Search results for: type-I error

Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

Abstract:

Opinion dynamics models use an agent-based modeling approach to model people’s opinions. Model's properties are usually explored by testing the two 'degrees of freedom': the interaction rule and the network topology. The latter defines the connection, and thus the possible interaction, among agents. The interaction rule, instead, determines how agents select each other and update their own opinion. Here we show the existence of the third degree of freedom. This can be used for turning one model into each other or to change the model’s output up to 100% of its initial value. Opinion dynamics models represent the evolution of real-world opinions parsimoniously. Thus, it is fundamental to know how real-world opinion (e.g., supporting a candidate) could be turned into a number. Specifically, we want to know if, by choosing a different opinion-to-number transformation, the model’s dynamics would be preserved. This transformation is typically not addressed in opinion dynamics literature. However, it has already been studied in psychometrics, a branch of psychology. In this field, real-world opinions are converted into numbers using abstract objects called 'scales.' These scales can be converted one into the other, in the same way as we convert meters to feet. Thus, in our work, we analyze how this scale transformation may affect opinion dynamics models. We perform our analysis both using mathematical modeling and validating it via agent-based simulations. To distinguish between scale transformation and measurement error, we first analyze the case of perfect scales (i.e., no error or noise). Here we show that a scale transformation may change the model’s dynamics up to a qualitative level. Meaning that a researcher may reach a totally different conclusion, even using the same dataset just by slightly changing the way data are pre-processed. Indeed, we quantify that this effect may alter the model’s output by 100%. By using two models from the standard literature, we show that a scale transformation can transform one model into the other. This transformation is exact, and it holds for every result. Lastly, we also test the case of using real-world data (i.e., finite precision). We perform this test using a 7-points Likert scale, showing how even a small scale change may result in different predictions or a number of opinion clusters. Because of this, we think that scale transformation should be considered as a third-degree of freedom for opinion dynamics. Indeed, its properties have a strong impact both on theoretical models and for their application to real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

Procedia PDF Downloads 136

Authors: Ran Etgar

Abstract:

The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X̄ chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter ȳ is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.

Keywords: SPC, round-off data, control limit, rounding error

Procedia PDF Downloads 54

Authors: Alicia C. Sanchez

Abstract:

This paper investigates the implementation of RAFU functions (radical functions) in robotics and automation. Specifically, the main goal is to show how these functions may be useful in lane-keeping control and the lateral control of autonomous machines, vehicles, robots or the like. From the knowledge of several points of a certain route, the RAFU functions are used to achieve the lateral control purpose and maintain the lane-keeping errors within the fixed limits. The stability that these functions provide, their ease of approaching any continuous trajectory and the control of the possible error made on the approximation may be useful in practice.

Keywords: automatic navigation control, lateral control, lane-keeping control, RAFU approximation

Procedia PDF Downloads 277

Authors: Reza Lotfalian, Sudarshan Martins, Peter Radziszewski

Abstract:

The effect of reliability on life-cycle cost, including initial and maintenance cost of a system is studied. The failure probability of a component is used to calculate the average maintenance cost during the operation cycle of the component. The standard deviation of the life-cycle cost is also calculated as an error measure for the average life-cycle cost. As a numerical example, the model is used to study the average life cycle cost of an electric motor.

Keywords: initial cost, life-cycle cost, maintenance cost, reliability

Procedia PDF Downloads 572

Authors: Ahlem Mougaida, Hedi Bel Hadj Salah

Abstract:

Several methods are suggested to improve the numerical integration in Galerkin weak form for Meshless methods. In fact, integrating without taking into account the characteristics of the shape functions reproduced by Meshless methods (rational functions, with compact support etc.), causes a large integration error that influences the PDE’s approximate solution. Comparisons between different methods of numerical integration for rational functions are discussed and compared. The algorithms are implemented in Matlab. Finally, numerical results were presented to prove the efficiency of our algorithms in improving results.

