Search results for: high-performance cycle model application
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24520

Search results for: high-performance cycle model application

20800 Estimation of Soil Moisture at High Resolution through Integration of Optical and Microwave Remote Sensing and Applications in Drought Analyses

Authors: Donglian Sun, Yu Li, Paul Houser, Xiwu Zhan

Abstract:

California experienced severe drought conditions in the past years. In this study, the drought conditions in California are analyzed using soil moisture anomalies derived from integrated optical and microwave satellite observations along with auxiliary land surface data. Based on the U.S. Drought Monitor (USDM) classifications, three typical drought conditions were selected for the analysis: extreme drought conditions in 2007 and 2013, severe drought conditions in 2004 and 2009, and normal conditions in 2005 and 2006. Drought is defined as negative soil moisture anomaly. To estimate soil moisture at high spatial resolutions, three approaches are explored in this study: the universal triangle model that estimates soil moisture from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST); the basic model that estimates soil moisture under different conditions with auxiliary data like precipitation, soil texture, topography, and surface types; and the refined model that uses accumulated precipitation and its lagging effects. It is found that the basic model shows better agreements with the USDM classifications than the universal triangle model, while the refined model using precipitation accumulated from the previous summer to current time demonstrated the closest agreements with the USDM patterns.

Keywords: soil moisture, high resolution, regional drought, analysis and monitoring

Procedia PDF Downloads 136
20799 Teachers Engagement to Teaching: Exploring Australian Teachers’ Attribute Constructs of Resilience, Adaptability, Commitment, Self/Collective Efficacy Beliefs

Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

Abstract:

Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

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20798 Causes of Variation Orders in the Egyptian Construction Industry: Time and Cost Impacts

Authors: A. Samer Ezeldin, Jwanda M. El Sarag

Abstract:

Variation orders are of great importance in any construction project. Variation orders are defined as any change in the scope of works of a project that can be an addition omission, or even modification. This paper investigates the variation orders that occur during construction projects in Egypt. The literature review represents a comparison of causes of variation orders among Egypt, Tanzania, Nigeria, Malaysia and the United Kingdom. A classification of occurrence of variation orders due to owner related factors, consultant related factors and other factors are signified in the literature review. These classified events that lead to variation orders were introduced in a survey with 19 events to observe their frequency of occurrence, and their time and cost impacts. The survey data was obtained from 87 participants that included clients, consultants, and contractors and a database of 42 scenarios was created. A model is then developed to help assist project managers in predicting the frequency of variations and account for a budget for any additional costs and minimize any delays that can take place. Two experts with more than 25 years of experience were given the model to verify that the model was working effectively. The model was then validated on a residential compound that was completed in July 2016 to prove that the model actually produces acceptable results.

Keywords: construction, cost impact, Egypt, time impact, variation orders

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20797 Analysis of a Coupled Hydro-Sedimentological Numerical Model for the Western Tombolo of Giens

Authors: Yves Lacroix, Van Van Than, Didier Léandri, Pierre Liardet

Abstract:

The western Tombolo of the Giens peninsula in southern France, known as Almanarre beach, is subject to coastal erosion. We are trying to use computer simulation in order to propose solutions to stop this erosion. Our aim was first to determine the main factors for this erosion and successfully apply a coupled hydro-sedimentological numerical model based on observations and measurements that have been performed on the site for decades. We have gathered all available information and data about waves, winds, currents, tides, bathymetry, coastal line, and sediments concerning the site. These have been divided into two sets: one devoted to calibrating a numerical model using Mike 21 software, the other to serve as a reference in order to numerically compare the present situation to what it could be if we implemented different types of underwater constructions. This paper presents the first part of the study: selecting and melting different sources into a coherent data basis, identifying the main erosion factors, and calibrating the coupled software model against the selected reference period. Our results bring calibration of the numerical model with good fitting coefficients. They also show that the winter South-Western storm events conjugated to depressive weather conditions constitute a major factor of erosion, mainly due to wave impact in the northern part of the Almanarre beach. Together, current and wind impact is shown negligible.

