A novel neural-based model for acoustic-articulatory inversion mapping

In this paper, a new bidirectional neural network for better acoustic-articulatory inversion mapping is proposed. The model is motivated by the parallel structure of human brain, processing information by having forward--reverse connections. In other words, there would be a feedback from articulatory system to the acoustic signals emitted from that organ. Inspired by this mechanism, a new bidirectional model is developed to map speech representations to articulatory features. Formation of attractor dynamics in such bidirectional model is first carried out by training the reference speaker subspace as the continuous attractor. Then, it is used to recognize the other speaker’s speech. In fact, the structure and training of this bidirectional model is designed in such a way that the network learns to denoise the signal step by step, using properties of attractors it has formed. In this work, the efficiency of a nonlinear feedforward network is compared to the same one with a bidirectional connection. The bidirectional model increases the accuracy up to approximately 3% (from 62.09 to 64.91%) in the phone recognition process.     

Characterization of Tribological and Mechanical Properties of the Si3N4 Coating Fabricated by Duplex Surface Treatment of Pack Siliconizing and Plasma Nitriding on AISI D2 Tool Steel

Silicon nitride (Si₃N₄) coating was deposited on AISI D2 tool steel through employing duplex surface treatments—pack siliconizing followed by plasma nitriding. Pack cementation was performed at 650 °C, 800 °C, and 950 °C for 2 and 3 hours by using various mixtures to realize the silicon coating. X-ray diffraction analyses and scanning electron microscopy observations were employed for demonstrating the optimal process conditions leading to high coating adhesion, uniform thickness, and composition. The optimized conditions belonging to siliconizing were employed to produce samples to be further processed via plasma nitriding. This treatment was performed with a gas mixture of 75 pct H₂-25 pct N₂, at the temperature of 550 °C for 7 hours. The results showed that different nitride phases such as Si₃N₄-β, Si₃N₄-γ, Fe₄N, and Fe₃N can be recognized as coatings reinforcements. It was demonstrated that the described composite coating procedure allowed to obtain a remarkable increase in hardness (80 pct higher with respect to the substrate) and wear resistance (30 pct decrease of weight loss) of the tool steel.

     

Challenges and alternatives for unmanned underwater vehicular research in the Amazon basin: Towards a more sustainable management of water resources and the environment

The Amazon basin is one of the largest hydrographic systems in the world, possessing a great diversity of natural resources in need of more sustainable water and environmental management. However, as much of what lies beneath the surface of Amazonian waters is still unexplored, underwater exploration technologies are seen as a means of research and monitoring. The present work therefore aims to answer two research questions: What are the current technologies that could be implemented for unmanned underwater research in the Amazon waters? What are the main limitations and existing alternatives for using unmanned underwater vehicles in the rivers of this region to provide more sustainable water and environment management? Our results demonstrate that remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) are possible options in the short and long terms, respectively. The main challenges in implementing these technologies are related to the variations in hydraulic geometry, current velocities and turbidity of the rivers, as well as the preservation of the region's biodiversity. This research can be taken as a starting point for planners and decision makers seeking more sustainable underwater and environmental exploration of the Amazon river system.     

Characterization of motion power loss of off-road wheeled robot in a slippery terrain

For the first time in realm of power study of off-road wheeled robots, this study deals with motion power loss due to slippage of robot wheels traversed on slippery terrain. For this purpose, effects of slippery terrain type (solid balls with diameter of 0.0127, 0.0254, and 0.0508 m), tire air pressure (20.68, 34.47, and 55.16 kPa), and robot forward speed (0.17, 0.33, and 0.5 m/s) on the power loss were characterized. Derived results proved that the increasing effect of slippery terrain type on the power loss was dominant (1.08 and 3.21 times) than that of robot forward speed and tire air pressure, respectively. Meanwhile, the increasing effect of robot forward speed on the power loss was prevailed (2.98 times) than that of tire air pressure. Hence, to minimize the power loss of the robot traversed on each type of slippery terrain, adjustment of robot forward speed should be considered as first priority. A comparison between motion power loss (43.60–249.40 W) and provided motion power for the robot (136–436.37 W) implies that 12.93–75.44% of provided motion power was wasted by slippage of the robot wheels on slippery terrains. Overall, the analytical results obtained in this study lead to open a new prospection for comprehending of the power loss trends of off-road wheeled robots traversed on slippery terrains. As slippery terrain composed of solid balls, the results can be especially utilized for final phase of unloading robotic operations of catalyst handling procedure in process towers and reactors of oil, gas, petrochemical, and chemical industries.     

