Search results for: empowerment model
16092 Discover Your Power: A Case for Contraceptive Self-Empowerment
Authors: Oluwaseun Adeleke, Samuel Ikan, Anthony Nwala, Mopelola Raji, Fidelis Edet
Abstract:
Background: The risks associated with each pregnancy is carried almost entirely by a woman; however, the decision about whether and when to get pregnant is a subject that several others contend with her to make. The self-care concept offers women of reproductive age the opportunity to take control of their health and its determinants with or without the influence of a healthcare provider, family, and friends. DMPA-SC Self-injection (SI) is becoming the cornerstone of contraceptive self-care and has the potential to expand access and create opportunities for women to take control of their reproductive health. Methodology: To obtain insight into the influences that interfere with a woman’s capacity to make contraceptive choices independently, the Delivering Innovations in Selfcare (DISC) project conducted two intensive rounds of qualitative data collection and triangulation that included provider, client, and community mobilizer interviews, facility observations, and routine program data collection. Respondents were sampled according to a convenience sampling approach and data collected analyzed using a codebook and Atlas-TI. The research team members came together for participatory analysis workshop to explore and interpret emergent themes. Findings: Insights indicate that women are increasingly finding their voice and independently seek services to prevent a deterioration of their economic situation and achieve personal ambitions. Women who hold independent decision-making power still prefer to share decision making power with their male partners. Male partners’ influence on women’s use of family planning and self-inject was most dominant. There were examples of men’s support for women’s use of contraception to prevent unintended pregnancy, as well as men withholding support. Other men outrightly deny their partners from obtaining contraceptive services and their partners cede this sexual and reproductive health right without objection. A woman’s decision to initiate family planning is affected by myths and misconceptions, many of which have cultural and religious origins. Some tribes are known for their reluctance to use contraception and often associate stigma with the pursuit of family planning (FP) services. Information given by the provider is accepted, and, in many cases, clients cede power to providers to shape their SI user journey. A provider’s influence on a client’s decision to self-inject is reinforced by their biases and concerns. Clients are inhibited by the presence of peers during group education at the health facility. Others are motivated to seek FP services by the interest expressed by peers. There is also a growing trend in the influence of social media on FP uptake, particularly Facebook fora. Conclusion: The convenience of self-administration at home is a benefit for those that contend with various forms of social influences as well as covert users. Beyond increasing choice and reducing barriers to accessing Sexual and Reproductive Health (SRH) services, it can initiate the process of self-discovery and agency in the contraceptive user journey.Keywords: selfcare, self-empowerment, agency, DMPA-SC, contraception, family planning, influences
Procedia PDF Downloads 6116091 The Use of Stochastic Gradient Boosting Method for Multi-Model Combination of Rainfall-Runoff Models
Authors: Phanida Phukoetphim, Asaad Y. Shamseldin
Abstract:
In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics
Procedia PDF Downloads 32616090 A Data-Driven Agent Based Model for the Italian Economy
Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio
Abstract:
We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data
Procedia PDF Downloads 6116089 Active Power Control of PEM Fuel Cell System Power Generation Using Adaptive Neuro-Fuzzy Controller
Authors: Khaled Mammar
Abstract:
This paper presents an application of adaptive neuro-fuzzy controller for PEM fuel cell system. The model proposed for control include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore, a Fuzzy Logic (FLC) and adaptive neuro-fuzzy controllers are used to control the active power of PEM fuel cell system. The controllers modify the hydrogen flow feedback from the terminal load. The validity of the controller is verified when the fuel cell system model is used in conjunction with the ANFIS controller to predict the response of the active power. Simulation results confirmed the high-performance capability of the neuo-fuzzy to control power generation.Keywords: fuel cell, PEMFC, modeling, simulation, Fuzzy Logic Controller, FLC, adaptive neuro-fuzzy controller, ANFIS
Procedia PDF Downloads 45116088 Recent Advancement in Dendrimer Based Nanotechnology for the Treatment of Brain Tumor
Authors: Nitin Dwivedi, Jigna Shah
Abstract:
Brain tumor is metastatic neoplasm of central nervous system, in most of cases it is life threatening disease with low survival rate. Despite of enormous efforts in the development of therapeutics and diagnostic tools, the treatment of brain tumors and gliomas remain a considerable challenge in the area of neuro-oncology. The most reason behind of this the presence of physiological barriers including blood brain barrier and blood brain tumor barrier, lead to insufficient reach ability of therapeutic agents at the site of tumor, result of inadequate destruction of gliomas. So there is an indeed need empowerment of brain tumor imaging for better characterization and delineation of tumors, visualization of malignant tissue during surgery, and tracking of response to chemotherapy and radiotherapy. Multifunctional different generations of dendrimer offer an improved effort for potentiate drug delivery at the site of brain tumor and gliomas. So this article emphasizes the innovative dendrimer approaches in tumor targeting, tumor imaging and delivery of therapeutic agent.Keywords: blood brain barrier, dendrimer, gliomas, nanotechnology
Procedia PDF Downloads 55416087 Numerical Investigation of Wastewater Rheological Characteristics on Flow Field Inside a Sewage Network
Authors: Seyed-Mohammad-Kazem Emami, Behrang Saki, Majid Mohammadian
Abstract:
The wastewater flow field inside a sewage network including pipe and manhole was investigated using a Computational Fluid Dynamics (CFD) model. The numerical model is developed by incorporating a rheological model to calculate the viscosity of wastewater fluid by means of open source toolbox OpenFOAM. The rheological properties of prepared wastewater fluid suspensions are first measured using a BrookField LVDVII Pro+ viscometer with an enhanced UL adapter and then correlated the suitable rheological viscosity model values from the measured rheological properties. The results show the significant effects of rheological characteristics of wastewater fluid on the flow domain of sewer system. Results were compared and discussed with the commonly used Newtonian model to evaluate the differences for velocity profile, pressure and shear stress. Keywords: Non-Newtonian flows, Wastewater, Numerical simulation, Rheology, Sewage Network
Procedia PDF Downloads 11916086 Effects of the Air Supply Outlets Geometry on Human Comfort inside Living Rooms: CFD vs. ADPI
Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil
Abstract:
The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency
Procedia PDF Downloads 40316085 Curriculum Based Measurement and Precision Teaching in Writing Empowerment Enhancement: Results from an Italian Learning Center
Authors: I. Pelizzoni, C. Cavallini, I. Salvaderi, F. Cavallini
Abstract:
We present the improvement in writing skills obtained by 94 participants (aged between six and 10 years) with special educational needs through a writing enhancement program based on fluency principles. The study was planned and conducted with a single-subject experimental plan for each of the participants, in order to confirm the results in the literature. These results were obtained using precision teaching (PT) methodology to increase the number of written graphemes per minute in the pre- and post-test, by curriculum based measurement (CBM). Results indicated an increase in the number of written graphemes for all participants. The average overall duration of the intervention is 144 minutes in five months of treatment. These considerations have been analyzed taking account of the complexity of the implementation of measurement systems in real operational contexts (an Italian learning center) and important aspects of replicability and cost-effectiveness of such interventions.Keywords: curriculum based measurement, precision teaching, writing skill, Italian learning center
Procedia PDF Downloads 12016084 Modelling of Pervaporation Separation of Butanol from Aqueous Solutions Using Polydimethylsiloxane Mixed Matrix Membranes
Authors: Arian Ebneyamini, Hoda Azimi, Jules Thibaults, F. Handan Tezel
Abstract:
In this study, a modification of Hennepe model for pervaporation separation of butanol from aqueous solutions using Polydimethylsiloxane (PDMS) mixed matrix membranes has been introduced and validated by experimental data. The model was compared to the original Hennepe model and few other models which are applicable for membrane gas separation processes such as Maxwell, Lewis Nielson and Pal. Theoretical modifications for non-ideal interface morphology have been offered to predict the permeability in case of interface void, interface rigidification and pore-blockage. The model was in a good agreement with experimental data.Keywords: butanol, PDMS, modeling, pervaporation, mixed matrix membranes
Procedia PDF Downloads 20716083 Estimation of the Pore Electrical Conductivity Using Dielectric Sensors
Authors: Fethi Bouksila, Magnus Persson, Ronny Berndtsson, Akissa Bahri
Abstract:
Under salinity conditions, we evaluate the performance of Hilhost (2000) model to predict pore electrical conductivity ECp from dielectric permittivity and bulk electrical conductivity (ECa) using Time and Frequency Domain Reflectometry sensors (TDR, FDR). Using FDR_WET sensor, RMSE of ECp was 4.15 dS m-1. By replacing the standard soil parameter (K0) in Hilhost model by K0-ECa relationship, the RMSE of ECp decreased to 0.68 dS m-1. WET sensor could give similar accuracy to estimate ECp than TDR if calibrated values of K0 were used instead of standard values in Hilhost model.Keywords: hilhost model, soil salinity, time domain reflectometry, frequency domain reflectometry, dielectric methods
Procedia PDF Downloads 12816082 Data Model to Predict Customize Skin Care Product Using Biosensor
Authors: Ashi Gautam, Isha Shukla, Akhil Seghal
