Titlebook: Emerging Trends and Applications in Artificial Intelligence; Selected papers from Fausto Pedro García Márquez,Akhtar Jamil,Isaac Seg Confer

一大群

警告

Lineare Gleichungssysteme, direkte Methoden,techniques. Anterior-Posterior and Lateral images are used together in this study to make identification much more accurate. The proposed system identifies five different knee implants with an accuracy of 86.25% and an Area Under curve of 0.974.

Constant

不斷的變動(dòng)

起波瀾

Gesture

,A Framework for?Knowledge Representation Integrated with?Dynamic Network Analysis,hold the semantic interaction across the entities and, using links, connect them in a better representable way. In this paper, we proposed a dynamic network analysis framework for understanding the evolution of Knowledge Graphs across timelines. To validate our findings, we applied a thorough analys

intelligible

,Time Series Forecasting Using Parallel Randomized Fuzzy Cognitive Maps and?Reservoir Computing,y to enhance accuracy and are well-equipped to handle uncertainty and emulate the dynamics of complex systems. The main goal of this article is to present a new randomized multiple-input multiple-output (MIMO) FCM-based forecasting technique named M-PRFCM to forecast real-world high-dimensional time

ANTH

,Review of?Offensive Language Detection on?Social Media: Current Trends and?Opportunities,fensive language gains traction due to the high and growing scale of social media user input. In this paper, we provide an overview of the field including background and recent research with a focus on natural language processing. We present a synopsis on the ambiguity in definition and categorizati

sclera

,Text Mining and?Sentimental Analysis to?Distinguish Systems Thinkers at?Various Levels: A Case Studsocial media analysis to explore the relationship between experts’ ST and their tweets, specifically focusing on COVID-19. Twitter is crucial for information dissemination, but misinformation can spread during a pandemic like COVID-19. By analyzing the emotional and sentimental aspects of tweets fro

visceral-fat

ADHD Prediction in Children Through Machine Learning Algorithms,diagnosed based on the presence of inattentive and hyperactive symptoms. Our objective is to identify ADHD from a Machine Learning (ML) perspective, utilizing symptom information and features such as socioeconomic status, social behavior, academic competence, and quality of life. We conducted extens