Comparative Study of Different Methods in Vibration-Based Terrain Classification for Wheeled Robots with Shock Absorbers

open access articleAutonomous robots that operate in the field can enhance their security and efficiency by accurate terrain classification, which can be realized by means of robot-terrain interaction-generated vibration signals. In this paper, we explore the vibration-based terrain classification (VTC), in particular for a wheeled robot with shock absorbers. Because the vibration sensors are usually mounted on the main body of the robot, the vibration signals are dampened significantly, which results in the vibration signals collected on different terrains being more difficult to discriminate. Hence, the existing VTC methods applied to a robot with shock absorbers may degrade. The contributions are two-fold: (1) Several experiments are conducted to exhibit the performance of the existing feature-engineering and feature-learning classification methods; and (2) According to the long short-term memory (LSTM) network, we propose a one-dimensional convolutional LSTM (1DCL)-based VTC method to learn both spatial and temporal characteristics of the dampened vibration signals. The experiment results demonstrate that: (1) The feature-engineering methods, which are efficient in VTC of the robot without shock absorbers, are not so accurate in our project; meanwhile, the feature-learning methods are better choices; and (2) The 1DCL-based VTC method outperforms the conventional methods with an accuracy of 80.18%, which exceeds the second method (LSTM) by 8.23%

SeACo-Paraformer: A Non-Autoregressive ASR System with Flexible and Effective Hotword Customization Ability

Hotword customization is one of the important issues remained in ASR field - it is of value to enable users of ASR systems to customize names of entities, persons and other phrases. The past few years have seen both implicit and explicit modeling strategies for ASR contextualization developed. While these approaches have performed adequately, they still exhibit certain shortcomings such as instability in effectiveness. In this paper we propose Semantic-augmented Contextual-Paraformer (SeACo-Paraformer) a novel NAR based ASR system with flexible and effective hotword customization ability. It combines the accuracy of the AED-based model, the efficiency of the NAR model, and the excellent performance in contextualization. In 50,000 hours industrial big data experiments, our proposed model outperforms strong baselines in customization and general ASR tasks. Besides, we explore an efficient way to filter large scale incoming hotwords for further improvement. The source codes and industrial models proposed and compared are all opened as well as two hotword test sets.Comment: updated draf

Thoughts and Targeted Initiatives for the Nurturing of Youth Football Reserve Talents in China

In order to strengthen the foundation for the cultivation of Chinese youth football reserve talents, a systematic review of the current ideas on the development of Chinese youth football reserve talents is conducted, and based on this, a targeted response is derived from it. The study concludes that the cultivation of Chinese youth football reserve talents should be based on the country and the world in a hierarchical and directional manner, with emphasis on the integration of the excellent Chinese traditional culture at the primary school level and the absorption of outstanding foreign achievements and experience at the secondary school level, and the promotion of three types of policy tools, namely the supply side, the demand side and the environment side, to form a protective synergy for the cultivation of youth football reserve talents, so as to build an effective and long-term development strategy that will benefit the present and the future. The aim is to speed up the construction of a reserve pool of Chinese youth football talents, improve the international competitiveness and influence of Chinese football, and contribute to the early realisation of the Chinese football dream

Learning Explicit Contact for Implicit Reconstruction of Hand-held Objects from Monocular Images

Reconstructing hand-held objects from monocular RGB images is an appealing yet challenging task. In this task, contacts between hands and objects provide important cues for recovering the 3D geometry of the hand-held objects. Though recent works have employed implicit functions to achieve impressive progress, they ignore formulating contacts in their frameworks, which results in producing less realistic object meshes. In this work, we explore how to model contacts in an explicit way to benefit the implicit reconstruction of hand-held objects. Our method consists of two components: explicit contact prediction and implicit shape reconstruction. In the first part, we propose a new subtask of directly estimating 3D hand-object contacts from a single image. The part-level and vertex-level graph-based transformers are cascaded and jointly learned in a coarse-to-fine manner for more accurate contact probabilities. In the second part, we introduce a novel method to diffuse estimated contact states from the hand mesh surface to nearby 3D space and leverage diffused contact probabilities to construct the implicit neural representation for the manipulated object. Benefiting from estimating the interaction patterns between the hand and the object, our method can reconstruct more realistic object meshes, especially for object parts that are in contact with hands. Extensive experiments on challenging benchmarks show that the proposed method outperforms the current state of the arts by a great margin.Comment: 17 pages, 8 figure

Designing Functional Carriage of High-Speed Medical Train – Systematic Analysis and Evaluation of Tasks, Functions and Flow Routes

This paper proposes a functional carriage design and an evaluation index system to improve the operational efficiency of high-speed medical trains. Hierarchical task analysis and human-machine-environment analysis were applied to model the transfer task and the functional modules of the medical train. The functional module configuration was obtained by performing a correlation analysis between the task and function. The relationship between carriages was elucidated by analysing material, personnel and information flow, and an optimal grouping diagram was obtained. Based on this design method, an innovative 6-carriage grouping design scheme was proposed. A functional evaluation index system for the carriage design was constructed, and the 6-carriage design was compared with the conventional 8-carriage design to verify the usability of the design method. The results showed that the 6-carriage high-speed trains can be flexibly configured to suit the changing task environment and are generally better than the 8-carriage design. This study provides theoretical and methodological support for constructing efficient and rational functional carriages for high-speed medical trains

