Merge Operations Research Articles

Refinements to a Procedure for Estimating Airfield Capacity

This paper presents a method for obtaining airfield capacity estimates using historical data from FAA's Aviation System Performance Metrics (ASPM) database. The process first involves merging individual flights and quarter-hour airport runway operations data sets from ASPM to create a new data set. Data for Newark Liberty International Airport (EWR) in New Jersey and San Diego International Airport in California from 2006 to 2011 were used. Then, filters for meteorological condition, runway configuration, called rates, and fleet mix were applied to the two airport data sets. The filtered data sets were then used in a censored regression model of capacity that included queue length (number of aircraft waiting to arrive or depart) and arrival–departure throughput count splits as independent variables. These attributes were found to affect airfield capacity at statistically significant levels, and parameters had expected signs and magnitudes. Additionally, capacities under ideal conditions were found to be reasonably close to other sources. The model also confirmed that average capacities at EWR during hours when a ground delay program (GDP) was running were lower than when there was no GDP in effect. The method described in this paper could be used to more precisely quantify airfield capacities in specific conditions of particular interest to air traffic controllers and airport operators to better facilitate decisions that rely heavily on a good understanding of capacity in these conditions. The data exploration and preparation undertaken as part of the study reveal some of the finer points of the ASPM data and how they can be used in a more meaningful way for airfield capacity estimation.

Generating Analysis Topology using Virtual Topology Operators

Virtual topology operations have been utilized to generate an analysis topology definition suitable for downstream mesh generation. Detailed descriptions are provided for virtual topology merge and split operations for all topological entities, where virtual decompositions are robustly linked to the underlying geometry. Current virtual topology technology is extended to allow the virtual partitioning of volume cells. A valid description of the topology, including relative orientations, is maintained which enables downstream interrogations to be performed on the analysis topology description, such as determining if a specific meshing strategy can be applied to the virtual volume cells. As the virtual representation is a true non-manifold description of the sub-divided domain the interfaces between cells are recorded automatically. Therefore, the advantages of non-manifold modelling are exploited within the manifold modelling environment of a major commercial CAD system without any adaptation of the underlying CAD model. A hierarchical virtual structure is maintained where virtual entities are merged or partitioned. This has a major benefit over existing solutions as the virtual dependencies here are stored in an open and accessible manner, providing the analyst with the freedom to create, modify and edit the analysis topology in any preferred sequence.

An Algebraic Approach to Combining Classifiers

Abstract In distributed classification, each learner observes its environment and deduces a classifier. As a learner has only a local view of its environment, classifiers can be exchanged among the learners and integrated, or merged , to improve accuracy. However, the operation of merging is not defined for most classifiers. Furthermore, the classifiers that have to be merged may be of different types in settings such as ad-hoc networks in which several generations of sensors may be creating classifiers. We introduce decision spaces as a framework for merging possibly different classifiers. We formally study the merging operation as an algebra, and prove that it satisfies a desirable set of properties. The impact of time is discussed for the two main data mining settings. Firstly, decision spaces can naturally be used with non-stationary distributions, such as the data collected by sensor networks, as the impact of a model decays over time. Secondly, we introduce an approach for stationary distributions, such as homogeneous databases partitioned over different learners, which ensures that all models have the same impact. We also present a method using storage flexibly to achieve different types of decay for non-stationary distributions.

Improving Hybrid FTL by Fully Exploiting Internal SSD Parallelism with Virtual Blocks

Compared with either block or page-mapping Flash Translation Layer (FTL), hybrid-mapping FTL for flash Solid State Disks (SSDs), such as Fully Associative Section Translation (FAST), has relatively high space efficiency because of its smaller mapping table than the latter and higher flexibility than the former. As a result, hybrid-mapping FTL has become the most commonly used scheme in SSDs. But the hybrid-mapping FTL incurs a large number of costly full-merge operations. Thus, a critical challenge to hybrid-mapping FTL is how to reduce the cost of full-merge operations and improve partial merge operations and switch operations. In this article, we propose a novel FTL scheme, called Virtual Block-based Parallel FAST (VBP-FAST), that divides flash area into Virtual Blocks (VBlocks) and Physical Blocks (PBlocks) where VBlocks are used to fully exploit channel-level, die-level, and plane-level parallelism of flash. Leveraging these three levels of parallelism, the cost of full merge in VBP-FAST is significantly reduced from that of FAST. In the meantime, VBP-FAST uses PBlocks to retain the advantages of partial merge and switch operations. Our extensive trace-driven simulation results show that VBP-FAST speeds up FAST by a factor of 5.3--8.4 for random workloads and of 1.7 for sequential workloads with channel-level, die-level, and plane-level parallelism of 8, 2, and 2 (i.e., eight channels, two dies, and two planes).

