2,963 research outputs found
StRDAN: Synthetic-to-Real Domain Adaptation Network for Vehicle Re-Identification
Vehicle re-identification aims to obtain the same vehicles from vehicle
images. This is challenging but essential for analyzing and predicting traffic
flow in the city. Although deep learning methods have achieved enormous
progress for this task, their large data requirement is a critical shortcoming.
Therefore, we propose a synthetic-to-real domain adaptation network (StRDAN)
framework, which can be trained with inexpensive large-scale synthetic and real
data to improve performance. The StRDAN training method combines domain
adaptation and semi-supervised learning methods and their associated losses.
StRDAN offers significant improvement over the baseline model, which can only
be trained using real data, for VeRi and CityFlow-ReID datasets, achieving 3.1%
and 12.9% improved mean average precision, respectively.Comment: 7 pages, 2 figures, CVPR Workshop Paper (Revised
Are Histrionic Personality Traits Associated with Irritability during Conscious Sedation Endoscopy?
Aim. We aimed to evaluate whether histrionic personality traits are associated with irritability during conscious sedation endoscopy (CSE). Materials and Methods. A prospective cross-sectional study was planned. Irritability during CSE was classified into five grades: 0, no response; I, minimal movement; II, moderate movement; III, severe movement; IV, fighting against procedure. Patients in grades III and IV were defined as the irritable group. Participants were required to complete questionnaire sheet assessing the extent of histrionic personality traits, extraversion-introversion, and current psychological status. The present authors also collected basic sociodemographic data including alcohol use history. Results. A total of 32 irritable patients and 32 stable patients were analyzed. The histrionic personality trait score of the irritable group was higher than that of the stable group (9.5 ± 3.1 versus 6.9 ± 2.9; P = 0.001), as was the anxiety score (52.8 ± 8.6 versus 46.1 ± 9.6; P = 0.004). Heavy alcohol use was more frequently observed in the irritable group (65.6% versus 28.1%; P = 0.003). In multivariate analysis, all these three factors were independently correlated with irritability during CSE. Conclusion. This study revealed that histrionic personality traits, anxiety, and heavy alcohol use can affect irritability during CSE
Zero-Permutation Jet-Parton Assignment using a Self-Attention Network
In high-energy particle physics events it can be useful to find the jets
correlated with the decay of intermediate states, for example the three jets
produced by the hadronic decay of the top quark. Typically, a
goodness-of-association measure, such as a related to the mass of the
associated jets, is constructed, and the best jet combination is found by
minimising this . As this process suffers from combinatorial explosion
with the number of jets, the number of permutations is limited by using only
the highest jets. The self-attention block is a neural network unit
used for the machine translation problem, which can highlight relationships
between any number of inputs in a single iteration without permutations. In
this paper, we introduce the self-attention for jet assignment (SaJa) network.
SaJa can take any number of jets for input, and outputs probabilities of
jet-parton assignment for all jets in a single step. We apply SaJa to find
jet-parton assignments of fully-hadronic events to test the
performance.Comment: Code available from https://github.com/CPLUOS/SaJ
Generating Dispatching Rules for the Interrupting Swap-Allowed Blocking Job Shop Problem Using Graph Neural Network and Reinforcement Learning
The interrupting swap-allowed blocking job shop problem (ISBJSSP) is a
complex scheduling problem that is able to model many manufacturing planning
and logistics applications realistically by addressing both the lack of storage
capacity and unforeseen production interruptions. Subjected to random
disruptions due to machine malfunction or maintenance, industry production
settings often choose to adopt dispatching rules to enable adaptive, real-time
re-scheduling, rather than traditional methods that require costly
re-computation on the new configuration every time the problem condition
changes dynamically. To generate dispatching rules for the ISBJSSP problem, we
introduce a dynamic disjunctive graph formulation characterized by nodes and
edges subjected to continuous deletions and additions. This formulation enables
the training of an adaptive scheduler utilizing graph neural networks and
reinforcement learning. Furthermore, a simulator is developed to simulate
interruption, swapping, and blocking in the ISBJSSP setting. Employing a set of
reported benchmark instances, we conduct a detailed experimental study on
ISBJSSP instances with a range of machine shutdown probabilities to show that
the scheduling policies generated can outperform or are at least as competitive
as existing dispatching rules with predetermined priority. This study shows
that the ISBJSSP, which requires real-time adaptive solutions, can be scheduled
efficiently with the proposed method when production interruptions occur with
