Indian Academy of Sciences (India)
have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming language Is called a program. From activities 1-3, we can observe that: • Each activity is a command.
Indian Academy of Sciences (India)
algorithms such as synthetic (polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language ... ·1 x:=sln(theta) x : = sm(theta) 1. ~. Idl d.t Read A.B,C. ~ lei ~ Print x.y.z. L;;;J. Figure 2 Symbols used In flowchart language to rep- resent Assignment, Read.
Indian Academy of Sciences (India)
In the previous articles, we have discussed various common data-structures such as arrays, lists, queues and trees and illustrated the widely used algorithm design paradigm referred to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted ...
Indian Academy of Sciences (India)
In the program shown in Figure 1, we have repeated the algorithm. M times and we can make the following observations. Each block is essentially a different instance of "code"; that is, the objects differ by the value to which N is initialized before the execution of the. "code" block. Thus, we can now avoid the repetition of the ...
Indian Academy of Sciences (India)
algorithms built into the computer corresponding to the logic- circuit rules that are used to .... For the purpose of carrying ou t ari thmetic or logical operations the memory is organized in terms .... In fixed point representation, one essentially uses integer arithmetic operators assuming the binary point to be at some point other ...
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
DEFF Research Database (Denmark)
Markham, Annette
layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...
Directory of Open Access Journals (Sweden)
Anna Bourmistrova
2011-02-01
Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.
Energy Technology Data Exchange (ETDEWEB)
Grefenstette, J.J.
1994-12-31
Genetic algorithms solve problems by using principles inspired by natural population genetics: They maintain a population of knowledge structures that represent candidate solutions, and then let that population evolve over time through competition and controlled variation. GAs are being applied to a wide range of optimization and learning problems in many domains.
Casanova, Henri; Robert, Yves
2008-01-01
""…The authors of the present book, who have extensive credentials in both research and instruction in the area of parallelism, present a sound, principled treatment of parallel algorithms. … This book is very well written and extremely well designed from an instructional point of view. … The authors have created an instructive and fascinating text. The book will serve researchers as well as instructors who need a solid, readable text for a course on parallelism in computing. Indeed, for anyone who wants an understandable text from which to acquire a current, rigorous, and broad vi
Skiena, Steven S
2008-01-01
Explaining designing algorithms, and analyzing their efficacy and efficiency, this book covers combinatorial algorithms technology, stressing design over analysis. It presents instruction on methods for designing and analyzing computer algorithms. It contains the catalog of algorithmic resources, implementations and a bibliography
DEFF Research Database (Denmark)
Bucher, Taina
2017-01-01
of algorithms affect people's use of these platforms, if at all? To help answer these questions, this article examines people's personal stories about the Facebook algorithm through tweets and interviews with 25 ordinary users. To understand the spaces where people and algorithms meet, this article develops....... Examining how algorithms make people feel, then, seems crucial if we want to understand their social power....
Algorithmically specialized parallel computers
Snyder, Lawrence; Gannon, Dennis B
1985-01-01
Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster
Approximate iterative algorithms
Almudevar, Anthony Louis
2014-01-01
Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and convergence rates, and for the optimal design of such algorithms. Techniques of functional analysis are used to derive analytical relationships between approximation methods and convergence properties for general classes of algorithms. This work provides the necessary background in functional analysis a
Autonomous Star Tracker Algorithms
DEFF Research Database (Denmark)
Betto, Maurizio; Jørgensen, John Leif; Kilsgaard, Søren
1998-01-01
Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances.......Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances....
Divasón, Jose; Joosten, Sebastiaan; Thiemann, René; Yamada, Akihisa
2018-01-01
The Lenstra-Lenstra-Lovász basis reduction algorithm, also known as LLL algorithm, is an algorithm to find a basis with short, nearly orthogonal vectors of an integer lattice. Thereby, it can also be seen as an approximation to solve the shortest vector problem (SVP), which is an NP-hard problem,
Nature-inspired optimization algorithms
Yang, Xin-She
2014-01-01
Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning
Akl, Selim G
1985-01-01
Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the
VISUALIZATION OF PAGERANK ALGORITHM
Perhaj, Ervin
2013-01-01
The goal of the thesis is to develop a web application that help users understand the functioning of the PageRank algorithm. The thesis consists of two parts. First we develop an algorithm to calculate PageRank values of web pages. The input of algorithm is a list of web pages and links between them. The user enters the list through the web interface. From the data the algorithm calculates PageRank value for each page. The algorithm repeats the process, until the difference of PageRank va...
Digital Arithmetic: Division Algorithms
DEFF Research Database (Denmark)
Montuschi, Paolo; Nannarelli, Alberto
2017-01-01
implement it in hardware to not compromise the overall computation performances. This entry explains the basic algorithms, suitable for hardware and software, to implement division in computer systems. Two classes of algorithms implement division or square root: digit-recurrence and multiplicative (e.......g., Newton–Raphson) algorithms. The first class of algorithms, the digit-recurrence type, is particularly suitable for hardware implementation as it requires modest resources and provides good performance on contemporary technology. The second class of algorithms, the multiplicative type, requires...
Modified Clipped LMS Algorithm
Directory of Open Access Journals (Sweden)
Lotfizad Mojtaba
2005-01-01
Full Text Available Abstract A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.
Yongquan Zhou; Jian Xie; Liangliang Li; Mingzhi Ma
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformati...
Recursive forgetting algorithms
DEFF Research Database (Denmark)
Parkum, Jens; Poulsen, Niels Kjølstad; Holst, Jan
1992-01-01
In the first part of the paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied...... to a specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm...
Explaining algorithms using metaphors
Forišek, Michal
2013-01-01
There is a significant difference between designing a new algorithm, proving its correctness, and teaching it to an audience. When teaching algorithms, the teacher's main goal should be to convey the underlying ideas and to help the students form correct mental models related to the algorithm. This process can often be facilitated by using suitable metaphors. This work provides a set of novel metaphors identified and developed as suitable tools for teaching many of the 'classic textbook' algorithms taught in undergraduate courses worldwide. Each chapter provides exercises and didactic notes fo
Spectral Decomposition Algorithm (SDA)
National Aeronautics and Space Administration — Spectral Decomposition Algorithm (SDA) is an unsupervised feature extraction technique similar to PCA that was developed to better distinguish spectral features in...
Algorithms in Algebraic Geometry
Dickenstein, Alicia; Sommese, Andrew J
2008-01-01
In the last decade, there has been a burgeoning of activity in the design and implementation of algorithms for algebraic geometric computation. Some of these algorithms were originally designed for abstract algebraic geometry, but now are of interest for use in applications and some of these algorithms were originally designed for applications, but now are of interest for use in abstract algebraic geometry. The workshop on Algorithms in Algebraic Geometry that was held in the framework of the IMA Annual Program Year in Applications of Algebraic Geometry by the Institute for Mathematics and Its
DEFF Research Database (Denmark)
Bilardi, Gianfranco; Pietracaprina, Andrea; Pucci, Geppino
2016-01-01
A framework is proposed for the design and analysis of network-oblivious algorithms, namely algorithms that can run unchanged, yet efficiently, on a variety of machines characterized by different degrees of parallelism and communication capabilities. The framework prescribes that a network-oblivi...
DEFF Research Database (Denmark)
Husfeldt, Thore
2015-01-01
This chapter presents an introduction to graph colouring algorithms. The focus is on vertex-colouring algorithms that work for general classes of graphs with worst-case performance guarantees in a sequential model of computation. The presentation aims to demonstrate the breadth of available...
Indian Academy of Sciences (India)
Computing connectivities between all pairs of vertices good algorithm wrt both space and time to compute the exact solution. Computing all-pairs distances good algorithm wrt both space and time - but only approximate solutions can be found. Optimal bipartite matchings an optimal matching need not always exist.
Algorithms and Their Explanations
Benini, M.; Gobbo, F.; Beckmann, A.; Csuhaj-Varjú, E.; Meer, K.
2014-01-01
By analysing the explanation of the classical heapsort algorithm via the method of levels of abstraction mainly due to Floridi, we give a concrete and precise example of how to deal with algorithmic knowledge. To do so, we introduce a concept already implicit in the method, the ‘gradient of
8. Algorithm Design Techniques
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 8. Algorithms - Algorithm Design Techniques. R K Shyamasundar. Series Article Volume 2 ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...
8. Algorithm Design Techniques
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 8. Algorithms - Algorithm Design Techniques. R K Shyamasundar. Series Article Volume 2 Issue 8 August 1997 pp 6-17. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/002/08/0006-0017 ...
Introduction to Algorithms -14 ...
Indian Academy of Sciences (India)
As elaborated in the earlier articles, algorithms must be written in an unambiguous formal way. Algorithms intended for automatic execution by computers are called programs and the formal notations used to write programs are called programming languages. The concept of a programming language has been around ...
Directory of Open Access Journals (Sweden)
Francesca Musiani
2013-08-01
Full Text Available Algorithms are increasingly often cited as one of the fundamental shaping devices of our daily, immersed-in-information existence. Their importance is acknowledged, their performance scrutinised in numerous contexts. Yet, a lot of what constitutes 'algorithms' beyond their broad definition as “encoded procedures for transforming input data into a desired output, based on specified calculations” (Gillespie, 2013 is often taken for granted. This article seeks to contribute to the discussion about 'what algorithms do' and in which ways they are artefacts of governance, providing two examples drawing from the internet and ICT realm: search engine queries and e-commerce websites’ recommendations to customers. The question of the relationship between algorithms and rules is likely to occupy an increasingly central role in the study and the practice of internet governance, in terms of both institutions’ regulation of algorithms, and algorithms’ regulation of our society.
Totally parallel multilevel algorithms
Frederickson, Paul O.
1988-01-01
Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.
Group leaders optimization algorithm
Daskin, Anmer; Kais, Sabre
2011-03-01
We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multi-dimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N 2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for a two-qubit Grover search algorithm which is a quantum algorithm providing quadratic speedup over the classical counterpart.
Directory of Open Access Journals (Sweden)
Hans Schonemann
1996-12-01
Full Text Available Some algorithms for singularity theory and algebraic geometry The use of Grobner basis computations for treating systems of polynomial equations has become an important tool in many areas. This paper introduces of the concept of standard bases (a generalization of Grobner bases and the application to some problems from algebraic geometry. The examples are presented as SINGULAR commands. A general introduction to Grobner bases can be found in the textbook [CLO], an introduction to syzygies in [E] and [St1]. SINGULAR is a computer algebra system for computing information about singularities, for use in algebraic geometry. The basic algorithms in SINGULAR are several variants of a general standard basis algorithm for general monomial orderings (see [GG]. This includes wellorderings (Buchberger algorithm ([B1], [B2] and tangent cone orderings (Mora algorithm ([M1], [MPT] as special cases: It is able to work with non-homogeneous and homogeneous input and also to compute in the localization of the polynomial ring in 0. Recent versions include algorithms to factorize polynomials and a factorizing Grobner basis algorithm. For a complete description of SINGULAR see [Si].
A New Modified Firefly Algorithm
Directory of Open Access Journals (Sweden)
Medha Gupta
2016-07-01
Full Text Available Nature inspired meta-heuristic algorithms studies the emergent collective intelligence of groups of simple agents. Firefly Algorithm is one of the new such swarm-based metaheuristic algorithm inspired by the flashing behavior of fireflies. The algorithm was first proposed in 2008 and since then has been successfully used for solving various optimization problems. In this work, we intend to propose a new modified version of Firefly algorithm (MoFA and later its performance is compared with the standard firefly algorithm along with various other meta-heuristic algorithms. Numerical studies and results demonstrate that the proposed algorithm is superior to existing algorithms.
Lewis, Dustin A.; Blum, Gabriella; Modirzadeh, Naz K.
2016-01-01
In this briefing report, we introduce a new concept — war algorithms — that elevates algorithmically-derived “choices” and “decisions” to a, and perhaps the, central concern regarding technical autonomy in war. We thereby aim to shed light on and recast the discussion regarding “autonomous weapon systems.” We define “war algorithm” as any algorithm that is expressed in computer code, that is effectuated through a constructed system, and that is capable of operating in relation to armed co...
Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization.
Directory of Open Access Journals (Sweden)
Yongquan Zhou
2014-01-01
Full Text Available Bat algorithm (BA is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization.
Unsupervised learning algorithms
Aydin, Kemal
2016-01-01
This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering,...
Algorithms for parallel computers
International Nuclear Information System (INIS)
Churchhouse, R.F.
1985-01-01
Until relatively recently almost all the algorithms for use on computers had been designed on the (usually unstated) assumption that they were to be run on single processor, serial machines. With the introduction of vector processors, array processors and interconnected systems of mainframes, minis and micros, however, various forms of parallelism have become available. The advantage of parallelism is that it offers increased overall processing speed but it also raises some fundamental questions, including: (i) which, if any, of the existing 'serial' algorithms can be adapted for use in the parallel mode. (ii) How close to optimal can such adapted algorithms be and, where relevant, what are the convergence criteria. (iii) How can we design new algorithms specifically for parallel systems. (iv) For multi-processor systems how can we handle the software aspects of the interprocessor communications. Aspects of these questions illustrated by examples are considered in these lectures. (orig.)
Static Analysis Numerical Algorithms
2016-04-01
STATIC ANALYSIS OF NUMERICAL ALGORITHMS KESTREL TECHNOLOGY, LLC APRIL 2016 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION...3. DATES COVERED (From - To) NOV 2013 – NOV 2015 4. TITLE AND SUBTITLE STATIC ANALYSIS OF NUMERICAL ALGORITHMS 5a. CONTRACT NUMBER FA8750-14-C...and Honeywell Aerospace Advanced Technology to combine model-based development of complex avionics control software with static analysis of the
Improved Chaff Solution Algorithm
2009-03-01
Programme de démonstration de technologies (PDT) sur l’intégration de capteurs et de systèmes d’armes embarqués (SISWS), un algorithme a été élaboré...technologies (PDT) sur l’intégration de capteurs et de systèmes d’armes embarqués (SISWS), un algorithme a été élaboré pour déterminer automatiquement
Optimization algorithms and applications
Arora, Rajesh Kumar
2015-01-01
Choose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs. The book covers both gradient and stochastic methods as solution techniques for unconstrained and constrained optimization problems. It discusses the conjugate gradient method, Broyden-Fletcher-Goldfarb-Shanno algorithm, Powell method, penalty function, augmented Lagrange multiplier method, sequential quadratic programming, method of feasible direc
Image Segmentation Algorithms Overview
Yuheng, Song; Hao, Yan
2017-01-01
The technology of image segmentation is widely used in medical image processing, face recognition pedestrian detection, etc. The current image segmentation techniques include region-based segmentation, edge detection segmentation, segmentation based on clustering, segmentation based on weakly-supervised learning in CNN, etc. This paper analyzes and summarizes these algorithms of image segmentation, and compares the advantages and disadvantages of different algorithms. Finally, we make a predi...
Algorithmic Principles of Mathematical Programming
Faigle, Ulrich; Kern, Walter; Still, Georg
2002-01-01
Algorithmic Principles of Mathematical Programming investigates the mathematical structures and principles underlying the design of efficient algorithms for optimization problems. Recent advances in algorithmic theory have shown that the traditionally separate areas of discrete optimization, linear
Directory of Open Access Journals (Sweden)
Wang Zi Min
2016-01-01
Full Text Available With the development of social services, people’s living standards improve further requirements, there is an urgent need for a way to adapt to the complex situation of the new positioning technology. In recent years, RFID technology have a wide range of applications in all aspects of life and production, such as logistics tracking, car alarm, security and other items. The use of RFID technology to locate, it is a new direction in the eyes of the various research institutions and scholars. RFID positioning technology system stability, the error is small and low-cost advantages of its location algorithm is the focus of this study.This article analyzes the layers of RFID technology targeting methods and algorithms. First, RFID common several basic methods are introduced; Secondly, higher accuracy to political network location method; Finally, LANDMARC algorithm will be described. Through this it can be seen that advanced and efficient algorithms play an important role in increasing RFID positioning accuracy aspects.Finally, the algorithm of RFID location technology are summarized, pointing out the deficiencies in the algorithm, and put forward a follow-up study of the requirements, the vision of a better future RFID positioning technology.
A Parallel Butterfly Algorithm
Poulson, Jack
2014-02-04
The butterfly algorithm is a fast algorithm which approximately evaluates a discrete analogue of the integral transform (Equation Presented.) at large numbers of target points when the kernel, K(x, y), is approximately low-rank when restricted to subdomains satisfying a certain simple geometric condition. In d dimensions with O(Nd) quasi-uniformly distributed source and target points, when each appropriate submatrix of K is approximately rank-r, the running time of the algorithm is at most O(r2Nd logN). A parallelization of the butterfly algorithm is introduced which, assuming a message latency of α and per-process inverse bandwidth of β, executes in at most (Equation Presented.) time using p processes. This parallel algorithm was then instantiated in the form of the open-source DistButterfly library for the special case where K(x, y) = exp(iΦ(x, y)), where Φ(x, y) is a black-box, sufficiently smooth, real-valued phase function. Experiments on Blue Gene/Q demonstrate impressive strong-scaling results for important classes of phase functions. Using quasi-uniform sources, hyperbolic Radon transforms, and an analogue of a three-dimensional generalized Radon transform were, respectively, observed to strong-scale from 1-node/16-cores up to 1024-nodes/16,384-cores with greater than 90% and 82% efficiency, respectively. © 2014 Society for Industrial and Applied Mathematics.
Directory of Open Access Journals (Sweden)
Hanns Holger Rutz
2016-11-01
Full Text Available Although the concept of algorithms has been established a long time ago, their current topicality indicates a shift in the discourse. Classical definitions based on logic seem to be inadequate to describe their aesthetic capabilities. New approaches stress their involvement in material practices as well as their incompleteness. Algorithmic aesthetics can no longer be tied to the static analysis of programs, but must take into account the dynamic and experimental nature of coding practices. It is suggested that the aesthetic objects thus produced articulate something that could be called algorithmicity or the space of algorithmic agency. This is the space or the medium – following Luhmann’s form/medium distinction – where human and machine undergo mutual incursions. In the resulting coupled “extimate” writing process, human initiative and algorithmic speculation cannot be clearly divided out any longer. An observation is attempted of defining aspects of such a medium by drawing a trajectory across a number of sound pieces. The operation of exchange between form and medium I call reconfiguration and it is indicated by this trajectory.