Keywords: adaptive methods, meshless, numerical integration, rational quadrature

Procedia PDF Downloads 336

Authors: S. Thomet, S. De-Paoli, F. Ghaffari, J. M. Daveau, P. Roche, O. Romain

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In this paper, we present a hardware module dedicated to understanding the fail reason of a System on Chip (SoC) exposed to a particle beam. Impact of Single-Event Effects (SEE) on processor-based SoCs is a concern that has increased in the past decade, particularly for terrestrial applications with automotive safety increasing requirements, as well as consumer and industrial domains. The SEE created by the impact of a particle on an SoC may have consequences that can end to instability or crashes. Specific hardening techniques for hardware and software have been developed to make such systems more reliable. SoC is then qualified using cosmic ray Accelerated Soft-Error Rate (ASER) to ensure the Soft-Error Rate (SER) remains in mission profiles. Understanding where errors are occurring is another challenge because of the complexity of operations performed in an SoC. Common techniques to monitor an SoC running under a beam are based on non-intrusive debug, consisting of recording the program counter and doing some consistency checking on the fly. To detect and understand SEE, we have developed a module embedded within the SoC that provide support for recording probes, hardware watchpoints, and a memory mapped register bank dedicated to software usage. To identify CPU failure modes and the most important resources to probe, we have carried out a fault injection campaign on the RTL model of the SoC. Probes are placed on generic CPU registers and bus accesses. They highlight the propagation of errors and allow identifying the failure modes. Typical resulting errors are bit-flips in resources creating bad addresses, illegal instructions, longer than expected loops, or incorrect bus accesses. Although our module is processor agnostic, it has been interfaced to a RISC-V by probing some of the processor registers. Probes are then recorded in a ring buffer. Associated hardware watchpoints are allowing to do some control, such as start or stop event recording or halt the processor. Finally, the module is also providing a bank of registers where the firmware running on the SoC can log information. Typical usage is for operating system context switch recording. The module is connected to a dedicated debug bus and is interfaced to a remote controller via a debugger link. Thus, a remote controller can interact with the monitoring module without any intrusiveness on the SoC. Moreover, in case of CPU unresponsiveness, or system-bus stall, the recorded information can still be recovered, providing the fail reason. A preliminary version of the module has been integrated into a test chip currently being manufactured at ST in 28-nm FDSOI technology. The module has been triplicated to provide reliable information on the SoC behavior. As the primary application domain is automotive and safety, the efficiency of the module will be evaluated by exposing the test chip under a fast-neutron beam by the end of the year. In the meantime, it will be tested with alpha particles and electromagnetic fault injection (EMFI). We will report in the paper on fault-injection results as well as irradiation results.

Keywords: fault injection, SoC fail reason, SoC soft error rate, terrestrial application

Procedia PDF Downloads 213

Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

Abstract:

Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

Procedia PDF Downloads 281

Authors: Anurag Sharma, Dinesh Kumar, Rahul Malhotra, Manoj Kumar

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 708

Authors: Fuad M. Alkoot

Abstract:

The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

Procedia PDF Downloads 191

Authors: Qiao-Yu Warren Cai

Abstract:

Due to the rise of big data, building corpora and using them to analyze ChineseL2 learners’ language output has become a trend. Various empirical research has been conducted using Chinese corpora built by different academic institutes. However, most of the research analyzed the data in the Chinese corpora usingcorpus-based qualitative content analysis with descriptive statistics. Descriptive statistics can be used to make summations about the subjects or samples that research has actually measured to describe the numerical data, but the collected data cannot be generalized to the population. Comte, a Frenchpositivist, has argued since the 19th century that human beings’ knowledge, whether the discipline is humanistic and social science or natural science, should be verified in a scientific way to construct a universal theory to explain the truth and human beings behaviors. Inferential statistics, able to make judgments of the probability of a difference observed between groups being dependable or caused by chance (Free Geography Notes, 2015)and to infer from the subjects or examples what the population might think or behave, is just the right method to support Comte’s argument in the field of TCSOL. Also, inferential statistics is a core of quantitative research, but little research has been conducted by combing corpora with inferential statistics. Little research analyzes the differences in Chinese L2 learners’ language corpus output errors by using theOne-way ANOVA so that the findings of previous research are limited to inferring the population's Chinese errors according to the given samples’ Chinese corpora. To fill this knowledge gap in the professional development of Taiwanese TCSOL, the present study aims to utilize the One-way ANOVA to analyze corpus output errors of Chinese L2 learners from America, Myanmar, and Singapore. The results show that no significant difference exists in ‘shì (是) sentence’ and word order errors, but compared with Americans and Singaporeans, it is significantly easier for Myanmar to have ‘sentence blends.’ Based on the above results, the present study provides an instructional approach and contributes to further exploration of how Chinese L2 learners can have (and use) learning strategies to lower errors.

