IJEER Vol no. 11, Issue 3


A Comparative Study of the CNN Based Models Used for Remote Sensing Image Classification

Remotely sensed images, their classification and accuracy play a vital role in measuring a country’s scientific growth and technological development. Remote Sensing (RS) can be interpreted as a way of assessing the characteristics of a surface or an entity from a distance. This task of identifying and classifying datasets of RS images can be done using Convolutional Neural Network (CNN). For classifying images of large-scale areas, the traditional CNN approach produces coarse maps. For addressing this issue, Object based CNN method can be used. Classifying images with high spatial resolution can be done effectively using Object based image analysis.

Read more

A New Closed Loop Constant v/f Control of Induction Motor with Torque Control Based on DPWM

An easy sensor-less scalar control algorithm is described in this article as a method for controlling the speed of an induction motor. For developing a closed-loop v/f control of the induction motor drive, a torque controller with PI is implemented. The torque command was estimated by utilizing the voltage command, the feedback current, and a torque estimator. Additionally, a torque reference was provided for the Torque PI controller. Considering this, the purpose of this work is to investigate the closed-loop PI-based torque control of an induction motor drive that applies DPWM.

Read more

Second Harmonic Frequency Adjustment Strategy for Class-E Amplifier Design

The ultrasonic transducers have numerous applications in industries, including medical probes for performing ultrasound scans. One of the significant drawbacks of the ultrasonic transducer is the wastage of a large portion of energy, due to high acoustic impedance, while transmitting ultrasonic waves to the target object. The present study is aimed to investigate the material design of the piezo-composite transducer and improve its performance.

Read more

Islanding Detection in Distribution Generation using Active Method

There are two techniques to ensure that renewable energy systems run continuously: on-grid and off-grid. In the first case the system can be managed in a network, in the second case it can be managed in a micro grid or island mode. Islanding means when a distributed generator (DG) keeps running even after there is no longer any external electricity.

Read more

Implementation of Turbo Trellis Coding Modulation Scheme for Fading Channel

In the context of data communication, encountering fading channels can lead to errors occurring at the receiving end due to multipath propagation. To address this challenge, researchers have persistently worked towards developing Error Correction Schemes that effectively manage these errors and guarantee error-free data reception for the receiver.

Read more

Image segmentation in Diagnosing the Ground Bud Necrosis Virus in Tomatoes using K-Means Clustering

Early-stage fruit disease detection will ensure the natural product quality for the organic agriculture business. The potential of using K-Means segmentation for diagnosing tomatoes fruit disease was intended to be explored by this proposed method. The main goal of paper is to increase classification accuracy by locating tomatoes with Ground Bud Necrosis Virus in Tomatoes disease using an image segmentation approach.

Read more

An Efficient Hybrid Analysis to Improve Data Rate Signal Transmission in Cognitive Radio Networks Using Multi- Hop

Spectrum scarcity problems can be resolved with the emerging communiqué technologies known as cognitive radio (CR). Cognitive radio networks (CRNs) will give mobile users greater bandwidth via wirelessly heterogeneity design and dynamic spectrum acquisition methods. The Cognitive Radio Mobile Ad-Hoc Network (CR-MANET) idea of Adaptive Routing a new network paradigm may be realized by using the functions of spectrum management to overcome such difficulties.

Read more

Design and Implementation of a Bootstrap-based Sample and Hold Circuit for SAR ADC Applications

The resolution and conversion speed of an Analog to Digital converter (ADCs) strongly depends on how efficiently Sampling and Hold (S&H) circuit handles the amplitude skewing of the input analog signal. In this article, a novel S&H circuit has been proposed to handle the errors produced because of amplitude skewing. This circuit has two different paths for sampling and holds process and avoids the non-ideal effects seen in most of the recent literature.

Read more

A Solution to VLSI: Digital Circuits Design in Quantum Dot Cellular Automata Technology

Quantum Dot Cellular Automata is a Nano device efficient than other devices in nanotechnology for the last two decades. It is beneficial over Complementary Metal Oxide Semiconductor technology like high speed, low energy dissipation, high device density and high computation efficiency. To achieve further optimization different methods like simplifications in Boolean expressions, tile method, clocking scheme, cell placement, cell arrangement, novel input techniques, etc.

