ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents

Robots have been successfully used to perform tasks with high precision. In real-world environments with sparse rewards and multiple goals, learning is still a major challenge and Reinforcement Learning (RL) algorithms fail to learn good policies. Training in simulation environments and then fine-tuning in the real world is a common approach. However, adapting to the real-world setting is a challenge. In this paper, we present a method named Ready for Production Hierarchical RL (ReProHRL) that divides tasks with hierarchical multi-goal navigation guided by reinforcement learning. We also use object detectors as a pre-processing step to learn multi-goal navigation and transfer it to the real world. Empirical results show that the proposed ReProHRL method outperforms the state-of-the-art baseline in simulation and real-world environments in terms of both training time and performance. Although both methods achieve a 100% success rate in a simple environment for single goal-based navigation, in a more complex environment and multi-goal setting, the proposed method outperforms the baseline by 18% and 5%, respectively. For the real-world implementation and proof of concept demonstration, we deploy the proposed method on a nano-drone named Crazyflie with a front camera to perform multi-goal navigation experiments.Comment: AAAI 2023 RL Ready for Production Worksho

Epidemiology of familial multiple sclerosis in Iran: a national registry-based study

Background Admittedly, little is known about the epidemiological signatures of familial multiple sclerosis (FMS) in different geographical regions of Iran. Objective To determine the epidemiology and the risk of FMS incidence in several provinces of Iran with a different ethnic population including, Fars, Tehran, Isfahan (Persians), and Mazandaran (Mazanis), Kermanshah (Kurds), and Chaharmahal and Bakhtiari (Lors). Methods This cross-sectional registry-based study was performed on nationwide MS registry of Iran (NMSRI) data collected from 2018 to 2021. This system, registers baseline characteristics, clinical presentations and symptoms, diagnostic and treatments at regional and national levels. Results A total of 9200 patients including, 7003 (76.1%) female and 2197 (23.9%) male, were participated. About 19% of patients reported a family history of MS; the order from highest to lowest FMS prevalence was as follows: Fars (26.5%), Chaharmahal and Bakhtiari (21.1%), Tehran (20.5%), Isfahan (20.3%), Mazandaran (18.0%), and Kermanshah (12.5%). Of all FMS cases, 74.7% (1308 cases) were female and 25.3% (442 cases) were male. FMS occurrence was much more common in females than males (P-value = 0.001). Further, the mean age at onset was 30 years among FMS cases. A substantially higher probability of relapsing-remitting MS and secondary-progressive MS was found among FMS cases than sporadic MS (SMS) (P_value = 0.001). There was no significant difference in Expanded Disability Status Scale (EDSS) scores between FMS and SMS. The majority of FMS cases were observed among first-degree relatives, with the highest rate in siblings. There was a significant association between MS risk and positive familial history in both maternal and paternal aunt/uncle (P_value = 0.043 and P_value = 0.019, respectively). Multiple sclerosis occurrence among offspring of females was higher than males (P_value = 0.027). Conclusions In summary, our findings imply a noteworthy upward trend of FMS in Iran, even more than the global prevalence, which suggests a unique Atlas of FMS prevalence in this multi-ethnic population. Despite the highest rate of FMS within Persian and Lor ethnicities, no statistically significant difference was observed among the provinces

Optimization Shape of Variable Capacitance Micromotor Using Differential Evolution Algorithm

A new method for optimum shape design of variable capacitance micromotor (VCM) using Differential Evolution (DE), a stochastic search algorithm, is presented. In this optimization exercise, the objective function aims to maximize torque value and minimize the torque ripple, where the geometric parameters are considered to be the variables. The optimization process is carried out using a combination of DE algorithm and FEM analysis. Fitness value is calculated by FEM analysis using COMSOL3.4, and the DE algorithm is realized by MATLAB7.4. The proposed method is applied to a VCM with 8 poles at the stator and 6 poles at the rotor. The results show that the optimized micromotor using DE algorithm had higher torque value and lower torque ripple, indicating the validity of this methodology for VCM design

Measuring the effect of an ongoing urbanization process on biodiversity conservation suitability index: integrating scenario-based urban growth modelling with Conservation Assessment and Prioritization System (CAPS)

The present study adopts an integrative modelling methodology, which combines the strengths of the SLEUTH model and the Conservation Assessment and Prioritization System (CAPS) method. By developing a scenario-based geographic information system simulation environment for Hashtpar City, Iran, the manageability of the landscape under each urban growth scenario is analysed. In addition, the CAPS approach was used for biodiversity conservation suitability mapping. The SLEUTH model was implemented to generate predictive urban layers of the years 2020, 2030, 2040 and 2050 for each scenario (dynamic factors for conservation suitability mapping). Accordingly, conservation suitability surface of the area is updated for each time point and under each urban development storyline. Two-way analysis of variance and Duncan’s new multiple range tests were employed to compare the functionality of the three scenarios. Based on results, the managed urban growth scenario depicted better results for manageability of the landscape and less negative impact on conservation suitability values

An attitude study on the environmental effects of rationing petrol in Tehran

The objective of this study is to assess the environmental effects of implementing petrol rationing and the issuance of fuel smartcards in central Tehran. The results and their application are significant from the perspective of preserving fuel sources and protecting the environment, both of which being among the goals of sustainable development. Through the analysis of soft data (owners of automobile and light pickup trucks attitude), 3 general hypotheses were assessed and the result was compared to hard data (the traffic situation information, petrol consumption and air pollution). The soft data was gathered using a comprehensive questionnaire which randomly distributed among 2000 automobile and pickup truck drivers in the central Tehran area who were at petrol stations to refuel their vehicles. The gathered data was then analyzed at two levels: descriptive and inferential. The results of this research reveal that according to the soft data, the smartcard project has resulted in a decline in traffic and petrol consumption and a rise in air pollution; furthermore, the positive cultural effects of this project have been comparatively prominent. The actual figures show that the project has led to lower traffic load and air pollution but petrol consumption remains the same as before.Fuel smartcards Attitude study Environmental effect

Peak-Power Aware Lifetime Reliability Improvement in Fault-Tolerant Mixed-Criticality Systems

Mixed-Criticality Systems (MCSs) include tasks with multiple levels of criticality and different modes of operation. These systems bring benefits such as energy and resource saving while ensuring safe operation. However, management of available resources in order to achieve high utilization, low power consumption, and required reliability level is challenging in MCSs. In many cases, there is a trade-off between these goals. For instance, although using fault-tolerance techniques, such as replication, leads to improving the timing reliability, it increases power consumption and can threaten life-time reliability. In this work, we introduce an approach named Life−timePeakPower management inMixed−Criticalitysystems (LPP-MC) to guarantee reliability, along with peak power reduction. This approach maps the tasks using a novel metric called Reliability-Power Metric (RPM). The LPP-MC approach uses this metric to balance the power consumption of different processor cores and to improve the life-time of a chip. Moreover, to guarantee the timing reliability of MCSs, a fault-tolerance technique, called task re-execution, is utilized in this approach. We evaluate the proposed approach by a real avionics task set, and various synthetic task sets. The experimental results show that the proposed approach mitigates the aging rate and reduces peak power by up to 20.6% and 17.6%, respectively, compared to state-of-the-art