Search results for: loss model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19698

Search results for: loss model

16188 Effective Parameter Selection for Audio-Based Music Mood Classification for Christian Kokborok Song: A Regression-Based Approach

Authors: Sanchali Das, Swapan Debbarma

Abstract:

Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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16187 3D Building Model Utilizing Airborne LiDAR Dataset and Terrestrial Photographic Images

Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

Abstract:

The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

Procedia PDF Downloads 324
16186 The Impact of a Model's Skin Tone and Ethnic Identification on Consumer Decision Making

Authors: Shanika Y. Koreshi

Abstract:

Sri Lanka housed the lingerie product development and manufacturing subsidiary to renowned brands such as La Senza, Marks & Spencer, H&M, Etam, Lane Bryant, and George. Over the last few years, they have produced local brands such as Amante to cater to the local and regional customers. Past research has identified factors such as quality, price, and design to be vital when marketing lingerie to consumers. However, there has been minimum research that looks into the ethnically targeted market and skin colour within the Asian population. Therefore, the main aim of the research was to identify whether consumer preference for lingerie is influenced by the skin tone of the model wearing it. Moreover, the secondary aim was to investigate if the consumer preference for lingerie is influenced by the consumer’s ethnic identification with the skin tone of the model. An experimental design was used to explore the above aims. The participants constituted of 66 females residing in the western province of Sri Lanka and were gathered via convenience sampling. Six computerized images of a real model were used in the study, and her skin tone was digitally manipulated to express three different skin tones (light, tan and dark). Consumer preferences were measured through a ranking order scale that was constructed via a focus group discussion and ethnic identity was measured by the Multigroup Ethnic Identity Measure-Revised. Wilcoxon signed-rank test, Friedman test, and chi square test of independence were carried out using SPSS version 20. The results indicated that majority of the consumers ethnically identified and preferred the tan skin over the light and dark skin tones. The findings support the existing literature that states there is a preference among consumers when models have a medium skin tone over a lighter skin tone. The preference for a tan skin tone in a model is consistent with the ethnic identification of the Sri Lankan sample. The study implies that lingerie brands should consider the model's skin tones when marketing the brand to different ethnic backgrounds.

Keywords: consumer preference, ethnic identification, lingerie, skin tone

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16185 Projection of Solar Radiation for the Extreme South of Brazil

Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Rafael Haag, Elton Rossini

Abstract:

This work aims to validate and make the projections of solar energy for the Brazilian period from 2025 to 2100. As the plants designed by the HadGEM2-AO (Global Hadley Model 2 - Atmosphere) General Circulation Model UK Met Office Hadley Center, belonging to Phase 5 of the Intercomparison of Coupled Models (CMIP5). The simulation results of the model are compared with monthly data from 2006 to 2013, measured by a network of meteorological sections of the National Institute of Meteorology (INMET). The performance of HadGEM2-AO is evaluated by the efficiency coefficient (CEF) and bias. The results are shown in the table of maps and maps. HadGEM2-AO, in the most pessimistic scenario, RCP 8.5 had a very good accuracy, presenting efficiency coefficients between 0.94 and 0.98, the perfect setting being Solar radiation, which indicates a horizontal trend, is a climatic alternative for some regions of the Brazilian scenario, especially in spring.

Keywords: climate change, projections, solar radiation, scenarios climate change

Procedia PDF Downloads 154
16184 Mastering Digitization: A Quality-Adapted Digital Transformation Model

Authors: Franziska Schaefer, Marlene Kuhn, Heiner Otten

Abstract:

In the very near future, digitization will be the main challenge a company has to master to survive in a highly competitive market. Developing the right transformation strategy by considering all relevant aspects determines the success or failure of a company. Especially the digital focus on the customer plays a key role in creating sustainable competitive advantages, also leading to new tasks within the quality management. Therefore, quality management needs to be particularly addressed to support the upcoming digital change. In this paper, we present an analysis of existing digital transformation approaches and derive a transformation strategy from a quality management perspective. We identify and classify different transformation dimensions and assess their relevance to quality management tasks, resulting in a quality-adapted digital transformation model. Furthermore, we introduce applicable and customized quality management methods to support the presented digital transformation tasks. With our developed model we provide a digital transformation guideline from a quality perspective to master future disruptive changes.

