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The bridge arms of traditional three-phase multilevel converters are independent of each other; thus, more active switches and passive diodes are required. In order to reduce the number of devices, a coupled three-phase converter architecture, which is suitable for both dc–ac and ac–dc converters, is presented. Based on this architecture, a ten-switch three-phase three-level (10S-3P-3L) inverter is proposed in this article. The proposed topology employs only ten active switches and no additional diodes, which helps to cut size, weight, and costs of system. The proposed space vector modulation enables 10S-3P-3L inverter to operate full modulation indexes. A comparison between the proposed inverter with some existing topologies in terms of device voltage and current stresses, conduction loss, switching loss, and other parameters is made to highlight its excellent performance. Moreover, the experimental results from a 3-kW experimental prototype reveal that the proposed inverter offers superior power quality.

The random forest (RF) algorithm is a typical representative of ensemble learning, which is widely used in rolling bearing fault diagnosis. In order to solve the problems of slower diagnosis speed and repeated voting of traditional RF algorithm in rolling bearing fault diagnosis under the big data environment, an efficient rolling bearing fault diagnosis method based on Spark and improved random forest (IRF) algorithm is proposed. By eliminating the decision trees with low classification accuracy and those prone to repeated voting in the original RF, an improved RF with faster diagnosis speed and higher classification accuracy is constructed. For the massive rolling bearing vibration data, in order to improve the training speed and diagnosis speed of the rolling bearing fault diagnosis model, the IRF algorithm is parallelized on the Spark platform. First, an original RF model is obtained by training multiple decision trees in parallel. Second, the decision trees with low classification accuracy in the original RF model are filtered. Third, all path information of the reserved decision trees is obtained in parallel. Fourth, a decision tree similarity matrix is constructed in parallel to eliminate the decision trees which are prone to repeated voting. Finally, an IRF model which can diagnose rolling bearing faults quickly and effectively is obtained. A series of experiments are carried out to evaluate the effectiveness of the proposed rolling bearing fault diagnosis method based on Spark and IRF algorithm. The results show that the proposed method can not only achieve good fault diagnosis accuracy, but also have fast model training speed and fault diagnosis speed for large-scale rolling bearing datasets.

Background: Dairy safety has caused widespread concern in society. Unsafe dairy products have threatened people's health and lives. In order to improve the safety of dairy products and effectively prevent the occurrence of dairy insecurity, countries have established different prevention and control measures and safety warnings. Objective: The purpose of this study is to establish a dairy safety prediction model based on machine learning to determine whether the dairy products are qualified. Methods: The 34 common items in the dairy sampling inspection were used as features in this study. Feature selection was performed on the data to obtain a better subset of features, and different algorithms were applied to construct the classification model. Results: The results show that the prediction model constructed by using a subset of features including “total plate”, “water” and “nitrate” is superior. The SN, SP and ACC of the model were 62.50%, 91.67% and 72.22%, respectively. It was found that the accuracy of the model established by the integrated algorithm is higher than that by the non-integrated algorithm. Conclusion: This study provides a new method for assessing dairy safety. It helps to improve the quality of dairy products, ensure the safety of dairy products, and reduce the risk of dairy safety.

Industrial equipment health management is an extension of traditional fault diagnosis, which is a frontier research field of information science. The definition and application area of industrial equipment health management are first clarified, and then technologies related to health management are introduced, including feature analysis, fault diagnosis, fault prognosis and other technologies. The difficulties and bottlenecks of various technologies are expounded through comparative analysis, and a feasible scheme for future health management and integration is also discussed in this article.

Single-phase five-level transformer-less inverter has been widely used in photovoltaic (PV) applications because of low total harmonic distortion (THD) and excellent output quality. However, a serious problem for transformer-less inverters is the leakage current issue which will lead to safety problems. This paper proposes a single-phase five-level transformer-less inverter to eliminate the leakage current. The circuit consists of eleven active switches and can keep the common mode voltage half of the DC bus voltage. The voltages of flying capacitors are balanced within one switching cycle through selecting the proper switching states. The mechanism of suppressing the leakage current is analyzed in detail with operational modes and modulation strategy. A 1 kW single-phase five-level inverter prototype is built to verify the validity and flexibility of the proposed topology and modulation.

A ten-switch three-phase three-level (10S-3P3L) inverter is proposed to reduce the cost for three-phase three-level inverter application, such as photovoltaic (PV) application. Compared with traditional neutral-point-clamped (NPC) three-phase three-level (3P3L) inverter, the proposed 10S-3P-3L inverter reduces two active switches and six clamping diodes. Due to the special circuit configuration of 10S-3P3L inverter, traditional space-vector pulse-width modulation (SVPWM) is not suitable for it anymore. To solve this problem and achieve almost same performance, a novel SVPWM strategy is also proposed. The proposed SVPWM strategy utilizes only 19 voltage vectors to synthesizes the reference. Simulation results and experimental results are presented to verify the feasibility and advantages of the proposed topology and modulation strategy.

