Search results for: model implementation

Authors: Reza Davoodi, Hamid Abbasi, Heidar Norouzi, Gholamabbas Alipourian

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A dynamic model shaping a process of knowledge management (KM) culture change is suggested. It is aimed at providing effective KM of employees for obtaining desired results in an organization. The essential requirements for obtaining KM culture change are determined. The proposed model realizes these requirements. Dynamics of the model are expressed by a change of its parameters. It is adjusted to the dynamic process of KM culture change. Building the model includes elaboration and integration of interconnected components. The “Result” is a central component of the model. This component determines a desired organizational goal and possible directions of its attainment. The “Confront” component engenders constructive confrontation in an organization. For this reason, the employees are prompted toward KM culture change with the purpose of attaining the desired result. The “Assess” component realizes complex assessments of employee proposals by management and peers. The proposals are directed towards attaining the desired result in an organization. The “Reward” component sets the order of assigning rewards to employees based on the assessments of their proposals.

Keywords: knowledge management, organizational culture change, employee, result

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Felix Böck

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Nowadays, data about learners and their digital activities are collected, which could help educational institutions to better understand learning processes, improve them and be able to provide better learning assistance. In this research project, custom knowledge- and data-driven recommendation algorithms will be used to offer students in higher education integrated learning assistance. The pre-requisite for this is a learner model that is as comprehensive as possible, which should first be created and then kept up-to-date largely automatically for being able to individualize and personalize the learning experience. In order to create such a learner model, a roadmap is presented that describes the individual phases up to the creation and evaluation of the finished model. The methodological process for the research project is disclosed, and the research question of how learners can be supported in their learning with personalized, customized learning recommendations is explored.

Keywords: research agenda, user model, learner model, higher education, adaptive educational digital learning environments, personalized learning paths, recommendation system, adaptation, personalization

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Authors: T. Holecki, J. Wozniak-Holecka, P. Romaniuk

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Due to the highly centralized model of financing health care in Poland, local self-government rarely undertook their own initiatives in the field of public health, particularly health promotion. However, since 2017 the possibility of applying for a subsidy to health policy programs has been allowed, with the additional resources to be retrieved from the National Health Fund, which is the dominant payer in the health system. The amount of subsidy depends on the number of inhabitants in a given unit and ranges about 40% of the total cost of the program. The aim of this paper is to assess the impact of newly implemented solutions in financing health policy on the management of public finances, as well as on the activity provided by local self-government in health promotion. An effort to estimate the amount of expenses that both local governments, and the National Health Fund, spent on local health policy programs while implementing the new solutions. The research method is the analysis of financial data obtained from the National Health Fund and from local government units, as well as reports published by the Agency for Health Technology Assessment and Pricing, which holds substantive control over the health policy programs, and releases permission for their implementation. The study was based on a comparative analysis of expenditures on the implementation of health programs in Poland in years 2010-2018. The presentation of the results includes the inclusion of average annual expenditures of local government units per 1 inhabitant, the total number of positively evaluated applications and the percentage share in total expenditures of local governments (16 voivodships areas). The most essential purpose is to determine whether the assumptions of the subsidy program are working correctly in practice, and what are the real effects of introducing legislative changes into local government levels in the context of public health tasks. The assumption of the study was that the use of a new motivation tool in the field of public management would result in multiplication of resources invested in the provision of health policy programs. Preliminary conclusions show that financial expenditures changed significantly after the introduction of public funding at the level of 40%, obtaining an increase in funding from own funds of local governments at the level of 80 to 90%.

Keywords: health care system, health policy programs, local self-governments, public health management

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Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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Authors: Nadish Anand, Richard D. Gould

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A simplistic model is introduced for determining the thermal characteristics of a Low-rise Residential (LRR) building and then predicts the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to changes in weather conditions which are reflected in the Ambient Temperature (Outside Air Temperature). The LRR buildings are treated as a simple lump for solving the heat transfer problem and the model is derived using the lumped capacitance model of transient conduction heat transfer from bodies. Since most contemporary HVAC systems have a thermostat control which will have an offset temperature and user defined set point temperatures which define when the HVAC system will switch on and off. The aim is to predict without any error the Body Temperature (i.e. the Inside Air Temperature) which will estimate the switching on and off of the HVAC system. To validate the mathematical model derived from lumped capacitance we have used EnergyPlus simulation engine, which simulates Buildings with considerable accuracy. We have predicted through the low order model the Inside Air Temperature of a single house kept in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error from the model for the same day as that of model parameter calculation has showed an error of < 10% in winter for almost all the orientations and climate zones. Whereas the prediction error is only <10% for all the orientations in the summer season for climate zone at higher latitudes (Raleigh & Detroit). Possible factors responsible for the large variations are also noted in the work, paving way for future research.