Keywords: digital transformation, digitization, quality management, strategy

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16183 Development of a Robust Protein Classifier to Predict EMT Status of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Tumors

Authors: ZhenlinJu, Christopher P. Vellano, RehanAkbani, Yiling Lu, Gordon B. Mills

Abstract:

The epithelial–mesenchymal transition (EMT) is a process by which epithelial cells acquire mesenchymal characteristics, such as profound disruption of cell-cell junctions, loss of apical-basolateral polarity, and extensive reorganization of the actin cytoskeleton to induce cell motility and invasion. A hallmark of EMT is its capacity to promote metastasis, which is due in part to activation of several transcription factors and subsequent downregulation of E-cadherin. Unfortunately, current approaches have yet to uncover robust protein marker sets that can classify tumors as possessing strong EMT signatures. In this study, we utilize reverse phase protein array (RPPA) data and consensus clustering methods to successfully classify a subset of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tumors into an EMT protein signaling group (EMT group). The overall survival (OS) of patients in the EMT group is significantly worse than those in the other Hormone and PI3K/AKT signaling groups. In addition to a shrinkage and selection method for linear regression (LASSO), we applied training/test set and Monte Carlo resampling approaches to identify a set of protein markers that predicts the EMT status of CESC tumors. We fit a logistic model to these protein markers and developed a classifier, which was fixed in the training set and validated in the testing set. The classifier robustly predicted the EMT status of the testing set with an area under the curve (AUC) of 0.975 by Receiver Operating Characteristic (ROC) analysis. This method not only identifies a core set of proteins underlying an EMT signature in cervical cancer patients, but also provides a tool to examine protein predictors that drive molecular subtypes in other diseases.

Keywords: consensus clustering, TCGA CESC, Silhouette, Monte Carlo LASSO

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16182 Health Risk Assessment of Exposing to Benzene in Office Building around a Chemical Industry Based on Numerical Simulation

Authors: Majid Bayatian, Mohammadreza Ashouri

Abstract:

Releasing hazardous chemicals is one of the major problems for office buildings in the chemical industry and, therefore, environmental risks are inherent to these environments. The adverse health effects of the airborne concentration of benzene have been a matter of significant concern, especially in oil refineries. The chronic and acute adverse health effects caused by benzene exposure have attracted wide attention. Acute exposure to benzene through inhalation could cause headaches, dizziness, drowsiness, and irritation of the skin. Chronic exposures have reported causing aplastic anemia and leukemia at the occupational settings. Association between chronic occupational exposure to benzene and the development of aplastic anemia and leukemia were documented by several epidemiological studies. Numerous research works have investigated benzene emissions and determined benzene concentration at different locations of the refinery plant and stated considerable health risks. The high cost of industrial control measures requires justification through lifetime health risk assessment of exposed workers and the public. In the present study, a Computational Fluid Dynamics (CFD) model has been proposed to assess the exposure risk of office building around a refinery due to its release of benzene. For simulation, GAMBIT, FLUENT, and CFD Post software were used as pre-processor, processor, and post-processor, and the model was validated based on comparison with experimental results of benzene concentration and wind speed. Model validation results showed that the model is highly validated, and this model can be used for health risk assessment. The simulation and risk assessment results showed that benzene could be dispersion to an office building nearby, and the exposure risk has been unacceptable. According to the results of this study, a validated CFD model, could be very useful for decision-makers for control measures and possibly support them for emergency planning of probable accidents. Also, this model can be used to assess exposure to various types of accidents as well as other pollutants such as toluene, xylene, and ethylbenzene in different atmospheric conditions.

Keywords: health risk assessment, office building, Benzene, numerical simulation, CFD

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16181 Optimization of a Convolutional Neural Network for the Automated Diagnosis of Melanoma

Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

Abstract:

The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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16180 Liquid Waste Management in Cluster Development

Authors: Abheyjit Singh, Kulwant Singh

Abstract:

There is a gradual depletion of the water table in the earth's crust, and it is required to converse and reduce the scarcity of water. This is only done by rainwater harvesting, recycling of water and by judicially consumption/utilization of water and adopting unique treatment measures. Domestic waste is generated in residential areas, commercial settings, and institutions. Waste, in general, is unwanted, undesirable, and nevertheless an inevitable and inherent product of social, economic, and cultural life. In a cluster, a need-based system is formed where the project is designed for systematic analysis, collection of sewage from the cluster, treating it and then recycling it for multifarious work. The liquid waste may consist of Sanitary sewage/ Domestic waste, Industrial waste, Storm waste, or Mixed Waste. The sewage contains both suspended and dissolved particles, and the total amount of organic material is related to the strength of the sewage. The untreated domestic sanitary sewage has a BOD (Biochemical Oxygen Demand) of 200 mg/l. TSS (Total Suspended Solids) about 240 mg/l. Industrial Waste may have BOD and TSS values much higher than those of sanitary sewage. Another type of impurities of wastewater is plant nutrients, especially when there are compounds of nitrogen N phosphorus P in the sewage; raw sanitary contains approx. 35 mg/l Nitrogen and 10 mg/l of Phosphorus. Finally, the pathogen in the waste is expected to be proportional to the concentration of facial coliform bacteria. The coliform concentration in raw sanitary sewage is roughly 1 billion per liter. The system of sewage disposal technique has been universally applied to all conditions, which are the nature of soil formation, Availability of land, Quantity of Sewage to be disposed of, The degree of treatment and the relative cost of disposal technique. The adopted Thappar Model (India) has the following designed parameters consisting of a Screen Chamber, a Digestion Tank, a Skimming Tank, a Stabilization Tank, an Oxidation Pond and a Water Storage Pond. The screening Chamber is used to remove plastic and other solids, The Digestion Tank is designed as an anaerobic tank having a retention period of 8 hours, The Skimming Tank has an outlet that is kept 1 meter below the surface anaerobic condition at the bottom and also help in organic solid remover, Stabilization Tank is designed as primary settling tank, Oxidation Pond is a facultative pond having a depth of 1.5 meter, Storage Pond is designed as per the requirement. The cost of the Thappar model is Rs. 185 Lakh per 3,000 to 4,000 population, and the Area required is 1.5 Acre. The complete structure will linning as per the requirement. The annual maintenance will be Rs. 5 lakh per year. The project is useful for water conservation, silage water for irrigation, decrease of BOD and there will be no longer damage to community assets and economic loss to the farmer community by inundation. There will be a healthy and clean environment in the community.

