Author name cluster

Ke Qiu

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11 papers

2 author rows

IROS Conference 2025 Conference Paper

Human-guided robotic-assistance handheld continuum medical robot system

Fei Wang
Changhao Luo
Zexi Zhao
Pingyu Xiang
Ke Qiu
Yufei Wei
Yue Wang 0020
Rong Xiong

Nowadays, laparoscopic surgery procedures face a trade-off between expensive, complex robotic systems and manual instruments with limited functionality. Fully robotic solutions offer precision but lack portability and intuitive control, while manual tools rely solely on the surgeon’s dexterity, limiting maneuverability and depth perception in confined spaces. To bridge this, we propose a Human-Guided Robotic-Assistance Handheld Continuum Medical Robot System (HRHC). This system simulates intuitive manual operation with robotic precision, extending the surgeon’s capabilities while maintaining portability. Additionally, a stereo vision system enhances real-time depth perception, improving spatial awareness in minimally invasive procedures.

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EAAI Journal 2025 Journal Article

Multisource-domain regression transfer learning framework for predicting student academic performance considering balanced similarity

Li Wang
Lucong Zhang
Haotian Wu
Teng Zhang
Ke Qiu
Tianyu Chen
Hongwu Qin

The increasing integration of information technology and artificial intelligence has extensively implemented computer-aided intelligent education systems in higher education. A critical task within these systems is student performance prediction, which forecasts future academic outcomes by analyzing data such as historical grades, learning behaviors, and classroom participation. This enables early intervention and personalized teaching based on scientific evidence. However, most existing methods rely on traditional machine learning techniques, which can hardly address issues such as domain distribution discrepancies and data imbalance effectively. To overcome these challenges, we propose a multisource-domain transfer learning regression framework that integrates domain selection, hybrid feature extraction, and dynamic joint distribution adaptation techniques. Specifically, the framework first selects appropriate source domains on the basis of preset thresholds via cross-validation. Thereafter, a hybrid feature extractor is used to derive (i) common features from the target and selected source domains and (ii) domain-specific features from the target domain. Finally, a dynamic adaptive factor is introduced to balance differences between the marginal and conditional distributions. Experimental results indicate that the proposed framework significantly reduces the root mean square error with an average prediction improvement of 21. 05 %, compared with baseline methods and other advanced approaches.

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IROS Conference 2024 Conference Paper

Learning the Inverse Kinematics of Magnetic Continuum Robot for Teleoperated Navigation

Pingyu Xiang
Ke Qiu
Danying Sun
Jingyu Zhang
Qin Fang
Xiangyu Mi
Shudong Wang
Mengxiao Chen

Magnetic continuum robots are subject to external magnetic fields and deformed remotely, simplifying the robot’s transmission mechanism and providing it with significant potential for miniaturization and operational flexibility. However, modeling magnetic field distribution generated by permanent magnets is complex and requires time-consuming pre-calibrations. Moreover, it is highly susceptible to environments with ferromagnetic materials, posing significant challenges for the control of magnetic continuum robots. In response, we propose an approach that does not overly focus on the magnetic field distribution but instead directly learns the inverse kinematics of magnetic continuum robots end-to-end. Binding the robot’s configuration to the pose of external magnets, precise control of continuum robots is facilitated. Additionally, we leverage teleoperation techniques to broaden the applicability of this method. By mounting magnets on a robotic arm and directly utilizing the target pose of the external magnet predicted by a multi-layer perceptron (MLP), we achieve the operation and navigation of magnetic continuum robots in complex environments. Experiments demonstrate that the mean control accuracy along the robot using our learning-based inverse kinematics is about half of the robot’s diameter.

