Search results for: musculoskeletal modeling
3320 On-Ice Force-Velocity Modeling Technical Considerations
Authors: Dan Geneau, Mary Claire Geneau, Seth Lenetsky, Ming -Chang Tsai, Marc Klimstra
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Introduction— Horizontal force-velocity profiling (HFVP) involves modeling an athletes linear sprint kinematics to estimate valuable maximum force and velocity metrics. This approach to performance modeling has been used in field-based team sports and has recently been introduced to ice-hockey as a forward skating performance assessment. While preliminary data has been collected on ice, distance constraints of the on-ice test restrict the ability of the athletes to reach their maximal velocity which result in limits of the model to effectively estimate athlete performance. This is especially true of more elite athletes. This report explores whether athletes on-ice are able to reach a velocity plateau similar to what has been seen in overground trials. Fourteen male Major Junior ice-hockey players (BW= 83.87 +/- 7.30 kg, height = 188 ± 3.4cm cm, age = 18 ± 1.2 years n = 14) were recruited. For on-ice sprints, participants completed a standardized warm-up consisting of skating and dynamic stretching and a progression of three skating efforts from 50% to 95%. Following the warm-up, participants completed three on ice 45m sprints, with three minutes of rest in between each trial. For overground sprints, participants completed a similar dynamic warm-up to that of on-ice trials. Following the warm-up participants completed three 40m overground sprint trials. For each trial (on-ice and overground), radar was used to collect instantaneous velocity (Stalker ATS II, Texas, USA) aimed at the participant’s waist. Sprint velocities were modelled using custom Python (version 3.2) script using a mono-exponential function, similar to previous work. To determine if on-ice tirals were achieving a maximum velocity (plateau), minimum acceleration values of the modeled data at the end of the sprint were compared (using paired t-test) between on-ice and overground trials. Significant differences (P<0.001) between overground and on-ice minimum accelerations were observed. It was found that on-ice trials consistently reported higher final acceleration values, indicating a maximum maintained velocity (plateau) had not been reached. Based on these preliminary findings, it is suggested that reliable HFVP metrics cannot yet be collected from all ice-hockey populations using current methods. Elite male populations were not able to achieve a velocity plateau similar to what has been seen in overground trials, indicating the absence of a maximum velocity measure. With current velocity and acceleration modeling techniques, including a dependency of a velocity plateau, these results indicate the potential for error in on-ice HFVP measures. Therefore, these findings suggest that a greater on-ice sprint distance may be required or the need for other velocity modeling techniques, where maximal velocity is not required for a complete profile.Keywords: ice-hockey, sprint, skating, power
Procedia PDF Downloads 933319 Estimation of the Upper Tail Dependence Coefficient for Insurance Loss Data Using an Empirical Copula-Based Approach
Authors: Adrian O'Hagan, Robert McLoughlin
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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient
Procedia PDF Downloads 2783318 A Machine Learning-Based Analysis of Autism Prevalence Rates across US States against Multiple Potential Explanatory Variables
Authors: Ronit Chakraborty, Sugata Banerji
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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling
Procedia PDF Downloads 913317 Study of the Relationship between the Roughness Configuration of Channel Bottom and the Creation of Vortices at the Rough Area: Numerical Modelling
Authors: Youb Said, Fourar Ali
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To describe the influence of bottom roughness on the free surface flows by numerical modeling, a two-dimensional model was developed. The equations of continuity and momentum (Naviers Stokes equations) are solved by the finite volume method. We considered a turbulent flow in an open channel with a bottom roughness. For our simulations, the K-ε model was used. After setting the initial and boundary conditions and solve the equations set, we were able to achieve the following results: vortex forming in the hollow causing substantial energy dissipation in the obstacle areas that form the bottom roughness. The comparison of our results with experimental ones shows a good agreement in terms of the results in the rough area. However, in other areas, differences were more or less important. These differences are in areas far from the bottom, especially the free surface area just after the bottom. These disagreements are probably due to experimental constants used by the k-ε model.Keywords: modeling, free surface flow, turbulence, bottom roughness, finite volume, K-ε model, energy dissipation
Procedia PDF Downloads 3743316 Safety Analysis and Accident Modeling of Transportation in Srinagar City
Authors: Adinarayana Badveeti, Mohammad Shafi Mir