Keywords: collection, treatment, utilization, economic

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16179 A Stochastic Model to Predict Earthquake Ground Motion Duration Recorded in Soft Soils Based on Nonlinear Regression

Authors: Issam Aouari, Abdelmalek Abdelhamid

Abstract:

For seismologists, the characterization of seismic demand should include the amplitude and duration of strong shaking in the system. The duration of ground shaking is one of the key parameters in earthquake resistant design of structures. This paper proposes a nonlinear statistical model to estimate earthquake ground motion duration in soft soils using multiple seismicity indicators. Three definitions of ground motion duration proposed by literature have been applied. With a comparative study, we select the most significant definition to use for predict the duration. A stochastic model is presented for the McCann and Shah Method using nonlinear regression analysis based on a data set for moment magnitude, source to site distance and site conditions. The data set applied is taken from PEER strong motion databank and contains shallow earthquakes from different regions in the world; America, Turkey, London, China, Italy, Chili, Mexico...etc. Main emphasis is placed on soft site condition. The predictive relationship has been developed based on 600 records and three input indicators. Results have been compared with others published models. It has been found that the proposed model can predict earthquake ground motion duration in soft soils for different regions and sites conditions.

Keywords: duration, earthquake, prediction, regression, soft soil

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16178 Towards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

Abstract:

Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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16177 Experimental and Computational Investigations of Baffle Position Effects on ‎the Performance of Oil and Water Separator Tanks

Authors: Haitham A. Hussein, Rozi Abdullah‏‎, Md Azlin Md Said ‎

Abstract:

Gravity separator tanks are used to separate oil from water in treatment units. Achieving the best flow ‎uniformity in a separator tank will improve the maximum removal efficiency of oil globules from water. ‎In this study, the effect on hydraulic performance of different baffle structure positions inside a tank ‎was investigated. Experimental data and 2D computation fluid dynamics were used for analysis. In the ‎numerical model, two-phase flow (drift flux model) was used to validate one-phase flow. For ‎laboratory measurements, the velocity fields were measured using an acoustic Doppler velocimeter. The ‎measurements were compared with the result of the computational model. The results of the ‎experimental and computational simulations indicate that the best location of a baffle structure is ‎achieved when the standard deviation of the velocity profile and the volume of the circulation zone ‎inside the tank are minimized.‎

Keywords: gravity separator tanks, CFD, baffle position, two phase flow, ADV, oil droplet

Procedia PDF Downloads 337
16176 Association between Single Nucleotide Polymorphism of Calpain1 Gene and Meat Tenderness Traits in Different Genotypes of Chicken: Malaysian Native and Commercial Broiler Line

Authors: Abtehal Y. Anaas, Mohd. Nazmi Bin Abd. Manap

Abstract:

Meat Tenderness is one of the most important factors affecting consumers' assessment of meat quality. Variation in meat tenderness is genetically controlled and varies among breeds, and it is also influenced by environmental factors that can affect its creation during rigor mortis and postmortem. The final postmortem meat tenderization relies on the extent of proteolysis of myofibrillar proteins caused by the endogenous activity of the proteolytic calpain system. This calpain system includes different calcium-dependent cysteine proteases, and an inhibitor, calpastatin. It is widely accepted that in farm animals including chickens, the μ-calpain gene (CAPN1) is a physiological candidate gene for meat tenderness. This study aimed to identify the association of single nucleotide polymorphism (SNP) markers in the CAPN1 gene with the tenderness of chicken breast meat from two Malaysian native and commercial broiler breed crosses. Ten, five months old native chickens and ten, 42 days commercial broilers were collected from the local market and breast muscles were removed two hours after slaughter, packed separately in plastic bags and kept at -20ºC for 24 h. The tenderness phenotype for all chickens’ breast meats was determined by Warner-Bratzler Shear Force (WBSF). Thawing and cooking losses were also measured in the same breast samples before using in WBSF determination. Polymerase chain reaction (PCR) was used to identify the previously reported C7198A and G9950A SNPs in the CAPN1 gene and assess their associations with meat tenderness in the two breeds. The broiler breast meat showed lower shear force values and lower thawing loss rates than the native chickens (p<0.05), whereas there were similar in the rates of cooking loss. The study confirms some previous results that the markers CAPN1 C7198A and G9950A were not significantly associated with the variation in meat tenderness in chickens. Therefore, further study is needed to confirm the functional molecular mechanism of these SNPs and evaluate their associations in different chicken populations.

