Search results for: estimating of trajectory
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1070

Search results for: estimating of trajectory

740 Estimating the Value of Statistical Life under the Subsidization and Cultural Effects

Authors: Mohammad A. Alolayan, John S. Evans, James K. Hammitt

Abstract:

The value of statistical life has been estimated for a middle eastern country with high economical subsidization system. In this study, in-person interviews were conducted on a stratified random sample to estimate the value of mortality risk. Double-bounded dichotomous choice questions followed by open-ended question were used in the interview to investigate the willingness to pay of the respondent for mortality risk reduction. High willingness to pay was found to be associated with high income and education. Also, females were found to have lower willingness to pay than males. The estimated value of statistical life is larger than the ones estimated for western countries where taxation system exists. This estimate provides a baseline for monetizing the health benefits for proposed policy or program to the decision makers in an eastern country. Also, the value of statistical life for a country in the region can be extrapolated from this this estimate by using the benefit transfer method.

Keywords: mortality, risk, VSL, willingness-to-pay

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739 Estimation of Desktop E-Wastes in Delhi Using Multivariate Flow Analysis

Authors: Sumay Bhojwani, Ashutosh Chandra, Mamita Devaburman, Akriti Bhogal

Abstract:

This article uses the Material flow analysis for estimating e-wastes in the Delhi/NCR region. The Material flow analysis is based on sales data obtained from various sources. Much of the data available for the sales is unreliable because of the existence of a huge informal sector. The informal sector in India accounts for more than 90%. Therefore, the scope of this study is only limited to the formal one. Also, for projection of the sales data till 2030, we have used regression (linear) to avoid complexity. The actual sales in the years following 2015 may vary non-linearly but we have assumed a basic linear relation. The purpose of this study was to know an approximate quantity of desktop e-wastes that we will have by the year 2030 so that we start preparing ourselves for the ineluctable investment in the treatment of these ever-rising e-wastes. The results of this study can be used to install a treatment plant for e-wastes in Delhi.

Keywords: e-wastes, Delhi, desktops, estimation

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738 Impact Assessment of Plum Research Investments in South Africa

Authors: Precious M. Tshabalala, Thula S. Dlamini, Frikkie Liebenberg, Johann Kirsten

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Numerous studies have been conducted, and the evidence has been unambiguous showing that investing in agricultural research and development increases productivity. Continued investments in agricultural research have led to the development of over 26 successful plum cultivars since 1980 at the Agricultural Research Council’s (ARC) Infruitec/Nietvoorbij in South Africa, and more continue to be developed to meet the specific needs of both producers and consumers. Yet very little is known about the returns on any of these research initiatives. The objective of the study was determine the economic impact of plum research investments at the ARC-the main plum breeding research organization in the country. The rate of return to plum research is estimated by estimating parameters in plum production and expressing research investment as an explanatory variable. The marginal rate of return is then determined to be 14.23 per cent. The rate of return to investment being this high is indicative of an under investment in plum research.

Keywords: Agricultural research investments, productivity and rate of return, plum

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737 Optimization of Flip Bucket Dents in Order to Reduce Scour Hole Depth (Plunge Pool) Using a Comprehensive Physical Model

Authors: Majid Galoie, Khodadad Safavi, Abdolreza Karami Nejad, Reza Roshan

Abstract:

Scour downstream of a flip bucket in a plunge pool is caused by impingement of water jet force. In order to reduce this force and consequently reduce scour hole depth, flip buckets may equip by dents. The minimum scour hole depth might be occurred by optimization of dents (number, shape, placement) on flip buckets. In this study, a comprehensive physical model has been developed and various options for dents have been investigated. The experimental data for each dent option such as scour hole depth, angle of impingement jet, piezometric pressure in tail-water and jet trajectory have been measured for various discharges. Finally, the best option can be found by analysis of the experimental results which has been expressed in this paper.

