Holistic Algorithm Research Articles

A new algorithm for mutual funds evaluation based on multiple attribute decision making techniques

Purpose The purpose of this paper is to consider compromise solutions of multiple attribute decision-making methods (TOPSIS, VIKOR, and similarity-based approach) in order to evaluate and rank mutual funds and to compare the capabilities of different approaches based on the different traditional indices of mutual funds assessment. In addition, a new algorithm for ranking mutual funds was proposed subsequently. Design/methodology/approach In this research, three groups of indices including general, risk-modified performance evaluation, and risk-modified performance evaluation indices using semivariance were used in the mutual funds assessment, which led to the comparison between selected mutual funds, using three mentioned methods and three different groups of criteria. The results of this comparison were compiled and synthesized with linear assignment method. At the end, an algorithm for decision making and investing in mutual funds for professional and unprofessional investors was proposed. Findings Using different methods and different criteria proved that the results of similarity-based approach as a MADM technique have the ability to rank and evaluate mutual funds regardless of the criteria used compared to TOPSIS and VIKOR. Furthermore, the authors propose the algorithm of this research as a new model of mutual funds evaluation which considers a wide range of variables with respect to amateur and professional points of view. Originality/value The originality of this paper is threefold: first, different criteria were considered to make the evaluation more comprehensive. Second, four different approaches were used to make the results more authentic. Third, a holistic algorithm with its implication was proposed.

Processing and Evaluating Partial Tree Pattern Queries on XML Data

XML query languages typically allow the specification of structural patterns using XPath. Usually, these structural patterns are in the form of trees (Tree-Pattern Queries-TPQs). Finding the occurrences of such patterns in an XML tree is a key operation in XML query evaluation. The multiple previous algorithms presented for this operation focus mainly on the evaluation of tree-pattern queries. Recently, requirements for flexible querying of XML data have motivated the consideration of query classes that are more expressive and flexible than TPQs for which efficient nonmain-memory evaluation algorithms are not known. In this paper, we consider a class of queries, called Partial Tree-Pattern Queries (PTPQs), which generalize and strictly contain TPQs. PTPQs represent a broad fragment of XPath which is very useful in practice. In order to process PTPQs, we introduce a set of sound and complete inference rules to characterize structural relationship derivation. We provide necessary and sufficient conditions for detecting query unsatisfiability and node redundancy. We also show that PTPQs can be represented as directed acyclic graphs augmented with the “same-path” constraints. In order to leverage existing efficient evaluation algorithms for less expressive classes of queries, we design two approaches that evaluate a PTPQ by decomposing it into a set of simpler queries: algorithm IndexTPQGen, exploits a structural summary of the XML data and evaluates a PTPQ by generating an equivalent set of TPQs and unioning their answers. Algorithm PartialPathJoin decomposes the PTPQ into partial-path queries, and merge-joins their solutions. We also develop PartialTreeStack, an original polynomial time holistic algorithm for PTPQs. To the best of our knowledge, this is the first algorithm to support the evaluation of such a broad structural fragment of XPath in the inverted lists evaluation model. We provide a theoretical analysis of our algorithm and identify cases where it is asymptotically optimal. An extensive experimental evaluation shows that it is more efficient, robust, and stable than the other two and it outperforms a state-of-the art XQuery engine on PTPQs.

Efficient processing of twig query with compound predicates in fuzzy XML

In order to find all occurrences of a twig pattern in XML documents, a considerable number of twig pattern matching algorithms have been proposed. Previous algorithms mainly focus on the conjunctive twig queries whose sibling edges are only connected by AND connectives. However, meaningful twig queries typically contain arbitrarily specified compound predicates including AND, OR and NOT in practical applications. Moreover, as far as we know, none of these twig matching algorithms have examined the processing of twig queries which contain all the compound predicates over fuzzy XML data. In this paper, we present the first study on evaluating twig queries with AND, OR and NOT connectives in fuzzy XML. We propose a novel holistic twig matching algorithm called LTwig for answering these complex queries. Our algorithm guarantees that the answers can be obtained by scanning the relevant data of the data streams associated with the nodes appearing in the twig pattern only once. A comprehensive set of experiments is finally carried out to demonstrate the effectiveness and efficiency of our proposed approach.

