10,099 research outputs found
Overview of methods to analyse dynamic data
This book gives an overview of existing data analysis methods to analyse the dynamic data obtained from full scale testing, with their advantages and drawbacks. The overview of full scale testing and dynamic data analysis is limited to energy performance characterization of either building components or whole buildings.
The methods range from averaging and regression methods to dynamic approaches based on system identification techniques. These methods are discussed in relation to their application in following in situ measurements:
-measurement of thermal transmittance of building components based on heat flux meters;
-measurement of thermal and solar transmittance of building components tested in outdoor calorimetric test cells;
-measurement of heat transfer coefficient and solar aperture of whole buildings based on co-heating or transient heating tests;
-characterisation of the energy performance of whole buildings based on energy use monitoring
A collective, probabilistic approach to schema mapping using diverse noisy evidence
We propose a probabilistic approach to the problem of schema mapping. Our approach is declarative, scalable, and extensible. It builds upon recent results in both schema mapping and probabilistic reasoning and contributes novel techniques in both fields. We introduce the problem of schema mapping selection, that is, choosing the best mapping from a space of potential mappings, given both metadata constraints and a data example. As selection has to reason holistically about the inputs and the dependencies between the chosen mappings, we define a new schema mapping optimization problem which captures interactions between mappings as well as inconsistencies and incompleteness in the input. We then introduce Collective Mapping Discovery (CMD), our solution to this problem using state-of-the-art probabilistic reasoning techniques. Our evaluation on a wide range of integration scenarios, including several real-world domains, demonstrates that CMD effectively combines data and metadata information to infer highly accurate mappings even with significant levels of noise
Interpretable Probabilistic Password Strength Meters via Deep Learning
Probabilistic password strength meters have been proved to be the most
accurate tools to measure password strength. Unfortunately, by construction,
they are limited to solely produce an opaque security estimation that fails to
fully support the user during the password composition. In the present work, we
move the first steps towards cracking the intelligibility barrier of this
compelling class of meters. We show that probabilistic password meters
inherently own the capability of describing the latent relation occurring
between password strength and password structure. In our approach, the security
contribution of each character composing a password is disentangled and used to
provide explicit fine-grained feedback for the user. Furthermore, unlike
existing heuristic constructions, our method is free from any human bias, and,
more importantly, its feedback has a clear probabilistic interpretation. In our
contribution: (1) we formulate the theoretical foundations of interpretable
probabilistic password strength meters; (2) we describe how they can be
implemented via an efficient and lightweight deep learning framework suitable
for client-side operability.Comment: An abridged version of this paper appears in the proceedings of the
25th European Symposium on Research in Computer Security (ESORICS) 202
Operational Effectiveness in Use fo BAS
The effectiveness of BAS in controlling building
systems is seen to reside in conjoint man machine
function. In an emerging industry paradigm, data is
extracted from the BAS and used for analytics that
inform enhanced operations. This processing may
include a mash up with data from other sources,
such as energy meters. KPI metrics and Building ReTuning, an on going commissioning process, are
suggested as important ways to guide operators in
training and subsequent understanding and use of
data intensive tools. Short case studies of work in
progress on two CUNY campuses are provided
Link-level simulator for 5G localization
Channel-state-information-based localization in 5G networks has been a
promising way to obtain highly accurate positions compared to previous
communication networks. However, there is no unified and effective platform to
support the research on 5G localization algorithms. This paper releases a
link-level simulator for 5G localization, which can depict realistic physical
behaviors of the 5G positioning signal transmission. Specifically, we first
develop a simulation architecture considering more elaborate parameter
configuration and physical-layer processing. The architecture supports the link
modeling at sub-6GHz and millimeter-wave (mmWave) frequency bands.
Subsequently, the critical physical-layer components that determine the
localization performance are designed and integrated. In particular, a
lightweight new-radio channel model and hardware impairment functions that
significantly limit the parameter estimation accuracy are developed. Finally,
we present three application cases to evaluate the simulator, i.e.
two-dimensional mobile terminal localization, mmWave beam sweeping, and
beamforming-based angle estimation. The numerical results in the application
cases present the performance diversity of localization algorithms in various
impairment conditions
A flexible flight display research system using a ground-based interactive graphics terminal
Requirements and research areas for the air transportation system of the 1980 to 1990's were reviewed briefly to establish the need for a flexible flight display generation research tool. Specific display capabilities required by aeronautical researchers are listed and a conceptual system for providing these capabilities is described. The conceptual system uses a ground-based interactive graphics terminal driven by real-time radar and telemetry data to generate dynamic, experimental flight displays. These displays are scan converted to television format, processed, and transmitted to the cockpits of evaluation aircraft. The attendant advantages of a Flight Display Research System (FDRS) designed to employ this concept are presented. The detailed implementation of an FDRS is described. The basic characteristics of the interactive graphics terminal and supporting display electronic subsystems are presented and the resulting system capability is summarized. Finally, the system status and utilization are reviewed
UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low vision
Vision-based localization approaches now underpin newly emerging navigation
pipelines for myriad use cases from robotics to assistive technologies.
Compared to sensor-based solutions, vision-based localization does not require
pre-installed sensor infrastructure, which is costly, time-consuming, and/or
often infeasible at scale. Herein, we propose a novel vision-based localization
pipeline for a specific use case: navigation support for end-users with
blindness and low vision. Given a query image taken by an end-user on a mobile
application, the pipeline leverages a visual place recognition (VPR) algorithm
to find similar images in a reference image database of the target space. The
geolocations of these similar images are utilized in downstream tasks that
employ a weighted-average method to estimate the end-user's location and a
perspective-n-point (PnP) algorithm to estimate the end-user's direction.
Additionally, this system implements Dijkstra's algorithm to calculate a
shortest path based on a navigable map that includes trip origin and
destination. The topometric map used for localization and navigation is built
using a customized graphical user interface that projects a 3D reconstructed
sparse map, built from a sequence of images, to the corresponding a priori 2D
floor plan. Sequential images used for map construction can be collected in a
pre-mapping step or scavenged through public databases/citizen science. The
end-to-end system can be installed on any internet-accessible device with a
camera that hosts a custom mobile application. For evaluation purposes, mapping
and localization were tested in a complex hospital environment. The evaluation
results demonstrate that our system can achieve localization with an average
error of less than 1 meter without knowledge of the camera's intrinsic
parameters, such as focal length
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