Search results for: loss model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19130

Search results for: loss model

18170 Media Richness Perspective on Web 2.0 Usage for Knowledge Creation: The Case of the Cocoa Industry in Ghana

Authors: Albert Gyamfi

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Cocoa plays critical role in the socio-economic development of Ghana. Meanwhile, smallholder farmers most of whom are illiterate dominate the industry. According to the cocoa-based agricultural knowledge and information system (AKIS) model knowledge is created and transferred to the industry between three key actors: cocoa researchers, extension experts, and cocoa farmers. Dwelling on the SECI model, the media richness theory (MRT), and the AKIS model, a conceptual model of web 2.0-based AKIS model (AKIS 2.0) is developed and used to assess the possible effects of social media usage for knowledge creation in the Ghanaian cocoa industry. A mixed method approach with a survey questionnaire was employed, and a second-order multi-group structural equation model (SEM) was used to analyze the data. The study concludes that the use of web 2.0 applications for knowledge creation would lead to sustainable interactions among the key knowledge actors for effective knowledge creation in the cocoa industry in Ghana.

Keywords: agriculture, cocoa, knowledge, media, web 2.0

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18169 Prediction of Terrorist Activities in Nigeria using Bayesian Neural Network with Heterogeneous Transfer Functions

Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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18168 Artificial Neural Network Based Approach for Estimation of Individual Vehicle Speed under Mixed Traffic Condition

Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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18167 Personality, Coping, Quality of Life, and Distress in Persons with Hearing Loss: A Cross-Sectional Study of Patients Referred to an Audiological Service

Authors: Oyvind Nordvik, Peder O. L. Heggdal, Jonas Brannstrom, Flemming Vassbotn, Anne Kari Aarstad, Hans Jorgen Aarstad

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Background: Hearing Loss (HL) is a condition that may affect people in all stages of life, but the prevalence increases with age, mostly because of age-related HL, generally referred to as presbyacusis. As human speech is related to relatively high frequencies, even a limited hearing loss at high frequencies may cause impaired speech intelligibility. Being diagnosed with, treated for and living with a chronic condition such as HL, must for many be a disabling and stressful condition that put ones coping resources to test. Stress is a natural part of life and most people will experience stressful events or periods. Chronic diseases, such as HL, are risk factor for distress in individuals, causing anxiety and lowered mood. How an individual cope with HL may be closely connected to the level of distress he or she is experiencing and to personality, which can be defined as those characteristics of a person that account for consistent patterns of feelings, thinking, and behavior. Thus, as to distress in life, such as illness or disease, available coping strategies may be more important than the challenge itself. The same line of arguments applies to level of experienced health-related quality of life (HRQoL). Aim: The aim of this study was to investigate the relationship between distress, HRQoL, reported hearing loss, personality and coping in patients with HL. Method: 158 adult (aged 18-78 years) patients with HL, referred for hearing aid (HA) fitting at Haukeland University Hospital in western Norway, participated in the study. Both first-time users, as well as patients referred for HA renewals were included. First-time users had been pre-examined by an ENT-specialist. The questionnaires were answered before the actual HA fitting procedure. The pure-tone average (PTA; frequencies 0.5, 1, 2, and 4 kHz) was determined for each ear. The Eysenck personality inventory, neuroticism and lie scales, the Theoretically Originated Measure of the Cognitive Activation Theory of Stress (TOMCATS) measuring active coping, hopelessness and helplessness, as well as distress (General Health Questionnaire (GHQ) - 12 items) and the EORTC Quality of Life Questionnaire general part were answered. In addition, we used a revised and shortened version of the Abbreviated Profile of Hearing Aid Benefit (APHAB) as a measure of patient-reported hearing loss. Results: Significant correlations were determined between APHAB (weak), HRQoL scores (strong), distress scores (strong) on the one side and personality and choice of coping scores on the other side. As measured by stepwise regression analyses, the distress and HRQoL scores were scored secondary to the obtained personality and coping scores. The APHAB scores were as determined by regression analyses scored secondary to PTA (best ear), level of neuroticism and lie score. Conclusion: We found that reported employed coping style, distress/HRQoL and personality are closely connected to each other in this patient group. Patient-reported HL was associated to hearing level and personality. There is need for further investigations on these questions, and how these associations may influence the clinical context.