Algorithms in invariant theory
Sturmfels, Bernd
2008-01-01
J. Kung and G.-C. Rota, in their 1984 paper, write: "Like the Arabian phoenix rising out of its ashes, the theory of invariants, pronounced dead at the turn of the century, is once again at the forefront of mathematics". The book of Sturmfels is both an easy-to-read textbook for invariant theory and a challenging research monograph that introduces a new approach to the algorithmic side of invariant theory. The Groebner bases method is the main tool by which the central problems in invariant theory become amenable to algorithmic solutions. Students will find the book an easy introduction to this "classical and new" area of mathematics. Researchers in mathematics, symbolic computation, and computer science will get access to a wealth of research ideas, hints for applications, outlines and details of algorithms, worked out examples, and research problems.
Detection of algorithmic trading
Bogoev, Dimitar; Karam, Arzé
2017-10-01
We develop a new approach to reflect the behavior of algorithmic traders. Specifically, we provide an analytical and tractable way to infer patterns of quote volatility and price momentum consistent with different types of strategies employed by algorithmic traders, and we propose two ratios to quantify these patterns. Quote volatility ratio is based on the rate of oscillation of the best ask and best bid quotes over an extremely short period of time; whereas price momentum ratio is based on identifying patterns of rapid upward or downward movement in prices. The two ratios are evaluated across several asset classes. We further run a two-stage Artificial Neural Network experiment on the quote volatility ratio; the first stage is used to detect the quote volatility patterns resulting from algorithmic activity, while the second is used to validate the quality of signal detection provided by our measure.
CERN. Geneva; PUNZI, Giovanni
2015-01-01
Charge particle reconstruction is one of the most demanding computational tasks found in HEP, and it becomes increasingly important to perform it in real time. We envision that HEP would greatly benefit from achieving a long-term goal of making track reconstruction happen transparently as part of the detector readout ("detector-embedded tracking"). We describe here a track-reconstruction approach based on a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature ('RETINA algorithm'). It turns out that high-quality tracking in large HEP detectors is possible with very small latencies, when this algorithm is implemented in specialized processors, based on current state-of-the-art, high-speed/high-bandwidth digital devices.
Handbook of Memetic Algorithms
Cotta, Carlos; Moscato, Pablo
2012-01-01
Memetic Algorithms (MAs) are computational intelligence structures combining multiple and various operators in order to address optimization problems. The combination and interaction amongst operators evolves and promotes the diffusion of the most successful units and generates an algorithmic behavior which can handle complex objective functions and hard fitness landscapes. “Handbook of Memetic Algorithms” organizes, in a structured way, all the the most important results in the field of MAs since their earliest definition until now. A broad review including various algorithmic solutions as well as successful applications is included in this book. Each class of optimization problems, such as constrained optimization, multi-objective optimization, continuous vs combinatorial problems, uncertainties, are analysed separately and, for each problem, memetic recipes for tackling the difficulties are given with some successful examples. Although this book contains chapters written by multiple authors, ...
Named Entity Linking Algorithm
Directory of Open Access Journals (Sweden)
M. F. Panteleev
2017-01-01
Full Text Available In the tasks of processing text in natural language, Named Entity Linking (NEL represents the task to define and link some entity, which is found in the text, with some entity in the knowledge base (for example, Dbpedia. Currently, there is a diversity of approaches to solve this problem, but two main classes can be identified: graph-based approaches and machine learning-based ones. Graph and Machine Learning approaches-based algorithm is proposed accordingly to the stated assumptions about the interrelations of named entities in a sentence and in general.In the case of graph-based approaches, it is necessary to solve the problem of identifying an optimal set of the related entities according to some metric that characterizes the distance between these entities in a graph built on some knowledge base. Due to limitations in processing power, to solve this task directly is impossible. Therefore, its modification is proposed. Based on the algorithms of machine learning, an independent solution cannot be built due to small volumes of training datasets relevant to NEL task. However, their use can contribute to improving the quality of the algorithm. The adaptation of the Latent Dirichlet Allocation model is proposed in order to obtain a measure of the compatibility of attributes of various entities encountered in one context.The efficiency of the proposed algorithm was experimentally tested. A test dataset was independently generated. On its basis the performance of the model was compared using the proposed algorithm with the open source product DBpedia Spotlight, which solves the NEL problem.The mockup, based on the proposed algorithm, showed a low speed as compared to DBpedia Spotlight. However, the fact that it has shown higher accuracy, stipulates the prospects for work in this direction.The main directions of development were proposed in order to increase the accuracy of the system and its productivity.
A cluster algorithm for graphs
S. van Dongen
2000-01-01
textabstractA cluster algorithm for graphs called the emph{Markov Cluster algorithm (MCL~algorithm) is introduced. The algorithm provides basically an interface to an algebraic process defined on stochastic matrices, called the MCL~process. The graphs may be both weighted (with nonnegative weight)
Fokkinga, M.M.
1992-01-01
An algorithm is the input-output effect of a computer program; mathematically, the notion of algorithm comes close to the notion of function. Just as arithmetic is the theory and practice of calculating with numbers, so is ALGORITHMICS the theory and practice of calculating with algorithms. Just as
Parallel Algorithms and Patterns
Energy Technology Data Exchange (ETDEWEB)
Robey, Robert W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-16
This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.
Wireless communications algorithmic techniques
Vitetta, Giorgio; Colavolpe, Giulio; Pancaldi, Fabrizio; Martin, Philippa A
2013-01-01
This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It focuses on single user systems, so ignoring multiple access techniques. Moreover, emphasis is put on single-input single-output (SISO) systems, although some relevant topics about multiple-input multiple-output (MIMO) systems are also illustrated.Comprehensive wireless specific guide to algorithmic techniquesProvides a detailed analysis of channel equalization and channel coding for wi
Algorithms for Reinforcement Learning
Szepesvari, Csaba
2010-01-01
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms'
New Optimization Algorithms in Physics
Hartmann, Alexander K
2004-01-01
Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have not been presented comprehensively until now. This presentation of recently developed algorithms applied in physics, including demonstrations of how they work and related results, aims to encourage their application, and as such the algorithms selected cover concepts and methods from statistical physics to optimization problems emerging in theoretical computer science.
Ball, Stanley
1986-01-01
Presents a developmental taxonomy which promotes sequencing activities to enhance the potential of matching these activities with learner needs and readiness, suggesting that the order commonly found in the classroom needs to be inverted. The proposed taxonomy (story, skill, and algorithm) involves problem-solving emphasis in the classroom. (JN)
Ferguson, David L.; Henderson, Peter B.
1987-01-01
Designed initially for use in college computer science courses, the model and computer-aided instructional environment (CAIE) described helps students develop algorithmic problem solving skills. Cognitive skills required are discussed, and implications for developing computer-based design environments in other disciplines are suggested by…
Improved Approximation Algorithm for
Byrka, Jaroslaw; Li, S.; Rybicki, Bartosz
2014-01-01
We study the k-level uncapacitated facility location problem (k-level UFL) in which clients need to be connected with paths crossing open facilities of k types (levels). In this paper we first propose an approximation algorithm that for any constant k, in polynomial time, delivers solutions of
Mitsutake, Ayori; Mori, Yoshiharu; Okamoto, Yuko
2013-01-01
In biomolecular systems (especially all-atom models) with many degrees of freedom such as proteins and nucleic acids, there exist an astronomically large number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. Enhanced conformational sampling techniques are thus in great demand. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms in biomolecular systems. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present various extensions of these three generalized-ensemble algorithms. The effectiveness of the methods is tested with short peptide and protein systems.
DEFF Research Database (Denmark)
This book constitutes the refereed proceedings of the 10th Scandinavian Workshop on Algorithm Theory, SWAT 2006, held in Riga, Latvia, in July 2006. The 36 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 154 submissions. The papers address all...
Algorithmic information theory
Grünwald, P.D.; Vitányi, P.M.B.; Adriaans, P.; van Benthem, J.
2008-01-01
We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain the main concepts of this quantitative approach to defining 'information'. We discuss the extent to which Kolmogorov's and Shannon's information theory have a common purpose, and where they are
Algorithmic information theory
Grünwald, P.D.; Vitányi, P.M.B.
2008-01-01
We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain the main concepts of this quantitative approach to defining `information'. We discuss the extent to which Kolmogorov's and Shannon's information theory have a common purpose, and where they are
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 9. Introduction to Algorithms Turtle Graphics. R K Shyamasundar. Series Article Volume 1 ... Author Affiliations. R K Shyamasundar1. Computer Science Group Tata Institute of Fundamental Research Homi Bhabha Road Mumbai 400 005, India.
Modular Regularization Algorithms
DEFF Research Database (Denmark)
Jacobsen, Michael
2004-01-01
The class of linear ill-posed problems is introduced along with a range of standard numerical tools and basic concepts from linear algebra, statistics and optimization. Known algorithms for solving linear inverse ill-posed problems are analyzed to determine how they can be decomposed into indepen......The class of linear ill-posed problems is introduced along with a range of standard numerical tools and basic concepts from linear algebra, statistics and optimization. Known algorithms for solving linear inverse ill-posed problems are analyzed to determine how they can be decomposed...... into independent modules. These modules are then combined to form new regularization algorithms with other properties than those we started out with. Several variations are tested using the Matlab toolbox MOORe Tools created in connection with this thesis. Object oriented programming techniques are explained...... and used to set up the illposed problems in the toolbox. Hereby, we are able to write regularization algorithms that automatically exploit structure in the ill-posed problem without being rewritten explicitly. We explain how to implement a stopping criteria for a parameter choice method based upon...
Algorithms for SCC Decomposition
J. Barnat; J. Chaloupka (Jakub); J.C. van de Pol (Jaco)
2008-01-01
htmlabstractWe study and improve the OBF technique [Barnat, J. and P.Moravec, Parallel algorithms for finding SCCs in implicitly given graphs, in: Proceedings of the 5th International Workshop on Parallel and Distributed Methods in Verification (PDMC 2006), LNCS (2007)], which was used in
Python algorithms mastering basic algorithms in the Python language
Hetland, Magnus Lie
2014-01-01
Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data struc
Fast autodidactic adaptive equalization algorithms
Hilal, Katia
Autodidactic equalization by adaptive filtering is addressed in a mobile radio communication context. A general method, using an adaptive stochastic gradient Bussgang type algorithm, to deduce two low cost computation algorithms is given: one equivalent to the initial algorithm and the other having improved convergence properties thanks to a block criteria minimization. Two start algorithms are reworked: the Godard algorithm and the decision controlled algorithm. Using a normalization procedure, and block normalization, the performances are improved, and their common points are evaluated. These common points are used to propose an algorithm retaining the advantages of the two initial algorithms. This thus inherits the robustness of the Godard algorithm and the precision and phase correction of the decision control algorithm. The work is completed by a study of the stable states of Bussgang type algorithms and of the stability of the Godard algorithms, initial and normalized. The simulation of these algorithms, carried out in a mobile radio communications context, and under severe conditions on the propagation channel, gave a 75% reduction in the number of samples required for the processing in relation with the initial algorithms. The improvement of the residual error was of a much lower return. These performances are close to making possible the use of autodidactic equalization in the mobile radio system.
A MEDLINE categorization algorithm
Directory of Open Access Journals (Sweden)
Gehanno Jean-Francois
2006-02-01
Full Text Available Abstract Background Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway. Methods The MEDLINE categorization algorithm (MCA is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links. Results The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics. Conclusion We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources
Reactive Collision Avoidance Algorithm
Scharf, Daniel; Acikmese, Behcet; Ploen, Scott; Hadaegh, Fred
2010-01-01
The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on
A MEDLINE categorization algorithm
Darmoni, Stefan J; Névéol, Aurelie; Renard, Jean-Marie; Gehanno, Jean-Francois; Soualmia, Lina F; Dahamna, Badisse; Thirion, Benoit
2006-01-01
Background Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway. Methods The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links. Results The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics. Conclusion We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms
Genetic Algorithms and Local Search
Whitley, Darrell
1996-01-01
The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.
Genetic Algorithm for Optimization: Preprocessor and Algorithm
Sen, S. K.; Shaykhian, Gholam A.
2006-01-01
Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.
Algorithms for Global Positioning
DEFF Research Database (Denmark)
Borre, Kai; Strang, Gilbert
and replaces the authors' previous work, Linear Algebra, Geodesy, and GPS (1997). An initial discussion of the basic concepts, characteristics and technical aspects of different satellite systems is followed by the necessary mathematical content which is presented in a detailed and self-contained fashion......The emergence of satellite technology has changed the lives of millions of people. In particular, GPS has brought an unprecedented level of accuracy to the field of geodesy. This text is a guide to the algorithms and mathematical principles that account for the success of GPS technology....... At the heart of the matter are the positioning algorithms on which GPS technology relies, the discussion of which will affirm the mathematical contents of the previous chapters. Numerous ready-to-use MATLAB codes are included for the reader. This comprehensive guide will be invaluable for engineers...
Kramer, Oliver
2017-01-01
This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.
Aydemir, Bahar
2017-01-01
The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider (LHC) at CERN is composed of a large number of distributed hardware and software components. TDAQ system consists of about 3000 computers and more than 25000 applications which, in a coordinated manner, provide the data-taking functionality of the overall system. There is a number of online services required to configure, monitor and control the ATLAS data taking. In particular, the configuration service is used to provide configuration of above components. The configuration of the ATLAS data acquisition system is stored in XML-based object database named OKS. DAL (Data Access Library) allowing to access it's information by C++, Java and Python clients in a distributed environment. Some information has quite complicated structure, so it's extraction requires writing special algorithms. Algorithms available on C++ programming language and partially reimplemented on Java programming language. The goal of the projec...
Partitional clustering algorithms
2015-01-01
This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...
Fatigue Evaluation Algorithms: Review
DEFF Research Database (Denmark)
Passipoularidis, Vaggelis; Brøndsted, Povl
A progressive damage fatigue simulator for variable amplitude loads named FADAS is discussed in this work. FADAS (Fatigue Damage Simulator) performs ply by ply stress analysis using classical lamination theory and implements adequate stiffness discount tactics based on the failure criterion of Puck...... series can be simulated. The predictions are validated against fatigue life data both from repeated block tests at a single stress ratio as well as against spectral fatigue using the WISPER, WISPERX and NEW WISPER load sequences on a Glass/Epoxy multidirectional laminate typical of a wind turbine rotor...... blade construction. Two versions of the algorithm, the one using single-step and the other using incremental application of each load cycle (in case of ply failure) are implemented and compared. Simulation results confirm the ability of the algorithm to take into account load sequence effects...
Boosting foundations and algorithms
Schapire, Robert E
2012-01-01
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.
Likelihood Inflating Sampling Algorithm
Entezari, Reihaneh; Craiu, Radu V.; Rosenthal, Jeffrey S.
2016-01-01
Markov Chain Monte Carlo (MCMC) sampling from a posterior distribution corresponding to a massive data set can be computationally prohibitive since producing one sample requires a number of operations that is linear in the data size. In this paper, we introduce a new communication-free parallel method, the Likelihood Inflating Sampling Algorithm (LISA), that significantly reduces computational costs by randomly splitting the dataset into smaller subsets and running MCMC methods independently ...
Constrained Minimization Algorithms
Lantéri, H.; Theys, C.; Richard, C.
2013-03-01
In this paper, we consider the inverse problem of restoring an unknown signal or image, knowing the transformation suffered by the unknowns. More specifically we deal with transformations described by a linear model linking the unknown signal to an unnoisy version of the data. The measured data are generally corrupted by noise. This aspect of the problem is presented in the introduction for general models. In Section 2, we introduce the linear models, and some examples of linear inverse problems are presented. The specificities of the inverse problems are briefly mentionned and shown on a simple example. In Section 3, we give some information on classical distances or divergences. Indeed, an inverse problem is generally solved by minimizing a discrepancy function (divergence or distance) between the measured data and the model (here linear) of such data. Section 4 deals with the likelihood maximization and with their links with divergences minimization. The physical constraints on the solution are indicated and the Split Gradient Method (SGM) is detailed in Section 5. A constraint on the inferior bound of the solution is introduced at first; the positivity constraint is a particular case of such a constraint. We show how to obtain strictly, the multiplicative form of the algorithms. In a second step, the so-called flux constraint is introduced, and a complete algorithmic form is given. In Section 6 we give some brief information on acceleration method of such algorithms. A conclusion is given in Section 7.
ALGORITHM OF OBJECT RECOGNITION
Directory of Open Access Journals (Sweden)
Loktev Alexey Alexeevich
2012-10-01
Full Text Available The second important problem to be resolved to the algorithm and its software, that comprises an automatic design of a complex closed circuit television system, represents object recognition, by virtue of which an image is transmitted by the video camera. Since imaging of almost any object is dependent on many factors, including its orientation in respect of the camera, lighting conditions, parameters of the registering system, static and dynamic parameters of the object itself, it is quite difficult to formalize the image and represent it in the form of a certain mathematical model. Therefore, methods of computer-aided visualization depend substantially on the problems to be solved. They can be rarely generalized. The majority of these methods are non-linear; therefore, there is a need to increase the computing power and complexity of algorithms to be able to process the image. This paper covers the research of visual object recognition and implementation of the algorithm in the view of the software application that operates in the real-time mode
Large scale tracking algorithms
Energy Technology Data Exchange (ETDEWEB)
Hansen, Ross L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Love, Joshua Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melgaard, David Kennett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Karelitz, David B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pitts, Todd Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zollweg, Joshua David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Anderson, Dylan Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nandy, Prabal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whitlow, Gary L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bender, Daniel A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Byrne, Raymond Harry [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-01-01
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
NEUTRON ALGORITHM VERIFICATION TESTING
Energy Technology Data Exchange (ETDEWEB)
COWGILL,M.; MOSBY,W.; ARGONNE NATIONAL LABORATORY-WEST
2000-07-19
Active well coincidence counter assays have been performed on uranium metal highly enriched in {sup 235}U. The data obtained in the present program, together with highly enriched uranium (HEU) metal data obtained in other programs, have been analyzed using two approaches, the standard approach and an alternative approach developed at BNL. Analysis of the data with the standard approach revealed that the form of the relationship between the measured reals and the {sup 235}U mass varied, being sometimes linear and sometimes a second-order polynomial. In contrast, application of the BNL algorithm, which takes into consideration the totals, consistently yielded linear relationships between the totals-corrected reals and the {sup 235}U mass. The constants in these linear relationships varied with geometric configuration and level of enrichment. This indicates that, when the BNL algorithm is used, calibration curves can be established with fewer data points and with more certainty than if a standard algorithm is used. However, this potential advantage has only been established for assays of HEU metal. In addition, the method is sensitive to the stability of natural background in the measurement facility.
