Search results for: predictive modelling

Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: S. Obregon-Cano, R. Moreno-Rojas, E. Cartea-Gonzalez, A. De Haro-Bailon

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The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), progoitrin (PRO) and glucobrassicanapin (GBN) in turnip greens and turnip tops was assessed. This crop is grown for edible leaves and stems for human consumption. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the vegetable samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression (calibration set of samples n= 350). The resulting models were satisfactory, with calibration coefficient values from 0.72 (GBN) to 0.98 (tGSL). The predictive ability of the equations obtained was tested using a set of samples (n=70) independent of the calibration set. The determination coefficients and prediction errors (SEP) obtained in the external validation were: GNA=0.94 (SEP=3.49); PRO=0.41 (SEP=1.08); GBN=0.55 (SEP=0.60); tGSL=0.96 (SEP=3.28). These results show that the equations developed for total glucosinolates, as well as for gluconapin can be used for screening these compounds in the leaves and stems of this species. In addition, the progoitrin and glucobrassicanapin equations obtained can be used to identify those samples with high, medium and low contents. The calibration equations obtained were accurate enough for a fast, non-destructive and reliable analysis of the content in GNA and tGSL directly from NIR spectra. The equations for PRO and GBN can be employed to identify samples with high, medium and low contents.

Keywords: brassica rapa, glucosinolates, gluconapin, NIRS, turnip greens

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Authors: C. Patrascioiu, M. Jamali

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The paper deals with the simulation of the crude distillation process using the Unisim Design simulator. The necessity of simulating this process is argued both by considerations related to the design of the crude distillation column, but also by considerations related to the design of advanced control systems. In order to use the Unisim Design simulator to simulate the crude distillation process, the identification of the simulators used in Romania and an analysis of the PRO/II, HYSYS, and Aspen HYSYS simulators were carried out. Analysis of the simulators for the crude distillation process has allowed the authors to elaborate the conclusions of the success of the crude modelling. A first aspect developed by the authors is the implementation of specific problems of petroleum liquid-vapors equilibrium using Unisim Design simulator. The second major element of the article is the development of the methodology and the elaboration of the simulation program for the crude distillation process, using Unisim Design resources. The obtained results validate the proposed methodology and will allow dynamic simulation of the process.  

Keywords: crude oil, distillation, simulation, Unisim Design, simulators

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Authors: Steven Latré, Frederik Desplentere, Ilya Straumit, Stepan V. Lomov

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A method is proposed in order to create a three-dimensional finite element model representing fibre reinforced insulation materials for the simulation software Siemens NX. VoxTex software, a tool for quantification of µCT images of fibrous materials, is used for the transformation of microtomography images of random fibre reinforced composites into finite element models. An automatic tool was developed to execute the import of the models to the thermal solver module of Siemens NX. The paper describes the numerical tools used for the image quantification and the transformation and illustrates them on several thermal simulations of fibre reinforced insulation blankets filled with low thermal conductive fillers. The calculation of thermal conductivity is validated by comparison with the experimental data.

Keywords: analysis, modelling, thermal, voxel

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Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Muhammad Fawad

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Monitoring and structural health assessment are the primary requirements for the performance evaluation of damaged bridges. This paper highlights the case study of a damaged Reinforced Concrete (RC) bridge structure where the Finite element (FE) modelling of this structure was done using the material properties extracted by the in-situ testing. Analysis was carried out to evaluate the bridge damage. On the basis of FE analysis results, this study proposes a proper Structural Health Monitoring (SHM) system that will extend the life cycle of the bridge with minimal repair costs and reduced risk of failure. This system is based on the installation of three different types of sensors: Liquid Levelling sensors (LLS) for measurement of vertical displacement, Distributed Fiber Optic Sensors (DFOS) for crack monitoring, and Weigh in Motion (WIM) devices for monitoring of moving loads on the bridge.

Keywords: bridges, reinforced concrete, finite element method, structural health monitoring, sensors

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Authors: N. Webb, A. Buchanan

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Digital and virtual heritage is often associated with the recreation of lost artefacts and architecture; however, we can also investigate works that were not completed, using digital tools and techniques. Here we explore physical evidence of a fourteenth-century Gothic vault located in the north transept of St Mary’s church in Nantwich, Cheshire, using existing springer stones that are built into the walls as a starting point. Digital surveying tools are used to document the architecture, followed by an analysis process to hypothesise and simulate possible design solutions, had the vault been completed. A number of options, both two-dimensionally and three-dimensionally, are discussed based on comparison with examples of other contemporary vaults, thus adding another specimen to the corpus of vault designs. Dissemination methods such as digital models and 3D prints are also explored as possible resources for demonstrating what the finished vault might have looked like for heritage interpretation and other purposes.

