Dynamic Image-based visual servo control using centroid and optic flow features

This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

Accelerating Large Scale Centroid-based Clustering with Locality Sensitive Hashing

Most traditional data mining algorithms struggle to cope with the sheer scale of data efficiently. In this paper, we propose a general framework to accelerate existing clustering algorithms to cluster large-scale datasets which contain large numbers of attributes, items, and clusters. Our framework makes use of locality sensitive hashing (LSH) to significantly reduce the cluster search space. We also theoretically prove that our framework has a guaranteed error bound in terms of the clustering quality. This framework can be applied to a set of centroid-based clustering algorithms that assign an object to the most similar cluster, and we adopt the popular K-Modes categorical clustering algorithm to present how the framework can be applied. We validated our framework with five synthetic datasets and a real world Yahoo! Answers dataset. The experimental results demonstrate that our framework is able to speed up the existing clustering algorithm between factors of 2 and 6, while maintaining comparable cluster purity.

Approximation of centroid end-points and switch points for replacing type reduction algorithms

Despite several years of research, type reduction (TR) operation in interval type-2 fuzzy logic system (IT2FLS) cannot perform as fast as a type-1 defuzzifier. In particular, widely used Karnik-Mendel (KM) TR algorithm is computationally much more demanding than alternative TR approaches. In this work, a data driven framework is proposed to quickly, yet accurately, estimate the output of the KM TR algorithm using simple regression models. Comprehensive simulation performed in this study shows that the centroid end-points of KM algorithm can be approximated with a mean absolute percentage error as low as 0.4%. Also, switch point prediction accuracy can be as high as 100%. In conjunction with the fact that simple regression model can be trained with data generated using exhaustive defuzzification method, this work shows the potential of proposed method to provide highly accurate, yet extremely fast, TR approximation method. Speed of the proposed method should theoretically outperform all available TR methods while keeping the uncertainty information intact in the process.

Matrix constructions of centroid sets for classification systems

This article continues the investigation of matrix constructions motivated by their applications to the design of classification systems. Our main theorems strengthen and generalize previous results by describing all centroid sets for classification systems that can be generated as one-sided ideals with the largest weight in structural matrix semirings. Centroid sets are well known in data mining, where they are used for the design of centroid-based classification systems, as well as for the design of multiple classification systems combining several individual classifiers.

Distances of centroid sets in a graph-based construction for information security applications

The aim of this paper is to prove that, for every balanced digraph, in every incidence semiring over a semifield, each centroid set J of the largest distance also has the largest weight, and the distance of J is equal to its weight. This result is surprising and unexpected, because examples show that distances of arbitrary centroid sets in incidence semirings may be strictly less than their weights. The investigation of the distances of centroid sets in incidence semirings of digraphs has been motivated by the information security applications of centroid sets.

8-Ammonionaphthalene-2-sulfonate monohydrate : the zwitterionic hydrate of 1,7-Cleve's acid

The structure of 8-amino-2-naphthalenesulfonic acid monohydrate (1,7-Cleve's acid hydrate), C10H9NO3S.H2O, shows the presence of a sulfonate-aminium group zwitterion, both groups and the water molecule of solvation giving cyclic R3/3(8) intermolecular hydrogen-bonding interactions forming chains which extend down a axis of the unit cell. Additional peripheral associations, including weak aromatic ring pi-pi interactions [centroid-centroid distance 3.6299(15)A], result in a two-dimensional sheet structure.

4-Chloroanilinium 2-carboxy-4,5-dichlorobenzoate

The structure of the 1:1 proton-transfer compound of 4-chloroaniline with 4,5-dichlorophthalic acid (DCPA), viz. C6H7ClN+ C8H3Cl2O4-, has been determined at 130 K. The non-planar hydrogen phthalate anions and the 4-chloroanilinium cations form two-dimensional O-H...O and N-H...O hydrogen-bonded substructures which have no peripheral extension. Between the sheets there are weak \p--\p associations between alternating cation--anion aromatic ring systems [shortest centroid separation, 3.735(4)A].

1,10-phenanthrolin-1-ium 2-carboxy-4,5-dichlorobenzoate

In the structure of the 1:1 proton-transfer compound of 1,10-phenanthroline with 4,5-dichlorophthalic acid, C12H9N2+ C8H3Cl2O4-, determined at 130 K, the 1,10-phenanthroline cation and the hydrogen 4,5-dichlorophthalate anion associate through a single N-H...O(carboxyl) hydrogen bond giving discrete units which have no extension except through a number of weak cation C-H...O(anion) associations and weak cation--anion aromatic ring pi-pi interactions [minimum centroid separation, 3.6815(12)A]. The anions are essentially planar [maximum deviation 0.214(1)A (a carboxyl O)] with the syn-related H atom of the carboxyl group forming a short intramolecular O-H...O(carboxyl) hydrogen bond.

Guanidinium quinoline-2-carboxylate

In the structure of the guanidinium salt of quinaldic acid, CH6N3+ C10H6NO2-, the asymmetric unit contains two independent cations and anions having similar inter-species hydrogen-bonding environments which include cyclic R2/2(8), R1/2(6) and R2/1(5) associations. These and additional weak aromatic ring pi-pi interactions [minimum ring centroid separation, 3.6621(16)A] give a two-dimensional layered structure.

Crystallographic characterization of the first reported crystalline form of the potent hallucinogen (R)-2-amino-1-(8-bromobenzo[1,2-b;5,4-b']difuran-4-yl)propane or `bromodragonfly': the 1:1 anhydrous proton-transfer compound with 3,5-dinitrosalicylic acid

The 1:1 proton-transfer compound of the potent substituted amphetamine hallucinogen (R)-1-(8-bromobenzo[1,2-b; 4,5-b']difuran-4-yl)-2-aminopropane (common trivial name 'bromodragonfly') with 3,5-dinitrosalicylic acid, 1-(8-bromobenzo[1,2-b;4,5-b']difuran-4-yl)-2-mmoniopropane 2-carboxy-4,6-dinitrophenolate, C13H13BrNO2+ C7H3N2O7- forms hydrogen-bonded cation-anion chain substructures comprising undulating head-to-tail anion chains formed through C(8) carboxyl O-H...O(nitro) associations and incorporating the aminium groups of the cations. The intra-chain cation-anion hydrogen-bonding associations feature proximal cyclic R33(8) interactions involving both a N+-H...O(phenolate) and the carboxyl O--H...O(nitro)associations. Also present are aromatic pi-pi ring interactions [minimum ring centroid separation, 3.566(2)A; inter-plane dihedral angle, 5.13(1)deg]. A lateral hydrogen-bonding interaction between the third aminium proton and a carboxyl O acceptor link the chain substructures giving a two-dimensional sheet structure. This determination represents the first of any form of this compound and confirms that it has the (R) absolute configuration. The atypical crystal stability is attributed both to the hydrogen-bonded chain substructures provided by the anions, which accommodate the aminium proton-donor groups of the cations and give cross-linking, and to the presence of cation--anion aromatic ring pi-pi interactions.

4-(4-Nitrobenzyl)pyridinium 5-nitrosalicylate

In the title salt, C12H11N2O2+·C7H4NO5-, the cations and anions interact through asymmetric cyclic pyridinium-carboxylate N-HO,O' hydrogen-bonding associations [graph set R12(4)], giving discrete heterodimers having weak cation-anion - aromatic ring interactions [minimum ring centroid separation = 3.7116 (9) Å]