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In Srinagar city, in India, road safety is an important aspect that creates ecological balance and social well being. A road accident creates a situation that leaves behind distress, sorrow, and sufferings. Therefore identification of causes of road accidents becomes highly essential for adopting necessary preventive measures against a critical event. The damage created by road accidents to large extent is unrepairable and therefore needs attention to eradicate this continuously increasing trend of awful 'epidemic'. Road accident in India is among the highest in the world, with at least approximately 142.000 people killed each year on the road. Kashmir region is an ecologically sensitive place but lacks necessary facilities and infrastructure regarding road transportation, ultimately resulting in the critical event-road accidents creating a major problem for common people in the region. The objective of this project is to study the safety aspect of Srinagar City and also model the accidents with different aspect that causes accidents and also to suggest the possible remedies for lessening/eliminating the road accidents.Keywords: road safety, road accident, road infrastructure, accident modeling
Procedia PDF Downloads 2463315 Occupational Health Hazards of Itinerant Waste Buyers (IWBs) in Kathmandu, Nepal
Authors: Ashish Khanal, Suja Giri
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The scrap collection work is associated with multiple health hazards. Cut and scratches during collection and transportation of scraps are common. IWBs purchase the scraps mainly papers, cartoons, glass bottles and metals from the households. This study was conducted in Kathmandu, the capital city of Nepal. The location was chosen because Kathmandu is the biggest city of Nepal with highest number of IWBs. The research used a case study strategy to examine the occupational health hazards of IWBs. The only mode of collecting and transporting of scraps in Kathmandu is the bicycle. They have to do this regular work even during the scorching sun and chilled winter. The musculoskeletal and gastrointestinal disorders are the common health problem shared by IWBs in Kathmandu, Nepal. Despite of these problems, IWBs don’t take it seriously and rarely goes for the health check-up. There is need of personal protective equipment and guidance for safety of IWBs. IWBs need to wear closed shoes and use gloves to avoid cuts during the collection and transportation of the recyclables.Keywords: itinerant waste buyers, Kathmandu, occupational health, scrap
Procedia PDF Downloads 1643314 Studying the Theoretical and Laboratory Design of a Concrete Frame and Optimizing Its Design for Impact and Earthquake Resistance
Authors: Mehrdad Azimzadeh, Seyed Mohammadreza Jabbari, Mohammadreza Hosseinzadeh Alherd
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This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.Keywords: optimization, reinforced concrete, optimization methods, impact load, earthquake
Procedia PDF Downloads 1723313 Comparison of Solar Radiation Models
Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci
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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)
Procedia PDF Downloads 3383312 The Effect of Pre-Cracks on Structural Strength of the Nextel Fibers: A Multiscale Modeling Approach
Authors: Seyed Mohammad Mahdi Zamani, Kamran Behdinan
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In this study, a multiscale framework is performed to model the strength of Nextel fibers in presence of an atomistic scale pre-crack at finite temperatures. The bridging cell method (BCM) is the multiscale technique applied in this study, which decomposes the system into the atomistic, bridging and continuum domains; solves the whole system in a finite element framework; and incorporates temperature dependent calculations. Since Nextel is known to be structurally stable and retain 70% of its initial strength up to 1100°C; simulations are conducted at both of the room temperatures, 25°C, and fire temperatures, 1200°C. Two cases are modeled for a pre-crack present in either phases of alumina or mullite of the Nextel structure. The materials’ response is studied with respect to deformation behavior and ultimate tensile strength. Results show different crack growth trends for the two cases, and as the temperature increases, the crack growth resistance and material’s strength decrease.Keywords: Nextel fibers, multiscale modeling, pre-crack, ultimate tensile strength
Procedia PDF Downloads 4083311 Business-Intelligence Mining of Large Decentralized Multimedia Datasets with a Distributed Multi-Agent System
Authors: Karima Qayumi, Alex Norta
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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)
Procedia PDF Downloads 4213310 An Integrated Approach to the Carbonate Reservoir Modeling: Case Study of the Eastern Siberia Field
Authors: Yana Snegireva
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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model
Procedia PDF Downloads 703309 Material Chemistry Level Deformation and Failure in Cementitious Materials
Authors: Ram V. Mohan, John Rivas-Murillo, Ahmed Mohamed, Wayne D. Hodo
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Cementitious materials, an excellent example of highly complex, heterogeneous material systems, are cement-based systems that include cement paste, mortar, and concrete that are heavily used in civil infrastructure; though commonly used are one of the most complex in terms of the material morphology and structure than most materials, for example, crystalline metals. Processes and features occurring at the nanometer sized morphological structures affect the performance, deformation/failure behavior at larger length scales. In addition, cementitious materials undergo chemical and morphological changes gaining strength during the transient hydration process. Hydration in cement is a very complex process creating complex microstructures and the associated molecular structures that vary with hydration. A fundamental understanding can be gained through multi-scale level modeling for the behavior and properties of cementitious materials starting from the material chemistry level atomistic scale to further explore their role and the manifested