Search results for: sport services model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19850

Search results for: sport services model

16670 Effect of Outliers in Assessing Significant Wave Heights Through a Time-Dependent GEV Model

Authors: F. Calderón-Vega, A. D. García-Soto, C. Mösso

Abstract:

Recorded significant wave heights sometimes exhibit large uncommon values (outliers) that can be associated with extreme phenomena such as hurricanes and cold fronts. In this study, some extremely large wave heights recorded in NOAA buoys (National Data Buoy Center, noaa.gov) are used to investigate their effect in the prediction of future wave heights associated with given return periods. Extreme waves are predicted through a time-dependent model based on the so-called generalized extreme value distribution. It is found that the outliers do affect the estimated wave heights. It is concluded that a detailed inspection of outliers is envisaged to determine whether they are real recorded values since this will impact defining design wave heights for coastal protection purposes.

Keywords: GEV model, non-stationary, seasonality, outliers

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16669 Exchange Rate Forecasting by Econometric Models

Authors: Zahid Ahmad, Nosheen Imran, Nauman Ali, Farah Amir

Abstract:

The objective of the study is to forecast the US Dollar and Pak Rupee exchange rate by using time series models. For this purpose, daily exchange rates of US and Pakistan for the period of January 01, 2007 - June 2, 2017, are employed. The data set is divided into in sample and out of sample data set where in-sample data are used to estimate as well as forecast the models, whereas out-of-sample data set is exercised to forecast the exchange rate. The ADF test and PP test are used to make the time series stationary. To forecast the exchange rate ARIMA model and GARCH model are applied. Among the different Autoregressive Integrated Moving Average (ARIMA) models best model is selected on the basis of selection criteria. Due to the volatility clustering and ARCH effect the GARCH (1, 1) is also applied. Results of analysis showed that ARIMA (0, 1, 1 ) and GARCH (1, 1) are the most suitable models to forecast the future exchange rate. Further the GARCH (1,1) model provided the volatility with non-constant conditional variance in the exchange rate with good forecasting performance. This study is very useful for researchers, policymakers, and businesses for making decisions through accurate and timely forecasting of the exchange rate and helps them in devising their policies.

Keywords: exchange rate, ARIMA, GARCH, PAK/USD

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16668 Organizational Commitment in Islamic Boarding School: The Implementation of Organizational Behavior Integrative Model

Authors: Siswoyo Haryono

Abstract:

Purpose – The fundamental goal of this research is to see if the integrative organizational behavior model can be used effectively in Islamic boarding schools. This paper also seeks to assess the effect of Islamic organizational culture, leadership, and spiritual intelligence on teachers' organizational commitment to Islamic Boarding schools. The goal of the mediation analysis is to see if the Islamic work ethic has a more significant effect on the instructors' organizational commitment than the direct effects of Islamic organizational culture, leadership, and Islamic spiritual intelligence. Design/methodology/approach – A questionnaire survey was used to obtain data from teachers at Islamic Boarding Schools. This study used the AMOS technique for structural equation modeling to evaluate the expected direct effect. To test the hypothesized indirect effect, employed Sobel test. Findings – Islamic organizational culture, Islamic leadership, and Islamic spiritual intelligence significantly affect Islamic work ethic. When it comes to Islamic corporate culture, Islamic leadership, Islamic spiritual intelligence, and Islamic work ethics have a significant impact. The findings of the mediation study reveal that Islamic organizational culture, leadership, and spiritual intelligence influences organizational commitment through Islamic work ethic. The total effect analysis shows that the most effective path to increasing teachers’ organizational commitment is Islamic leadership - Islamic work ethic – organizational commitment. Originality/value – This study evaluates the Integrative Model of Organizational Behavior by Colquitt (2016) applied in Islamic Boarding School. The model consists of contemporary leadership and individual characteristic as the antecedent. The mediating variables of the model consist of individual mechanisms such as trust, justice, and ethic. Individual performance and organizational commitment are the model's outcomes. These variables, on the other hand, do not represent the Islamic viewpoint as a whole. As a result, this study aims to assess the role of Islamic principles in the model. The study employs reliability and validity tests to get reliable and valid measures. The findings revealed that the evaluation model is proven to improve organizational commitment at Islamic Boarding School.

