for chemical species separation at lab-on-a-chip devices.

Keywords: dispersivity, microcapillary, Navier-slip condition, pulsatile electroosmotic flow, Taylor dispersion, Theory of Homogenization

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Ahmed Elrewainy

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Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l₁-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l₁-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets

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Authors: Yang-Kuei Lin, Yin-Yi Chou

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In this research, we have considered operating room scheduling problem. The objective is to minimize total operating cost. The total operating cost includes idle cost and overtime cost. We have proposed a dispatching rule that can guarantee to find feasible solutions for the studied problem efficiently. We compared the proposed dispatching rule with the optimal solutions found by solving Inter Programming, and other solutions found by using modified existing dispatching rules. The computational results indicates that the proposed heuristic can find near optimal solutions efficiently.

Keywords: assignment, dispatching rule, operation rooms, scheduling

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Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

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Authors: Eunsu Jang, Kang Park

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In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

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Authors: Mohammad Javad Shariatzadeh, Dana Grecov

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The tribological tests were performed on a new tribometer, in order to measure the coefficient of friction of a gland seal packing material on stainless steel shafts in presence of Cellulose Nanocrystal (CNC) suspension as a sustainable, environmentally friendly, water-based lubricant. To simulate the real situation from the slurry pumps, silica sands were used as slurry particles. The surface profiles after tests were measured by interferometer microscope to characterize the surface wear. Moreover, the coefficient of friction and surface wear were measured between stainless steel shaft and chrome steel ball to investigate the tribological effects of CNC in boundary lubrication region. Alignment of nanoparticles in the CNC suspensions are the main reason for friction and wear reduction. The homogeneous concentrated suspensions showed fingerprint patterns of a chiral nematic liquid crystal. These properties made CNC a very good lubricant additive in water.

Keywords: gland seal, lubricant additives, nanocrystalline cellulose, water-based lubricants

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Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

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Authors: Partha Sarathi Nayek, Abhiparna Dasgupta, Maheshreddy Gade

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Earth retaining structure plays a vital role in stabilizing unstable road cuts and slopes in the mountainous region. The retaining structures located in seismically active regions like the Himalayas may experience moderate to severe earthquakes. An earthquake produces two kinds of ground motion: permanent quasi-static displacement (fault rapture) on the fault rupture plane and transient vibration, traveling a long distance. There has been extensive research work to understand the dynamic behavior of retaining structures subjected to transient ground motions. However, understanding the effect caused by fault rapture phenomena on retaining structures is limited. The presence of shallow crustal active faults and natural slopes in the Himalayan region further highlights the need to study the response of retaining structures subjected to fault rupture phenomena. In this paper, an attempt has been made to understand the dynamic response of the cantilever retaining wall subjected to surface fault rupture. For this purpose, a 2D finite element model consists of a retaining wall, backfill and foundation have been developed using Abaqus 6.14 software. The backfill and foundation material are modeled as per the Mohr-Coulomb failure criterion, and the wall is modeled as linear elastic. In this present study, the interaction between backfill and wall is modeled as ‘surface-surface contact.’ The entire simulation process is divided into three steps, i.e., the initial step, gravity load step, fault rupture step. The interaction property between wall and soil and fixed boundary condition to all the boundary elements are applied in the initial step. In the next step, gravity load is applied, and the boundary elements are allowed to move in the vertical direction to incorporate the settlement of soil due to the gravity load. In the final step, surface fault rupture has been applied to the wall-backfill system. For this purpose, the foundation is divided into two blocks, namely, the hanging wall block and the footwall block. A finite fault rupture displacement is applied to the hanging wall part while the footwall bottom boundary is kept as fixed. Initially, a numerical analysis is performed considering the reverse fault mechanism with a dip angle of 45°. The simulated result is presented in terms of contour maps of permanent displacements of the wall-backfill system. These maps highlighted that surface fault rupture can induce permanent displacement in both horizontal and vertical directions, which can significantly influence the dynamic behavior of the wall-backfill system. Further, the influence of fault mechanism, dip angle, and surface fault rupture position is also investigated in this work.

