Search results for: input impedance

Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

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A 1 kW power factor correction boost converter with an active snubber cell is presented in this paper. In the converter, the main switch turns on under zero voltage transition (ZVT) and turns off under zero current transition (ZCT) without any additional voltage or current stress. The auxiliary switch turns on and off under zero current switching (ZCS). Besides, the main diode turns on under ZVS and turns off under ZCS. The output current and voltage are controlled by the PFC converter in wide line and load range. The simulation results of converter are obtained for 1 kW and 100 kHz. One of the most important feature of the given converter is that it has direct power transfer as well as excellent soft switching techniques. Also, the converter has 0.99 power factor with the sinusoidal input current shape.

Keywords: power factor correction, direct power transfer, zero-voltage transition, zero-current transition, soft switching

Procedia PDF Downloads 962

Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

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We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

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Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

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Authors: U. Chattaraj, D. Meena

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Growth of traffic brings various negative effects, such as road accidents. To avoid such problems, a model is developed for the purpose of highway safety. In such areas, fuzzy logic is the most well-known simulation in the larger field. A model is accomplished for hilly and steep terrain based on Fuzzy Inference System (FIS), for which output is super elevation and input data is horizontal radius, vertical gradient, accident rate (AR). This result shows that the system can be efficaciously applied as for highway safety tool distinguishing hazards components correlated to the characteristics of the highway and has a great influence to the making of decision for accident precaution in transportation models. From this model, a positive relationship between geometric elements, accident rate, and super elevation is also identified.

Keywords: accident rate, fuzzy inference system, fuzzy logic, gradient, radius, super elevation

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Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

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Authors: U. Gunal, H. I. Turgut, H. Gurler, S. Kaya

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There are many ever-increasing and newly emerging problems with rapid population growth in the world. With the increase in people's quality of life in our daily life, acoustic comfort has become an important feature in the textile industry. In order to meet all these expectations in people's comfort areas and survive in challenging competitive conditions in the market without compromising the customer product quality expectations of textile manufacturers, it has become a necessity to bring functionality to the products. It is inevitable to research and develop materials and processes that will bring these functionalities to textile products. The noise we encounter almost everywhere in our daily life, in the street, at home and work, is one of the problems which textile industry is working on. It brings with it many health problems, both mentally and physically. Therefore, noise control studies become more of an issue. Besides, materials used in noise control are not sufficient to reduce the effect of the noise level. The fabrics used in acoustic studies in the textile industry do not show sufficient performance according to their weight and high cost. Thus, acoustic textile products can not be used in daily life. In the thesis study, the attributions used in the noise control and building acoustics studies in the literature were analyzed, and the product with the highest damping value that a textile material will have was designed, manufactured, and tested. Optimum values were obtained by using different material samples that may affect the performance of the acoustic material. Acoustic measurement methods should be applied to verify the acoustic performances shown by the parameters and the designed three-dimensional structure at different values. In the measurements made in the study, the device designed for determining the acoustic performance of the material for both the impedance tube according to the relevant standards and the different noise types in the study was used. In addition, sound records of noise types encountered in daily life are taken and applied to the acoustic absorbent fabric with the aid of the device, and the feasibility of the results and the commercial ability of the product are examined. MATLAB numerical computing programming language and libraries were used in the frequency and sound power analyses made in the study.

Keywords: acoustic, egg crate, fabric, textile

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Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

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This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

Procedia PDF Downloads 389

Authors: Stephy Saavedra, Annsy C. Arredondo, Gisele Monteiro, Adalberto Pessoa Jr, Carol N. Flores-Fernandez, Amparo I. Zavaleta

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L-asparaginase from bacterial sources is used in leukemic treatment and food industry. This enzyme is classified based on its affinity towards L-asparagine and L-glutamine. Likewise, ansZ genes express L-asparaginase with higher affinity to L-asparagine. The aim of this work was to clone and express of ansZ gene from Bacillus sp. CH11 isolated from Chilca salterns in Peru. The gene encoding L-asparaginase was cloned into pET15b vector and transformed in Escherichia coli BL21 (DE3) pLysS. The expression was carried out in a batch culture using LB broth and 0.5 mM IPTG. The recombinant L-asparaginase showed a molecular weight of ~ 39 kDa by SDS PAGE and a specific activity of 3.19 IU/mg of protein. The cloning and expression of ansZ gene from this halotolerant Bacillus sp. CH11 allowed having a biological input to improve a future scaling-up.