Distributed fault detection and isolation in time-varying formation tracking UAV multi-agent systems

The problem of distributed fault detection and isolation (DFDI) in conjunction with time-varying formation control of unmanned aerial vehicle (UAV) multi-agent systems with multiple-leader leader–follower structure is studied, in this paper. It is assumed that the communication data of the agents are noisy, and faults may occur in either leaders or followers. The followers are not aware of the main trajectory and just follow the leaders. The first step in this paper is to reduce the communication noise. Besides, if a fault occurs in one of the leaders causing to exit the leader from the main trajectory, the followers should be able to detect the fault, isolate the leader, use the other leaders' data, and keep the main trajectory. Tracking the trajectory by followers in such a case is the second step of this paper. Preserving the time-varying formation despite a fault occurring in one of the followers is the next step. To reach these goals, a distributed array of Kalman filters is used for noise cancellation and data extraction. Next, the combination of state vector data fusion and some type of $\chi$² test are employed for DFDI, in agents. Besides, a controller is implemented in each agent for formation tracking. In this controller, estimated relative position and velocity vectors of the agents are employed to keep the time varying formation while tracking the leaders. The closed-loop stability is studied via Lyapunov stability theorem, and various simulations are carried out to demonstrate the capability of the proposed strategy.     

Comment on S. Ahmed,H. Wang,and Y. Tian, “Robust adaptive fractional-order terminal sliding mode control for lower-limb exoskeleton,” Asian J. Control,vol. 21, no. 1, pp. 1–10 (2019)

In this comment, it is shown that there are some non-negligible big mistakes in the analyses and stability proof of the proposed controller in the quoted paper, which makes the main results of this paper to be incorrect. The main unavoidable mistakes in the stability analysis of the main theorem (Theorem 1) are stated and some remarks are also mentioned to fix some of them.     

Zinc-based metal-organic frameworks: synthesis and recent progress in biomedical application

Journal of Inorganic and Organometallic Polymers and Materials - This review based on Zn-based MOF is summarized on new insights for targeted drug delivery of medicinal compounds and developed for...     

Effects of molecular weight,stereo configuration of PLA,and processing on the dispersion of multiwalled carbon nanotubes and properties of corresponding nanocomposites

Multiwalled carbon nanotubes (MWCNTs) were dispersed and distributed via a co-rotating twin-screw extruder (TSE) in high (h)- and low (l)-molecular-weight amorphous and semicrystalline polylactides (PLAs) (aPLA and scPLA, respectively). Effects of PLA molecular weight and D-lactic acid equivalents content (D-content), as well as processing parameters, were examined on the MWCNT dispersion quality in PLA. The effectiveness of the MWCNT dispersion in various PLA matrices was investigated using scanning electron microscopy (SEM) and small-amplitude oscillatory and transient shear flow rheometry in the molten state. The results showed a better dispersion of MWCNTs in the low-molecular-weight PLA grades (aPLAl and scPLAl). In addition, better MWCNT dispersion was observed in aPLA grades when processed at a higher temperature of 190°C than at 150°C. At 150°C, while MWCNT bundles in aPLAl could be broken down, a good dispersion could not be achieved in aPLAh due to the lower molecular mobility at such a temperature. The electrical conductivity of the samples was also shown to increase as the MWCNT dispersion was improved. The existence of crystallites in scPLA-based nanocomposites, however, disrupted the connectivity of the MWCNTs and decreased the final electrical conductivity. The lower molecular weight aPLAl prepared at 190°C showed the highest electrical conductivity (~10⁻⁵ S/m) at a low loading of 0.5 wt.% MWCNTs.     

Phenol biodegradation in a bioreactor considering different geometries and process parameters

In this study, a three-dimensional coupled lattice Boltzmann model and cellular automata platform was developed to simulate biofilm growth and phenol biodegradation as an effective and sustainable way to remove phenolic contaminants in aquatic systems. Two three-dimensional bioreactors with cubic or spherical obstacles at varying inlet phenol concentrations and flow velocities were examined. The results showed that the cubic-bioreactor had higher phenol reduction than the spheric-bioreactor due to the greater effects of cubic obstacles on flow patterns. The biofilm concentration in bioreactors decreased up to 36.4% as inlet velocity increased and in the spheric-bioreactor at the same inlet phenol concentration. The cubic-bioreactor had the highest normalized reduction rate of 1.194 at the lowest inlet phenol concentration, while the spheric-bioreactor had the lowest one of 0.871 at the highest inlet phenol concentration. The results proved the accuracy of the model to assess the performance of wastewater treatment bioreactors under different conditions.