Keywords: Almanarre beach, coastal erosion, hydro-sedimentological, numerical model

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20796 A Parallel Approach for 3D-Variational Data Assimilation on GPUs in Ocean Circulation Models

Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

Abstract:

This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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20795 Green Synthesis of Silver Nanoparticles by Olive Leaf Extract: Application in the Colorimetric Detection of Fe+3 Ions

Authors: Nasibeh Azizi Khereshki

Abstract:

Olive leaf (OL) extract as a green reductant agent was utilized for the biogenic synthesis of silver nanoparticles (Ag NPs) for the first time in this study, and then its performance was evaluated for colorimetric detection of Fe3+ in different media. Some analytical methods were used to characterize the nanosensor. The effective sensing parameters were optimized by central composite design (CCD) combined with response surface methodology (RSM) application. Then, the prepared material's applicability in antibacterial and optical chemical sensing for naked-eye detection of Fe3+ ions in aqueous solutions were evaluated. Furthermore, OL-Ag NPs-loaded paper strips were successfully applied to the colorimetric visualization of Fe3+. The colorimetric probe based on OL-AgNPs illustrated excellent selectivity and sensitivity towards Fe3+ ions, with LOD and LOQ of 0.81 μM and 2.7 μM, respectively. In addition, the developed method was applied to detect Fe3+ ions in real water samples and validated with a 95% confidence level against a reference spectroscopic method.

Keywords: Ag NPs, colorimetric detection, Fe(III) ions, green synthesis, olive leaves

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20794 Giftedness Cloud Model: A Psychological and Ecological Vision of Giftedness Concept

Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

Abstract:

The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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20793 3D Images Representation to Provide Information on the Type of Castella Beams Hole

Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi

Abstract:

Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.

Keywords: digital image, image processing, edge detection, grayscale, castella beams

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20792 Finite Element Simulation of RC Exterior Beam-Column Joints Using Damage Plasticity Model

Authors: A. M. Halahla, M. H. Baluch, M. K. Rahman, A. H. Al-Gadhib, M. N. Akhtar

Abstract:

In the present study, 3D simulation of a typical exterior (RC) beam–column joint (BCJ) strengthened with carbon fiber-reinforced plastic (CFRP) sheet are carried out. Numerical investigations are performed using a nonlinear finite element ( FE) analysis by incorporating damage plasticity model (CDP), for material behaviour the concrete response in compression, tension softening were used, linear plastic with isotropic hardening for reinforcing steel, and linear elastic lamina material model for CFRP sheets using the commercial FE software ABAQUS. The numerical models developed in the present study are validated with the results obtained from the experiment under monotonic loading using the hydraulic Jack in displacement control mode. The experimental program includes casting of deficient BCJ loaded to failure load for both un-strengthened and strengthened BCJ. The failure mode, and deformation response of CFRP strengthened and un-strengthened joints and propagation of damage in the components of BCJ are discussed. Finite element simulations are compared with the experimental result and are noted to yield reasonable comparisons. The damage plasticity model was able to capture with good accuracy of the ultimate load and the mode of failure in the beam column joint.

Keywords: reinforced concrete, exterior beam-column joints, concrete damage plasticity model, computational simulation, 3-D finite element model

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20791 An Interlock Model of Friction and Superlubricity

Authors: Azadeh Malekan, Shahin Rouhani

Abstract:

Superlubricity is a phenomenon where two surfaces in contact show negligible friction;this may be because the asperities of the two surfaces do not interlock. Two rough surfaces, when pressed against each other, can get into a formation where the summits of asperities of one surface lock into the valleys of the other surface. The amount of interlock depends on the geometry of the two surfaces. We suggest the friction force may then be proportional to the amount of interlock; this explains Superlubricity as the situation where there is little interlock. Then the friction force will be directly proportional to the normal force as it is related to the work necessary to lift the upper surface in order to clear the interlock. To investigate this model, we simulate the contact of two surfaces. In order to validate our model, we first investigate Amontons‘ law. Assuming that asperities retain deformations in the time scale while the top asperity moves across the lattice spacing Amonton’s law is observed. Structural superlubricity is examined by the hypothesis that surfaces are very rigid and there is no deformation in asperities. This may happen at small normal forces. When two identical surfaces come into contact, rotating the top surface we observe a peak in friction force near the angle of orientation where the two surfaces can interlock.