Keywords: ansZ gene, Bacillus sp, Chilca salterns, recombinant L-asparaginase

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Authors: Iva Nedelcheva

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This study is part of a doctoral thesis on the topic of Hyperfiction: Past, Present and Future of Storytelling through Hypertext. It explores in depth the impact of transmedia storytelling and the role of hypertext in the realm of the currently popular social media phenomenon Pokémon GO. Storytelling is a powerful method to engage and unite people. Moreover, the technology progress adds a whole new angle to the method, with hypertext and cross-platform sharing that enhance the traditional storytelling so much that transmedia storytelling gives unlimited opportunities to affect the everyday life of people across the globe. This research aims at examining the transmedia storytelling approach in Pokémon GO, and explaining how that contributed to its establishment as a massive worldwide hit in less than a week. The social engagement is investigated in all major media platforms, including traditional and online media channels. Observation and content analyses are reported in this paper to form the conclusion that transmedia storytelling with the input of hypertext has a promising future as a method of establishing a productive and rewarding communication strategy.

Keywords: communication, hypertext, Pokemon Go, storytelling, transmedia

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Osama Aziz, Hamza Ahmad, Muhibur Rahman

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The performance of wireless communication systems has been suggested to be improved by UWB MIMO antenna systems. However, creating a successful UWB MIMO antenna is a difficult undertaking that calls for resolving a number of design issues, including radiation efficiency, size, and frequency range. This study's primary objective is to create a novel, highly effective, small-sized, ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna and investigate its potential applications in body-centric communication. Two radiating elements, shared ground plane, circular stubs, and t-shaped isolation elements are used to achieve the MIMO antenna. Outstanding multiplexing efficiency, significant peak gain across the entire UWB frequency spectrum, extremely low mutual coupling (S21=-16 dB), high diversity gain (DG>9), and low envelop correlation are achieved. The proposed antenna will be one of the promising candidates for body centric communication.

Keywords: UWB communication, UWB MIMO antennas, body-centric communication, diversity gain

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Authors: Mohamad Baqer Heidari, Hefzollah.Mohammadian

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This brief presents two original implementations of improved accuracy current-mode multiplier/divider circuits. Besides the advantage of their simplicity, these original multiplier/divider structures present the advantage of very small linearity errors that can be obtained as a result of the proposed design techniques (0.75% and 0.9%, respectively, for an extended range of the input currents). The original multiplier/divider circuits permit a facile reconfiguration, the presented structures representing the functional basis for implementing complex function synthesizer circuits. The proposed computational structures are designed for implementing in 0.18-µm CMOS technology, with a low-voltage operation (a supply voltage of 1.2 V). The circuits’ power consumptions are 60 and 75 µW, respectively, while their frequency bandwidths are 79.6 and 59.7 MHz, respectively.

Keywords: analog signal processing, current-mode operation, functional core, multiplier, reconfigurable circuits, industrial package systems

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: MD Mashiur Rahman, Muhammad Arshadul Haque

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Emerging conservation agriculture (CA) is an option for improving soil health and maintaining environmental sustainability for intensive agriculture, especially in the tropical climate. Three years lengthy research experiment was performed in arid climate from 2018 to 2020 at research field of Bangladesh Agricultural Research Station (RARS)F, Jamalpur (soil texture belongs to Agro-Ecological Zone (AEZ)-8/9, 24˚56'11''N latitude and 89˚55'54''E longitude and an altitude of 16.46m) to evaluate the effect of CA approaches on energy use efficiency and a streamlined life cycle greenhouse gas (GHG) emission of wheat production. For this, the conservation tillage practices (strip tillage (ST) and minimum tillage (MT)) were adopted in comparison to the conventional farmers' tillage (CT), with retained a fixed level (30 cm) of residue retention. This study examined the relationship between energy consumption and life cycle greenhouse gas (GHG) emission of wheat cultivation in Jamalpur region of Bangladesh. Standard energy equivalents megajoules (MJ) were used to measure energy from different inputs and output, similarly, the global warming potential values for the 100-year timescale and a standard unit kilogram of carbon dioxide equivalent (kg CO₂eq) was used to estimate direct and indirect GHG emissions from the use of on-farm and off-farm inputs. Farm efficiency analysis tool (FEAT) was used to analyze GHG emission and its intensity. A non-parametric data envelopment (DEA) analysis was used to estimate the optimum energy requirement of wheat production. The results showed that the treatment combination having MT with optimum energy inputs is the best suit for cost-effective, sustainable CA practice in wheat cultivation without compromising with the yield during the dry season. A total of 22045.86 MJ ha⁻¹, 22158.82 MJ ha⁻¹, and 23656.63 MJ ha⁻¹ input energy for the practice of ST, MT, and CT was used in wheat production, and output energy was calculated as 158657.40 MJ ha⁻¹, 162070.55 MJ ha⁻¹, and 149501.58 MJ ha⁻¹, respectively; where energy use efficiency/net energy ratio was found to be 7.20, 7.31 and 6.32. Among these, MT is the most effective practice option taken into account in the wheat production process. The optimum energy requirement was found to be 18236.71 MJ ha⁻¹ demonstrating for the practice of MT that if recommendations are followed, 18.7% of input energy can be saved. The total greenhouse gas (GHG) emission was calculated to be 2288 kgCO₂eq ha⁻¹, 2293 kgCO₂eq ha⁻¹ and 2331 kgCO₂eq ha⁻¹, where GHG intensity is the ratio of kg CO₂eq emission per MJ of output energy produced was estimated to be 0.014 kg CO₂/MJ, 0.014 kg CO₂/MJ and 0.015 kg CO₂/MJ in wheat production. Therefore, CA approaches ST practice with 30 cm residue retention was the most effective GHG mitigation option when the net life cycle GHG emission was considered in wheat production in the silt clay loam soil of Bangladesh. In conclusion, the CA approaches being implemented for wheat production involving MT practice have the potential to mitigate global warming potential in Bangladesh to achieve soil carbon footprint, where the life cycle assessment approach needs to be applied to a more diverse range of wheat-based cropping systems.

