Features of the fiber-optics data system using optical solitons

The analysis of the parameters of a high-speed information data system using dispersion-managed solitons is carried out. It is shown that the quality of information transmission can be increased by choosing the input-output point of the symbol sequence on the dispersion map.

Detecting a multigranularity event in an unequal interval time series based on self-adaptive segmenting

Analyzing the temporal behaviors and revealing the hidden rules of objects that produce time series data to detect the events that users are interested in have recently received a large amount of attention. Generally, in various application scenarios and most research works, the equal interval sampling of a time series is a requirement. However, this requirement is difficult to guarantee because of the presence of sampling errors in most situations. In this paper, a multigranularity event detection method for an unequal interval time series, called SSED (self-adaptive segmenting based event detection), is proposed. First, in view of the trend features of a time series, a self-adaptive segmenting algorithm is proposed to divide a time series into unfixed-length segmentations based on the trends. Then, by clustering the segmentations and mapping the clusters to different identical symbols, a symbol sequence is built. Finally, based on unfixed-length segmentations, the multigranularity events in the discrete symbol sequence are detected using a tree structure. The SSED is compared to two previous methods with ten public datasets. In addition, the SSED is applied to the public transport systems in Xiamen, China, using bus-speed time-series data. The experimental results show that the SSED can achieve higher efficiency and accuracy than existing algorithms.

A Degradation Condition Assessment Technique Based on online_ISSE Degradation Feature and Logistic Regression Model

A degradation assessment technique based on an online improved symbol sequence entropy online_ISSE and a logistic regression model is proposed in this paper. Firstly, the threshold factor is introduced to retain the `coarse graining' information of direction changing and amplitude information, the `sensitivity' of improved symbol sequence entropy (SSE) to impact components is reduced and improved symbol sequence entropy (ISSE) is proposed. Then, a sliding window and Weibull distribution theory are used to effectively filter out the influence of fluctuations in the ISSE feature sequence, forming the degradation feature named online_ISSE. Finally, a logistic regression model is trained and constructed, and the health factor CV is calculated online to assess the degradation condition of the unknown signal samples. The lifetime vibration signal of the hoisting gearbox monitored from #8114 quay crane of the Shanghai Port Container Terminal is introduced for instance analysis. The results show that the proposed ISSE has a better effect in describing the complexity pattern than the SSE algorithm and that the degradation condition can be tracked and assessed accurately based on the technique proposed.

Analysis of Low Probability of Detection Capability for Chaotic Standard Map-Based FH-OFDMA System

A frequency hopping orthogonal frequency division multiple access (FH-OFDMA) can provide low probability of detection (LPD) and anti-jamming capabilities to users against adversary detectors. To obtain an extreme LPD capability that cannot be provided by the basic symbol-by-symbol (SBS)-based FH pattern, we proposed two FH patterns, namely chaotic standard map (CSM) and cat map for FH-OFDMA systems. In our previous work, through analysis of complexity to regenerate the transmitted symbol sequence, at the point of adversary detectors, we found that the CSM had a lower probability of intercept than the cat map and SBS. It is possible when a detector already knows symbol and frame structures, and the detector has been synchronized to the FH-OFDMA system. Unlike the previous work, here, we analyze whether the CSM provides greater LPD capability than the cat map and SBS by detection probability using spectrum sensing technique. We analyze the detection probability of the CSM and provide detection probabilities of the cat map and SBS compared to the CSM. Based on our analysis of the detection probability and numerical results, it is evident that the CSM provides greater LPD capability than both the cat map and SBS-based FH-OFDMA systems.

Cyclic dynamics of misfires and partial burns in a dilute spark-ignition engine

This study investigates the cyclic dynamics of cumulative heat release data past the edge of stability in a dilute spark-ignition engine. Emphasis is placed on analyzing the cyclic dynamics near the dilute limit where partial burns and misfires are frequent. These events are often followed by a higher-energy cycle due to the feed-forward mechanism present in the residual gases. These patterns are deterministic and increase the coefficient of variation to undesirable levels. Symbol sequence analysis was used to investigate the cyclic dynamics of these low–high patterns. The heat release was partitioned on an energy basis to give physical meaning to each partition and each sequence created when analyzing the symbol sequence results. This partitioning method provided insight into the differences in the dynamics when operating in the misfire or partial burn regime. These differences could impact the control method used.

Fast trie-based method for multiple pairwise sequence alignment

A method for efficient comparison of a symbol sequence with all strings of a set is presented, which performs considerably faster than the naive enumeration of comparisons with all strings in succession. The procedure is accelerated by applying an original algorithm combining a prefix tree and a standard dynamic programming algorithm searching for the edit distance (Levenshtein distance) between strings. The efficiency of the method is confirmed by numerical experiments with arrays consisting of tens of millions of biological sequences of variable domains of monoclonal antibodies.