An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis

Clustering is a popular data analysis and data mining technique. A popular technique for clustering is based on k-means such that the data is partitioned into K clusters. However, the k-means algorithm highly depends on the initial state and converges to local optimum solution. This paper presents a new hybrid evolutionary algorithm to solve nonlinear partitional clustering problem. The proposed hybrid evolutionary algorithm is the combination of FAPSO (fuzzy adaptive particle swarm optimization), ACO (ant colony optimization) and k-means algorithms, called FAPSO-ACO–K, which can find better cluster partition. The performance of the proposed algorithm is evaluated through several benchmark data sets. The simulation results show that the performance of the proposed algorithm is better than other algorithms such as PSO, ACO, simulated annealing (SA), combination of PSO and SA (PSO–SA), combination of ACO and SA (ACO–SA), combination of PSO and ACO (PSO–ACO), genetic algorithm (GA), Tabu search (TS), honey bee mating optimization (HBMO) and k-means for partitional clustering problem.     

Attention control with reinforcement learning for face recognition under partial occlusion

In this paper a new method for handling occlusion in face recognition is presented. In this method the faces are partitioned into blocks and a sequential recognition structure is developed. Then, a spatial attention control strategy over the blocks is learned using reinforcement learning. The outcome of this learning is a sorted list of blocks according to their average importance in the face recognition task. In the recall mode, the sorted blocks are employed sequentially until a confident decision is made. Obtained results of various experiments on the AR face database demonstrate the superior performance of proposed method as compared with that of the holistic approach in the recognition of occluded faces.     

Optimal Local Basis: A Reinforcement Learning Approach for Face Recognition

This paper presents a novel learning approach for Face Recognition by introducing Optimal Local Basis. Optimal local bases are a set of basis derived by reinforcement learning to represent the face space locally. The reinforcement signal is designed to be correlated to the recognition accuracy. The optimal local bases are derived then by finding the most discriminant features for different parts of the face space, which represents either different individuals or different expressions, orientations, poses, illuminations, and other variants of the same individual. Therefore, unlike most of the existing approaches that solve the recognition problem by using a single basis for all individuals, our proposed method benefits from local information by incorporating different bases for its decision. We also introduce a novel classification scheme that uses reinforcement signal to build a similarity measure in a non-metric space. Experiments on AR, PIE, ORL and YALE databases indicate that the proposed method facilitates robust face recognition under pose, illumination and expression variations. The performance of our method is compared with that of Eigenface, Fisherface, Subclass Discriminant Analysis, and Random Subspace LDA methods as well.     

Creating corroborated crisis reports from social media data through formal concept analysis

During a crisis citizens reach for their smart phones to report, comment and explore information surrounding the crisis. These actions often involve social media and this data forms a large repository of real-time, crisis related information. Law enforcement agencies and other first responders see this information as having untapped potential. That is, it has the capacity extend their situational awareness beyond the scope of a usual command and control centre. Despite this potential, the sheer volume, the speed at which it arrives, and unstructured nature of social media means that making sense of this data is not a trivial task and one that is not yet satisfactorily solved; both in crisis management and beyond. Therefore we propose a multi-stage process to extract meaning from this data that will provide relevant and near real-time information to command and control to assist in decision support. This process begins with the capture of real-time social media data, the development of specific LEA and crisis focused taxonomies for categorisation and entity extraction, the application of formal concept analysis for aggregation and corroboration and the presentation of this data via map-based and other visualisations. We demonstrate that this novel use of formal concept analysis in combination with context-based entity extraction has the potential to inform law enforcement and/or humanitarian responders about on-going crisis events using social media data in the context of the 2015 Nepal earthquake.     

