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13 articles for “active recall”
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CogniLeapAI: An Adaptive Personalized Learning Platform with AI-Powered Content Generation, Active Recall, and Intelligent Study Planning
Abstract: Students today must work through large volumes of academic PDFs with little tooling to support effective learning. Passive reading remains the default approach for most learners, yet it consistently produces poor retention and demands excessive preparation time. This paper presents CogniLeapAI, a web-based platform designed to convert static PDF documents into a closed-loop adaptive learning system. AI requests are routed across four providers (Google Gemini, OpenRouter, LaoZhang, and Kie.ai) with …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 2, 2026 · pp. 45–63 Read article
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Human Activity Recognition Using For Smartphone Sensors To Predict The Best Accuracy Based On Machine Learning Algorithms
Abstract: Human activity recognition requires predicting the action of a person based on sensor-generated data. Due to the enormous number of applications possible by modern ubiquitous computing devices, it has sparked a lot of attention in recent years. It categorizes data into actions such as walking, sitting, standing, and lying. The accelerometer and gyroscope were used to generate the sensor data, and the sensor signals were pre-processed with noise filters. The …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 12–23 Read article
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Nitrosamine: The Carcinogenic Impurity in Angiotensin Receptor Blockers
Abstract: Angiotensin II Receptor Blockers (ARBs), commonly known as the Sartans, are used in the treatment of hypertension for a long time. Currently, seven Sartan drugs, i.e. Valsartan, Losartan, Candesartan, Irbesartan, Telmisartan, Olmesartan, and Eprosartan, are in use. Recently, Nitroso impurity was detected in Valsartan active pharmaceutical ingredient, which led to the recall of batches of products containing it. Even in trace amounts, the impurity is said to be a probable …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 9, Issue 3, 2020 · pp. 36–43 Read article
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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
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A Study on Orthorexia Nervosa: When Healthy Eating Becomes an Obsession
Abstract: Orthorexia nervosa (ON) is a new eating disorder described as an obsession for healthy eating. Recently individuals exhibiting different ‘‘highly sensitive eating behavior disorders” are increasing with the increased consciousness about various diseases globally and the role of diet in their prevention. Accordingly, the purpose of this study was to identify individuals with obsessive eating behavior. Sample included 30 nutrition professionals and 30 non-nutrition professionals (n=60; all graduates and above). …
Published in Research and Reviews: A Journal of Health Professions · Vol. 4, Issue 3, 2014 · pp. 1–4 Read article
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Systematic Analysis of the Therapeutic Potential of Bacopa monnieri: A Wonder Therapeutic Plant
Abstract: Bacopa monnieri (L.) Wettst., a well-known perennial creeping herb, native to parts of America, the African subcontinent, and South Asia, had been a well-known nootropic plant, documented in ancient Indian systems of medicine, Ayurveda. The dynamic variations in the phytocompounds consortia, regulated by abiotic cultivation conditions and germplasm, provided a paradigm shift towards the exploring profound therapeutic effect of the plant along with advancements in scalable cultivation strategies. Tailoring the …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 2, 2026 · pp. 39–46 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 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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Solid Acid Catalysts for the Selective Conversion of Biomass to Levulinic Acid
Abstract: Levulinic acid (LA) has emerged as a versatile platform chemical with significant potential for producing renewable fuels like gamma-valerolactone (GVL), biodegradable polymers, and fine chemicals from biomass (both terrestrial and marine which ae rich in carbohydrate). The selective conversion of biomass-derived carbohydrates to LA requires efficient catalytic systems that can overcome the recalcitrance of the biomass, namely the stiff-necked structural integrity of cellulose and the kind of strong interactions between …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 23–35 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Curbing Speculation vs. Market Participation: A Study of SEBI’s 2024 Derivatives Measures
Abstract: The derivative market has become a cornerstone of India’s financial ecosystem, complementing the traditional stock market by enabling risk management, price discovery, and liquidity enhancement. However, with the rapid growth of this segment, concerns over speculative activities have prompted regulatory intervention. On October 1, 2024, the Securities and Exchange Board of India (SEBI) introduced significant reforms aimed at curbing speculation, protecting retail investors, and fostering market stability. While these changes …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 2, 2025 · pp. 28–43 Read article
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Linear Programming for Profit Optimization in Small-Scale Manufacturing: A Python-Based Simplex and Machine Learning Approach
Abstract: Profit maximization under resource constraints is a classic challenge. Small manufacturers face tight margins and scarce capital every day. This paper tackles that problem using four Python-based methods. The case study is Bintang Bakery in Bandar Lampung, Indonesia. The bakery makes three bread types and faces 18 resource constraints. Data comes from Anggoro et al. Methods tested include LP revised simplex, Differential Evolution, PSO, and ANN Surrogate. General-purpose scipy minimizers …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 01–11 Read article
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Evaluation of Ensemble and Deep Learning Classifiers on CSE-CIC-IDS2018 Dataset for Intelligent NIDS
Abstract: Network Intrusion Detection System (NIDS) plays an active role in preventing cyberattacks by early detection of threats before it really starts affecting targeted information services. Over the years, many intrusion detection system (IDS) have been developed applying signature or rule-based approach to prevent unauthorised access of network or computer devices. However, ever growing landscape of cyberattacks in recent years has motivated present day researchers to design and develop more accurate …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 1–11 Read article