Keywords: scouring process, plunge pool, scour hole depth, physical model, flip bucket

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736 An Automatic Speech Recognition Tool for the Filipino Language Using the HTK System

Authors: John Lorenzo Bautista, Yoon-Joong Kim

Abstract:

This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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735 Use of Artificial Intelligence Based Models to Estimate the Use of a Spectral Band in Cognitive Radio

Authors: Danilo López, Edwin Rivas, Fernando Pedraza

Abstract:

Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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734 Potential of Aerodynamic Feature on Monitoring Multilayer Rough Surfaces

Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

Abstract:

In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

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733 Parameter Interactions in the Cumulative Prospect Theory: Fitting the Binary Choice Experiment Data

Authors: Elzbieta Babula, Juhyun Park

Abstract:

Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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732 Development of an Efficient Algorithm for Cessna Citation X Speed Optimization in Cruise

Authors: Georges Ghazi, Marc-Henry Devillers, Ruxandra M. Botez

Abstract:

Aircraft flight trajectory optimization has been identified to be a promising solution for reducing both airline costs and the aviation net carbon footprint. Nowadays, this role has been mainly attributed to the flight management system. This system is an onboard multi-purpose computer responsible for providing the crew members with the optimized flight plan from a destination to the next. To accomplish this function, the flight management system uses a variety of look-up tables to compute the optimal speed and altitude for each flight regime instantly. Because the cruise is the longest segment of a typical flight, the proposed algorithm is focused on minimizing fuel consumption for this flight phase. In this paper, a complete methodology to estimate the aircraft performance and subsequently compute the optimal speed in cruise is presented. Results showed that the obtained performance database was accurate enough to predict the flight costs associated with the cruise phase.

Keywords: Cessna Citation X, cruise speed optimization, flight cost, cost index, and golden section search

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731 Robust Control of Traction Motors based Electric Vehicles by Means of High-Gain

Authors: H. Mekki, A. Djerioui, S. Zeghlache, L. Chrifi-Alaoui

Abstract:

Induction motor (IM)Induction motor (IM) are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system.

Keywords: electric vehicles, sliding mode control, induction motor drive, high gain observer

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730 Investigating Seasonal Changes of Urban Land Cover with High Spatio-Temporal Resolution Satellite Data via Image Fusion

Authors: Hantian Wu, Bo Huang, Yuan Zeng

Abstract:

Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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729 A Qualitative Study to Analyze Clinical Coders’ Decision Making Process of Adverse Drug Event Admissions

Authors: Nisa Mohan

Abstract:

Clinical coding is a feasible method for estimating the national prevalence of adverse drug event (ADE) admissions. However, under-coding of ADE admissions is a limitation of this method. Whilst the under-coding will impact the accurate estimation of the actual burden of ADEs, the feasibility of the coded data in estimating the adverse drug event admissions goes much further compared to the other methods. Therefore, it is necessary to know the reasons for the under-coding in order to improve the clinical coding of ADE admissions. The ability to identify the reasons for the under-coding of ADE admissions rests on understanding the decision-making process of coding ADE admissions. Hence, the current study aimed to explore the decision-making process of clinical coders when coding cases of ADE admissions. Clinical coders from different levels of coding job such as trainee, intermediate and advanced level coders were purposefully selected for the interviews. Thirteen clinical coders were recruited from two Auckland region District Health Board hospitals for the interview study. Semi-structured, one-on-one, face-to-face interviews using open-ended questions were conducted with the selected clinical coders. Interviews were about 20 to 30 minutes long and were audio-recorded with the approval of the participants. The interview data were analysed using a general inductive approach. The interviews with the clinical coders revealed that the coders have targets to meet, and they sometimes hesitate to adhere to the coding standards. Coders deviate from the standard coding processes to make a decision. Coders avoid contacting the doctors for clarifying small doubts such as ADEs and the name of the medications because of the delay in getting a reply from the doctors. They prefer to do some research themselves or take help from their seniors and colleagues for making a decision because they can avoid a long wait to get a reply from the doctors. Coders think of ADE as a small thing. Lack of time for searching for information to confirm an ADE admission, inadequate communication with clinicians, along with coders’ belief that an ADE is a small thing may contribute to the under-coding of the ADE admissions. These findings suggest that further work is needed on interventions to improve the clinical coding of ADE admissions. Providing education to coders about the importance of ADEs, educating clinicians about the importance of clear and confirmed medical records entries, availing pharmacists’ services to improve the detection and clear documentation of ADE admissions, and including a mandatory field in the discharge summary about external causes of diseases may be useful for improving the clinical coding of ADE admissions. The findings of the research will help the policymakers to make informed decisions about the improvements. This study urges the coding policymakers, auditors, and trainers to engage with the unconscious cognitive biases and short-cuts of the clinical coders. This country-specific research conducted in New Zealand may also benefit other countries by providing insight into the clinical coding of ADE admissions and will offer guidance about where to focus changes and improvement initiatives.

