Search results for: hybrid working models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11197

Search results for: hybrid working models

9097 A Machine Learning-based Study on the Estimation of the Threat Posed by Orbital Debris

Authors: Suhani Srivastava

Abstract:

This research delves into the classification of orbital debris through machine learning (ML): it will categorize the intensity of the threat orbital debris poses through multiple ML models to gain an insight into effectively estimating the danger specific orbital debris can pose to future space missions. As the space industry expands, orbital debris becomes a growing concern in Low Earth Orbit (LEO) because it can potentially obfuscate space missions due to the increased orbital debris pollution. Moreover, detecting orbital debris and identifying its characteristics has become a major concern in Space Situational Awareness (SSA), and prior methods of solely utilizing physics can become inconvenient in the face of the growing issue. Thus, this research focuses on approaching orbital debris concerns through machine learning, an efficient and more convenient alternative, in detecting the potential threat certain orbital debris pose. Our findings found that the Logistic regression machine worked the best with a 98% accuracy and this research has provided insight into the accuracies of specific machine learning models when classifying orbital debris. Our work would help provide space shuttle manufacturers with guidelines about mitigating risks, and it would help in providing Aerospace Engineers facilities to identify the kinds of protection that should be incorporated into objects traveling in the LEO through the predictions our models provide.

Keywords: aerospace, orbital debris, machine learning, space, space situational awareness, nasa

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9096 A Collective Intelligence Approach to Safe Artificial General Intelligence

Authors: Craig A. Kaplan

Abstract:

If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

Procedia PDF Downloads 92
9095 Gendering Science, Technology and Innovation: The Case of R&D in Turkey

Authors: Setenay Nil Doğan, Ece Oztan

Abstract:

Research and development (R&D) as a term denotes the innovative studies conducted systematically to increase knowledge and its practices. As R&D intensity of Turkey (0,84%) is quite below the EU average intensity score, it has displayed a continuous increase since the 2000s. Also, the development of human capital in R&D has been one of the basic aims of National Strategy of Science, Technology, and Innovation, and National Innovation System 2023 of Turkey. R&D is considered to one of the fields in which the gender gap is wide. The reflections of the analogy of leaky pipeline, a term used for vertical differentiation in academy can also be observed in those scientific activities related with the private sector. In the private sector, the gender gap becomes wider: the percentage of female researchers in the universities (41%) decreases to 24% in the private sector. Though half of the undergraduates and gradutes are female in Turkey, a widening gender gap is observed in terms of employment in R&D. Given this background, this paper will focus on gendered dynamics of careers in R&D through the interviews conducted with 25 female and 25 male employees, working in a university technopark and some of the large RD centers in Turkey working in several sectors such as electronics, automotive etc. Focusing on some aspects of gender differences in terms of career experiences in R&D and innovation, mobility, participation to the projects, patents and inclusion to other innovatory activities, home-work balance, it aims to explore the relationships between science, technology, innovation and gender.

Keywords: gender, innovation, R&D, science, technology

Procedia PDF Downloads 441
9094 Analysis of Linguistic Disfluencies in Bilingual Children’s Discourse

Authors: Sheena Christabel Pravin, M. Palanivelan

Abstract:

Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: bi-lingual, children who stutter, children with language impairment, hidden markov models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies

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9093 The Effect of Three-Dimensional Morphology on Vulnerability Assessment of Atherosclerotic Plaque

Authors: M. Zareh, H. Mohammadi, B. Naser

Abstract:

Atherosclerotic plaque rupture is the main trigger of heart attack and brain stroke which are the leading cause of death in developed countries. Better understanding of rupture-prone plaque can help clinicians detect vulnerable plaques- rupture prone or instable plaques- and apply immediate medical treatment to prevent these life-threatening cardiovascular events. Therefore, there are plenty of studies addressing disclosure of vulnerable plaques properties. Necrotic core and fibrous tissue are two major tissues constituting atherosclerotic plaque; using histopathological and numerical approaches, many studies have demonstrated that plaque rupture is strongly associated with a large necrotic core and a thin fibrous cap, two morphological characteristic which can be acquired by two-dimensional imaging of atherosclerotic plaque present in coronary and carotid arteries. Plaque rupture is widely considered as a mechanical failure inside plaque tissue; this failure occurs when the stress within plaque excesses the strength of tissue material; hence, finite element method, a strong numerical approach, has been extensively applied to estimate stress distribution within plaques with different compositions which is then used for assessment of various vulnerability characteristics including plaque morphology, material properties and blood pressure. This study aims to evaluate significance of three-dimensional morphology on vulnerability degree of atherosclerotic plaque. To reach this end, different two-dimensional geometrical models of atherosclerotic plaques are considered based on available data and named Main 2D Models (M2M). Then, for each of these M2Ms, two three-dimensional idealistic models are created. These two 3D models represent two possible three-dimensional morphologies which might exist for a plaque with similar 2D morphology to one of M2Ms. Finite element method is employed to estimate stress, von-Mises stress, within each 3D models. Results indicate that for each M2Ms stress can significantly varies due to possible 3D morphological changes in that plaque. Also, our results show that an atherosclerotic plaque with thick cap may experience rupture if it has a critical 3D morphology. This study highlights the effect of 3D geometry of plaque on its instability degree and suggests that 3D morphology of plaque might be necessary to more effectively and accurately assess atherosclerotic plaque vulnerability.

Keywords: atherosclerotic plaque, plaque rupture, finite element method, 3D model

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9092 Elimination Study of Organic Pollutants from Leachate Technical Landfill; Using Fenton and Photo-Fenton Systems Combined with Biological Treatment

Authors: Belahmadi M. S. O., Abdessemed A., Benchiheub M., Doukali H., Kaid Kasbah K. M.

Abstract:

The aim of this study is to evaluate the quality of leachate generated by the Batna landfill site, and to verify the performance of various advanced oxidation processes, in particular the Fenton and Photo-Fenton systems combined with biological treatment to eliminate the recalcitrant organic matter contained in this effluent, and to preserve reverse osmosis membranes used for leachate treatment. The average values obtained are compared with national and international discharge standards. The results of physico-chemical analyses show that the leachate has an alkaline pH =8.26 and a high organic load with a low oxygen content. Mineral pollution is represented by high conductivity (38.3 mS/cm), high Kjeldahl nitrogen content (1266.504 mg/L) and ammoniacal nitrogen (1098.384 mg/L). The average pollution indicator parameters measured were: BOD5 = 1483.333 mg O2 /L, COD = 99790.244 mg O 2/L, TOC = 22400 mg C/L. These parameters exceed Algerian standards. Hence, there is a necessity to treat this effluent before discharging it into the environment. A comparative study was carried out to estimate the efficiency of two oxidation processes. Under optimum reaction conditions, TOC removal efficiencies of 63.43% and 73.4% were achieved for the Fenton and Photo-Fenton processes, respectively. COD removal rates estimated at 88% and 99.5% for the Fenton and Photo- Fenton processes, respectively. In addition, the Photo-Fenton + bacteria + micro- algae hybrid treatment gave removal efficiencies of around 92.24% for TOC and 99.9% for COD; -0.5 for AOS and 0.01 for CN. The results obtained during this study showed that a hybrid approach combining the PhotoFenton process and biological treatment appears to be a highly effective alternative for achieving satisfactory treatment, which aimed at exploiting the advantages of this method in terms of organic pollutant removal.

Keywords: leachate, landfill, advanced oxidation processes, Fenton and Photo-Fenton systems, biological treatment, organic pollutants

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9091 Rural Development as a Strategy to Deter Migration in India - Re-Examining the Ideology of Cluster Development

Authors: Nandini Mohan, Thiruvengadam R. B.

Abstract:

Mahatma Gandhi advocated that the true indicator of modern India lay in the development of its villages. This has been proven with the recent outbreak of the Coronavirus pandemic and the surfacing predicament of our urban centers. Developed on the Industrialization model, the current state of the metropolis is of rampant overcrowding, high rates of unemployment, inadequate infrastructure, and resources to cater to the growing population. A majority of each city’s strength composes of the migrant population, demonstrated through the migrant crisis, a direct repercussion of COVID-19. This paper explores the ideology of how rural development can act as a tactic to counter the high rates of rural-urban migration. It establishes the need for a rural push, as India is predominantly an agrarian economy, with a vast disparity between the urban and rural centers due to its urban bias. It seeks to define development in holistic terms. It studies the models of ‘cluster’ as conceptualized by V.K.R.V. Rao, and detailed by Architect Charles Correa in his book, The New Landscape. The paper reexamines the theory of cluster development through existing models proposed by the government of India. Namely, PURA (Provision of Urban Amenities in Rural Areas), DRI (Deendayal Research Institute), and Rurban under Shyama Prasad Mukharjee Rurban Mission. It analyses the models, their strengths, weaknesses, and reasons for their failure and success to derive parameters for the ideation of an archetype model. A model of rural development that talks of the simultaneous development of existing adjacent villages, by the introduction of set unique functions, that may turn into self-sustaining clusters or agglomerations in the future, which could serve as the next step for Indian village development based on the cluster ideology.

