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1883 articles for “term” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Violent Event Recognition and Monitoring Using Deep Learning for Surveillance Videos
Abstract: The significance of real-time capabilities in human detection and tracking is discussed in the abstract of the paper. We talk about tracking, eye detection, and face detection. A thorough motion detection program for use in video monitoring and other applications is suggested by the study. The goal of the study is to further human tracking technology. Optical flow features and appearance-invariant features from a Darknet CNN model are integrated. Acquiring …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 2, 2023 · pp. 39–44 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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A review of the intelligent techniques for load forecasting of UHBVNL
Abstract: The primary aim of load forecasting is to know the change in power demand with the variable factors on a short-term, medium-term, and long-term basis and to evolve our power system network according to the changing variables. It ensures correct values to the operations, stability, demand management, scheduling generating capacity, efficiency, reliability, accuracy, economy, controlling, scheduling, security analysis, environmental sustainability, etc. Various forecasting techniques are there which are making it …
Published in Journal of Power Electronics and Power Systems · Vol. 13, Issue 3, 2023 · pp. 30–38 Read article
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Detecting the Additives Impact on The Durability of Asphalt Concrete
Abstract: Modification of asphalt cement with additives is considered as a sustainable issue to enhance the asphalt concrete quality and durability among the expected service life. An attempt has been made in the present investigation to detect the influence of modification of the asphalt binder by 2 % silica fumes and 4 % fly ash additives on the durability of asphalt concrete in terms of fatigue life under long-term ageing and …
Published in Trends in Transport Engineering and Applications · Vol. 8, Issue 2, 2021 · pp. 21–29 Read article
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TRACE: Tracking the Loss of Memory Provenance in LLM Agents
Abstract: AI agents that carry memory across sessions gain better personalization and decision-making, but this persistence opens a serious security gap. When an agent repeatedly condenses earlier interactions into compact “lessons,” the trail linking each lesson back to the interaction that produced it gradually fades. We term this effect Reflective Attribution Collapse (RAC): the progressive loss of provenance and forensic traceability that results from repeated memory reflection. Under RAC, a malicious …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 33–49 Read article
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Pattern Discovery for Text Mining
Abstract: Text mining refers to the process of extracting interesting, non-trivial information and knowledge from unstructured text. The challenging issue is to find accurate cognition or characteristics in text documents to help users to find what they want. Many term-based methods solved this but later suffered from the problems of polysemy and synonymy where polysemy means a word has multiple meanings and synonymy is multiple words having the same meaning. Later …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 1, 2014 · pp. 28–31 Read article
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Stock Market Prediction with LSTM-based Neural Networks: An Empirical Analysis
Abstract: A stock market is a composite of markets and exchanges where the buying and selling of publicly traded company stocks occur on a regular basis. It serves as a marketplace for the stocks of corporations that are available to the public. Companies opt for an initial public offering (IPO) on the primary market as a means to generate capital. People buy stocks primarily in the hope that they may rise …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 1, 2023 · pp. 9–14 Read article
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Prevalence and Factors of Pregnancy Execution among Nepalese Married Women: A Cross-Sectional Study
Abstract: This paper, statistically presents the pregnancy termination issues in context of Nepal. An application of logistic regression model is used to address the prevalence and cause factors of pregnancy termination. The estimate of parameters of the model is obtained through Maximum Likelihood Estimate (MLE) and validates the model through different diagnostic tests (log-likelihood, Hosmer and Lameshow R2, Negelkerke R2, Cox-Snell’s R2, residual plot and variance inflation factor). In outlook of …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 8, Issue 3, 2018 · pp. 16–21 Read article
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Classifying Abnormalities in Heartbeat Sound
Abstract: Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure in their early stages. In the proposed method, various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (mel-frequency cepstral coefficients). Then, a deep learning approach is applied in which the MFCC audio signals are sent to the CNN (convolutional neural …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 24–31 Read article
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Determining the Root Causes of Complications in Hemodialysis
Abstract: As with peritoneal dialysis and kidney transplantation, hemodialysis has been considered one of the most effective therapies for the replacement of kidney function. While this helps to save patients with the disease by decreasing morbidity /mortality/ rates, this medication has some side effects. These may manifest during the dialysis process alongside the ongoing treatment. Avoiding these barriers becomes crucial for improving the patients’ prognosis in this context.We are going to …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 1, 2024 · pp. 27–47 Read article
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Molecular Docking of Arjuna Tree Phytocompounds for Ischemic Heart Disease
Abstract: Heart disease is a serious condition that can be caused by several lifestyle changes and sometimes genetic problems. The primary protein component of apolipoprotein is the LDL receptor, which indicates that a reduction in LDL levels can reduce the risk of ischemic heart disease. Apolipoprotein levels are associated with increased levels of ischemic heart disease. Using ADMET analysis, drug likelihood prediction, and molecular docking, this work attempted to find natural …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 42–52 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Characterization of Thermochemical Properties and Combustion Behavior In AP/HTPB Polymer Composite Solid Propellant for Enhanced Performance
Abstract: The thermal decomposition of solid propellants containing hydroxyl-terminated polybutadiene (HTPB) binder is a complex process, driven by multiple interacting chemical and physical factors. Solid propellant combustion characteristics are profoundly influenced by the composition of the propellant, the conditions of pressure, the starting temperature, and a range of aero-thermochemical parameters. The paper explores the influence of polymeric structure in the HTPB binder on thermal decomposition characteristics of the AP/HTPB composite propellants …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 502–511 Read article
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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ECO Report Analys Achieving SDG 15
Abstract: This project creates automated data processing tool Eco Data Analyser for ecological data analysis for SDG 15: Life on Land conservation and biodiversity. File_picker, Excel, and CSV are used in the Flutter and Dart based cross-platform solution to assist environmental organizations in handling ecological data. Uploading ecological datasets, verifying data, classifying biodiversity indicators, and producing summary reports helps Eco Data Analyser to make conservation data accessible and valuable. User-defined parameters …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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Leveraging Standards and Deep Learning Approaches to Secure Internet of Things (IoT) Devices from Cyber Attack
Abstract: The widespread adoption of Internet of Things (IoT) devices between 2019 and 2024 has significantly grows in various sectors in Japan, including healthcare, manufacturing, and the development of smart cities. Although this growth offers many advantages, it also makes these devices more vulnerable to cyber threats. High-profile security breaches in Japan have sparked discussions about the requirement for enhanced security measures to protect the rapidly evolving IoT technologies. This study …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article