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TCS Journal 2023 Journal Article

On the g-extra connectivity of augmented cubes

Eddie Cheng
László Lipták
Ke Qiu
Zhizhang Shen
Abhishek Vangipuram

A g-extra cut of a non-complete graph G, g ≥ 0, is a set of vertices in G whose removal disconnects the graph, while every component in the survival graph contains at least g + 1 vertices. The g-extra connectivity of G then refers to the size of a minimum g-extra cut of G. The augmented hypercube, denoted by A Q n, n ≥ 3, is a rich variant of the hypercube structure. In this paper, we present a sequence of construction based upper bounds of its g-extra connectivity, study its lower bound via the super connectedness property, and suggest an asymptotically tight bound.

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TCS Journal 2022 Journal Article

On the g-extra diagnosability of enhanced hypercubes

Eddie Cheng
Ke Qiu
Zhizhang Shen

Several fault tolerant models have been investigated in order to study the fault-tolerance properties of self-diagnosable interconnection networks, which are often represented with a connected graph G. In particular, a g-extra cut of a non-complete graph G, g ≥ 0, is a set of vertices in G whose removal disconnects the graph, but every component in the survival graph contains at least g + 1 vertices. The g-extra diagnosability of G then refers to the maximum number of faulty vertices in G that can be identified when considering these g-extra faulty sets only. Enhanced hypercubes, denoted by Q n, k, n ≥ 3, k ∈ [ 1, n ], is another variant of the hypercube structure. In this paper, we make use of its super connectivity property to derive its g-extra diagnosability of ( g + 1 ) n − ( g 2 ) + 1 in terms of the PMC diagnostic model for g ∈ [ 1, min ⁡ { ( n − 3 ) / 2, k − 3 } ], n ≥ 2 g + 3, and k ∈ [ max ⁡ { 4, g + 3 }, n − 1 ]; as well as g ∈ [ 1, ( n − 5 ) / 2 ], and n = k; and that in terms of MM* model, when g ∈ [ 2, min ⁡ { ( n − 3 ) / 2, k − 3 } ], n ≥ 2 g + 3, and k ∈ [ max ⁡ { 4, g + 3 }, n − 1 ]; as well as g ∈ [ 2, ( n − 5 ) / 2 ], and n = k.

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TCS Journal 2020 Journal Article

A 2-approximation algorithm and beyond for the minimum diameter k-Steiner forest problem

Wei Ding
Ke Qiu

Given an edge-weighted undirected graph G = ( V, E, w ) and a subset T ⊆ V of p terminals, a k-Steiner forest spanning all the terminals in T includes k branches, where every branch is a Steiner tree. The diameter of a k-Steiner forest is referred to as the maximum distance between two terminals of a branch. This paper studies the minimum diameter k-Steiner forest problem (MDkSFP) and establishes the relationship between MDkSFP and the absolute k-Steiner center problem (AkSCP). We first obtain a 2-factor dual approximation algorithm for AkSCP, and then achieve a 2-approximation algorithm for MDkSFP based on the 2-approximation to AkSCP. Furthermore, we develop an improved 2ρ-approximation algorithm for MDkSFP, where ρ < 1 in general, by perturbing the sites of facilities and re-clustering the terminals.

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TCS Journal 2019 Journal Article

A general approach to deriving the g-good-neighbor conditional diagnosability of interconnection networks

Eddie Cheng
Ke Qiu
Zhizhang Shen

We discuss a general approach to deriving the g-good-neighbor conditional diagnosability of interconnection networks. As demonstrative examples, we derive the 1- and 2-good-neighbor conditional diagnosabilities of the arrangement graphs under both the commonly adopted PMC and MM ⁎ model. We also derive the general g-good-neighbor conditional diagnosability of the ( n, k ) -star graphs under the PMC model for g ∈ [ 1, n − k ], and under the MM ⁎ model for g ∈ [ 2, n − k ], as well as that of the related graphs, such as the star graph, the alternating group graph, and the alternating group network.