Read more

A New Soft Computing Fuzzy Logic Frequency Regulation Scheme for Two Area Hybrid Power Systems

Modern renewable energy power system designs provide significant application benefits, but they also produce losses. The total generation, total load demand, and system losses must be balanced in order for this structured power system to operate reliably. The actual and reactive power balances are disturbed as a result of changes in load demand. System frequency and tie line interchange power deviate from their planned values as a result of this. A high system frequency deviation can cause the system to crash.

Read more

Optimal Power Flow for Distribution System using Gradient-Based Optimizer

In the distribution network, DG penetration increases prominently, and has altered the nature of the distribution network into an active and passive network. DISCOMs/DSOs are incorporating all kinds of DGs, including non-renewables and renewables now a day. If DGs are planned and controlled adequately, then it improves voltage deviation, reduces active power loss, and leads to the economic operation of the active distribution network.

Read more

A Combination of Appropriate Placement and size of Multiple FACTS Controllers to reduce Voltage Sag and Swell

Today's power system is going through a power quality crisis as a result of rising power demand and an increase in industrial facilities. The forms must be pure sinusoidal and harmonic-free, and the power source must always be reachable within voltage and frequency restrictions. This study uses numerous FACTS controllers in a radial distribution system to handle power quality concerns. Placement of FACTs controllers in the distribution system under various load conditions presents the biggest challenge. The system is run while deploying single and multiple FACTS controllers at the critical buses in order to avoid conflicts. This paper presents on the installation of a DSTATCOM, Integrated Dynamic Voltage Restorer-Ultra Capacitor (IDVR-UC), and UPQC to reduce power quality issues for conventional IEEE-33 bus distribution systems.

Read more

Smart Energy Meets Smart Security: A Comprehensive Review of AI Applications in Cybersecurity for Renewable Energy Systems

The rapid adoption of renewable energy systems has brought forth a new set of cybersecurity challenges that require innovative solutions. In this context, artificial intelligence (AI) has emerged as a promising approach to tackle these challenges. This paper provides a comprehensive review of more than 19 studies that investigate the applications of AI in cybersecurity for renewable energy systems. By analyzing these studies, a range of opportunities and challenges associated with the integration of AI in this domain are identified.

Read more

VLSI Implementation of Hybrid Memristor Based Logic Gates

Practical memristors have gained attention from researchers and scientists due to their potential use in a variety of electronic circuits and devices. In our paper, a hybrid Memristor-CMOS (MeMOS) logic circuit was designed and its transient response was analyzed. This circuit, which uses a N-type metal oxide semiconductor (NMOS), and P-type metal oxide semiconductor (PMOS) transistors, Operational amplifiers (OPAMPs), resistors, capacitors and multipliers replicate memristor characteristics.

Read more

Optimization of Microstructure Patterning for Flexible Bioelectronics Application

Recent advancements in flexible electronics and wearable sensors have given biomedical technology a new edge overcoming the limitations of traditional rigid silicon-based electronics. Furthermore, high flexibility of these wearable sensors enables it to conformally sit over any uneven surface helping in accurate determination of any physical, chemical, or physiological parameter associate with the surface. Conventionally expensive micro/nano photolithography techniques under strict clean room conditions are used for the development of these flexible and wearable biomedical sensors with high degree of accuracy and sensitivity.

Read more

Demonstration of an Intelligent and Efficient Smart Monitoring System for Train Track By using Arduino

In Indian railway, the smart monitoring system for the train also train track is a significant aspect to prevent accidents. Indian railway system is underdeveloped in terms of smart monitoring of the train when compared with the other developed countries. Using the smart monitoring system for train, the deterioration of the railway track could be identified and secondly, accident between two trains could be prevented, thirdly any obstacle present in railway track, could be find and removed, two coaches of the train getting disconnected during the movement of the train due to manufacturing mistakes could also be detected.