Keywords: friction, amonton`s law, superlubricity, contact model

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20790 Transport of Reactive Carbo-Iron Composite Particles for in situ Groundwater Remediation Investigated at Laboratory and Field Scale

Authors: Sascha E. Oswald, Jan Busch

Abstract:

The in-situ dechlorination of contamination by chlorinated solvents in groundwater via zero-valent iron (nZVI) is potentially an efficient and prompt remediation method. A key requirement is that nZVI has to be introduced in the subsurface in a way that substantial quantities of the contaminants are actually brought into direct contact with the nZVI in the aquifer. Thus it could be a more flexible and precise alternative to permeable reactive barrier techniques using granular iron. However, nZVI are often limited by fast agglomeration and sedimentation in colloidal suspensions, even more so in the aquifer sediments, which is a handicap for the application to treat source zones or contaminant plumes. Colloid-supported nZVI show promising characteristics to overcome these limitations and Carbo-Iron Colloids is a newly developed composite material aiming for that. The nZVI is built onto finely ground activated carbon of about a micrometer diameter acting as a carrier for it. The Carbo-Iron Colloids are often suspended with a polyanionic stabilizer, and carboxymethyl cellulose is one with good properties for that. We have investigated the transport behavior of Carbo-Iron Colloids (CIC) on different scales and for different conditions to assess its mobility in aquifer sediments as a key property for making its application feasible. The transport properties were tested in one-dimensional laboratory columns, a two-dimensional model aquifer and also an injection experiment in the field. Those experiments were accompanied by non-invasive tomographic investigations of the transport and filtration processes of CIC suspensions. The laboratory experiments showed that a larger part of the CIC can travel at least scales of meters for favorable but realistic conditions. Partly this is even similar to a dissolved tracer. For less favorable conditions this can be much smaller and in all cases a particular fraction of the CIC injected is retained mainly shortly after entering the porous medium. As field experiment a horizontal flow field was established, between two wells with a distance of 5 meters, in a confined, shallow aquifer at a contaminated site in North German lowlands. First a tracer test was performed and a basic model was set up to define the design of the CIC injection experiment. Then CIC suspension was introduced into the aquifer at the injection well while the second well was pumped and samples taken there to observe the breakthrough of CIC. This was based on direct visual inspection and total particle and iron concentrations of water samples analyzed in the laboratory later. It could be concluded that at least 12% of the CIC amount injected reached the extraction well in due course, some of it traveling distances larger than 10 meters in the non-uniform dipole flow field. This demonstrated that these CIC particles have a substantial mobility for reaching larger volumes of a contaminated aquifer and for interacting there by their reactivity with dissolved contaminants in the pore space. Therefore they seem suited well for groundwater remediation by in-situ formation of reactive barriers for chlorinated solvent plumes or even source removal.

Keywords: carbo-iron colloids, chlorinated solvents, in-situ remediation, particle transport, plume treatment

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20789 Nanoparticle Induced Neurotoxicity Mediated by Mitochondria

Authors: Nandini Nalika, Suhel Parvez

Abstract:

Nanotechnology has emerged to play a vital role in developing all through the industrial world with an immense production of nanomaterials including nanoparticles (NPs). Many toxicological studies have confirmed that due to unique small size and physico-chemical properties of NPs (1-100nm), they can be potentially hazardous. Metallic NPs of small size have been shown to induce higher levels of cellular oxidative stress and can easily pass through the Blood Brain Barrier (BBB) and significantly accumulate in brain. With the wide applications of titanium dioxide nanoparticles (TNPs) in day-to-day life in form of cosmetics, paints, sterilisation and so on, there is growing concern regarding the deleterious effects of TNPs on central nervous system and mitochondria appear to be important cellular organelles targeted to the pro-oxidative effects of NPs and an important source that contribute significantly for the production of reactive oxygen species after some toxicity or an injury. The aim of our study was to elucidate the effect of TNPs in anatase form with different concentrations (5-50 µg/ml) following with various oxidative stress markers in isolated brain mitochondria as an in vitro model. Oxidative stress was determined by measuring the different oxidative stress markers like lipid peroxidation as well as the protein carbonyl content which was found to be significantly increased. Reduced glutathione content and major glutathione metabolizing enzymes were also modulated signifying the role of glutathione redox cycle in the pathophysiology of TNPs. The study also includes the mitochondrial enzymes (Complex 1, Complex II, complex IV, Complex V ) and the enzymes showed toxicity in a relatively short time due to the effect of TNPs. The study provide a range of concentration that were toxic to the neuronal cells and data pointing to a general toxicity in brain mitochondria by TNPs, therefore, it is in need to consider the proper utilization of NPs in the environment.

Keywords: mitochondria, nanoparticles, brain, in vitro

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20788 Simultaneous versus Sequential Model in Foreign Entry

Authors: Patricia Heredia, Isabel Saz, Marta Fernández

Abstract:

This article proposes that the decision regarding exporting and the choice of export channel are nested and non-independent decisions. We assume that firms make two sequential decisions before arriving at their final choice: the decision to access foreign markets and the decision about the type of channel. This hierarchical perspective of the choices involved in the process is appealing for two reasons. First, it supports the idea that people have a limited analytical capacity. Managers often break down a complex decision into a hierarchical process because this makes it more manageable. Secondly, it recognizes that important differences exist between entry modes. In light of the above, the objective of this study is to test different entry mode choice processes: independent decisions and nested and non-independent decisions. To do this, the methodology estimates and compares the following two models: (i) a simultaneous single-stage model with three entry mode choices (using a multinomial logit model); ii) a two-stage model with the export decision preceding the channel decision using a sequential logit model. The study uses resource-based factors in determining these decision processes concerning internationalization and the study carries out empirical analysis using a DOC Rioja sample of 177 firms.Using the Akaike and Schwarz Information Criteria, the empirical evidence supports the existence of a nested structure, where the decision about exporting precedes the export mode decision. The implications and contributions of the findings are discussed.

Keywords: sequential logit model, two-stage choice process, export mode, wine industry

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20787 Probabilistic and Stochastic Analysis of a Retaining Wall for C-Φ Soil Backfill

Authors: André Luís Brasil Cavalcante, Juan Felix Rodriguez Rebolledo, Lucas Parreira de Faria Borges

Abstract:

A methodology for the probabilistic analysis of active earth pressure on retaining wall for c-Φ soil backfill is described in this paper. The Rosenblueth point estimate method is used to measure the failure probability of a gravity retaining wall. The basic principle of this methodology is to use two point estimates, i.e., the standard deviation and the mean value, to examine a variable in the safety analysis. The simplicity of this framework assures to its wide application. For the calculation is required 2ⁿ repetitions during the analysis, since the system is governed by n variables. In this study, a probabilistic model based on the Rosenblueth approach for the computation of the overturning probability of failure of a retaining wall is presented. The obtained results have shown the advantages of this kind of models in comparison with the deterministic solution. In a relatively easy way, the uncertainty on the wall and fill parameters are taken into account, and some practical results can be obtained for the retaining structure design.

Keywords: retaining wall, active earth pressure, backfill, probabilistic analysis

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20786 Hydraulic Analysis of Irrigation Approach Channel Using HEC-RAS Model

Authors: Muluegziabher Semagne Mekonnen

Abstract:

This study was intended to show the irrigation water requirements and evaluation of canal hydraulics steady state conditions to improve on scheme performance of the Meki-Ziway irrigation project. The methodology used was the CROPWAT 8.0 model to estimate the irrigation water requirements of five major crops irrigated in the study area. The results showed that for the whole existing and potential irrigation development area of 2000 ha and 2599 ha, crop water requirements were 3,339,200 and 4,339,090.4 m³, respectively. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. In this study Hydraulic Analysis of Irrigation Canals Using HEC-RAS Model was conducted in Meki-Ziway Irrigation Scheme. The HEC-RAS model was tested in terms of error estimation and used to determine canal capacity potential.