Keywords: digital simulation, heritage interpretation, medieval vaults, virtual heritage, 3d scanning

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Authors: Shagil Akhtar, Syed Muneeb Iqbal, Mohammed R. Rahim

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Common steel tubes with similar confines were used in simulation of tubes with distinctive type of corrugated sections. These corrugated cross-sections were arc-tangent, triangular, trapezoidal and square corrugated sections. The outcome of fluctuating structures of tube cross-section shape on the deformation feedback, collapse form and energy absorption characteristics of tubes under quasi-static axial compression have been prepared numerically. The finite element package of ANSYS Workbench was applied in the current analysis. The axial load-displacement products accompanied by the fold formation of disparate tubes were inspected and compared. Deviation of the initial peak load and the mean crushing force of the tubes with distinctive cross-sections were conscientiously examined.

Keywords: absorbed energy, axial loading, corrugated tubes, finite element, initial peak load, mean crushing force

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Authors: Olga Orynycz, Andrzej Wasiak

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Mathematical model describing energetic efficiency (defined as a ratio of energy obtained in the form of biofuel to the sum of energy inputs necessary to facilitate production) of agricultural subsystem as a function of technological parameters was developed. Production technology is characterized by parameters of machinery, topological characteristics of the plantation as well as transportation routes inside and outside of plantation. The relationship between the energetic efficiency of agricultural and industrial subsystems is also derived. Due to the assumed large area of the individual field, the operations last for several days increasing inter-fields routes because of several returns. The total distance driven outside of the fields is, however, small as compared to the distance driven inside of the fields. This results in small energy consumption during inter-fields transport that, however, causes a substantial decrease of the energetic effectiveness of the whole system.

Keywords: biofuel, energetic efficiency, EROEI, mathematical modelling, production system

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Zaid Jamal Saeed Almahmoud

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Smart Grid is the vision of the future power system that combines advanced monitoring and communication technologies to provide energy in a smart, efficient, and user-friendly manner. This proposal considers a demand response model in the Smart Grid based on utility maximization. Given a set of consumers with conflicting preferences in terms of consumption and a utility company that aims to minimize the peak demand and match demand to supply, we study the problem of aggregating these preferences while modelling the problem as a game. We also investigate whether an equilibrium can be reached to maximize the social benefit. Based on such equilibrium, we propose a dynamic pricing heuristic that computes the equilibrium and sets the prices accordingly. The developed approach was analysed theoretically and evaluated experimentally using real appliances data. The results show that our proposed approach achieves a substantial reduction in the overall energy consumption.

Keywords: heuristics, smart grid, aggregation, mechanism design, equilibrium

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Authors: Onyebuchi Mogbo, Abdulsalam Mohammed, Salsabila Wali

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This research discusses the design and modeling of an amphibious building. The amphibious building is a house with the function of floating during a flood event. Over the years, houses have been built to resist flood events some of which have failed. The floating house is designed to work with nature and not against it. In the event of a flood, the house will rise with the increasing water level and protect the house from sinking. For the design and modeling of this house an estimated cost of N250, 000, approximately $700, will be needed. It is expected that the house will rise when lightweight materials are incorporated in the design, and the concrete dock (in form of a hollow box) carrying the entire house in its hollow space is well designed. When there is flooding the water will fill up the concrete dock, and the house will rise upwards with vertical guides preventing it from moving side to side or out of its boundary. Architectural and Structural designs will be used in this project.

Keywords: amphibious building, flood, housing, design and modelling

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Authors: Gilbert Makanda

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The problem of the teaching of mathematics is studied using differential equations. A mathematical model for knowledge acquisition in mathematics is developed. In this study we adopt the mathematical model that is normally used for disease modelling in the teaching of mathematics. It is assumed that teaching is 'infecting' students with knowledge thereby spreading this knowledge to the students. It is also assumed that students who gain this knowledge spread it to other students making disease model appropriate to adopt for this problem. The results of this study show that increasing recruitment rates, learning contact with teachers and learning materials improves the number of knowledgeable students. High dropout rates and forgetting taught concepts also negatively affect the number of knowledgeable students. The developed model is then solved using Matlab ODE45 and \verb"lsqnonlin" to estimate parameters for the actual data.