Read more

Disease Detection and Diagnosis of Agricultural Plant Leaf Using Machine Learning

Agriculture and allied activities still continue to be one of the major occupations in world. Various modern methods and inventions have been incorporated to make it more efficient and successful. One of the main problems the farmers are facing are plant diseases. This can affect the entire yield of a season, so to tackle that problem we are proposing a ResNet based Convolutional neural network model which can detect the various disease in plants in early stage itself.

Read more

Designing of Tunnel FET and FinFET using Sentaurus TCAD and Finding their Characteristics

In this paper, a FinFET and Tunnel FET (TFET) are designed and implemented using Sentaurus TCAD. Due to numerous advantages, the TFET and FinFET have been proposed as a possible alternative to the conventional metal oxide semiconductor FET (MOSFET). A phenomenal performance-has been achieved using FinFET technology up to a 7 nm feature size.

Read more

Hand Gesture Recognition System based on 60 GHz FMCW Radar and Deep Neural Network

The proposed study provides a novel technique for recognizing hand gestures that use a combination of Deep Convolutional Neural Networks (DCNN) and 60 GHz Frequency Modulated Continuous Wave (FMCW) radar. The motion of a Human's hand is detected using the FMCW radar, and the various gestures are classified using the DCNN. Motion detection and frequency analysis are two techniques that the suggested system combines.

Read more

Power Optimized VLSI Architecture of Distributed Arithmetic Based Block LMS Adaptive Filter

In this paper, we are presenting a power-efficient Distributed Arithmetic (DA) based Block Least Mean Square (BLMS) Adaptive Digital Filter (ADF). The proposed DA BLMS architecture proposes a shared area-efficient Multiplier Accumulate Block that calculates both the partial filter products and the weight increment terms in the same module. It also uses Multiplexers (MUX) and Demultiplexers (DEMUX) which passes only L out of N inputs, where N and L are the filter length and chosen block size respectively, into the MAC thus helping in achieving the DA functionality along with reduced power consumption.

Read more

A Machine Learning Approach for Detection and Suppression of Shadow or Wet Road Surfaces

In advanced driver assistance system detection of road surfaces is an important task. Few algorithms have been proposed in past to detect the road surfaces based on intensities. However, problem arises in detection process is due to the presence of shadows or wet road surfaces. Here we have proposed a novel algorithm for detection of shadows with the help of machine learning approaches. Initially shadow is being detected with the help of a threshold-based approach followed by windowing-based method.

Read more

A Machine Learning Approach for Detection and Suppression of Shadow or Wet Road Surfaces

Electrical demand, which makes up a large share of the overall power market, agriculture at the top of the list of priorities. To provide end users with a dependable and high-quality supply via various feeders and renewable energy sources, distribution generations are now being developed. In recent years, solar PV systems have been used to meet the demands of numerous applications, including boosting the efficiency of distribution networks.

Read more

Addressing Power Loss and Voltage Profile Issues in Electrical Distribution Systems: A Novel Approach Using Polar Bear Gradient-Based Optimization

Energy is an essential commodity for everyone, with electrical energy being the most preferred form. Unfortunately, non-renewable energy resources are gradually depleting, and renewable energy sources take several years to establish. To mitigate this problem, technology has shifted from non-renewable energy sources to electrical devices and machines, including household appliances like washing machines and air conditioners.

Read more

An Adaptive Grid Search Based Efficient Ensemble Model for Covid-19 Classification in Chest X-Ray Scans

Covid has resulted in millions of deaths worldwide, making it crucial to develop fast and safe diagnostic methods to control its spread. Chest X-Ray imaging can diagnose pulmonary diseases, including Covid. Most research studies have developed single convolution neural network models ignoring the advantage of combining different models.

Read more

Comprehensive Analysis of IoT with Artificial Intelligence to Predictive Maintenance Optimization for Indian Shipbuilding

The extensive review of the literature evaluation on predictive maintenance (PdM) in this work focuses on system designs, goals, and methodologies. In the business world, any equipment or system failures or unscheduled downtime would negatively affect or stop an organization's key operations, possibly incurring heavy fines and irreparable reputational damage.

Read more

Deep Learning Method of Predicting MANET Lifetime Using Graph Adversarial Network Routing

The prominence of mobile ad-hoc networks (MANETs) is on the rise. Within the domain of machine learning, a specialized subset known as deep learning (DL) employs diverse methodologies, each providing unique interpretations of the data it processes.