Keywords: Chinese corpus, error analysis, one-way analysis of variance, Chinese L2 learners, Americans, myanmar, Singaporeans

Procedia PDF Downloads 85

Authors: Jaehoon Ha, Byungmo Kang, Kilho Hong, Jungsoo Park

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Electro-optical (EO) stabilized platforms have been widely used for surveillance and reconnaissance on various types of vehicles, from surface ships to unmanned air vehicles (UAVs). EO stabilized platforms usually consist of an assembly of structure, bearings, and motors called gimbals in which a gyroscope is installed. EO elements such as a CCD camera and IR camera, are mounted to a gimbal, which has a range of motion in elevation and azimuth and can designate and track a target. In addition, a laser range finder (LRF) can be added to the gimbal in order to acquire the precise slant range from the platform to the target. Recently, a versatile functionality of target localization is needed in order to cooperate with the weapon systems that are mounted on the same platform. The target information, such as its location or velocity, needed to be more accurate. The accuracy of the target information depends on diverse component errors and alignment errors of each component. Specially, the type of moving platform can affect the accuracy of the target information. In the case of flying platforms, or UAVs, the target location error can be increased with altitude so it is important to measure altitude as precisely as possible. In the case of surface ships, target location error can be increased with obliqueness of the elevation angle of the gimbal since the altitude of the EO stabilized platform is supposed to be relatively low. The farther the slant ranges from the surface ship to the target, the more extreme the obliqueness of the elevation angle. This can hamper the precise acquisition of the target information. So far, there have been many studies on EO stabilized platforms of flying vehicles. However, few researchers have focused on ship-borne EO stabilized platforms of the surface ship. In this paper, we deal with a target localization method when an EO stabilized platform is located on the mast of a surface ship. Especially, we need to overcome the limitation caused by the obliqueness of the elevation angle of the gimbal. We introduce a well-known approach for target localization using Unscented Kalman Filter (UKF) and present the problem definition showing the above-mentioned limitation. Finally, we want to show the effectiveness of the approach that will be demonstrated through computer simulations.

Keywords: target localization, ship-borne electro-optical stabilized platform, unscented kalman filter

Procedia PDF Downloads 497

Authors: Kamal Kaushik, Trisha, Dandapni, Sambit Nanda, A. Mukherjee, S. Pradhan

Abstract:

INTRODUCTION: As complexity in radiotherapy practice and processes are increasing, there is a need to assure quality control to a greater extent. At present, no international literature available with regards to the optimal quality control indicators for radiotherapy; moreover, few clinical audits have been conducted in the field of radiotherapy. The primary aim is to improve the processes that directly impact clinical outcomes for patients in terms of patient safety and quality of care. PROCEDURE: A team of an Oncologist, a Medical Physicist and a Radiation Therapist was formed for weekly clinical audits of patient’s undergoing radiotherapy audits The stages for audits include Pre planning audits, Simulation, Planning, Daily QA, Implementation and Execution (with image guidance). Errors in all the parts of the chain were evaluated and recorded for the development of further departmental protocols for radiotherapy. EVALUATION: The errors at various stages of radiotherapy chain were evaluated and recorded for comparison before starting the clinical audits in the department of radiotherapy and after starting the audits. It was also evaluated to find the stage in which maximum errors were recorded. The clinical audits were used to structure standard protocols (in the form of checklist) in department of Radiotherapy, which may lead to further reduce the occurrences of clinical errors in the chain of radiotherapy. RESULTS: The aim of this study is to perform a comparison between number of errors in different part of RT chain in two groups (A- Before Audit and B-After Audit). Group A: 94 pts. (48 males,46 female), Total no. of errors in RT chain:19 (9 needed Resimulation) Group B: 94 pts. (61 males,33 females), Total no. of errors in RT chain: 8 (4 needed Resimulation) CONCLUSION: After systematic periodic clinical audits percentage of error in radiotherapy process reduced more than 50% within 2 months. There is a great need in improving quality control in radiotherapy, and the role of clinical audits can only grow. Although clinical audits are time-consuming and complex undertakings, the potential benefits in terms of identifying and rectifying errors in quality control procedures are potentially enormous. Radiotherapy being a chain of various process. There is always a probability of occurrence of error in any part of the chain which may further propagate in the chain till execution of treatment. Structuring departmental protocols and policies helps in reducing, if not completely eradicating occurrence of such incidents.