Abstract:
Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.Keywords: biosensors, data model, machine learning, skin care
Procedia PDF Downloads 8416081 An Equivalent Circuit Model Approach for Battery Pack Simulation in a Hybrid Electric Vehicle System Powertrain
Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka
Abstract:
The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model
Procedia PDF Downloads 28316080 4P-Model of Information Terrorism
Authors: Nataliya Venelinova
Abstract:
The paper proposes a new interdisciplinary model of reconsidering the role of mass communication effects by coverage of terrorism. The idea of 4P model is based on the synergy, created by the information strategy of threat, predominantly used by terrorist groups, the effects of mediating the symbolic action of the terrorist attacks or the taking of responsibility of any attacks, and the reshaped public perception for security after the attacks being mass communicated. The paper defines the mass communication cycle of terrorism, which leads not only to re-agenda setting of the societies, but also spirally amplifying the effect of propagating fears by over-informing on terrorism attacks. This finally results in the outlining of the so called 4P-model of information terrorism: mass propaganda, panic, paranoia and pandemic.Keywords: information terrorism, mass communication cycle, public perception, security
Procedia PDF Downloads 16316079 On Disaggregation and Consolidation of Imperfect Quality Shipments in an Extended EPQ Model
Authors: Hung-Chi Chang
Abstract:
For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory
Procedia PDF Downloads 36816078 Composite Forecasts Accuracy for Automobile Sales in Thailand
Authors: Watchareeporn Chaimongkol
Abstract:
In this paper, we compare the statistical measures accuracy of composite forecasting model to estimate automobile customer demand in Thailand. A modified simple exponential smoothing and autoregressive integrate moving average (ARIMA) forecasting model is built to estimate customer demand of passenger cars, instead of using information of historical sales data. Our model takes into account special characteristic of the Thai automobile market such as sales promotion, advertising and publicity, petrol price, and interest rate for loan. We evaluate our forecasting model by comparing forecasts with actual data using six accuracy measurements, mean absolute percentage error (MAPE), geometric mean absolute error (GMAE), symmetric mean absolute percentage error (sMAPE), mean absolute scaled error (MASE), median relative absolute error (MdRAE), and geometric mean relative absolute error (GMRAE).Keywords: composite forecasting, simple exponential smoothing model, autoregressive integrate moving average model selection, accuracy measurements
Procedia PDF Downloads 35216077 Uncertainty of the Brazilian Earth System Model for Solar Radiation
Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini
Abstract:
This study evaluated the uncertainties involved in the solar radiation projections generated by the Brazilian Earth System Model (BESM) of the Weather and Climate Prediction Center (CPTEC) belonging to Coupled Model Intercomparison Phase 5 (CMIP5), with the aim of identifying efficiency in the projections for solar radiation of said model and in this way establish the viability of its use. Two different scenarios elaborated by Intergovernmental Panel on Climate Change (IPCC) were evaluated: RCP 4.5 (with more optimistic contour conditions) and 8.5 (with more pessimistic initial conditions). The method used to verify the accuracy of the present model was the Nash coefficient and the Statistical bias, as it better represents these atmospheric patterns. The BESM showed a tendency to overestimate the data of solar radiation projections in most regions of the state of Rio Grande do Sul and through the validation methods adopted by this study, BESM did not present a satisfactory accuracy.Keywords: climate changes, projections, solar radiation, uncertainty
Procedia PDF Downloads 24116076 An Empirical Investigation of Mobile Banking Services Adoption in Pakistan
Authors: Aijaz A. Shaikh, Richard Glavee-Geo, Heikki Karjaluoto
Abstract:
Adoption of Information Systems (IS) is receiving increasing attention such that its implications have been closely monitored and studied by the IS management community, industry and professional gatekeepers. Building on previous research regarding the adoption of technology, this paper develops and validates an integrated model of the adoption of mobile banking. The model originates from the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB). This paper intends to offer a preliminary scrutiny of the antecedents of the adoption of mobile banking services in the context of a developing country. Data was collected from Pakistan. The findings showed that an integrated TAM and TPB model greatly explains the adoption intention of mobile banking; and perceived behavioural control and its antecedents play a significant role in predicting adoption Theoretical and managerial implications of findings are presented and discussed.Keywords: developing country, mobile banking service adoption, technology acceptance model, theory of planned behavior
Procedia PDF Downloads 40616075 A Type-2 Fuzzy Model for Link Prediction in Social Network
Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi
Abstract:
Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.Keywords: social network, link prediction, granular computing, type-2 fuzzy sets
Procedia PDF Downloads 31616074 An Empirical Dynamic Fuel Cell Model Used for Power System Verification in Aerospace
Authors: Giuliano Raimondo, Jörg Wangemann, Peer Drechsel
Abstract:
In systems development involving Fuel Cells generators, it is important to have from an early stage of the project a dynamic model for the electrical behavior of the stack to be shared between involved development parties. It allows independent and early design and tests of fuel cell related power electronic. This paper presents an empirical Fuel Cell system model derived from characterization tests on a real system. Moreover, it is illustrated how the obtained model is used to build and validate a real-time Fuel Cell system emulator which is used for aerospace electrical integration testing activities.Keywords: fuel cell, modelling, real time emulation, testing
Procedia PDF Downloads 32916073 Three-Dimensional Numerical Model of an Earth Air Heat Exchanger under a Constrained Urban Environment in India: Modeling and Validation
Authors: V. Rangarajan, Priyanka Kaushal
Abstract:
This study investigates the effectiveness of a typical Earth Air Heat Exchanger (EATHE) for energy efficient space cooling in an urban environment typified by space and soil-related constraints that preclude an optimal design. It involves the development of a three-dimensional numerical transient model that is validated by measurements at a live site in India. It is found that the model accurately predicts the soil temperatures at various depths as well as the EATHE outlet air temperature. The study shows that such an EATHE, even when designed under constraints, does provide effective space cooling especially during the hot months of the year.Keywords: earth air heat exchanger (EATHE), India, MATLAB, model, simulation
Procedia PDF Downloads 31516072 Urban Design via Estimation Model for Traffic Index of Cities Based on an Artificial Intelligence
Authors: Seyed Sobhan Alvani, Mohammad Gohari
Abstract:
By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.Keywords: traffic index, population growth rate, cities wideness, artificial neural network
Procedia PDF Downloads 2116071 Frailty Models for Modeling Heterogeneity: Simulation Study and Application to Quebec Pension Plan
Authors: Souad Romdhane, Lotfi Belkacem
Abstract:
When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study
Procedia PDF Downloads 35316070 The Non-Stationary BINARMA(1,1) Process with Poisson Innovations: An Application on Accident Data
Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer
Abstract:
This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.Keywords: non-stationary, BINARMA(1, 1) model, Poisson innovations, conditional maximum likelihood, CML
Procedia PDF Downloads 12216069 The Discriminate Analysis and Relevant Model for Mapping Export Potential
Authors: Jana Gutierez Chvalkovska, Michal Mejstrik, Matej Urban
Abstract:
There are pending discussions over the mapping of country export potential in order to refocus export strategy of firms and its evidence-based promotion by the Export Credit Agencies (ECAs) and other permitted vehicles of governments. In this paper we develop our version of an applied model that offers “stepwise” elimination of unattractive markets. We modify and calibrate the model for the particular features of the Czech Republic and specific pilot cases where we apply an individual approach to each sector.Keywords: export strategy, modeling export, calibration, export promotion
Procedia PDF Downloads 49316068 Control of an SIR Model for Basic Reproduction Number Regulation
Authors: Enrique Barbieri
Abstract:
The basic disease-spread model described by three states denoting the susceptible (S), infectious (I), and removed (recovered and deceased) (R) sub-groups of the total population N, or SIR model, has been considered. Heuristic mitigating action profiles of the pharmaceutical and non-pharmaceutical types may be developed in a control design setting for the purpose of reducing the transmission rate or improving the recovery rate parameters in the model. Even though the transmission and recovery rates are not control inputs in the traditional sense, a linear observer and feedback controller can be tuned to generate an asymptotic estimate of the transmission rate for a linearized, discrete-time version of the SIR model. Then, a set of mitigating actions is suggested to steer the basic reproduction number toward unity, in which case the disease does not spread, and the infected population state does not suffer from multiple waves. The special case of piecewise constant transmission rate is described and applied to a seventh-order SEIQRDP model, which segments the population into four additional states. The offline simulations in discrete time may be used to produce heuristic policies implemented by public health and government organizations.Keywords: control of SIR, observer, SEIQRDP, disease spread
Procedia PDF Downloads 9716067 Open Innovation Strategy (OIS) Paradigm and an OIS Capabilities Model
Authors: Anastasis D. Petrou
Abstract:
Innovation and strategy discussions do highlight open innovation as a new paradigm in business. Yet, a number of stumbling blocks in the form of closed innovation principles weaved into the fabric of a traditional business model stand in the way of the new paradigm’s momentum to increase value in various business contexts. The paper argues that businesses considering an engagement with the open innovation paradigm would need to take steps to improve their multiplicative, absorptive and relational capabilities, respectively. The needed improvements would amount to a business model evolutionary transformation and eventually bring about a paradigm overhaul in business. The transformation is worth staging over time to ensure that open innovation is developed across interconnected and partnered areas of strategic importance. This article develops an open innovation strategy (OIS) capabilities model, and employs examples from different industries to briefly discuss OIS’s potential to augment business value in a number of suggested areas for future research.Keywords: close innovation, open innovation paradigm, open innovation strategy (OIS) paradigm, OIS capabilities model, multiplicative capability, absorptive capability, relational capability
Procedia PDF Downloads 51216066 Potential Contribution of Local Food Resources towards Sustainable Food Tourism in Nueva Vizcaya
Authors: Marvin Eslava
Abstract:
The over-arching aim of this research is to determine the potential contribution of local food resources to the tourism growth of Nueva Vizcaya. It reviews some of the underpinning concepts and to provide a set of considerations for stakeholders to maximize the opportunity of local food can offer to businesses and the wider community. The basis of the study is to develop a sustainable food tourism model for Nueva Vizcaya. For the purpose of this research, there were 60 total numbers of respondents classified as samples from a six municipality. The respondents of the study were stakeholder consisting of government official, local producers, businessman and Non-government organizations in the selected municipalities of Nueva Vizcaya. Stratified purposive sampling was the appropriate technique that was used to the local government officials and employees, NGOs including the businessmen who are associated with local food resources and local producers. The documentary study, focus group discussion and survey questionnaire was used in order to meet the objectives of the study. Kruskall Wallis test was used to test the variances the ratings of the participants. This was used in the computation of hypothesis. The study concluded that the province of Nueva Vizcaya is blessed for its rich farmlands and fertile mountain soil boasts to produce high quality agricultural products. It is a home of various different indigenous groups creating a wide range of local cuisine. The province has substantial local food development evidence by the various food tourism related resources, increase in facilities and celebrating food tourism related events. The local food resources provide extensive potential economic empowerment and help in building the identity of the province. In addition, the local food resources extensively enhance the agriculture sector and other attractions in the province. Finally, it helps to preserve the authenticity of the food culture and generated pride among all stakeholders extensively. All stakeholders have the same perception on the potential contribution of local food resources to the development of the province of Nueva Vizcaya. The public and private sectors are cognizant on their roles to support the production of local food resources in Nueva Vizcaya. Major challenges and barriers in the development of sustainable food tourism in Nueva Vizcaya include production or supply and marketing.Keywords: local food resources, contribution, food tourism, benefits
Procedia PDF Downloads 25316065 Electricity Demand Modeling and Forecasting in Singapore
Authors: Xian Li, Qing-Guo Wang, Jiangshuai Huang, Jidong Liu, Ming Yu, Tan Kok Poh
Abstract:
In power industry, accurate electricity demand forecasting for a certain leading time is important for system operation and control, etc. In this paper, we investigate the modeling and forecasting of Singapore’s electricity demand. Several standard models, such as HWT exponential smoothing model, the ARMA model and the ANNs model have been proposed based on historical demand data. We applied them to Singapore electricity market and proposed three refinements based on simulation to improve the modeling accuracy. Compared with existing models, our refined model can produce better forecasting accuracy. It is demonstrated in the simulation that by adding forecasting error into the forecasting equation, the modeling accuracy could be improved greatly.Keywords: power industry, electricity demand, modeling, forecasting
Procedia PDF Downloads 63316064 Saltwater Intrusion Studies in the Cai River in the Khanh Hoa Province, Vietnam
Authors: B. Van Kessel, P. T. Kockelkorn, T. R. Speelman, T. C. Wierikx, C. Mai Van, T. A. Bogaard
Abstract:
Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate.Keywords: Cai River, hydraulic models, river discharge, saltwater intrusion, tidal barriers
Procedia PDF Downloads 10416063 Quantum Statistical Machine Learning and Quantum Time Series
Authors: Omar Alzeley, Sergey Utev
Abstract:
Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series
Procedia PDF Downloads 462