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 $\chi^2$ related to the mass of the associated jets, is constructed, and the best jet combination is found by minimising this $\chi^2$. As this process suffers from combinatorial explosion with the number of jets, the number of permutations is limited by using only the $n$ highest $p_T$ 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 $t\bar{t}$ 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