Security Analysis and Improvement on Two RFID Authentication Protocols

Several lightweight RFID authentication protocols have been proposed to settle the security and privacy problems. Nevertheless, most of these protocols are analyzed and they are not successful in their attempt to achieve the claimed security objectives. In this paper, we consider the security of two recently proposed typical RFID authentication protocols: RAPLT protocol and SRP+ protocol. RAPLT protocol is a new ultra-lightweight RFID protocol based on two new operations named $$merge$$merge and $$separation$$separation. Utilizing the linear property of the $$merge$$merge operation, we present a passive disclosure attack on RAPLT protocol, and we can deduce the shared secrets with overwhelming probability after eavesdropping about 100 round authentication sessions. SRP+ protocol is a novel secure RFID authentication protocol conforming to the EPC C-1 G-2 standard, and we present efficient de-synchronization attack and passive disclosure attack through exhaustive search. Our disclosure attack only needs one run of the protocol, and the attack complexity is $$O(2^{16})$$O(216) evaluation of the PRNG function in off-line analysis mode. In addition, to counteract the vulnerabilities, we propose a new modified version of SRP+ protocol, denoted by $$ SRP ^{++}$$SRP++, conforming to the EPC C-1 G-2 standard. Our security analysis demonstrates that $$ SRP ^{++}$$SRP++ protocol can resist the exhaustive search attack with the complexity $$O(2^{32})$$O(232), which is the optimal security bound.

No syntax saltation in language evolution

Much of the recent literature within the Minimalist/biolinguistic paradigm argues that the core language faculty, or more specifically ‘narrow syntax’, arose abruptly and rather recently, certainly within the last 100,000 years. The proposed syntax saltation is taken to be the result of a minor mutation, giving rise to the Merge operation which creates hierarchical structures. Moreover, externalization – using language for communication – is claimed to be a development subsequent to the use of language purely for internal thought. I argue against these claims, both on language-internal grounds, using evidence from the lexicon and from syntactic displacement, and on the basis of the archaeological findings.

Combining Structure and Parameter Adaptation of HMMs for Printed Text Recognition.

We present two algorithms that extend existing HMM parameter adaptation algorithms (MAP and MLLR) by adapting the HMM structure. This improvement relies on a smart combination of MAP and MLLR with a structure optimization procedure. Our algorithms are semi-supervised: to adapt a given HMM model on new data, they require little labeled data for parameter adaptation and a moderate amount of unlabeled data to estimate the criteria used for HMM structure optimization. Structure optimization is based on state splitting and state merging operations and proceeds so as to optimize either the likelihood or a heuristic criterion. Our algorithms are successfully applied to the recognition of printed characters by adapting the HMM character models of a polyfont printed text recognizer to new fonts. Our experiments involve a total of 1,120,000 real and 3,100,000 synthetic character images and concern a set of 89 HMM models. A comparison of our results with those of state-of-the-art adaptation algorithms (MAP and MLLR) shows a significant increase in the accuracy of character recognition.

Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm

To simulate solar cell systems or to optimize photovoltaic (PV) system performance, accurate parameter values of solar cell systems are extremely crucial. In this article, the parameter extraction of solar cell models is posed as an optimization process with an objective function minimizing the difference between the measured values and estimated data. A mutative-scale parallel chaos optimization algorithm (MPCOA) using crossover operation and merging operation is proposed for this optimization problem. To verify the performance of MPCOA, it is applied to extract the parameters of different solar cell models, i.e., double diode, single diode, and PV module. Comparison results with other parameter extraction techniques are in favor of the MPCOA, which signifies its potential as another optional method.

Multilevel Thresholding using PSO Clustering

Thresholding algorithms are quite easy and effective for bilevel thresholding but in case of multilevel thresholding, the performance becomes unreliable due to complexity in computation because the complexity will exponentially increase. In this approach, multilevel thresholding is done for comparison by taking help of Otsu’s clustering method and PSO clustering method. A dendogram of gray levels is created based on histogram of an image. The bottom-up generation of clusters employing a dendogram by the proposed method yields good separation of the clusters and obtains a robust estimate of the threshold. Such cluster organization will yield a clear separation between object and background even for the case of nearly unimodal or multimodal histogram. Since the hierarchical clustering method performs an iterative merging operation, it is extended to multi-level thresholding problem by eliminating grouping of clusters when the pixel values are obtained from the expected number of clusters.