Keywords: surface fault rupture, retaining wall, dynamic response, finite element analysis

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Authors: V. S. S. Kumar, B. Vikram

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The development of effective decision support tools that adopted in the construction industry is vital in the world we live in today, since it can lead to substantial cost reduction and efficient resource consumption. Solving the time-cost trade off problems and its related variants is at the heart of scientific research for optimizing construction planning problems. In general, the classical optimization techniques have difficulties in dealing with TCT problems. One of the main reasons of their failure is that they can easily be entrapped in local minima. This paper presents an investigation on the application of meta-heuristic techniques to two particular variants of the time-cost trade of analysis, the time-cost trade off problem (TCT), and time-cost trade off optimization problem (TCO). In first problem, the total project cost should be minimized, and in the second problem, the total project cost and total project duration should be minimized simultaneously. Finally it is expected that, the optimization models developed in this paper will contribute significantly for efficient planning and management of construction project.

Keywords: fuzzy sets, uncertainty, optimization, time cost trade off problems

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Authors: Noawanit Songkram

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This paper is a report on the findings of a study conducted on e–learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education. The methodology of this study was R&D research. The subjects were 18 undergraduate students in Faculty of Education, Chulalongkorn University in the academic year of 2013. The research instruments were a problem solving ability assessment, a team learning evaluation form, and an attitude questionnaire. The data was statistically analyzed using mean, standard deviation, one way repeated measure ANOVA and t–test. The research findings discovered the e –learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education consisted of five components:(1) online collaborative tools, (2) active learning activities, (3) creative thinking, (4) knowledge sharing process, (5) evaluation and nine processes which were (1) preparing in group working, (2) identifying interested topic, (3) analysing interested topic, (4) collecting data, (5) concluding idea (6) proposing idea, (7) creating workings, (8) workings evaluation, (9) sharing knowledge from empirical experience.

Keywords: e-learning system, problem solving ability, team leaning, virtual learning environment

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Renata Masarova, Bohuslava Juhasova, Martin Juhas, Zuzana Sutova

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In dynamic system theory a mathematical model is often used to describe their properties. In order to find a transfer matrix of a dynamic system we need to calculate an inverse matrix. The paper contains the fusion of the classical theory and the procedures used in the theory of automated control for calculating the inverse matrix. The final part of the paper models the given problem by the Matlab.

Keywords: dynamic system, transfer matrix, inverse matrix, modeling

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Authors: Daniele Traversaro

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Problem: Senior citizens have been facing a challenging reality as a result of strict public health measures designed to protect people from the COVID-19 outbreak. These include the risk of social isolation due to the inability of the elderly to integrate with technology. Never before have information and communication technology (ICT) skills become essential for their everyday life. Although third-age ICT education and lifelong learning are widely supported by universities and governments, there is a lack of literature on which teaching strategy/methodology to adopt in an entirely online ICT course aimed at third-age learners. This contribution aims to present an application of the Think-Pair-Share (TPS) learning method in an ICT third-age virtual classroom with an intergenerational approach to conducting online group labs and review activities. This collaborative strategy can help increase student engagement, promote active learning and online social interaction. Research Question: Is collaborative learning applicable and effective, in terms of student engagement and learning outcomes, for an entirely online third-age ICT introductory course? Methods: In the TPS strategy, a problem is posed by the teacher, students have time to think about it individually, and then they work in pairs (or small groups) to solve the problem and share their ideas with the entire class. We performed four experiments in the ICT course of the University of the Third Age of Genova (University of Genova, Italy) on the Microsoft Teams platform. The study cohort consisted of 26 students over the age of 45. Data were collected through online questionnaires. Two have been proposed, one at the end of the first activity and another at the end of the course. They consisted of five and three close-ended questions, respectively. The answers were on a Likert scale (from 1 to 4) except two questions (which asked the number of correct answers given individually and in groups) and the field for free comments/suggestions. Results: Results show that groups perform better than individual students (with scores greater than one order of magnitude) and that most students found it helpful to work in groups and interact with their peers. Insights: From these early results, it appears that TPS is applicable to an online third-age ICT classroom and useful for promoting discussion and active learning. Despite this, our experimentation has a number of limitations. First of all, the results highlight the need for more data to be able to perform a statistical analysis in order to determine the effectiveness of this methodology in terms of student engagement and learning outcomes as a future direction.

