Laura Smets,Werner Van Leekwijck,Ing Jyh Tsang et al.
Laura Smets et al.
Introduction: Hyperdimensional Computing (HDC) is a brain-inspired and lightweight machine learning method. It has received significant attention in the literature as a candidate to be applied in the wearable Internet of ...
Chao-Min Chang,Cheng-Te Li,Shou-De Lin
Chao-Min Chang
Time series forecasting is an essential tool across numerous domains, yet traditional models often falter when faced with unilateral boundary conditions, where data is systematically overestimated or underestimated. This paper introduces a ...
Mais Qandeel
Mais Qandeel
Despite their pronounced potential, unacceptable risk AI systems, such as facial recognition, have been used as tools for, inter alia, digital surveillance, and policing. This usage raises concerns in relation to the protection of basic fre...
Analyzing political party positions through multi-language twitter text embeddings [0.03%]
基于多语言twitter文本嵌入分析政党立场
Jinghui Chen,Takayuki Mizuno,Shohei Doi
Jinghui Chen
Traditional monolingual word embedding models transform words into high-dimensional vectors which represent semantics relations between words as relationships between vectors in the high-dimensional space. They serve as productive tools to ...
Elizabeth Newman,Lior Horesh,Haim Avron et al.
Elizabeth Newman et al.
Learning from complex, multidimensional data has become central to computational mathematics, and among the most successful high-dimensional function approximators are deep neural networks (DNNs). Training DNNs is posed as an optimization p...
Particulate matter forecast and prediction in Curitiba using machine learning [0.03%]
基于机器学习的库里蒂巴颗粒物预报与预测
Marianna Gonçalves Dias Chaves,Adriel Bilharva da Silva,Emílio Graciliano Ferreira Mercuri et al.
Marianna Gonçalves Dias Chaves et al.
Introduction: Air quality is directly affected by pollutant emission from vehicles, especially in large cities and metropolitan areas or when there is no compliance check for vehicle emission standards. Particulate Matter...
From theory to practice: insights and hurdles in collecting social media data for social science research [0.03%]
从理论到实践：社会科学中的社交媒体数据采集的启示与障碍
Yan Chen,Kate Sherren,Kyung Young Lee et al.
Yan Chen et al.
Social media has profoundly changed our modes of self-expression, communication, and participation in public discourse, generating volumes of conversations and content that cover every aspect of our social lives. Social media platforms have...
Cedric Waterschoot,Antal van den Bosch
Cedric Waterschoot
Introduction: Recently, content moderators on news platforms face the challenging task to select high-quality comments to feature on the webpage, a manual and time-consuming task exacerbated by platform growth. This paper...
Big data and its impact on the 3Rs: a home cage monitoring oriented review [0.03%]
大数据及其对3R的影响：以笼养监测为导向的回顾性研究
Sara Fuochi,Mara Rigamonti,Eoin C O&#x;Connor et al.
Sara Fuochi et al.
Undisturbed home cage recording of mouse activity and behavior has received increasing attention in recent years. In parallel, several technologies have been developed in a bid to automate data collection and interpretation. Thanks to these...
Development and application of a machine learning-based predictive model for obstructive sleep apnea screening [0.03%]
一种基于机器学习的阻塞性睡眠呼吸暂停筛查预测模型的研究与应用
Kang Liu,Shi Geng,Ping Shen et al.
Kang Liu et al.
Objective: To develop a robust machine learning prediction model for the automatic screening and diagnosis of obstructive sleep apnea (OSA) using five advanced algorithms, namely Extreme Gradient Boosting (XGBoost), Logis...