GAN–SOM: A clustering framework with SOM-similar network based on deep learning

Since an increasing amount of data is generated and collected in real life, clustering is more frequently applied to process these unlabeled data in practical problems. Due to the simple similarity measure of conventional clustering methods, they are unable to achieve good performance on current big data. With the popularity of deep learning, deep clustering has been developed in recent years and obtained remarkable results. However, they have complex architecture and consume numerous computational resources, which goes against the migration to edge devices. Therefore, methods with low cost are required to satisfy edge computing, which is the trend of development. In this paper, we propose GAN–SOM as a new architecture for clustering based on deep learning. A SOM-similar network is designed to simultaneously implement encoding and clustering purposes on data samples, which is jointly trained with a GAN to optimizes a new defined clustering loss. We also utilize self-attention mechanism and spectral normalization in the GAN architecture to enhance effects of generated data, which aims to achieve better clustering results. The experimental results compared with other clustering baselines with deep learning verify that our method maintains high clustering metrics while saving computational cost significantly.

     

A novel temporal protein complexes identification framework based on density–distance and heuristic algorithm

Neural Computing and Applications - The construction of dynamic protein–protein interaction networks is affected by cell tissue and its biological function, and the identification of protein...     

A comparison of face and facial feature detectors based on the Viola�CJones general object detection framework

The human face provides useful information during interaction; therefore, any system integrating Vision-Based Human Computer Interaction requires fast and reliable face and facial feature detection. Different approaches have focused on this ability but only open source implementations have been extensively used by researchers. A good example is the Viola–Jones object detection framework that particularly in the context of facial processing has been frequently used. The OpenCV community shares a collection of public domain classifiers for the face detection scenario. However, these classifiers have been trained in different conditions and with different data but rarely tested on the same datasets. In this paper, we try to fill that gap by analyzing the individual performance of all those public classifiers presenting their pros and cons with the aim of defining a baseline for other approaches. Solid comparisons will also help researchers to choose a specific classifier for their particular scenario. The experimental setup also describes some heuristics to increase the facial feature detection rate while reducing the face false detection rate.     

Modeling Robot “Psycho-Physical” State and Reactions – A New Option in Human–Robot Communication Part 2: Modeling and Simulation

This part of the paper examines numerically the possibility of modeling robot fatigue being representative of a human psychophysical state that can be applied to robots. Temperatures of driving motors are suggested as analogs to fatigue in muscles. Simulation of robot behavior is performed on a typical human task, namely handwriting. Three phases of task execution, characteristic for humans, are observed, i.e. regular motion, reconfiguration after symptoms of fatigue, and degeneration caused by the too long, hard work.     

Modeling Robot “Psycho-Physical” State and Reactions – A New Option in Human–Robot Communication Part 1: Concept and Background

Man–machine communication had been recognized a long time ago as a significant issue in the implementation of automation. It influences the machine effectiveness through direct costs for operator training and through more or less comfortable working conditions. The solution for the increased effectiveness might be found in user-friendly human–machine interface. In robotics, the question of communication and its user-friendliness is becoming even more significant. It is no longer satisfactory that a communication can be called human–machine interface, since one must see robots as future collaborators, service workers, and probably personal helpers. So, a new way of communication is needed. This paper starts from the fact that a variety of unconventional ways of communication is being explored: speech communication, handwriting, and facial mimicry. Speech recognition and generation, apart from its potentially strong impact to human–robot interface, is out of the scope of this study, and the same holds for handwriting. The facial mimicry and the wider field of robot emotion lead to a new way of communication that can be called gestural language. We may say that our research matches such a wide notion. However, there is an important specificity of our approach. Previous works in this field looked at facial and gestural expressions of emotions and messages as actually voluntary activities. They were induced by some situations, but such situations had to be recognized after which the appropriate preprogrammed reaction followed. Thus, some expert system or other artificial intelligence system were applied. The current study explores the conditional reactions that are chemically based. Human psycho-physical states like fear, stress and especially fatigue follow from complex chemical processes. Such states cannot be voluntarily controlled. They are not expressed through some specific mimicry or body movement, but they influence all movements. Any motion intended to accomplish some task will be changed, thus sending a message to the neighborhood. This change can be observed, and so the message is received. For processes of this kind and their resembling, we prefer using the term modeling psycho-physical states. Among various states interesting for application in robots, the present study concentrates on fatigue, which is a good example for the initial research. The first part of the paper explains the concept and the background, while the second part provides numerical justification.     