Stubbs, Allston Julius; Atilla, Halis Atil
2016-01-01
Summary Background Despite the rapid advancement of imaging and arthroscopic techniques about the hip joint, missed diagnoses are still common. As a deep joint and compared to the shoulder and knee joints, localization of hip symptoms is difficult. Hip pathology is not easily isolated and is often related to intra and extra-articular abnormalities. In light of these diagnostic challenges, we recommend an algorithmic approach to effectively diagnoses and treat hip pain. Methods In this review, hip pain is evaluated from diagnosis to treatment in a clear decision model. First we discuss emergency hip situations followed by the differentiation of intra and extra-articular causes of the hip pain. We differentiate the intra-articular hip as arthritic and non-arthritic and extra-articular pain as surrounding or remote tissue generated. Further, extra-articular hip pain is evaluated according to pain location. Finally we summarize the surgical treatment approach with an algorithmic diagram. Conclusion Diagnosis of hip pathology is difficult because the etiologies of pain may be various. An algorithmic approach to hip restoration from diagnosis to rehabilitation is crucial to successfully identify and manage hip pathologies. Level of evidence: V. PMID:28066734
An efficient algorithm for function optimization: modified stem cells algorithm
Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad
2013-03-01
In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).
Convex hull ranking algorithm for multi-objective evolutionary algorithms
Davoodi Monfrared, M.; Mohades, A.; Rezaei, J.
2012-01-01
Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity
Iterative Algorithms for Nonexpansive Mappings
Directory of Open Access Journals (Sweden)
Yao Yonghong
2008-01-01
Full Text Available Abstract We suggest and analyze two new iterative algorithms for a nonexpansive mapping in Banach spaces. We prove that the proposed iterative algorithms converge strongly to some fixed point of .
Foundations of genetic algorithms 1991
1991-01-01
Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems.This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; condition
Parallel Architectures and Bioinspired Algorithms
Pérez, José; Lanchares, Juan
2012-01-01
This monograph presents examples of best practices when combining bioinspired algorithms with parallel architectures. The book includes recent work by leading researchers in the field and offers a map with the main paths already explored and new ways towards the future. Parallel Architectures and Bioinspired Algorithms will be of value to both specialists in Bioinspired Algorithms, Parallel and Distributed Computing, as well as computer science students trying to understand the present and the future of Parallel Architectures and Bioinspired Algorithms.
Essential algorithms a practical approach to computer algorithms
Stephens, Rod
2013-01-01
A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures s
Efficient GPS Position Determination Algorithms
National Research Council Canada - National Science Library
Nguyen, Thao Q
2007-01-01
... differential GPS algorithm for a network of users. The stand-alone user GPS algorithm is a direct, closed-form, and efficient new position determination algorithm that exploits the closed-form solution of the GPS trilateration equations and works...
Recent results on howard's algorithm
DEFF Research Database (Denmark)
Miltersen, P.B.
2012-01-01
Howard’s algorithm is a fifty-year old generally applicable algorithm for sequential decision making in face of uncertainty. It is routinely used in practice in numerous application areas that are so important that they usually go by their acronyms, e.g., OR, AI, and CAV. While Howard’s algorithm...
Multisensor estimation: New distributed algorithms
Directory of Open Access Journals (Sweden)
Plataniotis K. N.
1997-01-01
Full Text Available The multisensor estimation problem is considered in this paper. New distributed algorithms, which are able to locally process the information and which deliver identical results to those generated by their centralized counterparts are presented. The algorithms can be used to provide robust and computationally efficient solutions to the multisensor estimation problem. The proposed distributed algorithms are theoretically interesting and computationally attractive.
Selfish Gene Algorithm Vs Genetic Algorithm: A Review
Ariff, Norharyati Md; Khalid, Noor Elaiza Abdul; Hashim, Rathiah; Noor, Noorhayati Mohamed
2016-11-01
Evolutionary algorithm is one of the algorithms inspired by the nature. Within little more than a decade hundreds of papers have reported successful applications of EAs. In this paper, the Selfish Gene Algorithms (SFGA), as one of the latest evolutionary algorithms (EAs) inspired from the Selfish Gene Theory which is an interpretation of Darwinian Theory ideas from the biologist Richards Dawkins on 1989. In this paper, following a brief introduction to the Selfish Gene Algorithm (SFGA), the chronology of its evolution is presented. It is the purpose of this paper is to present an overview of the concepts of Selfish Gene Algorithm (SFGA) as well as its opportunities and challenges. Accordingly, the history, step involves in the algorithm are discussed and its different applications together with an analysis of these applications are evaluated.
An Algorithmic Diversity Diet?
DEFF Research Database (Denmark)
Sørensen, Jannick Kirk; Schmidt, Jan-Hinrik
2016-01-01
diet system however triggers not only the classic discussion of the reach – distinctiveness balance for PSM, but also shows that ‘diversity’ is understood very differently in algorithmic recommender system communities than it is editorially and politically in the context of PSM. The design...... of a diversity diet system generates questions not just about editorial power, personal freedom and techno-paternalism, but also about the embedded politics of recommender systems as well as the human skills affiliated with PSM editorial work and the nature of PSM content....
Randomized Filtering Algorithms
DEFF Research Database (Denmark)
Katriel, Irit; Van Hentenryck, Pascal
2008-01-01
of AllDifferent and is generalization, the Global Cardinality Constraint. The first delayed filtering scheme is a Monte Carlo algorithm: its running time is superior, in the worst case, to that of enforcing are consistency after every domain event, while its filtering effectiveness is analyzed......Filtering every global constraint of a CPS to are consistency at every search step can be costly and solvers often compromise on either the level of consistency or the frequency at which are consistency is enforced. In this paper we propose two randomized filtering schemes for dense instances...
Recognition algorithms in knot theory
International Nuclear Information System (INIS)
Dynnikov, I A
2003-01-01
In this paper the problem of constructing algorithms for comparing knots and links is discussed. A survey of existing approaches and basic results in this area is given. In particular, diverse combinatorial methods for representing links are discussed, the Haken algorithm for recognizing a trivial knot (the unknot) and a scheme for constructing a general algorithm (using Haken's ideas) for comparing links are presented, an approach based on representing links by closed braids is described, the known algorithms for solving the word problem and the conjugacy problem for braid groups are described, and the complexity of the algorithms under consideration is discussed. A new method of combinatorial description of knots is given together with a new algorithm (based on this description) for recognizing the unknot by using a procedure for monotone simplification. In the conclusion of the paper several problems are formulated whose solution could help to advance towards the 'algorithmization' of knot theory
Fast algorithm for Morphological Filters
International Nuclear Information System (INIS)
Lou Shan; Jiang Xiangqian; Scott, Paul J
2011-01-01
In surface metrology, morphological filters, which evolved from the envelope filtering system (E-system) work well for functional prediction of surface finish in the analysis of surfaces in contact. The naive algorithms are time consuming, especially for areal data, and not generally adopted in real practice. A fast algorithm is proposed based on the alpha shape. The hull obtained by rolling the alpha ball is equivalent to the morphological opening/closing in theory. The algorithm depends on Delaunay triangulation with time complexity O(nlogn). In comparison to the naive algorithms it generates the opening and closing envelope without combining dilation and erosion. Edge distortion is corrected by reflective padding for open profiles/surfaces. Spikes in the sample data are detected and points interpolated to prevent singularities. The proposed algorithm works well both for morphological profile and area filters. Examples are presented to demonstrate the validity and superiority on efficiency of this algorithm over the naive algorithm.
Hybrid Cryptosystem Using Tiny Encryption Algorithm and LUC Algorithm
Rachmawati, Dian; Sharif, Amer; Jaysilen; Andri Budiman, Mohammad
2018-01-01
Security becomes a very important issue in data transmission and there are so many methods to make files more secure. One of that method is cryptography. Cryptography is a method to secure file by writing the hidden code to cover the original file. Therefore, if the people do not involve in cryptography, they cannot decrypt the hidden code to read the original file. There are many methods are used in cryptography, one of that method is hybrid cryptosystem. A hybrid cryptosystem is a method that uses a symmetric algorithm to secure the file and use an asymmetric algorithm to secure the symmetric algorithm key. In this research, TEA algorithm is used as symmetric algorithm and LUC algorithm is used as an asymmetric algorithm. The system is tested by encrypting and decrypting the file by using TEA algorithm and using LUC algorithm to encrypt and decrypt the TEA key. The result of this research is by using TEA Algorithm to encrypt the file, the cipher text form is the character from ASCII (American Standard for Information Interchange) table in the form of hexadecimal numbers and the cipher text size increase by sixteen bytes as the plaintext length is increased by eight characters.
Merceret, Francis; Lane, John; Immer, Christopher; Case, Jonathan; Manobianco, John
2005-01-01
The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.
Algorithmic Relative Complexity
Directory of Open Access Journals (Sweden)
Daniele Cerra
2011-04-01
Full Text Available Information content and compression are tightly related concepts that can be addressed through both classical and algorithmic information theories, on the basis of Shannon entropy and Kolmogorov complexity, respectively. The definition of several entities in Kolmogorov’s framework relies upon ideas from classical information theory, and these two approaches share many common traits. In this work, we expand the relations between these two frameworks by introducing algorithmic cross-complexity and relative complexity, counterparts of the cross-entropy and relative entropy (or Kullback-Leibler divergence found in Shannon’s framework. We define the cross-complexity of an object x with respect to another object y as the amount of computational resources needed to specify x in terms of y, and the complexity of x related to y as the compression power which is lost when adopting such a description for x, compared to the shortest representation of x. Properties of analogous quantities in classical information theory hold for these new concepts. As these notions are incomputable, a suitable approximation based upon data compression is derived to enable the application to real data, yielding a divergence measure applicable to any pair of strings. Example applications are outlined, involving authorship attribution and satellite image classification, as well as a comparison to similar established techniques.
Fatigue evaluation algorithms: Review
Energy Technology Data Exchange (ETDEWEB)
Passipoularidis, V.A.; Broendsted, P.
2009-11-15
A progressive damage fatigue simulator for variable amplitude loads named FADAS is discussed in this work. FADAS (Fatigue Damage Simulator) performs ply by ply stress analysis using classical lamination theory and implements adequate stiffness discount tactics based on the failure criterion of Puck, to model the degradation caused by failure events in ply level. Residual strength is incorporated as fatigue damage accumulation metric. Once the typical fatigue and static properties of the constitutive ply are determined,the performance of an arbitrary lay-up under uniaxial and/or multiaxial load time series can be simulated. The predictions are validated against fatigue life data both from repeated block tests at a single stress ratio as well as against spectral fatigue using the WISPER, WISPERX and NEW WISPER load sequences on a Glass/Epoxy multidirectional laminate typical of a wind turbine rotor blade construction. Two versions of the algorithm, the one using single-step and the other using incremental application of each load cycle (in case of ply failure) are implemented and compared. Simulation results confirm the ability of the algorithm to take into account load sequence effects. In general, FADAS performs well in predicting life under both spectral and block loading fatigue. (author)
Rabideau, Gregg R.; Chien, Steve A.
2010-01-01
AVA v2 software selects goals for execution from a set of goals that oversubscribe shared resources. The term goal refers to a science or engineering request to execute a possibly complex command sequence, such as image targets or ground-station downlinks. Developed as an extension to the Virtual Machine Language (VML) execution system, the software enables onboard and remote goal triggering through the use of an embedded, dynamic goal set that can oversubscribe resources. From the set of conflicting goals, a subset must be chosen that maximizes a given quality metric, which in this case is strict priority selection. A goal can never be pre-empted by a lower priority goal, and high-level goals can be added, removed, or updated at any time, and the "best" goals will be selected for execution. The software addresses the issue of re-planning that must be performed in a short time frame by the embedded system where computational resources are constrained. In particular, the algorithm addresses problems with well-defined goal requests without temporal flexibility that oversubscribes available resources. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. Thereby enabling shorter response times and greater autonomy for the system under control.
Applications of algorithmic differentiation to phase retrieval algorithms.
Jurling, Alden S; Fienup, James R
2014-07-01
In this paper, we generalize the techniques of reverse-mode algorithmic differentiation to include elementary operations on multidimensional arrays of complex numbers. We explore the application of the algorithmic differentiation to phase retrieval error metrics and show that reverse-mode algorithmic differentiation provides a framework for straightforward calculation of gradients of complicated error metrics without resorting to finite differences or laborious symbolic differentiation.
Optimal Fungal Space Searching Algorithms.
Asenova, Elitsa; Lin, Hsin-Yu; Fu, Eileen; Nicolau, Dan V; Nicolau, Dan V
2016-10-01
Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.
Algorithms and their others: Algorithmic culture in context
Directory of Open Access Journals (Sweden)
Paul Dourish
2016-08-01
Full Text Available Algorithms, once obscure objects of technical art, have lately been subject to considerable popular and scholarly scrutiny. What does it mean to adopt the algorithm as an object of analytic attention? What is in view, and out of view, when we focus on the algorithm? Using Niklaus Wirth's 1975 formulation that “algorithms + data structures = programs” as a launching-off point, this paper examines how an algorithmic lens shapes the way in which we might inquire into contemporary digital culture.
Fighting Censorship with Algorithms
Mahdian, Mohammad
In countries such as China or Iran where Internet censorship is prevalent, users usually rely on proxies or anonymizers to freely access the web. The obvious difficulty with this approach is that once the address of a proxy or an anonymizer is announced for use to the public, the authorities can easily filter all traffic to that address. This poses a challenge as to how proxy addresses can be announced to users without leaking too much information to the censorship authorities. In this paper, we formulate this question as an interesting algorithmic problem. We study this problem in a static and a dynamic model, and give almost tight bounds on the number of proxy servers required to give access to n people k of whom are adversaries. We will also discuss how trust networks can be used in this context.
Algorithmic Reflections on Choreography
Directory of Open Access Journals (Sweden)
Pablo Ventura
2016-11-01
Full Text Available In 1996, Pablo Ventura turned his attention to the choreography software Life Forms to find out whether the then-revolutionary new tool could lead to new possibilities of expression in contemporary dance. During the next 2 decades, he devised choreographic techniques and custom software to create dance works that highlight the operational logic of computers, accompanied by computer-generated dance and media elements. This article provides a firsthand account of how Ventura’s engagement with algorithmic concepts guided and transformed his choreographic practice. The text describes the methods that were developed to create computer-aided dance choreographies. Furthermore, the text illustrates how choreography techniques can be applied to correlate formal and aesthetic aspects of movement, music, and video. Finally, the text emphasizes how Ventura’s interest in the wider conceptual context has led him to explore with choreographic means fundamental issues concerning the characteristics of humans and machines and their increasingly profound interdependencies.
The Copenhagen Triage Algorithm
DEFF Research Database (Denmark)
Hasselbalch, Rasmus Bo; Plesner, Louis Lind; Pries-Heje, Mia
2016-01-01
BACKGROUND: Crowding in the emergency department (ED) is a well-known problem resulting in an increased risk of adverse outcomes. Effective triage might counteract this problem by identifying the sickest patients and ensuring early treatment. In the last two decades, systematic triage has become...... the standard in ED's worldwide. However, triage models are also time consuming, supported by limited evidence and could potentially be of more harm than benefit. The aim of this study is to develop a quicker triage model using data from a large cohort of unselected ED patients and evaluate if this new model...... is non-inferior to an existing triage model in a prospective randomized trial. METHODS: The Copenhagen Triage Algorithm (CTA) study is a prospective two-center, cluster-randomized, cross-over, non-inferiority trial comparing CTA to the Danish Emergency Process Triage (DEPT). We include patients ≥16 years...
An overview of smart grid routing algorithms
Wang, Junsheng; OU, Qinghai; Shen, Haijuan
2017-08-01
This paper summarizes the typical routing algorithm in smart grid by analyzing the communication business and communication requirements of intelligent grid. Mainly from the two kinds of routing algorithm is analyzed, namely clustering routing algorithm and routing algorithm, analyzed the advantages and disadvantages of two kinds of typical routing algorithm in routing algorithm and applicability.
Genetic Algorithms in Noisy Environments
THEN, T. W.; CHONG, EDWIN K. P.
1993-01-01
Genetic Algorithms (GA) have been widely used in the areas of searching, function optimization, and machine learning. In many of these applications, the effect of noise is a critical factor in the performance of the genetic algorithms. While it hals been shown in previous siiudies that genetic algorithms are still able to perform effectively in the presence of noise, the problem of locating the global optimal solution at the end of the search has never been effectively addressed. Furthermore,...
Mao-Gilles Stabilization Algorithm
Jérôme Gilles
2013-01-01
Originally, the Mao-Gilles stabilization algorithm was designed to compensate the non-rigid deformations due to atmospheric turbulence. Given a sequence of frames affected by atmospheric turbulence, the algorithm uses a variational model combining optical flow and regularization to characterize the static observed scene. The optimization problem is solved by Bregman Iteration and the operator splitting method. The algorithm is simple, efficient, and can be easily generalized for different sce...
Mao-Gilles Stabilization Algorithm
Directory of Open Access Journals (Sweden)
Jérôme Gilles
2013-07-01
Full Text Available Originally, the Mao-Gilles stabilization algorithm was designed to compensate the non-rigid deformations due to atmospheric turbulence. Given a sequence of frames affected by atmospheric turbulence, the algorithm uses a variational model combining optical flow and regularization to characterize the static observed scene. The optimization problem is solved by Bregman Iteration and the operator splitting method. The algorithm is simple, efficient, and can be easily generalized for different scenarios involving non-rigid deformations.
Unsupervised Classification Using Immune Algorithm
Al-Muallim, M. T.; El-Kouatly, R.
2012-01-01
Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed U...
Fuzzy HRRN CPU Scheduling Algorithm
Bashir Alam; R. Biswas; M. Alam
2011-01-01
There are several scheduling algorithms like FCFS, SRTN, RR, priority etc. Scheduling decisions of these algorithms are based on parameters which are assumed to be crisp. However, in many circumstances these parameters are vague. The vagueness of these parameters suggests that scheduler should use fuzzy technique in scheduling the jobs. In this paper we have proposed a novel CPU scheduling algorithm Fuzzy HRRN that incorporates fuzziness in basic HRRN using fuzzy Technique FIS.