The glucose metabolite methylglyoxal inhibits expression of the glucose transport genes by inactivating the cell surface glucose sensors Rgt2 and Snf3 in yeast

Methylglyoxal (MG) is a cytotoxic by-product of glycolysis. MG has inhibitory effect on the growth of cells ranging from microorganisms to higher eukaryotes, but its molecular targets are largely unknown. The yeast cell-surface glucose sensors Rgt2 and Snf3 function as glucose receptors that sense extracellular glucose and generate a signal for induction of expression of genes encoding glucose transporters (HXTs). Here we provide evidence that these glucose sensors are primary targets of MG in yeast. MG inhibits the growth of glucose-fermenting yeast cells by inducing endocytosis and degradation of the glucose sensors. However, the glucose sensors with mutations at their putative ubiquitin-acceptor lysine residues are resistant to MG-induced degradation. These results suggest that the glucose sensors are inactivated through ubiquitin-mediated endocytosis and degraded in the presence of MG. In addition, the inhibitory effect of MG on the glucose sensors is greatly enhanced in cells lacking Glo1, a key component of the MG detoxification system. Thus the stability of these glucose sensors seems to be critically regulated by intracellular MG levels. Taken together, these findings suggest that MG attenuates glycolysis by promoting degradation of the cell-surface glucose sensors and thus identify MG as a potential glycolytic inhibitor

Polymer-Based n-Type Yarn for Organic Thermoelectric Textiles

A conjugated-polymer-based n-type yarn for thermoelectric textiles is presented. Thermoelectric textile devices are intriguing power sources for wearable electronic devices. The use of yarns comprising conjugated polymers is desirable because of their potentially superior mechanical properties compared to other thermoelectric materials. While several examples of p-type conducting yarns exist, there is a lack of polymer-based n-type yarns. Here, a regenerated cellulose yarn is spray-coated with an n-type conducting-polymer-based ink composed of poly(benzimidazobenzophenanthroline) (BBL) and poly(ethyleneimine) (PEI). The n-type yarns display a bulk electrical conductivity of 8 7 10−3 S cm−1 and Seebeck coefficient of −79 \ub5V K−1. A promising level of air-stability for at least 13 days can be achieved by applying an additional thermoplastic elastomer coating. A prototype in-plane thermoelectric textile, produced with the developed n-type yarns and p-type yarns, composed of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)-coated regenerated cellulose, displays a stable device performance in air for at least 4 days with an open-circuit voltage per temperature difference of 1\ua0mV\ua0\ub0C−1. Evidently, polymer-based n-type yarns are a viable component for the construction of thermoelectric textile devices

Designing Functional Carriage of High-Speed Medical Train – Systematic Analysis and Evaluation of Tasks, Functions and Flow Routes

This paper proposes a functional carriage design and an evaluation index system to improve the operational efficiency of high-speed medical trains. Hierarchical task analysis and human-machine-environment analysis were applied to model the transfer task and the functional modules of the medical train. The functional module configuration was obtained by performing a correlation analysis between the task and function. The relationship between carriages was elucidated by analysing material, personnel and information flow, and an optimal grouping diagram was obtained. Based on this design method, an innovative 6-carriage grouping design scheme was proposed. A functional evaluation index system for the carriage design was constructed, and the 6-carriage design was compared with the conventional 8-carriage design to verify the usability of the design method. The results showed that the 6-carriage high-speed trains can be flexibly configured to suit the changing task environment and are generally better than the 8-carriage design. This study provides theoretical and methodological support for constructing efficient and rational functional carriages for high-speed medical trains

Highly insulating thermoplastic nanocomposites based on a polyolefin ternary blend for high-voltage direct current power cables

Octyl-silane-coated Al2O3 nanoparticles are found to be a promising conductivity-reducing additive for thermoplastic ternary blends comprising low-density polyethylene (LDPE), isotactic polypropylene and a styrenic copolymer. The ternary blend nanocomposites were prepared by compounding the blend components together with an LDPE-based masterbatch that contained the nanoparticles. The nanoparticles did not affect the superior stiffness of the ternary blends, compared to neat LDPE, between the melting temperatures of the two polyolefins. As a result, ternary blend nanocomposites comprising 38 wt% polypropylene displayed a storage modulus of more than 10 MPa up to at least 150 degrees C, independent of the chosen processing conditions. Moreover, the ternary blend nanocomposites featured a low direct-current electrical conductivity of about 3 x 10(-15) S m(-1) at 70 degrees C and an electric field of 30 kV mm(-1), which could only be achieved through the presence of both polypropylene and Al2O3 nanoparticles. This synergistic conductivity-reducing effect may facilitate the design of more resistive thermoplastic insulation materials for high-voltage direct current (HVDC) power cables