Real-world environment models for mobile network evaluation

Real-World Oriented Mobile Constellation Learning Environment Using Gaze Pointing

We developed a real-world oriented mobile constellation learning environment. Learners point at a target constellation by gazing through a cylinder with a gyro-sensor, which can display information related to the constellation. The system has a learning function. Through experimentation, we evaluated the learning environment to assess its learning effects.

Neural Network Models for Speech Recognition in Mobile Environment

Neural networks (NN) are well known for capturing the complex distributions present in data. The ability of the model depends on the structure of the network and the nature of the data used for training [1]. In this paper, we are exploring neural network models for digit recognition in mobile environment. Due to recent advancements and applications in mobile communication, there is a need to de...

Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful ...

Real-World Evaluation and Deployment of Adversary Attack Prediction Models

Conceptual models for real-world locomotion

During human and animal locomotion, the dynamics of the body can be represented with the help of simplified biomechanical models, such as the spring-mass model (often described as spring-loaded inverted pendulum, SLIP model). In this model, it is assumed that the force generated by each limb resembles that of a linear spring. Furthermore, it is assumed that force generated by the leg mainly act...