Group Decision Making by Using Incomplete Fuzzy Preference Relations Based on T‐Consistency and the Order Consistency

The existing group decision making techniques may not satisfy the order consistency for aggregation in some cases. The algorithm proposed in this paper overcomes the weaknesses of the existing techniques. The method determines the unknown preferences for group decision making in such a manner that the resulting matrix is T‐consistent and order consistent simultaneously.     

Mixed formulation of nonlinear beam on foundation elements

This paper presents an inelastic element for the analysis of beams on foundations. The element is derived from a two-field mixed formulation with independent approximation of forces and displacements. The state determination algorithm for the implementation of the element in a general purpose nonlinear finite element analysis program is presented and its stability characteristics are discussed. Numerical studies are performed to compare the model with the classical displacement formulation. The studies confirm the superiority of the proposed model in describing the inelastic behavior of beams on foundations.     

Pad effects on material-removal rate in chemical-mechanical planarization

The role of a porous pad in controlling material-removal rate (MRR) during the chemical-mechanical planarization (CMP) process has been studied numerically. The numerical results are used to develop a phenomenological model that correlates the forces on each individual abrasive particle to the applied nominal pressure. The model provides a physical explanation for the experimentally observed domains of pressure-dependent MRR, where the pad deformation controls the load sharing between active-abrasive particles and direct pad-wafer contact. The predicted correlations between MRR and slurry characteristics, i.e., particle size and concentration, are in agreement with experimentally measured trends reported by Ouma¹ and Izumitani.²     

A study of neutron and gamma radiation effects on transmission of various types of glasses, optical coatings, cemented optics and fiber

A study of radiation effects on various types of glasses, dielectric optical coatings, cemented optics and fiber was undertaken with a view to select them for extreme radiation environments. Samples were exposed to different radiation doses in the Pakistan Research Reactor-I (PARR-I) for neutron and Cobalt 60 source for gamma irradiation. Transmissions were measured before and after irradiation. The dielectric coatings were subjected to additional tests (adhesion, abrasion and humidity, etc.) as per MIL-M-13508C and MIL-C-675C. All 15 glasses studied showed varying amounts of transmission loss as expected, with negligible degradation for three types. Recovery of transmissions with time/ageing was also studied, with more or less complete recovery with temperature annealing. A faster bleaching of darkened/brown glasses was achieved by using UV lamps or UV laser. The dielectric coatings (HR, AR) and one of the two commercial optical cements showed excellent resistance to neutrons and gamma radiations, and could be good candidates for the fabrication and utilization of optical components in extreme radiation environments. The data allowed several Chinese glasses to be studied for the first time.     

Visual tracking using convolutional features with sparse coding

Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial...     

Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.     

Ambient‐cured polyesteramide‐based anticorrosive coatings from linseed oil—A sustainable resource

Ambient‐cured polyesteramide (APEA) coating resin synthesized from dihydroxy fatty amide obtained from linseed oil, a sustainable resource, and poly(styrene‐co‐maleic anhydride), a bifunctional acid component, was found to exhibit improved physicomechanical and anticorrosive properties. The structural elucidation of APEA resin has been carried out by FTIR, ¹H‐NMR, and ¹³C‐NMR spectroscopies. The physicomechanical and chemical resistance properties were investigated by standard methods. The corrosion resistance performance was evaluated in acid, alkali, and organic solvent. The thermal behavior was studied by TGA technique. A comparative study of these properties of APEA with reported baked polyesteramide (PEA) coatings was carried out. A remarkable improvement in the drying property of APEA was observed. The APEA coatings also showed improved physicomechanical and anticorrosive properties as compared to the baked PEA coatings. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1818–1824, 2005     

Vision Based Neuro-Fuzzy Controller for a Two Axes Gimbal System with Small UAV

This paper presents the development of a vision-based neuro-fuzzy controller for a two axes gimbal system mounted on a small Unmanned Aerial Vehicle (UAV). The controller uses vision-based object detection as input and generates pan and tilt motion and velocity commands for the gimbal in order to keep the interest object at the center of the image frame. A readial basis function based neuro-fuzzy system and a learning algorithm is developed for the controller to address the dynamic and non-linear characteristics of the gimbal movement. The controller uses two separate, but identical radial basis function networks, one for pan and one for tilt motion of the gimbal. Each system is initialized with a fixed number of neurons that act as rules basis for the fuzzy inference system. The membership functions and rule strengths are then adjusted with the feedback from the visual tracking system. The controller is trained off-line until a desired error level is achieved. Training is then continued on-line to allow the system to accommodate air speed changes. The algorithm learns from the error computed from the detected position of the object in image frame and generates position and velocity commands for the gimbal movement. Several tests including lab tests and actual flight tests of the UAV have been carried out to demonstrate the effectiveness of the controller. Test results show that the controller is able to converge effectively and generate accurate position and velocity commands to keep the object at the center of the image frame.     

Fuzzy decision support system for fertilizer

Fuzzy geographic information systems is a newly emerging field of computational intelligence. It combines fuzzy logic with spatial context. Most of the natural phenomena are fuzzy in nature. They show a degree of uncertainty or vagueness in their extent and attribute, which cannot be expressed by a crisp value. Agriculture is one of the fields of the spatial domain that needs to be described in fuzzy terms. Fertilizer is a key input for the agriculture sector. In this article, the spatial surfaces of fertilizers are developed for the wheat crop using a fuzzy decision support system. The algorithm of our system takes soil nutrients and cropping time as input, applies fuzzy logic on the input values, defuzzifies the fuzzy output to crisp value, and generates a fertilizer surface. The resultant output surface of fertilizer describes the amount of fertilizer needed to cultivate a specific crop in a specified area. The complexity of our algorithm is \(O(mnr)\) , where \(m\) is the height of the raster, \(n\) is the width of the raster, and \(r\) is the number of expert rules.