Keywords: HEC-RAS, irrigation, hydraulic. canal reach, capacity

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20785 Optimal Hedging of a Portfolio of European Options in an Extended Binomial Model under Proportional Transaction Costs

Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

Abstract:

Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

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20784 Proposing a Failure Criterion for Cohesionless Media Considering Cyclic Fabric Anisotropy

Authors: Ali Noorzad, Ehsan Badakhshan, Shima Zameni

Abstract:

The present paper is focused on a generalized failure criterion for geomaterials with cross-anisotropy. The cyclic behavior of granular material primarily depends on the nature and arrangement of constituent particles, particle size, and shape that affect fabric anisotropy. To account for the influence of loading directions on strength variations, an anisotropic variable in terms of the invariants of the stress tensor and fabric into the failure criterion is proposed. In an extension to original CANAsand constitutive model two concepts namely critical state and compact state play paramount roles as all of the moduli and coefficients are related to these states. The applicability of the present model is evaluated through comparisons between the predicted and the measured results. All simulations have demonstrated that the proposed constitutive model is capable of modeling the cyclic behavior of sand with inherent anisotropy.

Keywords: fabric, cohesionless media, cyclic loading, critical state, compact state, CANAsand constitutive model

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20783 Evaluation of Virtual Reality for the Rehabilitation of Athlete Lower Limb Musculoskeletal Injury: A Method for Obtaining Practitioner’s Viewpoints through Observation and Interview

Authors: Hannah K. M. Tang, Muhammad Ateeq, Mark J. Lake, Badr Abdullah, Frederic A. Bezombes

Abstract:

Based on a theoretical assessment of current literature, virtual reality (VR) could help to treat sporting injuries in a number of ways. However, it is important to obtain rehabilitation specialists’ perspectives in order to design, develop and validate suitable content for a VR application focused on treatment. Subsequently, a one-day observation and interview study focused on the use of VR for the treatment of lower limb musculoskeletal conditions in athletes was conducted at St George’s Park England National Football Centre with rehabilitation specialists. The current paper established the methods suitable for obtaining practitioner’s viewpoints through observation and interview in this context. Particular detail was provided regarding the method of qualitatively processing interview results using the qualitative data analysis software tool NVivo, in order to produce a narrative of overarching themes. The observations and overarching themes identified could be used as a framework and success criteria of a VR application developed in future research. In conclusion, this work explained the methods deemed suitable for obtaining practitioner’s viewpoints through observation and interview. This was required in order to highlight characteristics and features of a VR application designed to treat lower limb musculoskeletal injury of athletes and could be built upon to direct future work.

Keywords: athletes, lower-limb musculoskeletal injury, rehabilitation, return-to-sport, virtual reality

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20782 An Overview of Domain Models of Urban Quantitative Analysis

Authors: Mohan Li

Abstract:

Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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20781 D-Care: Diabetes Care Application to Enhance Diabetic Awareness to Diabetes in Indonesia

Authors: Samara R. Dania, Maulana S. Aji, Dewi Lestari

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Diabetes is a common disease in Indonesia. One of the risk factors of diabetes is an unhealthy diet which is consuming food that contains too much glucose, one of glucose sources presents in food containing carbohydrate. The purpose of this study is to identify the amount of glucose level in the consumed food. The authors use literature studies for this research method. For the results of this study, the authors expect diabetics to be more aware of diabetes by applying daily dietary regulation through D-Care. D-Care is an application that can enhance people awareness to diabetes in Indonesia. D-Care provides two menus; there are nutrition calculation and healthy food. Nutrition calculation menu is used for knowing estimated glucose intake level by calculating food that consumed each day. Whereas healthy food menu, it provides a combination of healthy food menu for diabetic. The conclusion is D-Care is useful to be used for reducing diabetes prevalence in Indonesia.

