A Survey: Clustering Ensembles Techniques

The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.

A New Evolutionary Algorithm for Cluster Analysis

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.

Optimization of Petroleum Refinery Configuration Design with Logic Propositions

This work concerns the topological optimization problem for determining the optimal petroleum refinery configuration. We are interested in further investigating and hopefully advancing the existing optimization approaches and strategies employing logic propositions to conceptual process synthesis problems. In particular, we seek to contribute to this increasingly exciting area of chemical process modeling by addressing the following potentially important issues: (a) how the formulation of design specifications in a mixed-logical-and-integer optimization model can be employed in a synthesis problem to enrich the problem representation by incorporating past design experience, engineering knowledge, and heuristics; and (b) how structural specifications on the interconnectivity relationships by space (states) and by function (tasks) in a superstructure should be properly formulated within a mixed-integer linear programming (MILP) model. The proposed modeling technique is illustrated on a case study involving the alternative processing routes of naphtha, in which significant improvement in the solution quality is obtained.

Multi-board Run-time Reconfigurable Implementation of Intrinsic Evolvable Hardware

A multi-board run-time reconfigurable (MRTR) system for evolvable hardware (EHW) is introduced with the aim to implement on hardware the bidirectional incremental evolution (BIE) method. The main features of this digital intrinsic EHW solution rely on the multi-board approach, the variable chromosome length management and the partial configuration of the reconfigurable circuit. These three features provide a high scalability to the solution. The design has been written in VHDL with the concern of not being platform dependant in order to keep a flexibility factor as high as possible. This solution helps tackling the problem of evolving complex task on digital configurable support.

Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.

In-Situ Monitoring the Thermal Forming of Glass and Si Foils for Space X-Ray Telescopes

We developed a non-contact method for the in-situ monitoring of the thermal forming of glass and Si foils to optimize the manufacture of mirrors for high-resolution space x-ray telescopes. Their construction requires precise and light-weight segmented optics with angular resolution better than 5 arcsec. We used 75x25 mm Desag D263 glass foils 0.75 mm thick and 0.6 mm thick Si foils. The glass foils were shaped by free slumping on a frame at viscosities in the range of 109.3-1012 dPa·s, the Si foils by forced slumping above 1000°C. Using a Nikon D80 digital camera, we took snapshots of a foil-s shape every 5 min during its isothermal heat treatment. The obtained results we can use for computer simulations. By comparing the measured and simulated data, we can more precisely define material properties of the foils and optimize the forming technology.

Dynamical Network Transmission of H1N1 Virus at the Local Level Transmission Model

A new strain of Type A influenza virus can cause the transmission of H1N1 virus. This virus can spread between the people by coughing and sneezing. Because the people are always movement, so this virus can be easily spread. In this study, we construct the dynamical network model of H1N1 virus by separating the human into five groups; susceptible, exposed, infectious, quarantine and recovered groups. The movement of people between houses (local level) is considered. The behaviors of solutions to our dynamical model are shown for the different parameters.

Analytic and Finite Element Solutions for Temperature Profiles in Welding using Varied Heat Source Models

Solutions for the temperature profile around a moving heat source are obtained using both analytic and finite element (FEM) methods. Analytic and FEM solutions are applied to study the temperature profile in welding. A moving heat source is represented using both point heat source and uniform distributed disc heat source models. Analytic solutions are obtained by solving the partial differential equation for energy conservation in a solid, and FEM results are provided by simulating welding using the ANSYS software. Comparison is made for quasi steady state conditions. The results provided by the analytic solutions are in good agreement with results obtained by FEM.

