Results 251 to 260 of about 2,131,360 (300)
TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications
Advanced Robotics Research, EarlyView.TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince +3 more
wiley +1 more source
Auditory–Tactile Congruence for Synthesis of Adaptive Pain Expressions in RoboPatients
Advanced Robotics Research, EarlyView.In this work, we explore auditory–tactile congruence for synthesizing adaptive vocal pain expressions in robopatients. Using a robopatient platform that integrates vocal pain sounds with palpation forces, we conducted 7680 trials across 20 participants.
Saitarun Nadipineni +4 more
wiley +1 more source
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot
Advanced Robotics Research, EarlyView.A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini +7 more
wiley +1 more source
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ORSA Journal on Computing, 1994
This paper considers the problem of partitioning the vertices of a weighted complete graph into cliques of unbounded size and number, such that the sum of the edge weights of all cliques is maximized. The problem is known as the clique-partitioning problem and arises as a clustering problem in qualitative data analysis.
Ulrich Dorndorf, Erwin Pesch
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This paper considers the problem of partitioning the vertices of a weighted complete graph into cliques of unbounded size and number, such that the sum of the edge weights of all cliques is maximized. The problem is known as the clique-partitioning problem and arises as a clustering problem in qualitative data analysis.
Ulrich Dorndorf, Erwin Pesch
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An Efficient Clustering Algorithm
IEEE Transactions on Systems, Man, and Cybernetics, 1976A new algorithm is presented (called matching algorithm), in order to reorganize data data and identify clusters. Thus the algorithm requires only three integer additions in each step, instead of comparing the entire row to evaluate the matchings with the neighboring rows.
M. V. Bhat, A. Haupt
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Proceedings Seventh International Conference on Database Systems for Advanced Applications DASFAA 2001 DASFAA-01, 2001
Clustering is one of the important techniques in data mining. The objective of clustering is to group objects into clusters such that objects within a cluster are more similar to each other than objects in different clusters. The similarity between two objects is defined by a distance function, e.g., the Euclidean distance, which satisfies the ...
Fei Wu 0009, Georges Gardarin
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Clustering is one of the important techniques in data mining. The objective of clustering is to group objects into clusters such that objects within a cluster are more similar to each other than objects in different clusters. The similarity between two objects is defined by a distance function, e.g., the Euclidean distance, which satisfies the ...
Fei Wu 0009, Georges Gardarin
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Parallel clustering algorithms
Parallel Computing, 1989zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiaobo Li 0001, Zhixi Fang
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An online clustering algorithm
2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011This paper presents a new online clustering algorithm called SAFN which is used to learn continuously evolving clusters from non-stationary data. The SAFN uses a fast adaptive learning procedure to take into account variations over time. In non-stationary and multi-class environment, the SAFN learning procedure consists of five main stages: creation ...
Kan Li, Fenglan Yao, Ruipeng Liu
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