DESIGNING HEDGE ALGEBRAIC CONTROLLER AND OPTIMIZING BY GENETIC ALGORITHM FOR SERIAL ROBOTS ADHERING TRAJECTORIES

In recent years, the application of hedge algebras in the field of control has been studied. The results show that this approach has many advantages. In additions, industrial robots are being well-developed and extensively used, especially in the industrial revolution 4.0. Accurate control of industrial robots is a class of problems that many scientists are interested in. In this paper, we design a controller based on hedge algebra for serial robots. The control rule is given by linguistic rule base system. The goal is to accurately control the moving robot arm which adheres given trajectories. Optimization of fuzzy parameters for the controller is done by genetic algorithms. The system has been simulated on the Matlab-Simulink software. The simulation results show that the orbital deviation is very small. Moreover, the controller worked well with correct control quality. This result once presents the simplicity and efficiency of the hedge algebras approach to control

Wind induced vibration of stay cable bridge evaluation based on the operational accelerometers monitoring data and field testing

Wind induced vibrations are considering as one of the major concerns of the owner, the engineers and contractors of stay cable bridges. This paper presents in premier lieu the assessment of the vibration monitoring data from the pre-installed accelerometers on the longest cables of the Bach Dang bridge, Quang Ninh province. The identified cables natural frequencies based on the ambient vibration monitoring data were then compared to the taut string vibrating model calculation based on lift-off tension forces showing a good concordant. The enhanced damping of the cables stayed were then estimated and compared to the damping test results of another stay cables bridge recently performed in Vietnam with similar range of cables length. The damping prediction are quite in line with the damping test results and comparable also to those given in most of International Standard for stay cable. Finally, the identified natural frequencies and predicted intrinsic damping were used for an assessment of the wind induced vibration instability including the wind/rain induced vibration, wake galloping and vortex excitation

EU-VIETNAM FREE TRADE AGREEMENT (EVFTA) AND VIETNAM AGRICULTURAL PRODUCTS EXPORT: OPPORTUNITIES AND CHALLENGES

EVFTA is a newly generated free trade agreement with the highest level of commitment that a partner has for Vietnam among the FTAs ​​ signed. Regarding agricultural products, which are Vietnam's strengths, the EVFTA's commitments bring opportunities to expand and diversify export markets; increase exports and promote the improvement of agricultural product quality. In order to meet the strict requirements of the EU, stakeholders including the Government, production facilities, and exporters of Vietnamese agricultural products must take advantage of opportunities and overcome challenges as a result of the EVFTA. By analyzing opportunities and challenges, the article proposes some solutions to take advantage of opportunities and remove difficulties in exporting Vietnamese agricultural products to the EU

AweGNN: Auto-parametrized weighted element-specific graph neural networks for molecules.

While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data representations via advanced mathematics, including algebraic topology, differential geometry, and graph theory, have demonstrated superiority in a variety of biomolecular applications, however, their performance is often dependent on manual parametrization. This work introduces the auto-parametrized weighted element-specific graph neural network, dubbed AweGNN, to overcome the obstacle of this tedious parametrization process while also being a suitable technique for automated feature extraction on these internally complex biomolecular data sets. The AweGNN is a neural network model based on geometric-graph features of element-pair interactions, with its graph parameters being updated throughout the training, which results in what we call a network-enabled automatic representation (NEAR). To enhance the predictions with small data sets, we construct multi-task (MT) AweGNN models in addition to single-task (ST) AweGNN models. The proposed methods are applied to various benchmark data sets, including four data sets for quantitative toxicity analysis and another data set for solvation prediction. Extensive numerical tests show that AweGNN models can achieve state-of-the-art performance in molecular property predictions

Earnings Expectations and the Quality of Financial Services

Using complaint data filed by consumers with the Consumer Financial Protection Bureau against financial institutions, we show that banks receive, on average, 13.3% more customer complaints in the quarter immediately after they narrowly beat analysts’ earnings forecasts. The effect is mainly driven by banks’ attempts to reduce their non-interest expenses to beat earnings benchmarks. The relationship is stronger when bank CEOs receive a greater proportion of incentive-based compensation. Overall, our

Proximity to bank headquarters and branch efficiency : evidence from mortgage lending

We use the staggered introduction of new flight routes to identify reductions in travel time between banks’ headquarters and branches to examine their effects on branch outputs and efficiency. Reductions in headquarters-branch travel time increases branch-level mortgage origination volume, and these loans exhibit higher ex-post performance. Further analyses suggest these effects are due to branch employees working harder and more efficiently in seeking new customers, and screening applications. Overall, our results suggest that geographic proximity enables bank headquarters to monitor branches more effectively and mitigate distance-related agency costs.Peer reviewe