Performance Analysis of Learning Automata-Based Routing Algorithms in Sparse Graphs

A number of routing algorithms based on learning automata technique have been proposed for communication networks. How ever, there has been little work on the effects of variation of graph scarcity on the performance of these algorithms. In this paper, a comprehensive study is launched to investigate the performance of LASPA, the first learning automata based solution to the dynamic shortest path routing, across different graph structures with varying scarcities. The sensitivity of three main performance parameters of the algorithm, being average number of processed nodes, scanned edges and average time per update, to variation in graph scarcity is reported. Simulation results indicate that the LASPA algorithm can adapt well to the scarcity variation in graph structure and gives much better outputs than the existing dynamic and fixed algorithms in terms of performance criteria.

Exponential Stability of Numerical Solutions to Stochastic Age-Dependent Population Equations with Poisson Jumps

The main aim of this paper is to investigate the exponential stability of the Euler method for a stochastic age-dependent population equations with Poisson random measures. It is proved that the Euler scheme is exponentially stable in mean square sense. An example is given for illustration.

Exponential Stability and Periodicity of a Class of Cellular Neural Networks with Time-Varying Delays

The problem of exponential stability and periodicity for a class of cellular neural networks (DCNNs) with time-varying delays is investigated. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via the methods of variation parameters and inequality techniques. These conditions are represented by some blocks of the interconnection matrices. Compared with some previous methods, the method used in this paper does not resort to any Lyapunov function, and the results derived in this paper improve and generalize some earlier criteria established in the literature cited therein. Two examples are discussed to illustrate the main results.

Optimal Manufacturing Scheduling for Dependent Details Processing

The increasing competitiveness in manufacturing industry is forcing manufacturers to seek effective processing schedules. The paper presents an optimization manufacture scheduling approach for dependent details processing with given processing sequences and times on multiple machines. By defining decision variables as start and end moments of details processing it is possible to use straightforward variables restrictions to satisfy different technological requirements and to formulate easy to understand and solve optimization tasks for multiple numbers of details and machines. A case study example is solved for seven base moldings for CNC metalworking machines processed on five different machines with given processing order among details and machines and known processing time-s duration. As a result of linear optimization task solution the optimal manufacturing schedule minimizing the overall processing time is obtained. The manufacturing schedule defines the moments of moldings delivery thus minimizing storage costs and provides mounting due-time satisfaction. The proposed optimization approach is based on real manufacturing plant problem. Different processing schedules variants for different technological restrictions were defined and implemented in the practice of Bulgarian company RAIS Ltd. The proposed approach could be generalized for other job shop scheduling problems for different applications.

Almost Periodic Solution for a Food-limited Population Model with Delay and Feedback Control

In this paper, we consider a food-limited population model with delay and feedback control. By applying the comparison theorem of the differential equation and constructing a suitable Lyapunov functional, sufficient conditions which guarantee the permanence and existence of a unique globally attractive positive almost periodic solution of the system are obtained.

Sustainable and Ecological Designs of the Built Environment

This paper reviews designs of the built environment from a sustainability perspective, emphasizing their importance in achieving ecological and sustainable economic objectives. The built environment has traditionally resulted in loss of biodiversity, extinction of some species, climate change, excessive water use, land degradation, space depletion, waste accumulation, energy consumption and environmental pollution. Materials used like plastics, metals, bricks, concrete, cement, natural aggregates, glass and plaster have wreaked havoc on the earth´s resources, since they have high levels of embodied energy hence not sustainable. Additional resources are consumed during use and disposal phases. Proposed designs for sustainability solutions include: ecological sanitation and eco-efficiency systems that ensure social, economic, environmental and technical sustainability. Renewable materials and energy systems, passive cooling and heating systems and material and energy reduction, reuse and recycling can improve the sector. These ideas are intended to inform the field of ecological design of the built environment.

Deformation of Water Waves by Geometric Transitions with Power Law Function Distribution

In this work, we analyze the deformation of surface waves in shallow flows conditions, propagating in a channel of slowly varying cross-section. Based on a singular perturbation technique, the main purpose is to predict the motion of waves by using a dimensionless formulation of the governing equations, considering that the longitudinal variation of the transversal section obey a power-law distribution. We show that the spatial distribution of the waves in the varying cross-section is a function of a kinematic parameter,κ , and two geometrical parameters εh and w ε . The above spatial behavior of the surface elevation is modeled by an ordinary differential equation. The use of single formulas to model the varying cross sections or transitions considered in this work can be a useful approximation to natural or artificial geometrical configurations.