Keywords: coping, distress, hearing loss, personality

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18166 Hope as a Predictor for Complicated Grief and Anxiety: A Bayesian Structural Equational Modeling Study

Authors: Bo Yan, Amy Y. M. Chow

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Bereavement is recognized as a universal challenging experience. It is important to gather research evidence on protective factors in bereavement. Hope is considered as one of the protective factors in previous coping studies. The present study aims to add knowledge by investigating hope at the first month after death to predict psychological symptoms altogether including complicated grief (CG), anxiety, and depressive symptoms at the seventh month. The data were collected via one-on-one interview survey in a longitudinal project with Hong Kong hospice users (sample size 105). Most participants were at their middle age (49-year-old on average), female (72%), with no religious affiliation (58%). Bayesian Structural Equation Modeling (BSEM) analysis was conducted on the longitudinal dataset. The BSEM findings show that hope at the first month of bereavement negatively predicts both CG and anxiety symptoms at the seventh month but not for depressive symptoms. Age and gender are controlled in the model. The overall model fit is good. The current study findings suggest assessing hope at the first month of bereavement. Hope at the first month after the loss is identified as an excellent predictor for complicated grief and anxiety symptoms at the seventh month. The result from this sample is clear, so it encourages cross-cultural research on replicated modeling and development of further clinical application. Particularly, practical consideration for early intervention to increase the level of hope has the potential to reduce the psychological symptoms and thus to improve the bereaved persons’ wellbeing in the long run.

Keywords: anxiety, complicated grief, depressive symptoms, hope, structural equational modeling

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18165 Half Mode Substrate Integrated Wave Guide of Band Pass Filter Based to Defected Ground Structure Cells

Authors: Damou Mehdi, Nouri Keltoum, Feham Mohammed, Khazini Mohammed, Bouazza Tayb Habibi Chawki

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The Half mode SIW filter is treated by two softwares (HFSS (High Frequency Structure Simulator) and CST (Computer Simulation Technology)). The filter HMSIW has a very simple structure and a very compact size. The simulated results by CST are presented and compared with the results simulated by a high-frequency structure simulator. Good agreement between the simulated CST and simulated results by HFSS is observed. By cascading two of them according to design requirement, a X-band bandpass filter is designed and simulated to meet compact size, low insertion loss, good return loss as well as second harmonic suppression. As an example, we designed the proposed HMSIW filter at X band by HFSS. The filter has a pass-band from 7.3 GHz to 9.8 GHz, and its relative operating fraction bandwidth is 29.5 %. There are one transmission zeros are located at 14.4 GHz.

Keywords: substrate integrated waveguide, filter, HMSIW, defected ground structures (DGS), simulation BPF

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18164 Microstrip Bandpass Filter with Wide Stopband and High Out-of-Band Rejection Based on Inter-Digital Capacitor

Authors: Mohamad Farhat, Bal Virdee

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This paper present a compact Microstrip Bandpass filter exhibiting a very wide stop band and high selectivity. The filter comprises of asymmetric resonator structures, which are interconnected by an inter-digital capacitor to enable the realization of a wide bandwidth with high rejection level. High selectivity is obtained by optimizing the parameters of the interdigital capacitor. The filter has high out-of-band rejection (> 30 dB), less than 0.6 dB of insertion-loss, up to 5.5 GHz spurii free, and about 18 dB of return-loss. Full-wave electromagnetic simulator ADSTM (Mom) is used to analyze and optimize the prototype bandpass filter. The proposed technique was verified practically to validate the design methodology. The experimental results of the prototype circuit are presented and a good agreement was obtained comparing with the simulation results. The dimensions of the proposed filter are 32 x 24 mm2.The filter’s characteristics and compact size make it suitable for wireless communication systems.