Keywords: D-Care, diabetes, awareness, healthy food

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20780 Effects of Aerodynamic on Suspended Cables Using Non-Linear Finite Element Approach

Authors: Justin Nwabanne, Sam Omenyi, Jeremiah Chukwuneke

Abstract:

This work presents structural nonlinear static analysis of a horizontal taut cable using Finite Element Analysis (FEA) method. The FEA was performed analytically to determine the tensions at each nodal point and subsequently, performed based on finite element displacement method computationally using the FEA software, ANSYS 14.0 to determine their behaviour under the influence of aerodynamic forces imposed on the cable. The convergence procedure is adapted into the method to prevent excessive displacements through the computations. The work compared the two FEA cases by examining the effectiveness of the analytical model in describing the response with few degrees of freedom and the ability of the nonlinear finite element procedure adopted to capture the complex features of cable dynamics with reference to the aerodynamic external influence. Results obtained from this work explain that the analytic FEM results without aerodynamic influence show a parabolic response with an optimum deflection at nodal points 12 and 13 with the cable weight at nodes 12 and 13 having the value -1.002936N while for the cable tension shows an optimum deflection value for nodes 12 and 13 at -189396.97kg/km. The maximum displacement for the cable system was obtained from ANSYS 14.0 as 4483.83 mm for X, Y and Z components of displacements at node number 2 while the maximum displacement obtained is 4218.75mm for all the directional components. The dynamic behaviour of a taut cable investigated has application in a typical power transmission line. Aerodynamic influences on the cables were considered using FEA approach by employing ANSYS 14.0 showed a complex modal behaviour as expected.

Keywords: aerodynamics, cable tension and weight, finite element analysis, nodal, non-linear model, optimum deflection, suspended cable, transmission line

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20779 Exploring the Activity Fabric of an Intelligent Environment with Hierarchical Hidden Markov Theory

Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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20778 Statistical Design of Central Point for Evaluate the Combination of PH and Cinnamon Essential Oil on the Antioxidant Activity Using the ABTS Technique

Authors: H. Minor-Pérez, A. M. Mota-Silva, S. Ortiz-Barrios

Abstract:

Substances of vegetable origin with antioxidant capacity have a high potential for application on the conservation of some foods, can prevent or reduce for example oxidation of lipids. However a food is a complex system whose wide variety of components wich can reduce or eliminate this antioxidant capacity. The antioxidant activity can be determined with the ABTS technique. The radical ABTS+ is generated from the acid 2, 2´ - Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). This radical is a composite color bluish-green, stable and with a spectrum of absorption into the UV-visible. The addition of antioxidants causes discoloration, value that can be reported as a percentage of inhibition of the cation radical ABTS+. The objective of this study was evaluated the effect of the combination of the pH and the essential oil of cinnamon (EOC) on inhibition of the radical ABTS+, using statistical design of central point (Design Expert) to obtain mathematical models that describe this phenomenon. Were evaluated 17 treatments with combinations of pH 5, 6 and 7 (citrate-phosphate buffer) and the concentration of essential oil of cinnamon (C): 0 µg/mL, 100 µg/mL and 200 µg/mL. The samples were analyzed using the ABTS technique. The reagent was dissolved in methanol 80% to standardized the absorbance to 0.7 +/- 0.1 at 754 nm. Then samples were mixed with reagent standardized ABTS and after 1 min and 7 min absorbance was read for each treatment at 754 nm. Was used a curve pattern with vitamin C and reported the values as inhibition (%) of radical ABTS+. The statistical analysis shows the experimental results were adjusted to a quadratic model, to the times of 1 min and 7 min. This model describes the influence of the factors investigated independently: pH and cinnamon essential oil (µg/mL) and the effect of the interaction between pH*C, as well as the square of the pH2 and C2. The model obtained was Y = 10.33684 - 3.98118*pH + 1.17031*C + 0.62745*pH2 - 3.26675*10-3*C2 - 0.013112*pH*C, where Y is the response variable. The coefficient of determination was 0.9949 for 1 min. The equation was obtained at 7 min and = - 10.89710 + 1.52341*pH + 1.32892*C + 0.47953*pH2 - 3.56605*10- *C2 - 0.034687*pH*C. The coefficient of determination was 0.9970. This means that only 1% of the total variation is not explained by the developed models. At 100 µg/mL of EOC was obtained an inhibition percentage of 80%, 84% and 97% for the pH values of 5,6 and 7 respectively, while a value of 200 µg/mL the inhibition (%) was very similar for the treatments. In these values of pH was obtained an inhibition close 97%. In conclusion the pH does not have a significant effect on the antioxidant capacity, while the concentration of EOC was decisive for the antioxidant capacity. The authors acknowledge the funding provided by the CONACYT for the project 131998.