Keywords: counter migration, models of rural development, cluster development theory, India

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9090 Industrial Ergonomics Improvement at a Refrigerator Manufacturing Company in Iran: An Approach on Interventional Ergonomics

Authors: Hassan S. Naeini

Abstract:

Nowadays a lot of people are working in several sorts of industrial sectors in which there are some risk factors which threaten human being especially in developing countries. One of the main problems which effect on workers’ health refers to Ergonomics. Ergonomics as multidisciplinary science concerns workers’ health and safety in terms of somatic and mental concepts. Surely ergonomics interventions and improvement make a better condition for workers and change the quality of working life to better condition. In this study, one of the factories in Iran which is producing some kinds of small and medium size of refrigerators was chosen as the sample. The preliminary ergonomics observation of the mentioned factory showed that there are some risk factors in terms of ergonomics aspects, so an ergonomic intervention was defined, then some ergonomic assessment methods such as NMQ,OWAS, and Environmental Ergonomic Assessment were used. Also Anthropometric measurement was done. This study shows that there are some workstations and plants which suffer some degrees of ergonomic problems. Considering with the gathered data, illumination, noise control and workstation design in metal workstation are known as the priority actions. Some parts of the mentioned interventions are ongoing actions. it seems that the mentioned intervention and workstations design make a better condition for workers, because ergonomics make a safer and more sustainable environments for human being.

Keywords: anthropometry, ergonomics, health, NMQ, OWAS

Procedia PDF Downloads 755
9089 Optimizing Inanda Dam Using Water Resources Models

Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno

Abstract:

The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective and management

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9088 Modeling of Masonry In-Filled R/C Frame to Evaluate Seismic Performance of Existing Building

Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

Abstract:

This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: masonry infill, framed structures, RC buildings, non-structural elements

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9087 2D Point Clouds Features from Radar for Helicopter Classification

Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

Abstract:

This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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9086 Speed Breaker/Pothole Detection Using Hidden Markov Models: A Deep Learning Approach

Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

Abstract:

A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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9085 Two Concurrent Convolution Neural Networks TC*CNN Model for Face Recognition Using Edge

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

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9084 Predicting Recessions with Bivariate Dynamic Probit Model: The Czech and German Case

Authors: Lukas Reznak, Maria Reznakova

Abstract:

Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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9083 A Condition-Based Maintenance Policy for Multi-Unit Systems Subject to Deterioration

Authors: Nooshin Salari, Viliam Makis

Abstract:

In this paper, we propose a condition-based maintenance policy for multi-unit systems considering the existence of economic dependency among units. We consider a system composed of N identical units, where each unit deteriorates independently. Deterioration process of each unit is modeled as a three-state continuous time homogeneous Markov chain with two working states and a failure state. The average production rate of units varies in different working states and demand rate of the system is constant. Units are inspected at equidistant time epochs, and decision regarding performing maintenance is determined by the number of units in the failure state. If the total number of units in the failure state exceeds a critical level, maintenance is initiated, where units in failed state are replaced correctively and deteriorated state units are maintained preventively. Our objective is to determine the optimal number of failed units to initiate maintenance minimizing the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. A numerical example is developed to demonstrate the proposed policy and the comparison with the corrective maintenance policy is presented.