A mutative-scale pseudo-parallel chaos optimization algorithm

Chaos optimization algorithms (COAs) utilize the chaotic map to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. Many existing applications show that COAs escape from the local minima more easily than classical stochastic optimization algorithms. However, the search efficiency of COAs crucially depends on appropriately starting values. In view of the limitation of COAs, a novel mutative-scale pseudo-parallel chaos optimization algorithm (MPCOA) with cross and merging operation is proposed in this paper. Both cross and merging operation can exchange information within population and produce new potential solutions, which are different from those generated by chaotic sequences. In addition, mutative-scale search space is used for elaborate search by continually reducing the search space. Consequently, a good balance between exploration and exploitation can be achieved in the MPCOA. The impacts of different chaotic maps and parallel numbers on the MPCOA are also discussed. Benchmark functions and parameter identification problem are used to test the performance of the MPCOA. Simulation results, compared with other algorithms, show that the MPCOA has good global search capability.

Improvement of QSM Algorithm and Its Application to Protocol Model Induction

Query-driven State Merging (QSM) algorithm extends the Regular Positive and Negative Inference (RPNI) and Blue-Fringe algorithms by allowing membership queries to be submitted to the oracle. In this paper, further constrains state merging operations by detecting loop structure in automation induction process and proves this improvement could make QSM algorithm get more accurate results. Furthermore, applies the improved QSM algorithm to the application of protocol model induction, and experiments demonstrate that 1. QSM algorithm is also efficient in protocol model induction besides software model induction, 2. QSM is better than any other methods in this research area.

The Use of OpenMP Parallel Standards in Massive Data Delaunay Triangulation

This paper uses OpenMP parallel standardsin massive data Delaunay triangulation.Based on the Fork/Join parallel mode in OpenMP, a quad-tree is designed to divide and map the point cloud data.And the hierarchical implementation of triangulation and merging operations are based on it. A WFM-JLP algorithm is used to schedule triangulationand merging operations in order to achieve better load balancing. Experiment show the proposed method can greatly reduce the real-time memory and computing time.

Realizing exterior Cromwell moves on rectangular diagrams by Reidemeister moves

If a rectangular diagram represents the trivial knot, then it can be deformed into the trivial rectangular diagram with only four edges by a finite sequence of merge operations and exchange operations, without increasing the number of edges, which was shown by Dynnikov in [Arc-presentations of links: Monotone simplification, Fund. Math. 190 (2006) 29–76; Recognition algorithms in knot theory, Uspekhi Mat. Nauk 58 (2003) 45–92. Translation in Russian Math. Surveys 58 (2003) 1093–1139]. Using this, Henrich and Kauffman gave in [Unknotting unknots, preprint (2011), arXiv:1006.4176v4 [math.GT]] an upper bound for the number of Reidemeister moves needed for unknotting a knot diagram of the trivial knot. However, exchange or merge moves on the top and bottom pairs of edges of rectangular diagrams are not considered in [Unknotting unknots, preprint (2011), arXiv:1006.4176v4 [math.GT]]. In this paper, we show that there is a rectangular diagram of the trivial knot which needs such an exchange move for being unknotted, and study upper bound of the number of Reidemeister moves needed for realizing such an exchange or merge move.

WExplore: Hierarchical Exploration of High-Dimensional Spaces Using the Weighted Ensemble Algorithm

As most relevant motions in biomolecular systems are inaccessible to conventional molecular dynamics simulations, algorithms that enhance sampling of rare events are indispensable. Increasing interest in intrinsically disordered systems and the desire to target ensembles of protein conformations (rather than single structures) in drug development motivate the need for enhanced sampling algorithms that are not limited to "two-basin" problems, and can efficiently determine structural ensembles. For systems that are not well-studied, this must often be done with little or no information about the dynamics of interest. Here we present a novel strategy to determine structural ensembles that uses dynamically defined sampling regions that are organized in a hierarchical framework. It is based on the weighted ensemble algorithm, where an ensemble of copies of the system ("replicas") is directed to new regions of configuration space through merging and cloning operations. The sampling hierarchy allows for a large number of regions to be defined, while using only a small number of replicas that can be balanced over multiple length scales. We demonstrate this algorithm on two model systems that are analytically solvable and examine the 10-residue peptide chignolin in explicit solvent. The latter system is analyzed using a configuration space network, and novel hydrogen bonds are found that facilitate folding.

Fast responsive flash translation layer for smart devices

The flash translation layer design of smart devices differs from that of traditional storages, because smart devices have frequent power-offs and limited resources. These unique features of smart devices generate inconsistent response times and performance degradation. This paper proposes a new FTL algorithm called the Fast Responsive Flash Translation Layer (FFTL) for smart devices. FFTL avoids frequent merge operations by first executing a cleaning policy and provides a faster response time than superblocklevel associativity algorithms by balancing the associativity of each log block. Furthermore, FFTL utilizes all the sectors within each page, thereby reducing the number of write operations. According to the experimental results, it outperforms MCSplit, Superblock, and MAST in terms of the average response time and number of operations.

