Application of web embedded system and machine learning in english corpus vocabulary recognition

Built-in applications built on a stand-alone device, TCP / IP network and interconnected are a need for high integration with other systems. The system provided through Web services interconnects service-oriented distributed architecture. The TCP / IP network is widely employed to integrate business applications. This integration is still not provided through the embedded application. The applications connected to the Internet are an especially difficult problem in embedded systems to interpret the sensor data. Real-time sensor function generates a training/classification result for IoT application selected, customized, or data structure design. It has an integrated hardware/software system to achieve the continuous training and real-time data analysis and re-training of Machine Learning (ML) algorithm. World of English native speakers on top of all, this is the database of words that have been separated from the local and non-collection English. It also reported a variety of methods that are used in the English vocabulary recognition system. Please check the study of learners of mediation based on the part of the corpus. Students, in writing, too much-advanced technology and general vocabulary. These students, publicly their discourse in and contributed to the professional corpus of "existence" I mentioned that there is a professional writer, is better. To stimulate the different means of integration, it evaluated several network technology today, discussing the balance between the use of shared with this integration in the adaptability and built-in the field of Web network technology of today.     

Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

Longitudinal permeability determination of dual-scale fibrous materials

In this work, the longitudinal permeability of squarely packed dual-scale fiber preforms is studied theoretically. These fiber preforms are composed of aligned porous tows and the tows are tightly packed. The effective permeability is calculated as a parallel-like network of intra-tow permeability and inter-tow permeability, which are quantified by Darcy’s law and the inscribed radius between tows, respectively. The jump velocity at the interface between inter-tow fluids and porous tows is considered, as derived by substituting Beavers and Joseph’s correlation into Brinkman’s equation. We further examine the effects of intra-tow permeability on the effective permeability of the fibrous system with three interface conditions: (1) interface velocity = 0, (2) interface velocity = mean intra-tow velocity, and (3) interface velocity = jump velocity. The jump-velocity-based model is found to be closest to numerical data. The influence of the fiber volume fraction of tows on the effective permeability is also analyzed.     

基于DF中继协作的车联网安全传输性能研究

5G时代的到来加快了以车路协同为核心的车联网技术的发展脚步。高效，可靠，安全的通信质量将是实现智能交通管理系统，完善智慧出行的基本要求。因此，针对存在信息窃取者的车联网中继协作传输场景，利用机会式中继选择策略与最大比合并技术设计了直接传输链路与多跳中继转发链路共存的安全传输方案，旨在提高信息传输的可靠性及安全性。同时，在获得信道概率密度函数及累积分布函数的基础上，利用全概率公式等方法推导出基于DF(Decode-Forward)中继协作传输的车联网系统安全中断概率的闭合表达式，其中涉及的信息传输信道均服从Nakagami-m分布，提高了理论推导的难度。最终的仿真实验证实了理论推导的准确性及本方案的可行性。      

Incidence and costs of bicycle-related traumatic brain injuries in the Netherlands

The main cause of death and serious disability in bicycle accidents is traumatic brain injury (TBI). The aim of this population-based study was to assess the incidence and costs of bicycle-related TBI across various age groups, and in comparison to all bicycle-related injuries, to identify main risk groups for the development of preventive strategies.Data from the National Injury Surveillance System and National Medical Registration were used for all patients with bicycle-related injuries and TBI who visited a Dutch emergency department (ED) between 1998 and 2012. Demographics and national, weighted estimates of injury mechanism, injury severity and costs were analysed per age group. Direct healthcare costs and indirect costs were determined using the incidence-based Dutch Burden of Injury Model.Between 1998 and 2012, the incidence of ED treatments due to bicycle-related TBI strongly increased with 54%, to 43 per 100,000 persons in 2012. However, the incidence of all bicycle-related injuries remained stable, from 444 in 1998 to 456/100,000 in 2012. Incidence of hospital admission increased in both TBI (92%) and all injuries from cycling (71%). Highest increase in incidence of both ED treatments and hospital admissions was seen in adults aged 55+. The injury rate of TBI per kilometre travelled increased (44%) except in children, but decreased (−4%) for all injuries, showing a strong decrease in children (−36%) but an increase in men aged 25+, and women aged 15+. Total costs of bicycle-related TBI were €74.5 million annually. Although bicycle-related TBI accounted for 9% of the incidence of all ED treatments due to cycling, it accounted for 18% of the total costs due to all bicycle-related injuries (€410.7 million). Children and adolescents (aged 0–24) had highest incidence of ED treatments due to bicycle-related injuries. Men in the working population (aged 15–64) had highest indirect costs following injuries from cycling, including TBI. Older cyclists (aged 55+) were identified as main risk group for TBI, as they had highest ED attendance, injury rate, injury severity, admission to hospital or intensive care unit, and costs.Incidence of ED treatments due to cycling are high and often involve TBI, imposing a high burden on individuals and society. Older cyclists aged 55+ were identified as main risk group for TBI to be targeted in preventive strategies, due to their high risk for (serious) injuries and ever-increasing share of ED visits and hospital admissions.     

Mathematical modeling of growth of Salmonella spp. and spoilage microorganisms in raw oysters

The main objective of this study was to develop the primary and secondary models to describe the growth kinetics of Salmonella as well as background microorganisms in raw, shucked oysters. Samples, inoculated with a cocktail of two Salmonella serotypes, S. Typhimurium (CICC22956) and S. Enteritidis (CICC21482), were incubated at 4, 8, 12, 16, 20, 25, 30, 33, 37, 40, and 43 °C. Growth of Salmonella was observed at all temperatures, except at 4 °C. The background microorganisms grew at all temperatures. All growth curves clearly exhibited lag, exponential and stationary phases, and were analyzed using the Huang growth model. Three secondary models (Ratkowsky square-root, Huang square-root, and Cardinal parameter models) were compared for evaluating the effect of temperature on bacterial growth rates. Data analysis was performed using IPMP 2013, a free predictive microbiology software tool developed by the USDA ARS.The Cardinal parameters model underestimated the specific rates of the microorganisms at low temperatures. The Huang square-root model was more suitable than the Ratkowsky square-root model for describing the effect of temperature on growth of Salmonella, while the Ratkowsky square-root model, on the other hand, was more suitable for background microorganisms. For both Salmonella and background microorganisms, the logarithms of the lag phase were expressed as linear functions of the logarithms of specific growth rates. The results of this study can be used by the food retailers and regulatory agencies to estimate the microbial shelf-life of raw, shucked oysters.