Showing papers on "Sorting published in 2012"

Sorting in Experiments with Application to Social Preferences

Abstract: Experiments provide a controlled environment where factors can be isolated and studied more easily than in the real world. But experiments are often challenged on the issue of applicability of results to the real world. A major feature of experiments is that they select subjects randomly. Non-laboratory environments, such as markets, instead allow people to sort to certain activities and away from others based on their preferences, beliefs and skills. We design an experiment to demonstrate the importance of sorting in the context of social preferences. When individuals are constrained to play a dictator game, 74% of the subjects share. But when the same subjects are allowed to avoid the situation altogether, less than one third share. This dramatic reversal of proportions demonstrates the importance of taking sorting into account when applying experimental results to the real world. We also show that institutions designed to entice pro-social behavior may actually induce adverse selection. Increasing the total surplus available for sharing induces first those individuals who are least willing to share to sort back into the dictator game. Thus the impact of social preferences remain much lower when sorting is possible than in a mandatory dictator game, even if sharing is subsidized by higher payoffs.

AHPSort: an AHP-based method for sorting problems

Abstract: Six problem formulations exist in the multi-criteria decision analysis (MCDA): choice, sorting, ranking, description, elimination and design problems. The analytic hierarchy process (AHP) is a useful and widespread method for solving choice and ranking problems. However, it is not adapted for sorting problems. Moreover, another practical limitation of AHP is that a high number of alternatives implies a large number of comparisons. This paper presents AHPSort, a new variant of AHP, used for the sorting of alternatives into predefined ordered categories. Furthermore, AHPSort requires far less comparisons than AHP, which facilitates decision making within large-scale problems. In this paper, a real case study for supplier selection is used to illustrate our approach. First, the candidates are sorted with AHPSort within two classes: accepted and rejected suppliers. Then, a single supplier is selected with AHP among the accepted suppliers.

Data Structures and Algorithm Analysis

Abstract: Introduction Algorithm Analysis Lists, Stacks, and Queues Trees Hashing Priority Queues Sorting The Disjoint Set ADT Graph Algorithms Algorithm Design Techniques Amortized Analysis Advanced Data Structures and Implementation

Massively parallel sort-merge joins in main memory multi-core database systems

Abstract: Two emerging hardware trends will dominate the database system technology in the near future: increasing main memory capacities of several TB per server and massively parallel multi-core processing. Many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O dominated the performance. In this work we take a new look at the well-known sort-merge join which, so far, has not been in the focus of research in scalable massively parallel multi-core data processing as it was deemed inferior to hash joins. We devise a suite of new massively parallel sort-merge (MPSM) join algorithms that are based on partial partition-based sorting. Contrary to classical sort-merge joins, our MPSM algorithms do not rely on a hard to parallelize final merge step to create one complete sort order. Rather they work on the independently created runs in parallel. This way our MPSM algorithms are NUMA-affine as all the sorting is carried out on local memory partitions. An extensive experimental evaluation on a modern 32-core machine with one TB of main memory proves the competitive performance of MPSM on large main memory databases with billions of objects. It scales (almost) linearly in the number of employed cores and clearly outperforms competing hash join proposals -- in particular it outperforms the "cutting-edge" Vectorwise parallel query engine by a factor of four.

Massively Parallel Sort-Merge Joins in Main Memory Multi-Core Database Systems

Abstract: Two emerging hardware trends will dominate the database system technology in the near future: increasing main memory capacities of several TB per server and massively parallel multi-core processing. Many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O dominated the performance. In this work we take a new look at the well-known sort-merge join which, so far, has not been in the focus of research in scalable massively parallel multi-core data processing as it was deemed inferior to hash joins. We devise a suite of new massively parallel sort-merge (MPSM) join algorithms that are based on partial partition-based sorting. Contrary to classical sort-merge joins, our MPSM algorithms do not rely on a hard to parallelize final merge step to create one complete sort order. Rather they work on the independently created runs in parallel. This way our MPSM algorithms are NUMA-affine as all the sorting is carried out on local memory partitions. An extensive experimental evaluation on a modern 32-core machine with one TB of main memory proves the competitive performance of MPSM on large main memory databases with billions of objects. It scales (almost) linearly in the number of employed cores and clearly outperforms competing hash join proposals - in particular it outperforms the "cutting-edge" Vectorwise parallel query engine by a factor of four.

