Articles published in IJEER

Volume 9

Articles in press are peer reviewed, accepted articles to be published in this publication. When the final article is assigned to volumes 9, issues 3 of the publication, the article in press version will be removed and the final version will appear in the associated published volumes/issues of the publication.

Eye Drowsiness Tiredness Detection Based on Driver Experience Using Image Mining

These techniques introduce eye position state and it is parameter as a feasible means of sleepiness recognition. It has been recommended that an increase of eye sleepy state might indicates sleepiness. Thus this method can be used to caution the driver’s risk if driver drives the vehicle. These suggestion were derived from investigative an example of driver’s in attentive and sleepy situation. The gadget evaluate is base on tracking of the eye retina pupil (circular area) to calculate rate of eye sleepy condition. In this research study, individual change in the path of growing sleepiness from a drivers’ eye retina is examined. Data analysis study is interest on the improvement of a prepared display of sleepiness based on an arrangement of eye white and eye black measure values. This will use very accurate operational indicator of drowsiness. However, the main constraint of measure is that driver’s may not show this eye state until they are purely sleepy and/or weaken.

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Directivity and Bandwidth Enhancement of Patch Antenna using Metamaterial

This manuscript is the outcome of detailed research. A novel metamaterial structure is proposed in this paper to improve the directivity of the antenna. In this research paper a method of implementing metamaterial over the patch is used to enhance the directivity of rectangular microstrip patch antenna. From the results proposed expectation has been achieved, it is noted that in the presence of the LHM, the antenna is more directive and has a higher gain. This proposed patch is designed at the frequency of 2.75 GHz. The proposed structure is a combination of circular rings by virtue of its backward wave propagation property and negative reflection it improve the parameters of antenna.

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Classification & Feature extraction of Brain tumor from MRI Images using Modified ANN Approach

These techniques introduce eye position state and it is parameter as a feasible means of sleepiness recognition. It has been recommended that an increase of eye sleepy state might indicates sleepiness. Thus this method can be used to caution the driver’s risk if driver drives the vehicle. These suggestion were derived from investigative an example of driver’s in attentive and sleepy situation. The gadget evaluate is base on tracking of the eye retina pupil (circular area) to calculate rate of eye sleepy condition. In this research study, individual change in the path of growing sleepiness from a drivers’ eye retina is examined. Data analysis study is interest on the improvement of a prepared display of sleepiness based on an arrangement of eye white and eye black measure values. This will use very accurate operational indicator of drowsiness. However, the main constraint of measure is that driver’s may not show this eye state until they are purely sleepy and/or weaken.

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Application of HFPSO-TOPSIS approach for optimally locating and sizing of reactive power compensating devices for voltage control ancillary service

Modern power system with renewables in distribution network has made the optimal sizing and location of reactive power support crucial and essential. By optimal locating and sizing of reactive power support resources causes a power loss reduction, improvement in voltage profile and maximizes techno-economic benefits to consumers and system operators while improving overall system performance and reliability.

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Investigating the Impact of Feature Reduction Through Information Gain and Correlation on the Performance of Error Back Propagation Based IDS

Research in the field of IDS has been going on since long time; however, there exists a number of ways to further improve the efficiency of IDS. This paper investigates the performance of Intrusion detection system using feature reduction and EBPA. The first step involves the reduction in number of features, based on the combination of information gain and correlation. In the next step, error back propagation algorithm (EBPA) is used to train the network and then analyze the performance. EBPA is commonly used due to its ease of use, high accuracy and efficiency. The proposed model is tested over the KDD Cup 99 and NSL-KDD datasets. Results show that the proposed IDS model with reduced feature set outperforms the other models, both in terms of performance metrics and processing time.

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A Study of Detection of Drowsiness and Awakeness using Non-contact Radar Sensors

Biometric information is used in a variety of industrial fields. Heart rate and respiration rate, in particular, are widely applied not only in medical institutions but also in life safety. However, a sensor must be worn or directly attached to the human body to obtain a bio signal, which is inconvenient and limits its application. In this study, a 24 GHz radar sensor module is developed, and an algorithm is implemented by analyzing the frequency and peak values of a human participant’s heartbeat and respiration signals in an unconstrained state. In the experiment, the existing ECG equipment (MP150) and radar sensor module are compared. The results indicate that the average value of MP150 is higher than that of the Doppler sensor in terms of all parameters; however, the deviation of the Doppler sensor is small, and the bias is low. Furthermore, it is confirmed that the HRV decreases in the drowsy state compared to that in the wakeful state in both devices. These results confirm that bio-signals change during drowsiness, and conversely, drowsiness can be detected through changes in bio-signals, which is a significant finding.

