263 research outputs found
2D Proactive Uplink Resource Allocation Algorithm for Event Based MTC Applications
We propose a two dimension (2D) proactive uplink resource allocation
(2D-PURA) algorithm that aims to reduce the delay/latency in event-based
machine-type communications (MTC) applications. Specifically, when an event of
interest occurs at a device, it tends to spread to the neighboring devices.
Consequently, when a device has data to send to the base station (BS), its
neighbors later are highly likely to transmit. Thus, we propose to cluster
devices in the neighborhood around the event, also referred to as the
disturbance region, into rings based on the distance from the original event.
To reduce the uplink latency, we then proactively allocate resources for these
rings. To evaluate the proposed algorithm, we analytically derive the mean
uplink delay, the proportion of resource conservation due to successful
allocations, and the proportion of uplink resource wastage due to unsuccessful
allocations for 2D-PURA algorithm. Numerical results demonstrate that the
proposed method can save over 16.5 and 27 percent of mean uplink delay,
compared with the 1D algorithm and the standard method, respectively.Comment: 6 pages, 6 figures, Published in 2018 IEEE Wireless Communications
and Networking Conference (WCNC
A profiling analysis of contributions of cigarette smoking, dietary calcium intakes, and physical activity to fragility fracture in the elderly
Fragility fracture and bone mineral density (BMD) are influenced by common and modifiable lifestyle factors. In this study, we sought to define the contribution of lifestyle factors to fracture risk by using a profiling approach. The study involved 1683 women and 1010 men (50+ years old, followed up for up to 20 years). The incidence of new fractures was ascertained by X-ray reports. A “lifestyle risk score” (LRS) was derived as the weighted sum of effects of dietary calcium intake, physical activity index, and cigarette smoking. Each individual had a unique LRS, with higher scores being associated with a healthier lifestyle. Baseline values of lifestyle factors were assessed. In either men or women, individuals with a fracture had a significantly lower age-adjusted LRS than those without a fracture. In men, each unit lower in LRS was associated with a 66% increase in the risk of total fracture (non-adjusted hazard ratio [HR] 1.66; 95% CI, 1.26 to 2.20) and still significant after adjusting for age, weight or BMD. However, in women, the association was uncertain (HR 1.30; 95% CI, 1.11 to 1.53). These data suggest that unhealthy lifestyle habits are associated with an increased risk of fracture in men, but not in women, and that the association is mediated by BMD
HR orientations and HR department effectiveness in Vietnam
Purpose
Human resource (HR) philosophy and an organization’s commitment to employees (OCE) are important components of a human resource management (HRM) system, yet the influences of these variables on the effectiveness of HRM implementation has been less evident. Similarly, few studies have examined the effect of intended and implemented HR practices on line managers’ perceptions of HR department effectiveness. The purpose of this paper is to examine how these factors could result in a positive evaluation of HR department effectiveness in Vietnam. Design/methodology/approach
Study 1 consisted of 405 line managers and the authors used this sample to test the proposed research model. Study 2, comprising 192 line managers, was used to validate the findings from Study 1. Findings
The authors found empirical evidence of how HR managers should leverage their relationships with line managers to enhance HR department effectiveness in a developing economy such as Vietnam. Research limitations/implications
As data were from line managers in one point in time, this study could be affected by common method bias. However, the authors conducted three common method variance checks and the analyses showed that this issue was not a major concern. Future studies could extend the sample of respondents by collecting information from CEOs, employees, and HR managers. Originality/value
This study contributes to the extant literature empirical evidence of determinants of HR department effectiveness. First, the study shows the simultaneous impacts of HR philosophy and OCE on the actual implementation of HR practices. Second, the authors provide an understanding of line managers’ evaluation of HR department effectiveness through their experience with implemented HR practices
When Virtual Reality Meets Rate Splitting Multiple Access: A Joint Communication and Computation Approach
Rate Splitting Multiple Access (RSMA) has emerged as an effective
interference management scheme for applications that require high data rates.
Although RSMA has shown advantages in rate enhancement and spectral efficiency,
it has yet not to be ready for latency-sensitive applications such as virtual
reality streaming, which is an essential building block of future 6G networks.
Unlike conventional High-Definition streaming applications, streaming virtual
reality applications requires not only stringent latency requirements but also
the computation capability of the transmitter to quickly respond to dynamic
users' demands. Thus, conventional RSMA approaches usually fail to address the
challenges caused by computational demands at the transmitter, let alone the
dynamic nature of the virtual reality streaming applications. To overcome the
aforementioned challenges, we first formulate the virtual reality streaming
problem assisted by RSMA as a joint communication and computation optimization
problem. A novel multicast approach is then proposed to cluster users into
different groups based on a Field-of-View metric and transmit multicast streams
in a hierarchical manner. After that, we propose a deep reinforcement learning
approach to obtain the solution for the optimization problem. Extensive
simulations show that our framework can achieve the millisecond-latency
requirement, which is much lower than other baseline schemes
Toward BCI-enabled Metaverse: A Joint Learning and Resource Allocation Approach
Toward user-driven Metaverse applications with fast wireless connectivity and
tremendous computing demand through future 6G infrastructures, we propose a
Brain-Computer Interface (BCI) enabled framework that paves the way for the
creation of intelligent human-like avatars. Our approach takes a first step
toward the Metaverse systems in which the digital avatars are envisioned to be
more intelligent by collecting and analyzing brain signals through cellular
networks. In our proposed system, Metaverse users experience Metaverse
applications while sending their brain signals via uplink wireless channels in
order to create intelligent human-like avatars at the base station. As such,
the digital avatars can not only give useful recommendations for the users but
also enable the system to create user-driven applications. Our proposed
framework involves a mixed decision-making and classification problem in which
the base station has to allocate its computing and radio resources to the users
and classify the brain signals of users in an efficient manner. To this end, we
propose a hybrid training algorithm that utilizes recent advances in deep
reinforcement learning to address the problem. Specifically, our hybrid
training algorithm contains three deep neural networks cooperating with each
other to enable better realization of the mixed decision-making and
classification problem. Simulation results show that our proposed framework can
jointly address resource allocation for the system and classify brain signals
of the users with highly accurate predictions
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