Mobile healthcare: opportunities and challenges
YY Shieh, FY Tsai, A Anavim… - … conference on the …, 2007 - ieeexplore.ieee.org
The healthcare crisis in the US has caught national attention because of its high percentage
of GDP spending. Healthcare reform has become a heated topic of discussion. Its key lies in …
of GDP spending. Healthcare reform has become a heated topic of discussion. Its key lies in …
A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting
In this paper, we propose a new day-ahead direct time series forecasting method for
competitive electricity markets based on clustering and next symbol prediction. In the …
competitive electricity markets based on clustering and next symbol prediction. In the …
Forecasting pedestrian movements using recurrent neural networks: An application of crowd monitoring data
DC Duives, G Wang, J Kim - Sensors, 2019 - mdpi.com
Currently, effective crowd management based on the information provided by crowd
monitoring systems is difficult as this information comes in at the moment adverse crowd …
monitoring systems is difficult as this information comes in at the moment adverse crowd …
Development of people mass movement simulation framework based on reinforcement learning
Understanding individual and crowd dynamics in urban environments is critical for
numerous applications, such as urban planning, traffic forecasting, and location-based …
numerous applications, such as urban planning, traffic forecasting, and location-based …
A survey on next-cell prediction in cellular networks: Schemes and applications
L Huang, L Lu, W Hua - IEEE Access, 2020 - ieeexplore.ieee.org
Mobility prediction is a powerful tool for network operators to optimize network performance.
From cell level, if network operators know the cells to which the users will be connected in …
From cell level, if network operators know the cells to which the users will be connected in …
Intercity simulation of human mobility at rare events via reinforcement learning
Agent-based simulations, combined with large scale mobility data, have been an effective
method for understanding urban scale human dynamics. However, collecting such large …
method for understanding urban scale human dynamics. However, collecting such large …
Continuous social distance monitoring in indoor space
The COVID-19 pandemic has caused over 6 million deaths since 2020. To contain the
spread of the virus, social distancing is one of the most simple yet effective approaches …
spread of the virus, social distancing is one of the most simple yet effective approaches …
Optimized handoff with mobility prediction scheme using hmm for femtocell networks
In this paper, we propose a new approach for optimizing the handoff decision in femtocell
networks using Hidden Markov Model. To do so, we formulate the handoff problem as an …
networks using Hidden Markov Model. To do so, we formulate the handoff problem as an …
Anomaly detection and modeling in 802.11 wireless networks
A Allahdadi, R Morla - Journal of Network and Systems Management, 2019 - Springer
IEEE 802.11 Wireless Networks are getting more and more popular at university campuses,
enterprises, shopping centers, airports and in so many other public places, providing …
enterprises, shopping centers, airports and in so many other public places, providing …
Location and mobility-aware routing for improving multimedia streaming performance in MANETs
Device mobility is an issue that affects both Mobile ad hoc networks (MANETs) and
opportunistic networks. While the former employs conventional routing techniques with …
opportunistic networks. While the former employs conventional routing techniques with …