Search results for: targeted maximum likelihood estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7223

Search results for: targeted maximum likelihood estimation

6263 Is Privatization Related with Macroeconomic Management? Evidence from Some Selected African Countries

Authors: E. O. George, P. Ojeaga, D. Odejimi, O. Mattehws

Abstract:

Has macroeconomic management succeeded in making privatization promote growth in Africa? What are the probable strategies that should accompany the privatization reform process to promote growth in Africa? To what extent has the privatization process succeeded in attracting foreign direct investment to Africa? The study investigates the relationship between macroeconomic management and privatization. Many African countries have embarked on one form of privatization reform or the other since 1980 as one of the stringent conditions for accessing capital from the IMF and the World Bank. Secondly globalization and the gradually integration of the African economy into the global economy also means that Africa has to strategically develop its domestic market to cushion itself from fluctuations and probable contagion associated with global economic crisis that are always inevitable Stiglitz. The methods of estimation used are the OLS, linear mixed effects (LME), 2SLS and the GMM method of estimation. It was found that macroeconomic management has the capacity to affect the success of the privatization reform process. It was also found that privatization was not promoting growth in Africa; privatization could promote growth if long run growth strategies are implemented together with the privatization reform process. Privatization was also found not to have the capacity to attract foreign investment to many African countries.

Keywords: Africa, political economy, game theory, macroeconomic management and privatization

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6262 Percolation Transition in an Agglomeration of Spherical Particles

Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

Abstract:

Agglomerations of polydisperse systems of spherical particles are created in computer simulations using a simplified stochastic-hydrodynamic model: Particles sink to the bottom of the cylinder, taking into account gravity reduced by the buoyant force, the Stokes friction force, the added mass effect, and random velocity changes. Two types of particles are considered, with one of them being able to create connections to neighboring particles of the same type, thus forming a network within the agglomeration at the bottom of a cylinder. Decreasing the fraction of these particles, a percolation transition occurs. The critical regime is determined by investigating the maximum cluster size and the percolation susceptibility.

Keywords: binary system, maximum cluster size, percolation, polydisperse

Procedia PDF Downloads 47
6261 Mathematical Modelling of Blood Flow with Magnetic Nanoparticles as Carrier for Targeted Drug Delivery in a Stenosed Artery

Authors: Sreeparna Majee, G. C. Shit

Abstract:

A study on targeted drug delivery is carried out in an unsteady flow of blood infused with magnetic NPs (nanoparticles) with an aim to understand the flow pattern and nanoparticle aggregation in a diseased arterial segment having stenosis. The magnetic NPs are supervised by the magnetic field which is significant for therapeutic treatment of arterial diseases, tumor and cancer cells and removing blood clots. Coupled thermal energy have also been analyzed by considering dissipation of energy because of the application of the magnetic field and the viscosity of blood. Simulation technique used to solve the mathematical model is vorticity-stream function formulations in the diseased artery. An elevation in SLP (Specific loss power) is noted in the aortic bloodstream when the agglomeration of nanoparticles is higher. This phenomenon has potential application in the treatment of hyperthermia. The study focuses on the lowering of WSS (Wall Shear Stress) with increasing particle concentration at the downstream of the stenosis which depicts the vigorous flow circulation zone. These low shear stress regions prolong the residing time of the nanoparticles carrying drugs which soaks up the LDL (Low Density Lipoprotein) deposition. Moreover, an increase in NP concentration enhances the Nusselt number which marks the increase of heat transfer from the arterial wall to the surrounding tissues to destroy tumor and cancer cells without affecting the healthy cells. The results have a significant influence in the study of medicine, to treat arterial diseases such as atherosclerosis without the need for surgery which can minimize the expenditures on cardiovascular treatments.

Keywords: magnetic nanoparticles, blood flow, atherosclerosis, hyperthermia

Procedia PDF Downloads 126
6260 Impact of Brassinosteroid with GA3, CPPU on Yield and Quality of Newly Introduced Grape cv. Italia

Authors: Senthilkumar S, Vijayakumar R M , Soorianathasundaram K, Durga Devi D

Abstract:

A study was conducted to assess the influence of brassinosteroid and other bioregulators as pre-harvest sprays on yield and quality of newly introduced Californian grape cv. Italia. The vines were exposed to standardized pruning level of pruning 50% of the canes to 5-6 bud level for fruiting and 50% of the canes to two bud level for vegetative growth. The influence of brassinosteroid was assessed using BR (1 ppm) alone and in combination with GA3 and CPPU, sprayed at three different stages over the control (water spray) were given as treatments. The results revealed that the bunches treated with Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage i.e., 7-8 mm berry size, recorded the maximum values on yield characters like bunch weight (719.94 g), yield per vine (12.70 kg/vine) and yield per hectare (15.88 t). The berry characters and quality traits were also significantly influenced by the application of bioregulators. The maximum value for all those characters was registered under bunch sprays of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage. The economic feasibility indicated that the treatment combination Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) had registered the maximum benefit cost ratio of 3.13, as compared to 1.89 in control (water spray). Overall, it was observed that a combined bunch spray of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) was adjudged as the best treatment for promoting the crop for better the bunch quality and yield.

