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588 articles for “Extract”
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Fabrication, Numerical Simulation and Compact Modeling of Ph-BTBT-C10 Organic Thin Film Transistor
Abstract: Flexible and cost-effective electronics have been necessitated by the advent of organic thin-film transistors (OTFTs). This study aims to study the performance of OTFT using a 2-decyl-7-phenyl-[1]benzothieno[3,2-b][1]benzothiophene (Ph-BTBT-C10) organic semiconductor. The paper also explore accurate device modeling for technology optimization and circuit design that supports device improvement. This research includes device fabrication, numerical simulation using TCAD, compact modeling, and parameter extraction. By combining temperature-dependent bandgap narrowing with existing theories, this …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 1–18 Read article
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Bioinformatics-based Preparation and Characterization of Silver Nanoparticles Synthesized from Pterocarpus marsupium
Abstract: Silver nanoparticles were synthesized using Pterocarpus marsupium bark extract in combination with silver nitrate solution through a green synthesis method. Silver nanoparticles formation was confirmed by the formation of dark brown from solution of silver nitrate, where the reduction of silver ion occurs which leads to the formation of silver nanoparticles. The UV–visible spectra showed a peak at 429 nm, confirming the reduction of silver ions and the subsequent synthesis …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 2, 2024 · pp. 21–34 Read article
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Comprehensive Analysis of MRSA Peptides Via Maldi
Abstract: The present study employed Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry to analyze methicillin-resistant Staphylococcus aureus peptides, focusing on various parameters associated with mass-to-charge (m/z) values. Through systematic data collection and analysis, including time, intensity, signal-to-noise ratios, quality factors, resolutions, areas under the peaks, relative intensities, full widths at half maximum, Chi-squared values, and background peaks, comprehensive insights into the spectral characteristics of methicillin-resistant Staphylococcus aureus peptides were obtained. Methicillin-resistant Staphylococcus …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 98–101 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Innovative Eyewear for the Visually Impaired
Abstract: Object detection systems are essential tools for identifying and locating objects within images or videos. When integrated into spectacles or wearable devices, these systems provide users with real-time information about objects present in their surroundings. This functionality serves diverse purposes, such as assisting visually impaired individuals in navigating their environment or offering augmented reality data to workers during tasks. Region-based Convolutional Neural Networks (RCNN) represent a prominent machine learning model …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Advancements in Handwriting Recognition: A Deep Learning Approach
Abstract: This article provides detailed information about handwriting text recognition. Some human characteristics are unique to the individual. Writing is one of the scientifically proven habits that is different for everyone. Handwriting Text Recognition (HTR) is responsible for identifying written characters and converting them into digital text. HTR is an intensively researched area, but improvements can still be made in accuracy and efficiency. Digitization of manuscripts is very useful in today's …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Eco-Friendly Elixirs: A Critical Review of Biosurfactants for Sustainable Wastewater Solutions
Abstract: Biosurfactants are the amphiphilic substances which are acquired from the remains of the living microorganisms and have attracted a lot of scientific interests because of their applicability in various fields. This review aims at reviewing current research and development on biosurfactants with special emphasis on their application in wastewater and oil. Biosurfactants being less hazardous to the environment are produced by microorganisms and works as a substitute for chemically produced …
Published in Emerging Trends in Chemical Engineering · Vol. 11, Issue 2, 2024 · pp. 14–33 Read article
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OpenCV, AI, and Haar Cascade File: A Review
Abstract: Real-time image processing applications using OpenCV encompass a diverse and crucial array of tasks in modern technology. OpenCV's robust capabilities enable the implementation of object detection and tracking, which are vital for surveillance systems to monitor and analyze activities in real time. In the realm of security, face recognition technology, powered by OpenCV, provides accurate and efficient identification and authentication, enhancing safety measures. Gesture recognition, another significant application, facilitates intuitive …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 39–46 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning Techniques
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
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Total Lipids and Storage Quality of Oil Seeds and Nuts as Influenced by Yeast Fermentation
Abstract: Oilseeds and the products made from them have a role in a healthy balanced diet, even though they are energy dense and contain a high proportion of fat. Most oilseeds are made up of protein and oil. In general, fat is 18–45% by weight of oilseeds and protein is about 16–40%. Fluctuations in oil yields can cause significant fluctuations in their rates. The oils contain fat-soluble vitamins and unsaturated fats …
Published in International Journal of Fungi · Vol. 1, Issue 2, 2024 · pp. 29–35 Read article
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Robustness of Deepfake Detection Systems Against Adversarial Attacks
Abstract: This paper explores a deep learning system to detect deepfake videos, a common type of fake media. With the use of sophisticated methods such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), our system can reliably discern between authentic and altered videos. It analyzes both the images and the audio in videos to find signs of deepfake manipulation. We process video frames and audio, extract features with CNNs …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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DOCSNAP: Integrating NLP and Computer Vision for Comprehensive Document Summarization
Abstract: Because of the exponential growth of digital content, sophisticated tools are required for effective data interpretation and administration.. This project harnesses the capabilities of the Gemini AI model developed by Google DeepMind to address the challenges of PDF summarization and image captioning. Gemini AI integrates cutting-edge algorithms, including transformer architectures, to process textual and visual data seamlessly. The project's system architecture involves modules for text and image extraction, with a …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article