Optimal and efficient generalized twig pattern processing: a combination of preorder and postorder filterings

Searching for occurrences of a twig pattern query (TPQ) in an XML document is a core task of all XML database query languages. The generalized twig pattern (GTP) extends the TPQ model to include semantics related to output nodes, optional nodes, and boolean expressions which are part of the XQuery language. Preorder filtering holistic algorithms such as TwigStack represent a significant class of TPQ processing approaches with a linear worst-case I/O complexity with respect to the sum of the input and output sizes for some query classes. Another important class of holistic approaches is represented by postorder filtering holistic algorithms such as $$\text{ Twig}^2$$ Stack which introduced a linear output enumeration time with respect to the result size. In this article, we introduce a holistic algorithm called GTPStack which is the first approach capable of processing a GTP with a linear worst-case I/O complexity with respect to the GTP result size. This is achieved by using a combination of the preorder and postorder filterings before storing nodes in an intermediate storage. Additionally, another contribution of this article is an introduction of a new perspective of holistic algorithm optimality. We show that the optimality depends not only on a query class but also on XML document characteristics. This new view on the optimality extends the general knowledge about the type of queries for which the holistic algorithms are optimal. Moreover, it allows us to determine that GTPStack is optimal for any GTP when a specific XML document is considered. We present a comprehensive experimental study of the state-of-the-art holistic algorithms showing under which conditions GTPStack outperforms the other holistic approaches.

Extended XML Tree Pattern Matching: Theories and Algorithms

As business and enterprises generate and exchange XML data more often, there is an increasing need for efficient processing of queries on XML data. Searching for the occurrences of a tree pattern query in an XML database is a core operation in XML query processing. Prior works demonstrate that holistic twig pattern matching algorithm is an efficient technique to answer an XML tree pattern with parent-child (P-C) and ancestor-descendant (A-D) relationships, as it can effectively control the size of intermediate results during query processing. However, XML query languages (e.g., XPath and XQuery) define more axes and functions such as negation function, order-based axis, and wildcards. In this paper, we research a large set of XML tree pattern, called extended XML tree pattern, which may include P-C, A-D relationships, negation functions, wildcards, and order restriction. We establish a theoretical framework about “matching cross” which demonstrates the intrinsic reason in the proof of optimality on holistic algorithms. Based on our theorems, we propose a set of novel algorithms to efficiently process three categories of extended XML tree patterns. A set of experimental results on both real-life and synthetic data sets demonstrate the effectiveness and efficiency of our proposed theories and algorithms.

Model-based reasoning: using visual tools to reveal student learning

Using visual models is common in science and should become more common in classrooms. Our research group has developed and completed studies on the use of a visual modeling tool, the Concept Connector. This modeling tool consists of an online concept mapping Java applet that has automatic scoring functions we refer to as Robograder. The Concept Connector enables students in large introductory science courses to visualize their thinking through online model building. The Concept Connector's flexible scoring system, based on tested grading schemes as well as instructor input, has enabled >1,000 physiology students to build maps of their ideas about plant and animal physiology with the guidance of automatic and immediate online scoring of homework. Criterion concept maps developed by instructors in this project contain numerous expert-generated or "correct" propositions connecting two concept words together with a linking phrase. In this study, holistic algorithms were used to test automated methods of scoring concept maps that might work as well as a human grader.

Optimization designs and performance comparison of two CUSUM schemes for monitoring process shifts in mean and variance

In statistical process control (SPC), when dealing with a quality characteristic x that is a variable, it is usually necessary to monitor both the mean value and variability. This article proposes an optimization algorithm (called the holistic algorithm) to design the CUSUM charts for this purpose. It facilitates the determination of the charting parameters of the CUSUM charts and considerably or significantly increases their overall detection effectiveness. A single CUSUM chart (called the ABS CUSUM chart) has been developed by the holistic algorithm and fully investigated. This chart is able to detect two-sided mean shifts and increasing variance shifts by inspecting the absolute value of sample mean shift. The results of performance studies show that the overall performance of the ABS CUSUM chart is nearly as good as an optimal 3-CUSUM scheme (a scheme incorporating three individual CUSUM charts). However, since the ABS CUSUM chart is easier for implementation and design, it may be more suitable for many SPC applications in which both mean and variance of a variable have to be monitored.