A multi-expert system for ranking patents: An approach based on fuzzy pay-off distributions and a TOPSIS–AHP framework

The aim of this paper is to introduce a decision support system that ranks patents based on multiple expert evaluations. The presented approach starts with the creation of three value scenarios for each considered patent by each expert. These are used for the construction of individual fuzzy pay-off distribution functions for the patent value; a consensual fuzzy pay-off distribution is then determined starting from the individual distributions. Possibilistic moments are calculated from the consensus pay-off distribution for each patent and used in ranking them with TOPSIS. It is further showed how the analytic hierarchy process (AHP) can be used to include additional decision variables into the patent selection, thus allowing for a two-tier decision making process. The system is illustrated with a numerical example and the usability of the system and the combination of methods it includes for patent portfolio selection in the real world context is discussed.     

Fuzzy control of neuromuscular block during general anesthesia—system design,development and implementation

We present a system for fuzzy control of neuromuscular block during general anesthesia. The system (Relax 2005) was clinically used in 50 patients undergoing neurosurgical intervention. From the medical point of view, the benefit of using this system is twofold. First, the workload of the anesthetist is reduced. Second, the efficacy of muscle relaxant administration is improved. As far as medical costs are concerned, using the system decreases the expenditure on muscle relaxants. We describe the design, development, and implementation of the system as well as the results of clinical tests.     

A conflict–congestion model for pedestrian–vehicle mixed evacuation based on discrete particle swarm optimization algorithm

A simulation model based on temporal–spatial conflict and congestion for pedestrian–vehicle mixed evacuation has been investigated. Assuming certain spatial behaviors of individuals during emergency evacuation, a discrete particle swarm optimization with neighborhood learning factor algorithm has been proposed to solve this problem. The proposed algorithm introduces a neighborhood learning factor to simulate the sub-group phenomenon among evacuees and to accelerate the evacuation process. The approach proposed here is compared with methods from the literatures, and simulation results indicate that the proposed algorithm achieves better evacuation efficiency while maintaining lower pedestrian–vehicle conflict levels.     

A cloud computing framework for analysis of agricultural big data based on Dempster–Shafer theory

The Journal of Supercomputing - This paper aims to extract optimal location for cultivating orange trees. In order to reach this goal, a combination of Dempster-Shafer theory (DST) and cloud...     

A numerical algorithm based on a variational iterative approximation for the discrete Hamilton–Jacobi–Bellman (HJB) equation

This paper presents a numerical algorithm based on a variational iterative approximation for the Hamilton–Jacobi–Bellman equation, and a domain decomposition technique based on this algorithm is also studied. The convergence theorems have been established. Numerical results indicate the efficiency and accuracy of the methods.     

A note on stability analysis of 2-D linear discrete systems based on the Fornasini–Marchesini second model: Stability with asymmetric Lyapunov matrix

A recently reported Lyapunov based criterion (Singh (2014) [7]) for the asymptotic stability of two-dimensional (2-D) linear discrete systems described by the Fornasini–Marchesini second local state-space (FMSLSS) model is reviewed. It is established in this paper that, despite utilizing a more general Lyapunov matrix, Singh's criterion will never lead to an enhanced stability region in the parameter-space as compared to that obtainable via Hinamoto–Lu's criterion.     

Sheet metal forming global control system based on artificial vision system and force–acoustic sensors

Forming processes are manufacturing processes based on deformation of raw material applying pressure in one or several stages until getting the final product. This process depends on many factors, e.g. process parameters, material properties or lubrication, leading to possible defective parts. Correct forming of parts is very important as any defective part may result in big economical losses, e.g. the return of a complete set of parts or the loss of some clients. Thus, in our European Craft Pro2Control project, leading German, French, Italian and Spanish companies, universities and forming industries are defining and implementing a zero-defect forming control system, minimizing costs and maximizing the throughput of parts.     

Joining the blunt and the pointy end of the spear: towards a common framework of joint action,human–machine cooperation,cooperative guidance and control,shared, traded and supervisory control

To introduce this special issue of shared and cooperative control, we will look into history of tools in cooperation between humans and aim to unify the plethora of related concepts and definitions that have been proposed in recent years, such as shared control, human–machine cooperation and cooperative guidance and control. Concretely, we provide definitions to relate these concepts and sketch a unifying framework of shared and cooperative control that sees the different concepts as different perspectives or foci on a common design space of shared intentionality, control and cooperation between humans and machines. One working hypothesis which the article explores is that shared control can be understood as cooperation at the control layer, while human–machine cooperation can include shared control, but can also extend towards cooperation at higher layers, e.g., of guidance and navigation, of maneuvers and goals. The relationship between shared control and human–machine cooperation is compared to the relationship between the sharp, pointy tip and the (blunt) shaft of a spear. Shared control is where cooperation comes sharply into effect at the control layer, but to be truly effective it should be supported by cooperation on all layers beyond the operational layer, e.g., on the tactical and strategic layer. A fourth layer addresses the meta-communication about the cooperation and supports the other three layers in a traversal way.

