24 results match your criteria: "Lakireddy Bali Reddy College of Engineering[Affiliation]"

In robotic arm controllers, the ability to shift signal levels is crucial for interfacing between different voltage domains in a processor. The level shifter (LS) has been used to convert signals operating near threshold voltage to signals operating well above the threshold voltage. Researchers have developed current mirror-based LSs to employ current mirrors, which duplicate the current from one transistor and accurately replicate it in another, ensuring precise current matching.

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This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. The incorporation of nanotechnology, through the addition of nanoparticles to conventional fuels, improves fuel atomization, combustion efficiency, and emission control. Simultaneously, LSTM models are employed to analyze and predict the complex spray behavior under diverse operational and geometric conditions.

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Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.

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Article Synopsis
  • Alzheimer's disease leads to the loss of memory-related brain cells and poses challenges for diagnosis due to complex brain processes and similarities in brain image data.
  • To address these challenges, hybrid feature extraction techniques like Gray Level Run Length Matrix (GLRLM), Gabor wavelet transform, and Local Energy-based Shape Histogram (LESH) are utilized to analyze enhanced brain MRI images.
  • The proposed model uses an optimized feature selection method called SEAGULL and a modified Deep Neural Network (DNN) to predict Alzheimer's disease, achieving high performance metrics of 91% precision, 98% accuracy, and 97% recall.
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This research presents an integrated framework designed to automate the classification of pulmonary chest x-ray images. Leveraging convolutional neural networks (CNNs) with a focus on transformer architectures, the aim is to improve both the accuracy and efficiency of pulmonary chest x-ray image analysis. A central aspect of this approach involves utilizing pre-trained networks such as VGG16, ResNet50, and MobileNetV2 to create a feature ensemble.

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Underwater cameras are crucial in marine ecology, but their data management needs automatic species identification. This study proposes a two-stage deep learning approach. First, the Unsharp Mask Filter (UMF) preprocesses images.

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Development of Wearable Textile MIMO Antenna for Sub-6 GHz Band New Radio 5G Applications.

Micromachines (Basel)

May 2024

Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia.

In this paper, an irregular octagonal two-port MIMO patch antenna is designed specifically for New Radio (NR) 5G applications in the mid-band sub-6 GHz. The proposed antenna comprises an irregularly shaped patch antenna equipped with a regular 50-ohm feed line and a parasitic strip line antenna, and is partially grounded. Jeans material serves as a substrate with an effective dielectric constant of 1.

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Efficiency and mechanistic insights of photocatalytic decomposition of tetracycline and rhodamine B utilizing Z-scheme g-CN/SnWO heterostructures under visible light irradiation.

Environ Res

August 2024

Department of Physics, Andhra University, Visakhapatnam, 530 003, Andhra Pradesh, India; Department of Physics, Visakha Govt. Degree College (W), Visakhapatnam, 530 020, Andhra Pradesh, India. Electronic address:

The hydrothermal approach was used in the design and construction of the SnWO (SW) nanoplates anchored g-CN (gCN) nanosheet heterostructures. Morphology, optical characteristics, and phase identification were investigated. The heterostructure architect construction and successful interface interaction were validated by the physicochemical characteristics.

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Background: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid radiologists in detecting and quantifying COVID-19-related lung infections.

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Driving errors as a function of listening to music and FM radio: A simulator study.

Traffic Inj Prev

December 2023

Cognitive Science Research Centre, Department of Mechanical Engineering, Lakireddy Bali Reddy College of Engineering, Krishna District, Andhra Pradesh, India.

Objectives: Driving is a dynamic activity that takes place in a constantly changing environment, carrying safety implications not only for the driver but also for other road users. Despite the potentially life-threatening consequences of incorrect driving behavior, drivers often engage in activities unrelated to driving. This study aims to investigate the frequency and types of errors committed by drivers when they are distracted compared to when they are not distracted.

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Recently, the infectious disease COVID-19 remains to have a catastrophic effect on the lives of human beings all over the world. To combat this deadliest disease, it is essential to screen the affected people quickly and least inexpensively. Radiological examination is considered the most feasible step toward attaining this objective; however, chest X-ray (CXR) and computed tomography (CT) are the most easily accessible and inexpensive options.

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Is It Feasible to Reduce Academic Stress in Net-Zero Energy Buildings? Reaction from ChatGPT.

Ann Biomed Eng

December 2023

Department of Electrical and Electronics Engineering, School of Engineering, Presidency University, Bangalore, Karnataka, 560064, India.

We may lessen the detrimental effects of global warming on human thought processes by reducing greenhouse gas emissions, encouraging sustainability, and giving adaption measures top priority. The purpose of the letter is to draw attention to the necessity of net-zero energy buildings (NZEB) in academic institutions in order to reduce academic stress, promote well-being, and improve cognitive functions. While some levels of stress might be advantageous, excessive and mismanaged stress can be detrimental to students' well-being.