Keywords: bioregulators, brassinosteroid, CPPU, GA3, Italia grape cultivar

Procedia PDF Downloads 226
6259 Estimation of Fragility Curves Using Proposed Ground Motion Selection and Scaling Procedure

Authors: Esra Zengin, Sinan Akkar

Abstract:

Reliable and accurate prediction of nonlinear structural response requires specification of appropriate earthquake ground motions to be used in nonlinear time history analysis. The current research has mainly focused on selection and manipulation of real earthquake records that can be seen as the most critical step in the performance based seismic design and assessment of the structures. Utilizing amplitude scaled ground motions that matches with the target spectra is commonly used technique for the estimation of nonlinear structural response. Representative ground motion ensembles are selected to match target spectrum such as scenario-based spectrum derived from ground motion prediction equations, Uniform Hazard Spectrum (UHS), Conditional Mean Spectrum (CMS) or Conditional Spectrum (CS). Different sets of criteria exist among those developed methodologies to select and scale ground motions with the objective of obtaining robust estimation of the structural performance. This study presents ground motion selection and scaling procedure that considers the spectral variability at target demand with the level of ground motion dispersion. The proposed methodology provides a set of ground motions whose response spectra match target median and corresponding variance within a specified period interval. The efficient and simple algorithm is used to assemble the ground motion sets. The scaling stage is based on the minimization of the error between scaled median and the target spectra where the dispersion of the earthquake shaking is preserved along the period interval. The impact of the spectral variability on nonlinear response distribution is investigated at the level of inelastic single degree of freedom systems. In order to see the effect of different selection and scaling methodologies on fragility curve estimations, results are compared with those obtained by CMS-based scaling methodology. The variability in fragility curves due to the consideration of dispersion in ground motion selection process is also examined.

Keywords: ground motion selection, scaling, uncertainty, fragility curve

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6258 Pectin Degrading Enzyme: Entrapment of Pectinase Using Different Synthetic and Non-Synthetic Polymers for Continuous Degradation of Pectin Polymer

Authors: Haneef Ur Rehman, Afsheen Aman, Abdul Hameed Baloch, Shah Ali Ul Qader

Abstract:

Pectinase is a heterogeneous group of enzymes that catalyze the hydrolysis of pectin substances and widely has been used in food and textile industries. In current study, pectinase from B. licheniformis KIBGE-IB21 was immobilized within different polymers (calcium alginate beads, polyacrylamide gel and agar-agar matrix) to enhance its catalytic properties. Polyacrylamide gel was found to be most promising one and gave maximum (89%) immobilization yield. While less immobilization yield was observed in case of calcium alginate beads that only retained 46 % activity. The reaction time for maximum pectinolytic activity was increased from 5.0 to 10 minutes after immobilization. The temperature of pectinase for maximum enzyme activity was increased from 45 °C to 50 °C and 55 °C when it was immobilized within agar-agar and calcium alginate beads, respectively. The optimum pH of pectinase didn’t alter when it was immobilized within polyacrylamide gel and calcium alginate beads, but in case of agar-agar it was changed from pH 10 to pH 9.0. Thermal stability of pectinase was improved after immobilization and immobilized pectinase showed higher toleration against different temperatures as compared to free enzyme. It can be concluded that the entrapment is a simple, single step and promising procedure to immobilized pectinase within different synthetic and non-synthetic polymers and enhanced its catalytic properties.

Keywords: pectinase, characterization immobilization, polyacrylamide, agar-agar, calcium alginate beads

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6257 FPGA Based Vector Control of PM Motor Using Sliding Mode Observer

Authors: Hanan Mikhael Dawood, Afaneen Anwer Abood Al-Khazraji

Abstract:

The paper presents an investigation of field oriented control strategy of Permanent Magnet Synchronous Motor (PMSM) based on hardware in the loop simulation (HIL) over a wide speed range. A sensorless rotor position estimation using sliding mode observer for permanent magnet synchronous motor is illustrated considering the effects of magnetic saturation between the d and q axes. The cross saturation between d and q axes has been calculated by finite-element analysis. Therefore, the inductance measurement regards the saturation and cross saturation which are used to obtain the suitable id-characteristics in base and flux weakening regions. Real time matrix multiplication in Field Programmable Gate Array (FPGA) using floating point number system is used utilizing Quartus-II environment to develop FPGA designs and then download these designs files into development kit. dSPACE DS1103 is utilized for Pulse Width Modulation (PWM) switching and the controller. The hardware in the loop results conducted to that from the Matlab simulation. Various dynamic conditions have been investigated.