Keywords: building energy, energy consumption, energy+, HVAC, low order model, lumped capacitance

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Authors: Zainab Fadhil Al Toki, Nader Ghareeb

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This study investigates how lightweight a fire resistance door will perform with under types of insulation materials. Data is initially collected from various websites, scientific books and research papers. Results show that different layers of insulation in a single door can perform better than one insulator. Furthermore, insulation materials that are lightweight, high strength and low thermal conductivity are the most preferred for fire-rated doors. Whereas heavy weight, low strength, and high thermal conductivity are least preferred for fire resistance doors. Fire-rated door specifications, theoretical test methodology, structural analysis, and comparison between five different models with diverse layers insulations are presented. Five different door models are being investigated with different insulation materials and arrangements. Model 1 contains an air gap between door layers. Model 2 includes phenolic foam, mild steel and polyurethane. Model 3 includes phenolic foam and glass wool. Model 4 includes polyurethane and glass wool. Model 5 includes only rock wool between the door layers. It is noticed that model 5 is the most efficient model, and its design is simple compared to other models. For this model, numerical calculations are performed to check its efficiency and the results are compared to data from experiments for validation. Good agreement was noticed.

Keywords: fire resistance, insulation, strength, thermal conductivity, lightweight, layers

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Authors: Kolesnik Nadezda A.

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The research aims to elaborate inter-organizational network relationships management model to maximize value co-creation. We propose a network management framework that requires evaluation of network partners with respect to their position and role in network; and elaboration of appropriate relationship development strategy with partners in network. Empirical research and approval is based on the case study method, including structured in-depth interviews with the companies from b2b market.

Keywords: inter-organizational networks, value co-creation, model, B2B market

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Authors: Hamda M. Al-Ali

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The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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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

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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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

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Authors: Khaled Mammar

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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

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Authors: Seyed-Mohammad-Kazem Emami, Behrang Saki, Majid Mohammadian

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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

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Authors: Luedech Girdwichai, Withaya Mekhum

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This research intended to develop the model of community management for sustainable utilization by investigating on 2 groups of population, the family heads and the community management team. The population of the former group consisted of family heads from 511 families in 12 areas to complete the questionnaires which were returned at 479 sets. The latter group consisted of the community management team of 12 areas with 1 representative from each area to give the interview. The questionnaires for the family heads consisted of 2 main parts; general information such as occupations, etc. in the form of checklist. The second part dealt with the data on self reliance community development based on 4P Framework, i.e., People (human resource) development, Place (area) development, Product (economic and income source) development, and Plan (community plan) development in the form of rating scales. Data in the 1st part were calculated to find frequency and percentage while those in the 2nd part were analyzed to find arithmetic mean and SD. Data from the 2nd group of population or the community management team were derived from focus group to find factors influencing successful management together with the in depth interview which were analyzed by descriptive statistics. The results showed that 479 family heads reported that the aspect on the implementation of community plan to self reliance community activities based on Sufficient Economy Philosophy and the 4P was at the average of 3.28 or moderate level. When considering in details, it was found that the 1st aspect was on the area development with the mean of 3.71 or high level followed by human resource development with the mean of 3.44 or moderate level, then, economic and source of income development with the mean of 3.09 or moderate level. The last aspect was community plan development with the mean of 2.89. The results from the small group discussion revealed some factors and guidelines for successful community management as follows: 1) on the People (human resource) development aspect, there was a project to support and develop community leaders. 2) On the aspect of Place (area) development, there was a development on conservative tourism areas. 3) On the aspect of Product (economic and source of income) development, the community leaders promoted the setting of occupational group, saving group, and product processing group. 4) On the aspect of Plan (community plan) development, there was a prioritization through public hearing.