Keywords: antioxidant activity, ABTS technique, essential oil of cinnamon, mathematical models

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20777 Leverage Effect for Volatility with Generalized Laplace Error

Authors: Farrukh Javed, Krzysztof Podgórski

Abstract:

We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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20776 The Role of Information and Communication Technology in Curbing Electoral Malpractices in Nigeria

Authors: Fred Fudah Moveh, Muhammad Abba Jallo

Abstract:

Electoral fraud remains a persistent threat to democracy in Nigeria, undermining public trust and stalling political development. This study explores the role of Information and Communication Technology (ICT) in curbing electoral fraud, focusing on its application in recent Nigerian elections. The paper identifies the main forms of electoral fraud, evaluates the effectiveness of ICT-based interventions like the Permanent Voter Card (PVC) and the Bi-modal Voter Accreditation System (BVAS), and discusses challenges such as poor infrastructure, voter intimidation, and legal inadequacies. Data was collected through structured questionnaires and interviews and analyzed using SPSS software. Results reveal that while ICT has mitigated some forms of fraud, systemic issues continue to hinder its full potential. The study concludes with recommendations for enhancing the application of ICT in Nigeria’s electoral process.

Keywords: ICT, electoral fraud, election process, Nigeria, political instability

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20775 Replicating Brain’s Resting State Functional Connectivity Network Using a Multi-Factor Hub-Based Model

Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

Abstract:

The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity

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20774 Application of Deep Learning in Colorization of LiDAR-Derived Intensity Images

Authors: Edgardo V. Gubatanga Jr., Mark Joshua Salvacion

Abstract:

Most aerial LiDAR systems have accompanying aerial cameras in order to capture not only the terrain of the surveyed area but also its true-color appearance. However, the presence of atmospheric clouds, poor lighting conditions, and aerial camera problems during an aerial survey may cause absence of aerial photographs. These leave areas having terrain information but lacking aerial photographs. Intensity images can be derived from LiDAR data but they are only grayscale images. A deep learning model is developed to create a complex function in a form of a deep neural network relating the pixel values of LiDAR-derived intensity images and true-color images. This complex function can then be used to predict the true-color images of a certain area using intensity images from LiDAR data. The predicted true-color images do not necessarily need to be accurate compared to the real world. They are only intended to look realistic so that they can be used as base maps.

Keywords: aerial LiDAR, colorization, deep learning, intensity images

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20773 From the Sharing Economy to Social Manufacturing: Analyzing Collaborative Service Networks in the Manufacturing Domain

Authors: Babak Mohajeri

Abstract:

In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.

Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development

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20772 Application of a Model-Free Artificial Neural Networks Approach for Structural Health Monitoring of the Old Lidingö Bridge

Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

Abstract:

Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

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20771 Volatility Model with Markov Regime Switching to Forecast Baht/USD

Authors: Nop Sopipan

Abstract:

In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.

Keywords: volatility, Markov Regime Switching, forecasting, Baht/USD

Procedia PDF Downloads 302