Keywords: differential equations, knowledge acquisition, least squares, dynamical systems

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Authors: Montserrat Guillen, Stephania Mosquera-Lopez, Jorge Uribe

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An empirical study of market risk transmission between electricity prices in the Nord Pool interconnected market is done. Crucially, it is differentiated between risk propagation in the two tails of the price variation distribution. Thus, the downside risk from upside risk spillovers is distinguished. The results found document an asymmetric nature of risk and risk propagation in the two tails of the electricity price log variations. Risk spillovers following price increments in the market are transmitted to a larger extent than those after price reductions. Also, asymmetries related to both, the size of the transaction area and related to whether a given area behaves as a net-exporter or net-importer of electricity, are documented. For instance, on the one hand, the bigger the area of the transaction, the smaller the size of the volatility shocks that it receives. On the other hand, exporters of electricity, alongside countries with a significant dependence on renewable sources, tend to be net-transmitters of volatility to the rest of the system. Additionally, insights on the predictive power of positive and negative semivariances for future market volatility are provided. It is shown that depending on the forecasting horizon, downside and upside shocks to the market are featured by a distinctive persistence, and that upside volatility impacts more on net-importers of electricity, while the opposite holds for net-exporters.

Keywords: electricity prices, realized volatility, semivariances, volatility spillovers

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

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Authors: Cristian Crespo

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Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

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Authors: Ibram Khalafalla Roshdy Shokry

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This paper gives service feel multiple get entry to (CSMA) verbal exchange model based totally totally on SoC format method. Such model can be used to guide the modelling of the complex c084d04ddacadd4b971ae3d98fecfb2a communique systems, consequently use of such communication version is an crucial method in the creation of excessive general overall performance conversation. SystemC has been selected as it gives a homogeneous format drift for complicated designs (i.e. SoC and IP based format). We use a swarm device to validate CSMA designed version and to expose how advantages of incorporating communication early within the layout process. The wireless conversation created via the modeling of CSMA protocol that may be used to attain conversation among all of the retailers and to coordinate get proper of entry to to the shared medium (channel).The device of automobiles with wi-fiwireless communique abilities is expected to be the important thing to the evolution to next era intelligent transportation systems (ITS). The IEEE network has been continuously operating at the development of an wireless vehicular communication protocol for the enhancement of wi-fi get admission to in Vehicular surroundings (WAVE). Vehicular verbal exchange systems, known as V2X, help car to car (V2V) and automobile to infrastructure (V2I) communications. The wi-ficiencywireless of such communication systems relies upon on several elements, amongst which the encircling surroundings and mobility are prominent. as a result, this observe makes a speciality of the evaluation of the actual performance of vehicular verbal exchange with unique cognizance on the effects of the actual surroundings and mobility on V2X verbal exchange. It begins by wi-fi the actual most range that such conversation can guide and then evaluates V2I and V2V performances. The Arada LocoMate OBU transmission device changed into used to check and evaluate the effect of the transmission range in V2X verbal exchange. The evaluation of V2I and V2V communique takes the real effects of low and excessive mobility on transmission under consideration.Multiagent systems have received sizeable attention in numerous wi-fields, which include robotics, independent automobiles, and allotted computing, where a couple of retailers cooperate and speak to reap complicated duties. wi-figreen communication among retailers is a critical thing of these systems, because it directly influences their usual performance and scalability. This scholarly work gives an exploration of essential communication factors and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of those protocols across diverse situations. The studies additionally sheds light on rising tendencies within verbal exchange protocols for multiagent systems, together with the incorporation of device mastering strategies and the adoption of blockchain-based totally solutions to make sure comfy communique. those developments offer valuable insights into the evolving landscape of multiagent structures and their verbal exchange protocols.

Keywords: communication, multi-agent systems, protocols, consensussystemC, modelling, simulation, CSMA

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

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In order to sustain the advantages of an advanced manufacturing technique, such as laser sintering, minimization of total processing cost of the parts being produced is very important. An efficient time management would usually very important in optimal cost attainment which would ultimately result in an efficient advanced manufacturing process planning and control. During Laser Scanning Process Scanning (SLS) procedures it is possible to adjust various manufacturing parameters which are used to influence the improvement of various mechanical and other properties of the products. In this study, Modelling and mathematical analysis, including sensitivity analysis, of the laser sintering process time were carried out. The results of the analyses were represented with graphs, from where conclusions were drawn. It was specifically observed that achievement of optimal total scanning time is key for economic efficiency which is required for sustainability of the process.