Keywords: audit, clinical, radiotherapy, improving functionality

Procedia PDF Downloads 68

Authors: Mounir Bekaik, Messaoud Ramdani

Abstract:

We present in this work a new technique of stabilization for fault nonlinear systems. The approach we adopt focus on a fuzzy Luenverger observer. The T-S approximation of the nonlinear observer is based on fuzzy C-Means clustering algorithm to find local linear subsystems. The MOESP identification approach was applied to design an empirical model describing the subsystems state variables. The gain of the observer is given by the minimization of the estimation error through Lyapunov-krasovskii functional and LMI approach. We consider a three tank hydraulic system for an illustrative example.

Keywords: nonlinear system, fuzzy, faults, TS, Lyapunov-Krasovskii, observer

Procedia PDF Downloads 307

Authors: Suyeb Ahmed Khan, Mahmood Mian

Abstract:

Simulation plays an important role during all phases of the design and engineering of communications systems, from early stages of conceptual design through the various stages of implementation, testing, and fielding of the system. In the present paper, a simulation model has been constructed for the WCDMA system in order to evaluate the performance. This model describes multiusers effects and calculation of BER (Bit Error Rate) in 3G mobile systems using Simulink MATLAB 7.1. Gaussian Approximation defines the multi-user effect on system performance. BER has been analyzed with comparison between transmitting data and receiving data.

Keywords: WCDMA, simulations, BER, MATLAB

Procedia PDF Downloads 567

Authors: Said Elkassimi, Said Safi, B. Manaut

Abstract:

This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.

Keywords: adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF

Procedia PDF Downloads 298

Authors: Lukasz Grabowski, Konrad Pietrykowski, Michal Bialy

Abstract:

This paper presents the results of the research to verify the combustion in aircraft piston engine Asz62-IR. This engine was modernized and a type of ignition system was developed. Due to the high costs of experiments of a nine-cylinder 1,000 hp aircraft engine, a simulation technique should be applied. Therefore, computational fluid dynamics to simulate the combustion process is a reasonable solution. Accordingly, the tests for varied ignition advance angles were carried out and the optimal value to be tested on a real engine was specified. The CFD model was created with the AVL Fire software. The engine in the research had two spark plugs for each cylinder and ignition advance angles had to be set up separately for each spark. The results of the simulation were verified by comparing the pressure in the cylinder. The courses of the indicated pressure of the engine mounted on a test stand were compared. The real course of pressure was measured with an optical sensor, mounted in a specially drilled hole between the valves. It was the OPTRAND pressure sensor, which was designed especially to engine combustion process research. The indicated pressure was measured in cylinder no 3. The engine was running at take-off power. The engine was loaded by a propeller at a special test bench. The verification of the CFD simulation results was based on the results of the test bench studies. The course of the simulated pressure obtained is within the measurement error of the optical sensor. This error is 1% and reflects the hysteresis and nonlinearity of the sensor. The real indicated pressure measured in the cylinder and the pressure taken from the simulation were compared. It can be claimed that the verification of CFD simulations based on the pressure is a success. The next step was to research on the impact of changing the ignition advance timing of spark plugs 1 and 2 on a combustion process. Moving ignition timing between 1 and 2 spark plug results in a longer and uneven firing of a mixture. The most optimal point in terms of indicated power occurs when ignition is simultaneous for both spark plugs, but so severely separated ignitions are assured that ignition will occur at all speeds and loads of engine. It should be confirmed by a bench experiment of the engine. However, this simulation research enabled us to determine the optimal ignition advance angle to be implemented into the ignition control system. This knowledge allows us to set up the ignition point with two spark plugs to achieve as large power as possible.