Keywords: reliability, maintenance optimization, semi-Markov decision process, production

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9082 Factors Contributing to Work Stress Among Nurses in Hadiya Zone’s Public Hospitals, Central Ethiopia, in 2023

Authors: Asnakech Zekiwos

Abstract:

Background: Stress in nursing refers to the reactions nurses experience when faced with work demands that exceed their knowledge, skills, or ability to cope. Nursing, as a profession, is particularly susceptible to work-related stress. Methods: A cross-sectional study was conducted among 405 randomly selected nurses working in Hadiya Zone Public Hospitals from March 1 to 30, 2023. Data were collected using a pre-tested self-administered questionnaire. The data were entered using Epi-data version 3.1 and analyzed using SPSS version 20.0. Multivariable logistic regression analysis was performed to identify factors associated with the level of work stress. Variables with a p-value <0.05 were considered statistically significant. Results: In this study, 56% (95% CI 50.9-61.2) of the participants reported being stressed in their work. Several factors were found to be associated with work stress, including being female (AOR=1.94, 95% CI 1.19-3.16), rotating shifts (AOR=2.06, 95% CI 1.31-3.25), working in the intensive care unit (AOR=3.42, 95% CI 1.20-9.73), and having post-basic training (AOR=0.55, 95% CI 0.34-0.92). Conclusion: The study revealed a high level of work stress among nurses in the study area. The zonal health unit takes measures to address work stress by providing job orientation during the hiring process, rotation, and on-the-job training to help nurses cope with and manage stressful events. Stress in public hospitals and among nurses is an important issue that needs attention.

Keywords: stress, nurses, public hospitals, expanded stress scale

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9081 Using Complete Soil Particle Size Distributions for More Precise Predictions of Soil Physical and Hydraulic Properties

Authors: Habib Khodaverdiloo, Fatemeh Afrasiabi, Farrokh Asadzadeh, Martinus Th. Van Genuchten

Abstract:

The soil particle-size distribution (PSD) is known to affect a broad range of soil physical, mechanical and hydraulic properties. Complete descriptions of a PSD curve should provide more information about these properties as opposed to having only information about soil textural class or the soil sand, silt and clay (SSC) fractions. We compared the accuracy of 19 different models of the cumulative PSD in terms of fitting observed data from a large number of Iranian soils. Parameters of the six most promising models were correlated with measured values of the field saturated hydraulic conductivity (Kfs), the mean weight diameter of soil aggregates (MWD), bulk density (ρb), and porosity (∅). These same soil properties were correlated also with conventional PSD parameters (SSC fractions), selected geometric PSD parameters (notably the mean diameter dg and its standard deviation σg), and several other PSD parameters (D50 and D60). The objective was to find the best predictions of several soil physical quality indices and the soil hydraulic properties. Neither SSC nor dg, σg, D50 and D60 were found to have a significant correlation with both Kfs or logKfs, However, the parameters of several cumulative PSD models showed statistically significant correlation with Kfs and/or logKfs (|r| = 0.42 to 0.65; p ≤ 0.05). The correlation between MWD and the model parameters was generally also higher than either with SSC fraction and dg, or with D50 and D60. Porosity (∅) and the bulk density (ρb) also showed significant correlation with several PSD model parameters, with ρb additionally correlating significantly with various geometric (dg), mechanical (D50 and D60), and agronomic (clay and sand) representations of the PSD. The fitted parameters of selected PSD models furthermore showed statistically significant correlations with Kfs,, MWD and soil porosity, which may be viewed as soil quality indices. Results of this study are promising for developing more accurate pedotransfer functions.

Keywords: particle size distribution, soil texture, hydraulic conductivity, pedotransfer functions

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9080 A Study of Effective Event Development and the Sustainability of Tourism Industry in Lagos State, Nigeria

Authors: Olajumoke Elizabeth Olawale-Olakunle

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This research examined effective event development on the sustainability of tourism in Lagos State. The objectives were to ascertain the implication of effective event development on cost, environmental innovations, opportunity for participants, job creation and working conditions. Also, there was a focus on employee participation and the sustainability of the tourism industry. However, the primary data were obtained via the use of structured questionnaire administered to the selected respondents. Simple random sampling was used to select the respondents, using the Yaro Yame formula. The formulated hypothesis was tested using Analysis of Variance (ANOVA) and Non-parametric chi-square. From the tests conducted, the results showed that effective event development has helped to reduce costs, bring about environmental innovations, offer unique opportunity among event participants, create jobs and promote better working conditions, and the influence it has on employee participation affects the sustainability of the tourism industry. Based on these results, it was concluded that effective event development helps to achieve sustainability in the tourism industry by reducing costs, ensuring efficient use of tourism resources and offers a unique opportunity among event participants. It was, therefore, recommended that events should be developed in such a way that it can help to reduce cost and help leverage the financial burdens of participants and stakeholders, thereby, achieving sustainability in the tourism industry.

