Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of the actual smart grid system is high in cost. Thus, simulation and modelling of the system is important to see the capability of the actual system before being employed. Since the smart grid and its components are usually modeled using MATLAB/Simulink, the communication between MATLAB/Simulink, IoT platform such as ThingSpeak and mobile application is crucial to be explored to gain a better understanding of the features of the smart grid. To achieve the objectives, there are five main steps which are simulation of grid-connected photovoltaic (PV) system to generate data to be monitored and controlled using HOMER software, then, development of monitoring on ThingSpeak and mobile application using MIT App Inventor 2. Next, the control system is developed on mobile application and the communication on how data are transferred between all the softwares are set up. The results show that all the seletected parameters can be monitored in real-time successfully. The developed mobile application can be used to control the MATLAB/Simulink in two modes. During automatic mode, ThingSpeak controls the MATLAB/Simulink by giving a zero signal (OFF) if load demand is less than the power generated by PV and a one signal (ON) if the load demand is greater than PV power. During manual mode, consumer can send ON or OFF signal to MATLAB/Simulink via the mobile application unconditionally. It is hoped that the proposed system will bring many benefits in modeling a complete smart grid system in MATLAB/Simulink.
One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,
... Show MoreThe purpose of our work is to report a theoretical study of electrons tunneling through semiconductor superlattice (SSL). The (SSL) that we have considered is (GaN/AlGaN) system within the energy range of ε < Vo, ε = Vo and ε > Vo, where Vo is the potential barrier height. The transmission coefficient (TN) was determined using the transfer matrix method. The resonant energies are obtained from the T (E) relation. From such system, we obtained two allowed quasi-levels energy bands for ε < VO and one band for ε VO.
Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreBackground:-The Modified Alvarado Scoring System (MASS) has been reported to be a cheap and quick diagnostic tool in patients with acute appendicitis. However, differences in diagnostic accuracy have been observed if the scores were applied to various populations and clinical settings.
Objectives:- The purpose of this study was to evaluate the diagnostic value of Modified Alvarado Scoring System in patients with acute appendicitis in our setting.
Methods:-one hundre twenty eight patients ,were included in this study, admitted to Al-Kindy teaching hospital from June 2009 to June 2010. Patients’ age ranged from 8 to 56 years (21±10) they were divided into three groups; paediatrics, child bearing age females & adult males,. MAS
The performance analyses of 15 kWp (kW peak) Grid -Tied solar PV system (that considered first of its type) implemented at the Training and Energy Research Center Subsidiary of Iraqi Ministry of Electricity in Baghdad city has been achieved. The system consists of 72 modules arranged in 6 strings were each string contains 12 modules connected in series to increase the voltage output while these strings connected in parallel to increase the current output. According to the observed duration, the reference daily yields, array daily yields and final daily yields of this system were (5.9, 4.56, 4.4) kWh/kWp/day respectively. The energy yield was 1585 kWh/kWp/year while the annual total solar irradiation received by solar array system was 198
... Show MoreAlzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
... Show MoreThe importance of this research has been to rationalize the cost of producing maize seeds through the followers of modern techniques and methods in agricultural activities such as genetic engineering for increasing production efficiency of maize seeds as well as the importance of calculating seed cost rationalization through the ABC system and thus rationalizing government spending. The research is based on one hypothesis in two ways that the use of genetic engineering on maize seeds works to: one - increase production efficiency of seeds and savings in agricultural inputs. 2. Rationalize the costs of examining and planting maize seeds. In order to calculate the costs will be based on the cost system based on activities ABC. The research
... Show MoreRecommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
... Show Moreالوصف Mixed ligand complexes of Cu (II), Co (II) and Zn (II) with 2-((4-(1-(4-chlorophenylimino) ethyl) phenylimino) methyl) phenol (L) and histidine (His) have been prepared and diagnosed by ¹H and13 C NMR, FT-IR and electronic spectral data, thermal gravimetric, molar conductance and metal analysis measurements. The ligand (L) shows a bidentate nature and the coordination occurs through N and O atoms of imine group and phenol group respectively whereas (His) behave as tridentate ligand, coordinating through the-NH2 group and carboxylate oxygen group and N atoms of imidazole ring. The analytical studies for three complexes have shown octahedral structure. The anticancer activity was screened against human cancer cell such Follicular
... Show MoreThree mesoporous silica with different functional group were prepared by one-step synthesis based on the simultaneous hydrolysis and condensation of sodium silicate with organo - silane in the presence of template surfactant polydimethylsiloxane - polyethyleneoxide (PDMS - PEO). The prepared materials were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), atomic force microscopy (AFM) and nitrogen adsorption/desorption experiments. The results indicate that the preparation of methyl and phenyl functionalized silica were successful and the mass of methyl and phenyl groups bonded to the silica structure are 15, 38 mmol per gram silica. The average diameter of the silica particles are 103.51,
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