Keywords: CAPNl, chicken, meat tenderness, meat quality, SNPs

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16175 Numerical Simulation of Three-Dimensional Cavitating Turbulent Flow in Francis Turbines with ANSYS

Authors: Raza Abdulla Saeed

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In this study, the three-dimensional cavitating turbulent flow in a complete Francis turbine is simulated using mixture model for cavity/liquid two-phase flows. Numerical analysis is carried out using ANSYS CFX software release 12, and standard k-ε turbulence model is adopted for this analysis. The computational fluid domain consist of spiral casing, stay vanes, guide vanes, runner and draft tube. The computational domain is discretized with a three-dimensional mesh system of unstructured tetrahedron mesh. The finite volume method (FVM) is used to solve the governing equations of the mixture model. Results of cavitation on the runner’s blades under three different boundary conditions are presented and discussed. From the numerical results it has been found that the numerical method was successfully applied to simulate the cavitating two-phase turbulent flow through a Francis turbine, and also cavitation is clearly predicted in the form of water vapor formation inside the turbine. By comparison the numerical prediction results with a real runner; it’s shown that the region of higher volume fraction obtained by simulation is consistent with the region of runner cavitation damage.

Keywords: computational fluid dynamics, hydraulic francis turbine, numerical simulation, two-phase mixture cavitation model

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16174 Seismic Behavior of Pile-Supported Bridges Considering Soil-Structure Interaction and Structural Non-Linearity

Authors: Muhammad Tariq A. Chaudhary

Abstract:

Soil-structure interaction (SSI) in bridges under seismic excitation is a complex phenomenon which involves coupling between the non-linear behavior of bridge pier columns and SSI in the soil-foundation part. It is a common practice in the study of SSI to model the bridge piers as linear elastic while treating the soil and foundation with a non-linear or an equivalent linear modeling approach. Consequently, the contribution of soil and foundation to the SSI phenomenon is disproportionately highlighted. The present study considered non-linear behavior of bridge piers in FEM model of a 4-span, pile-supported bridge that was designed for five different soil conditions in a moderate seismic zone. The FEM model of the bridge system was subjected to a suite of 21 actual ground motions representative of three levels of earthquake hazard (i.e. Design Basis Earthquake, Functional Evaluation Earthquake and Maximum Considered Earthquake). Results of the FEM analysis were used to delineate the influence of pier column non-linearity and SSI on critical design parameters of the bridge system. It was found that pier column non-linearity influenced the bridge lateral displacement and base shear more than SSI for majority of the analysis cases for the class of bridge investigated in the study.

Keywords: bridge, FEM model, reinforced concrete pier, pile foundation, seismic loading, soil-structure interaction

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16173 Mitigation of Cascading Power Outage Caused Power Swing Disturbance Using Real-time DLR Applications

Authors: Dejenie Birile Gemeda, Wilhelm Stork

Abstract:

The power system is one of the most important systems in modern society. The existing power system is approaching the critical operating limits as views of several power system operators. With the increase of load demand, high capacity and long transmission networks are widely used to meet the requirement. With the integration of renewable energies such as wind and solar, the uncertainty, intermittence bring bigger challenges to the operation of power systems. These dynamic uncertainties in the power system lead to power disturbances. The disturbances in a heavily stressed power system cause distance relays to mal-operation or false alarms during post fault power oscillations. This unintended operation of these relays may propagate and trigger cascaded trappings leading to total power system blackout. This is due to relays inability to take an appropriate tripping decision based on ensuing power swing. According to the N-1 criterion, electric power systems are generally designed to withstand a single failure without causing the violation of any operating limit. As a result, some overloaded components such as overhead transmission lines can still work for several hours under overload conditions. However, when a large power swing happens in the power system, the settings of the distance relay of zone 3 may trip the transmission line with a short time delay, and they will be acting so quickly that the system operator has no time to respond and stop the cascading. Misfiring of relays in absence of fault due to power swing may have a significant loss in economic performance, thus a loss in revenue for power companies. This research paper proposes a method to distinguish stable power swing from unstable using dynamic line rating (DLR) in response to power swing or disturbances. As opposed to static line rating (SLR), dynamic line rating support effective mitigation actions against propagating cascading outages in a power grid. Effective utilization of existing transmission lines capacity using machine learning DLR predictions will improve the operating point of distance relay protection, thus reducing unintended power outages due to power swing.