Keywords: tourism, hospitality, industry, development

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9079 Modeling Geogenic Groundwater Contamination Risk with the Groundwater Assessment Platform (GAP)

Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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9078 A Dual-Mode Infinite Horizon Predictive Control Algorithm for Load Tracking in PUSPATI TRIGA Reactor

Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The PUSPATI TRIGA Reactor (RTP), Malaysia reached its first criticality on June 28, 1982, with power capacity 1MW thermal. The Feedback Control Algorithm (FCA) which is conventional Proportional-Integral (PI) controller, was used for present power control method to control fission process in RTP. It is important to ensure the core power always stable and follows load tracking within acceptable steady-state error and minimum settling time to reach steady-state power. At this time, the system could be considered not well-posed with power tracking performance. However, there is still potential to improve current performance by developing next generation of a novel design nuclear core power control. In this paper, the dual-mode predictions which are proposed in modelling Optimal Model Predictive Control (OMPC), is presented in a state-space model to control the core power. The model for core power control was based on mathematical models of the reactor core, OMPC, and control rods selection algorithm. The mathematical models of the reactor core were based on neutronic models, thermal hydraulic models, and reactivity models. The dual-mode prediction in OMPC for transient and terminal modes was based on the implementation of a Linear Quadratic Regulator (LQR) in designing the core power control. The combination of dual-mode prediction and Lyapunov which deal with summations in cost function over an infinite horizon is intended to eliminate some of the fundamental weaknesses related to MPC. This paper shows the behaviour of OMPC to deal with tracking, regulation problem, disturbance rejection and caters for parameter uncertainty. The comparison of both tracking and regulating performance is analysed between the conventional controller and OMPC by numerical simulations. In conclusion, the proposed OMPC has shown significant performance in load tracking and regulating core power for nuclear reactor with guarantee stabilising in the closed-loop.

Keywords: core power control, dual-mode prediction, load tracking, optimal model predictive control

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9077 Demographic Dividend Explained by Infrastructure Costs of Population Growth Rate, Distinct from Age Dependency

Authors: Jane N. O'Sullivan

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Although it is widely believed that fertility decline has benefitted economic advancement, particularly in East and South-East Asian countries, the causal mechanisms for this stimulus are contested. Since the turn of this century, demographic dividend theory has been increasingly recognised, hypothesising that higher proportions of working-age people can contribute to economic expansion if conditions are met to employ them productively. Population growth rate, as a systemic condition distinct from age composition, has not been similar attention since the 1970s and has lacked methodology for quantitative assessment. This paper explores conceptual and empirical quantification of the burden of expanding physical capital to accommodate a growing population. In proof-of-concept analyses of Australia and the United Kingdom, actual expenditure on gross fixed capital formation was compiled over four decades and apportioned to maintenance/turnover or expansion to accommodate population growth, based on lifespan of capital assets and population growth rate. In both countries, capital expansion was estimated to cost 6.5-7.0% of GDP per 1% population growth rate. This opportunity cost impedes the improvement of per capita capacity needed to realise the potential of the working-age population. Economic modelling of demographic scenarios have to date omitted this channel of influence; the implications of its inclusion are discussed.

Keywords: age dependency, demographic dividend, infrastructure, population growth rate

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9076 Boron Nitride Nanoparticle Enhanced Prepreg Composite Laminates

Authors: Qiong Tian, Lifeng Zhang, Demei Yu, Ajit D. Kelkar

Abstract:

Low specific weight and high strength is the basic requirement for aerospace materials. Fiber-reinforced epoxy resin composites are attractive materials for this purpose. Boron nitride nanoparticles (BNNPs) have good radiation shielding capacity, which is very important to aerospace materials. Herein a processing route for an advanced hybrid composite material is demonstrated by introducing dispersed BNNPs in standard prepreg manufacturing. The hybrid materials contain three parts: E-fiberglass, an aerospace-grade epoxy resin system, and BNNPs. A vacuum assisted resin transfer molding (VARTM) was utilized in this processing. Two BNNP functionalization approaches are presented in this study: (a) covalent functionalization with 3-aminopropyltriethoxysilane (KH-550); (b) non-covalent functionalization with cetyltrimethylammonium bromide (CTAB). The functionalized BNNPs were characterized by Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction(XRD) and scanning electron microscope (SEM). The results showed that BN powder was successfully functionalized via the covalent and non-covalent approaches without any crystal structure change and big agglomerate particles were broken into platelet-like nanoparticles (BNNPs) after functionalization. Compared to pristine BN powder, surface modified BNNPs could result in significant improvement in mechanical properties such as tensile, flexural and compressive strength and modulus. CTAB functionalized BNNPs (CTAB-BNNPs) showed higher tensile and flexural strength but lower compressive strength than KH-550 functionalized BNNPs (KH550-BNNPs). These reinforcements are mainly attributed to good BNNPs dispersion and interfacial adhesion between epoxy matrix and BNNPs. This study reveals the potential in improving mechanical properties of BNNPs-containing composites laminates through surface functionalization of BNNPs.

Keywords: boron nitride, epoxy, functionalization, prepreg, composite

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9075 Basket Option Pricing under Jump Diffusion Models

Authors: Ali Safdari-Vaighani

Abstract:

Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.

Keywords: basket option, jump diffusion, ‎radial basis function, RBF-PUM

Procedia PDF Downloads 354
9074 An Analysis of Innovative Cloud Model as Bridging the Gap between Physical and Virtualized Business Environments: The Customer Perspective

Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike Lloyd-Williams

Abstract:

This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: innovation, virtualization, cloud computing, organizational flexibility

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9073 Social Business Models: When Profits and Impacts Are Not at Odds

Authors: Elisa Pautasso, Matteo Castagno, Michele Osella

Abstract:

In the last decade, the emergence of new social needs as an effect of the economic crisis has stimulated the flourishing of business endeavours characterised by explicit social goals. Social start-ups, social enterprises or Corporate Social Responsibility operations carried out by traditional companies are quintessential examples in this regard. This paper analyses these kinds of initiatives in order to discover the main characteristics of social business models and to provide insights to social entrepreneurs for developing or improving their strategies. The research is conducted through the integration of literature review and case study analysis and, thanks to the recognition of the importance of both profits and social impacts as the key success factors for a social business model, proposes a framework for identifying indicators suitable for measuring the social impacts generated.

Keywords: business model, case study, impacts, social business

Procedia PDF Downloads 349
9072 Frailty Models for Modeling Heterogeneity: Simulation Study and Application to Quebec Pension Plan

Authors: Souad Romdhane, Lotfi Belkacem

Abstract:

When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

Procedia PDF Downloads 359
9071 Using an Empathy Intervention Model to Enhance Empathy and Socially Shared Regulation in Youth with Autism Spectrum Disorder

Authors: Yu-Chi Chou

Abstract:

The purpose of this study was to establish a logical path of an instructional model of empathy and social regulation, providing feasibility evidence on the model implementation in students with autism spectrum disorder (ASD). This newly developed Emotional Bug-Out Bag (BoB) curriculum was designed to enhance the empathy and socially shared regulation of students with ASD. The BoB model encompassed three instructional phases of basic theory lessons (BTL), action plan practices (APP), and final theory practices (FTP) during implementation. Besides, a learning flow (teacher-directed instruction, student self-directed problem-solving, group-based task completion, group-based reflection) was infused into the progress of instructional phases to deliberately promote the social regulatory process in group-working activities. A total of 23 junior high school students with ASD were implemented with the BoB curriculum. To examine the logical path for model implementation, data was collected from the participating students’ self-report scores on the learning nodes and understanding questions. Path analysis using structural equation modeling (SEM) was utilized for analyzing scores on 10 learning nodes and 41 understanding questions through the three phases of the BoB model. Results showed (a) all participants progressed throughout the implementation of the BoB model, and (b) the models of learning nodes and phases were positive and significant as expected, confirming the hypothesized logic path of this curriculum.

Keywords: autism spectrum disorder, empathy, regulation, socially shared regulation

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9070 Deficits and Solutions in the Development of Modular Factory Systems

Authors: Achim Kampker, Peter Burggräf, Moritz Krunke, Hanno Voet

Abstract:

As a reaction to current challenges in factory planning, many companies think about introducing factory standards to lower planning times and decrease planning costs. If these factory standards are set-up with a high level of modularity, they are defined as modular factory systems. This paper deals with the main current problems in the application of modular factory systems in practice and presents a solution approach with its basic models. The methodology is based on methods from factory planning but also uses the tools of other disciplines like product development or technology management to deal with the high complexity, which the development of modular factory systems implies. The four basic models that such a methodology has to contain are introduced and pointed out.