Keywords: Islamic leadership, Islamic spiritual intelligence, Islamic work ethic, organizational commitment, Islamic boarding school

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16667 Assessment of Hydrologic Response of a Naturalized Tropical Coastal Mangrove Ecosystem Due to Land Cover Change in an Urban Watershed

Authors: Bryan Clark B. Hernandez, Eugene C. Herrera, Kazuo Nadaoka

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Mangrove forests thriving in intertidal zones in tropical and subtropical regions of the world offer a range of ecosystem services including carbon storage and sequestration. They can regulate the detrimental effects of climate change due to carbon releases two to four times greater than that of mature tropical rainforests. Moreover, they are effective natural defenses against storm surges and tsunamis. However, their proliferation depends significantly on the prevailing hydroperiod at the coast. In the Philippines, these coastal ecosystems have been severely threatened with a 50% decline in areal extent observed from 1918 to 2010. The highest decline occurred in 1950 - 1972 when national policies encouraged the development of fisheries and aquaculture. With the intensive land use conversion upstream, changes in the freshwater-saltwater envelope at the coast may considerably impact mangrove growth conditions. This study investigates a developing urban watershed in Kalibo, Aklan province with a 220-hectare mangrove forest replanted for over 30 years from coastal mudflats. Since then, the mangrove forest was sustainably conserved and declared as protected areas. Hybrid land cover classification technique was used to classify Landsat images for years, 1990, 2010, and 2017. Digital elevation model utilized was Interferometric Synthetic Aperture Radar (IFSAR) with a 5-meter resolution to delineate the watersheds. Using numerical modelling techniques, the hydrologic and hydraulic analysis of the influence of land cover change to flow and sediment dynamics was simulated. While significant land cover change occurred upland, thereby increasing runoff and sediment loads, the mangrove forests abundance adjacent to the coasts for the urban watershed, was somehow sustained. However, significant alteration of the coastline was observed in Kalibo through the years, probably due to the massive land-use conversion upstream and significant replanting of mangroves downstream. Understanding the hydrologic-hydraulic response of these watersheds to change land cover is essential to helping local government and stakeholders facilitate better management of these mangrove ecosystems.

Keywords: coastal mangroves, hydrologic model, land cover change, Philippines

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16666 The Best Prediction Data Mining Model for Breast Cancer Probability in Women Residents in Kabul

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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16665 The Patterns Designation by the Inspiration from Flower at Suan Sunandha Palace

Authors: Nawaporn Srisarankullawong

Abstract:

This research is about the creating the design by the inspiration of the flowers, which were once planted in Suan Sunandha Palace. The researcher have conducted the research regarding the history of Suan Sunandha Palace and the flowers which have been planted in the palace’s garden, in order to use this research to create the new designs in the future. The objective are as follows; 1. To study the shape and the pattern of the flowers in Suan Sunandha Palace, in order to select a few of them as the model to create the new design. 2. In order to create the flower design from the flowers in Suan Sunandha Palace by using the current photograph of the flowers which were once used to be planted inside the palace and using adobe Illustrator and Adobe Photoshop programs to create the patterns and the model. The result of the research: From the research, the researcher had selected three types of flowers to crate the pattern model; they are Allamanda, Orchids and Flamingo Plant. The details of the flowers had been reduced in order to show the simplicity and create the pattern model to use them for models, so three flowers had created three pattern models and they had been developed into six patterns, using universal artist techniques, so the pattern created are modern and they can be used for further decoration.

Keywords: patterns design, Suan Sunandha Palace, pattern of the flowers, visual arts and design

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16664 Study on Flexible Diaphragm In-Plane Model of Irregular Multi-Storey Industrial Plant

Authors: Cheng-Hao Jiang, Mu-Xuan Tao

Abstract:

The rigid diaphragm model may cause errors in the calculation of internal forces due to neglecting the in-plane deformation of the diaphragm. This paper thus studies the effects of different diaphragm in-plane models (including in-plane rigid model and in-plane flexible model) on the seismic performance of structures. Taking an actual industrial plant as an example, the seismic performance of the structure is predicted using different floor diaphragm models, and the analysis errors caused by different diaphragm in-plane models including deformation error and internal force error are calculated. Furthermore, the influence of the aspect ratio on the analysis errors is investigated. Finally, the code rationality is evaluated by assessing the analysis errors of the structure models whose floors were determined as rigid according to the code’s criterion. It is found that different floor models may cause great differences in the distribution of structural internal forces, and the current code may underestimate the influence of the floor in-plane effect.