The Impact of Size Sorting on the Polarimetric Radar Variables

Abstract: Differential sedimentation of precipitation occurs because heavier hydrometeors fall faster than lighter ones. Updrafts and vertical wind shear can maintain this otherwise transient size sorting, resulting in prolonged regions of ongoing particle sorting in storms. This study quantifies the impact of size sorting on the S-band polarimetric radar variables (radar reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, specific differential phase KDP, and the copolar cross-correlation coefficient ρhv). These variables are calculated from output of two idealized bin models: a one-dimensional model of pure raindrop fallout and a two-dimensional rain shaft encountering vertical wind shear. Additionally, errors in the radar variables as simulated by single-, double-, and triple-moment bulk microphysics parameterizations are quantified for the same size sorting scenarios.Size sorting produces regions of sparsely concentrated large drops with a lack of smaller drops, causing ZDR ...

Polarized sorting and trafficking in epithelial cells

Abstract: The polarized distribution of proteins and lipids at the surface membrane of epithelial cells results in the formation of an apical and a basolateral domain, which are separated by tight junctions. The generation and maintenance of epithelial polarity require elaborate mechanisms that guarantee correct sorting and vectorial delivery of cargo molecules. This dynamic process involves the interaction of sorting signals with sorting machineries and the formation of transport carriers. Here we review the recent advances in the field of polarized sorting in epithelial cells. We especially highlight the role of lipid rafts in apical sorting.

Bidirectional Optical Sorting of Gold Nanoparticles

Abstract: We present a generic technique allowing size-based all-optical sorting of gold nanoparticles. Optical forces acting on metallic nanoparticles are substantially enhanced when they are illuminated at a wavelength near the plasmon resonance, as determined by the particle’s geometry. Exploiting these resonances, we realize sorting in a system of two counter-propagating evanescent waves, each at different wavelengths that selectively guide nanoparticles of different sizes in opposite directions. We validate this concept by demonstrating bidirectional sorting of gold nanoparticles of either 150 or 130 nm in diameter from those of 100 nm in diameter within a mixture.

Continuous-flow ferrohydrodynamic sorting of particles and cells in microfluidic devices

Abstract: A new sorting scheme based on ferrofluid hydrodynamics (ferrohydrodynamics) was used to separate mixtures of particles and live cells simultaneously. Two species of cells, including Escherichia coli and Saccharomyces cerevisiae, as well as fluorescent polystyrene microparticles were studied for their sorting throughput and efficiency. Ferrofluids are stable magnetic nanoparticles suspensions. Under external magnetic field gradients, magnetic buoyancy forces exerted on particles and cells lead to size-dependent deflections from their laminar flow paths and result in spatial separation. We report the design, modeling, fabrication and characterization of the sorting device. This scheme is simple, low-cost and label-free compared to other existing techniques.

Multi-objective biogeography based optimization for optimal PMU placement

Abstract: The paper proposes a multi-objective biogeography based optimization (MO-BBO) algorithm to design optimal placement of phasor measurement units (PMU) which makes the power system network completely observable. The simultaneous optimization of the two conflicting objectives such as minimization of the number of PMUs and maximization of measurement redundancy are performed. The Pareto optimal solution is obtained using the non-dominated sorting and crowding distance. The compromised solution is chosen using a fuzzy based mechanism from the Pareto optimal solution. Simulation results are compared with Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Non-dominated Sorting Differential Evolution (NSDE). Developed PMU placement method is illustrated using IEEE standard systems to demonstrate the effectiveness of the proposed algorithm.

Sorting games of chance

Abstract: In various embodiments a display may allow a secondary player to select a game of an appropriate primary player.

Analysis of complex data objects and multiple parameter systems

Abstract: A computer facilitates multiple parameters data analysis by special visualization and navigation methods. Data to be analyzed is loaded from an external source the computer displays the data in response to user input using a variety of methods including data tables, slices of data spaces, hierarchically navigated data spaces, dynamic slice tables, filters, sorting, color-mapping, numerical operations, and other methods.

Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II

Abstract: Parametric optimization of electric discharge machining (EDM) process is a multi-objective optimization task. In general, no single combination of input parameters can provide the best cutting speed and the best surface finish simultaneously. Genetic algorithm has been proven as one of the most popular multi-objective optimization techniques for the parametric optimization of EDM process. In this work, controlled elitist non-dominated sorting genetic algorithm has been used to optimize the process. Experiments have been carried out on die-sinking EDM by taking Inconel 718 as work piece and copper as tool electrode. Artificial neural network (ANN) with back propagation algorithm has been used to model EDM process. ANN has been trained with the experimental data set. Controlled elitist non-dominated sorting genetic algorithm has been employed in the trained network and a set of pareto-optimal solutions is obtained.