Keywords: modeling and analysis, optimal planning and control, laser sintering process, scanning time

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Authors: Jeevan Balaji, Shreyas Chigurupati

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Pneumatic gripper use compressed air to operate its actuators (fingers). Unlike the conventional metallic gripper, a soft pneumatic actuator (SPA) can be used for relocating fragile objects. An added advantage for this gripper is that the pressure exerted on the object can be varied by changing the dimensions of the air chambers and also by the number of chambers. SPAs have many benefits over conventional robots in the military, medical fields because of their compliance nature and are easily produced using the 3D printing process. In the paper, SPA is proposed to perform pick and place tasks. A design was developed for the actuators, which is convenient for gripping any fragile objects. Thermoplastic polyurethane (TPU) is used for 3D printing the actuators. The actuator model behaves differently as the parameters such as its chamber height, number of chambers change. A detailed FEM model of the actuator is drafted for different pressure inputs using ABAQUS CAE software, and a safe loading pressure range is found.

Keywords: soft robotics, pneumatic actuator, design and modelling, bending analysis

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Authors: Ryan D. Hoult

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The inherent assumption in the elementary theory of bending that plane sections remain plane is commonly used in the design of reinforced concrete members. However, in reality, a shear flow would develop in non-rectangular sections, where the longitudinal strains in between the web and flanges of the element would lag behind those at the boundary ends. This phenomenon, known as shear lag, can significantly reduce the expected moment capacity of non-rectangular reinforced concrete walls. This study focuses on shear lag effects in reinforced concrete U-shaped walls, which are commonly used as lateral load resisting elements in reinforced concrete buildings. An extensive number of finite element modelling analyses are conducted to estimate the vertical strain distributions across the web and flanges of a U-shaped wall with different axial load ratios and longitudinal reinforcement detailing. The results show that shear lag effects are prominent and sometimes significant in U-shaped walls, particularly for the wall sections perpendicular to the direction of loading.

Keywords: shear lag, walls, U-shaped, moment-curvature

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Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

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Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

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Authors: Nadia Zahra Karimi Khiavi, Amir Ghiami Rad

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Due to the high likelihood of injuries in karate, karatekas' injuries warrant special treatment. This study explores the prevalence of karate injuries in East Azerbaijan, Iran and provides a model for karatekas to use in the prevention of such injuries. This study employs a descriptive approach. Male and female participants with a brown belt or above in either control or non-control styles in East Azerbaijan province are included in the study's statistical population. A statistical sample size of 100 people was computed using the tools employed (smartpls), and the samples were drawn at random from all clubs in the province with the assistance of the Karate Board in order to give a model for the prevention of karate injuries. Information was gathered by means of a survey that made use of the Standard Questionnaire for Australian Sports Medicine Injury Reports. The information is presented in the form of tables and samples, and descriptive statistics were used to organise and summarise the data. Control and non-control independent t-tests were conducted using SPSS version 20, and structural equation modelling (pls) was utilised for injury prevention modelling at a 0.05 level of significance. The results showed that the most common areas of injury among the control groups were the upper limbs (46.15%), lower limbs (34.61%), trunk (15.38%), and head and neck (3.84%). The most common types of injuries were broken bones (34.61%), sprain or strain (23.13%), bruising and contusions (23.13%), trauma to the face and mouth (11.53%), and damage to the nerves (69.69%). Uncontrolled committees are most likely to sustain injuries to the head and neck (33.33%), trunk (25.92%), upper limbs (22.22%), and lower limbs (18.51%). The most common injuries were to the mouth and face (33.33%), dislocations and fractures (22.22%), aspirin and strain (22.22%), bruises and contusions (18.51%), and nerves (70%), in that order. Among those who practice control kata, injuries to the upper limb account for 45.83%, the lower limb for 41.666%, the trunk for 8.33%, and the head and neck for 4.166%. The most common types of injuries are dislocations and fractures (41.66 per cent), aspirin and strain (29.16 per cent), bruising and bruises (16.66 per cent), and nerves (12.5%). Injuries to the face and mouth were not reported among those practising the control kata. By far, the most common sites of injury for those practising uncontrolled kata were the lower limb (43.74%), upper limb (39.13%), trunk (13.14%), and head and neck (4.34%). The most common types of injuries were dislocations and fractures (34.82%), aspirin and strain (26.08%), bruises and contusions (21.73%), mouth and face (13.14%), and nerves. Teaching the concepts of cooling and warming (0.591) and enhancing the degree of safety in the sports environment (0.413) were shown to play the most essential roles in reducing sports injuries among karate practitioners of controlling and uncontrolled styles, respectively. Use of common sports gear (0.390), Modification of training programme principles (0.341), Formulation of an effective diet plan for athletes (0.284), Evaluation of athletes' physical anatomy, physiology, chemistry, and physics (0.247).

