Distributed Tree Comparison with Nodes of Limited Memory

The demands for indoor positioning in location-based services (LBS) and applications grow rapidly. It is beneficial for indoor positioning to combine attitude and heading information. Accurate attitude and heading estimation based on magnetic, angular rate, and gravity (MARG) sensors of micro-electro-mechanical systems (MEMS) has received increasing attention due to its high availability and independence. This paper proposes a quaternion-based adaptive cubature Kalman filter (ACKF) algorithm to estimate the attitude and heading based on smart phone-embedded MARG sensors. In this algorithm, the fading memory weighted method and the limited memory weighted method are used to adaptively correct the statistical characteristics of the nonlinear system and reduce the estimation bias of the filter. The latest step data is used as the memory window data of the limited memory weighted method. Moreover, for restraining the divergence, the filter innovation sequence is used to rectify the noise covariance measurements and system. Besides, an adaptive factor based on prediction residual construction is used to overcome the filter model error and the influence of abnormal disturbance. In the static test, compared with the Sage-Husa cubature Kalman filter (SHCKF), cubature Kalman filter (CKF), and extended Kalman filter (EKF), the mean absolute errors (MAE) of the heading pitch and roll calculated by the proposed algorithm decreased by 4–18%, 14–29%, and 61–77% respectively. In the dynamic test, compared with the above three filters, the MAE of the heading reduced by 1–8%, 2–18%, and 2–21%, and the mean of location errors decreased by 9–22%, 19–31%, and 32–54% respectively by using the proposed algorithm for three participants. Generally, the proposed algorithm can effectively improve the accuracy of heading. Moreover, it can also improve the accuracy of attitude under quasistatic conditions.

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On-Shelf Utility Mining of Sequence Data

ACM Transactions on Knowledge Discovery from Data ◽

10.1145/3457570 ◽

2021 ◽

Vol 16 (2) ◽

pp. 1-31

Author(s):

Chunkai Zhang ◽

Zilin Du ◽

Yuting Yang ◽

Wensheng Gan ◽

Philip S. Yu

Keyword(s):

High Efficiency ◽

Sequence Data ◽

Real Life ◽

Search Space ◽

Upper Bounds ◽

Utility Mining ◽

Limited Memory ◽

Time Periods ◽

High Utility ◽

Synthetic Datasets

Utility mining has emerged as an important and interesting topic owing to its wide application and considerable popularity. However, conventional utility mining methods have a bias toward items that have longer on-shelf time as they have a greater chance to generate a high utility. To eliminate the bias, the problem of on-shelf utility mining (OSUM) is introduced. In this article, we focus on the task of OSUM of sequence data, where the sequential database is divided into several partitions according to time periods and items are associated with utilities and several on-shelf time periods. To address the problem, we propose two methods, OSUM of sequence data (OSUMS) and OSUMS + , to extract on-shelf high-utility sequential patterns. For further efficiency, we also design several strategies to reduce the search space and avoid redundant calculation with two upper bounds time prefix extension utility ( TPEU ) and time reduced sequence utility ( TRSU ). In addition, two novel data structures are developed for facilitating the calculation of upper bounds and utilities. Substantial experimental results on certain real and synthetic datasets show that the two methods outperform the state-of-the-art algorithm. In conclusion, OSUMS may consume a large amount of memory and is unsuitable for cases with limited memory, while OSUMS + has wider real-life applications owing to its high efficiency.

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Event-Driven Distributed Kalman-Consensus Filter with Limited Memory Information

2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) ◽

10.1109/ddcls49620.2020.9275057 ◽

2020 ◽

Author(s):

Chunxi Yang ◽

Jie Zhu ◽

Chi Zhai

Keyword(s):

Limited Memory ◽

Event Driven ◽

Consensus Filter

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Multilocus phylogenies reveal three new truffle-like taxa and the traces of interspecific hybridization in Octaviania (Boletaceae, Boletales)

IMA Fungus ◽

10.1186/s43008-021-00066-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Takamichi Orihara ◽

Rosanne Healy ◽

Adriana Corrales ◽

Matthew E. Smith

Keyword(s):

Rna Polymerase Ii ◽

Phylogenetic Analyses ◽

Large Subunit ◽

Gene Tree ◽

Phylogenetic Network ◽

Elongation Factor ◽

Morphological Observation ◽

Tree Comparison ◽

Unknown Species ◽

The Usa

ABSTRACTAmong many convergently evolved sequestrate fungal genera in Boletaceae (Boletales, Basidiomycota), the genus Octaviania is the most diverse. We recently collected many specimens of Octaviania subg. Octaviania, including several undescribed taxa, from Japan and the Americas. Here we describe two new species in subgenus Octaviania, O. tenuipes and O. tomentosa, from temperate to subtropical evergreen Fagaceae forests in Japan based on morphological observation and robust multilocus phylogenetic analyses (nrDNA ITS and partial large subunit [LSU], translation elongation factor 1-α gene [TEF1] and the largest subunit of RNA polymerase II gene [RPB1]). Based on specimens from the Americas as well as studies of the holotype, we also taxonomically re-evaluate O. asterosperma var. potteri. Our analysis suggests that O. asterosperma var. potteri is a distinct taxon within the subgenus Octaviania so we recognize this as O. potteri stat. nov. We unexpectedly collected O. potteri specimens from geographically widespread sites in the USA, Japan and Colombia. This is the first verified report of Octaviania from the South American continent. Our molecular analyses also revealed that the RPB1 sequence of one O. tenuipes specimen was identical to that of a closely related species, O. japonimontana, and that one O. potteri specimen from Minnesota had an RPB1 sequence of an unknown species of O. subg. Octaviania. Additionally, one O. japonimontana specimen had an unusually divergent TEF1 sequence. Gene-tree comparison and phylogenetic network analysis of the multilocus dataset suggest that these heterogenous sequences are most likely the result of previous inter- and intra-specific hybridization. We hypothesize that frequent hybridization events in Octaviania may have promoted the high genetic and species diversity found within the genus.

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