Identifying lncRNA-protein Interactions (LPIs) is vital to understanding various key biological processes. Wet experiments found a few LPIs, but experimental methods are costly and time-consuming. Therefore, computational methods are increasingly exploited to capture LPI candidates. We introduced relevant data repositories, focused on two types of LPI prediction models: network-based methods and machine learning-based methods. Machine learning-based methods contain matrix factorization-based techniques and ensemble learning-based techniques. To detect the performance of computational methods, we compared parts of LPI prediction models on Leave-One-Out cross validation (LOOCV) and five-fold cross validation. The results show that SFPEL-LPI obtained the best performance of AUC. Although computational models have efficiently unraveled some LPI candidates, there are many limitations involved. We discussed future directions to further boost LPI predictive performance.

Learning from the successful application of the sound absorption seats in the music halls and theaters and also based on the features of the noise spectrum in high speed trains a sound absorption seat design which applies specifically to the high-speed trains is put forward in this paper. High performance absorbing materials and perforated plates are selected and designed. Finally, seats of full train carriage were made and tested in the high-speed train on the railway. The test results showed that the installation of the sound absorption seats results in the noise level at the standard point in the passenger compartment decreases by 1.5 dB compared with that of the normal seats.

At present, the international high-speed rail on clean and green and intelligent technology received unprecedented attention, especially the integration of security technology has become a core technology development trends. First, this paper does reliability analysis from the high-speed train system. Statistics of the subsystems of the failure rate is done. Then important subsystems bogie system reliability is analyzed combining with the maintenance on the high-speed train system reliability analysis. The parts distribution functions and associated parameters are fitted on software. Finally, we set up truck event tree model and reliability analysis of bogie system.

In order to improve the accuracy reliability of the high-speed train bogie system, fuzzy comprehensive assessment matrix was applied to allocate the reliability of bogie system. The effects of the reliability allocation of the high-speed train bogie system have a multilayered and multifactor characteristic which includes the quantitative and qualitative indexes. A fuzzy analytic hierarchy process (AHP) with five-point scale was proposed. The influence factors were considered and endowed with different weights according to the influence degree. A structural model of AHP is proposed for bogie system, which used interval number instead of fuzzy assessment matrix to express uncertain information. It can make use of expert’s experience and the field test information comprehensively. A high-speed train bogie system was taken as example to illustrate the application of this method.

Magnetic resonance imaging is a new imaging technology based on the hydrogen’s magnetic resonance feature. Gradient module should have high calculation speed and accuracy to complete massive computation work including rotation transform, eddy compensation and shimming in a very short time. We make a deep exploration into the gradient module from its function, real-time and accuracy requirements. Then, we propose and realize a novel gradient module based on high performance DSP. Experiments indicate that the gradient module we designed satisfies the function, real-time and accuracy requirements. It provides a practical gradient module solution for the development of digital Spectrometer.

Meeting the deadline requirement for the application flow is always a challenge in data centre. Aiming at this problem, many transmission control protocol (TCP) variants are proposed and most of them focus on improving the congestion avoidance phase while rarely considering the slow-start. This paper presents an improved TCP slow-start mechanism, which uses large initial windows (LIW) to help more flows to be finished before their deadlines and does not increase the network congestion meanwhile. The simulation results show that LIW can greatly enhance the meeting deadline ratio of flows involved in web searching and data mining application services which are common in data centres. Moreover, LIW can be easily deployed with rarely modifying the TCP stack.

A wireless sensor network (WSN) has resource constraints, which include a limited amount of energy, short communication range, low bandwidth, and limited processing and storage in each node. In this paper, an ant-routing algorithm is presented for wireless sensor networks. In the algorithm, ants are guided to choose different paths by adjusting heuristic factor. Mean-while, the weights are dynamically coordinated in the probability function. The evaporation coefficient of pheromone is improved by utilizing the idea of simulated annealing algorithm. In order to prevent local optimization, it introduces a reward and punishment mechanism into the pheromone update process. The simulation results show that the algorithm is better than the other current typical routing algorithms.

Digital certificate is the key element that implements trust and trust authentication in e-government and e-commerce, however CA may be canceled and revoked in advance by accident in practical applications. Therefore it is critical for the users of this certificate to obtain the latest certificate status as soon as possible, it is also critical for realizing credibility in PKI system. It summarizes the advantages and disadvantages in PKI system, and discusses the difficulties in practical application by analyzing the OCSP protocol. Some corresponding methods are proposed to solve the above problems.