Keywords: asymmetric resonator, bandpass filter, microstrip, spurious suppression, ultra-wide stop band

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18163 A Comparison of Inverse Simulation-Based Fault Detection in a Simple Robotic Rover with a Traditional Model-Based Method

Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: fault detection, ground robot, inverse simulation, rover

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18162 Redirection of Cytokine Production Patterns by Dydrogesterone, an Orally-Administered Progestogen

Authors: Raj Raghupathy

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Recurrent Spontaneous Miscarriage (RSM) is a common form of pregnancy loss, 50% of which are due to ‘unexplained’ causes. Evidence exists to suggest that RSM may be caused by immunologic factors such as cytokines which are critical molecules of the immune system, with an impressive array of capabilities. An association appears to exist between Th2-type reactivity (mediated by Th2 or anti-inflammatory cytokines) and normal, successful pregnancy, and between unexplained RSM and Th1 cytokine dominance. If pro-inflammatory cytokines are indeed associated with pregnancy loss, the suppression of these cytokines, and thus the ‘redirection’ of maternal reactivity, may help prevent cytokine-mediated pregnancy loss. The objective of this study was to explore the possibility of modulating cytokine production using Dydrogesterone (Duphaston®), an orally-administered progestogen. Peripheral blood mononuclear cells from 34 women with a history of at least 3 unexplained recurrent miscarriages were stimulated in vitro with a mitogen (to elicit cytokine production) in the presence and absence of dydrogesterone. Levels of selected pro- and anti-inflammatory cytokines produced by peripheral blood mononuclear cells were measured after exposure to these progestogens. Dydrogesterone down-regulates the production of pro-inflammatory cytokines and up-regulates the production of anti-inflammatory cytokines. The ratios of Th2 to Th1 cytokines are markedly elevated in the presence of dydrogesterone, indicating a shift from potentially harmful maternal Th1 reactivity to a more pregnancy-conducive Th2 profile. We used a progesterone receptor antagonist to show that this cytokine-modulating effect of dydrogesterone is mediated via the progesterone receptor. Dydrogesterone also induces the production of the Progesterone-Induced Blocking Factor (PIBF); lymphocytes exposed to PIBF produce higher levels of Th2 cytokines, affecting a Th1 → Th2 cytokine shift which could be favourable to the success of pregnancy. We conclude that modulation of maternal cytokine production profiles is possible with dydrogesterone which has the merits that it can be administered orally and that it is safe.

Keywords: cytokines, dydrogesterone, progesterone, recurrent spontaneous miscarriage

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18161 Computational Fluid Dynamics Analysis and Optimization of the Coanda Unmanned Aerial Vehicle Platform

Authors: Nigel Q. Kelly, Zaid Siddiqi, Jin W. Lee

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It is known that using Coanda aerosurfaces can drastically augment the lift forces when applied to an Unmanned Aerial Vehicle (UAV) platform. However, Coanda saucer UAVs, which commonly use a dish-like, radially-extending structure, have shown no significant increases in thrust/lift force and therefore have never been commercially successful: the additional thrust/lift generated by the Coanda surface diminishes since the airstreams emerging from the rotor compartment expand radially causing serious loss of momentums and therefore a net loss of total thrust/lift. To overcome this technical weakness, we propose to examine a Coanda surface of straight, cylindrical design and optimize its geometry for highest thrust/lift utilizing computational fluid dynamics software ANSYS Fluent®. The results of this study reveal that a Coanda UAV configured with 4 sides of straight, cylindrical Coanda surface achieve an overall 45% increase in lift compared to conventional Coanda Saucer UAV configurations. This venture integrates with an ongoing research project where a Coanda prototype is being assembled. Additionally, a custom thrust-stand has been constructed for thrust/lift measurement.

Keywords: CFD, Coanda, lift, UAV

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18160 Interaction between the Rio Conventions on Climate and Biodiversity: Analysis of the Integration of Ecosystem-Based Approaches and Nature-Based Solutions into the UNFCCC

