Raif-Semantics: A Robust Automated Interlinking Framework for Semantic Web Using MapReduce and Multi-node Data Processing

The era of the web has evolved and the industry strives to work better every day, the constant need for data to be accessible at a random moment is expanding, and with this expansion, the need to create a meaningful query technique in the web is a major concerns. To transmit meaningful data or rich semantics, machines/projects need to have the ability to reach the correct information and make adequate connections, this problem is addressed after the emergence of Web 3.0, the semantic web is developing and being collected an immense. Information to prepare, this passes the giant data management test, to provide an ideal result at any time needed. Accordingly, in this article, we present an ideal system for managing huge information using MapReduce structures that internally help an engine bring information using the strength of fair preparation using smaller map occupations and connection disclosure measures. Calculations for similarity can be challenging, this work performs five similarity detection algorithms and determines the time it takes to address the patterns that has to be a better choice in the calculation decision. The proposed framework is created using the most recent and widespread information design, that is, the JSON design, the HIVE query language to obtain and process the information planned according to the customer’s needs and calculations for the disclosure of the interface. Finally, the results on a web page is made available that helps a user stack json information and make connections somewhere in the range of dataset 1 and dataset 2. The results are examined in 2 different sets, the results show that the proposed approach helps to interconnect significantly faster; Regardless of how large the information is, the time it takes is not radically extended. The results demonstrate the interlinking of the dataset 1 and dataset 2 is most notable using LD and JW, the time required is ideal in both calculations, this paper has mechanized the method involved with interconnecting via a web page, where customers can merge two sets of data that should be associated and used.

Intelligent signal detectors with random moment of appearance in rail lines monitoring systems

The article discusses the issues of building intelligent receivers of pulsed signals with an unknown arrival time without restrictions on the value of the signal-to-noise ratio under the influence of a complex of interfering factors. Using recurrent methods for detecting disturbances of random processes and an algorithm of cumulative sums, the problem of synthesizing algorithms for detecting Markov signals with random moments of appearance against the background of various combinations of destabilizing factors acting in control systems for the states of rail lines in normal and shunt operating modes is solved. To assess the efficiency of detecting a random signal by the method of cumulative sums, statistical modeling of the specified algorithm was carried out.

Moment-Based Hybrid Polynomial Chaos Method for Interval and Random Uncertain Analysis of Periodical Composite Structural-Acoustic System with Multi-Scale Parameters

An interval and random moment-based arbitrary polynomial chaos method (IRMAPCM) is proposed in this paper for the analysis of periodical composite structural-acoustic systems with multi-scale uncertain-but-bounded parameters. In IRMAPCM, the response of structural-acoustic system is approximated as moment-based arbitrary polynomial chaos (maPC) expansion. IRMAPCM can construct the polynomial basis according to the moment of the random variable without knowing the Probability Density Function (PDF), which can avoid the errors introduced by estimating the PDF. Numerical examples of a hexahedral box and an automobile passenger compartment are given to investigate the effectiveness of IRMAPCM for the prediction of the sound pressure response of structural-acoustic systems.

Effects of ageing on responses to stepping-target displacements during walking

Purpose Human sensory and motor systems deteriorate with age. When walking, older adults may therefore find it more difficult to adjust their steps to new visual information, especially considering that such adjustments require control of balance as well as of foot trajectory. Our study investigates the effects of ageing on lower limb responses to unpredictable target shifts. Methods Participants walked on a treadmill with projected stepping targets that occasionally shifted in the medial or lateral direction. The shifts occurred at a random moment during the early half of the swing phase of either leg. Kinematic, kinetic and muscle activity data were collected. Results Older adults responded later and corrected for a smaller proportion of the shift than young adults. The order in which muscle activation changed was similar in both groups, with responses of gluteus medius and semitendinosus from about 120 to 140 ms after the shift. Most muscles responded slightly later to lateral target shifts in the older adults than in the young adults, but this difference was not observed for medial target shifts. Ageing delayed the behavioural responses more than it did the electromyographic (EMG) responses. Conclusions Our study suggests that older adults can adjust their walking to small target shifts during the swing phase, but not as well as young adults. Furthermore, muscle strength probably plays a substantial role in the changes in online adjustments during ageing.