Surface reconstruction techniques: a review

Surface reconstruction means that retrieve the data by scanning an object using a device such as laser scanner and construct it using the computer to gain back the soft copy of data on that particular object. It is a reverse process and is very useful especially when that particular object original data is missing without doing any backup. Hence, by doing so, the data can be recollected and can be stored for future purposes. The type of data can be in the form of structure or unstructured points. The accuracy of the reconstructed result should be concerned because if the result is incorrect, hence it will not exactly same like the original shape of the object. Therefore, suitable methods should be chosen based on the data used. Soft computing methods also have been used in the reconstruction field. This papers highlights the previous researches and methods that has been used in the surface reconstruction field.     

Object Bank: An Object-Level Image Representation for High-Level Visual Recognition

It is a remarkable fact that images are related to objects constituting them. In this paper, we propose to represent images by using objects appearing in them. We introduce the novel concept of object bank (OB), a high-level image representation encoding object appearance and spatial location information in images. OB represents an image based on its response to a large number of pre-trained object detectors, or ‘object filters’, blind to the testing dataset and visual recognition task. Our OB representation demonstrates promising potential in high level image recognition tasks. It significantly outperforms traditional low level image representations in image classification on various benchmark image datasets by using simple, off-the-shelf classification algorithms such as linear SVM and logistic regression. In this paper, we analyze OB in detail, explaining our design choice of OB for achieving its best potential on different types of datasets. We demonstrate that object bank is a high level representation, from which we can easily discover semantic information of unknown images. We provide guidelines for effectively applying OB to high level image recognition tasks where it could be easily compressed for efficient computation in practice and is very robust to various classifiers.     

A memetic algorithm for the capacitated m-ring-star problem

The Capacitated m-Ring-Star Problem (CmRSP) models a network topology design problem in the telecommunications industry. In this paper, we propose to solve this problem using a memetic algorithm that includes a crossover operation, a mutation operation, a local search involving three neighborhood operators, and a population selection strategy that maintains population diversity. Our approach generates the best known solutions for 131 out of 138 benchmark instances, improving on the previous best solutions for 24 of them, and exhibits more advantages on large benchmark instances when compared with the best existing approach. Additionally, all existing algorithms for this problem in literature assume that the underlying graph of the problem instance satisfies the triangle inequality rule; our approach does not require this assumption. We also generated a new set of 36 larger test instances based on a digital data service network price structure to serve as a new benchmark data set for future researchers.     

Predicting external sulphur requirement of alfalfa from sulphate sorption isotherm of Tanzanian soils

For Tanzanian soils dominant in hydrous oxides of iron and amorphous ferri-alumino silicate, a 48-hour (hr) mixing period with the sulphate (SO₄) solution was adequate for a near-equilibrium condition. Although differing in their SO₄ sorption capacity, all the soils sorbed SO₄ at or beyond 1µg ml^–1 sulphur (S) concentration in the supernatant. Hydroxyl (OH) ions were displaced during SO₄ sorption as indicated by a significant positive correlation between the amount of sorbed SO₄ and the difference in pH values determined in 0.1N K₂ SO₄ and 0.1N KCl, i.e. the dpH values.In a greenhouse experiment, alfalfa was grown on eight soils at six adjusted S concentrations. Sulphur deficiency symptoms appeared in the control pots of those soils which were low in native sorbed SO₄, SO₄ sorption capacity and initial soil solution S concentration. Sulphur fertilization increased dry matter (DM) yield as well as response to applied S. The external S concentration, i.e. adjusted S concentration required for 95% of the maximum DM yield, ranged from 0.8 to 8.2µg S ml^–1 with values less than 2.0 on most of the soils. The external S concentration decreased hyperbolically as the SO₄ sorption capacity of the soils increased. The total amount of fertilizer S required to obtain the external S concentration in solution, and at the same time satisfy the SO₄ sorption capacity of the soil at the external S concentration (determined from the sorption isotherm) was defined as the external S requirement for the specified yield level of alfalfa. The external S requirement for 95% of the maximum yield of alfalfa varied from soil to soil due to differences in their capacity and intensity for S nutrition.Part of a thesis by the senior author for the MSc (Agric) degree of the University of Dar es Salaam     

Non-Isothermal crystallization of isotactic polypropylene in dotriacontane. II: Effects of dilution,cooling rate,and nucleating agent addition on growth rate

Non-isothermal crystallization growth rates of nucleated and non-nucleated isotactic polypropylene (iPP) in dotriacontane were determined experimentally by thermal optical microscopy. Adipic acid was used as the nucleating agent. The non-isothermal growth rates of the nucleated and non-nucleated systems were compared with experimentally determined isothermal growth rates. The Lauritzen and Hoffman growth rate equation, originally developed for isothermal crystallization, was modified to describe the non-isothermal growth. The modified Lauritzen-Hoffman equation was used to predict isothermal growth rates from non-isothermal crystallization for the nucleated and non-nucleated polymer-diluent mixtures. This study is the first to deal with polymer-diluent-nucleating agent systems vital to membrane production.     