Authors: Dieudonne Mevono Mvogo

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The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES)-Intergovernmental Panel on Climate Change (IPCC) co-sponsored workshop report suggests that climate change and biodiversity loss are two of the most pressing issues of the Anthropocene. Research establishes the interconnection between climate change and biodiversity. On the one hand, the impact of climate change on biodiversity loss – 14 % over the past century – is projected to surpass other threats – land and sea use 34 % and direct exploitation of species 23 % – during the 21st century. Response measures to climate change also affect biodiversity negatively or positively. On the other hand, actions to halt or reverse biodiversity loss can enhance land and ocean capacity for carbon sequestration. These actions can also promote adaptation by ensuring adaptive capacity. This systemic interaction between climate change and biodiversity affects the human quality of life. The United Nations Secretariat's report entitled 'Gaps in international environmental law and environment-related instruments: towards a global pact for the environment,' released in 2018, states that cooperation and mutual support among agreements dealing with climate change, the protection of the marine environment, freshwater resources and hazardous waste are indispensable for the effective implementation of the Convention on the Biological Diversity (CBD). Since biodiversity is being lost at an alarming rate, this study aims to evaluate the cooperative framework for the coherence and coordination between climate change and biodiversity regimes to provide co-benefits for climate and biodiversity crises. It questions the potential improvement regarding integrating ecosystem-based approaches and nature-based solutions – promoted by the CBD – into the United Nations Framework Convention on Climate Change (UNFCCC).

Keywords: rio conventions, climate change, biodiversity, cooperative framework, ecosystem-based approaches, nature-based solutions

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18159 Production Factor Coefficients Transition through the Lens of State Space Model

Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

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18158 An Analysis of Socio-Demographics, Living Conditions, and Physical and Emotional Child Abuse Patterns in the Context of the 2010 Haiti Earthquake

Authors: Sony Subedi, Colleen Davison, Susan Bartels

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Objective: The aim of this study is to i) investigate the socio-demographics and living conditions of households in Haiti pre- and post 2010 earthquake, ii) determine the household prevalence of emotional and physical abuse in children (aged 2-14) after the earthquake, and iii) explore the association between earthquake-related loss and experience of emotional and physical child abuse in the household while considering potential confounding variables and the interactive effects of a number of social, economic, and demographic factors. Methods: A nationally representative sample of Haitian households from the 2005/6 and 2012 phases of the Demographic and Health Surveys (DHS) was used. Descriptive analysis was summarized using frequencies and measures of central tendency. Chi-squared and independent t-tests were used to compare data that was available pre-earthquake and post-earthquake. The association between experiences of earthquake-related loss and emotional and physical child abuse was assessed using log-binomial regression models. Results: Comparing pre-post-earthquake, noteworthy improvements were observed in the educational attainment of the household head (9.1% decrease in “no education” category) and in possession of the following household items: electricity, television, mobile-phone, and radio post-earthquake. Approximately 77.0% of children aged 2-14 experienced at least one form of physical abuse and 78.5% of children experienced at least one form of emotional abuse one month prior to the 2012 survey period. Analysis regarding the third objective (association between experiences of earthquake-related loss and emotional and physical child abuse) is in progress. Conclusions: The extremely high prevalence of emotional and physical child abuse in Haiti indicates an immediate need for improvements in the enforcement of existing policies and interventions aimed at decreasing child abuse in the household.

Keywords: Haiti earthquake, physical abuse, emotional abuse, natural disasters, children

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18157 Modeling Heat-Related Mortality Based on Greenhouse Emissions in OECD Countries

Authors: Anderson Ngowa Chembe, John Olukuru

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Greenhouse emissions by human activities are known to irreversibly increase global temperatures through the greenhouse effect. This study seeks to propose a mortality model with sensitivity to heat-change effects as one of the underlying parameters in the model. As such, the study sought to establish the relationship between greenhouse emissions and mortality indices in five OECD countries (USA, UK, Japan, Canada & Germany). Upon the establishment of the relationship using correlation analysis, an additional parameter that accounts for the sensitivity of heat-changes to mortality rates was incorporated in the Lee-Carter model. Based on the proposed model, new parameter estimates were calculated using iterative algorithms for optimization. Finally, the goodness of fit for the original Lee-Carter model and the proposed model were compared using deviance comparison. The proposed model provides a better fit to mortality rates especially in USA, UK and Germany where the mortality indices have a strong positive correlation with the level of greenhouse emissions. The results of this study are of particular importance to actuaries, demographers and climate-risk experts who seek to use better mortality-modeling techniques in the wake of heat effects caused by increased greenhouse emissions.