Keywords: model of community management, sustainable utilization, family heads, community management team

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Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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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

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Authors: Beata Ślusarczyk, Sebastian Kot

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In subjective terms, Polish SME sector occupies a prominent position in the national economic development, in which planning of the management strategies should be primarily based on identifying and meeting the innovation needs. As a research sample, there is chosen a printing sector of industry. SMEs share in printing sector in Poland is estimated at the level of 81% of all enterprises. In recent years, the printing industry achieved one of the highest levels of EU support in Poland. There is a relatively high increase in the development of technological innovations in equipment and the associated significant increase in production capacity. It can be also noticed that on average, every third enterprise belonging to the printing industry has implemented innovations, but not all of them effected in better economic results. Therefore, the aim of this article is to evaluate the impact of the implementation of innovation projects financed from the EU funds for performance of SMEs in the printing industry. As the results of research of EU funds co-financing effects on the development of innovation in the printing industry, it was specified that examined SMEs prefer to implement product innovation to receive a grant to the project at a level between 40% to 60%, the remaining part of the investment is usually covered with equity. The most common type of innovation had indicated a single implementation, related only to the change in process, technology, or organization. The relationship between variables of the EU funds and management of innovative activities was verified. It has been observed that the identified variables arising from the support in a form of the EU funds had a positive effect on the level of earned revenue, the increase in margin and in increase in employment as well. It was confirmed that the implemented innovations supported by the European funds have a positive impact on the performance of the printing companies. Although there is a risk that due to the decreasing demand for printing services such a high level of funding the companies in this sector will significantly increase competition in the long term, that may also contribute to the economic problems of the enterprises belonging to the analyzed branch.

Keywords: innovations, SMEs, performance, results

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Authors: Arian Ebneyamini, Hoda Azimi, Jules Thibaults, F. Handan Tezel

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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

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Authors: Fethi Bouksila, Magnus Persson, Ronny Berndtsson, Akissa Bahri

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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

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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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

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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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

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Authors: Nataliya Venelinova

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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

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Authors: Adil Loya, Ali Haider, Arslan A. Ghaffor, Abubaker Siddique

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Simulation and modelling of Unmanned Aero Vehicle (UAV) has gained wide popularity in front of aerospace community. The demand of designing and modelling optimized control system for UAV has increased ten folds since last decade. The reason is next generation warfare is dependent on unmanned technologies. Therefore, this research focuses on the simulation of nonlinear UAV dynamics on Simulink and its integration with Flightgear. There has been lots of research on implementation of optimizing control using Simulink, however, there are fewer known techniques to simulate these dynamics over Flightgear and a tedious technique of acquiring data has been tackled in this research horizon. Sending data to Flightgear is easy but receiving it from Simulink is not that straight forward, i.e. we can only receive control data on the output. However, in this research we have managed to get the data out from the Flightgear by implementation of level 2 s-function block within Simulink. Moreover, the results captured from Flightgear over a Universal Datagram Protocol (UDP) communication are then compared with the attitude signal that were sent previously. This provide useful information regarding the difference in outputs attained from Simulink to Flightgear. It was found that values received on Simulink were in high agreement with that of the Flightgear output. And complete study has been conducted in a discrete way.

Keywords: aerospace, flight control, flightgear, communication, Simulink

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Authors: Hung-Chi Chang

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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

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Authors: Watchareeporn Chaimongkol

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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

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

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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

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Authors: Kumudini Achchi

Abstract:

India, being known for its rich cultural values has given a special place to women who are also been victims of humiliation, torture, and exploitation. The major share of Human Trafficking goes to sex trafficking which is recognised as world’s second most huge social evil. The original form of sex trafficking in India is prostitution with and without religious sanction. Today the situation of such women reached as an issue of human rights where they rights are denied severely. This situation demanded intervention to protect them from the exploitative situation. NGO are the proactive initiatives which offer support to the exploited women in sex trade. To understand the intervention programs of NGOs in South India, a study was conducted covering four states and a union territory considering 32 NGOs based on their preparedness to participate in the research study. Descriptive and diagnostic research design was adopted along with interview schedule as a tool for collecting data. The study reveals that these NGOs believes in the possibility of mainstreaming commercially sexually exploited women and found adopted seven different programs in the process such as rescue, rehabilitation, reintegration, prevention, developmental, advocacy and research. Each area involves different programs to reach and prepare the exploited women towards mainstreamed society which has been discussed in the paper. Implementation of these programs is not an easy task for the organizations rather they are facing hardships in the areas such as social, legal, financial, political which are hindering the successful operations. Rescue, advocacy, and research are the least adopted areas by the NGOs because of lack of support as well as knowledge in the area. Rehabilitation stands as the most adopted area in implementation. The paper further deals with the challenges in the implementation of the programs as well as the remedial measures in social work point of view having Indian cultural background.

Keywords: NGOs, commercially sexually exploited women, programmes, South India

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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

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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

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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

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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 322