A new deep intuitionistic fuzzy time series forecasting method based on long short-term memory

The Journal of Supercomputing - In recent years, deep artificial neural networks can have better forecasting performance than many other artificial neural networks. The long short-term memory...     

Maximization of total surface area of Pt-SnO<Subscript>2</Subscript>/Al<Subscript>2</Subscript>O<Subscript>3</Subscript> catalyst by the Taguchi method

The maximization of the total surface area of Pt-SnO₂/Al₂O₃ catalyst was studied by using the Taguchi method of experimental design. The catalysts were prepared by sol-gel method. The effects of HNO₃, H₂O and aluminum nitrate concentrations and the stirring rate on the total surface area were studied at three levels of each. L₉ orthogonal array leading nine experiments was used in the experimental design. The parameter levels that give maximum total surface area were determined and experimentally verified. In the range of conditions studied it was found that, medium levels of HNO₃ and H₂O concentration and lower levels of aluminum nitrate concentration and stirring rate maximize the total surface area.     

Improved phase performance for rotman lens

Rotman lenses are used to obtain multiple beams from a single array. Although the beams produced by the feed antennas at focal points have no path length errors, the beams produced by feed antennas at off focal points may have large path length errors. These path length errors cause deterioration in the multiple beams. In this article, two novel methods are introduced to obtain feed curves which reduce the path length errors of off focal feed points significantly, compared with the commonly used circular and elliptical feed curves. The first method obtains feed curve points based on having zero path length error at three chosen points of the radiating array for each beam direction. The second method uses the particle swarm optimization method for obtaining optimum feed points for each beam direction. The results show that there is a very significant drop in the level of the maximum path length errors (in the order of about 1:4). © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE 23: 634–638, 2013.     

A multiperiod set covering location model for dynamic redeployment of ambulances

Emergency medical service (EMS) providers continually seek ways to improve system performance particularly the response time to incidents. The demand for ambulances fluctuate throughout the week, depending on the day of week, and even the time of day, therefore EMS operators can improve system performance by dynamic relocation/redeployment of ambulances in response to fluctuating demand patters. The objective of the model is to determine the minimum number of ambulances and their locations for each time cluster in which significant changes in demand pattern occur while meeting coverage requirement with a predetermined reliability. The model is further enhanced by calculating ambulance specific busy probabilities and validated by a comprehensive simulation model. Computational results on experimental data sets and data from an EMS agency are provided.     

Prosthetic Hand Finger Control Using Fuzzy Sliding Modes

In order to improve the life quality of amputees, providing approximate manipulation ability of a human hand to that of a prosthetic hand is considered by many researchers. In this study, a biomechanical model of the index finger of the human hand is developed based on the human anatomy. Since the activation of finger bones are carried out by tendons, a tendon configuration of the index finger is introduced and used in the model to imitate the human hand characteristics and functionality. Then, fuzzy sliding mode control where the slope of the sliding surface is tuned by a fuzzy logic unit is proposed and applied to have the finger model to follow a certain trajectory. The trajectory of the finger model, which mimics the motion characteristics of the human hand, is pre-determined from the camera images of a real hand during closing and opening motion. Also, in order to check the robust behaviour of the controller, an unexpected joint friction is induced on the prosthetic finger on its way. Finally, the resultant prosthetic finger motion and the tendon forces produced are given and results are discussed.     

Limited Scale-Free Overlay Topologies for Unstructured Peer-to-Peer Networks

In unstructured peer-to-peer (P2P) networks, the overlay topology (or connectivity graph) among peers is a crucial component in addition to the peer/data organization and search. Topological characteristics have profound impact on the efficiency of a search on such unstructured P2P networks, as well as other networks. A key limitation of scale-free (power-law) topologies is the high load (i.e., high degree) on a very few number of hub nodes. In a typical unstructured P2P network, peers are not willing to maintain high degrees/loads as they may not want to store a large number of entries for construction of the overlay topology. Therefore, to achieve fairness and practicality among all peers, hard cutoffs on the number of entries are imposed by the individual peers, which limits scale-freeness of the overall topology, hence limited scale-free networks. Thus, it is expected that the efficiency of the flooding search reduces as the size of the hard cutoff does. We investigate the construction of scale-free topologies with hard cutoffs (i.e., there are not any major hubs) and the effect of these hard cutoffs on the search efficiency. Interestingly, we observe that the efficiency of normalized flooding and random walk search algorithms increases as the hard cutoff decreases.     

Using fuzzy inference system for architectural space analysis

Though architectural space is the main source and the only indispensable component of any architectural construction, in many cases its boundaries are uncertain, leading intuitive spatial design. Creating a mathematical model of architectural space with concrete results will offer many possibilities for design process in analysing spatial organization, independently from in architect's experience and intuitions. This paper presents a fuzzy inference system based spatial analysis model for spatial analysis for architectural design which brings many advantages to design process. The aim of this article is to investigate the potential of a fuzzy system with a Mamdami inference engine, considering different numbers of membership functions. Two venues have been selected and the fuzzy inference system based spatial analysis model is applied. For better judgement, outcomes of the model have been compared to depthmap analysis model. The results of the model indicate that fuzzy inference system based spatial analysis model performs very well, even with the limited and imprecise data. Such prototype can evolve into a tool for identifying spatial formations for improvements during the architectural design process.     

Visualization of fibrous and thread-like data

Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization since they tend to be densely packed in small volumes of tissue. This makes it difficult for an observer to interpret useful patterns from the data or trace individual fibers. In this paper we describe several methods for dealing with large amounts of thread-like data, such as data sets collected using Knife-Edge Scanning Microscopy (KESM) and Serial Block-Face Scanning Electron Microscopy (SBF-SEM). These methods allow us to collect volumetric data from embedded samples of whole-brain tissue. The neuronal and microvascular data that we acquire consists of thin, branching structures extending over very large regions. Traditional visualization schemes are not sufficient to make sense of the large, dense, complex structures encountered. In this paper, we address three methods to allow a user to explore a fiber network effectively. We describe interactive techniques for rendering large sets of neurons using self-orienting surfaces implemented on the GPU. We also present techniques for rendering fiber networks in a way that provides useful information about flow and orientation. Third, a global illumination framework is used to create high-quality visualizations that emphasize the underlying fiber structure. Implementation details, performance, and advantages and disadvantages of each approach are discussed.