Deductive sort and climbing sort: New methods for non-dominated sorting

Abstract: In recent years an increasing number of real-world many-dimensional optimisation problems have been identified across the spectrum of research fields. Many popular evolutionary algorithms use non-dominance as a measure for selecting solutions for future generations. The process of sorting populations into non-dominated fronts is usually the controlling order of computational complexity and can be expensive for large populations or for a high number of objectives. This paper presents two novel methods for non-dominated sorting: deductive sort and climbing sort. The two new methods are compared to the fast non-dominated sort of NSGA-II and the non-dominated rank sort of the omni-optimizer. The results demonstrate the improved efficiencies of the deductive sort and the reductions in comparisons that can be made when applying inferred dominance relationships defined in this paper.

Multi-objective particle swarm optimisation (PSO) for feature selection

Abstract: Feature selection (FS) is an important data preprocessing technique, which has two goals of minimising the classification error and minimising the number of features selected. Based on particle swarm optimisation (PSO), this paper proposes two multi-objective algorithms for selecting the Pareto front of non-dominated solutions (feature subsets) for classification. The first algorithm introduces the idea of non-dominated sorting based multi-objective genetic algorithm II into PSO for FS. In the second algorithm, multi-objective PSO uses the ideas of crowding, mutation and dominance to search for the Pareto front solutions. The two algorithms are compared with two single objective FS methods and a conventional FS method on nine datasets. Experimental results show that both proposed algorithms can automatically evolve a smaller number of features and achieve better classification performance than using all features and feature subsets obtained from the two single objective methods and the conventional method. Both the continuous and the binary versions of PSO are investigated in the two proposed algorithms and the results show that continuous version generally achieves better performance than the binary version. The second new algorithm outperforms the first algorithm in both continuous and binary versions.

Near-Perfect Sorting of Orbital Angular Momentum and Angular Position States of Light

Abstract: We present a novel method for efficient sorting of photons prepared in states of orbital angular momentum (OAM) and angular position (ANG). A log-polar optical transform is used in combination with a holographic beam-splitting method to achieve better mode discrimination and reduced cross-talk than reported previously. Simulating this method for 7 modes, we have calculated an improved mutual information of 2.43 bits/photon and 2.29 bits/photon for OAM and ANG modes respectively. In addition, we present preliminary results from an experimental implementation of this technique. This method is expected to have important applications for high-dimensional quantum key distribution systems.

Method and device for predicting advertisement click rate based on user behaviors

Abstract: The invention discloses a method and device for predicting advertisement click rate based on user behaviors. The method comprises the following steps of: behavior directional prediction: training a behavior directional model by analyzing the user behaviors, and predicting the click rates of the user on different types of advertisements to obtain a predicted value of the click rate; in-type sorting: sorting the advertisements of each type according to the current behavior type of the user to obtain an in-type advertisement sorting list; and comprehensive sorting: sorting the click rates of all advertisements according to the predicted value of click rate and the in-type advertisement sorting list to obtain a comprehensive sorting list. Through the method disclosed by the invention, a prediction model can be established for each type of advertisements so as to sort the advertisements more accurately according to the type characteristics of the advertisements.

Practically efficient multi-party sorting protocols from comparison sort algorithms

Abstract: Sorting is one of the most important primitives in various systems, for example, database systems, since it is often the dominant operation in the running time of an entire system Therefore, there is a long list of work on improving its efficiency It is also true in the context of secure multi-party computation (MPC), and several MPC sorting protocols have been proposed However, all existing MPC sorting protocols are based on less efficient sorting algorithms, and the resultant protocols are also inefficient This is because only a method for converting data-oblivious algorithms to corresponding MPC protocols is known, despite the fact that most efficient sorting algorithms such as quicksort and merge sort are not data-oblivious We propose a simple and general approach of converting non-data-oblivious comparison sort algorithms, which include the above algorithms, into corresponding MPC protocols We then construct an MPC sorting protocol from the well known efficient sorting algorithm, quicksort, with our approach The resultant protocol is practically efficient since it significantly improved the running time compared to existing protocols in experiments

Multi-objective hybrid evolutionary algorithms for radial basis function neural network design

Abstract: This paper presents new multi-objective evolutionary hybrid algorithms for the design of Radial Basis Function Networks (RBFNs) for classification problems. The algorithms are memetic Pareto particle swarm optimization based RBFN (MPPSON), Memetic Elitist Pareto non dominated sorting genetic algorithm based RBFN (MEPGAN) and Memetic Elitist Pareto non dominated sorting differential evolution based RBFN (MEPDEN). The proposed methods integrate accuracy and structure of RBFN simultaneously. These algorithms are implemented on two-class and multiclass pattern classification problems with one complex real problem. The results reveal that the proposed methods are viable, and provide an effective means to solve multi-objective RBFNs with good generalization ability and simple network structure. The accuracy and complexity of the network obtained by the proposed algorithms are compared through statistical tests. This study shows that the proposed methods obtain RBFNs with an appropriate balance between accuracy and simplicity.