Keywords: adverse drug events, clinical coders, decision making, hospital admissions

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728 Polynomially Adjusted Bivariate Density Estimates Based on the Saddlepoint Approximation

Authors: S. B. Provost, Susan Sheng

Abstract:

An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

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727 Genetic Algorithms Based ACPS Safety

Authors: Emine Laarouchi, Daniela Cancila, Laurent Soulier, Hakima Chaouchi

Abstract:

Cyber-Physical Systems as drones proved their efficiency for supporting emergency applications. For these particular applications, travel time and autonomous navigation algorithms are of paramount importance, especially when missions are performed in urban environments with high obstacle density. In this context, however, safety properties are not properly addressed. Our ambition is to optimize the system safety level under autonomous navigation systems, by preserving performance of the CPS. At this aim, we introduce genetic algorithms in the autonomous navigation process of the drone to better infer its trajectory considering the possible obstacles. We first model the wished safety requirements through a cost function and then seek to optimize it though genetics algorithms (GA). The main advantage in the use of GA is to consider different parameters together, for example, the level of battery for navigation system selection. Our tests show that the GA introduction in the autonomous navigation systems minimize the risk of safety lossless. Finally, although our simulation has been tested for autonomous drones, our approach and results could be extended for other autonomous navigation systems such as autonomous cars, robots, etc.

Keywords: safety, unmanned aerial vehicles , CPS, ACPS, drones, path planning, genetic algorithms

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726 The Effectiveness of Spatial Planning and Land Use Management Policies to Promote Tourism Development in the Wild Coast, Eastern Cape

Authors: Siyamthanda Makhwabe

Abstract:

Tourism development and spatial planning within the broader spectrum of the Eastern Cape needs to be strategically integrated to give effectiveness to development planning within the province. Tourism was severely affected and limited by policies of the previous regime. Tourism development in the Eastern Cape has been identified as one of the underdeveloped sectors that have the potential to improve the province’s local economic development trajectory The proposed study reviews literature on tourism development in an urban/rural and regional context in the Eastern Cape province. The proposed study will therefore offer an in-depth literature review on issues pertaining to spatial planning, land use management policies and tourism development within the Eastern Cape using the scoping review method. The intention of the proposed study is to identify synergies between the intertwined municipalities within the Wild Coast region in order to create a tourism belt that would yield benefit from Coffee Bay to East London.

Keywords: development, Eastern Cape, policies, spatial planning, tourism

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725 Human Posture Estimation Based on Multiple Viewpoints

Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

Abstract:

This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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724 Health and Wellbeing: Measuring and Mapping Diversity in India

Authors: Swati Rajput

Abstract:

Wellbeing is a multifaceted concept. Its definition has evolved to become more holistic over the years. The paper attempts to build up the understanding of the concept of wellbeing and marks the trajectory of its conceptual evolution. The paper will also elaborate and analyse various indicators of socio-economic wellbeing in India at state level. Ranking method has been applied to assess the situation of each state in context to the variable selected and wellbeing as a whole. Maps have been used to depict and illustrate the same. The data shows that the socio-economic wellbeing level is higher in states of Himachal Pradesh, Jammu and Kashmir, Punjab, Uttrakhand, Uttar Pradesh, Tamil Nadu, Bihar, and Lakshadweep. The level of wellbeing is very lower in Rajasthan, Madhya Pradesh, Telengana, Andhra Pradesh, Odisha, Assam, Arunachal Pradesh, and Tripura. Environment plays an important role in maintaining health. Environment and health are important indicators of wellbeing. The paper would further analyse some indicators of environment and health and find the change in the result of wellbeing levels of different states.

Keywords: socio economic factors, wellbeing index, health, mapping

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723 Analysis of Risk Factors Affecting the Motor Insurance Pricing with Generalized Linear Models

Authors: Puttharapong Sakulwaropas, Uraiwan Jaroengeratikun

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Casualty insurance business, the optimal premium pricing and adequate cost for an insurance company are important in risk management. Normally, the insurance pure premium can be determined by multiplying the claim frequency with the claim cost. The aim of this research was to study in the application of generalized linear models to select the risk factor for model of claim frequency and claim cost for estimating a pure premium. In this study, the data set was the claim of comprehensive motor insurance, which was provided by one of the insurance company in Thailand. The results of this study found that the risk factors significantly related to pure premium at the 0.05 level consisted of no claim bonus (NCB) and used of the car (Car code).