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An Improved Particle Swarm Optimization for Prediction of Accident Severity

In this work, an attempt is made to improve the accuracy of accident severity. To achieve the same, a particle swarm optimization-based algorithm is applied for evaluating the accident severity. Prior to implement the PSO, two modification are incorporated into PSO algorithm, called improved PSO. These modifications can be described as mutation operator and trail candidate generation. The performance of improved PSO is examined over accident traffic severity dataset and results are evaluated using accuracy, recall@5 and precision@5 metrics. Several existing techniques are considered for comparing the results of IPSO algorithm. It is revealed that IPSO achieves more accurate results among all techniques.

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Secure and Reliable Data sharing scheme using Attribute-based Encryption with weighted attribute-based Encryption in Cloud Environment

In this research a secured data access control is proposed using the Advanced Encryption Standard (AES) combined with a weighted attribute-based Encryption (AES-WABE). To encrypt the data, the access control policies are used and weight is assigned according to its significance of each attribute. The outsourced data is stored by the cloud service provider and the attribute authority based on the weight that updates the attributes. To minimize the computational overload the data file is accessed by the receiver corresponding to its weight. The proposed procedure provides resistance for collusion, multiple user security with control of fine-grained access based on protection, reliability and efficiency. On concerning the data collaboration and confidentiality, the performance rating is done related with the Cipher-text Policy–Attribute-based Encryption (CP-ABE) and the hybrid attribute-based encryption (HABE) scheme, access control flexibility, limited decryption, full delegation, verification and partial signing.

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A Review on the Feasibility of Deployment of Renewable Energy Sources for Electric Vehicles under Smart Grid Environment

This paper presents a summary of recent research in the domain of integration of renewable energy sources with electric vehicles (EVs) under the smart grid environment. Electric vehicles-smart grid integrated systems face several issues related to communication, grid infrastructure and control in the future power system. Feasibility of integration of solar and wind energy systems with electric vehicles is discussed in section 2. The existing research articles in this area are classified into two based on the purpose: EVs integration into the electric grid and Vehicle to grid services. The function of V2G in the electricity market, as well as its management concerns, are investigated in section 3. Finally, the research gaps and future scope of incorporating electric vehicles with renewable energy sources and the Smart grid are highlighted.

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Implementation of GF-HOG Technique for Effective Commercial and Industrial Load Clustering and Classification for Better Demand Response

With increased penetration of renewables since last decade has evolved measures from the regulator for robust distribution network mostly catering to residential load. With increasing future demand of commercial and industrial load (CIL) due to aspiring GDP growth and insistence of popular governments to encourage renewable use, large chunk of the CIL will be served by renewables. So increasing the robustness alone on the renewable supply side will be in vain unless effective Demand response with rationalized tariff system for CIL which is more profitable energy market than subsidized residential tariff in India .

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Performance Analysis of Permanent Magnet Synchronous Machine due to Winding Failures

The paper describes winding failures in Permanent Magnet Synchronous Motor (PMSM) which are preferred in Electric Vehicles. Drive can be designed with fault tolerance to continue to operate under occurrence of faults. Winding insulation failure is responsible for some of the most serious faults. A method for detecting open circuit of winding, short circuit of winding or turn to turn short circuit in winding may result as a failure of winding insulation is presented. Further a technique for continued post-fault operation of the drive is discussed based upon mathematical model. The detection method operates in real time without the use of additional sensors and is sensitive enough to detect the presence of an air-gap between turns.

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Solar Water Pumping Model Using Zeta Converter for Irrigation Application

A solar pumping model is proposed in this paper using a Brushless DC (BLDC) motor. Zeta converter is used as a DC-DC link between the voltage source inverter and the PV array. Zeta converter enables soft starting of the BLDC motor and the speed control is achieved by simple variation of DC link voltage, thereby eliminating the need for complex switching circuitry. Zeta converter belongs to the class of buck-boost converter hence offers a wide range of operating voltage. The proposed model is simple and cost-effective so it can be practically implemented with minimum cost. The proposed model is tested for its suitability in the MATLAB/Simulink environment.