Machine Learning an algorithmic perspective
Marsland, Stephen
2009-01-01
Traditional books on machine learning can be divided into two groups - those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement le
Algorithmic complexity of quantum capacity
Oskouei, Samad Khabbazi; Mancini, Stefano
2018-04-01
We analyze the notion of quantum capacity from the perspective of algorithmic (descriptive) complexity. To this end, we resort to the concept of semi-computability in order to describe quantum states and quantum channel maps. We introduce algorithmic entropies (like algorithmic quantum coherent information) and derive relevant properties for them. Then we show that quantum capacity based on semi-computable concept equals the entropy rate of algorithmic coherent information, which in turn equals the standard quantum capacity. Thanks to this, we finally prove that the quantum capacity, for a given semi-computable channel, is limit computable.
Diversity-Guided Evolutionary Algorithms
DEFF Research Database (Denmark)
Ursem, Rasmus Kjær
2002-01-01
Population diversity is undoubtably a key issue in the performance of evolutionary algorithms. A common hypothesis is that high diversity is important to avoid premature convergence and to escape local optima. Various diversity measures have been used to analyze algorithms, but so far few...... algorithms have used a measure to guide the search. The diversity-guided evolutionary algorithm (DGEA) uses the wellknown distance-to-average-point measure to alternate between phases of exploration (mutation) and phases of exploitation (recombination and selection). The DGEA showed remarkable results...
Backtrack Orbit Search Algorithm
Knowles, K.; Swick, R.
2002-12-01
A Mathematical Solution to a Mathematical Problem. With the dramatic increase in satellite-born sensor resolution traditional methods of spatially searching for orbital data have become inadequate. As data volumes increase end-users of the data have become increasingly intolerant of false positives. And, as computing power rapidly increases end-users have come to expect equally rapid search speeds. Meanwhile data archives have an interest in delivering the minimum amount of data that meets users' needs. This keeps their costs down and allows them to serve more users in a more timely manner. Many methods of spatial search for orbital data have been tried in the past and found wanting. The ever popular lat/lon bounding box on a flat Earth is highly inaccurate. Spatial search based on nominal "orbits" is somewhat more accurate at much higher implementation cost and slower performance. Spatial search of orbital data based on predict orbit models are very accurate at a much higher maintenance cost and slower performance. This poster describes the Backtrack Orbit Search Algorithm--an alternative spatial search method for orbital data. Backtrack has a degree of accuracy that rivals predict methods while being faster, less costly to implement, and less costly to maintain than other methods.
Diagnostic algorithm for syncope.
Mereu, Roberto; Sau, Arunashis; Lim, Phang Boon
2014-09-01
Syncope is a common symptom with many causes. Affecting a large proportion of the population, both young and old, it represents a significant healthcare burden. The diagnostic approach to syncope should be focused on the initial evaluation, which includes a detailed clinical history, physical examination and 12-lead electrocardiogram. Following the initial evaluation, patients should be risk-stratified into high or low-risk groups in order to guide further investigations and management. Patients with high-risk features should be investigated further to exclude significant structural heart disease or arrhythmia. The ideal currently-available investigation should allow ECG recording during a spontaneous episode of syncope, and when this is not possible, an implantable loop recorder may be considered. In the emergency room setting, acute causes of syncope must also be considered including severe cardiovascular compromise due to pulmonary, cardiac or vascular pathology. While not all patients will receive a conclusive diagnosis, risk-stratification in patients to guide appropriate investigations in the context of a diagnostic algorithm should allow a benign prognosis to be maintained. Copyright © 2014 Elsevier B.V. All rights reserved.
Toward an Algorithmic Pedagogy
Directory of Open Access Journals (Sweden)
Holly Willis
2007-01-01
Full Text Available The demand for an expanded definition of literacy to accommodate visual and aural media is not particularly new, but it gains urgency as college students transform, becoming producers of media in many of their everyday social activities. The response among those who grapple with these issues as instructors has been to advocate for new definitions of literacy and particularly, an understanding of visual literacy. These efforts are exemplary, and promote a much needed rethinking of literacy and models of pedagogy. However, in what is more akin to a manifesto than a polished argument, this essay argues that we need to push farther: What if we moved beyond visual rhetoric, as well as a game-based pedagogy and the adoption of a broad range of media tools on campus, toward a pedagogy grounded fundamentally in a media ecology? Framing this investigation in terms of a media ecology allows us to take account of the multiply determining relationships wrought not just by individual media, but by the interrelationships, dependencies and symbioses that take place within the dynamic system that is today’s high-tech university. An ecological approach allows us to examine what happens when new media practices collide with computational models, providing a glimpse of possible transformations not only ways of being but ways of teaching and learning. How, then, may pedagogical practices be transformed computationally or algorithmically and to what ends?
Streaming Algorithms for Line Simplification
DEFF Research Database (Denmark)
Abam, Mohammad; de Berg, Mark; Hachenberger, Peter
2010-01-01
this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...
Echo Cancellation I: Algorithms Simulation
Directory of Open Access Journals (Sweden)
P. Sovka
2000-04-01
Full Text Available Echo cancellation system used in mobile communications is analyzed.Convergence behavior and misadjustment of several LMS algorithms arecompared. The misadjustment means errors in filter weight estimation.The resulting echo suppression for discussed algorithms with simulatedas well as rela speech signals is evaluated. The optional echocancellation configuration is suggested.
Algorithms on ensemble quantum computers.
Boykin, P Oscar; Mor, Tal; Roychowdhury, Vwani; Vatan, Farrokh
2010-06-01
In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified, as the common strategy of delaying the measurements usually does not resolve this ensemble-measurement problem. Here we present several new strategies for resolving this problem. Based on these strategies we provide new versions of some of the most important quantum algorithms, versions that are suitable for implementing on ensemble quantum computers, e.g., on liquid NMR quantum computers. These algorithms are Shor's factorization algorithm, Grover's search algorithm (with several marked items), and an algorithm for quantum fault-tolerant computation. The first two algorithms are simply modified using a randomizing and a sorting strategies. For the last algorithm, we develop a classical-quantum hybrid strategy for removing measurements. We use it to present a novel quantum fault-tolerant scheme. More explicitly, we present schemes for fault-tolerant measurement-free implementation of Toffoli and σ(z)(¼) as these operations cannot be implemented "bitwise", and their standard fault-tolerant implementations require measurement.
International Nuclear Information System (INIS)
Grady, M.
1986-01-01
I describe a fast fermion algorithm which utilizes pseudofermion fields but appears to have little or no systematic error. Test simulations on two-dimensional gauge theories are described. A possible justification for the algorithm being exact is discussed. 8 refs
Global alignment algorithms implementations | Fatumo ...
African Journals Online (AJOL)
In this paper, we implemented the two routes for sequence comparison, that is; the dotplot and Needleman-wunsch algorithm for global sequence alignment. Our algorithms were implemented in python programming language and were tested on Linux platform 1.60GHz, 512 MB of RAM SUSE 9.2 and 10.1 versions.
Recovery Rate of Clustering Algorithms
Li, Fajie; Klette, Reinhard; Wada, T; Huang, F; Lin, S
2009-01-01
This article provides a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance of the algorithm when calculating a family of new clusters. Under the assumption of dealing with simulated data (i.e., known old
Diversity-Guided Evolutionary Algorithms
DEFF Research Database (Denmark)
Ursem, Rasmus Kjær
2002-01-01
Population diversity is undoubtably a key issue in the performance of evolutionary algorithms. A common hypothesis is that high diversity is important to avoid premature convergence and to escape local optima. Various diversity measures have been used to analyze algorithms, but so far few algorit...
Quantum algorithms and learning theory
Arunachalam, S.
2018-01-01
This thesis studies strengths and weaknesses of quantum computers. In the first part we present three contributions to quantum algorithms. 1) consider a search space of N elements. One of these elements is "marked" and our goal is to find this. We describe a quantum algorithm to solve this problem
Where are the parallel algorithms?
Voigt, R. G.
1985-01-01
Four paradigms that can be useful in developing parallel algorithms are discussed. These include computational complexity analysis, changing the order of computation, asynchronous computation, and divide and conquer. Each is illustrated with an example from scientific computation, and it is shown that computational complexity must be used with great care or an inefficient algorithm may be selected.
Online co-regularized algorithms
Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.
2012-01-01
We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks
Algorithms in combinatorial design theory
Colbourn, CJ
1985-01-01
The scope of the volume includes all algorithmic and computational aspects of research on combinatorial designs. Algorithmic aspects include generation, isomorphism and analysis techniques - both heuristic methods used in practice, and the computational complexity of these operations. The scope within design theory includes all aspects of block designs, Latin squares and their variants, pairwise balanced designs and projective planes and related geometries.
Executable Pseudocode for Graph Algorithms
B. Ó Nualláin (Breanndán)
2015-01-01
textabstract Algorithms are written in pseudocode. However the implementation of an algorithm in a conventional, imperative programming language can often be scattered over hundreds of lines of code thus obscuring its essence. This can lead to difficulties in understanding or verifying the
On exact algorithms for treewidth
Bodlaender, H.L.; Fomin, F.V.; Koster, A.M.C.A.; Kratsch, D.; Thilikos, D.M.
2006-01-01
We give experimental and theoretical results on the problem of computing the treewidth of a graph by exact exponential time algorithms using exponential space or using only polynomial space. We first report on an implementation of a dynamic programming algorithm for computing the treewidth of a
Cascade Error Projection Learning Algorithm
Duong, T. A.; Stubberud, A. R.; Daud, T.
1995-01-01
A detailed mathematical analysis is presented for a new learning algorithm termed cascade error projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters.
Novel medical image enhancement algorithms
Agaian, Sos; McClendon, Stephen A.
2010-01-01
In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.
Elementary functions algorithms and implementation
Muller, Jean-Michel
2016-01-01
This textbook presents the concepts and tools necessary to understand, build, and implement algorithms for computing elementary functions (e.g., logarithms, exponentials, and the trigonometric functions). Both hardware- and software-oriented algorithms are included, along with issues related to accurate floating-point implementation. This third edition has been updated and expanded to incorporate the most recent advances in the field, new elementary function algorithms, and function software. After a preliminary chapter that briefly introduces some fundamental concepts of computer arithmetic, such as floating-point arithmetic and redundant number systems, the text is divided into three main parts. Part I considers the computation of elementary functions using algorithms based on polynomial or rational approximations and using table-based methods; the final chapter in this section deals with basic principles of multiple-precision arithmetic. Part II is devoted to a presentation of “shift-and-add” algorithm...
Portable Health Algorithms Test System
Melcher, Kevin J.; Wong, Edmond; Fulton, Christopher E.; Sowers, Thomas S.; Maul, William A.
2010-01-01
A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.
Learning from nature: Nature-inspired algorithms
DEFF Research Database (Denmark)
Albeanu, Grigore; Madsen, Henrik; Popentiu-Vladicescu, Florin
2016-01-01
During last decade, the nature has inspired researchers to develop new algorithms. The largest collection of nature-inspired algorithms is biology-inspired: swarm intelligence (particle swarm optimization, ant colony optimization, cuckoo search, bees' algorithm, bat algorithm, firefly algorithm etc...
Complex networks an algorithmic perspective
Erciyes, Kayhan
2014-01-01
Network science is a rapidly emerging field of study that encompasses mathematics, computer science, physics, and engineering. A key issue in the study of complex networks is to understand the collective behavior of the various elements of these networks.Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, few books focus on the algorithmic aspects of complex network analysis. Filling this need, Complex Networks: An Algorithmic Perspective supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every r
An investigation of genetic algorithms
International Nuclear Information System (INIS)
Douglas, S.R.
1995-04-01
Genetic algorithms mimic biological evolution by natural selection in their search for better individuals within a changing population. they can be used as efficient optimizers. This report discusses the developing field of genetic algorithms. It gives a simple example of the search process and introduces the concept of schema. It also discusses modifications to the basic genetic algorithm that result in species and niche formation, in machine learning and artificial evolution of computer programs, and in the streamlining of human-computer interaction. (author). 3 refs., 1 tab., 2 figs
Instance-specific algorithm configuration
Malitsky, Yuri
2014-01-01
This book presents a modular and expandable technique in the rapidly emerging research area of automatic configuration and selection of the best algorithm for the instance at hand. The author presents the basic model behind ISAC and then details a number of modifications and practical applications. In particular, he addresses automated feature generation, offline algorithm configuration for portfolio generation, algorithm selection, adaptive solvers, online tuning, and parallelization. The author's related thesis was honorably mentioned (runner-up) for the ACP Dissertation Award in 2014,
Quantum Computations: Fundamentals and Algorithms
International Nuclear Information System (INIS)
Duplij, S.A.; Shapoval, I.I.
2007-01-01
Basic concepts of quantum information theory, principles of quantum calculations and the possibility of creation on this basis unique on calculation power and functioning principle device, named quantum computer, are concerned. The main blocks of quantum logic, schemes of quantum calculations implementation, as well as some known today effective quantum algorithms, called to realize advantages of quantum calculations upon classical, are presented here. Among them special place is taken by Shor's algorithm of number factorization and Grover's algorithm of unsorted database search. Phenomena of decoherence, its influence on quantum computer stability and methods of quantum errors correction are described
Algorithms Design Techniques and Analysis
Alsuwaiyel, M H
1999-01-01
Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) solution of the formulated problem. One can solve a problem on its own using ad hoc techniques or follow those techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions and the context appropriate for each of them. This book advocates the study of algorithm design techniques by presenting most of the useful algorithm desi
Subcubic Control Flow Analysis Algorithms
DEFF Research Database (Denmark)
Midtgaard, Jan; Van Horn, David
We give the first direct subcubic algorithm for performing control flow analysis of higher-order functional programs. Despite the long held belief that inclusion-based flow analysis could not surpass the ``cubic bottleneck, '' we apply known set compression techniques to obtain an algorithm...... that runs in time O(n^3/log n) on a unit cost random-access memory model machine. Moreover, we refine the initial flow analysis into two more precise analyses incorporating notions of reachability. We give subcubic algorithms for these more precise analyses and relate them to an existing analysis from...
Adaptive Maneuvering Target Tracking Algorithm
Directory of Open Access Journals (Sweden)
Chunling Wu
2014-07-01
Full Text Available Based on the current statistical model, a new adaptive maneuvering target tracking algorithm, CS-MSTF, is presented. The new algorithm keep the merits of high tracking precision that the current statistical model and strong tracking filter (STF have in tracking maneuvering target, and made the modifications as such: First, STF has the defect that it achieves the perfect performance in maneuvering segment at a cost of the precision in non-maneuvering segment, so the new algorithm modified the prediction error covariance matrix and the fading factor to improve the tracking precision both of the maneuvering segment and non-maneuvering segment; The estimation error covariance matrix was calculated using the Joseph form, which is more stable and robust in numerical. The Monte- Carlo simulation shows that the CS-MSTF algorithm has a more excellent performance than CS-STF and can estimate efficiently.
Recursive Algorithm For Linear Regression
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
Designing algorithms using CAD technologies
Directory of Open Access Journals (Sweden)
Alin IORDACHE
2008-01-01
Full Text Available A representative example of eLearning-platform modular application, Ã¢Â€Â˜Logical diagramsÃ¢Â€Â™, is intended to be a useful learning and testing tool for the beginner programmer, but also for the more experienced one. The problem this application is trying to solve concerns young programmers who forget about the fundamentals of this domain, algorithmic. Logical diagrams are a graphic representation of an algorithm, which uses different geometrical figures (parallelograms, rectangles, rhombuses, circles with particular meaning that are called blocks and connected between them to reveal the flow of the algorithm. The role of this application is to help the user build the diagram for the algorithm and then automatically generate the C code and test it.
A quantum causal discovery algorithm
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
Multiagent scheduling models and algorithms
Agnetis, Alessandro; Gawiejnowicz, Stanisław; Pacciarelli, Dario; Soukhal, Ameur
2014-01-01
This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.
Efficient Algorithms for Subgraph Listing
Directory of Open Access Journals (Sweden)
Niklas Zechner
2014-05-01
Full Text Available Subgraph isomorphism is a fundamental problem in graph theory. In this paper we focus on listing subgraphs isomorphic to a given pattern graph. First, we look at the algorithm due to Chiba and Nishizeki for listing complete subgraphs of fixed size, and show that it cannot be extended to general subgraphs of fixed size. Then, we consider the algorithm due to Ga̧sieniec et al. for finding multiple witnesses of a Boolean matrix product, and use it to design a new output-sensitive algorithm for listing all triangles in a graph. As a corollary, we obtain an output-sensitive algorithm for listing subgraphs and induced subgraphs isomorphic to an arbitrary fixed pattern graph.
A retrodictive stochastic simulation algorithm
International Nuclear Information System (INIS)
Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.
2010-01-01
In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.
Autonomous algorithms for image restoration
Griniasty, Meir
1994-01-01
We describe a general theoretical framework for algorithms that adaptively tune all their parameters during the restoration of a noisy image. The adaptation procedure is based on a mean field approach which is known as ``Deterministic Annealing'', and is reminiscent of the ``Deterministic Bolzmann Machiné'. The algorithm is less time consuming in comparison with its simulated annealing alternative. We apply the theory to several architectures and compare their performances.
New algorithms for parallel MRI
International Nuclear Information System (INIS)
Anzengruber, S; Ramlau, R; Bauer, F; Leitao, A
2008-01-01
Magnetic Resonance Imaging with parallel data acquisition requires algorithms for reconstructing the patient's image from a small number of measured lines of the Fourier domain (k-space). In contrast to well-known algorithms like SENSE and GRAPPA and its flavors we consider the problem as a non-linear inverse problem. However, in order to avoid cost intensive derivatives we will use Landweber-Kaczmarz iteration and in order to improve the overall results some additional sparsity constraints.
When the greedy algorithm fails
Bang-Jensen, Jørgen; Gutin, Gregory; Yeo, Anders
2004-01-01
We provide a characterization of the cases when the greedy algorithm may produce the unique worst possible solution for the problem of finding a minimum weight base in an independence system when the weights are taken from a finite range. We apply this theorem to TSP and the minimum bisection problem. The practical message of this paper is that the greedy algorithm should be used with great care, since for many optimization problems its usage seems impractical even for generating a starting s...
A* Algorithm for Graphics Processors
Inam, Rafia; Cederman, Daniel; Tsigas, Philippas
2010-01-01
Today's computer games have thousands of agents moving at the same time in areas inhabited by a large number of obstacles. In such an environment it is important to be able to calculate multiple shortest paths concurrently in an efficient manner. The highly parallel nature of the graphics processor suits this scenario perfectly. We have implemented a graphics processor based version of the A* path finding algorithm together with three algorithmic improvements that allow it to work faster and ...
Algorithm for programming function generators
International Nuclear Information System (INIS)
Bozoki, E.