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TCS Journal 2019 Journal Article

Approximating the restricted 1-center in graphs

Wei Ding
Ke Qiu

This paper studies the restricted vertex 1-center problem (RV1CP) and restricted absolute 1-center problem (RA1CP) in general undirected graphs with each edge having two weights, cost and delay. First, we devise a simple FPTAS for RV1CP with O ( m n 3 ( 1 ϵ + log ⁡ log ⁡ n ) ) running time, based on FPTAS proposed by Lorenz and Raz (1999) [11] for computing end-to-end restricted shortest path (RSP). During the computation of the FPTAS for RV1CP, we derive a RSP distance matrix. Next, we discuss RA1CP in such graphs where the delay is a separable (e. g. , linear) function of the cost on edge. We investigate an important property that the FPTAS for RV1CP can find a ( 1 + ϵ ) -approximation of RA1CP when the RSP distance matrix has a saddle point. In addition, we show that it is harder to find an approximation of RA1CP when the matrix has no saddle point. This paper develops a scaling algorithm with at most O ( m n 3 K ( log ⁡ K η + log ⁡ log ⁡ n ) ) running time where K is a step-size parameter and η is a given positive number, to find a ( 1 + η ) -approximation of RA1CP.

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TCS Journal 2017 Journal Article

Incremental single-source shortest paths in digraphs with arbitrary positive arc weights

Wei Ding
Ke Qiu

This paper studies the incremental single-source shortest paths (SSSP) problem in general digraphs with arbitrary positive arc weights. First, we examine several properties of single-source shortest paths in general digraphs with arbitrary positive arc weights, and devise a nontrivial local search algorithm LSA to handle a single arc weight increase in such a digraph, which takes at most O ( n ⋅ max ⁡ { 1, n log ⁡ n / m } ) expected update time where n is the number of nodes and m is the number of arcs in the digraph. LSA also works on undirected graphs. Furthermore, this paper analyzes the expected update time of LSA dealing with edge weight increases or edge deletions in Erdös–Rényi (a. k. a. , G ( n, p ) ) random graphs. For weighted G ( n, p ) random graphs with arbitrary positive edge weights, LSA takes at most O ( h ( T s ) ) expected update time to deal with a single edge weight increase as well as O ( p n 2 h ( T s ) ) total update time, where h ( T s ) is the height of input SSSP tree T s. For G ( n, p ) random graphs, LSA takes O ( ln ⁡ n ) expected update time to handle a single edge deletion as well as O ( p n 2 ln ⁡ n ) total update time when 20 ln ⁡ n / n ≤ p < 2 ln ⁡ n / n, and O ( 1 ) expected update time to handle a single edge deletion as well as O ( p n 2 ) total update time when p > 2 ln ⁡ n / n. Specifically, LSA takes the least total update time of O ( n ln ⁡ n h ( T s ) ) for weighted G ( n, p ) random graphs with p = c ln ⁡ n / n, c > 1 as well as O ( n 3 / 2 ( ln ⁡ n ) 1 / 2 ) for G ( n, p ) random graphs with p = c ln ⁡ n / n, c > 2.

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TCS Journal 2014 Journal Article

On the conditional diagnosability of matching composition networks

Eddie Cheng
Ke Qiu
Zhizhang Shen

The conditional diagnosability of interconnection networks has been studied by using a number of ad-hoc methods. Recently, gathering various ad-hoc methods developed in the last decade, a unified approach was developed, and this approach was used to find the conditional diagnosability of many interconnection networks. In this paper, we study the conditional diagnosability of matching composition networks, including those that are not triangle-free.

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TCS Journal 2009 Journal Article

On the surface area of the ( n, k ) -star graph

Zhizhang Shen
Ke Qiu
Eddie Cheng

We present an explicit formula for the surface area of the ( n, k ) -star graph, i. e. , the number of nodes at a certain distance from the identity node in the graph, by identifying the unique cycle structures associated with the nodes in the graph, deriving a distance expression in terms of such structures between the identity node of the graph and any other node, and enumerating those cycle structures satisfying the distance restriction. The above surface area derivation process can also be applied to some of the other node symmetric interconnection structures defined on the symmetric group, when the aforementioned distance expression is available.

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