Keywords: CFD model, combustion, engine, simulation

Procedia PDF Downloads 345

Authors: Mohammadreza DaqiqShirazi, Rouhollah Torabi, Alireza Riasi, Ahmad Nourbakhsh

Abstract:

In this paper, the flow in a sidewall gap of an impeller which belongs to a centrifugal pump is studied using numerical method. The flow in sidewall gap forms internal leakage and is the source of “disk friction loss” which is the most important cause of reduced efficiency in low specific speed centrifugal pumps. Simulation is done using CFX software and a high quality mesh, therefore the modeling error has been reduced. Navier-Stokes equations have been solved for this domain. In order to predict the turbulence effects the SST model has been employed.

Keywords: numerical study, centrifugal pumps, disk friction loss, sidewall gap

Procedia PDF Downloads 500

Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

Abstract:

In urban area, several landmarks may affect housing price and rents, hedonic analysis should employ distance variables corresponding to each landmarks. Unfortunately, the effects of distances to landmarks on housing prices are generally not consistent with the true price. These distance variables may cause magnitude error in regression, pointing a problem of spatial multicollinearity. In this paper, we provided some approaches for getting the samples with less bias and method on locating the specific sampling area to avoid the multicollinerity problem in two specific landmarks case.

Keywords: landmarks, hedonic regression, distance variables, collinearity, multicollinerity

Procedia PDF Downloads 437

Authors: S. J. Bindhu, Edwina G. Rodrigues, Jijo Balakrishnan

Abstract:

A grid-connected photovoltaic (PV) micro inverter with good performance properties is proposed in this paper. The proposed inverter with a quadrupler, having more efficiency and less voltage stress across the diodes. The stress that come across the diodes that use in the inverter section is considerably low in the proposed converter, also the protection scheme that we provided can eliminate the chances of the error due to fault. The proposed converter is implemented using perturb and observe algorithm so that the fluctuation in the voltage can be reduce and can attain maximum power point. Finally, some simulation and experimental results are also presented to demonstrate the effectiveness of the proposed converter.

Keywords: DC-DC converter, MPPT, quadrupler, PV panel

Procedia PDF Downloads 822

Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu, Tigray

Abstract:

Sesame is an important oilseed crop in Ethiopia; which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool; which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validated the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates; 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99; and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99, and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, sesame, normalized water productivity, nitrogen fertilizer

Procedia PDF Downloads 48

Authors: Keunhong Chae, Seokho Yoon

Abstract:

This paper proposes a cooperative Alamouti space time transmission scheme with low relay complexity for the cooperative communication systems. In the proposed scheme, the source node combines the data symbols to construct the Alamouti-coded form at the destination node, while the conventional scheme performs the corresponding operations at the relay nodes. In simulation results, it is shown that the proposed scheme achieves the second order cooperative diversity while maintaining the same bit error rate (BER) performance as that of the conventional scheme.

Keywords: Space-time transmission, cooperative communication system, MIMO.

Procedia PDF Downloads 328

Authors: Shagufta Tabassum

Abstract:

The study of dielectric properties in a binary mixture of liquids is very useful to understand the liquid structure, molecular interaction, dynamics, and kinematics of the mixture. Time-domain reflectometry (TDR) is a powerful tool for studying the cooperation and molecular dynamics of the H-bonded system. In this paper, we discuss the basic calibration and normalization procedure for time-domain reflectometry measurements. Our approach is to explain the different types of error occur during TDR measurements and how these errors can be eliminated or minimized.

Keywords: time domain reflectometry measurement techinque, cable and connector loss, oscilloscope loss, and normalization technique

Procedia PDF Downloads 183

Authors: Soheila Sadeghi

Abstract:

Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

Procedia PDF Downloads 23

Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu

Abstract:

Sesame is an important oilseed crop in Ethiopia, which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool, which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validate the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates, 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99, and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99 and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, normalized water productivity, nitrogen fertilizer, canopy cover, sesame

Procedia PDF Downloads 47

Authors: Sourabh Jain, Parul Madan

Abstract:

Traffic noise pollution has become a challenging problem for all metro cities of India due to rapid urbanization, growing population and rising number of vehicles and transport development. In Delhi the prime source of noise pollution is vehicular traffic. In Delhi it is found that the ambient noise level (Leq) is exceeding the standard permissible value at all the locations. Noise barriers or enclosures are definitely useful in obtaining effective deduction of traffic noise disturbances in urbanized areas. US’s Federal Highway Administration Model (FHWA) and Calculation of Road Traffic Noise (CORTN) of UK are used to develop spread sheets for noise prediction. Spread sheets are also developed for evaluating effectiveness of existing boundary walls abutting houses in mitigating noise, redesigning them as noise barriers. Study was also carried out to examine the changes in noise level due to designed noise barrier by using both models FHWA and CORTN respectively. During the collection of various data it is found that receivers are located far away from road at Rithala and Moolchand sites and hence extra barrier height needed to meet prescribed limits was less as seen from calculations and most of the noise diminishes by propagation effect.On the basis of overall study and data analysis, it is concluded that FHWA and CORTN models under estimate noise levels. FHWA model predicted noise levels with an average percentage error of -7.33 and CORTN predicted with an average percentage error of -8.5. It was observed that at all sites noise levels at receivers were exceeding the standard limit of 55 dB. It was seen from calculations that existing walls are reducing noise levels. Average noise reduction due to walls at Rithala was 7.41 dB and at Panchsheel was 7.20 dB and lower amount of noise reduction was observed at Friend colony which was only 5.88. It was observed from analysis that Friends colony sites need much greater height of barrier. This was because of residential buildings abutting the road. At friends colony great amount of traffic was observed since it is national highway. At this site diminishing of noise due to propagation effect was very less.As FHWA and CORTN models were developed in excel programme, it eliminates laborious calculations of noise. There was no reflection correction in FHWA models as like in CORTN model.

Keywords: IFHWA, CORTN, Noise Sources, Noise Barriers

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Authors: Tribhuvan N. Soorya

Abstract:

Charging and discharging of a capacitor through a resistor can be shown as exponential curve. Theoretically, it takes infinite time to fully charge or discharge a capacitor. The flow of charge is due to electrons having finite and fixed value of charge. If we carefully examine the charging and discharging process after several time constants, the points on q vs t graph become discrete and curve become discontinuous. Moreover for all practical purposes capacitor with charge (q0-e) can be taken as fully charged, as it introduces an error less than one part per million. Similar is the case for discharge of a capacitor, where the capacitor with the last electron (charge e) can be taken as fully discharged. With this, we can estimate the finite value of time for fully charging and discharging a capacitor.

Keywords: charging, discharging, RC Circuit, capacitor

Procedia PDF Downloads 424

Authors: Wu Sa, Zhang Qian, Li Qi, Wang Ye

Abstract:

Currently in humidity tests having not put the Dew point temperature as a control parameter, this paper selects wet and dry bulb thermometer to measure the vapor pressure, and introduces several the saturation vapor pressure formulas easily calculated on the controller. Then establish the Dew point temperature calculation model to obtain the relationship between the Dew point temperature and vapor pressure. Finally check through the 100 groups of sample in the range of 0-100 ℃ from "Psychrometric handbook", find that the average error is small. This formula can be applied to calculate the Dew point temperature in the humidity test.

Keywords: dew point temperature, psychrometric handbook, saturation vapor pressure, wet and dry bulb thermometer

Procedia PDF Downloads 461

Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi

Abstract:

This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.

Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables

Procedia PDF Downloads 341

Authors: Meetty Tomy, Arxhana G Thosar

Abstract:

This paper provides the implementation of optimal control for an armature-controlled DC motor. The selection of error weighted Matrix and control weighted matrix in order to implement optimal control theory for improving the dynamic behavior of DC motor is presented. The closed loop performance of Armature controlled DC motor with derived linear optimal controller is then evaluated for the transient operating condition (starting). The result obtained from MATLAB is compared with that of PID controller and simple closed loop response of the motor.

Keywords: optimal control, DC motor, performance index, MATLAB

Procedia PDF Downloads 386

Authors: Kaewkarn Phuangsombat, Arthit Phuangsombat, Anupun Terdwongworakul

Abstract:

Hard seeds will not grow and can cause mold in sprouting process. Thus, the hard seeds need to be separated from the normal seeds. Near infrared hyperspectral imaging in a range of 900 to 1700 nm was implemented to develop a model by partial least squares discriminant analysis to discriminate the hard seeds from the normal seeds. The orientation of the seeds was also studied to compare the performance of the models. The model based on hilum-up orientation achieved the best result giving the coefficient of determination of 0.98, and root mean square error of prediction of 0.07 with classification accuracy was equal to 100%.

Keywords: mung bean, near infrared, germinatability, hard seed

Procedia PDF Downloads 279