Subwavelength optical absorber with an integrated photon sorter

Abstract: We provide the experimental and theoretical evidence that several nano-patch antennas assembled within a wavelength-scale region may constitute an efficient and easily tunable multi-band photodetector. The system uses highly confined localization states of light and exhibits a robust spectral sorting capability, paving the way to highly integrated hyperspectral imaging.

Using manipulation primitives for brick sorting in clutter

Abstract: This paper explores the idea of manipulation-aided perception and grasping in the context of sorting small objects on a tabletop. We present a robust pipeline that combines perception and manipulation to accurately sort Duplo bricks by color and size. The pipeline uses two simple motion primitives to manipulate the scene in ways that help the robot to improve its perception. This results in the ability to sort cluttered piles of Duplo bricks accurately. We present experimental results on the PR2 robot comparing brick sorting without the aid of manipulation to sorting with manipulation primitives that show the benefits of the latter, particularly as the degree of clutter in the environment increases.

Sorting Out the Virtual Patient: How to Exploit Artificial Intelligence, Game Technology and Sound Educational Practices to Create Engaging Role-Playing Simulations

Abstract: Since Dr. Howard Barrows (1964) introduced the human standardized patient in 1963, there have been attempts to game a computer-based simulacrum of a patient encounter; the first being a heart attack simulation using the online PLATO system (Bitzer, 1966). With the now ubiquitous use of computers in medicine, interest and effort have expended in the area of Virtual Patients (VPs). One problem in trying to understand VPs is that there are several quite distinct educational approaches that are all called a ‘virtual patient.’ This article is not a general review of virtual patients as current reviews of excellent quality exist (Poulton & Balasubramaniam, 2011; Cook & Triola, 2009). Also, research that demonstrates the efficacy of virtual patients is ample (Triola, et al., 2006). This article assesses the different kinds of things the authors call “virtual patients”, which are often mutually exclusive approaches, then analyzes their interaction structure or ‘game-play’, and considers the best use scenarios for that design strategy. This article also explores dialogue-based conversational agents as virtual patients and the technology approaches to creating them. Finally, the authors offer a theoretical approach that synthesizes several educational approaches over the course of a medical encounter and recommend the optimal technology for the type of encounter desired. DOI: 10.4018/jgcms.2012070101 2 International Journal of Gaming and Computer-Mediated Simulations, 4(3), 1-19, July-September 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. A WHIRLWIND TOUR OF VIRTUAL PATIENTS As previously stated, many different entities with unique approaches and attributes are all often called virtual patients. Such approaches include case presentations, interactive patient scenarios, virtual patient games, human standardized patients, high fidelity software simulations, high fidelity manikins and virtual human conversational agents. Salient features of these virtual patient approaches are summarized in Table 1. The Case Presentation Case Presentations are a staple of medical education and are widely employed in both multimedia and print. They consist of a paragraph of text that summarizes a patient presentation and findings followed by a series of multiple-choice questions (Figure 1). They are often employed to test or reinforce basic medical knowledge regarding a specific type of case and are also used to evaluate clinical reasoning. Case presentations may not even be interactive, but may simply record learner responses for testing purposes. With multimedia case presentations, some at least try to provide feedback regarding the learner’s choice of responses (Talbot, 1997). This level of interaction is fairly limited and really can’t be considered as game play. Some online and multimedia versions of case presentations have been labeled as virtual patients simply because they are presented on a computer. These flat constructs test core medical knowledge and clinical reasoning skills. They can be useful educational adjuncts for teaching knowledge items and clinical reasoning if they are built in a way that offers some type of useful feedback. Providing scores that tally correct and incorrect responses, a typical approach, may be worthwhile for assessment but they are not useful for didactic purposes because numeric scores contain no educational content. The primary reason for the ubiquity of case presentations is that they are very easy to author. They can be written by a typical medical educator who need only provide a medical history, several questions and hopefully useful responses to user input. Interactive Patient Scenarios Interactive patient scenarios (IPSs) represent a very common form of virtual patient. When the term “Virtual Patient” is employed, this is the type of learning tool typically referred to. Interactive patient scenarios, which are usually text-based multimedia, build upon the case presentation with a few novel features; they may advance the progress of the patient over time, they employ substantial multimedia and they may have a branching structure that allows for considerable variation of the encounter experience. Interactive patient scenarios are typically generated online and contain considerable multimedia in the form of photographs of patient findings, radiographs and auscultation sounds. The case history and progression may be presented through text or voice narration. They may advance a case to show ongoing symptom progression or response to treatment. If the interactive scenario does not allow the user to control the patient, it is called a linear case scenario. If it alters the progress of the case based upon the learner’s decisions (typically multiple choice), it is called a branching scenario. Branching scenarios allow for considerably different patient outcomes based upon learner choices and they permit a richer experience. The main drawback to branching scenarios is complexity and effort to author them. Each branch represents a potential geometric increase in authoring effort unless the branching is tied back to one or a few linear narratives. Branching IPSs are often employed for teaching clinical reasoning skills and will often include both the diagnostic phase (interview, physical exam & test data) as well as the treatment phase of the patient encounter. Branching interactive scenarios provide a good deal of game-play if the author creates interesting, mutually exclusive choices to the learner. They also can be interesting for repeat 17 more pages are available in the full version of this document, which may be purchased using the \"Add to Cart\" button on the product's webpage: www.igi-global.com/article/sorting-out-virtualpatient/74790?camid=4v1 This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Communications and Social Science, InfoSciSelect, InfoSci-Select, InfoSci-Artificial Intelligence and Smart Computing eJournal Collection, InfoSciCommunications, Online Engagement, and Media eJournal Collection, InfoSci-Journal Disciplines Computer Science, Security, and Information Technology, InfoSci-Journal Disciplines Engineering, Natural, and Physical Science. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2