Keywords: collaborative learning, information technology education, lifelong learning, older adult education, think-pair-share

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Authors: P. G. Siddheshwar, B. N. Veena

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Rayleigh-B´enard convection of a nanoliquid in shallow, square and tall enclosures is studied using the Khanafer-Vafai-Lightstone single-phase model. The thermophysical properties of water, copper, copper-oxide, alumina, silver and titania at 3000 K under stagnant conditions that are collected from literature are used in calculating thermophysical properties of water-based nanoliquids. Phenomenological laws and mixture theory are used for calculating thermophysical properties. Free-free, rigid-rigid and rigid-free boundary conditions are considered in the study. Intractable Lorenz model for each boundary combination is derived and then reduced to the tractable Ginzburg-Landau model. The amplitude thus obtained is used to quantify the heat transport in terms of Nusselt number. Addition of nanoparticles is shown not to alter the influence of the nature of boundaries on the onset of convection as well as on heat transport. Amongst the three enclosures considered, it is found that tall and shallow enclosures transport maximum and minimum energy respectively. Enhancement of heat transport due to nanoparticles in the three enclosures is found to be in the range 3% - 11%. Comparison of results in the case of rigid-rigid boundaries is made with those of an earlier work and good agreement is found. The study has limitations in the sense that thermophysical properties are calculated by using various quantities modelled for static condition.

Keywords: enclosures, free-free, rigid-rigid, rigid-free boundaries, Ginzburg-Landau model, Lorenz model

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Ziya Uddin

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This paper deals with the theoretical and numerical investigation of magneto-hydrodynamic boundary layer flow of a nano fluid past a wedge shaped wick in heat pipe used for the cooling of electronic components and different type of machines. To incorporate the effect of nanoparticle diameter, concentration of nanoparticles in the pure fluid, nano thermal layer formed around the nanoparticle and Brownian motion of nano particles etc., appropriate models are used for the effective thermal and physical properties of nano fluids. To model the rotation of nano particles inside the base fluid, microfluidics theory is used. In this investigation ethylene glycol (EG) based nanofluids, are taken into account. The non-linear equations governing the flow and heat transfer are solved by using a very effective particle swarm optimization technique along with Runge-Kutta method. The values of heat transfer coefficient are found for different parameters involved in the formulation viz. nanoparticle concentration, nanoparticle size, magnetic field and wedge angle etc. It is found that the wedge angle, presence of magnetic field, nanoparticle size and nanoparticle concentration etc. have prominent effects on fluid flow and heat transfer characteristics for the considered configuration.

Keywords: nanofluids, wedge shaped wick, heat pipe, numerical modeling, particle swarm optimization, nanofluid applications, Heat transfer

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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

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

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Authors: Tiffany Chuang

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The study of inequality in urban space has typically emphasized class and race as dimensions of stratification, but a small and growing body of work also pays attention to exclusionary processes based on moral grounds, as is the case with mainstream disapproval of sexually oriented businesses and red-light districts. However, many sexually-oriented businesses co-exist with similar non-sexually oriented businesses in the tourism and broader entertainment industries. Furthermore, regulators and tourism- and entertainment industries are acknowledged by regulators and ordinary citizens as important contributors to the economy, and in the case of aspiring global cities, to urban prestige. Under such circumstances, it is important to examine how policymakers, residents, and other stakeholders distinguish between sexually oriented and non-sexually oriented businesses, as well as how such efforts shape moral geographies in urban settings. To address this question, this paper introduces the concept of permeable industries to describe businesses that, by their very nature of providing adult entertainment along with a measure of privacy and discretion, facilitate easy interchange between their officially sanctioned purposes and illicit or stigmatised uses, most notably by the sex industry. The permeability and ambiguity surrounding the sexual- and non-sexual activities in such establishments is in fact, a source of tension that generates energetic boundary-drawing exercises that designate legitimate from illegitimate establishments. This paper draws on three years of ethnographic fieldwork, qualitative research, and archival research (1920—2020) on Joo Chiat, a neighborhood in the city-state of Singapore. It then analyzes how middle-class residents reacted to the sudden influx of sexually oriented businesses in the early 2000s, turning the once-quiet residential and commercial neighborhood into a semi-red-light district staffed by migrant Asian women. Ironically, the red-light district had been inadvertently precipitated by the state’s neoliberal policies in the 1990s to cultivate suburban neighborhoods as decentralized tourist attractions while loosening social regulations in pursuit of global city ambitions. Residents mobilized around the discourse of “sleaze”, using it to draw symbolic boundaries while advocating for regulatory boundaries between sexually oriented and non-sexually oriented businesses in the neighborhood. Since the concept of “sleaze” was informed by middle-class distaste for low-status sex work, the result of residents’ efforts was a state-endorsed moral geography that excluded sexually-oriented businesses while tolerating adult-oriented entertainment businesses that dovetailed with global city aspirations. This study contributes to the study of urban inequality by demonstrating the importance of boundary work in reproducing respectability politics, which in turn shapes the urban geographies of moral worth.