Keywords: climate risk, greenhouse emissions, Lee-Carter model, OECD

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18156 Analyzing the Effect of Biomass and Cementitious Materials on Air Content in Concrete

Authors: Mohammed Albahttiti, Eliana Aguilar

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A push for sustainability in the concrete industry is increasing. Cow manure itself is becoming a problem and having the potential solution to use it in concrete as a cementitious replacement would be an ideal solution. For cow manure ash to become a well-rounded substitute, it would have to meet the right criteria to progress in becoming a more popular idea in the concrete industry. This investigation primarily focuses on how the replacement of cow manure ash affects the air content and air void distribution in concrete. In order to assess these parameters, the Super Air Meter (SAM) was used to test concrete in this research. In addition, multiple additional tests were performed, which included the slump test, temperature, and compression test. The strength results of the manure ash in concrete were promising. The manure showed compression strength results that are similar to that of the other supplementary cementitious materials tested. On the other hand, concrete samples made with cow manure ash showed 2% air content loss and an increasing SAM number proportional to cow manure content starting at 0.38 and increasing to 0.8. In conclusion, while the use of cow manure results in loss of air content, it results in compressive strengths similar to other supplementary cementitious materials.

Keywords: air content, biomass ash, cow manure ash, super air meter, supplementary cementitious materials

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18155 Design Channel Non Persistent CSMA MAC Protocol Model for Complex Wireless Systems Based on SoC

Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa

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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).

Keywords: systemC, modelling, simulation, CSMA

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18154 A Deep Learning Based Integrated Model For Spatial Flood Prediction

Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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18153 Drought Stress and the Importance of Osmotic Adjustment

Authors: Hooman Rowshanaie

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The majority of green plants have 70%-90% water, this amount depend on age of plants, species, tissues of plants and also the environmental conditions that plants growth and development on it. Because of intense plant demanding to achieve the available water for growing and developing, always plants need a water sources and also mechanisms to retention the water and reduction water loss under critical situation and water deficit conditions otherwise the yield of plants would be decreased. Decreasing the yield depend on genotypes, intense of water deficit and also growth stage. Recently the mechanisms and also compound that have major role to water stress adaption of plants would be consideration. Osmotic adjustment is one of the most important mechanisms in terms of this field that many valuable researches focused on it because the majority of organic and inorganic solutes directly or even indirectly have pivotal role in this phenomenon. The contribution of OA to prevent water loss in response to water deficit and resistance to water stress taken to consideration recently and also the organic and inorganic compounds to OA tended has a high rate of significant.

Keywords: water deficit, drought stress, osmotic adjustment, organic compound, inorganic compound, solute

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18152 Simulation of Ester Based Mud Performance through Drilling Genting Timur Field

Authors: Lina Ismail Jassim, Robiah Yunus

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To successfully drill oil or gas well, two main characteristics of numerous other tasks of an efficient drilling fluid are required, which are suspended and carrying cuttings from the beneath wellbore to the surface and managed between pore (formation) and hydrostatic pressure (mud pressure). Several factors like mud composition and its rheology, wellbore design, drilled cuttings characteristics and drilling string rotation contribute to drill wellbore successfully. Simulation model can support an appropriate indication on the drilling fluid performance in the real field as Genting Timur field, located in Pahang in Malaysia on 4295 m depth, held the world record in Sempah Muda 1 (Vertical). A detailed 3 dimensional CFD analysis of vertical, concentric annular two phase flow was developed to study and asses Herschel Bulkley drilling fluid. The effect of Hematite, Barite and calcium carbonates types and size of cutting rock particles on such flow is analyzed. The vertical flows are also associated with a good amount of temperature variation along the depth. This causes a good amount of change in viscosity of the fluid, which is non-Newtonian in nature. Good understanding of the nature of such flows is imperative in developing and maintaining successful vertical well systems. A detailed analysis of flow characteristics due to the drill pipe rotation is done in this work. The inner cylinder of the annulus gets different rotational speed, depending upon the operating conditions. This speed induces a good swirl on the particles and primary fluids which interpret in Ester based drilling fluid cleaning well ability, which in turn determines energy loss along the pipe. Energy loss is assessed in this work in terms of wall shear stress and pressure drop along the pipe. The flow is under an adverse pressure gradient condition, which causes chance of reversed flow and transfers the rock cuttings to the surface.