1981-01-01
The present paper deals with a mathematical problem, encountered when driving a fully programmable μ-processor controlled function generator. An algorithm is presented to approximate a desired function by a set of straight segments in such a way that additional restrictions (hardware imposed) are also satisfied. A computer program which incorporates this algorithm and automatically generates the necessary input for the function generator for a broad class of desired functions is also described
Cascade Error Projection: A New Learning Algorithm
Duong, T. A.; Stubberud, A. R.; Daud, T.; Thakoor, A. P.
1995-01-01
A new neural network architecture and a hardware implementable learning algorithm is proposed. The algorithm, called cascade error projection (CEP), handles lack of precision and circuit noise better than existing algorithms.
Rotational Invariant Dimensionality Reduction Algorithms.
Lai, Zhihui; Xu, Yong; Yang, Jian; Shen, Linlin; Zhang, David
2017-11-01
A common intrinsic limitation of the traditional subspace learning methods is the sensitivity to the outliers and the image variations of the object since they use the norm as the metric. In this paper, a series of methods based on the -norm are proposed for linear dimensionality reduction. Since the -norm based objective function is robust to the image variations, the proposed algorithms can perform robust image feature extraction for classification. We use different ideas to design different algorithms and obtain a unified rotational invariant (RI) dimensionality reduction framework, which extends the well-known graph embedding algorithm framework to a more generalized form. We provide the comprehensive analyses to show the essential properties of the proposed algorithm framework. This paper indicates that the optimization problems have global optimal solutions when all the orthogonal projections of the data space are computed and used. Experimental results on popular image datasets indicate that the proposed RI dimensionality reduction algorithms can obtain competitive performance compared with the previous norm based subspace learning algorithms.
Artificial Flora (AF Optimization Algorithm
Directory of Open Access Journals (Sweden)
Long Cheng
2018-02-01
Full Text Available Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems. Although a plant cannot move, it can spread seeds within a certain range to let offspring to find the most suitable environment. The stochastic process is easy to copy, and the spreading space is vast; therefore, it is suitable for applying in intelligent optimization algorithm. First, the algorithm randomly generates the original plant, including its position and the propagation distance. Then, the position and the propagation distance of the original plant as parameters are substituted in the propagation function to generate offspring plants. Finally, the optimal offspring is selected as a new original plant through the selection function. The previous original plant becomes the former plant. The iteration continues until we find out optimal solution. In this paper, six classical evaluation functions are used as the benchmark functions. The simulation results show that proposed algorithm has high accuracy and stability compared with the classical particle swarm optimization and artificial bee colony algorithm.
Algebraic Algorithm Design and Local Search
National Research Council Canada - National Science Library
Graham, Robert
1996-01-01
.... Algebraic techniques have been applied successfully to algorithm synthesis by the use of algorithm theories and design tactics, an approach pioneered in the Kestrel Interactive Development System (KIDS...
Golden Sine Algorithm: A Novel Math-Inspired Algorithm
Directory of Open Access Journals (Sweden)
TANYILDIZI, E.
2017-05-01
Full Text Available In this study, Golden Sine Algorithm (Gold-SA is presented as a new metaheuristic method for solving optimization problems. Gold-SA has been developed as a new search algorithm based on population. This math-based algorithm is inspired by sine that is a trigonometric function. In the algorithm, random individuals are created as many as the number of search agents with uniform distribution for each dimension. The Gold-SA operator searches to achieve a better solution in each iteration by trying to bring the current situation closer to the target value. The solution space is narrowed by the golden section so that the areas that are supposed to give only good results are scanned instead of the whole solution space scan. In the tests performed, it is seen that Gold-SA has better results than other population based methods. In addition, Gold-SA has fewer algorithm-dependent parameters and operators than other metaheuristic methods, increasing the importance of this method by providing faster convergence of this new method.
Mathematical algorithms for approximate reasoning
Murphy, John H.; Chay, Seung C.; Downs, Mary M.
1988-01-01
Most state of the art expert system environments contain a single and often ad hoc strategy for approximate reasoning. Some environments provide facilities to program the approximate reasoning algorithms. However, the next generation of expert systems should have an environment which contain a choice of several mathematical algorithms for approximate reasoning. To meet the need for validatable and verifiable coding, the expert system environment must no longer depend upon ad hoc reasoning techniques but instead must include mathematically rigorous techniques for approximate reasoning. Popular approximate reasoning techniques are reviewed, including: certainty factors, belief measures, Bayesian probabilities, fuzzy logic, and Shafer-Dempster techniques for reasoning. A group of mathematically rigorous algorithms for approximate reasoning are focused on that could form the basis of a next generation expert system environment. These algorithms are based upon the axioms of set theory and probability theory. To separate these algorithms for approximate reasoning various conditions of mutual exclusivity and independence are imposed upon the assertions. Approximate reasoning algorithms presented include: reasoning with statistically independent assertions, reasoning with mutually exclusive assertions, reasoning with assertions that exhibit minimum overlay within the state space, reasoning with assertions that exhibit maximum overlay within the state space (i.e. fuzzy logic), pessimistic reasoning (i.e. worst case analysis), optimistic reasoning (i.e. best case analysis), and reasoning with assertions with absolutely no knowledge of the possible dependency among the assertions. A robust environment for expert system construction should include the two modes of inference: modus ponens and modus tollens. Modus ponens inference is based upon reasoning towards the conclusion in a statement of logical implication, whereas modus tollens inference is based upon reasoning away
A review on quantum search algorithms
Giri, Pulak Ranjan; Korepin, Vladimir E.
2017-12-01
The use of superposition of states in quantum computation, known as quantum parallelism, has significant advantage in terms of speed over the classical computation. It is evident from the early invented quantum algorithms such as Deutsch's algorithm, Deutsch-Jozsa algorithm and its variation as Bernstein-Vazirani algorithm, Simon algorithm, Shor's algorithms, etc. Quantum parallelism also significantly speeds up the database search algorithm, which is important in computer science because it comes as a subroutine in many important algorithms. Quantum database search of Grover achieves the task of finding the target element in an unsorted database in a time quadratically faster than the classical computer. We review Grover's quantum search algorithms for a singe and multiple target elements in a database. The partial search algorithm of Grover and Radhakrishnan and its optimization by Korepin called GRK algorithm are also discussed.
Algorithms, complexity, and the sciences.
Papadimitriou, Christos
2014-11-11
Algorithms, perhaps together with Moore's law, compose the engine of the information technology revolution, whereas complexity--the antithesis of algorithms--is one of the deepest realms of mathematical investigation. After introducing the basic concepts of algorithms and complexity, and the fundamental complexity classes P (polynomial time) and NP (nondeterministic polynomial time, or search problems), we discuss briefly the P vs. NP problem. We then focus on certain classes between P and NP which capture important phenomena in the social and life sciences, namely the Nash equlibrium and other equilibria in economics and game theory, and certain processes in population genetics and evolution. Finally, an algorithm known as multiplicative weights update (MWU) provides an algorithmic interpretation of the evolution of allele frequencies in a population under sex and weak selection. All three of these equivalences are rife with domain-specific implications: The concept of Nash equilibrium may be less universal--and therefore less compelling--than has been presumed; selection on gene interactions may entail the maintenance of genetic variation for longer periods than selection on single alleles predicts; whereas MWU can be shown to maximize, for each gene, a convex combination of the gene's cumulative fitness in the population and the entropy of the allele distribution, an insight that may be pertinent to the maintenance of variation in evolution.
SDR Input Power Estimation Algorithms
Nappier, Jennifer M.; Briones, Janette C.
2013-01-01
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Computational geometry algorithms and applications
de Berg, Mark; Overmars, Mark; Schwarzkopf, Otfried
1997-01-01
Computational geometry emerged from the field of algorithms design and anal ysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The suc cess of the field as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains--computer graphics, geographic in formation systems (GIS), robotics, and others-in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or difficult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simplified many of the previous approaches. In this textbook we have tried to make these modem algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can ...
Universal algorithm of time sharing
International Nuclear Information System (INIS)
Silin, I.N.; Fedyun'kin, E.D.
1979-01-01
Timesharing system algorithm is proposed for the wide class of one- and multiprocessor computer configurations. Dynamical priority is the piece constant function of the channel characteristic and system time quantum. The interactive job quantum has variable length. Characteristic recurrent formula is received. The concept of the background job is introduced. Background job loads processor if high priority jobs are inactive. Background quality function is given on the base of the statistical data received in the timesharing process. Algorithm includes optimal trashing off procedure for the jobs replacements in the memory. Sharing of the system time in proportion to the external priorities is guaranteed for the all active enough computing channels (back-ground too). The fast answer is guaranteed for the interactive jobs, which use small time and memory. The external priority control is saved for the high level scheduler. The experience of the algorithm realization on the BESM-6 computer in JINR is discussed
Scalable algorithms for contact problems
Dostál, Zdeněk; Sadowská, Marie; Vondrák, Vít
2016-01-01
This book presents a comprehensive and self-contained treatment of the authors’ newly developed scalable algorithms for the solutions of multibody contact problems of linear elasticity. The brand new feature of these algorithms is theoretically supported numerical scalability and parallel scalability demonstrated on problems discretized by billions of degrees of freedom. The theory supports solving multibody frictionless contact problems, contact problems with possibly orthotropic Tresca’s friction, and transient contact problems. It covers BEM discretization, jumping coefficients, floating bodies, mortar non-penetration conditions, etc. The exposition is divided into four parts, the first of which reviews appropriate facets of linear algebra, optimization, and analysis. The most important algorithms and optimality results are presented in the third part of the volume. The presentation is complete, including continuous formulation, discretization, decomposition, optimality results, and numerical experimen...
Algorithms and Public Service Media
DEFF Research Database (Denmark)
Sørensen, Jannick Kirk; Hutchinson, Jonathon
2018-01-01
When Public Service Media (PSM) organisations introduce algorithmic recommender systems to suggest media content to users, fundamental values of PSM are challenged. Beyond being confronted with ubiquitous computer ethics problems of causality and transparency, also the identity of PSM as curator...... and agenda-setter is challenged. The algorithms represents rules for which content to present to whom, and in this sense they may discriminate and bias the exposure of diversity. Furthermore, on a practical level, the introduction of the systems shifts power within the organisations and changes...... the regulatory conditions. In this chapter we analyse two cases - the EBU-members' introduction of recommender systems and the Australian broadcaster ABC's experiences with the use of chatbots. We use these cases to exemplify the challenges that algorithmic systems poses to PSM organisations....
Quantum walks and search algorithms
Portugal, Renato
2013-01-01
This book addresses an interesting area of quantum computation called quantum walks, which play an important role in building quantum algorithms, in particular search algorithms. Quantum walks are the quantum analogue of classical random walks. It is known that quantum computers have great power for searching unsorted databases. This power extends to many kinds of searches, particularly to the problem of finding a specific location in a spatial layout, which can be modeled by a graph. The goal is to find a specific node knowing that the particle uses the edges to jump from one node to the next. This book is self-contained with main topics that include: Grover's algorithm, describing its geometrical interpretation and evolution by means of the spectral decomposition of the evolution operater Analytical solutions of quantum walks on important graphs like line, cycles, two-dimensional lattices, and hypercubes using Fourier transforms Quantum walks on generic graphs, describing methods to calculate the limiting d...
Algorithms for Decision Tree Construction
Chikalov, Igor
2011-01-01
The study of algorithms for decision tree construction was initiated in 1960s. The first algorithms are based on the separation heuristic [13, 31] that at each step tries dividing the set of objects as evenly as possible. Later Garey and Graham [28] showed that such algorithm may construct decision trees whose average depth is arbitrarily far from the minimum. Hyafil and Rivest in [35] proved NP-hardness of DT problem that is constructing a tree with the minimum average depth for a diagnostic problem over 2-valued information system and uniform probability distribution. Cox et al. in [22] showed that for a two-class problem over information system, even finding the root node attribute for an optimal tree is an NP-hard problem. © Springer-Verlag Berlin Heidelberg 2011.
Some nonlinear space decomposition algorithms
Energy Technology Data Exchange (ETDEWEB)
Tai, Xue-Cheng; Espedal, M. [Univ. of Bergen (Norway)
1996-12-31
Convergence of a space decomposition method is proved for a general convex programming problem. The space decomposition refers to methods that decompose a space into sums of subspaces, which could be a domain decomposition or a multigrid method for partial differential equations. Two algorithms are proposed. Both can be used for linear as well as nonlinear elliptic problems and they reduce to the standard additive and multiplicative Schwarz methods for linear elliptic problems. Two {open_quotes}hybrid{close_quotes} algorithms are also presented. They converge faster than the additive one and have better parallelism than the multiplicative method. Numerical tests with a two level domain decomposition for linear, nonlinear and interface elliptic problems are presented for the proposed algorithms.
Next Generation Suspension Dynamics Algorithms
Energy Technology Data Exchange (ETDEWEB)
Schunk, Peter Randall [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Higdon, Jonathon [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Chen, Steven [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-12-01
This research project has the objective to extend the range of application, improve the efficiency and conduct simulations with the Fast Lubrication Dynamics (FLD) algorithm for concentrated particle suspensions in a Newtonian fluid solvent. The research involves a combination of mathematical development, new computational algorithms, and application to processing flows of relevance in materials processing. The mathematical developments clarify the underlying theory, facilitate verification against classic monographs in the field and provide the framework for a novel parallel implementation optimized for an OpenMP shared memory environment. The project considered application to consolidation flows of major interest in high throughput materials processing and identified hitherto unforeseen challenges in the use of FLD in these applications. Extensions to the algorithm have been developed to improve its accuracy in these applications.
Fault Tolerant External Memory Algorithms
DEFF Research Database (Denmark)
Jørgensen, Allan Grønlund; Brodal, Gerth Stølting; Mølhave, Thomas
2009-01-01
Algorithms dealing with massive data sets are usually designed for I/O-efficiency, often captured by the I/O model by Aggarwal and Vitter. Another aspect of dealing with massive data is how to deal with memory faults, e.g. captured by the adversary based faulty memory RAM by Finocchi and Italiano....... However, current fault tolerant algorithms do not scale beyond the internal memory. In this paper we investigate for the first time the connection between I/O-efficiency in the I/O model and fault tolerance in the faulty memory RAM, and we assume that both memory and disk are unreliable. We show a lower...... bound on the number of I/Os required for any deterministic dictionary that is resilient to memory faults. We design a static and a dynamic deterministic dictionary with optimal query performance as well as an optimal sorting algorithm and an optimal priority queue. Finally, we consider scenarios where...
Empirical tests of the Gradual Learning Algorithm
Boersma, P.; Hayes, B.
2001-01-01
The Gradual Learning Algorithm (Boersma 1997) is a constraint-ranking algorithm for learning optimality-theoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and
A new cluster algorithm for graphs
S. van Dongen
1998-01-01
textabstractA new cluster algorithm for graphs called the emph{Markov Cluster algorithm ($MCL$ algorithm) is introduced. The graphs may be both weighted (with nonnegative weight) and directed. Let~$G$~be such a graph. The $MCL$ algorithm simulates flow in $G$ by first identifying $G$ in a
Seamless Merging of Hypertext and Algorithm Animation
Karavirta, Ville
2009-01-01
Online learning material that students use by themselves is one of the typical usages of algorithm animation (AA). Thus, the integration of algorithm animations into hypertext is seen as an important topic today to promote the usage of algorithm animation in teaching. This article presents an algorithm animation viewer implemented purely using…
Deterministic algorithms for multi-criteria TSP
Manthey, Bodo; Ogihara, Mitsunori; Tarui, Jun
2011-01-01
We present deterministic approximation algorithms for the multi-criteria traveling salesman problem (TSP). Our algorithms are faster and simpler than the existing randomized algorithms. First, we devise algorithms for the symmetric and asymmetric multi-criteria Max-TSP that achieve ratios of
Using Alternative Multiplication Algorithms to "Offload" Cognition
Jazby, Dan; Pearn, Cath
2015-01-01
When viewed through a lens of embedded cognition, algorithms may enable aspects of the cognitive work of multi-digit multiplication to be "offloaded" to the environmental structure created by an algorithm. This study analyses four multiplication algorithms by viewing different algorithms as enabling cognitive work to be distributed…
AN ALGORITHM FOR AN ALGORITHM FOR THE DESIGN THE ...
African Journals Online (AJOL)
eobe
focuses on the development of an algorithm for designing an axial flow compressor for designing an axial flow compressor for designing an axial flow compressor for a power generation gas turbine generation gas turbine and attempt and attempt and attempts to bring to the public domain some parameters regarded as.
Big Data Mining: Tools & Algorithms
Directory of Open Access Journals (Sweden)
Adeel Shiraz Hashmi
2016-03-01
Full Text Available We are now in Big Data era, and there is a growing demand for tools which can process and analyze it. Big data analytics deals with extracting valuable information from that complex data which can’t be handled by traditional data mining tools. This paper surveys the available tools which can handle large volumes of data as well as evolving data streams. The data mining tools and algorithms which can handle big data have also been summarized, and one of the tools has been used for mining of large datasets using distributed algorithms.
CATEGORIES OF COMPUTER SYSTEMS ALGORITHMS
Directory of Open Access Journals (Sweden)
A. V. Poltavskiy
2015-01-01
Full Text Available Philosophy as a frame of reference on world around and as the first science is a fundamental basis, "roots" (R. Descartes for all branches of the scientific knowledge accumulated and applied in all fields of activity of a human being person. The theory of algorithms as one of the fundamental sections of mathematics, is also based on researches of the gnoseology conducting cognition of a true picture of the world of the buman being. From gnoseology and ontology positions as fundamental sections of philosophy modern innovative projects are inconceivable without development of programs,and algorithms.
Industrial Applications of Evolutionary Algorithms
Sanchez, Ernesto; Tonda, Alberto
2012-01-01
This book is intended as a reference both for experienced users of evolutionary algorithms and for researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, and advice on solving issues related to fitness computation, modeling and setting appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of all evolutionary algorithms exploited to solve different problems. The book could fill the gap between the
Wavelets theory, algorithms, and applications
Montefusco, Laura
2014-01-01
Wavelets: Theory, Algorithms, and Applications is the fifth volume in the highly respected series, WAVELET ANALYSIS AND ITS APPLICATIONS. This volume shows why wavelet analysis has become a tool of choice infields ranging from image compression, to signal detection and analysis in electrical engineering and geophysics, to analysis of turbulent or intermittent processes. The 28 papers comprising this volume are organized into seven subject areas: multiresolution analysis, wavelet transforms, tools for time-frequency analysis, wavelets and fractals, numerical methods and algorithms, and applicat
Parallel algorithms and cluster computing
Hoffmann, Karl Heinz
2007-01-01
This book presents major advances in high performance computing as well as major advances due to high performance computing. It contains a collection of papers in which results achieved in the collaboration of scientists from computer science, mathematics, physics, and mechanical engineering are presented. From the science problems to the mathematical algorithms and on to the effective implementation of these algorithms on massively parallel and cluster computers we present state-of-the-art methods and technology as well as exemplary results in these fields. This book shows that problems which seem superficially distinct become intimately connected on a computational level.
