Sentence examples for user based on the from inspiring English sources

Song et al. [102] addressed this question and investigated to what extent one could predict the subsequent location of a user based on the sequence of his previous visited locations.

Access frequency, which is a figure estimated by the user based on the likely usage of the content.

OFDMA allows a wireless network to flexibly assign bandwidth and physical resources to a user based on the application running, bandwidth needs and/or the users' data subscription plan.

The scenario and the system model are introduced in Section 2. The optimization problem formulation of resource reuse for one CU vs. one D2D user based on the proportional fairness criterion is proposed in Section 3, and also the procedures of the optimal solution, with the name of proportional fairness scheduling (PFS) algorithm, are derived.

WeFi can then ascertain the location of that user based on the known location of one of the hotspots that the WeFi client sees, without the need to be connected to it.

The proposed recommendation algorithm could suggest many high-quality recommendation lists for the target user based on the concept of Pareto dominance in one run.

Personalization algorithms can then be employed to choose from these stories the ones most suitable for each individual user, based on the semantics of the stories and information within the user profile.

The layer-3 CC assignment module in the eNB configures one or multiple CCs for each user based on the quality-of-service (QoS) requirements, terminal capability, and CC deployment scenario, etc. Separate RRM blocks such as independent link adaption, packet scheduling, and hybrid automatic repeat request (HARQ) operate independently on each CC in coherence with LTE Rel'8 assumptions [5].

A threshold is set for each user based on the variability of his latency signatures.

This can be expressed as follows: begin{aligned} P(f_{1}...f_{k})= P u P(f_{1}...f_{k}|u) + P u')P(f_{1}...f_{k}|u'), end{aligned}where (P(f_{1}...f_{k}|u')) denotes the probability of being an adversary (i.e., non-user) based on the response features.

Each antipsychotic medication user was 1 1 matched with a non-user based on the HDPS score within 0.2 standard deviations and on maternal age at delivery within 3 years.