effects at larger length and engineering scales. This predictive modeling enables the understanding, and studying the influence of material chemistry level changes and nanomaterial additives on the expected resultant material characteristics and deformation behavior. Atomistic-molecular dynamic level modeling is required to couple material science to engineering mechanics. Starting at the molecular level a comprehensive description of the material’s chemistry is required to understand the fundamental properties that govern behavior occurring across each relevant length scale. Material chemistry level models and molecular dynamics modeling and simulations are employed in our work to describe the molecular-level chemistry features of calcium-silicate-hydrate (CSH), one of the key hydrated constituents of cement paste, their associated deformation and failure. The molecular level atomic structure for CSH can be represented by Jennite mineral structure. Jennite has been widely accepted by researchers and is typically used to represent the molecular structure of the CSH gel formed during the hydration of cement clinkers. This paper will focus on our recent work on the shear and compressive deformation and failure behavior of CSH represented by Jennite mineral structure that has been widely accepted by researchers and is typically used to represent the molecular structure of CSH formed during the hydration of cement clinkers. The deformation and failure behavior under shear and compression loading deformation in traditional hydrated CSH; effect of material chemistry changes on the predicted stress-strain behavior, transition from linear to non-linear behavior and identify the on-set of failure based on material chemistry structures of CSH Jennite and changes in its chemistry structure will be discussed.Keywords: cementitious materials, deformation, failure, material chemistry modeling
Procedia PDF Downloads 2793308 A Methodology to Integrate Data in the Company Based on the Semantic Standard in the Context of Industry 4.0
Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini
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Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling
Procedia PDF Downloads 833307 Post-Earthquake Damage Detection Using System Identification with a Pair of Seismic Recordings
Authors: Lotfi O. Gargab, Ruichong R. Zhang
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A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake
Procedia PDF Downloads 3663306 Numerical Study of the Influence of the Primary Stream Pressure on the Performance of the Ejector Refrigeration System Based on Heat Exchanger Modeling
Authors: Elhameh Narimani, Mikhail Sorin, Philippe Micheau, Hakim Nesreddine
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Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.Keywords: Coefficient of Performance, COP, Ejector Refrigeration System, ERS, exergy efficiency (ηII), heat exchangers modeling, moving boundary method
Procedia PDF Downloads 1923305 PWM Based Control of Dstatcom for Voltage Sag, Swell Mitigation in Distribution Systems
Authors: A. Assif
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This paper presents the modeling of a prototype distribution static compensator (D-STATCOM) for voltage sag and swell mitigation in an unbalanced distribution system. Here the concept that an inverter can be used as generalized impedance converter to realize either inductive or capacitive reactance has been used to mitigate power quality issues of distribution networks. The D-STATCOM is here supposed to replace the widely used StaticVar Compensator (SVC). The scheme is based on the Voltage Source Converter (VSC) principle. In this model PWM based control scheme has been implemented to control the electronic valves of VSC. Phase shift control Algorithm method is used for converter control. The D-STATCOM injects a current into the system to mitigate the voltage sags. In this paper the modeling of D¬STATCOM has been designed using MATLAB SIMULINIC. Accordingly, simulations are first carried out to illustrate the use of D-STATCOM in mitigating voltage sag in a distribution system. Simulation results prove that the D-STATCOM is capable of mitigating voltage sag as well as improving power quality of a system.Keywords: D-STATCOM, voltage sag, voltage source converter (VSC), phase shift control
Procedia PDF Downloads 3333304 Instant Fire Risk Assessment Using Artifical Neural Networks
Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan
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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index
Procedia PDF Downloads 1253303 Energy Consumption Modeling for Strawberry Greenhouse Crop by Adaptive Nero Fuzzy Inference System Technique: A Case Study in Iran
Authors: Azar Khodabakhshi, Elham Bolandnazar
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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.Keywords: crop yield, energy, neuro-fuzzy method, strawberry
Procedia PDF Downloads 3683302 Modeling of Oxygen Supply Profiles in Stirred-Tank Aggregated Stem Cells Cultivation Process
Authors: Vytautas Galvanauskas, Vykantas Grincas, Rimvydas Simutis
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This paper investigates a possible practical solution for reasonable oxygen supply during the pluripotent stem cells expansion processes, where the stem cells propagate as aggregates in stirred-suspension bioreactors. Low glucose and low oxygen concentrations are preferred for efficient proliferation of pluripotent stem cells. However, strong oxygen limitation, especially inside of cell aggregates, can lead to cell starvation and death. In this research, the oxygen concentration profile inside of stem cell aggregates in a stem cell expansion process was predicted using a modified oxygen diffusion model. This profile can be realized during the stem cells cultivation process by manipulating the oxygen concentration in inlet gas or inlet gas flow. The proposed approach is relatively simple and may be attractive for installation in a real pluripotent stem cell expansion processes.Keywords: aggregated stem cells, dissolved oxygen profiles, modeling, stirred-tank, 3D expansion
