Thermal Analysis of Fair Scheduling in Real-time Embedded Systems

Over the past few decades, increased demand of highly sophisticated real-time applications with complex functionalities has directly led to exponentially increased power consumption and significantly elevated system temperatures. These elevated temperature and thermal variations present formidable challenges towards system reliability, performance, cooling cost and leakages. This article explores the thermal management strength of two fairness based algorithms, namely Proportional Fair (PFair) and Deadline Partitioning Fair (DP-Fair). In related literature, the introduction of fairness is often considered as a tool to achieve optimality in multiprocessor scheduling algorithms. This work shows that these algorithms bring about better thermal profile when compared with the commonly used Earliest Deadline First (EDF) algorithm in similar conditions both in uniprocessor and multiprocessor environments. A simulation is conducted for periodic task set model. The obtained results are encouraging and show that use of fairness based algorithms reduces the operating temperature, peak temperature, and thermal variations

Hybrid System Power Generation'wind-photovoltaic' connected to the Electrical Network 220 kV

Renewable energy have the potential to generate electricity cleanly without pollution and a lesser dependence of resources for this production of electric power by these systems sources such as solar, wind, hydro, geothermal and biomass instead anti-environmental conventional systems such as gas, coal and oil is a remarkable idea but not frequent in Algeria. Our research focuses on the study of a hybrid energy system (Photovoltaic-Wind), connected to the Electrical Network 220 kV and this by tracking the maximum power point (MPPT) for two energy sources. For this, methods based on optimization algorithms were used side PV array and Wind turbine. With regard to the wind turbine, optimization was based on an analytical approach method. The Matlab/Simulink  is used for simulated power output from Hybrid System, power delivered to or from grid and phase voltage of the inverter le

Angular Symmetric Axis Constellation Model for off-line Odia Handwritten Characters Recognition

Optical character recognition is one of the emerging research topics in the field of image processing, and it has extensive area of application in pattern recognition. Odia handwritten script is the most research concern area because it has eldest and most likable language in the state of odisha, India. Odia character is a usually handwritten, which was generally occupied by scanner into machine readable form. In this regard several recognition technique have been evolved for variance kind of languages but writing pattern of odia character is just like as curve appearance; Hence it is more difficult for recognition. In this article we have presented the novel approach for Odia character recognition based on the different angle based symmetric axis feature extraction technique which gives high accuracy of recognition pattern. This empirical model generates a unique angle based boundary points on every skeletonised character images. These points are interconnected with each other in order to extract row and column symmetry axis. We extracted feature matrix having mean distance of row, mean angle of row, mean distance of column and mean angle of column from centre of the image to midpoint of the symmetric axis respectively. The system uses a 10 fold validation to the random forest (RF) classifier and SVM for feature matrix. We have considered the standard database on 200 images having each of 47 Odia character and 10 Odia numeric for simulation. As we have noted outcome of simulation of SVM and RF yields 96.3% and 98.2% accuracy rate on NIT Rourkela Odia character database and 88.9% and 93.6% from ISI Kolkata Odia numerical database

Improving Resilience and Self-Esteem among University Students with Entrepreneurship Simulation Board Game

This study aims to evaluate the effect of the frequency of playing a board game that simulates entrepreneurial experience called “Traders” on the university students’ resilience and self-esteem. Traders Board Game (TBG) was developed in 2015 with an aim to improve several entrepreneurship skills among young adults, and resilience being one of them. Pre and posttests of resilience have been done to 12 participants before they were divided into three groups: the control group, who did not play the game, the experimental group A, who played the game once a week for three weeks, and the experimental group B, who played the game twice a week for three weeks. Resilience was measured by adapting Connor-Davidson Resilience Scale, whereas self-esteem was measured by utilizing Mruk two-dimensional Self-esteem scale. There was a statistically significant difference among the the three groups in resilience improvement, where the experimental group A scored the highest, and no significant difference was discovered in terms of self-eteem improvement. The results suggested that playing TBG in certain frequency significantly improves resilience among the participants

Impact of Different Time of Use Electricity Pricing Structure on Residential Consumer

Load profile for residential users is different from commercial users where peak load occurs outside of work hours compared to working hours. Consequently, the Time of Use-based electricity price must be different not only in terms of price, but also in terms of time block structure. This paper examines the impacts of different TOU structures on TOU prices and load profiles of residential consumer. Four TOU structures are tested on the real load profile for a selected residential consumer area in Malaysia. Two elasticity factors are used for each structure to represent two different groups of users, a group that responds highly to price changes and a group that does not. The TOU price set for each structure is determined optimally subject to the following constraints; the price difference between the TOU and a fixed price per hour should be minimized and the amount of difference between price increase and price drop should be equal. From the analysis, the TOU structure with 12-time blocks provides better price signals and peak load reduction