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Fuzzy and ANFIS Controllers to Improve the Power Quality of Grid Connected PV System with Cascaded Multilevel Inverter

In this paper, A Cascaded Multi level Inverter (CMLI) interconnected with the 10 KW PV System, Boost Converter along with Cascaded Feed Forwarded Neural Network (CFFNN) MPPT Controller is proposed to improve the Power Quality (PQ) for Linear, Non-linear and unbalanced loading conditions and minimize the total Harmonic Distortion (THD). The CMLI Consists of Novel type 9-Level Inverter with Reduced number of switches, and is connected to Bridged type inverter as cascaded, to get the required amount of Output voltage which can be used for grid integration.

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Development of DSTATCOM Optimal Sizing and Location Technique Based on IA-GA for Power Loss Reduction and Voltage Profile Enhancement in an RDN

In this paper, an innovative technique based on hybridized Immune and Genetic Algorithm (IA-GA) for optimal DSTATCOM placement and sizing for three distinct load levels is proposed. Simulation and analysis of the proposed algorithm were carried out using IEEE-33 bus radial distribution network (RDN) in MATLAB. The simulation results demonstrate a substantial decrease in power loss and a significant improvement in the voltage profile. Evaluation of the proposed method against existing techniques reveals that the proposed technique outperforms IA and PSO in terms of decreasing power loss and enhancement of voltage profiles. A cost-benefit analysis was performed, and it was discovered that the proposed technique yields improved annual cost savings.

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REULEAUX Triangle Shaped MSPA for 5G and WLAN Applications

This research work proposes a low-key Reuleaux Triangle Shaped antenna having a square, rectangular Patch attached through the feedline. This antenna has Reuleaux Triangle as a patch element with a bottom having square-shaped geometry to attain ultra-wideband characteristics. This compact wideband antenna for WLAN, 5G and WiMAX applications has been presented in this manuscript.

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Electrical Load Forecasting using ARIMA, Prophet and LSTM Networks

Forecasting electrical load plays a vital role in power system planning. However, it is quite difficult to forecast electrical load, as the load on the system varies continuously concerning time and seasons. In this paper, we are proposing an advanced artificial neural network model to forecast short-term electrical load. The proposed method tested on historical data collected from Karnataka power corporation, India, and test results compared with other data-driven models viz. ARIMA, RNN, LSTM, and Prophet. The accuracy and RMSE values were calculated and observed that the proposed model was superior in a day and weekly ahead electrical load forecasting.

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Smart Heart Disease Detection using Particle Swarm Optimization and Support Vector Machine

Healthcare and disease detection in early stage is important in every human being. Proper and optimum detection of disease with smart controller is done using Particle swarm optimization (PSO) and Support Vector Machine (SVM). The research includes the Fuzzy Proportional Integral and Derivative (Fuzzy PID) controller was used with support vector machine to classify the heart disease. Particle Swarm Optimization is designed to remove the noise introduced in Electrocardiogram signal. Fuzzy PID controller was implemented for disease detection and prediction. Fuzzy PID controller provides most accurate and stable results.

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An Integrated Fundus Image Segmentation Algorithm for Multiple Eye Ailments

The detection of eye illnesses requires a thorough inspection of all of the eye's structures. Most significantly, the presence of blood vessels, an optical disc, and any other unwelcome objects, if any are discovered, is critical in determining the type of eye disease present. Specifically, the goal of this research is to establish a thorough segmentation framework that will aid in the detection of anatomical anomalies in the eye. A novel segmentation technique for analyzing blood vessels, optical disc health, and the presence of exudates has been added into the software.

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Modelling of Electric Vehicle with PID Controller Transfer Function using GA and Model-Reduced Order DRA Algorithm

In this paper, a model of an electric vehicle transfer function using GA and a model-reduced order discrete time realization (DRA) algorithm is presented. The electric vehicle (EV) control system regulates vehicle speed according to the driver’s command signal and brings the vehicle to its equilibrium point, i.e., the desired speed under any abnormal conditions. The controller transfer function is designed based on EV's dynamic differential equations. An infinite-order transcendental transfer function for the EV model is approximated to find high-reliability discrete-time state-space reduced-order models (ROMs).

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Contrast Enhancement of Colour Images by Optimized Fuzzy Intensification

Contrast enhancement is a critical and difficult issue because inappropriate enhancement by existing global image enhancement techniques might result in over or under enhancement. Varying areas of the image that are lighted indicate different shades and contrast in the output images. Projected technique uses local colour correction in the Hue Saturation Luminance (HSL) colour space. To control colour fidelity in initial phase an optimized fuzzy intensification parameters are extracted automatically form fuzzy inference system for that particular image.

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