Geospatial Network Analysis Using Particle Swarm Optimization

The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Stress Intensity Factors for Plates with Collinear and Non-Aligned Straight Cracks

Multi-site damage (MSD) has been a challenge to aircraft, civil and power plant structures. In real life components are subjected to cracking at many vulnerable locations such as the bolt holes. However, we do not consider for the presence of multiple cracks. Unlike components with a single crack, these components are difficult to predict. When two cracks approach one another, their stress fields influence each other and produce enhancing or shielding effect depending on the position of the cracks. In the present study, numerical studies on fracture analysis have been conducted by using the developed code based on the modified virtual crack closure integral (MVCCI) technique and finite element analysis (FEA) software ABAQUS for computing SIF of plates with multiple cracks. Various parametric studies have been carried out and the results have been compared with literature where ever available and also with the solution, obtained by using ABAQUS. By conducting extensive numerical studies expressions for SIF have been obtained for collinear cracks and non-aligned cracks.

Current Situation and Possible Solutions of Acid Rain in South Korea

Environmental statistics reveals that the pollution of acid rain in South Korea is a serious issue. Yet the awareness of people is low. Even after a gradual decrease of pollutant emission in Korea, the acidity has not been reduced. There no boundaries in the atmosphere are set and the influence of the neighboring countries such as China is apparent. Governmental efforts among China, Japan and Korea have been made on this issue. However, not much progress has been observed. Along with the governmental activities, therefore, an active monitoring of the pollution among the countries and the promotion of environmental awareness at the civil level including especially the middle and high schools are highly recommended. It will be this young generation who will face damaged country as inheritance not the current generation.

Organoclay of Cetyl Trimethyl Ammonium- Montmorillonite: Preparation and Study in Adsorption of Benzene-Toluene-2-Chlorophenol

Contamination of aromatic compounds in water can cause severe long-lasting effects not only for biotic organism but also on human health. Several alternative technologies for remediation of polluted water have been attempted. One of these is adsorption process of aromatic compounds by using organic modified clay mineral. Porous structure of clay is potential properties for molecular adsorptivity and it can be increased by immobilizing hydrophobic structure to attract organic compounds. In this work natural montmorillonite were modified with cetyltrimethylammonium (CTMA+) and was evaluated for use as adsorbents of aromatic compounds: benzene, toluene, and 2-chloro phenol in its single and multicomponent solution by ethanol:water solvent. Preparation of CTMA-montmorillonite was conducted by simple ion exchange procedure and characterization was conducted by using x-day diffraction (XRD), Fourier-transform infra red (FTIR) and gas sorption analysis. The influence of structural modification of montmorillonite on its adsorption capacity and adsorption affinity of organic compound were studied. It was shown that adsorptivity of montmorillonite was increased by modification associated with arrangements of CTMA+ in the structure even the specific surface area of modified montmorillonite was lower than raw montmorillonite. Adsorption rate indicated that material has affinity to adsorb compound by following order: benzene> toluene > 2-chloro phenol. The adsorption isotherms of benzene and toluene showed 1st order adsorption kinetic indicating a partition phenomenon of compounds between the aqueous and organophilic CTMAmontmorillonite.

A proposed High-Resolution Time-Frequency Distribution for the Analysis of Multicomponent and Speech Signals

In this paper, we propose a novel time-frequency distribution (TFD) for the analysis of multi-component signals. In particular, we use synthetic as well as real-life speech signals to prove the superiority of the proposed TFD in comparison to some existing ones. In the comparison, we consider the cross-terms suppression and the high energy concentration of the signal around its instantaneous frequency (IF).