Read more

Modified E-Shape Rectangular Microstrip Patch Antenna with DGS for Wireless Communication

A modified E-shape dual bands rectangular microstrip patch antenna for wireless applications is presented in this paper. An E-slot Microstrip patch antenna with a defective ground structure method has been proposed and getting two bands at 1.9 GHz and 2.89 GHz with S11-10dB.

Read more

A Novel Black Widow Optimized Controller Approach for Automatic Generation Control in Modern Hybrid Power Systems

This research paper demonstrates an application of the Black Widow Optimization (BWO) approach to address the issue of load-frequency control (LFC) in networked power systems. BWO is an innovative metaheuristic method that quickly suggests technique is initially evaluated on a non-reheat thermal-thermal (NRTT) power system spanning two areas of interconnection, and then it is applied to two different actual power systems:

Read more

Feature Fusion of Time-frequency and Deep Learning Features for Epileptic Seizure Detection using EEG Signals

A persistent brain's neurological state is epilepsy, characterised by recurring seizure. Brain electrical activity is measured using EEG signals, which can be used to detect and diagnose significant brain problems such as Epilepsy, Autism, Alzheimer’s etc. However, manual EEG data processing is time-consuming, requires highly skilled clinicians, and is associated with low inter-rater reliability (IRA).

Read more

Estimation of Common Mode noise and Differential Mode noise generated by DC-DC Power Converters

The study contains a review of the body of knowledge regarding differential mode (DM) and common mode (CM)noise and how they affect power converter performance. With an emphasis on practical application, this work seeks to give an estimation of differential mode (DM) and common mode (CM) noise for cutting-edge DC-DC power converters such as Zeta converters, Single Ended Primary Inductance Converters (SEPIC), and Cuk converters.

Read more

Advancements in Machine Learning-Based Face Mask Detection: A Review of Methods and Challenges

Wearing face masks is crucial in various environments, particularly where there is high potential of viral transmission. Proper wearing of face masks always is important in hospitals and healthcare facilities where the risk of transmission of different contagious diseases is very high. The COVID-19 pandemic has been recognized as a global health crisis, exerting deep impacts on various sectors such as industry, economy, public transportation, education, and residential domains. This rapidly spreading virus has created considerable public health risks, resulting in serious health consequences and fatalities.

Read more

Performance Enhancement of CNFET-based Approximate Compressor for Error Resilient Image Processing

The approximate computing has emerged as an appealing approach to minimize energy consumption. By implementing inexact circuits at the transistor level, significant enhancements in various performance metrics such as power consumption, delay, energy, and area can be achieved. Consequently, researchers worldwide have been actively exploring the application of inexact techniques in circuit design. This paper introduces a novel technique for designing low-power digital circuits called extremely low power modified gate diffusion input (ELP-MGDI).

Read more

Robust medical image watermarking in frequency domain

Protecting patient information in medical image watermarking poses a significant challenge, especially when traditional methods like the Arnold transform prove inadequate in ensuring security. This paper introduces a novel approach within the Discrete Wavelet Transform (DWT) domain to address this issue effectively. By employing the Advanced Encryption Standard (AES), the security and robustness of the system are greatly enhanced through the encryption of both the medical image and patient data.

Read more

A Novel Buffer Packet Delivery Strategy for High Throughput and Better Health (HTBH) Method in Wireless Sensor Networks

There is massive call for the Packet Sender Device Network (PSDN) primarily based on tracking of areas, figuring out the consequences of climate, detection of enemy vehicles. The PSDN could have useful Packet Sender Devices (PSD’s) which can study the vicinity and then send the data from initial to receiver PSD. There are numerous constraints which have restrictions on the feature like battery, memory, and range. There is hierarchical community wherein the PSDs are spread on more than one area with every vicinity having their very own PSD’s whilst communique has to manifest among PSDs of various areas then it requires chief PSD in every vicinity which have to be elected primarily based on higher battery degree, distance to base station in addition to mobility of the PSD over a duration of time.

Read more