Optimisation combinatoire Theorie et algorithmes
Korte, Bernhard; Fonlupt, Jean
2010-01-01
Ce livre est la traduction fran aise de la quatri me et derni re dition de Combinatorial Optimization: Theory and Algorithms crit par deux minents sp cialistes du domaine: Bernhard Korte et Jens Vygen de l'universit de Bonn en Allemagne. Il met l accent sur les aspects th oriques de l'optimisation combinatoire ainsi que sur les algorithmes efficaces et exacts de r solution de probl mes. Il se distingue en cela des approches heuristiques plus simples et souvent d crites par ailleurs. L ouvrage contient de nombreuses d monstrations, concises et l gantes, de r sultats difficiles. Destin aux tudia
Algorithms over partially ordered sets
DEFF Research Database (Denmark)
Baer, Robert M.; Østerby, Ole
1969-01-01
We here study some problems concerned with the computational analysis of finite partially ordered sets. We begin (in § 1) by showing that the matrix representation of a binary relationR may always be taken in triangular form ifR is a partial ordering. We consider (in § 2) the chain structure...... in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi...
Deceptiveness and genetic algorithm dynamics
Energy Technology Data Exchange (ETDEWEB)
Liepins, G.E. (Oak Ridge National Lab., TN (USA)); Vose, M.D. (Tennessee Univ., Knoxville, TN (USA))
1990-01-01
We address deceptiveness, one of at least four reasons genetic algorithms can fail to converge to function optima. We construct fully deceptive functions and other functions of intermediate deceptiveness. For the fully deceptive functions of our construction, we generate linear transformations that induce changes of representation to render the functions fully easy. We further model genetic algorithm selection recombination as the interleaving of linear and quadratic operators. Spectral analysis of the underlying matrices allows us to draw preliminary conclusions about fixed points and their stability. We also obtain an explicit formula relating the nonuniform Walsh transform to the dynamics of genetic search. 21 refs.
A Distributed Spanning Tree Algorithm
DEFF Research Database (Denmark)
Johansen, Karl Erik; Jørgensen, Ulla Lundin; Nielsen, Sven Hauge
We present a distributed algorithm for constructing a spanning tree for connected undirected graphs. Nodes correspond to processors and edges correspond to two-way channels. Each processor has initially a distinct identity and all processors perform the same algorithm. Computation as well...... as communication is asynchronous. The total number of messages sent during a construction of a spanning tree is at most 2E+3NlogN. The maximal message size is loglogN+log(maxid)+3, where maxid is the maximal processor identity....
A distributed spanning tree algorithm
DEFF Research Database (Denmark)
Johansen, Karl Erik; Jørgensen, Ulla Lundin; Nielsen, Svend Hauge
1988-01-01
We present a distributed algorithm for constructing a spanning tree for connected undirected graphs. Nodes correspond to processors and edges correspond to two way channels. Each processor has initially a distinct identity and all processors perform the same algorithm. Computation as well...... as communication is asyncronous. The total number of messages sent during a construction of a spanning tree is at most 2E+3NlogN. The maximal message size is loglogN+log(maxid)+3, where maxid is the maximal processor identity....
Performance Evaluation of A* Algorithms
Martell, Victor; Sandberg, Aron
2016-01-01
Context. There have been a lot of progress made in the field of pathfinding. One of the most used algorithms is A*, which over the years has had a lot of variations. There have been a number of papers written about the variations of A* and in what way they specifically improve A*. However, few papers have been written comparing A* with several different variations of A*. Objectives. The objectives of this thesis is to find how Dijkstra's algorithm, IDA*, Theta* and HPA* compare against A* bas...
Analysis and Improvement of Fireworks Algorithm
Xi-Guang Li; Shou-Fei Han; Chang-Qing Gong
2017-01-01
The Fireworks Algorithm is a recently developed swarm intelligence algorithm to simulate the explosion process of fireworks. Based on the analysis of each operator of Fireworks Algorithm (FWA), this paper improves the FWA and proves that the improved algorithm converges to the global optimal solution with probability 1. The proposed algorithm improves the goal of further boosting performance and achieving global optimization where mainly include the following strategies. Firstly using the opp...
A survey of parallel multigrid algorithms
Chan, Tony F.; Tuminaro, Ray S.
1987-01-01
A typical multigrid algorithm applied to well-behaved linear-elliptic partial-differential equations (PDEs) is described. Criteria for designing and evaluating parallel algorithms are presented. Before evaluating the performance of some parallel multigrid algorithms, consideration is given to some theoretical complexity results for solving PDEs in parallel and for executing the multigrid algorithm. The effect of mapping and load imbalance on the partial efficiency of the algorithm is studied.
Some Practical Payments Clearance Algorithms
Kumlander, Deniss
The globalisation of corporations' operations has produced a huge volume of inter-company invoices. Optimisation of those known as payment clearance can produce a significant saving in costs associated with those transfers and handling. The paper revises some common and so practical approaches to the payment clearance problem and proposes some novel algorithms based on graphs theory and heuristic totals' distribution.
Algorithmic Issues in Modeling Motion
DEFF Research Database (Denmark)
Agarwal, P. K; Guibas, L. J; Edelsbrunner, H.
2003-01-01
This article is a survey of research areas in which motion plays a pivotal role. The aim of the article is to review current approaches to modeling motion together with related data structures and algorithms, and to summarize the challenges that lie ahead in producing a more unified theory...
Hill climbing algorithms and trivium
DEFF Research Database (Denmark)
Borghoff, Julia; Knudsen, Lars Ramkilde; Matusiewicz, Krystian
2011-01-01
This paper proposes a new method to solve certain classes of systems of multivariate equations over the binary field and its cryptanalytical applications. We show how heuristic optimization methods such as hill climbing algorithms can be relevant to solving systems of multivariate equations...
Understanding Algorithms in Different Presentations
Csernoch, Mária; Biró, Piroska; Abari, Kálmán; Máth, János
2015-01-01
Within the framework of the Testing Algorithmic and Application Skills project we tested first year students of Informatics at the beginning of their tertiary education. We were focusing on the students' level of understanding in different programming environments. In the present paper we provide the results from the University of Debrecen, the…
Template Generation and Selection Algorithms
Guo, Y.; Smit, Gerardus Johannes Maria; Broersma, Haitze J.; Heysters, P.M.; Badaway, W.; Ismail, Y.
The availability of high-level design entry tooling is crucial for the viability of any reconfigurable SoC architecture. This paper presents a template generation method to extract functional equivalent structures, i.e. templates, from a control data flow graph. By inspecting the graph the algorithm
Document Organization Using Kohonen's Algorithm.
Guerrero Bote, Vicente P.; Moya Anegon, Felix de; Herrero Solana, Victor
2002-01-01
Discussion of the classification of documents from bibliographic databases focuses on a method of vectorizing reference documents from LISA (Library and Information Science Abstracts) which permits their topological organization using Kohonen's algorithm. Analyzes possibilities of this type of neural network with respect to the development of…
Classification algorithms using adaptive partitioning
Binev, Peter
2014-12-01
© 2014 Institute of Mathematical Statistics. Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set approximation to the Bayes set and thus fall into the general category of set estimators. In contrast with the most studied tree-based algorithms, which utilize piecewise constant approximation on the generated partition [IEEE Trans. Inform. Theory 52 (2006) 1335.1353; Mach. Learn. 66 (2007) 209.242], we consider decorated trees, which allow us to derive higher order methods. Convergence rates for these methods are derived in terms the parameter - of margin conditions and a rate s of best approximation of the Bayes set by decorated adaptive partitions. They can also be expressed in terms of the Besov smoothness β of the regression function that governs its approximability by piecewise polynomials on adaptive partition. The execution of the algorithms does not require knowledge of the smoothness or margin conditions. Besov smoothness conditions are weaker than the commonly used Holder conditions, which govern approximation by nonadaptive partitions, and therefore for a given regression function can result in a higher rate of convergence. This in turn mitigates the compatibility conflict between smoothness and margin parameters.
Tau reconstruction and identification algorithm
Indian Academy of Sciences (India)
2012-11-15
Nov 15, 2012 ... from electrons, muons and hadronic jets. These algorithms enable extended reach for the searches for MSSM Higgs, Z and other exotic particles. Keywords. CMS; tau; LHC; ECAL; HCAL. PACS No. 13.35.Dx. 1. Introduction. Tau is the heaviest known lepton (Mτ = 1.78 GeV) which decays into lighter leptons.
Privacy preserving randomized gossip algorithms
Hanzely, Filip
2017-06-23
In this work we present three different randomized gossip algorithms for solving the average consensus problem while at the same time protecting the information about the initial private values stored at the nodes. We give iteration complexity bounds for all methods, and perform extensive numerical experiments.
Associative Algorithms for Computational Creativity
Varshney, Lav R.; Wang, Jun; Varshney, Kush R.
2016-01-01
Computational creativity, the generation of new, unimagined ideas or artifacts by a machine that are deemed creative by people, can be applied in the culinary domain to create novel and flavorful dishes. In fact, we have done so successfully using a combinatorial algorithm for recipe generation combined with statistical models for recipe ranking…
Parallel Algorithms for Model Checking
van de Pol, Jaco; Mousavi, Mohammad Reza; Sgall, Jiri
2017-01-01
Model checking is an automated verification procedure, which checks that a model of a system satisfies certain properties. These properties are typically expressed in some temporal logic, like LTL and CTL. Algorithms for LTL model checking (linear time logic) are based on automata theory and graph
Algorithms and Public Service Media
DEFF Research Database (Denmark)
Sørensen, Jannick Kirk; Hutchinson, Jonathon
2018-01-01
the regulatory conditions. In this chapter we analyse two cases - the EBU-members' introduction of recommender systems and the Australian broadcaster ABC's experiences with the use of chatbots. We use these cases to exemplify the challenges that algorithmic systems poses to PSM organisations....
The TROPOMI surface UV algorithm
Lindfors, Anders V.; Kujanpää, Jukka; Kalakoski, Niilo; Heikkilä, Anu; Lakkala, Kaisa; Mielonen, Tero; Sneep, Maarten; Krotkov, Nickolay A.; Arola, Antti; Tamminen, Johanna
2018-02-01
The TROPOspheric Monitoring Instrument (TROPOMI) is the only payload of the Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of the European Space Agency (ESA). TROPOMI is a nadir-viewing spectrometer measuring in the ultraviolet, visible, near-infrared, and the shortwave infrared that provides near-global daily coverage. Among other things, TROPOMI measurements will be used for calculating the UV radiation reaching the Earth's surface. Thus, the TROPOMI surface UV product will contribute to the monitoring of UV radiation by providing daily information on the prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on the heritage of the Ozone Monitoring Instrument (OMI) and the Satellite Application Facility for Atmospheric Composition and UV Radiation (AC SAF) algorithms. This paper provides a description of the algorithm that will be used for estimating surface UV radiation from TROPOMI observations. The TROPOMI surface UV product includes the following UV quantities: the UV irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV; and the vitamin-D weighted UV. Each of these are available as (i) daily dose or daily accumulated irradiance, (ii) overpass dose rate or irradiance, and (iii) local noon dose rate or irradiance. In addition, all quantities are available corresponding to actual cloud conditions and as clear-sky values, which otherwise correspond to the same conditions but assume a cloud-free atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm has been tested using input based on OMI and the Global Ozone Monitoring Experiment-2 (GOME-2) satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.
The TROPOMI surface UV algorithm
Directory of Open Access Journals (Sweden)
A. V. Lindfors
2018-02-01
Full Text Available The TROPOspheric Monitoring Instrument (TROPOMI is the only payload of the Sentinel-5 Precursor (S5P, which is a polar-orbiting satellite mission of the European Space Agency (ESA. TROPOMI is a nadir-viewing spectrometer measuring in the ultraviolet, visible, near-infrared, and the shortwave infrared that provides near-global daily coverage. Among other things, TROPOMI measurements will be used for calculating the UV radiation reaching the Earth's surface. Thus, the TROPOMI surface UV product will contribute to the monitoring of UV radiation by providing daily information on the prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on the heritage of the Ozone Monitoring Instrument (OMI and the Satellite Application Facility for Atmospheric Composition and UV Radiation (AC SAF algorithms. This paper provides a description of the algorithm that will be used for estimating surface UV radiation from TROPOMI observations. The TROPOMI surface UV product includes the following UV quantities: the UV irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV; and the vitamin-D weighted UV. Each of these are available as (i daily dose or daily accumulated irradiance, (ii overpass dose rate or irradiance, and (iii local noon dose rate or irradiance. In addition, all quantities are available corresponding to actual cloud conditions and as clear-sky values, which otherwise correspond to the same conditions but assume a cloud-free atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm has been tested using input based on OMI and the Global Ozone Monitoring Experiment-2 (GOME-2 satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.
Comparative analysis of distributed power control algorithms in CDMA
Abdulhamid, Mohanad F.
2017-01-01
This paper presents comparative analysis of various algorithms of distributed power control used in Code Division Multiple Access (CDMA) systems. These algorithms include Distributed Balancing power control algorithm (DB), Modified Distributed Balancing power control algorithm (MDB), Fully Distributed Power Control algorithm (FDPC), Distributed Power Control algorithm (DPC), Distributed Constrained Power Control algorithm (DCPC), Unconstrained Second-Order Power Control algorithm (USOPC), Con...
Opposition-Based Adaptive Fireworks Algorithm
Directory of Open Access Journals (Sweden)
Chibing Gong
2016-07-01
Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.
Fused Entropy Algorithm in Optical Computed Tomography
Directory of Open Access Journals (Sweden)
Xiong Wan
2014-02-01
Full Text Available In most applications of optical computed tomography (OpCT, limited-view problems are often encountered, which can be solved to a certain extent with typical OpCT reconstructive algorithms. The concept of entropy first emerged in information theory has been introduced into OpCT algorithms, such as maximum entropy (ME algorithms and cross entropy (CE algorithms, which have demonstrated their superiority over traditional OpCT algorithms, yet have their own limitations. A fused entropy (FE algorithm, which follows an optimized criterion combining self-adaptively ME with CE, is proposed and investigated by comparisons with ME, CE and some traditional OpCT algorithms. Reconstructed results of several physical models show this FE algorithm has a good convergence and can achieve better precision than other algorithms, which verifies the feasibility of FE as an approach of optimizing computation, not only for OpCT, but also for other image processing applications.
Linear Bregman algorithm implemented in parallel GPU
Li, Pengyan; Ke, Jue; Sui, Dong; Wei, Ping
2015-08-01
At present, most compressed sensing (CS) algorithms have poor converging speed, thus are difficult to run on PC. To deal with this issue, we use a parallel GPU, to implement a broadly used compressed sensing algorithm, the Linear Bregman algorithm. Linear iterative Bregman algorithm is a reconstruction algorithm proposed by Osher and Cai. Compared with other CS reconstruction algorithms, the linear Bregman algorithm only involves the vector and matrix multiplication and thresholding operation, and is simpler and more efficient for programming. We use C as a development language and adopt CUDA (Compute Unified Device Architecture) as parallel computing architectures. In this paper, we compared the parallel Bregman algorithm with traditional CPU realized Bregaman algorithm. In addition, we also compared the parallel Bregman algorithm with other CS reconstruction algorithms, such as OMP and TwIST algorithms. Compared with these two algorithms, the result of this paper shows that, the parallel Bregman algorithm needs shorter time, and thus is more convenient for real-time object reconstruction, which is important to people's fast growing demand to information technology.
Indian Academy of Sciences (India)
immediate successor as well as the immediate predecessor explicitly. Such a list is referred to as a doubly linked list. A typical doubly linked list is shown in Figure 3f. The ability to get to either the successor or predecessor not only makes access easy but also enables one to backtrack in a search. Two Dimensional Arrays: It ...
Indian Academy of Sciences (India)
SERIES I ARTICLE. Table 2 Merging two sorted arrays. procedure MERGE_TWO _ARRA YS(A[I,p], B(1, q], C[I,p+q]:integer);. (* A[l,p], B[l, q] are the sorted arrays to be merged and placed in array C. *). (* Note that array C will be oflength p+q; in the program we use parameters *). (* p and q explicidy *) var i, j, k: integer; begin.
Indian Academy of Sciences (India)
like programming language. Recursion. One of the usual techniques of problem solving is to break the problem into smaller problems. From the solution of these smaller problems, one obtains a solution for the original problem. Consider the procedural abstraction described above. It is possible to visualize the given ...
Indian Academy of Sciences (India)
guesses for the technique discussed above. The method described above for computing the approximate square root is referred to as Newton's method for finding..Ja after the famous English mathematician Isaac Newton. In Table 5, we have essentially solved the nonlinear equation. RESONANCE I March 1996 - ---- .
Indian Academy of Sciences (India)
In the previous article of this series, we looked at simple data types and their representation in computer memory. The notion of a simple data type can be extended to denote a set of elements corresponding to one data item at a higher level. The process of structuring or grouping of the basic data elements is often referred ...
Indian Academy of Sciences (India)
var A: array [looN, 100M] of integer;. The above declaration denotes that A is an array having N rows and M columns. Applications for arrays are innumerable; the simplest being the classical multiplication table. A table can also be used to store hostel room numbers and codes of the persons staying in the respective rooms.
Indian Academy of Sciences (India)
1 It must be noted that if the input assertion is not satisfied at this point, then any output assertion holds due to the classical implication operator. ..... on our intuitive knowledge about the underlying theory. The above processes can be formalised in a logical framework without relying on the intuitive deductions we have used.
Denni Algorithm An Enhanced Of SMS (Scan, Move and Sort) Algorithm
Aprilsyah Lubis, Denni; Salim Sitompul, Opim; Marwan; Tulus; Andri Budiman, M.