     

Effects of agricultural quad bike driving on postural control during static,dynamic and functional tasks – A field study

BackgroundDriving a quad bike in a rural occupational setting is likely to expose the driver to various physical stimuli including whole-body vibration (WBV). These exposures may be linked to post-driving postural alterations which in turn could lead to an increased risk of spinal injury while undertaking manual material handling activities immediately following driving or falls while exiting from a vehicle.PurposeThe purpose of this study was to use a battery of postural tasks namely; bipedal and unipedal stance, limits of stability (LOS) and lifting task to assess how quad bike driving alters the postural control (PC) in a group of rural workers.MethodsThe PC, determined from centre of pressure (COP) displacements in a group of rural workers (n = 34), was evaluated at three time (T) periods, once (T-I) before the 30 min quad bike driving session on a typical New Zealand farm terrain and twice (T-II and T-III) immediately following driving, each time period lasted approximately 10 min later.ResultsThe results demonstrated a significant (p < 0.05) increase and decrease in the magnitude of the COP measures for the lifting task and unipedal stance respectively during both T-II and T-III periods. However significant (p < 0.05) increase in the magnitude COP measures of bipedal stance, and increase in the maximal stability limits (LOS) were demonstrated only in the T-III.ConclusionsThese results demonstrate both immediate and sustained alterations in the PC following a period of occupational vehicle driving. Also, the results demonstrate both a worsening and improvement in postural control during the performance of a battery of tasks. Observed adverse or facilitatory postural effects will require further laboratory based investigations in order to determine how such disparity can best be explained or challenged.Relevance to industryThe findings will inform ergonomists about the potential risk involved in carrying out physically demanding occupational tasks following vehicle driving. This putative situation could be prevented by adopting behavioural strategies by drivers, and engineered interventions designed to reduce WBV exposure.     

Human–automation interaction for multiple robot control: the effect of varying automation assistance and individual differences on operator performance

In a human–automation interaction study, automation assistance level (AL) was investigated for its effects on operator performance in a dynamic, multi-tasking environment. Participants supervised a convoy of manned and unmanned vehicles traversing a simulated environment in three AL conditions, while maintaining situation awareness and identifying targets. Operators’ situation awareness, target detection performance, workload and individual differences were evaluated. Results show increasing AL generally improved task performance and decreased perceived workload, however, differential effects due to operator spatial ability and perceived attentional control were found. Eye-tracking measures were useful in parsing out individual differences that subjective measures did not detect. At the highest AL, participants demonstrated potentially complacent behaviour, indicating task disengagement.

Practitioner Summary: The effect of varying automation assistance level (AL) on operator performance on multiple tasks were examined in a within-subjects experiment. Findings indicated a moderate AL improved performance, while higher levels encouraged complacent behaviour. Effects due to individual differences suggest that effective AL depends on the underlying characteristics of the operator.     

CASQUS: A new simulation tool for coupled 3D finite element modeling of tectonic and surface processes based on ABAQUS™ and CASCADE

CASQUS is a numerical simulation tool to model the feedback mechanism between surface and tectonic processes. It includes the surface processes model CASCADE into the finite element solver ABAQUS/Standard?. The finite element method allows for geomechanical simulations of the subsurface with geometrically complex structures in 3D. Additionally, in the commercial software ABAQUS? various types of rheological behavior are already implemented. CASCADE simulates erosion and sedimentation as the combination of fluvial transport and hillslope processes. For the integration of CASCADE into ABAQUS/Standard? an Arbitrary Lagrangian–Eulerian modeling technique is used, which makes a coupled and automated simulation possible. Two benchmark models that are easy to reproduce demonstrate the functionality of CASQUS. Our tool aims at a better understanding of the feedback between mass redistribution at the Earth's surface and processes within a heterogenous subsurface, and at a quantification of the involved processes.     

Modeling,analysis and control of robot–object nonsmooth underactuated Lagrangian systems: A tutorial overview and perspectives

So-called robot–object Lagrangian systems consist of a class of nonsmooth underactuated complementarity Lagrangian systems, with a specific structure: an “object” and a “robot”. Only the robot is actuated. The object dynamics can thus be controlled only through the action of the contact Lagrange multipliers, which represent the interaction forces between the robot and the object. Juggling, walking, running, hopping machines, robotic systems that manipulate objects, tapping, pushing systems, kinematic chains with joint clearance, crawling, climbing robots, some cable-driven manipulators, and some circuits with set-valued nonsmooth components, belong this class. This article aims at presenting their main features, then many application examples which belong to the robot–object class, then reviewing the main tools and control strategies which have been proposed in the Automatic Control and in the Robotics literature. Some comments and open issues conclude the article.