Dynamic graph storage systems are essential for real-time applications such as social networks and recommendation, where the graph continuously evolves. However, they face significant challenges in efficiently handling concurrent read and write operations. We find that existing methods suffer from write queries interfering with read efficiency, substantial time and space overhead due to per-edge versioning, and an inability to balance performance, such as slow searches. To address these issues, we propose RapidStore, a holistic approach for efficient in-memory dynamic graph storage designed for read-intensive workloads. Our key idea is to exploit the characteristics of graph queries through a decoupled system design that separates the management of read and write queries and decouples version data from graph data. Besides, we design an efficient dynamic graph store to cooperate with the graph concurrency control mechanism. Experiments show that RapidStore enables fast and scalable concurrent graph queries, effectively balancing the performance of inserts, searches, and scans, and significantly improving efficiency in dynamic graph storage systems.

The solar array wing deployment of orbiting satellites cannot be performed due to power failure of the connector caused by uncertain loads such as high temperature or vibration in the launching process of the spacecraft. There is currently a lack of suitable unlocking solutions for solar wing re-unfolding. This paper proposes a solution in which an extensible continuum robot (ECR) carrying the unlocking device enters the gap between the satellite and the solar wing, re-unlocking the solar wing. This solution effectively leverages the advantages of ECR collision buffering and adaptable maneuverability within confined space. In response to the proposed solution, the designed ECR with two segments helical spring structure features scalability, hollowness, lightweight, and a big length-diameter ratio. To perform the critical unlocking task, an end effector with the function of loosening and unplugging the aerospace connector for communication is designed based on the drive device away from itself to reduce the inertia of the manipulator. The information from the cameras and force sensors is used to estimate the extent of task execution. We establish an experimental setup to simulate the process of unlocking. The results validate that the ECR successfully accesses the gap (65mm) and accomplishes the unlocking task. The ECR has great application potential for on-orbit service.

Selecting the best items in a dataset is a common task in data exploration. However, the concept of “best” lies in the eyes of the beholder: Different users may consider different attributes more important and, hence, arrive at different rankings. Nevertheless, one can remove “dominated” items and create a “representative” subset of the data, comprising the “best items” in it. A Pareto-optimal representative is guaranteed to contain the best item of each possible ranking, but it can be a large portion of data. A much smaller representative can be found if we relax the requirement of including the best item for each user and instead just limit the users’ “regret.” Existing work defines regret as the loss in score by limiting consideration to the representative instead of the full dataset, for any chosen ranking function. However, the score is often not a meaningful number, and users may not understand its absolute value. Sometimes small ranges in score can include large fractions of the dataset. In contrast, users do understand the notion of rank ordering. Therefore, we consider items’ positions in the ranked list in defining the regret and propose the rank-regret representative as the minimal subset of the data containing at least one of the top- k of any possible ranking function. This problem is polynomial time solvable in two-dimensional space but is NP-hard on three or more dimensions. We design a suite of algorithms to fulfill different purposes, such as whether relaxation is permitted on k , the result size, or both, whether a distribution is known, whether theoretical guarantees or practical efficiency is important, and so on. Experiments on real datasets demonstrate that we can efficiently find small subsets with small rank-regrets.

With the rapid development of the Internet, people are confronted with information overload. Many recommendation methods are designed to solve this problem. The main contributions of recommendation methods proposed in this paper are as follows: (1) An improved collaborative filtering recommendation algorithm based on user clustering is proposed. Clustering is performed according to user similarity based on the user-item rating matrix. So the search space of recommendation algorithm is reduced. (2) Considering the factor that user’s interests may dynamically change over time, a time decay function is introduced. (3) A method of real-time recommendation based on topic for microblogs is designed to realize real-time recommendation effectively by preserving intermediate variables of user similarity. Experiments show that the proposed algorithms have been improved in terms of running time and accuracy.

Capacitive current is an important influential ingredient for extinguishing electric arc, which comes into being when single phase ground fault occurs in resonance networks. In order to seize transient capacitive current's characters, two identification methods are presented using back propagation (BP) neural network and novel improved cerebellar model articulation controller network (ICMAC) separately. With two methods, the maximal amplitude and the minimal amplitude of transient capacitive current can be identified, occurring time of transient capacitive current amplitude can be confirmed as well as. These methods were proved by simulation with Matlab, the simulating results indicate that this novel ICMAC network makes learning identification speed faster and identification precision higher than normal BP network, through adjusting learning factor dynamically. Effective identification of transient capacitive current's characteristics provides evidences for further cure of capacitive current.

A redundant robot configured with a parallel base and a series manipulator is proposed in this paper. The position and orientation of end manipulator are considered as the result of the joints' ordinal motion according to the equivalence principle, so the close analytic solution for self-motion of this redundant robot is obtained via geometrical method. The Jacobian matrices of the parallel base and the whole robot system are solved respectively. Based on this, the solution for self-motion in two classes of singular configuration is also obtained. Finally a self-motion simulation of the redundant robot is performed via software MATLAB and ADAMS to validate the algorithm