2017-12-01
Sorting has been a profound area for the algorithmic researchers, and many resources are invested to suggest a more working sorting algorithm. For this purpose many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. Efficient sorting is important to optimize the use of other algorithms that require sorted lists to work correctly. Sorting has been considered as a fundamental problem in the study of algorithms that due to many reasons namely, the necessary to sort information is inherent in many applications, algorithms often use sorting as a key subroutine, in algorithm design there are many essential techniques represented in the body of sorting algorithms, and many engineering issues come to the fore when implementing sorting algorithms., Many algorithms are very well known for sorting the unordered lists, and one of the well-known algorithms that make the process of sorting to be more economical and efficient is SMS (Scan, Move and Sort) algorithm, an enhancement of Quicksort invented Rami Mansi in 2010. This paper presents a new sorting algorithm called Denni-algorithm. The Denni algorithm is considered as an enhancement on the SMS algorithm in average, and worst cases. The Denni algorithm is compared with the SMS algorithm and the results were promising.
Hybrid employment recommendation algorithm based on Spark
Li, Zuoquan; Lin, Yubei; Zhang, Xingming
2017-08-01
Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.
MUSIC algorithms for rebar detection
International Nuclear Information System (INIS)
Solimene, Raffaele; Leone, Giovanni; Dell’Aversano, Angela
2013-01-01
The MUSIC (MUltiple SIgnal Classification) algorithm is employed to detect and localize an unknown number of scattering objects which are small in size as compared to the wavelength. The ensemble of objects to be detected consists of both strong and weak scatterers. This represents a scattering environment challenging for detection purposes as strong scatterers tend to mask the weak ones. Consequently, the detection of more weakly scattering objects is not always guaranteed and can be completely impaired when the noise corrupting data is of a relatively high level. To overcome this drawback, here a new technique is proposed, starting from the idea of applying a two-stage MUSIC algorithm. In the first stage strong scatterers are detected. Then, information concerning their number and location is employed in the second stage focusing only on the weak scatterers. The role of an adequate scattering model is emphasized to improve drastically detection performance in realistic scenarios. (paper)
A fast meteor detection algorithm
Gural, P.
2016-01-01
A low latency meteor detection algorithm for use with fast steering mirrors had been previously developed to track and telescopically follow meteors in real-time (Gural, 2007). It has been rewritten as a generic clustering and tracking software module for meteor detection that meets both the demanding throughput requirements of a Raspberry Pi while also maintaining a high probability of detection. The software interface is generalized to work with various forms of front-end video pre-processing approaches and provides a rich product set of parameterized line detection metrics. Discussion will include the Maximum Temporal Pixel (MTP) compression technique as a fast thresholding option for feeding the detection module, the detection algorithm trade for maximum processing throughput, details on the clustering and tracking methodology, processing products, performance metrics, and a general interface description.
Loewenstein, M.; Greenblatt. B. J.; Jost, H.; Podolske, J. R.; Elkins, Jim; Hurst, Dale; Romanashkin, Pavel; Atlas, Elliott; Schauffler, Sue; Donnelly, Steve;
2000-01-01
De-nitrification and excess re-nitrification was widely observed by ER-2 instruments in the Arctic vortex during SOLVE in winter/spring 2000. Analyses of these events requires a knowledge of the initial or pre-vortex state of the sampled air masses. The canonical relationship of NOy to the long-lived tracer N2O observed in the unperturbed stratosphere is generally used for this purpose. In this paper we will attempt to establish the current unperturbed NOy:N2O relationship (NOy* algorithm) using the ensemble of extra-vortex data from in situ instruments flying on the ER-2 and DC-8, and from the Mark IV remote measurements on the OMS balloon. Initial analysis indicates a change in the SOLVE NOy* from the values predicted by the 1994 Northern Hemisphere NOy* algorithm which was derived from the observations in the ASHOE/MAESA campaign.
Interactive video algorithms and technologies
Hammoud, Riad
2006-01-01
This book covers both algorithms and technologies of interactive videos, so that businesses in IT and data managements, scientists and software engineers in video processing and computer vision, coaches and instructors that use video technology in teaching, and finally end-users will greatly benefit from it. This book contains excellent scientific contributions made by a number of pioneering scientists and experts from around the globe. It consists of five parts. The first part introduces the reader to interactive video and video summarization and presents effective methodologies for automatic abstraction of a single video sequence, a set of video sequences, and a combined audio-video sequence. In the second part, a list of advanced algorithms and methodologies for automatic and semi-automatic analysis and editing of audio-video documents are presented. The third part tackles a more challenging level of automatic video re-structuring, filtering of video stream by extracting of highlights, events, and meaningf...
Combinatorial optimization theory and algorithms
Korte, Bernhard
2018-01-01
This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This sixth edition has again been updated, revised, and significantly extended. Among other additions, there are new sections on shallow-light trees, submodular function maximization, smoothed analysis of the knapsack problem, the (ln 4+ɛ)-approximation for Steiner trees, and the VPN theorem. Thus, this book continues to represent the state of the art of combinatorial opti...
Algorithms for Lightweight Key Exchange.
Alvarez, Rafael; Caballero-Gil, Cándido; Santonja, Juan; Zamora, Antonio
2017-06-27
Public-key cryptography is too slow for general purpose encryption, with most applications limiting its use as much as possible. Some secure protocols, especially those that enable forward secrecy, make a much heavier use of public-key cryptography, increasing the demand for lightweight cryptosystems that can be implemented in low powered or mobile devices. This performance requirements are even more significant in critical infrastructure and emergency scenarios where peer-to-peer networks are deployed for increased availability and resiliency. We benchmark several public-key key-exchange algorithms, determining those that are better for the requirements of critical infrastructure and emergency applications and propose a security framework based on these algorithms and study its application to decentralized node or sensor networks.
Innovations in Lattice QCD Algorithms
Energy Technology Data Exchange (ETDEWEB)
Konstantinos Orginos
2006-06-25
Lattice QCD calculations demand a substantial amount of computing power in order to achieve the high precision results needed to better understand the nature of strong interactions, assist experiment to discover new physics, and predict the behavior of a diverse set of physical systems ranging from the proton itself to astrophysical objects such as neutron stars. However, computer power alone is clearly not enough to tackle the calculations we need to be doing today. A steady stream of recent algorithmic developments has made an important impact on the kinds of calculations we can currently perform. In this talk I am reviewing these algorithms and their impact on the nature of lattice QCD calculations performed today.
MUSIC algorithms for rebar detection
Solimene, Raffaele; Leone, Giovanni; Dell'Aversano, Angela
2013-12-01
The MUSIC (MUltiple SIgnal Classification) algorithm is employed to detect and localize an unknown number of scattering objects which are small in size as compared to the wavelength. The ensemble of objects to be detected consists of both strong and weak scatterers. This represents a scattering environment challenging for detection purposes as strong scatterers tend to mask the weak ones. Consequently, the detection of more weakly scattering objects is not always guaranteed and can be completely impaired when the noise corrupting data is of a relatively high level. To overcome this drawback, here a new technique is proposed, starting from the idea of applying a two-stage MUSIC algorithm. In the first stage strong scatterers are detected. Then, information concerning their number and location is employed in the second stage focusing only on the weak scatterers. The role of an adequate scattering model is emphasized to improve drastically detection performance in realistic scenarios.
Genetic Algorithms for Case Adaptation
International Nuclear Information System (INIS)
Salem, A.M.; Mohamed, A.H.
2008-01-01
Case based reasoning (CBR) paradigm has been widely used to provide computer support for recalling and adapting known cases to novel situations. Case adaptation algorithms generally rely on knowledge based and heuristics in order to change the past solutions to solve new problems. However, case adaptation has always been a difficult process to engineers within (CBR) cycle. Its difficulties can be referred to its domain dependency; and computational cost. In an effort to solve this problem, this research explores a general-purpose method that applying a genetic algorithm (GA) to CBR adaptation. Therefore, it can decrease the computational complexity of the search space in the problems having a great dependency on their domain knowledge. The proposed model can be used to perform a variety of design tasks on a broad set of application domains. However, it has been implemented for the tablet formulation as a domain of application. The proposed system has improved the performance of the CBR design systems
Algorithms for Protein Structure Prediction
DEFF Research Database (Denmark)
Paluszewski, Martin
) and contact number (CN) measures only. We show that the HSE measure is much more information-rich than CN, nevertheless, HSE does not appear to provide enough information to reconstruct the C-traces of real-sized proteins. Our experiments also show that using tabu search (with our novel tabu definition......The problem of predicting the three-dimensional structure of a protein given its amino acid sequence is one of the most important open problems in bioinformatics. One of the carbon atoms in amino acids is the C-atom and the overall structure of a protein is often represented by a so-called C...... is competitive in quality and speed with other state-of-the-art decoy generation algorithms. Our third C-trace reconstruction approach is based on bee-colony optimization [24]. We demonstrate why this algorithm has some important properties that makes it suitable for protein structure prediction. Our approach...
Computed laminography and reconstruction algorithm
International Nuclear Information System (INIS)
Que Jiemin; Cao Daquan; Zhao Wei; Tang Xiao
2012-01-01
Computed laminography (CL) is an alternative to computed tomography if large objects are to be inspected with high resolution. This is especially true for planar objects. In this paper, we set up a new scanning geometry for CL, and study the algebraic reconstruction technique (ART) for CL imaging. We compare the results of ART with variant weighted functions by computer simulation with a digital phantom. It proves that ART algorithm is a good choice for the CL system. (authors)
Machine vision theory, algorithms, practicalities
Davies, E R
2005-01-01
In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directl
Parallel External Memory Graph Algorithms
DEFF Research Database (Denmark)
Arge, Lars Allan; Goodrich, Michael T.; Sitchinava, Nodari
2010-01-01
In this paper, we study parallel I/O efficient graph algorithms in the Parallel External Memory (PEM) model, one o f the private-cache chip multiprocessor (CMP) models. We study the fundamental problem of list ranking which leads to efficient solutions to problems on trees, such as computing lowest...... an optimal speedup of Â¿(P) in parallel I/O complexity and parallel computation time, compared to the single-processor external memory counterparts....
Graphics and visualization principles & algorithms
Theoharis, T; Platis, Nikolaos; Patrikalakis, Nicholas M
2008-01-01
Computer and engineering collections strong in applied graphics and analysis of visual data via computer will find Graphics & Visualization: Principles and Algorithms makes an excellent classroom text as well as supplemental reading. It integrates coverage of computer graphics and other visualization topics, from shadow geneeration and particle tracing to spatial subdivision and vector data visualization, and it provides a thorough review of literature from multiple experts, making for a comprehensive review essential to any advanced computer study.-California Bookw
Parallel algorithms for continuum dynamics
International Nuclear Information System (INIS)
Hicks, D.L.; Liebrock, L.M.
1987-01-01
Simply porting existing parallel programs to a new parallel processor may not achieve the full speedup possible; to achieve the maximum efficiency may require redesigning the parallel algorithms for the specific architecture. The authors discuss here parallel algorithms that were developed first for the HEP processor and then ported to the CRAY X-MP/4, the ELXSI/10, and the Intel iPSC/32. Focus is mainly on the most recent parallel processing results produced, i.e., those on the Intel Hypercube. The applications are simulations of continuum dynamics in which the momentum and stress gradients are important. Examples of these are inertial confinement fusion experiments, severe breaks in the coolant system of a reactor, weapons physics, shock-wave physics. Speedup efficiencies on the Intel iPSC Hypercube are very sensitive to the ratio of communication to computation. Great care must be taken in designing algorithms for this machine to avoid global communication. This is much more critical on the iPSC than it was on the three previous parallel processors
Comparison of turbulence mitigation algorithms
Kozacik, Stephen T.; Paolini, Aaron; Sherman, Ariel; Bonnett, James; Kelmelis, Eric
2017-07-01
When capturing imagery over long distances, atmospheric turbulence often degrades the data, especially when observation paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms has different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for postprocessing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005. We will compare techniques from the literature with our commercially available, real-time, GPU-accelerated turbulence mitigation software. These comparisons will be made using real (not synthetic), experimentally obtained data for a variety of conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation. Additionally, we will present a technique for quantitatively comparing turbulence mitigation algorithms using real images of radial resolution targets.
Unconventional Algorithms: Complementarity of Axiomatics and Construction
Directory of Open Access Journals (Sweden)
Gordana Dodig Crnkovic
2012-10-01
Full Text Available In this paper, we analyze axiomatic and constructive issues of unconventional computations from a methodological and philosophical point of view. We explain how the new models of algorithms and unconventional computations change the algorithmic universe, making it open and allowing increased flexibility and expressive power that augment creativity. At the same time, the greater power of new types of algorithms also results in the greater complexity of the algorithmic universe, transforming it into the algorithmic multiverse and demanding new tools for its study. That is why we analyze new powerful tools brought forth by local mathematics, local logics, logical varieties and the axiomatic theory of algorithms, automata and computation. We demonstrate how these new tools allow efficient navigation in the algorithmic multiverse. Further work includes study of natural computation by unconventional algorithms and constructive approaches.
Teaching Multiplication Algorithms from Other Cultures
Lin, Cheng-Yao
2007-01-01
This article describes a number of multiplication algorithms from different cultures around the world: Hindu, Egyptian, Russian, Japanese, and Chinese. Students can learn these algorithms and better understand the operation and properties of multiplication.
Algorithm for Shaffer's Multiple Comparison Tests.
Rasmussen, Jeffrey Lee
1993-01-01
J. P. Shaffer has presented two tests to improve the power of multiple comparison procedures. This article described an algorithm to carry out the tests. The logic of the algorithm and an application to a data set are given. (SLD)
Trilateral market coupling. Algorithm appendix
International Nuclear Information System (INIS)
2006-03-01
Market Coupling is both a mechanism for matching orders on the exchange and an implicit cross-border capacity allocation mechanism. Market Coupling improves the economic surplus of the coupled markets: the highest purchase orders and the lowest sale orders of the coupled power exchanges are matched, regardless of the area where they have been submitted; matching results depend however on the Available Transfer Capacity (ATC) between the coupled hubs. Market prices and schedules of the day-ahead power exchanges of the several connected markets are simultaneously determined with the use of the Available Transfer Capacity defined by the relevant Transmission System Operators. The transmission capacity is thereby implicitly auctioned and the implicit cost of the transmission capacity from one market to the other is the price difference between the two markets. In particular, if the transmission capacity between two markets is not fully used, there is no price difference between the markets and the implicit cost of the transmission capacity is null. Market coupling relies on the principle that the market with the lowest price exports electricity to the market with the highest price. Two situations may appear: either the Available Transfer Capacity (ATC) is large enough and the prices of both markets are equalized (price convergence), or the ATC is too small and the prices cannot be equalized. The Market Coupling algorithm takes as an input: 1 - The Available Transfer Capacity (ATC) between each area for each flow direction and each Settlement Period of the following day (i.e. for each hour of following day); 2 - The (Block Free) Net Export Curves (NEC) of each market for each hour of the following day, i.e., the difference between the total quantity of Divisible Hourly Bids and the total quantity of Divisible Hourly Offers for each price level. The NEC reflects a market's import or export volume sensitivity to price. 3 - The Block Orders submitted by the participants in
Opposition-Based Adaptive Fireworks Algorithm
Chibing Gong
2016-01-01
A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based a...
Automatic Algorithm Selection for Complex Simulation Problems
Ewald, Roland
2012-01-01
To select the most suitable simulation algorithm for a given task is often difficult. This is due to intricate interactions between model features, implementation details, and runtime environment, which may strongly affect the overall performance. An automated selection of simulation algorithms supports users in setting up simulation experiments without demanding expert knowledge on simulation. Roland Ewald analyzes and discusses existing approaches to solve the algorithm selection problem in the context of simulation. He introduces a framework for automatic simulation algorithm selection and
A Deterministic and Polynomial Modified Perceptron Algorithm
Directory of Open Access Journals (Sweden)
Olof Barr
2006-01-01
Full Text Available We construct a modified perceptron algorithm that is deterministic, polynomial and also as fast as previous known algorithms. The algorithm runs in time O(mn3lognlog(1/ρ, where m is the number of examples, n the number of dimensions and ρ is approximately the size of the margin. We also construct a non-deterministic modified perceptron algorithm running in timeO(mn2lognlog(1/ρ.
EM Algorithm and Stochastic Control in Economics
Kou, Steven; Peng, Xianhua; Xu, Xingbo
2016-01-01
Generalising the idea of the classical EM algorithm that is widely used for computing maximum likelihood estimates, we propose an EM-Control (EM-C) algorithm for solving multi-period finite time horizon stochastic control problems. The new algorithm sequentially updates the control policies in each time period using Monte Carlo simulation in a forward-backward manner; in other words, the algorithm goes forward in simulation and backward in optimization in each iteration. Similar to the EM alg...
A Euclidean algorithm for integer matrices
DEFF Research Database (Denmark)
Lauritzen, Niels; Thomsen, Jesper Funch
2015-01-01
We present a Euclidean algorithm for computing a greatest common right divisor of two integer matrices. The algorithm is derived from elementary properties of finitely generated modules over the ring of integers.......We present a Euclidean algorithm for computing a greatest common right divisor of two integer matrices. The algorithm is derived from elementary properties of finitely generated modules over the ring of integers....
A New Perspective on Randomized Gossip Algorithms
Loizou, Nicolas; Richtárik, Peter
2016-01-01
In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how that Randomized Block Kaczmarz (RBK) method - a method for solving linear systems - works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case. Subsequently, we reveal a hidden duality of randomized gossip algorithms, with the ...
Algorithm 896: LSA: Algorithms for Large-Scale Optimization
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2009-01-01
Roč. 36, č. 3 (2009), 16-1-16-29 ISSN 0098-3500 R&D Projects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : algorithms * design * large-scale optimization * large-scale nonsmooth optimization * large-scale nonlinear least squares * large-scale nonlinear minimax * large-scale systems of nonlinear equations * sparse problems * partially separable problems * limited-memory methods * discrete Newton methods * quasi-Newton methods * primal interior -point methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.904, year: 2009
Engineering a cache-oblivious sorting algorithm
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Fagerberg, Rolf; Vinther, Kristoffer
2007-01-01
This paper is an algorithmic engineering study of cache-oblivious sorting. We investigate by empirical methods a number of implementation issues and parameter choices for the cache-oblivious sorting algorithm Lazy Funnelsort, and compare the final algorithm with Quicksort, the established standard...
Learning Intelligent Genetic Algorithms Using Japanese Nonograms
Tsai, Jinn-Tsong; Chou, Ping-Yi; Fang, Jia-Cen
2012-01-01
An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and…
Discrete Riccati equation solutions: Distributed algorithms
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available In this paper new distributed algorithms for the solution of the discrete Riccati equation are introduced. The algorithms are used to provide robust and computational efficient solutions to the discrete Riccati equation. The proposed distributed algorithms are theoretically interesting and computationally attractive.
