Search
169 articles for “extraction efficiency”
-
A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
-
A Comprehensive Tool for Authenticating Instagram Profiles Using Instaloader
Abstract: With the rapid growth of Instagram as a dominant social media platform, there is an increasing need for tools that allow users to extract, analyze, and monitor profile data efficiently. Instagram has become one of the leading platforms for personal branding, influencer marketing, business promotion, and public communication. As businesses and individuals seek to better understand their presence and influence on this platform, the need for reliable data extraction tools …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 93–98 Read article
-
Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
-
Big Data, Big Impact: The Role of Analytics in Modern Business
Abstract: In modern business, “Big Data” signifies the vast amount of data collected from various sources, and “Big Data Analytics” refers to the process of analyzing this data to extract valuable insights, enabling companies to make data-driven decisions, optimize operations, better understand customers, and ultimately gain a competitive edge by identifying trends, patterns, and opportunities that might otherwise be missed. This study analyzes large datasets, by which businesses can gain deeper …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
-
Energy-efficient Image Classification on Edge Devices: Implementation and Evaluation
Abstract: Image classification is a computer vision problem where an algorithm determines a class or label for a given image. Various real-time applications like object recognition, medical diagnosis, person recognition, etc. Image classification property on edge devices is useful for autonomous vehicles, surveillance, and healthcare and internet of things deployments. The advancement of deep learning based methods and graphics processing units (GPU) devices allows efficient processing locally. The study utilizes a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 10–18 Read article
-
Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
-
Comparative Evaluation of Hibiscus Cannabinus and Solanum Trilobatum Extracts as Inhibitors for C- Steel Corrosion protection in Acidic Medium
Abstract: This study analyzed the efficacy of various inhibitors in safeguarding carbon steel against corrosion in hydrochloric acid. The compounds that were subjected to testing included Acalypha indica root extract (AIRE), Hibiscus cannabinus (HC), and Solanum trilobatum (ST) leaf extracts. The investigation focused on the inhibitory efficacy through the application of gravimetric and electrochemical impedance methods. GC-MS and FTIR were employed to investigate the features of the inhibitors and co-inhibitors. Tafel …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 555–565 Read article
-
Optimization of a new Bebq2/BCP-based OLED structure for optimum performance
Abstract: Opto-electronic devices exhibit highly nonlinear current–voltage (I–V) characteristics that significantly affect charge injection, transport, and recombination, evaluating their performance remains a difficult challenge. Device optimization is a key research goal in organic light-emitting diodes (OLEDs), as the thickness and arrangement of individual functional layers greatly influence electrical and optical responses. For a suggested Bebq2/BCP-based OLED structure, this work methodically examines the movement of charge carriers, their transport behavior, and the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
-
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
-
Isolation and Characterization of Glucuronide Compound from Luffa Tuberosa (Roxb.) for Potential Applications in Polymer Chemistry
Abstract: This study explores the isolation process of glucuronide compounds from Luffa tuberosa (Roxb.) using an efficient and cost-effective method. The extracted compound, Gypsogenin-3β-O-β-D-Methyl glucuronide, is characterized using spectroscopic techniques such as IR, NMR, and Mass Spectrometry. The polymeric nature of glucuronide-based compounds and their potential applications in polymer and composite materials are discussed. The findings highlight the suitability of glucuronide derivatives in biomedical, pharmaceutical, and polymeric drug delivery systems. Additionally, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 566–572 Read article
-
Advancements in Ore Beneficiation Technologies: A Review of Modern Extraction Methods
Abstract: Ore beneficiation plays an essential role in the mining industry, as it facilitates the extraction of valuable minerals from their ores while ensuring maximum efficiency and minimal environmental impact. Beneficiation technologies have evolved significantly over time, leading to improvements in metal recovery rates and reduced waste generation. These advancements have enabled the mining industry to address increasing resource demands, with a particular focus on sustainability and cost-effectiveness. In this review, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 36–40 Read article
-
Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
-
LLM-based Chatbot for Course-based Question Answering
Abstract: The “LLM-based Chatbot for Course-Based Question Answering” project addresses the pressing need for tailored and efficient learning tools in education. By using a state-of-the-art Large Language Model (LLM) with a diverse dataset, including textbooks, professor slides, and web scraping data, the chatbot offers accurate and contextually enriched responses to students' course-related queries. Using recent advances in language modeling, this work presents a Longformer-based Language Model (LLM) for constructing a smart …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 30–41 Read article
-
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
-
Accelerate Drug Development with Pharmacokinetic Softwares
Abstract: During continuously evolving technologies and mechanized equipments, there has been a tremendous growth in the pharmaceutical sector over the past few decades. New technologies, software, devices, and techniques are being developed or researched upon with each passing day. By leveraging pharmacokinetic software, researchers can efficiently analyze vast datasets from preclinical and clinical studies, extracting actionable insights that inform decision-making early in the development cycle. This predictive capability not only accelerates …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
-
Effect of Particle Size on Recovery of Moringa (Moringa oleifera) Seeds Oil and Quality Characterization
Abstract: Utilization of various plant parts of the moringa tree is gaining interest nowadays due to their versatile quality characteristics. Different parts of the moringa tree, like leaves, flowers, fruits, seeds, and barks, are distinguished well in the decade due to their inherent nutritional as well as medicinal properties. Moringa seed oil has potential quality characteristics like other well-regarded oils, viz., olive oil, coconut oil. The objective of this study was …
Published in Research & Reviews : Journal of Herbal Science · Vol. 14, Issue 1, 2025 · pp. 1–14 Read article
-
Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
-
Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
-
Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
-
Design and Analysis of Quantum Dot Solar Cell Using SCAPS-1D Software
Abstract: Compared to conventional solar cells, quantum dot solar cells (QDSCs) have drawn a lot of attention due to their hybrid structure, low production cost, and greater power conversion efficiency. Nevertheless, carrier recombination in the quasi-neutral region (QNR) continues to limit their performance. The electron transport layer (ETL) and hole transport layer (HTL) are two of the layers that are most important in determining the overall efficiency of the device. The …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 · pp. 15–20 Read article