Keywords: conservation agriculture and tillage, energy use efficiency, life cycle GHG, Bangladesh

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Authors: Rebecca M. Dagger, Katy Hadgraft, Matthew Teggart, Peter Angell

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Background: There is a growing body of evidence that demonstrates the association between sedentary behaviour, cardiometabolic risk and all-cause mortality. Since full time working adults spend approximately 8 hours per day in the workplace, interventions to reduce sedentary behaviour at work may alleviate some of the negative health outcomes associated with sedentary behaviour. The aims of this pilot study were to assess the impacts of using a Sit-Stand workstation on markers of cardiometabolic health in a cohort of desk workers. Methods: Twenty eight participants were recruited and randomly assigned to a control (n=5 males, 9 females, mean age 37 years ± 9.4 years) or intervention group (n= 5 males, 9 females, mean age 42 years ± 12.7 years). All participants attended the labs on 2 occasion’s pre and post intervention, following baseline measurements the intervention participants had the Sit Stand Workstations (Ergotron, USA) installed for a 10 week intervention period. The Sit Stand workstations allow participants to stand or sit at their usual workstation and participants were encouraged to the use the desk in a standing position at regular intervals throughout the working day. Cardiometabolic risk markers assessed were body mass, body composition (using bio impedance analysis; Tanita, Tokyo), fasting blood Total Cholesterol (TC), lipid profiles (HDL-C, LDL-C, TC: HDL-C ratio), triglycerides and fasting glucose (Cholestech LDX), resting systolic and diastolic blood pressure and resting heart rate. ANCOVA controlling for baseline values was used to assess the group difference in changes in risk markers between pre and post intervention. Results: The 10 week intervention was associated with significant reductions in some cardiometabolic risk factors. There were significant group effects on change in body mass (F (1,25)=5.915, p<0.05), total body fat percentage (F(1,25)=12.615, p<0.01), total fat mass (F (1,25)=6.954, p<0.05), and systolic blood pressure (F (1,25)=5.012, p<0.05). There were no other significant group effects on changes in other cardiometabolic risk markers. Conclusion: This pilot study highlights the importance of reducing sedentary behaviour in the workplace for reduction in cardiometabolic risk markers. Further research is required to support these findings.

Keywords: sedentary behaviour, caridometabolic risk, evidence, risk makers

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Huey-Kuo Chen

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This paper applies directional marginal productivity model to study the shadow price of emissions by transportation modes in the years of 2011 and 2013 with the aim to provide a reference for policy makers to improve the emission of pollutants. One input variable (i.e., energy consumption), one desirable output variable (i.e., vehicle kilometers traveled) and three undesirable output variables (i.e., carbon dioxide, sulfur oxides and nitrogen oxides) generated by road transportation modes were used to evaluate directional marginal productivity and directional shadow price for 18 transportation modes. The results show that the directional shadow price (DSP) of SOx is much higher than CO2 and NOx. Nevertheless, the emission of CO2 is the largest among the three kinds of pollutants. To improve the air quality, the government should pay more attention to the emission of CO2 and apply the alternative solution such as promoting public transportation and subsidizing electric vehicles to reduce the use of private vehicles.