Keywords: sports injuries, karate, prevention, cooling and warming

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Authors: R. Tamborrino, F. Rinaudo

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Digital technologies offer possibilities to effectively convert historical archives into instruments of knowledge able to provide a guide for the interpretation of historical phenomena. Digital conversion and management of those documents allow the possibility to add other sources in a unique and coherent model that permits the intersection of different data able to open new interpretations and understandings. Urban history uses, among other sources, the inventories that register human activities in a specific space (e.g. cadastres, censuses, etc.). The geographic localisation of that information inside cartographic supports allows for the comprehension and visualisation of specific relationships between different historical realities registering both the urban space and the peoples living there. These links that merge the different nature of data and documentation through a new organisation of the information can suggest a new interpretation of other related events. In all these kinds of analysis, the use of GIS platforms today represents the most appropriate answer. The design of the related databases is the key to realise the ad-hoc instrument to facilitate the analysis and the intersection of data of different origins. Moreover, GIS has become the digital platform where it is possible to add other kinds of data visualisation. This research deals with the industrial development of Turin at the beginning of the 20th century. A census of factories realized just prior to WWI provides the opportunity to test the potentialities of GIS platforms for the analysis of urban landscape modifications during the first industrial development of the town. The inventory includes data about location, activities, and people. GIS is shaped in a creative way linking different sources and digital systems aiming to create a new type of platform conceived as an interface integrating different kinds of data visualisation. The data processing allows linking this information to an urban space, and also visualising the growth of the city at that time. The sources, related to the urban landscape development in that period, are of a different nature. The emerging necessity to build, enlarge, modify and join different buildings to boost the industrial activities, according to their fast development, is recorded by different official permissions delivered by the municipality and now stored in the Historical Archive of the Municipality of Turin. Those documents, which are reports and drawings, contain numerous data on the buildings themselves, including the block where the plot is located, the district, and the people involved such as the owner, the investor, and the engineer or architect designing the industrial building. All these collected data offer the possibility to firstly re-build the process of change of the urban landscape by using GIS and 3D modelling technologies thanks to the access to the drawings (2D plans, sections and elevations) that show the previous and the planned situation. Furthermore, they access information for different queries of the linked dataset that could be useful for different research and targets such as economics, biographical, architectural, or demographical. By superimposing a layer of the present city, the past meets to the present-industrial heritage, and people meet urban history.

Keywords: digital urban history, census, digitalisation, GIS, modelling, digital humanities

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Authors: R. Ranjith Kumar

Abstract:

Computer modeling and simulation of human movement is playing an important role in sports and rehabilitation. Accurate modeling and analysis of human knee join is more complex because of complicated structure whose geometry is not easily to represent by a solid model. As part of this project, from the number of CT scan images of human knee join surface reconstruction is carried out using 3D slicer software, an open source software. From this surface reconstruction model, using mesh lab (another open source software) triangular meshes are created on reconstructed surface. This final triangular mesh model is imported to Solid Works, 3D mechanical CAD modeling software. Finally this CAD model is imported to ABAQUS, finite element analysis software for analyzing the knee joints. The results obtained are encouraging and provides an accurate way of modeling and analysis of biological parts without human intervention.