Keywords: magnetic saturation, rotor position estimation, sliding mode observer, hardware in the loop (HIL)

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6256 Photoluminescent Properties of Noble Metal Nanoparticles Supported Yttrium Aluminum Garnet Nanoparticles Doped with Cerium (Ⅲ) Ions

Authors: Mitsunobu Iwasaki, Akifumi Iseda

Abstract:

Yttrium aluminum garnet doped with cerium (Ⅲ) ions (Y3Al5O12:Ce3+, YAG:Ce3+) has attracted a great attention because it can efficiently convert the blue light into a very broad yellow emission band, which produces white light emitting diodes and is applied for panel displays. To improve the brightness and resolution of the display, a considerable attention has been directed to develop fine phosphor particles. We have prepared YAG:Ce3+ nanophosphors by environmental-friendly wet process. The peak maximum of absorption spectra of surface plasmon of Ag nanopaticles are close to that of the excitation spectra (460 nm) of YAG:Ce3+. It can be expected that Ag nanoparticles supported onto the surface of YAG:Ce3+ (Ag-YAG:Ce3+) enhance the absorption of Ce3+ ions. In this study, we have prepared Ag-YAG:Ce3+ nanophosphors and investigated their photoluminescent properties. YCl3・6H2O and AlCl3・6H2O with a molar ratio of Y:Al=3:5 were dissolved in ethanol (100 ml), and CeCl3•7H2O (0.3 mol%) was further added to the above solution. Then, NaOH (4.6×10-2 mol) dissolved in ethanol (50 ml) was added dropwise to the mixture under reflux over 2 hours, and the solution was further refluxed for 1 hour. After cooling to room temperature, precipitates in the reaction mixture were heated at 673 K for 1 hour. After the calcination, the particles were immersed in AgNO3 solution for 1 hour, followed by sintering at 1123 K for 1 hour. YAG:Ce3+ were confirmed to be nanocrystals with a crystallite size of 50-80 nm in diameter. Ag nanoparticles supported onto YAG:Ce3+ were single nanometers in diameter. The excitation and emission spectra were 454 nm and 539 nm at a maximum wavelength, respectively. The emission intensity was maximum for Ag-YAG:Ce3+ immersed into 0.5 mM AgCl (Ag-YAG:Ce (0.5 mM)). The absorption maximum (461 nm) was increased for Ag-YAG:Ce3+ in comparison with that for YAG:Ce3+, indicating that the absorption was enhanced by the addition of Ag. The external and internal quantum efficiencies became 11.2 % and 36.9 % for Ag-YAG:Ce (0.5 mM), respectively. The emission intensity and absorption maximum of Ag-YAG:Ce (0.5 mM)×n (n=1, 2, 3) were increased with an increase of the number of supporting times (n), respectively. The external and internal quantum efficiencies were increased for the increase of n, respectively. The external quantum efficiency of Ag-YAG:Ce (0.5 mM) (n=3) became twice as large as that of YAG:Ce. In conclusion, Ag nanoparticles supported onto YAG:Ce3+ increased absorption and quantum efficiency. Therefore, the support of Ag nanoparticles enhanced the photoluminescent properties of YAG:Ce3+.

Keywords: plasmon, quantum efficiency, silver nanoparticles, yttrium aluminum garnet

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6255 Design and Implementation of DC-DC Converter with Inc-Cond Algorithm

Authors: Mustafa Engin Başoğlu, Bekir Çakır

Abstract:

The most important component affecting the efficiency of photovoltaic power systems are solar panels. Efficiency of these systems are significantly affected because of being low efficiency of solar panel. Therefore, solar panels should be operated under maximum power point conditions through a power converter. In this study, design boost converter with maximum power point tracking (MPPT) operation has been designed and performed with Incremental Conductance (Inc-Cond) algorithm by using direct duty control. Furthermore, it is shown that performance of boost converter with MPPT operation fails under low load resistance connection.

Keywords: boost converter, incremental conductance (Inc-Cond), MPPT, solar panel

Procedia PDF Downloads 1034
6254 Offline Parameter Identification and State-of-Charge Estimation for Healthy and Aged Electric Vehicle Batteries Based on the Combined Model

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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6253 An Approach for Estimation in Hierarchical Clustered Data Applicable to Rare Diseases

Authors: Daniel C. Bonzo

Abstract:

Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

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6252 Games behind Bars: A Longitudinal Study of Inmates Pro-Social Preferences

Authors: Mario A. Maggioni, Domenico Rossignoli, Simona Beretta, Sara Balestri

Abstract:

The paper presents the results of a Longitudinal Randomized Control Trial implemented in 2016 two State Prisons in California (USA). The subjects were randomly assigned to a 10-months program (GRIP, Guiding Rage Into Power) aiming at undoing the destructive behavioral patterns that lead to criminal actions by raising the individual’s 'mindfulness'. This study tests whether the participation to this program (treatment), based on strong relationships and mutual help, affects pro-social behavior of participants, in particular with reference to trust and inequality aversion. The research protocol entails the administration of two questionnaires including a set of behavioral situations ('games') - widely used in the relevant literature in the field - to 80 inmates, 42 treated (enrolled in the program) and 38 controls. The first questionnaire has been administered before treatment and randomization took place; the second questionnaire at the end of the program. The results of a Difference-in-Differences estimation procedure, show that trust significantly increases GRIP participants to compared to the control group. The result is robust to alternative estimation techniques and to the inclusion of a set of covariates to further control for idiosyncratic characteristics of the prisoners.