Disturbance and recovery of trunk mechanical and neuromuscular behaviours following prolonged trunk flexion: influences of duration and external load on creep-induced effects

Trunk flexion results in adverse mechanical effects on the spine and is associated with a higher incidence of low back pain. To examine the effects of creep deformation on trunk behaviours, participants were exposed to full trunk flexion in several combinations of exposure duration and external load. Trunk mechanical and neuromuscular behaviours were obtained pre- and post-exposure and during recovery using sudden perturbations. Intrinsic trunk stiffness decreased with increasing flexion duration and in the presence of the external load. Recovery of intrinsic stiffness required more time than the exposure duration and was influenced by exposure duration. Reflexive trunk responses increased immediately following exposure but recovered quickly (～2.5 min). Alterations in reflexive trunk behaviour following creep deformation exposures may not provide adequate compensation to allow for complete recovery of concurrent reductions in intrinsic stiffness, which may increase the risk of injury due to spinal instability. STATEMENT OF RELEVANCE: An increased risk of low back injury may result from flexion-induced disturbances to trunk behaviours. Such effects, however, appear to depend on the type of flexion exposure, and have implications for the design of work involving trunk flexion.     

Fast evolving neuro-fuzzy model and its application in online classification and time series prediction

A strategy for improving speed of the previously proposed evolving neuro-fuzzy model (ENFM) is presented in this paper to make it more appropriate for online applications. By considering a recursive extension of Gath?CGeva clustering, the ENFM takes advantage of elliptical clusters for defining validity region of its neurons which leads to better modeling with less number of neurons. But this necessitates the computing of reverse and determinant of the covariance matrices which are time consuming in online applications with large number of input variables. In this paper a strategy for recursive estimation of singular value decomposition components of covariance matrices is proposed which converts the burdensome computations to calculating reverse and determinant of a diagonal matrix while keeping the advantages of elliptical clusters. The proposed method is applied to online detection of epileptic seizures in addition to prediction of Mackey?CGlass time series and modeling a time varying heat exchanger. Simulation results show that required time for training and test of fast ENFM is far less than its basic model. Moreover its modeling ability is similar to the ENFM which is superior to other online modeling approaches.     

Vacuum desorption of gases from inorganic solvents with various boiling points

The vacuum desorption of gases from inorganic solvents with low and high boiling points is reported. A thin-film evaporator consisting of regular tubular packing elements is considered. A laminar downward cocurrent flow of liquid and vapor is analyzed. General theoretical propositions are illustrated by the example of the desorption of simple gases from lower alcohols (methanol, ethanol) and liquid naphthalene, as well as by the example of removing the products of ester decomposition from esters at high temperatures.     

Control of Hybrid Active Power Filter Based on Switching Function Coefficients

A pulse width modulation (PWM)-based control method for a three-level, four-wire neutral point clamped (NPC) inverter employed in a hybrid active power filter (HAPF) is proposed in this paper. The control method is based on switching function coefficients (SFCs) for harmonic compensation. An interior loop is also proposed for control and balancing of the DC-link voltages. In the proposed control system, one carrier signal is employed in the PWM unit in order to simplify its hardware as compared with traditional PWMs. Based on Fourier decomposition technique, mathematical analysis of the proposed control method is also presented. To decrease the NPC inverter rated power, passive power filters (PPFs) are designed to eliminate fifth and seventh order harmonic currents and to compensate source reactive currents. The proposed control system is implemented by a digital signal processing (DSP) in a laboratory prototype. The experimental results confirmed the validity of the proposed control method in compensation of harmonic currents under non-linear conditions     

Drawing in Time: Processes of Design and Fabrication

Drawing embeds time within itself, notating changes in space and duration. For Babak Bryan and Henry Grosman , founding partners of BanG studio in Long Island City, New York: ‘The drawing is a result of process, but it also describes process.’ It is only through this temporal practice that an essential connection is developed between drawing and building. With the widespread adoption of building information modelling (BIM), linear graphic representation finds itself in crisis, challenged by the static inertia of the model. As Bryan and Grosman describe, the well-crafted drawing remains essential to their studio's approach informing the method of ‘making and remaking’.