Procedia PDF Downloads 2993301 Physical Modeling of Woodwind Ancient Greek Musical Instruments: The Case of Plagiaulos
Authors: Dimitra Marini, Konstantinos Bakogiannis, Spyros Polychronopoulos, Georgios Kouroupetroglou
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Archaemusicology cannot entirely depend on the study of the excavated ancient musical instruments as most of the time their condition is not ideal (i.e., missing/eroded parts) and moreover, because of the concern damaging the originals during the experiments. Researchers, in order to overcome the above obstacles, build replicas. This technique is still the most popular one, although it is rather expensive and time-consuming. Throughout the last decades, the development of physical modeling techniques has provided tools that enable the study of musical instruments through their digitally simulated models. This is not only a more cost and time-efficient technique but also provides additional flexibility as the user can easily modify parameters such as their geometrical features and materials. This paper thoroughly describes the steps to create a physical model of a woodwind ancient Greek instrument, Plagiaulos. This instrument could be considered as the ancestor of the modern flute due to the common geometry and air-jet excitation mechanism. Plagiaulos is comprised of a single resonator with an open end and a number of tone holes. The combination of closed and open tone holes produces the pitch variations. In this work, the effects of all the instrument’s components are described by means of physics and then simulated based on digital waveguides. The synthesized sound of the proposed model complies with the theory, highlighting its validity. Further, the synthesized sound of the model simulating the Plagiaulos of Koile (2nd century BCE) was compared with its replica build in our laboratory by following the scientific methodologies of archeomusicology. The aforementioned results verify that robust dynamic digital tools can be introduced in the field of computational, experimental archaemusicology.Keywords: archaeomusicology, digital waveguides, musical acoustics, physical modeling
Procedia PDF Downloads 1033300 Assessing the Effectiveness of Machine Learning Algorithms for Cyber Threat Intelligence Discovery from the Darknet
Authors: Azene Zenebe
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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science
Procedia PDF Downloads 1433299 The Impact of Gamification on Self-Assessment for English Language Learners in Saudi Arabia
Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy
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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.Keywords: e-learning system, gamification, motivation, social comparison, visualization
Procedia PDF Downloads 1413298 An Extended Domain-Specific Modeling Language for Marine Observatory Relying on Enterprise Architecture
Authors: Charbel Aoun, Loic Lagadec
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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS
Procedia PDF Downloads 1673297 A Computational Diagnostics for Dielectric Barrier Discharge Plasma
Authors: Zainab D. Abd Ali, Thamir H. Khalaf
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In this paper, the characteristics of electric discharge in gap between two (parallel-plate) dielectric plates are studies, the gap filled with Argon gas in atm pressure at ambient temperature, the thickness of gap typically less than 1 mm and dielectric may be up 10 cm in diameter. One of dielectric plates a sinusoidal voltage is applied with Rf frequency, the other plates is electrically grounded. The simulation in this work depending on Boltzmann equation solver in first few moments, fluid model and plasma chemistry, in one dimensional modeling. This modeling have insight into characteristics of Dielectric Barrier Discharge through studying properties of breakdown of gas, electric field, electric potential, and calculating electron density, mean electron energy, electron current density ,ion current density, total plasma current density. The investigation also include: 1. The influence of change in thickness of gap between two plates if we doubled or reduced gap to half. 2. The effect of thickness of dielectric plates. 3. The influence of change in type and properties of dielectric material (gass, silicon, Teflon).Keywords: computational diagnostics, Boltzmann equation, electric discharge, electron density
Procedia PDF Downloads 7683296 Realistic Modeling of the Preclinical Small Animal Using Commercial Software
Authors: Su Chul Han, Seungwoo Park
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As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.Keywords: mimics, preclinical small animal, segmentation, 3D printer
Procedia PDF Downloads 3593295 Building Capacity and Personnel Flow Modeling for Operating amid COVID-19
Authors: Samuel Fernandes, Dylan Kato, Emin Burak Onat, Patrick Keyantuo, Raja Sengupta, Amine Bouzaghrane