Keywords: behavioral economics, difference in differences, longitudinal study, pro-social preferences

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6251 Evaluation of Expected Annual Loss Probabilities of RC Moment Resisting Frames

Authors: Saemee Jun, Dong-Hyeon Shin, Tae-Sang Ahn, Hyung-Joon Kim

Abstract:

Building loss estimation methodologies which have been advanced considerably in recent decades are usually used to estimate socio and economic impacts resulting from seismic structural damage. In accordance with these methods, this paper presents the evaluation of an annual loss probability of a reinforced concrete moment resisting frame designed according to Korean Building Code. The annual loss probability is defined by (1) a fragility curve obtained from a capacity spectrum method which is similar to a method adopted from HAZUS, and (2) a seismic hazard curve derived from annual frequencies of exceedance per peak ground acceleration. Seismic fragilities are computed to calculate the annual loss probability of a certain structure using functions depending on structural capacity, seismic demand, structural response and the probability of exceeding damage state thresholds. This study carried out a nonlinear static analysis to obtain the capacity of a RC moment resisting frame selected as a prototype building. The analysis results show that the probability of being extensive structural damage in the prototype building is expected to 0.004% in a year.

Keywords: expected annual loss, loss estimation, RC structure, fragility analysis

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6250 Experimental investigation on the lithium-Ion Battery Thermal Management System Based on Micro Heat Pipe Array in High Temperature Environment

Authors: Ruyang Ren, Yaohua Zhao, Yanhua Diao

Abstract:

The intermittent and unstable characteristics of renewable energy such as solar energy can be effectively solved through battery energy storage system. Lithium-ion battery is widely used in battery energy storage system because of its advantages of high energy density, small internal resistance, low self-discharge rate, no memory effect and long service life. However, the performance and service life of lithium-ion battery is seriously affected by its operating temperature. Thus, the safety operation of the lithium-ion battery module is inseparable from an effective thermal management system (TMS). In this study, a new type of TMS based on micro heat pipe array (MHPA) for lithium-ion battery is established, and the TMS is applied to a battery energy storage box that needs to operate at a high temperature environment of 40 °C all year round. MHPA is a flat shape metal body with high thermal conductivity and excellent temperature uniformity. The battery energy storage box is composed of four battery modules, with a nominal voltage of 51.2 V, a nominal capacity of 400 Ah. Through the excellent heat transfer characteristics of the MHPA, the heat generated by the charge and discharge process can be quickly transferred out of the battery module. In addition, if only the MHPA cannot meet the heat dissipation requirements of the battery module, the TMS can automatically control the opening of the external fan outside the battery module according to the temperature of the battery, so as to further enhance the heat dissipation of the battery module. The thermal management performance of lithium-ion battery TMS based on MHPA is studied experimentally under different ambient temperatures and the condition to turn on the fan or not. Results show that when the ambient temperature is 40 °C and the fan is not turned on in the whole charge and discharge process, the maximum temperature of the battery in the energy storage box is 53.1 °C and the maximum temperature difference in the battery module is 2.4 °C. After the fan is turned on in the whole charge and discharge process, the maximum temperature is reduced to 50.1 °C, and the maximum temperature difference is reduced to 1.7 °C. Obviously, the lithium-ion battery TMS based on MHPA not only could control the maximum temperature of the battery below 55 °C, but also ensure the excellent temperature uniformity of the battery module. In conclusion, the lithium-ion battery TMS based on MHPA can ensure the safe and stable operation of the battery energy storage box in high temperature environment.

Keywords: heat dissipation, lithium-ion battery thermal management, micro heat pipe array, temperature uniformity

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6249 Conversion of Sweet Sorghum Bagasse to Sugars for Succinic Acid Production

Authors: Enlin Lo, Ioannis Dogaris, George Philippidis

Abstract:

Succinic acid is a compound used for manufacturing lacquers, resins, and other coating chemicals. It is also used in the food and beverage industry as a flavor additive. It is predominantly manufactured from petrochemicals, but it can also be produced by fermentation of sugars from renewable feedstocks, such as plant biomass. Bio-based succinic acid has great potential in becoming a platform chemical (building block) for commodity and high-value chemicals. In this study, the production of bio-based succinic acid from sweet sorghum was investigated. Sweet sorghum has high fermentable sugar content and can be cultivated in a variety of climates. In order to avoid competition with food feedstocks, its non-edible ‘bagasse’ (the fiber part after extracting the juice) was targeted. Initially, various conditions of pretreating sweet sorghum bagasse (SSB) were studied in an effort to remove most of the non-fermentable components and expose the cellulosic fiber containing the fermentable sugars (glucose). Concentrated (83%) phosphoric acid was utilized at temperatures 50-80 oC for 30-60 min at various SSB loadings (10-15%), coupled with enzymatic hydrolysis using commercial cellulase (Ctec2, Novozymes) enzyme, to identify the conditions that lead to the highest glucose yields for subsequent fermentation to succinic acid. As the pretreatment temperature and duration increased, the bagasse color changed from light brown to dark brown-black, indicating decomposition, which ranged from 15% to 72%, while the theoretical glucose yield is 91%. With Minitab software statistical analysis, a model was built to identify the optimal pretreatment condition for maximum glucose released. The projected theoretical bio-based succinic acid production is 23g per 100g of SSB, which will be confirmed with fermentation experiments using the bacterium Actinobacillus succinogenes.

Keywords: biomass, cellulose, enzymatic hydrolysis, fermentation, pretreatment, succinic acid

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6248 High Speed Motion Tracking with Magnetometer in Nonuniform Magnetic Field

Authors: Jeronimo Cox, Tomonari Furukawa

Abstract:

Magnetometers have become more popular in inertial measurement units (IMU) for their ability to correct estimations using the earth's magnetic field. Accelerometer and gyroscope-based packages fail with dead-reckoning errors accumulated over time. Localization in robotic applications with magnetometer-inclusive IMUs has become popular as a way to track the odometry of slower-speed robots. With high-speed motions, the accumulated error increases over smaller periods of time, making them difficult to track with IMU. Tracking a high-speed motion is especially difficult with limited observability. Visual obstruction of motion leaves motion-tracking cameras unusable. When motions are too dynamic for estimation techniques reliant on the observability of the gravity vector, the use of magnetometers is further justified. As available magnetometer calibration methods are limited with the assumption that background magnetic fields are uniform, estimation in nonuniform magnetic fields is problematic. Hard iron distortion is a distortion of the magnetic field by other objects that produce magnetic fields. This kind of distortion is often observed as the offset from the origin of the center of data points when a magnetometer is rotated. The magnitude of hard iron distortion is dependent on proximity to distortion sources. Soft iron distortion is more related to the scaling of the axes of magnetometer sensors. Hard iron distortion is more of a contributor to the error of attitude estimation with magnetometers. Indoor environments or spaces inside ferrite-based structures, such as building reinforcements or a vehicle, often cause distortions with proximity. As positions correlate to areas of distortion, methods of magnetometer localization include the production of spatial mapping of magnetic field and collection of distortion signatures to better aid location tracking. The goal of this paper is to compare magnetometer methods that don't need pre-productions of magnetic field maps. Mapping the magnetic field in some spaces can be costly and inefficient. Dynamic measurement fusion is used to track the motion of a multi-link system with us. Conventional calibration by data collection of rotation at a static point, real-time estimation of calibration parameters each time step, and using two magnetometers for determining local hard iron distortion are compared to confirm the robustness and accuracy of each technique. With opposite-facing magnetometers, hard iron distortion can be accounted for regardless of position, Rather than assuming that hard iron distortion is constant regardless of positional change. The motion measured is a repeatable planar motion of a two-link system connected by revolute joints. The links are translated on a moving base to impulse rotation of the links. Equipping the joints with absolute encoders and recording the motion with cameras to enable ground truth comparison to each of the magnetometer methods. While the two-magnetometer method accounts for local hard iron distortion, the method fails where the magnetic field direction in space is inconsistent.

Keywords: motion tracking, sensor fusion, magnetometer, state estimation

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6247 Runoff Estimation Using NRCS-CN Method

Authors: E. K. Naseela, B. M. Dodamani, Chaithra Chandran

Abstract:

The GIS and remote sensing techniques facilitate accurate estimation of surface runoff from watershed. In the present study an attempt has been made to evaluate the applicability of Natural Resources Service Curve Number method using GIS and Remote sensing technique in the upper Krishna basin (69,425 Sq.km). Landsat 7 (with resolution 30 m) satellite data for the year 2012 has been used for the preparation of land use land cover (LU/LC) map. The hydrologic soil group is mapped using GIS platform. The weighted curve numbers (CN) for all the 5 subcatchments calculated on the basis of LU/LC type and hydrologic soil class in the area by considering antecedent moisture condition. Monthly rainfall data was available for 58 raingauge stations. Overlay technique is adopted for generating weighted curve number. Results of the study show that land use changes determined from satellite images are useful in studying the runoff response of the basin. The results showed that there is no significant difference between observed and estimated runoff depths. For each subcatchment, statistically positive correlations were detected between observed and estimated runoff depth (0.6Keywords: curve number, GIS, remote sensing, runoff

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6246 Multivariate Control Chart to Determine Efficiency Measurements in Industrial Processes