Keywords: concentric annulus, non-Newtonian, two phase, Herschel Bulkley

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18151 Model of Transhipment and Routing Applied to the Cargo Sector in Small and Medium Enterprises of Bogotá, Colombia

Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca

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This paper presents a design of a model for planning the distribution logistics operation. The significance of this work relies on the applicability of this fact to the analysis of small and medium enterprises (SMEs) of dry freight in Bogotá. Two stages constitute this implementation: the first one is the place where optimal planning is achieved through a hybrid model developed with mixed integer programming, which considers the transhipment operation based on a combined load allocation model as a classic transshipment model; the second one is the specific routing of that operation through the heuristics of Clark and Wright. As a result, an integral model is obtained to carry out the step by step planning of the distribution of dry freight for SMEs in Bogotá. In this manner, optimum assignments are established by utilizing transshipment centers with that purpose of determining the specific routing based on the shortest distance traveled.

Keywords: transshipment model, mixed integer programming, saving algorithm, dry freight transportation

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18150 A Model for Predicting Organic Compounds Concentration Change in Water Associated with Horizontal Hydraulic Fracturing

Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo

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Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.

Keywords: model, shale gas, concentration, organic compounds

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18149 Unified Structured Process for Health Analytics

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

Abstract:

Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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18148 Effect of Exercise Training on Body Composition and Metabolic Profile in Older Adults during Cancer Treatment

Authors: Adeline Fontvieille, Hugo Parent-Roberge, Marie-France Langlois, Tamas Fulop, Michel Pavic, Eleonor Riesco

Abstract:

Introduction: Total lean body mass is reduced during cancer treatment. This loss is called cancer cachexia and is accompanied by a progressive loss of fat mass. In older adults, these body composition changes can have a larger impact on metabolic health, physical autonomy, and cancer survival. Although currently untreatable, exercise training could reduce these effects. Hence, the objective of this pilot study is to investigate if 12 weeks of exercise training during cancer treatment can mitigate the loss of muscle mass and fat mass in older adults. Methods: A total of 40 older adults (65-80 years) with an ongoing treatment for a curable cancer are currently recruited and randomised in two groups: 1) Combined training (EX, n=20) and 2) Control group (CON, n=20). All variables are measured before and after 12 weeks of intervention: Anthropometry (weight, height, body mass index), body composition (total fat mass, visceral adipose tissue, total and appendicular muscle mass; DXA), metabolic profile (HDL-C and LDL-C, triglycerides, glucose and insulin levels). Results: Preliminary analyses revealed no impact of exercise training on appendicular muscle mass (p=0,31) and fat mass (p=0,31). Furthermore, total body weight, waist circumference, HDL-cholesterol, LDL-cholesterol, glucose and insulin levels remained unchanged (all p ≥ 0.79) after 12 weeks of training. However, statistical analyses revealed that triglyceride levels slightly increased (p=0.03), irrespective of the group. Conclusion: Preliminary analyses did not reveal any impact of aerobic and resistance exercise training on body composition in oncogeriatric patients. Furthermore, exercise training seems not efficient to prevent the cancer treatment-related triglyceride levels increase.

Keywords: muscle mass, fat mass, metabolic profile, combined training, aging, cancer

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18147 Weighted Rank Regression with Adaptive Penalty Function

Authors: Kang-Mo Jung

Abstract:

The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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18146 A Novel RLS Based Adaptive Filtering Method for Speech Enhancement

Authors: Pogula Rakesh, T. Kishore Kumar

Abstract:

Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

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18145 Analysis of the Temperature Dependence of Local Avalanche Compact Model for Bipolar Transistors

Authors: Robert Setekera, Ramses van der Toorn

Abstract:

We present an extensive analysis of the temperature dependence of the local avalanche model used in most of the modern compact models for bipolar transistors. This local avalanche model uses the Chynoweth's empirical law for ionization coefficient to define the generation of the avalanche current in terms of the local electric field. We carry out the model analysis using DC-measurements taken on both Si and advanced SiGe bipolar transistors. For the advanced industrial SiGe-HBTs, we consider both high-speed and high-power devices (both NPN and PNP transistors). The limitations of the local avalanche model in modeling the temperature dependence of the avalanche current mostly in the weak avalanche region are demonstrated. In addition, the model avalanche parameters are analyzed to see if they are in agreement with semiconductor device physics.

