On methods of defuzzification of parametrically represented fuzzy numbers

A comparative analysis of such methods of defuzzification of fuzzy numbers as WABL (Weighted Averaging Based on Levels), centroid, and mean of maxima (MOM) is presented in the study. Analytic formulas are presented for calculating the defuzzification values for parametrically represented fuzzy numbers of triangular and trapezoidal form.     

Ensemble of multiple instance classifiers for image re-ranking

Text-based image retrieval may perform poorly due to the irrelevant and/or incomplete text surrounding the images in the web pages. In such situations, visual content of the images can be leveraged to improve the image ranking performance. In this paper, we look into this problem of image re-ranking and propose a system that automatically constructs multiple candidate “multi-instance bags (MI-bags)”, which are likely to contain relevant images. These automatically constructed bags are then utilized by ensembles of Multiple Instance Learning (MIL) classifiers and the images are re-ranked according to the final classification responses. Our method is unsupervised in the sense that, the only input to the system is the text query itself, without any user feedback or annotation. The experimental results demonstrate that constructing multiple instance bags based on the retrieval order and utilizing ensembles of MIL classifiers greatly enhance the retrieval performance, achieving on par or better results compared to the state-of-the-art.     

Control of underactuated planar pronking through an embedded spring-mass Hopper template

Autonomous use of legged robots in unstructured, outdoor settings requires dynamically dexterous behaviors to achieve sufficient speed and agility without overly complex and fragile mechanics and actuation. Among such behaviors is the relatively under-studied pronking (aka. stotting), a dynamic gait in which all legs are used in synchrony, usually resulting in relatively slow speeds but long flight phases and large jumping heights. Instantiations of this gait for robotic systems have been mostly limited to open-loop strategies, suffering from severe pitch instability for underactuated designs due to the lack of active feedback. However, both the kinematic simplicity of this gait and its dynamic nature suggest that the Spring-Loaded Inverted Pendulum model (SLIP) would be a good basis for the implementation of a more robust feedback controller for pronking. In this paper, we describe how template-based control, a controller structure based on the embedding of a simple dynamical “template” within a more complex “anchor” system, can be used to achieve very stable pronking for a planar, underactuated hexapod robot. In this context, high-level control of the gait is regulated through speed and height commands to the SLIP template, while the embedding controller ensures the stability of the remaining degrees of freedom. We use simulation studies to show that unlike existing open-loop alternatives, the resulting control structure provides explicit gait control authority and significant robustness against sensor and actuator noise.     

An assessment of total RMR classification system using unified simulation model based on artificial neural networks

Engineering design has great importance in the cost and safety of engineering structures. Rock mass rating (RMR) system has become a reliable and widespread pre-design system for its ease of use and variety in engineering applications such as tunnels, foundations, and slopes. In RMR system, six parameters are employed in classifying a rock mass: uniaxial compressive strength of intact rock material (UCS), rock quality designation (RQD), spacing of discontinuities (SD), condition of discontinuities (CD), condition of groundwater (CG), and orientation of discontinuities (OD). The ratings of the first three parameters UCS, RQD, and SD are determined via graphic readings where the last three parameters CD, CG, and OD are estimated by the tables that are composed of interval valued linguistic expressions. Because of these linguistic expresions, the estimated rating values of the last three become fuzzy especially when the related conditions are close to border of any two classes. In such cases, these fuzzy situations could lead up incorrect rock class estimations. In this study, an empirical database based on the linguistic expressions for CD, CG, and OD is developed for training Artificial Neural Network (ANN) classifiers. The results obtained from graphical readings and ANN classifiers are unified in a simulation model (USM). The data obtained from five different tunnels, which were excavated for derivation purpose, are used to evaluate classification results of conventional method and proposed model. Finally, it is noted that more accurate and realistic ratings are reached by means of proposed model.     

Parallel force measurement with a polymeric microbeam array using an optical microscope and micromanipulator

An image analysis method and its validation are presented for tracking the displacements of parallel mechanical force sensors. Force is measured using a combination of beam theory, optical microscopy, and image analysis. The primary instrument is a calibrated polymeric microbeam array mounted on a micromanipulator with the intended purpose of measuring traction forces on cell cultures or cell arrays. One application is the testing of hypotheses involving cellular mechanotransduction mechanisms. An Otsu-based image analysis code calculates displacement and force on cellular or other soft structures by using edge detection and image subtraction on digitally captured optical microscopy images. Forces as small as 250+/-50 nN and as great as 25+/-2.5 microN may be applied and measured upon as few as one or as many as hundreds of structures in parallel. A validation of the method is provided by comparing results from a rigid glass surface and a compliant polymeric surface.     

An adaptive signal compression system with pre-specified reconstruction quality and compression rate

Two essential properties of a signal compression method are the compression rate and the distance between the original signal and the reconstruction from the compressed signal. These two properties are used to assess the performance and quality of the method. In a recent work [B. Tümer, B. Demir?z, Lecture Notes in Computer Science-Computer and Information Sciences, volume 2869, chapter Signal Compression Using Growing Cell Structures: A Transformational Approach, Springer Verlag, 2003, pp. 952-959], an adaptive signal compression system (ACS) is presented which defines the performance of the system as a function of the system complexity, system sensitivity and data size. For a compression method, it is desirable to formulate the performance of the system as a function of the system complexity and sensitivity to optimize the performance of the system. It would be further desirable to express the reconstruction quality in terms of the same system parameters so as to know up front what compression rate to end up with for a specific reconstruction quality. In this work, we modify ACS such that the modified ACS (MACS) estimates the reconstruction quality for a given system complexity and sensitivity. Once this relation is identified it is possible to optimize either compression rate or reconstruction quality with respect to system sensitivity and system complexity while limiting the other one.     

Rheological,Thermodynamic, and Gas Solubility Properties of Phenylacetic Acid‐Based Deep Eutectic Solvents

Choline chloride + phenylacetic acid‐based deep eutectic solvents are studied. Their most relevant experimental physicochemical properties at different mixing ratios together with the CO₂ solubility data obtained in wide pressure and temperature ranges are reported. The presented materials exhibit a significant CO₂ capture performance with low corrosion effect when compared with the most common amine‐based CO₂ capture agents. Detailed rheological measurements are carried out and various models are applied to describe the dynamic flow behavior of the solvents. The CO₂ absorption mechanism is evaluated by studying the behavior of the liquid gas and interface. Due to the advantages of low cost, nontoxicity, and favorable physical properties, these solvents are an environmentally promising alternative for effective CO₂ capture technological applications.