Keywords: solid works, CATIA, Pro-e, CAD

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Authors: Candice Lemaitre

Abstract:

During the 1990s, an alliance of international intergovernmental and non-governmental organizations proposed a set of regulatory norms designed to reduce corruption. Many governments in developing countries, such as Vietnam, enacted these global anti-corruption norms into their domestic law. This article draws on empirical research to understand why these anti-corruption norms have failed to reduce corruption in Vietnam and many other developing countries. Rather than investigating state compliance with global anti-corruption provisions, a topic that has already attracted considerable attention, this article aims to explore the comparatively under-researched area of business compliance. Based on data collected from semi-structured interviews with business managers in Vietnam and archival research, this article examines how businesses in Vietnam interpret and comply with global anti-corruption norms. It investigates why different types of companies in Vietnam engage with and respond to these norms in different ways. This article suggests that global anti-corruption norms have not been effective in reducing corruption in Vietnam because there is fragmentation in the way companies in Vietnam interpret and respond to these norms. This fragmentation results from differences in the epistemic (or interpretive) communities that companies draw upon to interpret global anti-corruption norms. This article uses discourse analysis to understand how the communities interpret global anti-corruption norms. This investigation aims to generate some predictive insights into how companies are likely to respond to anti-corruption regimes based on global anti-corruption norms.

Keywords: anti-corruption, business law, legal transfer, Vietnam

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Authors: Aurore Cauquis, Philippe Heinrich, Mario Ricchiuto, Audrey Gailler

Abstract:

In this talk, we look for an accurate time scheme to model the propagation of waves. Several numerical schemes have been developed to solve the extended weakly nonlinear weakly dispersive Boussinesq Equations. The temporal schemes used are two Lax-Wendroff schemes, second or third order accurate, two Runge-Kutta schemes of second and third order and a simplified third order accurate Lax-Wendroff scheme. Spatial derivatives are evaluated with fourth order accuracy. The numerical model is applied to two monodimensional benchmarks on a flat bottom. It is also applied to the simulation of the Algerian tsunami generated by a Mw=6 seism on the 18th March 2021. The tsunami propagation was highly dispersive and propagated across the Mediterranean Sea. We study here the effects of the order of temporal discretization on the accuracy of the results and on the time of computation.

Keywords: numerical analysis, tsunami propagation, water wave, boussinesq equations

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Authors: A. Falenski, A. Kaesbohrer, M. Filter

Abstract:

Introduction: Risk assessments can be performed in various ways and in different degrees of complexity. In order to assess risks associated with imported foods additional information needs to be taken into account compared to a risk assessment on regional products. The present review is an overview on currently available best practise approaches and data sources used for food import risk assessments (IRAs). Methods: A literature review has been performed. PubMed was searched for articles about food IRAs published in the years 2004 to 2014 (English and German texts only, search string “(English [la] OR German [la]) (2004:2014 [dp]) import [ti] risk”). Titles and abstracts were screened for import risks in the context of IRAs. The finally selected publications were analysed according to a predefined questionnaire extracting the following information: risk assessment guidelines followed, modelling methods used, data and software applied, existence of an analysis of uncertainty and variability. IRAs cited in these publications were also included in the analysis. Results: The PubMed search resulted in 49 publications, 17 of which contained information about import risks and risk assessments. Within these 19 cross references were identified to be of interest for the present study. These included original articles, reviews and guidelines. At least one of the guidelines of the World Organisation for Animal Health (OIE) and the Codex Alimentarius Commission were referenced in any of the IRAs, either for import of animals or for imports concerning foods, respectively. Interestingly, also a combination of both was used to assess the risk associated with the import of live animals serving as the source of food. Methods ranged from full quantitative IRAs using probabilistic models and dose-response models to qualitative IRA in which decision trees or severity tables were set up using parameter estimations based on expert opinions. Calculations were done using @Risk, R or Excel. Most heterogeneous was the type of data used, ranging from general information on imported goods (food, live animals) to pathogen prevalence in the country of origin. These data were either publicly available in databases or lists (e.g., OIE WAHID and Handystatus II, FAOSTAT, Eurostat, TRACES), accessible on a national level (e.g., herd information) or only open to a small group of people (flight passenger import data at national airport customs office). In the IRAs, an uncertainty analysis has been mentioned in some cases, but calculations have been performed only in a few cases. Conclusion: The current state-of-the-art in the assessment of risks of imported foods is characterized by a great heterogeneity in relation to general methodology and data used. Often information is gathered on a case-by-case basis and reformatted by hand in order to perform the IRA. This analysis therefore illustrates the need for a flexible, modular framework supporting the connection of existing data sources with data analysis and modelling tools. Such an infrastructure could pave the way to IRA workflows applicable ad-hoc, e.g. in case of a crisis situation.

Keywords: import risk assessment, review, tools, food import

Procedia PDF Downloads 299