Keywords: blackout, cascading outages, dynamic line rating, power swing, overhead transmission lines

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16172 Using Confirmatory Factor Analysis to Test the Dimensional Structure of Tourism Service Quality

Authors: Ibrahim A. Elshaer, Alaa M. Shaker

Abstract:

Several previous empirical studies have operationalized service quality as either a multidimensional or unidimensional construct. While few earlier studies investigated some practices of the assumed dimensional structure of service quality, no study has been found to have tested the construct’s dimensionality using confirmatory factor analysis (CFA). To gain a better insight into the dimensional structure of service quality construct, this paper tests its dimensionality using three CFA models (higher order factor model, oblique factor model, and one factor model) on a set of data collected from 390 British tourists visited Egypt. The results of the three tests models indicate that service quality construct is multidimensional. This result helps resolving the problems that might arise from the lack of clarity concerning the dimensional structure of service quality, as without testing the dimensional structure of a measure, researchers cannot assume that the significant correlation is a result of factors measuring the same construct.

Keywords: service quality, dimensionality, confirmatory factor analysis, Egypt

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16171 Multidisciplinary Approach for a Tsunami Reconstruction Plan in Coquimbo, Chile

Authors: Ileen Van den Berg, Reinier J. Daals, Chris E. M. Heuberger, Sven P. Hildering, Bob E. Van Maris, Carla M. Smulders, Rafael Aránguiz

Abstract:

Chile is located along the subduction zone of the Nazca plate beneath the South American plate, where large earthquakes and tsunamis have taken place throughout history. The last significant earthquake (Mw 8.2) occurred in September 2015 and generated a destructive tsunami, which mainly affected the city of Coquimbo (71.33°W, 29.96°S). The inundation area consisted of a beach, damaged seawall, damaged railway, wetland and old neighborhood; therefore, local authorities started a reconstruction process immediately after the event. Moreover, a seismic gap has been identified in the same area, and another large event could take place in the near future. The present work proposed an integrated tsunami reconstruction plan for the city of Coquimbo that considered several variables such as safety, nature & recreation, neighborhood welfare, visual obstruction, infrastructure, construction process, and durability & maintenance. Possible future tsunami scenarios are simulated by means of the Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) model with 5 nested grids and a higher grid resolution of ~10 m. Based on the score from a multi-criteria analysis, the costs of the alternatives and a preference for a multifunctional solution, the alternative that includes an elevated coastal road with floodgates to reduce tsunami overtopping and control the return flow of a tsunami was selected as the best solution. It was also observed that the wetlands are significantly restored to their former configuration; moreover, the dynamic behavior of the wetlands is stimulated. The numerical simulation showed that the new coastal protection decreases damage and the probability of loss of life by delaying tsunami arrival time. In addition, new evacuation routes and a smaller inundation zone in the city increase safety for the area.

Keywords: tsunami, Coquimbo, Chile, reconstruction, numerical simulation

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16170 Effective Validation Model and Use of Mobile-Health Apps for Elderly People

Authors: Leonardo Ramirez Lopez, Edward Guillen Pinto, Carlos Ramos Linares

Abstract:

The controversy brought about by the increasing use of mHealth apps and their effectiveness for disease prevention and diagnosis calls for immediate control. Although a critical topic in research areas such as medicine, engineering, economics, among others, this issue lacks reliable implementation models. However, projects such as Open Web Application Security Project (OWASP) and various studies have helped to create useful and reliable apps. This research is conducted under a quality model to optimize two mHealth apps for older adults. Results analysis on the use of two physical activity monitoring apps - AcTiv (physical activity) and SMCa (energy expenditure) - is positive and ideal. Through a theoretical and practical analysis, precision calculations and personal information control of older adults for disease prevention and diagnosis were performed. Finally, apps are validated by a physician and, as a result, they may be used as health monitoring tools in physical performance centers or any other physical activity. The results obtained provide an effective validation model for this type of mobile apps, which, in turn, may be applied by other software developers that along with medical staff would offer digital healthcare tools for elderly people.

Keywords: model, validation, effective, healthcare, elderly people, mobile app

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16169 Authoring of Augmented Reality Manuals for Not Physically Available Products

Authors: Vito M. Manghisi, Michele Gattullo, Alessandro Evangelista, Enricoandrea Laviola

Abstract:

In this work, we compared two solutions for displaying a demo version of an Augmented Reality (AR) manual when the real product is not available, opting to replace it with its computer-aided design (CAD) model. AR has been proved to be effective in maintenance and assembly operations by many studies in the literature. However, most of them present solutions for existing products, usually converting old, printed manuals into AR manuals. In this case, authoring consists of defining how to convey existing instructions through AR. It is not a simple choice, and demo versions are created to test the design goodness. However, this becomes impossible when the product is not physically available, as for new products. A solution could be creating an entirely virtual environment with the product and the instructions. However, in this way, user interaction is completely different from that in the real application, then it would be hard testing the usability of the AR manual. This work aims to propose and compare two different solutions for the displaying of a demo version of an AR manual to support authoring in case of a product that is not physically available. We used as a case study that of an innovative semi-hermetic compressor that has not yet been produced. The applications were developed for a handheld device, using Unity 3D. The main issue was how to show the compressor and attach instructions on it. In one approach, we used Vuforia natural feature tracking to attach a CAD model of the compressor to a 2D image that is a drawing in scale 1:1 of the top-view of the CAD model. In this way, during the AR manual demonstration, the 3D model of the compressor is displayed on the user's device in place of the real compressor, and all the virtual instructions are attached to it. In the other approach, we first created a support application that shows the CAD model of the compressor on a marker. Then, we registered a video of this application, moving around the marker, obtaining a video that shows the CAD model from every point of view. For the AR manual, we used the Vuforia model target (360° option) to track the CAD model of the compressor, as it was the real compressor. Then, during the demonstration, the video is shown on a fixed large screen, and instructions are displayed attached to it in the AR manual. The first solution presents the main drawback to keeping the printed image with everyone working on the authoring of the AR manual, but allows to show the product in a real scale and interaction during the demonstration is very simple. The second one does not need a printed marker during the demonstration but a screen. Still, the compressor model is resized, and interaction is awkward since the user has to play the video on the screen to rotate the compressor. The two solutions were evaluated together with the company, and the preferred was the first one due to a more natural interaction.

Keywords: augmented reality, human computer interaction, operating instructions, maintenance, assembly

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16168 Investigation and Comprehensive Benefit Analysis of 11 Typical Polar-Based Agroforestry Models Based on Analytic Hierarchy Process in Anhui Province, Eastern China

Authors: Zhihua Cao, Hongfei Zhao, Zhongneng Wu

Abstract:

The development of polar-based agroforestry was necessary due to the influence of the timber market environment in China, which can promote the coordinated development of forestry and agriculture, and gain remarkable ecological, economic and social benefits. The main agroforestry models of the main poplar planting area in Huaibei plain and along the Yangtze River plain were carried out. 11 typical management models of poplar were selected to sum up: pure poplar forest, poplar-rape-soybean, poplar-wheat-soybean, poplar-rape-cotton, poplar-wheat, poplar-chicken, poplar-duck, poplar-sheep, poplar-Agaricus blazei, poplar-oil peony, poplar-fish, represented by M0-M10, respectively. 12 indexes related with economic, ecological and social benefits (annual average cost, net income, ratio of output to investment, payback period of investment, land utilization ratio, utilization ratio of light energy, improvement and system stability of ecological and production environment, product richness, labor capacity, cultural quality of labor force, sustainability) were screened out to carry on the comprehensive evaluation and analysis to 11 kinds of typical agroforestry models based on analytic hierarchy process (AHP). The results showed that the economic benefit of each agroforestry model was in the order of: M8 > M6 > M9 > M7 > M5 > M10 > M4 > M1 > M2 > M3 > M0. The economic benefit of poplar-A. blazei model was the highest (332, 800 RMB / hm²), followed by poplar-duck and poplar-oil peony model (109, 820RMB /hm², 5, 7226 RMB /hm²). The order of comprehensive benefit was: M8 > M4 > M9 > M6 > M1 > M2 > M3 > M7 > M5 > M10 > M0. The economic benefit and comprehensive benefit of each agroforestry model were higher than that of pure poplar forest. The comprehensive benefit of poplar-A. blazei model was the highest, and that of poplar-wheat model ranked second, while its economic benefit was not high. Next were poplar-oil peony and poplar-duck models. It was suggested that the model of poplar-wheat should be adopted in the plain along the Yangtze River, and the whole cycle mode of poplar-grain, popalr-A. blazei, or poplar-oil peony should be adopted in Huaibei plain, northern Anhui. Furthermore, wheat, rape, and soybean are the main crops before the stand was closed; the agroforestry model of edible fungus or Chinese herbal medicine can be carried out when the stand was closed in order to maximize the comprehensive benefit. The purpose of this paper is to provide a reference for forest farmers in the selection of poplar agroforestry model in the future and to provide the basic data for the sustainable and efficient study of poplar agroforestry in Anhui province, eastern China.

Keywords: agroforestry, analytic hierarchy process (AHP), comprehensive benefit, model, poplar

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16167 Manufacturing of Vacuum Glazing with Metal Edge Seal

Authors: Won Kyeong Kang, Tae-Ho Song

Abstract:

Vacuum glazing (VG) is a super insulator, which is able to greatly improve the energy efficiency of building. However, a significant amount of heat loss occurs through the welded edge of conventional VG. The joining method should be improved for further application and commercialization. For this purpose VG with metal edge seal is conceived. In this paper, the feasibility of joining stainless steel and soda lime glass using glass solder is assessed numerically and experimentally. In the case of very thin stainless steel, partial joining with glass is identified, which need further improvement for practical application.