Design and Optimization of a High Gain Multiband Patch Antenna for Millimeter Wave Applications

This paper presents an enhanced Quadri-band microstrip patch antenna, using defective slots in the ground plane, designed to operate in the millimeter wave band, formulated using cavity model and simulated by an EM-simulator, based on finite element method: HFSSv15 (High Frequency Structure Simulator). The proposed antenna incorporates two symmetric patterns of “U” shaped slots with an “I” shaped slot engraved in the middle of the ground plane. The resulting antenna has four frequency bands; the first resonant frequency is located in the Ka band, at about 27Ghz, the second at nearly 35Ghz, the third at 41Ghz and the last one at 51GHz. Those resonant frequencies could be shifted by tuning the slots dimensions introduced if the ground plane of the proposed antenna.

A Flexible Optical Sensor for Microalbuminuria Spectroscopy

A flexible optical sensor unit was developed for the detection of albumin level in human urine. It consists of polydimethylsiloxane thinfilm with the microscopic glass as the substrate. A gradual increase of albumin level may indicate signs of health problem such as diabetes, hypertension, and endothelial dysfunction. The experimental results showed there are a spectral shift and an increase in absorbed light increase in intensity of light with sodium urate at different concentration as a substitute of urine sample. The transmittance and reflection of PDMS was determined in the 400–1400 nm wavelength range using halogen-detrium as the excitation light source to predict the sensor sensitivity based on the Beer–Lambert law. The results exhibited that the light intensity increases as the concentration of the sodium urate increases. This performance of prototype sensor ignites an alternative for albumin detection using flexible structure

Mathematical Modeling of Photovoltaic Thermal-Thermoelectric (PVT-TE) Air Collector

Photovoltaic (PV) cell from solar energy is one of the most widely adopted renewable energy source and commercially available system that can be used in various applications. More appealing application of PV arrays used in thermoelectric (TE) device was it can convert solar thermal energy from temperature difference into electric energy to act as power generators. In this study, a theoretical model is developed by using conducting steady state energy analysis of a PVT-TE air collector. The matrix inversion method is used to obtain energy balance equation. The effect of various parameters also investigated. The mass flow rate of range 0.01 kg/s to 0.05 kg/s and solar intensity of 400 W/m2, 600 W/m2 and 800 W/m2 was used to obtain outlet temperature, To in the range about 28.9oC to 43.7oC and PV temperature, Tp about 35.3oC to 60oC

A Fault Detection Technique for Series-Compensated Lines by TCSC during Power Swing

The performance of a distance relay is very susceptible to power swing. In order to avoid generating unwanted trip in such condition, a power swing block function (PSB) is used in distance relays. However, if a fault occurs in power swing condition, the relay should distinguish the fault from power swing and generate trip rapidly. Detection a fault in a series-compensated line by Series Capacitor (SC) during the power swing is more complicated than in an uncompensated line due to complex transients generated by series capacitor and the Metal–Oxide Varistor (MOV) operation. In a series-compensated line by TCSC, it is further complicated due to nonlinear variation of compensation level during power swing and fault, moreover, non-unique application mode of TCSC for different faults which is dependent on fault current. This paper examines a method based on negative sequence current to detecting all types of fault during power swing in a series-compensated line by TCSC. The method is tested for different TCSC-compensated power systems include SMIB and 9-bus 3-machine systems. Different types of faults, i.e., symmetrical, asymmetrical and high resistance faults occurring during a power swing are simulated by MATLAB/SIMULINK to examine the algorithm

Very-Short Term Wind Power Forecasting through Wavelet Based ANFIS

This paper proposes a Wavelet based Adaptive Neuro-Fuzzy Inference System (WANFIS) applied to forecast the wind power and enhance the accuracy of one step ahead with a 10 minutes resolution of real time data collected from a wind farm in North India. The proposed method consists two cases. In the first case all the inputs of wind series and output of wind power decomposition coefficients are carried out to predict the wind power. In the second case all the inputs of wind series decomposition coefficients are carried out to get wind power prediction. The performance of proposed WANFIS is compared to Wavelet Neural Network (WNN) and the results of the proposed model are shown superior to compared methods