Keywords: generalized linear models, risk factor, pure premium, regression model

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722 Specified Human Motion Recognition and Unknown Hand-Held Object Tracking

Authors: Jinsiang Shaw, Pik-Hoe Chen

Abstract:

This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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721 From Problem Space to Executional Architecture: The Development of a Simulator to Examine the Effect of Autonomy on Mainline Rail Capacity

Authors: Emily J. Morey, Kevin Galvin, Thomas Riley, R. Eddie Wilson

Abstract:

The key challenges faced by integrating autonomous rail operations into the existing mainline railway environment have been identified through the understanding and framing of the problem space and stakeholder analysis. This was achieved through the completion of the first four steps of Soft Systems Methodology, where the problem space has been expressed via conceptual models. Having identified these challenges, we investigated one of them, namely capacity, via the use of models and simulation. This paper examines the approach used to move from the conceptual models to a simulation which can determine whether the integration of autonomous trains can plausibly increase capacity. Within this approach, we developed an architecture and converted logical models into physical resource models and associated design features which were used to build a simulator. From this simulator, we are able to analyse mixtures of legacy-autonomous operations and produce fundamental diagrams and trajectory plots to describe the dynamic behaviour of mixed mainline railway operations.

Keywords: autonomy, executable architecture, modelling and simulation, railway capacity

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720 Ultrasonic Pulse Velocity Investigation of Polypropylene and Steel Fiber Reinforced Concrete

Authors: Erjola Reufi, Jozefita Marku, Thomas Bier

Abstract:

Ultrasonic pulse velocity (UPV) method has been shown for some time to provide a reliable means of estimating properties and offers a unique opportunity for direct, quick and safe control of building damaged by earthquake, fatigue, conflagration and catastrophic scenarios. On this investigation hybrid reinforced concrete has been investigated by UPV method. Hooked end steel fiber of length 50 and 30 mm was added to concrete in different proportion 0, 0.25, 0.5, and 1 % by the volume of concrete. On the other hand, polypropylene fiber of length 12, 6, 3 mm was added to concrete of 0.1, 0.2, and 0.4 % by the volume of concrete. Fifteen different mixture has been prepared to investigate the relation between compressive strength and UPV values and also to investigate on the effect of volume and type of fiber on UPV values.

Keywords: compressive strength, polypropylene fiber, steel fiber, ultrasonic pulse velocity, volume, type of fiber

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719 Additive Manufacturing of Overhangs: From Temporary Supports to Self-Support

Authors: Paulo Mendonca, Nzar Faiq Naqeshbandi

Abstract:

The objective of this study is to propose an interactive design environment that outlines the underlying computational framework to reach self-supporting overhangs. The research demonstrates the digital printability of overhangs taking into consideration factors related to the geometry design, the material used, the applied support, and the printing set-up of slicing and the extruder inclination. Parametric design tools can contribute to the design phase, form-finding, and stability optimization of self-supporting structures while printing in order to hold the components in place until they are sufficiently advanced to support themselves. The challenge is to ensure the stability of the printed parts in the critical inclinations during the whole fabrication process. Facilitating the identification of parameterization will allow to predict and optimize the process. Later, in the light of the previous findings, some guidelines of simulations and physical tests are given to be conducted for estimating the structural and functional performance.

Keywords: additive manufacturing, overhangs, self-support overhangs, printability, parametric tools

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718 Evaluation of the Sterilization Practice in Liberal Dental Surgeons at Sidi Bel Abbes- Algeria

Authors: A. Chenafa, S. Boulenouar, M. Zitouni, M. Boukouria

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The sterilization of medical devices constitutes for all the medical professions, an inescapable obligation. It has for objective to prevent the infectious risk, both for the patient and for the medical team. The Dental surgeon as every healthcare professional has to master perfectly this subject and to train his staff to the various techniques of sterilization. It is the only way to assure the patients all the security for which they are entitled to wait when they undergo a dental care. It’s for it, that we undertook to lead an investigation aiming at estimating the sterilization practice at the dental surgeon of Sidi bel Abbes. The survey result showed a youth marked with the profession with a majority use of autoclave with cycle B and an almost total absence of the sterilization controls (test of Bowie and Dick). However, the majority of the dentists control and validate their sterilizers. Finally, our survey allowed us to describe some practices which must be improved regarding control, regarding qualification and regarding staff training. And suggestions were made in this sense.

