2,428 research outputs found
The Rent Adjustment Process and the Structural Vacancy Rate in the Commercial Real Estate Market
Existing studies of the office-rent adjustment process employ empirical model specifications that assume an intertemporally constant structural vacancy rate. Such specifications, however, contradict prevailing theoretical definitions of the latter which point towards its intertemporal variability. Against this background, this study extends the traditional rent adjustment specifications to account for an intertemporal variable structural vacancy rate. The empirical results suggest that the extended model may be more appropriate than the traditional one in explaining office rent changes during the period 1980-1988. They also suggest that the structural vacancy rate may indeed vary both through time and across markets.
Depth Superresolution using Motion Adaptive Regularization
Spatial resolution of depth sensors is often significantly lower compared to
that of conventional optical cameras. Recent work has explored the idea of
improving the resolution of depth using higher resolution intensity as a side
information. In this paper, we demonstrate that further incorporating temporal
information in videos can significantly improve the results. In particular, we
propose a novel approach that improves depth resolution, exploiting the
space-time redundancy in the depth and intensity using motion-adaptive low-rank
regularization. Experiments confirm that the proposed approach substantially
improves the quality of the estimated high-resolution depth. Our approach can
be a first component in systems using vision techniques that rely on high
resolution depth information
Partitioning of Distributed MIMO Systems based on Overhead Considerations
Distributed-Multiple Input Multiple Output (DMIMO) networks is a promising
enabler to address the challenges of high traffic demand in future wireless
networks. A limiting factor that is directly related to the performance of
these systems is the overhead signaling required for distributing data and
control information among the network elements. In this paper, the concept of
orthogonal partitioning is extended to D-MIMO networks employing joint
multi-user beamforming, aiming to maximize the effective sum-rate, i.e., the
actual transmitted information data. Furthermore, in order to comply with
practical requirements, the overhead subframe size is considered to be
constrained. In this context, a novel formulation of constrained orthogonal
partitioning is introduced as an elegant Knapsack optimization problem, which
allows the derivation of quick and accurate solutions. Several numerical
results give insight into the capabilities of D-MIMO networks and the actual
sum-rate scaling under overhead constraints.Comment: IEEE Wireless Communications Letter
- …