|
|
|
Mohamed A. Damos, Jun Zhu, Weilian Li, Elhadi Khalifa, Abubakr Hassan, Rashad Elhabob, Alaa Hm and Esra Ei
Social media platforms play a vital role in determining valuable tourist objectives, which greatly aids in optimizing tourist path planning. As data classification and analysis methods have advanced, machine learning (ML) algorithms such as the k-means a...
ver más
|
|
|
|
|
|
|
Kegong Shi, Jinjin Yan and Jinquan Yang
Reasonable semantic partition of indoor areas can improve space utilization, optimize property management, and enhance safety and convenience. Existing algorithms for such partitions have drawbacks, such as the inability to consider semantics, slow conve...
ver más
|
|
|
|
|
|
|
Kyle DeMedeiros, Chan Young Koh and Abdeltawab Hendawi
The Chicago Array of Things (AoT) is a robust dataset taken from over 100 nodes over four years. Each node contains over a dozen sensors. The array contains a series of Internet of Things (IoT) devices with multiple heterogeneous sensors connected to a p...
ver más
|
|
|
|
|
|
|
Nattakan Supajaidee, Nawinda Chutsagulprom and Sompop Moonchai
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK)...
ver más
|
|
|
|
|
|
|
Frank Klawonn and Georg Hoffmann
Clustering algorithms are usually iterative procedures. In particular, when the clustering algorithm aims to optimise an objective function like in k-means clustering or Gaussian mixture models, iterative heuristics are required due to the high non-linea...
ver más
|
|
|
|
|
|
|
Li Sun, Jingfa Yao, Hongbo Cao, Haijiang Chen and Guifa Teng
In agricultural production, rapid and accurate detection of peach blossom bloom plays a crucial role in yield prediction, and is the foundation for automatic thinning. The currently available manual operation-based detection and counting methods are extr...
ver más
|
|
|
|
|
|
|
Dimitris Fotakis, Panagiotis Patsilinakos, Eleni Psaroudaki and Michalis Xefteris
In this work, we consider the problem of shape-based time-series clustering with the widely used Dynamic Time Warping (DTW) distance. We present a novel two-stage framework based on Sparse Gaussian Modeling. In the first stage, we apply Sparse Gaussian P...
ver más
|
|
|
|
|
|
|
Yuchen Liang, Yanan Cheng, Zhaoxin Zhang, Tingting Chai and Chao Li
Detecting and controlling illegal websites (gambling and pornography sites) through illegal domain names has been an unsolved problem. Therefore, how to mine and discover potential illegal domain names in advance has become a current research hotspot. Th...
ver más
|
|
|
|
|
|
|
Abdullah Ali Jawad Al-Abadi, Mbarka Belhaj Mohamed and Ahmed Fakhfakh
In recent years, the combination of wireless body sensor networks (WBSNs) and the Internet ofc Medical Things (IoMT) marked a transformative era in healthcare technology. This combination allowed for the smooth communication between medical devices that ...
ver más
|
|
|
|
|
|
|
Sejeong Kim and Jongho Park
Recently, an Unmanned Aerial Vehicle (UAV)-based Wireless Sensor Network (WSN) for data collection was proposed. Multiple UAVs are more effective than a single UAV in wide WSNs. However, in this scenario, many factors must be considered, such as collisio...
ver más
|
|
|
|