Keywords: industrial plant, diaphragm, calculating error, code rationality

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16663 Using Jumping Particle Swarm Optimization for Optimal Operation of Pump in Water Distribution Networks

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

Abstract:

Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

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16662 Computational Fluid Dynamics of a Bubbling Fluidized Bed in Wood Pellets

Authors: Opeyemi Fadipe, Seong Lee, Guangming Chen, Steve Efe

Abstract:

In comparison to conventional combustion technologies, fluidized bed combustion has several advantages, such as superior heat transfer characteristics due to homogeneous particle mixing, lower temperature needs, nearly isothermal process conditions, and the ability to operate continuously. Computational fluid dynamics (CFD) can help anticipate the intricate combustion process and the hydrodynamics of a fluidized bed thoroughly by using CFD techniques. Bubbling Fluidized bed was model using the Eulerian-Eulerian model, including the kinetic theory of the flow. The model was validated by comparing it with other simulation of the fluidized bed. The effects of operational gas velocity, volume fraction, and feed rate were also investigated numerically. A higher gas velocity and feed rate cause an increase in fluidization of the bed.

Keywords: fluidized bed, operational gas velocity, volume fraction, computational fluid dynamics

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16661 The Effect of Connections Form on Seismic Behavior of Portal Frames

Authors: Kiavash Heidarzadeh

Abstract:

The seismic behavior of portal frames is mainly based on the shape of their joints. In these structures, vertical and inclined connections are the two general forms of connections. The shapes of connections can make differences in seismic responses of portal frames. Hence, in this paper, for the first step, the non-linear performance of portal frames with vertical and inclined connections has been investigated by monotonic analysis. Also, the effect of section sizes is considered in this analysis. For comparison, hysteresis curves have been evaluated for two model frames with different forms of connections. Each model has three various sizes of the column and beam. Other geometrical parameters have been considered constant. In the second step, for every model, an appropriate size of sections has been selected from the previous step. Next, the seismic behavior of each model has been analyzed by the time history method under three near-fault earthquake records. Finite element ABAQUS software is used for simulation and analysis of samples. Outputs show that connections form can impact on reaction forces of portal frames under earthquake loads. Also, it is understood that the load capacity in frames with vertical connections is more than the frames with inclined connections.

Keywords: inclined connections, monotonic, portal frames, seismic behavior, time history, vertical connections

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16660 Vulnerability of Groundwater to Pollution in Akwa Ibom State, Southern Nigeria, using the DRASTIC Model and Geographic Information System (GIS)

Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

Abstract:

Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

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16659 Developed Text-Independent Speaker Verification System

Authors: Mohammed Arif, Abdessalam Kifouche

Abstract:

Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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16658 Modeling of Production Lines Systems with Layout Constraints

Authors: Sadegh Abebi

Abstract:

There are problems with estimating time of product process of products, especially when there is variable serving time, like control stage. These problems will cause overestimation of process time. Layout constraints, reworking constraints and inflexible product schedule in multi product lines, needs a precise planning to reduce volume in particular situation of line stock. In this article, by analyzing real queue systems with layout constraints and by using concepts and principles of Markov chain in queue theory, a hybrid model has been presented. This model can be a base to assess queue systems with probable parameters of service. Here by presenting a case study, the proposed model will be described. so, production lines of a home application manufacturer will be analyzed.

Keywords: Queuing theory, Markov Chain, layout, line balance

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16657 Machine Learning Development Audit Framework: Assessment and Inspection of Risk and Quality of Data, Model and Development Process

Authors: Jan Stodt, Christoph Reich

Abstract:

The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

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16656 Cirrhosis Mortality Prediction as Classification using Frequent Subgraph Mining

Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

Abstract:

In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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16655 A Comparative Study on the Dimensional Error of 3D CAD Model and SLS RP Model for Reconstruction of Cranial Defect

Authors: L. Siva Rama Krishna, Sriram Venkatesh, M. Sastish Kumar, M. Uma Maheswara Chary

Abstract:

Rapid Prototyping (RP) is a technology that produces models and prototype parts from 3D CAD model data, CT/MRI scan data, and model data created from 3D object digitizing systems. There are several RP process like Stereolithography (SLA), Solid Ground Curing (SGC), Selective Laser Sintering (SLS), Fused Deposition Modelling (FDM), 3D Printing (3DP) among them SLS and FDM RP processes are used to fabricate pattern of custom cranial implant. RP technology is useful in engineering and biomedical application. This is helpful in engineering for product design, tooling and manufacture etc. RP biomedical applications are design and development of medical devices, instruments, prosthetics and implantation; it is also helpful in planning complex surgical operation. The traditional approach limits the full appreciation of various bony structure movements and therefore the custom implants produced are difficult to measure the anatomy of parts and analyse the changes in facial appearances accurately. Cranioplasty surgery is a surgical correction of a defect in cranial bone by implanting a metal or plastic replacement to restore the missing part. This paper aims to do a comparative study on the dimensional error of CAD and SLS RP Models for reconstruction of cranial defect by comparing the virtual CAD with the physical RP model of a cranial defect.

Keywords: rapid prototyping, selective laser sintering, cranial defect, dimensional error

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16654 Mobile Schooling for the Most Vulnerable Children on the Street: An Innovation

Authors: Md. Shakhawat Ullah Chowdhury

Abstract:

Mobile school is an innovative methodology in non-formal education to increase access to education for children during conflict through theatre for education for appropriate basic education to children during conflict. The continuous exposure to harsh environments and the nature of the lifestyles of children in conflict make them vulnerable. However, the mobile school initiative takes into consideration the mobile lifestyle of children in conflict. Schools are provided considering the pocket area of the street children with portable chalkboards, tin of books and materials as communities move. Teaching is multi-grade to ensure all children in the community benefit. The established mobile schools, while focused on basic literacy and numeracy skills according to traditions of the communities. The school teachers are selected by the community and trained by a theatre activist. These teachers continue to live and move with the community and provide continuous education for children in conflict. The model proposed a holistic team work to deliver education focused services to the street children’s pocket area where the team is mobile. The team consists of three members –an educator (theatre worker), a psychological counsellor and paramedics. The mobile team is responsible to educate street children and also play dramas which specially produce on the basis of national curriculum and awareness issues for street children. Children enjoy play and learn about life skills and basic literacy and numeracy skills which may be a pillar of humanitarian aid during conflict.

Keywords: vulnerable, children in conflict, mobile schooling, child-friendly

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16653 A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks

Authors: Naghmeh Moradpoor Sheykhkanloo

Abstract:

Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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16652 CFD Study on the Effect of Primary Air on Combustion of Simulated MSW Process in the Fixed Bed

Authors: Rui Sun, Tamer M. Ismail, Xiaohan Ren, M. Abd El-Salam

Abstract:

Incineration of municipal solid waste (MSW) is one of the key scopes in the global clean energy strategy. A computational fluid dynamics (CFD) model was established. In order to reveal these features of the combustion process in a fixed porous bed of MSW. Transporting equations and process rate equations of the waste bed were modeled and set up to describe the incineration process, according to the local thermal conditions and waste property characters. Gas phase turbulence was modeled using k-ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The heterogeneous reaction rates were determined using Arrhenius eddy dissipation and the Arrhenius-diffusion reaction rates. The effects of primary air flow rate and temperature in the burning process of simulated MSW are investigated experimentally and numerically. The simulation results in bed are accordant with experimental data well. The model provides detailed information on burning processes in the fixed bed, which is otherwise very difficult to obtain by conventional experimental techniques.

Keywords: computational fluid dynamics (CFD) model, waste incineration, municipal solid waste (MSW), fixed bed, primary air

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16651 Developing Cucurbitacin a Minimum Inhibition Concentration of Meloidogyne Incognita Using a Computer-Based Model

Authors: Zakheleni P. Dube, Phatu W. Mashela

Abstract:

Minimum inhibition concentration (MIC) is the lowest concentration of a chemical that brings about significant inhibition of target organism. The conventional method for establishing the MIC for phytonematicides is tedious. The objective of this study was to use the Curve-fitting Allelochemical Response Data (CARD) to determine the MIC for pure cucurbitacin A on Meloidogyne incognita second-stage juveniles (J2) hatch, immobility and mortality. Meloidogyne incognita eggs and freshly hatched J2 were separately exposed to a series of pure cucurbitacin A concentrations of 0.00, 0.25, 0.50, 0.75, 1.00, 1.25, 1.50, 1.75, 2.00, 2.25 and 2.50 μg.mL⁻¹for 12, 24, 48 and 72 h in an incubator set at 25 ± 2°C. Meloidogyne incognita J2 hatch, immobility and mortality counts were determined using a stereomicroscope and the significant means were subjected to the CARD model. The model exhibited density-dependent growth (DDG) patterns of J2 hatch, immobility and mortality to increasing concentrations of cucurbitacin A. The average MIC for cucurbitacin A on M. incognita J2 hatch, immobility and mortality were 2.2, 0.58 and 0.63 µg.mL⁻¹, respectively. Meloidogyne incognita J2 hatch had the highest average MIC value followed by mortality and immobility had the least. In conclusion, the CARD model was able to generate MIC for cucurbitacin A, hence it could serve as a valuable tool in the chemical-nematode bioassay studies.

Keywords: inhibition concentration, phytonematicide, sensitivity index, threshold stimulation, triterpenoids.

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16650 Absorptive Capabilities in the Development of Biopharmaceutical Industry: The Case of Bioprocess Development and Research Unit, National Polytechnic Institute

Authors: Ana L. Sánchez Regla, Igor A. Rivera González, María del Pilar Monserrat Pérez Hernández

Abstract:

The ability of an organization to identify and get useful information from external sources, assimilate it, transform and apply to generate products or services with added value is called absorptive capacity. Absorptive capabilities contribute to have market opportunities to firms and get a leader position with respect to others competitors. The Bioprocess Development and Research Unit (UDIBI) is a Research and Development (R&D) laboratory that belongs to the National Polytechnic Institute (IPN), which is a higher education institute in Mexico. The UDIBI was created with the purpose of carrying out R and D activities for the Transferon®, a biopharmaceutical product developed and patented by IPN. The evolution of competence and scientific and technological platform made UDIBI expand its scope by providing technological services (preclínical studies and bio-compatibility evaluation) to the national pharmaceutical industry and biopharmaceutical industry. The relevance of this study is that those industries are classified as high scientific and technological intensity, and yet, after a review of the state of the art, there is only one study of absorption capabilities in biopharmaceutical industry with a similar scope to this research; in the case of Mexico, there is none. In addition to this, UDIBI belongs to a public university and its operation does not depend on the federal budget, but on the income generated by its external technological services. This fact represents a highly remarkable case in Mexico's public higher education context. This current doctoral research (2015-2019) is contextualized within a case study, its main objective is to identify and analyze the absorptive capabilities that characterise the UDIBI that allows it had become in a one of two third authorized laboratory by the sanitary authority in Mexico for developed bio-comparability studies to bio-pharmaceutical products. The development of this work in the field is divided into two phases. In a first phase, 15 interviews were conducted with the UDIBI personnel, covering management levels, heads of services, project leaders and laboratory personnel. These interviews were structured under a questionnaire, which was designed to integrate open questions and to a lesser extent, others, whose answers would be answered on a Likert-type rating scale. From the information obtained in this phase, a scientific article was made (in review and a proposal of presentation was submitted in different academic forums. A second stage will be made from the conduct of an ethnographic study within this organization under study that will last about 3 months. On the other hand, it is intended to carry out interviews with external actors around the UDIBI (suppliers, advisors, IPN officials, including contact with an academic specialized in absorption capacities to express their comments on this thesis. The inicial findings had shown two lines: i) exist institutional, technological and organizational management elements that encourage and/or limit the creation of absorption capacities in this scientific and technological laboratory and, ii) UDIBI has had created a set of multiple transfer technology of knowledge mechanisms which have had permitted to build a huge base of prior knowledge.