Authors: J. J. Vargas, N. Prieto, L. A. Toro

Abstract:

Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

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6245 Transient Level in the Surge Chamber at the Robert-bourassa Generating Station

Authors: Maryam Kamali Nezhad

Abstract:

The Robert-Bourassa development (LG-2), the first to be built on the Grande Rivière, comprises two sets of eight turbines- generator units each, the East and West powerhouses. Each powerhouse has two tailrace tunnels with an average length of about 1178 m. The LG-2A powerhouse houses 6 turbine-generator units. The water is discharged through two tailrace tunnels with a length of about 1330 m. The objective of this work, at RB (LG-2), is; 1) to establish a new maximum transient level in the surge chamber, 2) to define the new maximum equipment flow rate for the future turbine-generator units, 3) to ensure safe access to various intervention locations in the surge chamber. The transient levels under normal operating conditions at the RB plant were determined in 2001 by the Hydraulics Unit of HQE using the "Chamber" software. It is a one-dimensional mass oscillation calculation software; it is used to determine the variation of the water level in the equilibrium chamber located downstream of a power plant during the load shedding of the power plant units; it can also be used in the case of an equilibrium stack upstream of a power plant. The RB (LG-2) plant study is based on the theoretical nominal geometry of the chamber and the tailrace tunnels and the flow-level relationship at the outlet of the galleries established during design. The software is used in such a way that the results have an acceptable margin of safety, especially with respect to the maximum transient level (e.g., resumption of flow at an inopportune time), to take into account the turbulent and three-dimensional aspects of the actual flow in the chamber. Note that the transient levels depend on the water levels in the river and in the steady-state equilibrium chambers. These data are established in the HQP CRP database and updated from time to time. The maximum transient levels in the RB-East and RB-West powerhouses surge chamber were revised based on the latest update (set 4) of in-river rating curves and steady-state surge chamber water levels. The results of the revision were also used to update the technical advice on the operating conditions for the aforementioned surge chamber access while considering revisions to the calculated water levels.

Keywords: generating station, surge chamber, maximum transient level, hydroelectric power station, turbine-generator, reservoir

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6244 Studies on the Feasibility of Cow’s Urine as Non-Conventional Energy Sources

Authors: Raj Kumar Rajak, Bharat Mishra

Abstract:

Bio-batteries represent an entirely new long-term, reasonable, reachable, and eco-friendly approach to generation of sustainable energy. In the present experimental work, we have studied the effect of the generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow’s urine as an electrolyte. C-Mg electrode pair shows maximum Voltage and Short Circuit Current (SCC), while C-Zn electrode pair shows less Open Circuit Voltage (OCV) and SCC. By the studies of cow urine and different electrodes, it is found that C-Zn electrode battery is more economical. The cow urine battery with C-Zn electrode provides maximum power (707.4 mW) and durability (up to 145 h). This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: bio-batteries, cow's urine, electrodes, non-conventional

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6243 Hydrology and Hydraulics Analysis of Beko Abo Dam and Appurtenant Structre Design, Ethiopia

Authors: Azazhu Wassie

Abstract:

This study tried to evaluate the maximum design flood for appurtenance structure design using the given climatological and hydrological data analysis on the referenced study area. The maximum design flood is determined by using flood frequency analysis. Using this method, the peak discharge is 32,583.67 m3/s, but the data is transferred because the dam site is not on the gauged station. Then the peak discharge becomes 38,115 m3/s. The study was conducted in June 2023. This dam is built across a river to create a reservoir on its upstream side for impounding water. The water stored in the reservoir is used for various purposes, such as irrigation, hydropower, navigation, fishing, etc. The total average volume of annual runoff is estimated to be 115.1 billion m3. The total potential of the land for irrigation development can go beyond 3 million ha.

Keywords: dam design, flow duration curve, peak flood, rainfall, reservoir capacity, risk and reliability

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6242 An Approach to Apply Kernel Density Estimation Tool for Crash Prone Location Identification

Authors: Kazi Md. Shifun Newaz, S. Miaji, Shahnewaz Hazanat-E-Rabbi

Abstract:

In this study, the kernel density estimation tool has been used to identify most crash prone locations in a national highway of Bangladesh. Like other developing countries, in Bangladesh road traffic crashes (RTC) have now become a great social alarm and the situation is deteriorating day by day. Today’s black spot identification process is not based on modern technical tools and most of the cases provide wrong output. In this situation, characteristic analysis and black spot identification by spatial analysis would be an effective and low cost approach in ensuring road safety. The methodology of this study incorporates a framework on the basis of spatial-temporal study to identify most RTC occurrence locations. In this study, a very important and economic corridor like Dhaka to Sylhet highway has been chosen to apply the method. This research proposes that KDE method for identification of Hazardous Road Location (HRL) could be used for all other National highways in Bangladesh and also for other developing countries. Some recommendations have been suggested for policy maker to reduce RTC in Dhaka-Sylhet especially in black spots.