Efficient parallel merge sort for fixed and variable length keys

Abstract: We design a high-performance parallel merge sort for highly parallel systems. Our merge sort is designed to use more register communication (not shared memory), and does not suffer from over-segmentation as opposed to previous comparison based sorts. Using these techniques we are able to achieve a sorting rate of 250 MKeys/sec, which is about 2.5 times faster than Thrust merge sort performance, and 70% faster than non-stable state-of-the-art GPU merge sorts. Building on this sorting algorithm, we develop a scheme for sorting variable-length key/value pairs, with a special emphasis on string keys. Sorting non-uniform, unaligned data such as strings is a fundamental step in a variety of algorithms, yet it has received comparatively little attention. To our knowledge, our system is the first published description of an efficient string sort for GPUs. We are able to sort strings at a rate of 70 MStrings/s on an NVidia GTX 580 on one dataset, and up to 1.25 GB/s on another dataset.

Incentive Schemes, Sorting, and Behavioral Biases of Employees: Experimental Evidence

Abstract: We investigate how the convexity of a firm's incentives interacts with worker overconfidence to affect sorting decisions and performance. We demonstrate, experimentally, that overconfident employees are more likely to sort into a nonlinear incentive scheme over a linear one, even though this reduces pay for many subjects and despite the presence of clear feedback. Additionally, the linear scheme attracts demotivated, underconfident workers who perform below their ability. Our findings suggest that firms may design incentive schemes that adapt to the behavioral biases of employees to "sort in" ("sort away") attractive (unattractive) employees; such schemes may also reduce a firm's wage bill. (JEL D03, D83, J24, J31, M12)

Collaborative filtering recommendation algorithm based on article sorting and user sorting

Abstract: The invention relates to a collaborative filtering algorithm, in particular to a collaborative filtering recommendation algorithm based on article sorting and user sorting, which is characterized by including steps: A, article clustering and sorting; B, user clustering and sorting; C, integration of article clustering and user clustering; and D, sorting recommendation. Compared with the prior art, collaborative filtering recommendation algorithm has the advantages that the data clustering is completed by means of modified KMEANS algorithm, the method is simple, and extensibility is improved while the problems of sparsity and cold boot are solved.

Mutual Fund Tournaments: The Sorting Bias and New Evidence

Abstract: Previous findings regarding the risk-shifting behavior of mid-year underperforming mutual fund managers are mixed. In this article, I show that this is due to a "sorting bias," which is caused by the sorting of first-half risk levels when establishing relative mid-year performance. Even without risk-shifting behavior, mean reversion of these sorted risk levels results in the detection of tournament behavior. After correcting for this bias, I find evidence supporting the hypothesis that first-half underperforming managers increase portfolio risk during the second half of the year and that this tournament behavior is not dependent on first-half market conditions. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.