Keywords: absorptive capabilities, biopharmaceutical industry, high research and development intensity industries, knowledge management, transfer of knowledge

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16649 Pharmacovigilance in Hospitals: Retrospective Study at the Pharmacovigilance Service of UHE-Oran, Algeria

Authors: Nadjet Mekaouche, Hanane Zitouni, Fatma Boudia, Habiba Fetati, A. Saleh, A. Lardjam, H. Geniaux, A. Coubret, H. Toumi

Abstract:

Medicines have undeniably played a major role in prolonging shelf life and improving quality. The absolute efficacy of the drug remains a lever for innovation, its benefit/risk balance is not always assured and it does not always have the expected effects. Prior to marketing, knowledge about adverse drug reactions is incomplete. Once on the market, phase IV drug studies begin. For years, the drug was prescribed with less care to a large number of very heterogeneous patients and often in combination with other drugs. It is at this point that previously unknown adverse effects may appear, hence the need for the implementation of a pharmacovigilance system. Pharmacovigilance represents all methods for detecting, evaluating, informing and preventing the risks of adverse drug reactions. The most severe adverse events occur frequently in hospital and that a significant proportion of adverse events result in hospitalizations. In addition, the consequences of hospital adverse events in terms of length of stay, mortality and costs are considerable. It, therefore, appears necessary to develop ‘hospital pharmacovigilance’ aimed at reducing the incidence of adverse reactions in hospitals. The most widely used monitoring method in pharmacovigilance is spontaneous notification. However, underreporting of adverse drug reactions is common in many countries and is a major obstacle to pharmacovigilance assessment. It is in this context that this study aims to describe the experience of the pharmacovigilance service at the University Hospital of Oran (EHUO). This is a retrospective study extending from 2011 to 2017, carried out on archived records of declarations collected at the level of the EHUO Pharmacovigilance Department. Reporting was collected by two methods: ‘spontaneous notification’ and ‘active pharmacovigilance’ targeting certain clinical services. We counted 217 statements. It involved 56% female patients and 46% male patients. Age ranged from 5 to 78 years with an average of 46 years. The most common adverse reaction was drug toxidermy. For the drugs in question, they were essentially according to the ATC classification of anti-infectives followed by anticancer drugs. As regards the evolution of declarations by year, a low rate of notification was noted in 2011. That is why we decided to set up an active approach at the level of some services where a resident of reference attended the staffs every week. This has resulted in an increase in the number of reports. The declarations came essentially from the services where the active approach was installed. This highlights the need for ongoing communication between all relevant health actors to stimulate reporting and secure drug treatments.

Keywords: adverse drug reactions, hospital, pharmacovigilance, spontaneous notification

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16648 Simulation of Corn Yield in Carmen, North Cotabato, Philippines Using Aquacrop Model

Authors: Marilyn S. Painagan

Abstract:

This general objective of the study was to apply the AquaCrop model to the conditions in the municipality of Carmen, North Cotabato in terms of predicting corn yields in this area and determine the influence of rainfall and soil depth on simulated yield. The study revealed wide disparity in monthly yields as a consequence of similarly varying monthly rainfall magnitudes. It also found out that simulated yield varies with the depth of soil, which in this case was clay loam, the predominant soil in the study area. The model was found to be easy to use even with limited data and shows a vast potential for various farming and policy applications, such as formulation of a cropping calendar.

Keywords: aquacrop, evapotranspiration, crop modelling, crop simulation

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16647 Urban Energy Demand Modelling: Spatial Analysis Approach

Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

Abstract:

Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

Procedia PDF Downloads 133
16646 A Model of Foam Density Prediction for Expanded Perlite Composites

Authors: M. Arifuzzaman, H. S. Kim

Abstract:

Multiple sets of variables associated with expanded perlite particle consolidation in foam manufacturing were analyzed to develop a model for predicting perlite foam density. The consolidation of perlite particles based on the flotation method and compaction involves numerous variables leading to the final perlite foam density. The variables include binder content, compaction ratio, perlite particle size, various perlite particle densities and porosities, and various volumes of perlite at different stages of process. The developed model was found to be useful not only for prediction of foam density but also for optimization between compaction ratio and binder content to achieve a desired density. Experimental verification was conducted using a range of foam densities (0.15–0.5 g/cm3) produced with a range of compaction ratios (1.5-3.5), a range of sodium silicate contents (0.05–0.35 g/ml) in dilution, a range of expanded perlite particle sizes (1-4 mm), and various perlite densities (such as skeletal, material, bulk, and envelope densities). A close agreement between predictions and experimental results was found.