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The COVID-19 pandemic has spread across the United States, forcing cities to impose stay-at-home and shelter-in-place orders. Building operations had to adjust as non-essential personnel worked from home. But as buildings prepare for personnel to return, they need to plan for safe operations amid new COVID-19 guidelines. In this paper we propose a methodology for capacity and flow modeling of personnel within buildings to safely operate under COVID-19 guidelines. We model personnel flow within buildings by network flows with queuing constraints. We study maximum flow, minimum cost, and minimax objectives. We compare our network flow approach with a simulation model through a case study and present the results. Our results showcase various scenarios of how buildings could be operated under new COVID-19 guidelines and provide a framework for building operators to plan and operate buildings in this new paradigm.Keywords: network analysis, building simulation, COVID-19
Procedia PDF Downloads 1513294 Forecasting Electricity Spot Price with Generalized Long Memory Modeling: Wavelet and Neural Network
Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem
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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting
Procedia PDF Downloads 2213293 PM10 Prediction and Forecasting Using CART: A Case Study for Pleven, Bulgaria
Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova
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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.Keywords: cross-validation, decision tree, lagged variables, short-term forecasting
Procedia PDF Downloads 1883292 Modeling Of The Random Impingement Erosion Due To The Impact Of The Solid Particles
Authors: Siamack A. Shirazi, Farzin Darihaki
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Solid particles could be found in many multiphase flows, including transport pipelines and pipe fittings. Such particles interact with the pipe material and cause erosion which threats the integrity of the system. Therefore, predicting the erosion rate is an important factor in the design and the monitor of such systems. Mechanistic models can provide reliable predictions for many conditions while demanding only relatively low computational cost. Mechanistic models utilize a representative particle trajectory to predict the impact characteristics of the majority of the particle impacts that cause maximum erosion rate in the domain. The erosion caused by particle impacts is not only due to the direct impacts but also random impingements. In the present study, an alternative model has been introduced to describe the erosion due to random impingement of particles. The present model provides a realistic trend for erosion with changes in the particle size and particle Stokes number. The present model is examined against the experimental data and CFD simulation results and indicates better agreement with the data incomparison to the available models in the literature.Keywords: erosion, mechanistic modeling, particles, multiphase flow, gas-liquid-solid
Procedia PDF Downloads 1633291 Approaches to Valuing Ecosystem Services in Agroecosystems From the Perspectives of Ecological Economics and Agroecology
Authors: Sandra Cecilia Bautista-Rodríguez, Vladimir Melgarejo
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Climate change, loss of ecosystems, increasing poverty, increasing marginalization of rural communities and declining food security are global issues that require urgent attention. In this regard, a great deal of research has focused on how agroecosystems respond to these challenges as they provide ecosystem services (ES) that lead to higher levels of resilience, adaptation, productivity and self-sufficiency. Hence, the valuing of ecosystem services plays an important role in the decision-making process for the design and management of agroecosystems. This paper aims to define the link between ecosystem service valuation methods and ES value dimensions in agroecosystems from ecological economics and agroecology. The method used to identify valuation methodologies was a literature review in the fields of Agroecology and Ecological Economics, based on a strategy of information search and classification. The conceptual framework of the work is based on the multidimensionality of value, considering the social, ecological, political, technological and economic dimensions. Likewise, the valuation process requires consideration of the ecosystem function associated with ES, such as regulation, habitat, production and information functions. In this way, valuation methods for ES in agroecosystems can integrate more than one value dimension and at least one ecosystem function. The results allow correlating the ecosystem functions with the ecosystem services valued, and the specific tools or models used, the dimensions and valuation methods. The main methodologies identified are multi-criteria valuation (1), deliberative - consultative valuation (2), valuation based on system dynamics modeling (3), valuation through energy or biophysical balances (4), valuation through fuzzy logic modeling (5), valuation based on agent-based modeling (6). Amongst the main conclusions, it is highlighted that the system dynamics modeling approach has a high potential for development in valuation processes, due to its ability to integrate other methods, especially multi-criteria valuation and energy and biophysical balances, to describe through causal cycles the interrelationships between ecosystem services, the dimensions of value in agroecosystems, thus showing the relationships between the value of ecosystem services and the welfare of communities. As for methodological challenges, it is relevant to achieve the integration of tools and models provided by different methods, to incorporate the characteristics of a complex system such as the agroecosystem, which allows reducing the limitations in the processes of valuation of ES.Keywords: ecological economics, agroecosystems, ecosystem services, valuation of ecosystem services
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