Keywords: hazardous road location (HRL), crash, GIS, kernel density

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6241 Development of DNDC Modelling Method for Evaluation of Carbon Dioxide Emission from Arable Soils in European Russia

Authors: Olga Sukhoveeva

Abstract:

Carbon dioxide (CO2) is the main component of carbon biogeochemical cycle and one of the most important greenhouse gases (GHG). Agriculture, particularly arable soils, are one the largest sources of GHG emission for the atmosphere including CO2.Models may be used for estimation of GHG emission from agriculture if they can be adapted for different countries conditions. The only model used in officially at national level in United Kingdom and China for this purpose is DNDC (DeNitrification-DeComposition). In our research, the model DNDC is offered for estimation of GHG emission from arable soils in Russia. The aim of our research was to create the method of DNDC using for evaluation of CO2 emission in Russia based on official statistical information. The target territory was European part of Russia where many field experiments are located. At the first step of research the database on climate, soil and cropping characteristics for the target region from governmental, statistical, and literature sources were created. All-Russia Research Institute of Hydrometeorological Information – World Data Centre provides open daily data about average meteorological and climatic conditions. It must be calculated spatial average values of maximum and minimum air temperature and precipitation over the region. Spatial average values of soil characteristics (soil texture, bulk density, pH, soil organic carbon content) can be determined on the base of Union state register of soil recourses of Russia. Cropping technologies are published by agricultural research institutes and departments. We offer to define cropping system parameters (annual information about crop yields, amount and types of fertilizers and manure) on the base of the Federal State Statistics Service data. Content of carbon in plant biomass may be calculated via formulas developed and published by Ministry of Natural Resources and Environment of the Russian Federation. At the second step CO2 emission from soil in this region were calculated by DNDC. Modelling data were compared with empirical and literature data and good results were obtained, modelled values were equivalent to the measured ones. It was revealed that the DNDC model may be used to evaluate and forecast the CO2 emission from arable soils in Russia based on the official statistical information. Also, it can be used for creation of the program for decreasing GHG emission from arable soils to the atmosphere. Financial Support: fundamental scientific researching theme 0148-2014-0005 No 01201352499 ‘Solution of fundamental problems of analysis and forecast of Earth climatic system condition’ for 2014-2020; fundamental research program of Presidium of RAS No 51 ‘Climate change: causes, risks, consequences, problems of adaptation and regulation’ for 2018-2020.

Keywords: arable soils, carbon dioxide emission, DNDC model, European Russia

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6240 Estimating View-Through Ad Attribution from User Surveys Using Convex Optimization

Authors: Yuhan Lin, Rohan Kekatpure, Cassidy Yeung

Abstract:

In Digital Marketing, robust quantification of View-through attribution (VTA) is necessary for evaluating channel effectiveness. VTA occurs when a product purchase is aided by an Ad but without an explicit click (e.g. a TV ad). A lack of a tracking mechanism makes VTA estimation challenging. Most prevalent VTA estimation techniques rely on post-purchase in-product user surveys. User surveys enable the calculation of channel multipliers, which are the ratio of the view-attributed to the click-attributed purchases of each marketing channel. Channel multipliers thus provide a way to estimate the unknown VTA for a channel from its known click attribution. In this work, we use Convex Optimization to compute channel multipliers in a way that enables a mathematical encoding of the expected channel behavior. Large fluctuations in channel attributions often result from overfitting the calculations to user surveys. Casting channel attribution as a Convex Optimization problem allows an introduction of constraints that limit such fluctuations. The result of our study is a distribution of channel multipliers across the entire marketing funnel, with important implications for marketing spend optimization. Our technique can be broadly applied to estimate Ad effectiveness in a privacy-centric world that increasingly limits user tracking.

Keywords: digital marketing, survey analysis, operational research, convex optimization, channel attribution

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6239 Internal Financing Constraints and Corporate Investment: Evidence from Indian Manufacturing Firms

Authors: Gaurav Gupta, Jitendra Mahakud

Abstract:

This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

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6238 Reconnaissance Investigation of Thermal Springs in the Middle Benue Trough, Nigeria by Remote Sensing

Authors: N. Tochukwu, M. Mukhopadhyay, A. Mohamed

Abstract:

It is no new that Nigeria faces a continual power shortage problem due to its vast population power demand and heavy reliance on nonrenewable forms of energy such as thermal power or fossil fuel. Many researchers have recommended using geothermal energy as an alternative; however, Past studies focus on the geophysical & geochemical investigation of this energy in the sedimentary and basement complex; only a few studies incorporated the remote sensing methods. Therefore, in this study, the preliminary examination of geothermal resources in the Middle Benue was carried out using satellite imagery in ArcMap. Landsat 8 scene (TIR, NIR, Red spectral bands) was used to estimate the Land Surface Temperature (LST). The Maximum Likelihood Classification (MLC) technique was used to classify sites with very low, low, moderate, and high LST. The intermediate and high classification happens to be possible geothermal zones, and they occupy 49% of the study area (38077km2). Riverline were superimposed on the LST layer, and the identification tool was used to locate high temperate sites. Streams that overlap on the selected sites were regarded as geothermal springs as. Surprisingly, the LST results show lower temperatures (<36°C) at the famous thermal springs (Awe & Wukari) than some unknown rivers/streams found in Kwande (38°C), Ussa, (38°C), Gwer East (37°C), Yola Cross & Ogoja (36°C). Studies have revealed that temperature increases with depth. However, this result shows excellent geothermal resources potential as it is expected to exceed the minimum geothermal gradient of 25.47 with an increase in depth. Therefore, further investigation is required to estimate the depth of the causative body, geothermal gradients, and the sustainability of the reservoirs by geophysical and field exploration. This method has proven to be cost-effective in locating geothermal resources in the study area. Consequently, the same procedure is recommended to be applied in other regions of the Precambrian basement complex and the sedimentary basins in Nigeria to save a preliminary field survey cost.

Keywords: ArcMap, geothermal resources, Landsat 8, LST, thermal springs, MLC

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6237 The Response of the Central Bank to the Exchange Rate Movement: A Dynamic Stochastic General Equilibrium-Vector Autoregressive Approach for Tunisian Economy

Authors: Abdelli Soulaima, Belhadj Besma

Abstract:

The paper examines the choice of the central bank toward the movements of the nominal exchange rate and evaluates its effects on the volatility of the output growth and the inflation. The novel hybrid method of the dynamic stochastic general equilibrium called the DSGE-VAR is proposed for analyzing this policy experiment in a small scale open economy in particular Tunisia. The contribution is provided to the empirical literature as we apply the Tunisian data with this model, which is rarely used in this context. Note additionally that the issue of treating the degree of response of the central bank to the exchange rate in Tunisia is special. To ameliorate the estimation, the Bayesian technique is carried out for the sample 1980:q1 to 2011 q4. Our results reveal that the central bank should not react or softly react to the exchange rate. The variance decomposition displayed that the overall inflation volatility is more pronounced with the fixed exchange rate regime for most of the shocks except for the productivity and the interest rate. The output volatility is also higher with this regime with the majority of the shocks exempting the foreign interest rate and the interest rate shocks.

Keywords: DSGE-VAR modeling, exchange rate, monetary policy, Bayesian estimation

Procedia PDF Downloads 285
6236 Predictive Analytics in Traffic Flow Management: Integrating Temporal Dynamics and Traffic Characteristics to Estimate Travel Time

Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

Abstract:

This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

Procedia PDF Downloads 63
6235 The Relationships between Carbon Dioxide (CO2) Emissions, Energy Consumption, and GDP for Turkey: Time Series Analysis, 1980-2010

Authors: Jinhoa Lee

Abstract:

The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of CO2 emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), carbon dioxide (CO2) emissions and gross domestic product (GDP) for Turkey using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Phillips–Perron (PP) test for stationarity, Johansen maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. All the variables in this study show very strong significant effects on GDP in the country for the long term. The long-run equilibrium in the VECM suggests negative long-run causalities from consumption of petroleum products and the direct combustion of crude oil, coal and natural gas to GDP. Conversely, positive impacts of CO2 emissions and electricity consumption on GDP are found to be significant in Turkey during the period. There exists a short-run bidirectional relationship between electricity consumption and natural gas consumption. There exists a positive unidirectional causality running from electricity consumption to natural gas consumption, while there exists a negative unidirectional causality running from natural gas consumption to electricity consumption. Moreover, GDP has a negative effect on electricity consumption in Turkey in the short run. Overall, the results support arguments that there are relationships among environmental quality, energy use and economic output but the associations can to be differed by the sources of energy in the case of Turkey over of period 1980-2010.

Keywords: CO2 emissions, energy consumption, GDP, Turkey, time series analysis

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6234 Optimisation of Photovoltaic Array with DC-DC Converter Groups

Authors: Fatma Soltani

Abstract:

In power electronics the DC-DC converters or choppers are now employed in large areas, particularly in the field of electricity generation by wind and solar energy conversion. Photovoltaic generators (GPV) can deliver maximum power for a point on the characteristic P = f (Vpv), called maximum power point (MPP), or climatic variations, entraiment fluctuation PPM. To remedy this problem is interposed between the generator and receiver a DC-DC converter. The converter is usually used a simple MOSFET chopper. However, the MOSFET can be applied in the field of low power when you need a high switching frequency but becomes highly dissipative when should block large voltages For PV generators medium and high power, the use of IGBT chopper is by far the most recommended. To reduce stress on semiconductor components using several choppers series connected in parallel is known as interleaved chopper. These choppers lead to rotas.

Keywords: converter DC-DC entrelaced, photovoltaic generators, IGBT, optimisation

Procedia PDF Downloads 528