random machine shutdowns.Comment: 14 pages, 10 figures. Supplementary Material not include
Forecasts covering one month using a cut-cell model
This paper investigates the impact and potential use of the cut-cell vertical
discretisation for forecasts covering five days and climate simulations. A
first indication of the usefulness of this new method is obtained by a set of
five-day forecasts, covering January 1989 with six forecasts. The model area
was chosen to include much of Asia, the Himalayas and Australia. The cut-cell
model LMZ (Lokal Modell with z-coordinates) provides a much more accurate
representation of mountains on model forecasts than the terrain-following
coordinate used for comparison. Therefore we are in particular interested in
potential forecast improvements in the target area downwind of the Himalayas,
over southeastern China, Korea and Japan. The LMZ has previously been tested
extensively for one-day forecasts on a European area. Following indications of
a reduced temperature error for the short forecasts, this paper investigates
the model error for five days in an area influenced by strong orography. The
forecasts indicated a strong impact of the cut-cell discretisation on forecast
quality. The cut-cell model is available only for an older (2003) version of
the model LM (Lokal Modell). It was compared using a control model differing
by the use of the terrain-following coordinate only. The cut-cell model
improved the precipitation forecasts of this old control model everywhere by a
large margin. An improved, more transferable version of the terrain-following
model LM has been developed since then under the name CLM (Climate version of
the Lokal Modell). The CLM has been used and tested in all climates, while the
LM was used for small areas in higher latitudes. The precipitation forecasts
of the cut-cell model were compared also to the CLM. As the cut-cell model LMZ
did not incorporate the developments for CLM since 2003, the precipitation
forecast of the CLM was not improved in all aspects. However, for the target
area downstream of the Himalayas, the cut-cell model considerably improved the
prediction of the monthly precipitation forecast even in comparison with the
modern CLM version. The cut-cell discretisation seems to improve in particular
the localisation of precipitation, while the improvements leading from LM to
CLM had a positive effect mainly on amplitude
Effect of accumulated vs continuous exercise on excess post-exercise oxygen consumption
Background: A continuous aerobic exercise program is an effective method of improving calorie consumption on the metabolism of skeletal muscle. However, studies report that accumulated exercise of 30 minutes divided into three sessions of 10 minutes is as effective as one continuous exercise session for 30 minutes. As yet, no study has compared the excess post-exercise oxygen consumption associated with accumulated exercise and continuous exercise over these timeframes.
Objective: The primary purpose of this study was to compare the excess post-exercise oxygen consumption associated with performing continuous exercise for 30 minutes and three sessions of accumulated exercise for 10 minutes at the same intensity of 60% VO2max.
Method: Posters about the study were posted on the February 2019 Konkuk university homepage and bulletin board, and a total of 34 college students (males, n=18; females, n=16) volunteered to participate. Using a balanced repeated-measures crossover design, the subjects randomly took two exercises: continuous exercise (1 x 30 minutes) or accumulated exercise (3 x 10 minutes), and the washout period between the two exercises was a week. All exercises were performed using an ergometer at 60% maximal oxygen consumption. Oxygen consumption and heart rate were monitored and measured during exercise and after exercise. Lipid profile and lactate acid were measured at rest, exercise end, exercise end plus 30 minutes, and exercise end plus 60 minutes. IBM SPSS Statistics 23 was used to perform a paired t-test, and the statistically significant difference was set at <.05.
Results: Excess post-exercise oxygen consumption parameters (e.g., total oxygen consumption, total calorie, and summation of heart rate) were higher in accumulated exercise than in continuous exercise (p<.05). No significant difference in the calorie during exercise between CEx and AEx (p = .140). No significant difference was observed in the lipid profile between accumulated exercise and continuous exercise (p>.05). No significant differences were observed at rest, exercise end plus 30 minutes, exercise end plus 60 minutes in lactic acid in the blood (p <.05). However, at exercise end, it was significantly higher in the accumulated exercise (p<.01).
Conclusions: This study confirmed that after equalizing energy expenditure for continuous exercise and accumulated exercise in participants in their 20s, accumulated exercise results in higher excess post-exercise oxygen consumption than continuous exercise. The data suggests that accumulated exercise may be more effective in reducing body fat than continuous exercise for a given amount of energy expenditure. [Ethiop.J. Health Dev. 2020;34(Special issue-3):84-90]
Keywords: Continuous exercise, accumulated exercise, excess post-exercise oxygen consumptio
- …