Evaluation Techniques for Generalized Path Pattern Queries on XML Data

Finding the occurrences of structural patterns in XML data is a key operation in XML query processing. Existing algorithms for this operation focus almost exclusively on path patterns or tree patterns. Current applications of XML require querying of data whose structure is complex or is not fully known to the user, or integrating XML data sources with different structures. These applications have motivated recently the introduction of query languages that allow a partial specification of path patterns in a query. In this paper, we consider partial path queries, a generalization of path pattern queries, and we focus on their efficient evaluation under the indexed streaming evaluation model. Our approach explicitly deals with repeated labels (that is, multiple occurrences of the same label in a query). We show that partial path queries can be represented as rooted dags for which a topological ordering of the nodes exists. We present three algorithms for the efficient evaluation of these queries. The first one exploits a structural summary of data to generate a set of path patterns that together are equivalent to a partial path query. To evaluate these path patterns, we extend a previous algorithm for path-pattern queries so that it can work on path patterns with repeated labels. The second one extracts a spanning tree from the query dag, uses a stack-based algorithm to find the matches of the root-to-leaf paths in the tree, and merge-joins the matches to compute the answer. Finally, the third one exploits multiple pointers of stack entries and a topological ordering of the query dag to apply a stack-based holistic technique. We analyze our algorithms and perform extensive experimental evaluations. Our experimental results show that the holistic algorithm outperforms the other ones. Our approaches are the first ones to efficiently evaluate this class of queries in the indexed streaming model.

Macro–micro interlocked simulation algorithm: an exemplification for aurora arc evolution

Using an innovative holistic simulation algorithm that can self-consistently treat a system that evolves as cooperation between macroscopic and microscopic processes, the evolution of a colorful aurora arc is beautifully reproduced as the result of cooperation between the global field-aligned feedback instability of the coupled magnetosphere–ionosphere system and the ensuing microscopic ion-acoustic instability that generates electric double layers and accelerates aurora electrons. These results are in agreement with rocket and satellite observations. This shows that the proposed holistic algorithm could be a reliable tool to reveal complex real dramatic events and become, in the near future, a viable scientifically secure prediction tool for natural disasters such as earthquakes, landslides and floods caused by typhoons.

Efficient processing of ordered XML twig pattern matching based on extended Dewey

Finding all occurrences of a twig pattern is a core operation of extensible markup language (XML) query processing. Holistic twig join algorithms, which avoid a large number of intermediate results, represent the state-of-the-art algorithms. However, ordered XML twig join is mentioned rarely in the literature and previous algorithms developed in attempts to solve the problem of ordered twig pattern (OTP) matching have poor performance. In this paper, we first propose a novel children linked stacks encoding scheme to represent compactly the partial ordered twig join results. Based on this encoding scheme and extended Dewey, we design a novel holistic OTP matching algorithm, called OTJFast, which needs only to access the labels of the leaf query nodes. Furthermore, we propose a new algorithm, named OTJFaster, incorporating three effective optimization rules to avoid unnecessary computations. This works well on available indices (such as B+-tree), skipping useless elements. Thus, not only is disk access reduced greatly, but also many unnecessary computations are avoided. Finally, our extensive experiments over both real and synthetic datasets indicate that our algorithms are superior to previous approaches.

Recent advances in face biometrics with Gabor wavelets: A review

In this paper we focus on the great outburst of Gabor-based methods for face biometrics occurred in the last few years. Analytical approaches rely on the representation of a face with the Gabor responses computed on specific landmarks, while holistic methods take into account the face as a whole. We explore the role played by Gabor wavelets in international competitions, such as FERET or BANCA, where Gabor algorithms ranked first above other methods. By means of the analysis of five quantifiable factors, we present a ranking of methods as a function of their goodness. An enhanced version of AdaBoost, a complex-valued Gabor representation and a Gabor adaptive downsampling method are the three algorithms that lead the ranking. We also show there is a global trend toward face recognition methods, as well as toward Gabor holistic algorithms, due to their higher success rates.

A unified framework for improving the accuracy of all holistic face identification algorithms

Reconstructing the challenging human face identification process as a stability problem, we show that Electoral College can be used as a framework that provides a significantly enhanced face identification process by improving the accuracy of all holistic algorithms. The results are demonstrated by extensive experiments on benchmark face databases applying the Electoral College framework embedded with standard baseline and newly developed face identification algorithms.