Keywords: marginal productivity, road transportation modes, shadow price, undesirable outputs

Procedia PDF Downloads 147

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Sopida Vacharasukpo, Sudarat Khwan-On

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This paper proposes a high step-up DC-DC converter topology for renewable energy system applications. The proposed converter employs only a single power switch instead of using several switches. Compared to the conventional DC-DC step-up converters the higher voltage gain with small output ripples can be achieved by using the proposed high step-up DC-DC converter topology. It can step up the low input voltage (20-50Vdc) generated from the photovoltaic modules to the high output voltage level approximately 600Vdc in order to supply the three-phase inverter fed the three-phase motor drive. In this paper, the operating principle of the proposed converter topology and its control strategy under the continuous conduction mode (CCM) are described. Finally, simulation results are shown to demonstrate the effectiveness of the proposed high step-up DC-DC converter with its control strategy to increase the voltage step-up conversion ratio.

Keywords: DC-DC converter, high step-up ratio, renewable energy, single switch

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Authors: Oleg Oborin

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This paper is dedicated to the development of the model, which can be used to evaluate the effectiveness of long-term corporate strategies and identify the best strategies. The theoretical model of the relatively homogenous product market (such as iron and steel industry, mobile services or road transport) has been developed. In the model, the market consists of a large number of companies with different internal characteristics and objectives. The companies can perform mergers and acquisitions in order to increase their market share. The model allows the simulation of long-time dynamics of the market (for a period longer than 20 years). Therefore, a large number of simulations on random input data was conducted in the framework of the model. After that, the results of the model were compared with the dynamics of real markets, such as the US steel industry from the beginning of the XX century to the present day, and the market of mobile services in Germany for the period between 1990 and 2015.

Keywords: Economic Modelling, Long-Time Strategy, Mergers and Acquisitions, Simulation

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Authors: Muhammad Ilyas, Awais Khan, Syed Ali Raza Shah

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DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is getting the interest of the scientific community in robotics, especially in the robotic arm, a flexible joint manipulator. The current research work is based on position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in hardware setup based on LabVIEW programming is slightly greater than simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the dc motor varies between 0-8V to ensure minimal steady error while tracking the position and speed of the DC motor.

Keywords: DC motor, labview, proportional integral derivative control, position tracking, speed tracking

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

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Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Norzalina Othman, Nurul Na’imy Wan, Azliza Mohd Rusli, Wan Noor Syahirah Meor Idris

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Iris detection is a process where the position of the eyes is extracted from the face images. It is a current method used for many applications such as for security purpose and drowsiness detection. This paper proposes the use of eyes detection in controlling side mirror of motor vehicles. The eyes detection method aims to make driver easy to adjust the side mirrors automatically. The system will determine the midpoint coordinate of eyes detection on RGB (color) image and the input signal from y-coordinate will send it to controller in order to rotate the angle of side mirror on vehicle. The eye position was cropped and the coordinate of midpoint was successfully detected from the circle of iris detection using Viola Jones detection and circular Hough transform methods on RGB image. The coordinate of midpoint from the experiment are tested using controller to determine the angle of rotation on the side mirrors.

Keywords: iris detection, midpoint coordinates, RGB images, side mirror

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Authors: Jesus Ruano, Asensi Oliva

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The hydrodynamic field generated by a jet expansion is computed via three dimensional compressible Large Eddy Simulation (LES). Finite Volume Method (FVM) will be the discretization used during this simulation as well as hybrid schemes based on Kinetic Energy Preserving (KEP) schemes and up-winding Godunov based schemes with instabilities detectors. Velocity and pressure fields will be stored at different surfaces near the jet, but far enough to enclose all the fluctuations, in order to use them as input for the acoustic solver. The acoustic field is obtained in the far-field region at several locations by means of a hybrid method based on Ffowcs-Williams and Hawkings (FWH) equation. This equation will be formulated in the spectral domain, via Fourier Transform of the acoustic sources, which are modeled from the results of the initial simulation. The obtained results will allow the study of the broadband noise generated as well as sound directivities.

Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, jet noise

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Authors: Ramesh P., Aby Joseph

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Micro Inverters provide Module Embedded Solution for harvesting energy from small-scale solar photovoltaic (PV) panels. In addition to higher modularity & reliability (25 years of life), the MicroInverter has inherent advantages such as avoidance of long DC cables, eliminates module mismatch losses, minimizes partial shading effect, improves safety and flexibility in installations etc. Due to the above-stated benefits, the renewable energy technology with Solar Photovoltaic (PV) Micro Inverter becomes more widespread in Village Nano Grid application ensuring grid independence for rural communities and areas without access to electricity. While the primary objective of this paper is to discuss the problems related to rural electrification, this concept can also be extended to urban installation with grid connectivity. This work presents a comprehensive analysis of the power circuit design, control methodologies and prototyping of 300Wₚ Single Phase PV Micro Inverter. This paper investigates two different topologies for PV Micro Inverters, based on the first hand on Single Stage Flyback/ Forward PV Micro-Inverter configuration and the other hand on the Double stage configuration including DC-DC converter, H bridge DC-AC Inverter. This work covers Power Decoupling techniques to reduce the input filter capacitor size to buffer double line (100 Hz) ripple energy and eliminates the use of electrolytic capacitors. The propagation of the double line oscillation reflected back to PV module will affect the Maximum Power Point Tracking (MPPT) performance. Also, the grid current will be distorted. To mitigate this issue, an independent MPPT control algorithm is developed in this work to reject the propagation of this double line ripple oscillation to PV side to improve the MPPT performance and grid side to improve current quality. Here, the power hardware topology accepts wide input voltage variation and consists of suitably rated MOSFET switches, Galvanically Isolated gate drivers, high-frequency magnetics and Film capacitors with a long lifespan. The digital controller hardware platform inbuilt with the external peripheral interface is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the PV Micro Inverter is written in C language and was developed using code composer studio Integrated Development Environment (IDE). In this work, the prototype hardware for the Single Phase Photovoltaic Micro Inverter with Double stage configuration was developed and the comparative analysis between the above mentioned configurations with experimental results will be presented.

Keywords: double line oscillation, micro inverter, MPPT, nano grid, power decoupling

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Authors: Abderraouf Gaaloul, Faouzi Msahli

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The use of standard sliding mode controller, usually, leads to the appearing of an undesirable chattering phenomenon affecting the control signal. Such problem can be overcome using a higher-order sliding mode controller (HOSMC) which preserves the main properties of the standard sliding mode and deliberately increases the control smoothness. In this paper, we propose a new HOSMC for a class of uncertain multi-input multi-output nonlinear systems. Based on high gain and integral sliding mode paradigms, the established control scheme removes theoretically the chattering phenomenon and provides the stability of the control system. Numerical simulations are developed to show the effectiveness of the proposed controller when applied to solve a control problem of two water levels into a quadruple-tank process.

Keywords: nonlinear systems, sliding mode control, high gain, higher order

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Authors: Kuei-Chun Liu, Yu-Yu Lai, Ching-Hong Wu, Hsiao-Han Huang

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The number of Android applications (Apps) has increased rapidly in recent years. In order to get better programmatic control over Apps, we designed a record-and-replay mechanism to record Android input events and accessibility service events then make shortcuts. The shortcut is useful for complicated routine works and to Android beginners. We also generated graphical user interface (GUI) API by these shortcuts. GUI API helps developers make integrated Apps which can control other third-party Apps even if the official API is not offered by their providers. We demonstrated the usage of GUI API with two integrated Apps: Universal Bank App and Universal Communication App. Universal Bank App integrates three accounts from different banks and Universal Communication App integrates Line with WhatsApp. Both of them show the advantage of extendable GUI API. Furthermore, using our mechanism, shortcuts could replay almost all of the Top-100 Apps on Google Play correctly. In sum, the approach we present can help both Android developers and general users.

Keywords: graphical user interface, GUI API, record-and-replay, third-party apps

Procedia PDF Downloads 407

Authors: Manish Gupta

Abstract:

Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).

Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use

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Authors: Glaoui Hachemi

Abstract:

In this paper, a scheme based on multi-input multi output Fuzzy Sliding Mode control (MIMO-FSMC) for linear speed regulation of winding system is proposed. Once the uncoupled model of the winding system was obtained, a smooth control function with a threshold was selected to indicate how far away the case was from the sliding surface. nevertheless, this control function depends closely on the higher bound of the uncertainties, which generates overlap. So, this size has to be chosen with broad care to obtain high performances. Usually, the upper bound of uncertainties is difficult to know before motor operation, so, a Fuzzy Sliding Mode controller is investigated to resolve this problem, a simple Fuzzy inference mechanism is used to decrease the chattering phenomenon by simple adjustments. A simulation study is achieved and that the indicate fuzzy sliding mode controllers have great potential for use as an alternative to the conventional sliding mode control.

Keywords: Winding system, induction machine, Mechanical tension, Proportional-integral (PI), sliding mode control, Fuzzy logic

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Authors: Nermin Sökmen

Abstract:

An effort estimation model is needed for software-intensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

Keywords: functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis

Procedia PDF Downloads 293