Keywords: moral geography, boundary work, respectability politics, entertainment businesses

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Authors: Chibuzo Okoye Daniels, Gillian Glegg, Lynda Rodwell

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Marine debris from fishing nets to medical equipment to food packaging that play major roles in boosting the economy and protecting human health is now more than an environmental problem that can be solved by legislation, law enforcement and technical solutions. It has also been identified as a cultural problem that can only be addressed by identifying instruments that can be used to change human attitudes and behaviors. This may be through management approaches, education and involvement of all sectors/interests, including the public. To contribute to the sustainable development of coastal Nigeria, two case study areas (Ikoyi and Victoria Islands of Lagos State) were used to evaluate the socio-economic impacts of marine debris problem in coastal Nigeria. The following methods were used: (1) semi-structured interviews with key stakeholders and businesses on beaches, waterfronts and waterways within the study areas and (2) observational study of beaches, waterfronts and waterways within the study areas. The results of the study have shown that marine debris is a cultural and multi-sectoral problem that poses great threat not only to the environmental sustainability of the study areas but also to the wellbeing of its citizens and the economy of coastal Nigeria. Current solid waste and marine debris management practices are inefficient due to inadequate knowledge of how to tackle the problem. To ensure environmental sustainability in coastal Nigeria and avoid waste of scarce financial resources, adequate, appropriate and cost effective solutions to the marine debris problem need to be identified and effectively transferred for implementation in the study areas.

Keywords: sustainability, coastal Nigeria, study areas, aquaculture

Procedia PDF Downloads 554

Authors: Pradeep A. G, Gorantla Giridhar, Vijay Turaga, Vinod Srinivasa

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The major problem in the flow control valve is of lower Cv, which will reduce the overall efficiency of the flow circuit. Designers are continuously working to improve the Cv of the valve, but they need to validate the design ideas they have regarding the improvement of Cv. The traditional method of prototyping and testing takes a lot of time. That is where CFD comes into the picture with very quick and accurate validation along with visualization, which is not possible with the traditional testing method. We have developed a method to predict Cv value using CFD analysis by iterating on various Boundary conditions, solver settings and by carrying out grid convergence studies to establish the correlation between the CFD model and Test data. The present study investigates 3 different ideas put forward by the designers for improving the flow capacity of the valves, like reducing the cage thickness, changing the port position, and using the parabolic plug to guide the flow. Using CFD, we analyzed all design changes using the established methodology that we developed. We were able to evaluate the effect of these design changes on the Valve Cv. We optimized the wetted surface of the valve further by suggesting the design modification to the lower part of the valve to make the flow more streamlined. We could find that changing cage thickness and port position has little impact on the valve Cv. The combination of optimized wetted surface and introduction of parabolic plug improved the Flow capacity (Cv) of the valve significantly.

Keywords: flow control valves, flow capacity (Cv), CFD simulations, design validation

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

Procedia PDF Downloads 287

Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: beam structures, layerwise, optimization, variable stiffness

Procedia PDF Downloads 141