Keywords: dental surgeon, medical devices, sterilization, survey

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717 The Effects of Affective Dimension of Face on Facial Attractiveness

Authors: Kyung-Ja Cho, Sun Jin Park

Abstract:

This study examined what effective dimension affects facial attractiveness. Two orthogonal dimensions, sharp-soft and babyish-mature, were used to rate the levels of facial attractiveness in 20’s women. This research also investigated the sex difference on the effect of effective dimension of face on attractiveness. The test subjects composed of 15 males and 18 females. They looked 330 photos of women in 20s. Then they rated the levels of the effective dimensions of faces with sharp-soft and babyish-mature, and the attraction with charmless-charming. The respond forms were Likert scales, the answer was scored from 1 to 9. As a result of multiple regression analysis, the subject reported the milder and younger appearance as more attractive. Both male and female subjects showed the same evaluation. This result means that two effective dimensions have the effect on estimating attractiveness.

Keywords: affective dimension of faces, facial attractiveness, sharp-soft, babyish-mature

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716 Scouring Rate Pattern/Monitoring at Coastal and Offshore Structures

Authors: Ahmad Saifullah Mazlan, Hossein Basser, Shatirah Akib

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Scouring pattern evaluation and measuring its depth around coastal and offshore structures is very essential issue to assure the safety of the structures as well as providing needed design parameters. Scouring is known as one of the important phenomena which threatens the safety of infrastructures. Several countermeasures have been developed to control scouring by protecting the structures against water flow attack directly or indirectly by changing the water flow pattern. Recently, monitoring methods for estimating water flow pattern and scour depth are studied to track the safety of structures. Since most of studies regarding scouring is related to monitoring scouring around piers in rivers therefore it is necessary to develop researches investigating scouring around piers in coastal and offshore areas. This paper describes a review of monitoring methods may be used for detecting scour depth around piers in coastal and offshore structures.

Keywords: scour, monitoring, pier, coastal, offshore

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715 Modeling Of The Random Impingement Erosion Due To The Impact Of The Solid Particles

Authors: Siamack A. Shirazi, Farzin Darihaki

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Solid particles could be found in many multiphase flows, including transport pipelines and pipe fittings. Such particles interact with the pipe material and cause erosion which threats the integrity of the system. Therefore, predicting the erosion rate is an important factor in the design and the monitor of such systems. Mechanistic models can provide reliable predictions for many conditions while demanding only relatively low computational cost. Mechanistic models utilize a representative particle trajectory to predict the impact characteristics of the majority of the particle impacts that cause maximum erosion rate in the domain. The erosion caused by particle impacts is not only due to the direct impacts but also random impingements. In the present study, an alternative model has been introduced to describe the erosion due to random impingement of particles. The present model provides a realistic trend for erosion with changes in the particle size and particle Stokes number. The present model is examined against the experimental data and CFD simulation results and indicates better agreement with the data incomparison to the available models in the literature.

Keywords: erosion, mechanistic modeling, particles, multiphase flow, gas-liquid-solid

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714 Forecasting for Financial Stock Returns Using a Quantile Function Model

Authors: Yuzhi Cai

Abstract:

In this paper, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, financial returns, predictive distribution, quantile function model

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713 Identification of Impact Load and Partial System Parameters Using 1D-CNN

Authors: Xuewen Yu, Danhui Dan

Abstract:

The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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712 A Quantification Method of Attractiveness of Stations and an Estimation Method of Number of Passengers Taking into Consideration the Attractiveness of the Station

Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

Abstract:

In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station

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711 An Efficient Fundamental Matrix Estimation for Moving Object Detection

Authors: Yeongyu Choi, Ju H. Park, S. M. Lee, Ho-Youl Jung

Abstract:

In this paper, an improved method for estimating fundamental matrix is proposed. The method is applied effectively to monocular camera based moving object detection. The method consists of corner points detection, moving object’s motion estimation and fundamental matrix calculation. The corner points are obtained by using Harris corner detector, motions of moving objects is calculated from pyramidal Lucas-Kanade optical flow algorithm. Through epipolar geometry analysis using RANSAC, the fundamental matrix is calculated. In this method, we have improved the performances of moving object detection by using two threshold values that determine inlier or outlier. Through the simulations, we compare the performances with varying the two threshold values.

Keywords: corner detection, optical flow, epipolar geometry, RANSAC

Procedia PDF Downloads 382