Principles of Holism for sequential twig pattern matching

Modern applications face the challenge of dealing with structured and semi-structured data. They have to deal with complex objects, most of them presenting some kind of internal structure, which often forms a hierarchy. Though XML documents are the most known, chemical compounds, CAD drawings, web-sites and many other applications have to deal with similar problems. In such environments, ordered and unordered tree pattern matching are the fundamental search operations. One of the main thrusts of research activities for tree pattern matching is the class of holistic approaches. Their ultimate goal is to evaluate a query twig as a whole by relying on sequential access patterns and non trivial auxiliary storage structures, typically stored in main memory. Based on the pre/post-order ranks of individual tree nodes, we establish strong theoretical bases as a foundation for correct and efficient holistic pattern matching algorithms. In particular, we define and prove sufficient and necessary conditions to minimize the amount of data retained in memory, thus introducing a correct and complete framework on which different holistic solutions can be compared. We also show how these rules can be applied for building algorithms for ordered and unordered tree-pattern matching. Thanks to the above theoretical achievements, each holistic algorithm gains in efficiency as it is directly implemented on the adopted numbering scheme, avoids expensive matching refinements and keeps memory requirements stable. An experimental analysis and comparison with previous approaches confirms the superiority of our approach tested on synthetic as well as real-life data sets.

Holistically Stream-based Processing Xtwig Queries

Unlike a twig query, an Xtwig query contains some selection predicates with reverse axes which are either ancestor or parent. To evaluate such queries in the stream-based context, some rewriting rules have been proposed to transform the paths with reverse axes into equivalent reverse-axis-free ones. However, the transformation method is expensive due to multiple scanning input streams and the generation of unnecessary intermediate results. To solve these problems, a holistic stream-based algorithm XtwigStack is proposed for Xtwig queries. Experiments show that XtwigStack is much more efficient than the transformation method.

Twig pattern matching based on compressed path labeling scheme

Holistic twig query processing techniques based on region encoding have been developed to minimize the intermediate results, namely, those root-to-leaf path matches that are not in the final twig results. These algorithms have to scan all the streams of tags in query patterns. However, useless path matches cannot be completely avoided. TJFast which is based on the labeling scheme of Extended Dewey has been proposed to avoid useless intermediate results, and it only needs to access the labels of the leaf query nodes. However, it don’t concern about the characteristics of elements with the same parent, and it has to merge join all the intermediate results which are evaluated during the first phrase. We propose a new labeling scheme to compress the XML elements which have the same characteristic. Based on the compressed path-labeled streams, a new novel holistic twig query algorithm named CPJoin is designed. Finally, implementation results are provided to show that CPJoin has good performance on both real and synthetic data.

Element substitution algorithm for general two-terminal network reliability analyses

The computation of the reliability of two-terminal networks is a classical reliability problem. For these types of problems, one is interested, from a general perspective, in obtaining the probability that two specific nodes can communicate. This paper presents a holistic algorithm for the analysis of general networks that follow a two-terminal rationale. The algorithm is based on a set replacement approach and an element inheritance strategy that effectively obtains the minimal cut sets associated with a given network. The vast majority of methods available for obtaining two-terminal reliability are generally based on assumptions about the performance of the network. Some methods assume network components can be in one of two states: (i) either completely failed; or (ii) perfectly functioning, others usually assume that nodes are perfectly reliable and thus, these methods have to be complemented or transformed to account for node failure, and the remaining methods assume minimal cut sets can be readily computed in order to analyze more complex network and component behavior. The algorithm presented in this paper significantly differs from previous approaches available in the literature in the sense that it is based on a predecessor matrix and an element substitution technique that allows for the exact computation of minimal cut sets and the immediate inclusion of node failure without any changes to the pseudo-code. Several case networks are used to validate and illustrate the algorithms.

Constraint batch sizing in a lean environment

The underlying research discussed in this paper is derived from a research programme along three tiers of an automotive steel supply network. The main objective of the initial research was to pinpoint wasteful activities in the supply chain, and in later stages, to develop solutions. The preliminary work involved mapping the dynamics of the supply chain focusing on how the demand information is passed from the final customer back to the material suppliers. Production scheduling approaches were found to be a main cause of distortion in the dynamics of supply chain, and the initial studies led to proposals for scheduling improvements both within and between companies. These proposals include changing the scheduling frequency in accordance to the specific demand patterns – coupled with the use of kanban, changeover reduction, and total preventive maintenance. Specifically, the scheduling of batch operations in first and second tier suppliers of the supply chain was identified as a key problem area in further supply chain dynamics analysis. Therefore, a new and holistic scheduling algorithm was developed, which will be presented and discussed in theory and application.

Holistic algorithms: A paradigm for multiprocessor programming

The concept ‘holistic algorithm’ is a MIMD paradigm for defining the highest level of parallelism possible in the design of an algorithm. In this paper we show how a general holistic algorithm may be implemented by using the monitor synchronization concept. As an application a holistic vertex enumeration algorithm is designed based on a sequential predecessor.