Keywords: VG, metal edge seal, vacuum glazing, manufacturing,

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16166 Talent-Priority: Exploring the Human Resource Reengineering Model in Digital Transformation of a Benchmark Company

Authors: Hsiu Hua Hu

Abstract:

Digital transformation has widely affected various industries. It provides technological innovation, process redesign, new business model construction, and talent value creation. This transformation not only allows organizations to obtain and deploy specific technologies and methods suitable for organizational reengineering but also is an important way to solve management problems in human resource (HR) reengineering, business efficiency, and process redesign. In this study, we present the results of a qualitative study that offers insight into a series of key feature of reengineering related to the digital transformation and how to create talent value when the companies successfully perform digital transformation and human resource reengineering, which is led by business digitalization strategies including talent planning, talent acquisition, talent adjustment, and talent development. Drawing from the qualitative investigation findings, we built an inductive model of HR reengineering, which aims to provide research and practical references on future digital transformation and management inquiry.

Keywords: talent value creation, digital transformation, HR reengineering, qualitative study

Procedia PDF Downloads 161
16165 Network Traffic Classification Scheme for Internet Network Based on Application Categorization for Ipv6

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 568
16164 Modeling and Mapping of Soil Erosion Risk Using Geographic Information Systems, Remote Sensing, and Deep Learning Algorithms: Case of the Oued Mikkes Watershed, Morocco

Authors: My Hachem Aouragh, Hind Ragragui, Abdellah El-Hmaidi, Ali Essahlaoui, Abdelhadi El Ouali

Abstract:

This study investigates soil erosion susceptibility in the Oued Mikkes watershed, located in the Meknes-Fez region of northern Morocco, utilizing advanced techniques such as deep learning algorithms and remote sensing integrated within Geographic Information Systems (GIS). Spanning approximately 1,920 km², the watershed is characterized by a semi-arid Mediterranean climate with irregular rainfall and limited water resources. The waterways within the watershed, especially the Oued Mikkes, are vital for agricultural irrigation and potable water supply. The research assesses the extent of erosion risk upstream of the Sidi Chahed dam while developing a spatial model of soil loss. Several important factors, including topography, land use/land cover, and climate, were analyzed, with data on slope, NDVI, and rainfall erosivity processed using deep learning models (DLNN, CNN, RNN). The results demonstrated excellent predictive performance, with AUC values of 0.92, 0.90, and 0.88 for DLNN, CNN, and RNN, respectively. The resulting susceptibility maps provide critical insights for soil management and conservation strategies, identifying regions at high risk for erosion across 24% of the study area. The most high-risk areas are concentrated on steep slopes, particularly near the Ifrane district and the surrounding mountains, while low-risk areas are located in flatter regions with less rugged topography. The combined use of remote sensing and deep learning offers a powerful tool for accurate erosion risk assessment and resource management in the Mikkes watershed, highlighting the implications of soil erosion on dam siltation and operational efficiency.

Keywords: soil erosion, GIS, remote sensing, deep learning, Mikkes Watershed, Morocco

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16163 Method for Tuning Level Control Loops Based on Internal Model Control and Closed Loop Step Test Data

Authors: Arnaud Nougues

Abstract:

This paper describes a two-stage methodology derived from internal model control (IMC) for tuning a proportional-integral-derivative (PID) controller for levels or other integrating processes in an industrial environment. Focus is the ease of use and implementation speed which are critical for an industrial application. Tuning can be done with minimum effort and without the need for time-consuming open-loop step tests on the plant. The first stage of the method applies to levels only: the vessel residence time is calculated from equipment dimensions and used to derive a set of preliminary proportional-integral (PI) settings with IMC. The second stage, re-tuning in closed-loop, applies to levels as well as other integrating processes: a tuning correction mechanism has been developed based on a series of closed-loop simulations with model errors. The tuning correction is done from a simple closed-loop step test and the application of a generic correlation between observed overshoot and integral time correction. A spin-off of the method is that an estimate of the vessel residence time (levels) or open-loop process gain (other integrating process) is obtained from the closed-loop data.

