Abstract Rivers carry suspended sediments along with their flow. These deposit at different places depending on the discharge and course of river. However, deposition these impacts environmental health, agricultural activities, portable water sources. Deposition reduces flow area, thus affecting movement aquatic lives ultimately leading to change river course. Thus, data variation is crucial information for various authorities. Various authorities require forecasted in operate hydraulic...

The suspended sediment load (SSL) is one of the major hydrological processes affecting sustainability river planning and management. Moreover, sediments have a significant impact on dam operation reservoir capacity. To this end, reliable applicable models are required to compute classify SSL in rivers. application machine learning has become common solve complex problems such as modeling. present research investigated ability several data. This investigation aims explore new version...

Human detection in videos plays an important role various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they highly susceptible to dynamical events such as illumination changes, camera jitter, variations object sizes. On the other hand, proposed feature learning cheaper easier because abstract discriminative can be produced automatically without need expert knowledge. In...

Hormone receptor status is determined primarily to identify breast cancer patients who may benefit from hormonal therapy. The current clinical practice for the testing using either Allred score or H-score still based on laborious manual counting and estimation of amount intensity positively stained cells in immunohistochemistry (IHC)-stained slides. This work integrates cell detection classification workflow carcinoma estrogen (ER)-IHC-stained images presents an automated evaluation system....

Blood cell counting plays a crucial role in clinical diagnosis to evaluate the overall health condition of an individual. Traditionally, blood cells are manually counted using hemocytometer; however, this task has been found be time-consuming and error-prone. Recently, machine learning-based approaches have employed effectively automate tasks. In work, fifth version 'you only look once' (YOLOv5) object detection method was adopted automatically detect count white (WBCs) porcine smear images....

Ozone (O3) is one of the common air pollutants. An increase in ozone concentration can adversely affect public health and environment such as vegetation crops. Therefore, atmospheric quality monitoring systems were found to monitor predict concentration. Due complex formation influenced by precursors meteorological conditions, there a need examine evaluate various machine learning (ML) models for prediction. This study aims utilize ML including Linear Regression (LR), Tree (TR), Support...

Human detection and activity recognition (HDAR) in videos plays an important role various real-life applications. Recently, object methods such as "you only look once" (YOLO), faster region based convolutional neural network (R-CNN), EfficientDet have been used to detect humans for subsequent decision-making This paper aims address the problem of human aerial captured video sequences using a moving camera attached platform with dynamical events varied altitudes, illumination changes, jitter,...

Intestinal parasitic infections (IPIs) caused by protozoan and helminth parasites are among the most common in humans low-and-middle-income countries. IPIs affect not only health status of a country, but also economic sector. Over last decade, pattern recognition image processing techniques have been developed to automatically identify eggs microscopic images. Existing identification still suffering from diagnosis errors low sensitivity. Therefore, more accurate faster solution is required...

Hyper-personalized medicine represents the cutting edge of healthcare, which aims to tailor treatment and prevention strategies uniquely each individual. Unlike traditional approaches, often adopt a one-size-fits-all or even broadly personalized approach based on broad genetic categories, hyper-personalized considers an individual's comprehensive health data by integrating unique biological, genetic, lifestyle, environmental influences. This method goes beyond simple profiling recognizing...

TikTok is a major force among social media platforms with over billion monthly active users worldwide and 170 million in the United States. The platform's status as key news source, particularly younger demographics, raises concerns about its potential influence on politics U.S. globally. Despite these concerns, there scant research investigating TikTok's recommendation algorithm for political biases. We fill this gap by conducting 323 independent algorithmic audit experiments testing...

Tumor boards are multidisciplinary teams of healthcare professionals that working together to encompass the full spectrum care around diagnosing, planning treatment, and advising outcomes for individual cancer patients. These typically consist oncologists, radiologists, pathologists, geneticists, surgeons, nurse practitioners, other palliative (National Cancer Institute, 2024). create a collaborative space experts from various disciplines assess clinical factors patient circumstances,...

The integration of Generative Artificial Intelligence (GenAI) into university-level academic writing presents both opportunities and challenges, particularly in relation to cognitive dissonance (CD). This work explores how GenAI serves as a trigger amplifier CD, students navigate ethical concerns, integrity, self-efficacy their practices. By synthesizing empirical evidence theoretical insights, we introduce hypothetical construct GenAI-induced illustrating the psychological tension between...

Accessing the internet in regions with expensive data plans and limited connectivity poses significant challenges, restricting information access economic growth. Images, as a major contributor to webpage sizes, exacerbate this issue, despite advances compression formats like WebP AVIF. The continued growth of complex curated web content, coupled suboptimal optimization practices many regions, has prevented meaningful reductions page sizes. This paper introduces PixLift, novel solution...

Abstract Generative Artificial Intelligence (AI) is a cutting-edge technology capable of producing text, images, and various media content leveraging generative models user prompts. Between 2022 2023, AI surged in popularity with plethora applications spanning from AI-powered movies to chatbots. This paper investigates the potential within realm World Wide Web, specifically focusing on image generation. Web developers already harness help craft text while browsers might use it future locally...

OPINION article Front. Pharmacol., 08 November 2021Sec. Drugs Outcomes Research and Policies https://doi.org/10.3389/fphar.2021.754011

Recognition of space objects including spacecraft and debris is one the main components in situational awareness (SSA) system. Various tasks such as satellite formation, on-orbit servicing, active removal require object recognition to be done perfectly. The task actual imagery highly complex because sensing conditions are largely diverse. include various backgrounds affected by noise, several orbital scenarios, high contrast, low signal-to-noise ratio, sizes. To address problem recognition,...

Abstract Natural calamities like droughts have harmed not just humanity throughout history but also the economy, food, agricultural production, flora, animal habitat, etc. A drought monitoring system must incorporate a study of geographical and temporal fluctuation characteristics to function effectively. This investigated space–time heterogeneity features across Sabah Sarawak, East Malaysia. The Standardized Precipitation Index (SPIs) at timescales 1-month, 3-months, 6-months was selected...

Abstract Due to excessive streamflow (SF), Peninsular Malaysia has historically experienced floods and droughts. Forecasting mitigate municipal environmental damage is therefore crucial. Streamflow prediction been extensively demonstrated in the literature estimate continuous values of level. Prediction not necessary several applications at same time it very challenging task because uncertainty. A category more advantageous for addressing uncertainty numerical point forecasting, considering...

Abstract With over two billion monthly active users, YouTube currently shapes the landscape of online political video consumption, with 25% adults in United States regularly consuming content via platform. Considering that nearly three-quarters videos watched on are delivered its recommendation algorithm, propensity this algorithm to create echo chambers and deliver extremist has been an area research. However, it is unclear whether may exhibit leanings toward either Left or Right. To fill...

Video pornography and nudity detection aim to detect classify people in videos into nude or normal for censorship purposes. Recent literature has demonstrated utilising the convolutional neural network (CNN) extract features directly from whole frames support vector machine (SVM) extracted two categories. However, existing methods were not able small-scale content of with diverse backgrounds. This limitation led a high false-negative rate (FNR) misclassification as ones. In order address...

Abstract Network Anomaly Detection is still an open challenging task that aims to detect anomalous network traffic for security purposes. Usually, the data are large-scale and imbalanced. Additionally, they have noisy labels. This paper addresses previous challenges utilizes million-scale highly imbalanced ZYELL’s dataset. We propose train deep neural networks with class weight optimization learn complex patterns from rare anomalies observed data. proposes a novel model fusion combines two...