Keywords: factory planning, modular factory systems, factory standards, cost-benefit analysis

Procedia PDF Downloads 595
9069 Experimental and Numerical Investigation on the Torque in a Small Gap Taylor-Couette Flow with Smooth and Grooved Surface

Authors: L. Joseph, B. Farid, F. Ravelet

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Fundamental studies were performed on bifurcation, instabilities and turbulence in Taylor-Couette flow and applied to many engineering applications like astrophysics models in the accretion disks, shrouded fans, and electric motors. Such rotating machinery performances need to have a better understanding of the fluid flow distribution to quantify the power losses and the heat transfer distribution. The present investigation is focused on high gap ratio of Taylor-Couette flow with high rotational speeds, for smooth and grooved surfaces. So far, few works has been done in a very narrow gap and with very high rotation rates and, to the best of our knowledge, not with this combination with grooved surface. We study numerically the turbulent flow between two coaxial cylinders where R1 and R2 are the inner and outer radii respectively, where only the inner is rotating. The gap between the rotor and the stator varies between 0.5 and 2 mm, which corresponds to a radius ratio η = R1/R2 between 0.96 and 0.99 and an aspect ratio Γ= L/d between 50 and 200, where L is the length of the rotor and d being the gap between the two cylinders. The scaling of the torque with the Reynolds number is determined at different gaps for different smooth and grooved surfaces (and also with different number of grooves). The fluid in the gap is air. Re varies between 8000 and 30000. Another dimensionless parameter that plays an important role in the distinction of the regime of the flow is the Taylor number that corresponds to the ratio between the centrifugal forces and the viscous forces (from 6.7 X 105 to 4.2 X 107). The torque will be first evaluated with RANS and U-RANS models, and compared to empirical models and experimental results. A mesh convergence study has been done for each rotor-stator combination. The results of the torque are compared to different meshes in 2D dimensions. For the smooth surfaces, the models used overestimate the torque compared to the empirical equations that exist in the bibliography. The closest models to the empirical models are those solving the equations near to the wall. The greatest torque achieved with grooved surface. The tangential velocity in the gap was always higher in between the rotor and the stator and not on the wall of rotor. Also the greater one was in the groove in the recirculation zones. In order to avoid endwall effects, long cylinders are used in our setup (100 mm), torque is measured by a co-rotating torquemeter. The rotor is driven by an air turbine of an automotive turbo-compressor for high angular velocities. The results of the experimental measurements are at rotational speed of up to 50 000 rpm. The first experimental results are in agreement with numerical ones. Currently, quantitative study is performed on grooved surface, to determine the effect of number of grooves on the torque, experimentally and numerically.

Keywords: Taylor-Couette flow, high gap ratio, grooved surface, high speed

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9068 Creative Applications for Socially Assistive Robots to Support Mental Health: A Patient-Centered Feasibility Study

Authors: Andreas Kornmaaler Hansen, Carlos Gomez Cubero, Elizabeth Jochum

Abstract:

The use of the arts in therapy and rehabilitation is well established, and there is growing recognition of the value of the arts for improving health and well-being across diverse populations. Combining arts with socially assistive robots is a relatively under-explored research area. This paper presents the results of a feasibility study conducted within an existing arts and health program to scope the possibility of combining visual arts with socially assistive robots to promote mental health and well-being. Using a participatory research design with participant-led perspectives, we present the results of our feasibility study with a collaborative drawing robot among an adult population with mild to severe mental illness. We identify key methodological challenges and advantages of working with participatory and human-centered approaches. Based on the results of three pilot workshops with participants and lay health workers, we outline suggestions for authentic engagement with real stakeholders toward the development of socially assistive robots in community health contexts. Working closely with a patient population at all levels of the research process is key for developing tools and interventions that center patient experience and priorities while minimizing the risks of alienating patients and communities.

Keywords: arts and health, visual art, health promotion, mental health, collaborative robots, creativity, socially assistive robots

Procedia PDF Downloads 64