Circulating fluidized bed combustion of a high-sulphur eastern canadian coal

Combustion tests were carried out with Minto coal in combination with three different limestones in the University of British Columbia (UBC) pilot scale (152 mm square x 7.3 m tall) circulating fluidized bed combustion (CFBC) unit. Operating conditions were chosen to be typical of those employed in large-scale CFBC power boilers. Recycling of fine particles captured by the secondary cyclone was found to be of considerable importance in increasing sulphur capture, enhancing combustion efficiency and reducing the amount of calcium sulphide in the solids residues. NO_x emissions increased as the Ca:S ratio increased. Local gas concentrations inside the reactor were strongly influenced by the core-annulus solids distribution patterns which characterize circulating fluidized beds.     

Scalable and leaderless Byzantine consensus in cloud computing environments

Traditional Byzantine consensus in distributed systems requires n ≥ 3f + 1, where n is the number of nodes. In this paper, we present a scalable and leaderless Byzantine consensus implementation based on gossip, requiring only n ≥ 2f + 1 nodes. Unlike conventional distributed systems, the network topology of cloud computing systems is often not fully connected, but loosely coupled and layered. Hence, we revisit the Byzantine consensus problem in cloud computing environments, in which each node maintains some number of neighbors, called local view. The message complexity of our Byzantine consensus scheme is O(n), instead of O(n ²). Experimental results and correctness proof show that our Byzantine consensus scheme can solve the Byzantine consensus problem safely in a scalable way without a bottleneck and a leader in cloud computing environments.     

Multiple categorizations of products: cognitive modeling of customers through social media data mining

As various forms of social media are spreading, we often witness that an idea of an individual user drives macroscopic changes. From the perspectives of product development and marketing, the opinions left by potential consumers in online social network can generate big ripple effects. This study analyzes the user opinions in online space to grasp preferences toward various products psychologically categorized by users. We also suggest an aspect of the market mentally configured by users using network modeling while following the framework of economic sociology. Existing analyses on online market place are mainly dealing with structural issues such as inter-actor relationships and status measurement. This study, however, analyzes complex preferences regarding diverse products and brands and derives a new model for inter-market connections. We expect that our study will provide important consequences on digital marketing and community design of corporations planning word of mouth effect in online space.     

A three-dimensional model for suspension-to-membrane-wall heat transfer in circulating fluidized beds

A three-dimensional model is proposed for both furnace-side and wall-side heat transfer in circulating fluidized beds with membrane walls. Following previous publications (Int. J. Heat Mass Transfer (2003a, b)), a core-annulus flow structure is employed in the model, with consideration of the membrane wall influence on bed hydrodynamics. The model couples radiation, conduction and convection on the furnace side to conduction and convection on the wall side. Radiation in the wall layer is simulated by the moment method. A finite-element method is employed to solve the set of non-linear, partial differential equations. The solution is demonstrated for a typical example. The model gives predictions of suspension-to-wall heat transfer which show satisfactory agreement with published experimental data.     

Development of density distributions in injection molded amorphous engineering plastics. Part I

The gapwise density distributions of the injection molded specimens of two engineering thermoplastics, i.e., poly(phenylene ether) and poly(ether imide), were characterized employing the density gradient column technique. The samples were molded using a 40t Van Dorn injection molding machine. The effects of the thermal history on the density distribution of unconstrained quenched specimens were also investigated. In addition, various material properties, such as pressure-volume-temperature, isothermal contraction, and pressure induced densification behavior were characterized, for the two resins employed in this study. The moldings of the two resins exhibited different trends in their density distributions. These findings were explained in terms of the competing effects of cooling rate and the pressure history experienced by the engineering plastic resins during the molding cycle. The data collected were also used as input to mathematical modeling of density distributions in injection molded articles, which is reported in Part II of this article.