Complexity management methodology for fuzzy systems with feedback rule bases

This paper proposes a complexity management methodology for fuzzy systems with feedback rule bases. The methodology is based on formal methods for presentation, manipulation and transformation of fuzzy rule bases. First, Boolean matrices are used for formal presentation of rule bases. Then, binary merging operations are used for formal manipulation of rule bases. Finally, repetitive merging operations are used for formal transformation of rule bases. The formal methods facilitate the understanding and modelling of fuzzy systems in terms of interacting subsystems. In particular, the methods reduce the qualitative complexity in fuzzy systems by improving the transparency of the rule bases.

Adaptive in-page logging for flash-memory storage systems

Flash memory is widely used in embedded devices and enterprise storage systems. Currently, flash-based storage devices usually use a flash translation layer (FTL) to cope with the special features of flash memory. Many methods for the design and implementation of the FTL have been proposed, such as BAST (block-associative sector translation), FAST (fully associative sector translation), and IPL (inpage logging), of which IPL has been demonstrated to have the best performance. However, IPL offers little consideration to reducing merge operations that consequently result in the degradation of the overall performance of flash-memory storage systems. We propose an improvement to IPL, called adaptive IPL (AIPL). The idea of adaptive IPL is to make the log region in a block resizable, therefore a hot block (i.e., a write-intensive block) will use a large log region so as to absorb more page updates and in turn reduce the merge operations, while a cold block, i.e., a block rarely written to, will use a small log region. This is realized by first detecting the update pattern of a block and then presenting an updatepattern-based algorithm to dynamically adjust the log region size of a newly allocated block. We conduct experiments on TPC-C traces and synthetic traces and compare the performance of AIPL with other competitors in terms of merge count, write count and elapsed time. The results demonstrate that compared with IPL, AIPL can reduce merge operations by 65% and write operations by 54% on average.

Is Word Order Asymmetry Mathematically Expressible?

The computational procedure for human natural language (CHL) shows an asymmetry in unmarked orders for S, O, and V. Following Lyle Jenkins, it is speculated that the asymmetry is expressible as a group-theoretical factor (included in Chomsky’s third factor): “[W]ord order types would be the (asymmetric) stable solutions of the symmetric still-to-be-discovered ‘equations’ governing word order distribution”. A possible “symmetric equation” is a linear transformation f(x) = y, where function f is a set of merge operations (transformations) expressed as a set of symmetric transformations of an equilateral triangle, x is the universal base vP input expressed as the identity triangle, and y is a mapped output tree expressed as an output triangle that preserves symmetry. Although the symmetric group S3 of order 3! = 6 is too simple, this very simplicity is the reason that in the present work cost differences are considered among the six symmetric operations of S3. This article attempts to pose a set of feasible questions for future research.

Auto-configuration of Physical Cell ID in LTE femtocellular systems using Self Organizing Networks

The commercial success of cellular networks, combined with advances in digital electronics, signal processing, and telecommunications research have lead to the design of next generation 4G-based long term evolution (LTE) wireless systems. The key essence of these emerging, LTE cellular systems lie in deployment of multiple femtocells for improved coverage and higher data rates. However, the arbitrary deployment of a wide number of femtocells makes the configuration, management and planning of LTE systems quite complex and challenging. In order to support dynamic and efficient network configuration, every cell needs to be assigned a particular Physical Cell ID (PCID). In this paper we show that the dynamic, optimal PCID allocation problem in LTE systems is NP-complete. Subsequently we provide a near-optimal solution using Self-Organizing Networks which models the problem using new merge operations and explores the search space using a suitable randomized algorithmic approach. We also discuss two feasible options for dynamic auto-configuration of the system and analyze the algorithm to prove its convergence. Simulation results point out that our proposed near-optimal solution dynamically achieves ~85−90 % of global optimal auto-configuration in computationally feasible time.

New Concept of Traffic Rotary Design at Road Intersections

Traffic Rotary at road intersections is special form of grade change of lanes to channelize movement of vehicles in one direction around a central traffic island. With rapid growth of traffic it is experienced that widening of roads and providing flyovers have become imperative to overcome major conflicts at intersections such as collision between through and right- turn movements. In this way, major conflicts are converted into milder conflicts like merging and diverging. The vehicles entering the rotary are gently forced to move in a clockwise direction. They then weave out of the rotary to the desired direction. The crossing of vehicles is avoided by allowing all vehicles to merge into a stream around the rotary and then to diverge out to the desired radiating road. Thus the crossing conflicts eliminate and convert into weaving manoeuvre or a merging operation from right and a diverging operation to the left. In this paper, designing rotaries at road intersections is discussed and a software package is developed to be used in road works.