Keywords: expanded perlite, flotation method, foam density, model, prediction, sodium silicate

Procedia PDF Downloads 393
16645 Elastic and Plastic Collision Comparison Using Finite Element Method

Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

Abstract:

The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: collision, impact models, finite element method, Hertz Theory

Procedia PDF Downloads 158
16644 A Hybrid Traffic Model for Smoothing Traffic Near Merges

Authors: Shiri Elisheva Decktor, Sharon Hornstein

Abstract:

Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

Procedia PDF Downloads 90
16643 Construction of a Dynamic Migration Model of Extracellular Fluid in Brain for Future Integrated Control of Brain State

Authors: Tomohiko Utsuki, Kyoka Sato

Abstract:

In emergency medicine, it is recognized that brain resuscitation is very important for the reduction of mortality rate and neurological sequelae. Especially, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) are most required for stabilizing brain’s physiological state in the treatment for such as brain injury, stroke, and encephalopathy. However, the manual control of BT, ICP, and CBF frequently requires the decision and operation of medical staff, relevant to medication and the setting of therapeutic apparatus. Thus, the integration and the automation of the control of those is very effective for not only improving therapeutic effect but also reducing staff burden and medical cost. For realizing such integration and automation, a mathematical model of brain physiological state is necessary as the controlled object in simulations, because the performance test of a prototype of the control system using patients is not ethically allowed. A model of cerebral blood circulation has already been constructed, which is the most basic part of brain physiological state. Also, a migration model of extracellular fluid in brain has been constructed, however the condition that the total volume of intracranial cavity is almost changeless due to the hardness of cranial bone has not been considered in that model. Therefore, in this research, the dynamic migration model of extracellular fluid in brain was constructed on the consideration of the changelessness of intracranial cavity’s total volume. This model is connectable to the cerebral blood circulation model. The constructed model consists of fourteen compartments, twelve of which corresponds to perfused area of bilateral anterior, middle and posterior cerebral arteries, the others corresponds to cerebral ventricles and subarachnoid space. This model enable to calculate the migration of tissue fluid from capillaries to gray matter and white matter, the flow of tissue fluid between compartments, the production and absorption of cerebrospinal fluid at choroid plexus and arachnoid granulation, and the production of metabolic water. Further, the volume, the colloid concentration, and the tissue pressure of/in each compartment are also calculable by solving 40-dimensional non-linear simultaneous differential equations. In this research, the obtained model was analyzed for its validation under the four condition of a normal adult, an adult with higher cerebral capillary pressure, an adult with lower cerebral capillary pressure, and an adult with lower colloid concentration in cerebral capillary. In the result, calculated fluid flow, tissue volume, colloid concentration, and tissue pressure were all converged to suitable value for the set condition within 60 minutes at a maximum. Also, because these results were not conflict with prior knowledge, it is certain that the model can enough represent physiological state of brain under such limited conditions at least. One of next challenges is to integrate this model and the already constructed cerebral blood circulation model. This modification enable to simulate CBF and ICP more precisely due to calculating the effect of blood pressure change to extracellular fluid migration and that of ICP change to CBF.

Keywords: dynamic model, cerebral extracellular migration, brain resuscitation, automatic control

Procedia PDF Downloads 139
16642 A Fuzzy Linear Regression Model Based on Dissemblance Index

Authors: Shih-Pin Chen, Shih-Syuan You

Abstract:

Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy.

Keywords: dissemblance index, fuzzy linear regression, graded mean integration, mathematical programming

Procedia PDF Downloads 421
16641 Mathematical Model of Corporate Bond Portfolio and Effective Border Preview

Authors: Sergey Podluzhnyy

Abstract:

One of the most important tasks of investment and pension fund management is building decision support system which helps to make right decision on corporate bond portfolio formation. Today there are several basic methods of bond portfolio management. They are duration management, immunization and convexity management. Identified methods have serious disadvantage: they do not take into account credit risk or insolvency risk of issuer. So, identified methods can be applied only for management and evaluation of high-quality sovereign bonds. Applying article proposes mathematical model for building an optimal in case of risk and yield corporate bond portfolio. Proposed model takes into account the default probability in formula of assessment of bonds which results to more correct evaluation of bonds prices. Moreover, applied model provides tools for visualization of the efficient frontier of corporate bonds portfolio taking into account the exposure to credit risk, which will increase the quality of the investment decisions of portfolio managers.

Keywords: corporate bond portfolio, default probability, effective boundary, portfolio optimization task

Procedia PDF Downloads 309