Keywords: avalanche multiplication, avalanche current, bipolar transistors, compact modeling, electric field, impact ionization, local avalanche

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18144 Special Case of Trip Distribution Model and Its Use for Estimation of Detailed Transport Demand in the Czech Republic

Authors: Jiri Dufek

Abstract:

The national model of the Czech Republic has been modified in a detailed way to get detailed travel demand in the municipality level (cities, villages over 300 inhabitants). As a technique for this detailed modelling, three-dimensional procedure for calibrating gravity models, was used. Besides of zone production and attraction, which is usual in gravity models, the next additional parameter for trip distribution was introduced. Usually it is called by “third dimension”. In the model, this parameter is a demand between regions. The distribution procedure involved calculation of appropriate skim matrices and its multiplication by three coefficients obtained by iterative balancing of production, attraction and third dimension. This type of trip distribution was processed in R-project and the results were used in the Czech Republic transport model, created in PTV Vision. This process generated more precise results in local level od the model (towns, villages)

Keywords: trip distribution, three dimension, transport model, municipalities

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18143 Exploring Perceptions of Local Stakeholders in Climate Change Adaptation in Central and Western Terai, Nepal

Authors: Shree Kumar Maharjan

Abstract:

Climate change has varied impacts on diverse livelihood sectors, which is more prominent at the community level. The stakeholders and local institutions have been supporting the communities either by building adaptive capacities and resilience or minimizing the impacts of different adaptation interventions. Some of these interventions are effective, whereas others need further dynamisms and exertions considering the complexity of the risks and vulnerabilities. Hence, consolidated efforts of concerned stakeholders are required to minimize and adapt the present and future impacts. This study digs out and analyses the perceptions of local stakeholders in climate change adaptation in Madi and Deukhuri valleys of Nepal through a questionnaire survey. The study has categorized the local stakeholders into 5 groups in the study sites – Farmers groups and cooperatives, Government, I/NGOs, Development banks and education and other organizations. The local stakeholders revealed flood, drought, cold wave and riverbank erosion as the major climatic risks and hazards found in the sites eventually impacting on the loss of agricultural production, loss of agricultural land and properties, loss of livestock, the emergence of diseases and pest. The stakeholders believed that most of the farmers dealing with these impacts based on their traditional knowledge and practices, followed by with the support of NGOs and with the help of neighbors and community. The major supports of the stakeholders to deal with these impacts were on training and awareness, risk analysis and minimization, livelihood improvement, financial support, coordination and networking and facilitation in policy formulation. The stakeholders emphasized primarily on capacity building, appropriate technologies, community-based planning and monitoring, prioritization to the poor and the marginalized and establishment of community fund respectively for building adaptive capacities.

Keywords: climate change adaptation, local stakeholders, Madi, Deukhuri, Nepal

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18142 Forecasting Unemployment Rate in Selected European Countries Using Smoothing Methods

Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

Abstract:

The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate

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18141 Simulation of Flow Patterns in Vertical Slot Fishway with Cylindrical Obstacles

Authors: Mohsen Solimani Babarsad, Payam Taheri

Abstract:

Numerical results of vertical slot fishways with and without cylinders study are presented. The simulated results and the measured data in the fishways are compared to validate the application of the model. This investigation is made using FLUENT V.6.3, a Computational Fluid Dynamics solver. Advantages of using these types of numerical tools are the possibility of avoiding the St.-Venant equations’ limitations, and turbulence can be modeled by means of different models such as the k-ε model. In general, the present study has demonstrated that the CFD model could be useful for analysis and design of vertical slot fishways with cylinders.

Keywords: slot Fish-way, CFD, k-ε model, St.-Venant equations’

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