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This study mainly focuses on pre-processing the HAM10000 and BCN20000 skin lesion datasets to select important features that will drive for proper skin cancer classification. In this work, three feature fusion strategies have been proposed by utilizing three pre-trained Convolutional Neural Network (CNN) models, namely VGG16, EfficientNet B0, and ResNet50 to select the important features based on the weights of the features and are coined as Adaptive Weighted Feature Set (AWFS). Then, two other strategies, Model-based Optimized Weighted Feature Set (MOWFS) and Feature-based Optimized Weighted Feature Set (FOWFS), are proposed by optimally and adaptively choosing the weights using a meta-heuristic artificial jellyfish (AJS) algorithm.

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The Internet of Things, sometimes known as IoT, is a relatively new kind of Internet connectivity that connects physical objects to the Internet in a way that was not possible in the past. The Internet of Things is another name for this concept (IoT). The Internet of Things has a larger attack surface as a result of its hyperconnectivity and heterogeneity, both of which are characteristics of the IoT.

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Improved tunicate swarm search-based MPPT for photovoltaic on a "grid-connected" inverter system.

Environ Sci Pollut Res Int

November 2022

Department of Electrical and Electronics Engineering, Lakireddy Bali Reddy College of Engineering (Autonomous), Mylavaram, Krishna Dt, Andhra Pradesh, 521230, India.

Photovoltaic (PV) systems are broadly utilized, especially for remote electrification. It is easier for installation and is free of greenhouse gases, so the impacts on the environment are reduced. The temperature and irradiance change during the day, and the circumstances are more dynamic on cloudy days.

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The discipline of computer vision is becoming more popular as a research subject. In a surveillance-based computer vision application, item identification and tracking are the core procedures. They consist of segmenting and tracking an object of interest from a sequence of video frames, and they are both performed using computer vision algorithms.

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Influence of Ultra-Thin Ge₃N₄ Passivation Layer on Structural, Interfacial, and Electrical Properties of HfO₂/Ge Metal-Oxide-Semiconductor Devices.

J Nanosci Nanotechnol

February 2020

Information and Communication Device Laboratory, School of Information and Communication Engineering, Sungkyunkwan University, 2066, Seobu-ro, jangan-gu, suwon-si, gyeong gi-Do, 16419, Republic of Korea.

We report the effects of the nitride passivation layer on the structural, electrical, and interfacial properties of Ge metal-oxide-semiconductor (MOS) devices with a hafnium oxide (HfO₂) gate dielectric layer deposited on -type 〈100〉 Ge substrates. X-ray photoelectron spectroscopy analysis confirmed the chemical states and formation of HfO₂/Ge₃N₄ on Ge. The interfacial quality and thickness of the layers grown on Ge were confirmed by high-resolution transmission electron microscopy.

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This work examines the feasibility of fuelling biodiesel derived from Eichhornia crassipes in a compression ignition engine. This work also proposes water hyacinth biodiesel (WHB) as a potential alternative energy source since the above species is available extensively in freshwater, marine, and aquatic ecosystems throughout the world. WHB was blended with petroleum diesel fuel at various volume proportions of 10%, 20%, 30%, 40%, and 100% and their properties were analyzed as per ASTM standards for its application as biofuel.

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Stringent emission regulations and depletion of crude oil are driving researchers toward alternative fuels. In this context, palm oil emerges as a good competitor as it is highly economical compared to other alternative fuels. The current research work centers around the impact of palm oil methyl ester on performance, combustion, and emission characteristics at varying injection timings and exhaust gas recirculation rates.

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In the process of creating eco-friendly environment and conserving fossil fuels for the future generations, biodiesel has been chosen as a good substitute for diesel. It is a proven fact that biodiesel operated diesel engine can deliver comparable results with diesel. The present work focuses on TSME20 (tamarind seed methyl ester 20% + diesel 80%) as a renewable fuel, and its performance and emission results are analyzed at different exhaust gas recirculation rates and various injection pressures.

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Rare earth ion Dy-doped tellurite glasses were synthesised in the system of (75-x)TeO-15SbO-10WO-xDyO (TSWD glasses). XRD and FTIR characterizations were used to find the crystalline and structural properties. The intensities of the electronic transitions and the ligand environment around the Dy ion were determined using the Judd-Ofelt (J-O) theory on the absorption spectra of the glasses.

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Performing accurate and fully automated lung segmentation of high-resolution computed tomography (HRCT) images affected by dense abnormalities is a challenging problem. This paper presents a novel algorithm for automated segmentation of lungs based on modified convex hull algorithm and mathematical morphology techniques. Sixty randomly selected lung HRCT scans with different abnormalities are used to test the proposed algorithm, and experimental results show that the proposed approach can accurately segment the lungs even in the presence of disease patterns, with some limitations in the apices and bases of lungs.

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Millions of people worldwide are affected by motor vehicle accidents each year, with driver distractions identified as their foremost cause. This paper examines the influence of distraction types on driver response time as well as on neural activity in the brain. Ten subjects participated in this computer based simulation study, with three distraction conditions (Cognitive distraction, Visual distraction and Audio distraction) and a No distraction condition that served as the baseline for comparison.

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A need exists to develop a better predictive tool for estimating deterioration in the visual system. This pilot study examined changes in EEG spectral power of subjects with varying visual impairments. EEG activity of five subjects was recorded while playing a driving game both with and without their corrective glasses.

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