Keywords: closed-loop model identification, IMC-PID tuning method, integrating process control, on-line PID tuning adaptation

Procedia PDF Downloads 227
16162 Evaluating the Validity of CFD Model of Dispersion in a Complex Urban Geometry Using Two Sets of Experimental Measurements

Authors: Mohammad R. Kavian Nezhad, Carlos F. Lange, Brian A. Fleck

Abstract:

This research presents the validation study of a computational fluid dynamics (CFD) model developed to simulate the scalar dispersion emitted from rooftop sources around the buildings at the University of Alberta North Campus. The ANSYS CFX code was used to perform the numerical simulation of the wind regime and pollutant dispersion by solving the 3D steady Reynolds-averaged Navier-Stokes (RANS) equations on a building-scale high-resolution grid. The validation study was performed in two steps. First, the CFD model performance in 24 cases (eight wind directions and three wind speeds) was evaluated by comparing the predicted flow fields with the available data from the previous measurement campaign designed at the North Campus, using the standard deviation method (SDM), while the estimated results of the numerical model showed maximum average percent errors of approximately 53% and 37% for wind incidents from the North and Northwest, respectively. Good agreement with the measurements was observed for the other six directions, with an average error of less than 30%. In the second step, the reliability of the implemented turbulence model, numerical algorithm, modeling techniques, and the grid generation scheme was further evaluated using the Mock Urban Setting Test (MUST) dispersion dataset. Different statistical measures, including the fractional bias (FB), the geometric mean bias (MG), and the normalized mean square error (NMSE), were used to assess the accuracy of the predicted dispersion field. Our CFD results are in very good agreement with the field measurements.

Keywords: CFD, plume dispersion, complex urban geometry, validation study, wind flow

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16161 Identity Verification Based on Multimodal Machine Learning on Red Green Blue (RGB) Red Green Blue-Depth (RGB-D) Voice Data

Authors: LuoJiaoyang, Yu Hongyang

Abstract:

In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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16160 Breast Cancer Incidence Estimation in Castilla-La Mancha (CLM) from Mortality and Survival Data

Authors: C. Romero, R. Ortega, P. Sánchez-Camacho, P. Aguilar, V. Segur, J. Ruiz, G. Gutiérrez

Abstract:

Introduction: Breast cancer is a leading cause of death in CLM. (2.8% of all deaths in women and 13,8% of deaths from tumors in womens). It is the most tumor incidence in CLM region with 26.1% from all tumours, except nonmelanoma skin (Cancer Incidence in Five Continents, Volume X, IARC). Cancer registries are a good information source to estimate cancer incidence, however the data are usually available with a lag which makes difficult their use for health managers. By contrast, mortality and survival statistics have less delay. In order to serve for resource planning and responding to this problem, a method is presented to estimate the incidence of mortality and survival data. Objectives: To estimate the incidence of breast cancer by age group in CLM in the period 1991-2013. Comparing the data obtained from the model with current incidence data. Sources: Annual number of women by single ages (National Statistics Institute). Annual number of deaths by all causes and breast cancer. (Mortality Registry CLM). The Breast cancer relative survival probability. (EUROCARE, Spanish registries data). Methods: A Weibull Parametric survival model from EUROCARE data is obtained. From the model of survival, the population and population data, Mortality and Incidence Analysis MODel (MIAMOD) regression model is obtained to estimate the incidence of cancer by age (1991-2013). Results: The resulting model is: Ix,t = Logit [const + age1*x + age2*x2 + coh1*(t – x) + coh2*(t-x)2] Where: Ix,t is the incidence at age x in the period (year) t; the value of the parameter estimates is: const (constant term in the model) = -7.03; age1 = 3.31; age2 = -1.10; coh1 = 0.61 and coh2 = -0.12. It is estimated that in 1991 were diagnosed in CLM 662 cases of breast cancer (81.51 per 100,000 women). An estimated 1,152 cases (112.41 per 100,000 women) were diagnosed in 2013, representing an increase of 40.7% in gross incidence rate (1.9% per year). The annual average increases in incidence by age were: 2.07% in women aged 25-44 years, 1.01% (45-54 years), 1.11% (55-64 years) and 1.24% (65-74 years). Cancer registries in Spain that send data to IARC declared 2003-2007 the average annual incidence rate of 98.6 cases per 100,000 women. Our model can obtain an incidence of 100.7 cases per 100,000 women. Conclusions: A sharp and steady increase in the incidence of breast cancer in the period 1991-2013 is observed. The increase was seen in all age groups considered, although it seems more pronounced in young women (25-44 years). With this method you can get a good estimation of the incidence.

Keywords: breast cancer, incidence, cancer registries, castilla-la mancha

Procedia PDF Downloads 313
16159 A Novel Design of a Low Cost Wideband Wilkinson Power Divider

Authors: A. Sardi, J. Zbitou, A. Errkik, L. El Abdellaoui, A. Tajmouati, M. Latrach

Abstract:

This paper presents analysis and design of a wideband Wilkinson power divider for wireless applications. The design is accomplished by transforming the lengths and impedances of the quarter wavelength sections of the conventional Wilkinson power divider into U-shaped sections. The designed power divider is simulated by using ADS Agilent technologies and CST microwave studio software. It is shown that the proposed power divider has simple topology and good performances in terms of insertion loss, port matching and isolation at all operating frequencies (1.8 GHz, 2.45 GHz and 3.55 GHz).

Keywords: ADS agilent technologies, CST microwave studio, microstrip, wideband, wilkinson power divider

Procedia PDF Downloads 373