Search
295 articles for “ML”
-
Complications with Malware Identification in IoT and an Overview of Artificial Immune Approaches
Abstract: An immunity is facilitated by lymphocyte T&B-cells; that possess a wide range of T&B-cell; receptors, respectively. These cells can identify and react to pathogens and diseased cells by presenting peptide antigens by means of significant histocompatibility complexes (MHCs). The amount of data on the repertoire of adaptive immune receptors has increased dramatically in recent years because to advancements in deep sequencing. Furthermore, the presentation of peptides with MHC has been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 1, 2024 · pp. 54–62 Read article
-
Freshwater Resources in Delhi: A Decadal Analysis of Land Use Changes
Abstract: The escalating global concern over the pollution of freshwater resources, driven by the amplifying stress and scarcity of freshwater, underscores the significance of this study. The investigation examined the alterations in land use and land cover (LULC) in Delhi, concurrently assessing the coliform count in water sources designated for drinking and other purposes. LANDSAT 7 satellite imagery scrutinized the LULC changes in Delhi over a decade (2011 to 2021) to …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 1, 2024 · pp. 13–22 Read article
-
Panoramic review on Sida rhombifolia L.
Abstract: Sida Rhombifolia is also called Bala and is a well-known Ayurvedic herbal preparation used to treat inflammation, pain and neurological disorders. Literature calls Bala as Sida cordifolia, Sida, root powder acute, Sida cordata or Sida Rhombifolia subsp. retusa to achieve clinical efficacy of standardization of ksheerBala thailam Balamulacherna is essential.The objective of the study is to authenticate the pharmacognostic standards of Sida Rhombifolia root powder. Sida Rhombifolia was standardized with …
Published in International Journal of Pathogens · Vol. 1, Issue 1, 2024 · pp. 20–32 Read article
-
Enhancing Mutual Fund Investment Decision-making Using Machine Learning: A Survey
Abstract: In India, a significant portion of individuals save a part of their income for a secure future. Government and various public sector financial companies also provide some saving schemes through banks, post offices, and Life Insurance Corporation (LICs) such as Recurring Deposit (RD), Public Provident Fund (PPF), Sukanya Samridhhi Account (SSA) fixed deposits, etc. Over the past decade, many individuals have shifted their saving schemes to vigorously searching for investment …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 43–51 Read article
-
A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
-
Empowering Communication: A Review of Sign Language Translation Systems Powered by Machine Learning
Abstract: This research study offers a fresh solution to the communication gap between the hearing population and the deaf and hard-of-hearing community: the creation of a machine learning-based sign language translator. By utilizing cutting-edge K Nearest Neighbour (K-NN), the system effectively converts sign language motions into text and vice versa, facilitating smooth communication between sign language users and well-read people. The basis of the project is thorough data collection and careful …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 25–31 Read article
-
Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
-
Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
-
Estimation of Alogliptin and Dapagliflozin in Synthetic Mixture by RP-HPLC Method
Abstract: The primary objective of the proposed research was to develop and validate analytical methods for the simultaneous quantification of Alogliptin and Dapagliflozin in a synthetic mixture. Alogliptin and Dapagliflozin are medications used for managing diabetes, with Alogliptin inhibiting the enzyme Dipeptidyl peptidase-4 and Dapagliflozin belonging to the class of sodium-glucose cotransporter 2 inhibitors. High-performance liquid chromatography method development was conducted using a C18 column (250 mmX4.6 mm, 5 μm particle …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 37–46 Read article
-
Toxicology-Focused Development and Validation of an RP-HPLC Technique for Quantifying Bempefoic Acid and Rosuvastatin in a Fixed-Dose Combination
Abstract: A straightforward, precise method was developed to simultaneously assess Bempedoic acid and Rosuvastatin in both bulk and tablet forms. Utilizing a DIKMA Spursil C18 column (4.6 mm x 250 mm, 3.0 μm), chromatography was conducted with a mobile phase comprising 30% phosphate buffer and 70% acetonitrile, flowing at 1 ml/min. Operating at ambient temperature, the optimized wavelength for detection was set at 240 nm, revealing retention times of 4.418 min …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
-
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
-
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
-
Bioremediation Potential: Discovering Naphthalene-Degrading Microbes in Iraqi Contaminated Soil
Abstract: A polycyclic aromatic hydrocarbon, napthalene is an environmental contaminant with a slow rate of disintegration. Biological treatment by microbes present in contaminated places is the most important of the several approaches applied to remove it from the environment. At depths of 5 to 10 cm, soil samples were collected from areas polluted by oil near the Al-Dora and Sheikh Omar refineries. Nutrient agar was cultured with 0.1 ml of each …
Published in International Journal of Pathogens · Vol. 1, Issue 2, 2024 · pp. 32–41 Read article
-
Exploring Artificial Intelligence in the Finance Sector
Abstract: Artificial intelligence (AI), machine learning (ML), and progressive algorithms illustrate a substantial technological leap with wide applications across sectors like automobiles, healthcare, gaming, finance, entertainment, and more. The foremost objective of AI is to produce intelligent, independent systems capable of self-sustaining decision-making. This study delivers a concise summary of AI, concentrating on its transformative influence on finance, especially within banking, asset firms, derivatives markets, and insurance enterprises. It summarizes the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 3, 2024 · pp. 16–23 Read article
-
“Evaluation of superoxide Dismutase (SOD) enzyme level and some indicators in people exposed to smoke”
Abstract: The aim of this study is to assess the level of SOD enzyme and its impact in people who are exposed to smoking, in addition to measuring C-interactive protein, and finally measure a complete picture of blood samples taken from patients. The results of the current study showed there is a significant differences (p<0.05) in the activity of the SOD. The mean of SOD activity in patient was 127.9 U/ml …
Published in International Journal of Toxins and Toxics · Vol. 1, Issue 2, 2024 · pp. 52–55 Read article
-
Identification of Brain Stroke Using Artificial Intelligence
Abstract: Globally, strokes are the primary cause of disability and mortality. Recently, machine learning (ML) and deep learning (DL) have been employed by artificial intelligence algorithms as effective stroke diagnosing techniques. These days, machine learning and data mining technologies are used in the construction of the main models. We have used five machine learning algorithms to determine if a stroke has occurred or is likely to occur based on a patient’s …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
-
Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
-
A New Separation Technique for Method, Development and Validation of Aclidinium Bromide and Formoterol Fumarate in Its Pure and Pharmaceutical Dosage Form by Using Rp-HPLC
Abstract: A new simple, precise, selective and accurate, a new method of development and validation using Rp-HPLC for the estimation of Aclidinium bromide and Formoterol Fumarate in its pure and pharmaceutical dosage form. Chromatogram was run through DIKMA Spursil, C18 segment (4.6×150 mm, 5µ0). Mobile phases contain 0.1% OPA: Acetonitrile (30:70) with the use of the 0.1% OPA buffer, stream rate of 1 ml/min and measured in 280 nm. The run …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 18–36 Read article
-
Management of Steroid Induced Diabetes with Unani Medicine: A Case Report
Abstract: Background: Glucocorticoids (GC), such as prednisolone, are commonly used for their anti-inflammatory and immunosuppressive properties. However, chronic GC use can lead to adverse effects, including diabetes. This case study evaluates the efficacy of Arq Afsanteen, an Unani compound drug, in managing GC-induced diabetes. A 50-year-old man with a family history of type 2 diabetes and a history of partial gastrectomy was diagnosed with sarcoid tuberculosis and began treatment with ATT …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 11, Issue 3, 2024 · pp. 49–53 Read article
-
AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article