Successive combination jet algorithm for hadron collisions
International Nuclear Information System (INIS)
Ellis, S.D.; Soper, D.E.
1993-01-01
Jet finding algorithms, as they are used in e + e- and hadron collisions, are reviewed and compared. It is suggested that a successive combination style algorithm, similar to that used in e + e- physics, might be useful also in hadron collisions, where cone style algorithms have been used previously
Feedback model predictive control by randomized algorithms
Batina, Ivo; Stoorvogel, Antonie Arij; Weiland, Siep
2001-01-01
In this paper we present a further development of an algorithm for stochastic disturbance rejection in model predictive control with input constraints based on randomized algorithms. The algorithm presented in our work can solve the problem of stochastic disturbance rejection approximately but with
A Robustly Stabilizing Model Predictive Control Algorithm
Ackmece, A. Behcet; Carson, John M., III
2007-01-01
A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.
Storage capacity of the Tilinglike Learning Algorithm
International Nuclear Information System (INIS)
Buhot, Arnaud; Gordon, Mirta B.
2001-01-01
The storage capacity of an incremental learning algorithm for the parity machine, the Tilinglike Learning Algorithm, is analytically determined in the limit of a large number of hidden perceptrons. Different learning rules for the simple perceptron are investigated. The usual Gardner-Derrida rule leads to a storage capacity close to the upper bound, which is independent of the learning algorithm considered
Searching Algorithms Implemented on Probabilistic Systolic Arrays
Czech Academy of Sciences Publication Activity Database
Kramosil, Ivan
1996-01-01
Roč. 25, č. 1 (1996), s. 7-45 ISSN 0308-1079 R&D Projects: GA ČR GA201/93/0781 Keywords : searching algorithms * probabilistic algorithms * systolic arrays * parallel algorithms Impact factor: 0.214, year: 1996
Algorithm FIRE-Feynman Integral REduction
International Nuclear Information System (INIS)
Smirnov, A.V.
2008-01-01
The recently developed algorithm FIRE performs the reduction of Feynman integrals to master integrals. It is based on a number of strategies, such as applying the Laporta algorithm, the s-bases algorithm, region-bases and integrating explicitly over loop momenta when possible. Currently it is being used in complicated three-loop calculations.
Portfolio selection using genetic algorithms | Yahaya | International ...
African Journals Online (AJOL)
In this paper, one of the nature-inspired evolutionary algorithms – a Genetic Algorithms (GA) was used in solving the portfolio selection problem (PSP). Based on a real dataset from a popular stock market, the performance of the algorithm in relation to those obtained from one of the popular quadratic programming (QP) ...
On König's root finding algorithms
DEFF Research Database (Denmark)
Buff, Xavier; Henriksen, Christian
2003-01-01
In this paper, we first recall the definition of a family of root-finding algorithms known as König's algorithms. We establish some local and some global properties of those algorithms. We give a characterization of rational maps which arise as König's methods of polynomials with simple roots. We...
Hardware Acceleration of Sparse Cognitive Algorithms
2016-05-01
is clear that these emerging algorithms that can support unsupervised , or lightly supervised learning , as well as incremental learning , map poorly...distribution unlimited. 8.0 CONCLUDING REMARKS These emerging algorithms that can support unsupervised , or lightly supervised learning , as well as...15. SUBJECT TERMS Cortical Algorithms; Machine Learning ; Hardware; VLSI; ASIC 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT: SAR
An algorithm for reduct cardinality minimization
AbouEisha, Hassan M.
2013-12-01
This is devoted to the consideration of a new algorithm for reduct cardinality minimization. This algorithm transforms the initial table to a decision table of a special kind, simplify this table, and use a dynamic programming algorithm to finish the construction of an optimal reduct. Results of computer experiments with decision tables from UCI ML Repository are discussed. © 2013 IEEE.
Research on AHP decision algorithms based on BP algorithm
Ma, Ning; Guan, Jianhe
2017-10-01
Decision making is the thinking activity that people choose or judge, and scientific decision-making has always been a hot issue in the field of research. Analytic Hierarchy Process (AHP) is a simple and practical multi-criteria and multi-objective decision-making method that combines quantitative and qualitative and can show and calculate the subjective judgment in digital form. In the process of decision analysis using AHP method, the rationality of the two-dimensional judgment matrix has a great influence on the decision result. However, in dealing with the real problem, the judgment matrix produced by the two-dimensional comparison is often inconsistent, that is, it does not meet the consistency requirements. BP neural network algorithm is an adaptive nonlinear dynamic system. It has powerful collective computing ability and learning ability. It can perfect the data by constantly modifying the weights and thresholds of the network to achieve the goal of minimizing the mean square error. In this paper, the BP algorithm is used to deal with the consistency of the two-dimensional judgment matrix of the AHP.
Filtering algorithm for dotted interferences
Energy Technology Data Exchange (ETDEWEB)
Osterloh, K., E-mail: kurt.osterloh@bam.de [Federal Institute for Materials Research and Testing (BAM), Division VIII.3, Radiological Methods, Unter den Eichen 87, 12205 Berlin (Germany); Buecherl, T.; Lierse von Gostomski, Ch. [Technische Universitaet Muenchen, Lehrstuhl fuer Radiochemie, Walther-Meissner-Str. 3, 85748 Garching (Germany); Zscherpel, U.; Ewert, U. [Federal Institute for Materials Research and Testing (BAM), Division VIII.3, Radiological Methods, Unter den Eichen 87, 12205 Berlin (Germany); Bock, S. [Technische Universitaet Muenchen, Lehrstuhl fuer Radiochemie, Walther-Meissner-Str. 3, 85748 Garching (Germany)
2011-09-21
An algorithm has been developed to remove reliably dotted interferences impairing the perceptibility of objects within a radiographic image. This particularly is a major challenge encountered with neutron radiographs collected at the NECTAR facility, Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II): the resulting images are dominated by features resembling a snow flurry. These artefacts are caused by scattered neutrons, gamma radiation, cosmic radiation, etc. all hitting the detector CCD directly in spite of a sophisticated shielding. This makes such images rather useless for further direct evaluations. One approach to resolve this problem of these random effects would be to collect a vast number of single images, to combine them appropriately and to process them with common image filtering procedures. However, it has been shown that, e.g. median filtering, depending on the kernel size in the plane and/or the number of single shots to be combined, is either insufficient or tends to blur sharp lined structures. This inevitably makes a visually controlled processing image by image unavoidable. Particularly in tomographic studies, it would be by far too tedious to treat each single projection by this way. Alternatively, it would be not only more comfortable but also in many cases the only reasonable approach to filter a stack of images in a batch procedure to get rid of the disturbing interferences. The algorithm presented here meets all these requirements. It reliably frees the images from the snowy pattern described above without the loss of fine structures and without a general blurring of the image. It consists of an iterative, within a batch procedure parameter free filtering algorithm aiming to eliminate the often complex interfering artefacts while leaving the original information untouched as far as possible.
Statistical Mechanics Algorithms and Computations
Krauth, Werner
2006-01-01
This book discusses the computational approach in modern statistical physics, adopting simple language and an attractive format of many illustrations, tables and printed algorithms. The discussion of key subjects in classical and quantum statistical physics will appeal to students, teachers and researchers in physics and related sciences. The focus is on orientation with implementation details kept to a minimum. - ;This book discusses the computational approach in modern statistical physics in a clear and accessible way and demonstrates its close relation to other approaches in theoretical phy
Algorithms for optimizing drug therapy
Directory of Open Access Journals (Sweden)
Martin Lene
2004-07-01
Full Text Available Abstract Background Drug therapy has become increasingly efficient, with more drugs available for treatment of an ever-growing number of conditions. Yet, drug use is reported to be sub optimal in several aspects, such as dosage, patient's adherence and outcome of therapy. The aim of the current study was to investigate the possibility to optimize drug therapy using computer programs, available on the Internet. Methods One hundred and ten officially endorsed text documents, published between 1996 and 2004, containing guidelines for drug therapy in 246 disorders, were analyzed with regard to information about patient-, disease- and drug-related factors and relationships between these factors. This information was used to construct algorithms for identifying optimum treatment in each of the studied disorders. These algorithms were categorized in order to define as few models as possible that still could accommodate the identified factors and the relationships between them. The resulting program prototypes were implemented in HTML (user interface and JavaScript (program logic. Results Three types of algorithms were sufficient for the intended purpose. The simplest type is a list of factors, each of which implies that the particular patient should or should not receive treatment. This is adequate in situations where only one treatment exists. The second type, a more elaborate model, is required when treatment can by provided using drugs from different pharmacological classes and the selection of drug class is dependent on patient characteristics. An easily implemented set of if-then statements was able to manage the identified information in such instances. The third type was needed in the few situations where the selection and dosage of drugs were depending on the degree to which one or more patient-specific factors were present. In these cases the implementation of an established decision model based on fuzzy sets was required. Computer programs
Complex fluids modeling and algorithms
Saramito, Pierre
2016-01-01
This book presents a comprehensive overview of the modeling of complex fluids, including many common substances, such as toothpaste, hair gel, mayonnaise, liquid foam, cement and blood, which cannot be described by Navier-Stokes equations. It also offers an up-to-date mathematical and numerical analysis of the corresponding equations, as well as several practical numerical algorithms and software solutions for the approximation of the solutions. It discusses industrial (molten plastics, forming process), geophysical (mud flows, volcanic lava, glaciers and snow avalanches), and biological (blood flows, tissues) modeling applications. This book is a valuable resource for undergraduate students and researchers in applied mathematics, mechanical engineering and physics.
Algorithmes Efficaces en Calcul Formel
Bostan, Alin; Chyzak, Frédéric; Giusti, Marc; Lebreton, Romain; Lecerf, Grégoire; Salvy, Bruno; Schost, Eric
2017-01-01
Voir la page du livre à l’adresse \\url{https://hal.archives-ouvertes.fr/AECF/}; International audience; Le calcul formel traite des objets mathématiques exacts d’un point de vue informatique. Cet ouvrage « Algorithmes efficaces en calcul formel » explore deux directions : la calculabilité et la complexité. La calculabilité étudie les classes d’objets mathématiques sur lesquelles des réponses peuvent être obtenues algorithmiquement. La complexité donne ensuite des outils pour comparer des algo...
Integrated Association Rules Complete Hiding Algorithms
Directory of Open Access Journals (Sweden)
Mohamed Refaat Abdellah
2017-01-01
Full Text Available This paper presents database security approach for complete hiding of sensitive association rules by using six novel algorithms. These algorithms utilize three new weights to reduce the needed database modifications and support complete hiding, as well as they reduce the knowledge distortion and the data distortions. Complete weighted hiding algorithms enhance the hiding failure by 100%; these algorithms have the advantage of performing only a single scan for the database to gather the required information to form the hiding process. These proposed algorithms are built within the database structure which enables the sanitized database to be generated on run time as needed.
New Algorithm For Calculating Wavelet Transforms
Directory of Open Access Journals (Sweden)
Piotr Lipinski
2009-04-01
Full Text Available In this article we introduce a new algorithm for computing Discrete Wavelet Transforms (DWT. The algorithm aims at reducing the number of multiplications, required to compute a DWT. The algorithm is general and can be used to compute a variety of wavelet transform (Daubechies and CDF. Here we focus on CDF 9/7 filters, which are used in JPEG2000 compression standard. We show that the algorithm outperforms convolution-based and lifting-based algorithms in terms of number of multiplications.
MSDR-D Network Localization Algorithm
Coogan, Kevin; Khare, Varun; Kobourov, Stephen G.; Katz, Bastian
We present a distributed multi-scale dead-reckoning (MSDR-D) algorithm for network localization that utilizes local distance and angular information for nearby sensors. The algorithm is anchor-free and does not require particular network topology, rigidity of the underlying communication graph, or high average connectivity. The algorithm scales well to large and sparse networks with complex topologies and outperforms previous algorithms when the noise levels are high. The algorithm is simple to implement and is available, along with source code, executables, and experimental results, at http://msdr-d.cs.arizona.edu/.
New algorithms for binary wavefront optimization
Zhang, Xiaolong; Kner, Peter
2015-03-01
Binary amplitude modulation promises to allow rapid focusing through strongly scattering media with a large number of segments due to the faster update rates of digital micromirror devices (DMDs) compared to spatial light modulators (SLMs). While binary amplitude modulation has a lower theoretical enhancement than phase modulation, the faster update rate should more than compensate for the difference - a factor of π2 /2. Here we present two new algorithms, a genetic algorithm and a transmission matrix algorithm, for optimizing the focus with binary amplitude modulation that achieve enhancements close to the theoretical maximum. Genetic algorithms have been shown to work well in noisy environments and we show that the genetic algorithm performs better than a stepwise algorithm. Transmission matrix algorithms allow complete characterization and control of the medium but require phase control either at the input or output. Here we introduce a transmission matrix algorithm that works with only binary amplitude control and intensity measurements. We apply these algorithms to binary amplitude modulation using a Texas Instruments Digital Micromirror Device. Here we report an enhancement of 152 with 1536 segments (9.90%×N) using a genetic algorithm with binary amplitude modulation and an enhancement of 136 with 1536 segments (8.9%×N) using an intensity-only transmission matrix algorithm.
The global Minmax k-means algorithm.
Wang, Xiaoyan; Bai, Yanping
2016-01-01
The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.
Empirical study of parallel LRU simulation algorithms
Carr, Eric; Nicol, David M.
1994-01-01
This paper reports on the performance of five parallel algorithms for simulating a fully associative cache operating under the LRU (Least-Recently-Used) replacement policy. Three of the algorithms are SIMD, and are implemented on the MasPar MP-2 architecture. Two other algorithms are parallelizations of an efficient serial algorithm on the Intel Paragon. One SIMD algorithm is quite simple, but its cost is linear in the cache size. The two other SIMD algorithm are more complex, but have costs that are independent on the cache size. Both the second and third SIMD algorithms compute all stack distances; the second SIMD algorithm is completely general, whereas the third SIMD algorithm presumes and takes advantage of bounds on the range of reference tags. Both MIMD algorithm implemented on the Paragon are general and compute all stack distances; they differ in one step that may affect their respective scalability. We assess the strengths and weaknesses of these algorithms as a function of problem size and characteristics, and compare their performance on traces derived from execution of three SPEC benchmark programs.
Smell Detection Agent Based Optimization Algorithm
Vinod Chandra, S. S.
2016-09-01
In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.
Learning algorithms and automatic processing of languages
International Nuclear Information System (INIS)
Fluhr, Christian Yves Andre
1977-01-01
This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts
Active noise cancellation algorithms for impulsive noise.
Li, Peng; Yu, Xun
2013-04-01
Impulsive noise is an important challenge for the practical implementation of active noise control (ANC) systems. The advantages and disadvantages of popular filtered- X least mean square (FXLMS) ANC algorithm and nonlinear filtered-X least mean M-estimate (FXLMM) algorithm are discussed in this paper. A new modified FXLMM algorithm is also proposed to achieve better performance in controlling impulsive noise. Computer simulations and experiments are carried out for all three algorithms and the results are presented and analyzed. The results show that the FXLMM and modified FXLMM algorithms are more robust in suppressing the adverse effect of sudden large amplitude impulses than FXLMS algorithm, and in particular, the proposed modified FXLMM algorithm can achieve better stability without sacrificing the performance of residual noise when encountering impulses.
Formal verification of a deadlock detection algorithm
Directory of Open Access Journals (Sweden)
Freek Verbeek
2011-10-01
Full Text Available Deadlock detection is a challenging issue in the analysis and design of on-chip networks. We have designed an algorithm to detect deadlocks automatically in on-chip networks with wormhole switching. The algorithm has been specified and proven correct in ACL2. To enable a top-down proof methodology, some parts of the algorithm have been left unimplemented. For these parts, the ACL2 specification contains constrained functions introduced with defun-sk. We used single-threaded objects to represent the data structures used by the algorithm. In this paper, we present details on the proof of correctness of the algorithm. The process of formal verification was crucial to get the algorithm flawless. Our ultimate objective is to have an efficient executable, and formally proven correct implementation of the algorithm running in ACL2.
A Hybrid Chaotic Quantum Evolutionary Algorithm
DEFF Research Database (Denmark)
Cai, Y.; Zhang, M.; Cai, H.
2010-01-01
and enhance the global search ability. A large number of tests show that the proposed algorithm has higher convergence speed and better optimizing ability than quantum evolutionary algorithm, real-coded quantum evolutionary algorithm and hybrid quantum genetic algorithm. Tests also show that when chaos......A hybrid chaotic quantum evolutionary algorithm is proposed to reduce amount of computation, speed up convergence and restrain premature phenomena of quantum evolutionary algorithm. The proposed algorithm adopts the chaotic initialization method to generate initial population which will form...... a perfect distribution in feasible solution space in advantage of randomicity and non-repetitive ergodicity of chaos, the simple quantum rotation gate to update non-optimal individuals of population to reduce amount of computation, and the hybrid chaotic search strategy to speed up its convergence...
An Algorithm for Successive Identification of Reflections
DEFF Research Database (Denmark)
Hansen, Kim Vejlby; Larsen, Jan
1994-01-01
A new algorithm for successive identification of seismic reflections is proposed. Generally, the algorithm can be viewed as a curve matching method for images with specific structure. However, in the paper, the algorithm works on seismic signals assembled to constitute an image in which the inves......A new algorithm for successive identification of seismic reflections is proposed. Generally, the algorithm can be viewed as a curve matching method for images with specific structure. However, in the paper, the algorithm works on seismic signals assembled to constitute an image in which...... on a synthetic CMP gather, whereas the other is based on a real recorded CMP gather. Initially, the algorithm requires an estimate of the wavelet that can be performed by any wavelet estimation method.>...
FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS
Directory of Open Access Journals (Sweden)
Evans BAIDOO
2017-03-01
Full Text Available Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, this paper validates the effect of runtime on the algorithm performance.
Hardware Acceleration of Adaptive Neural Algorithms.
Energy Technology Data Exchange (ETDEWEB)
James, Conrad D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-11-01
As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - world conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.
The GRAPE aerosol retrieval algorithm
Directory of Open Access Journals (Sweden)
G. E. Thomas
2009-11-01
Full Text Available The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations – this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998, as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE data-set.
The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.
GPU accelerated population annealing algorithm
Barash, Lev Yu.; Weigel, Martin; Borovský, Michal; Janke, Wolfhard; Shchur, Lev N.
2017-11-01
Population annealing is a promising recent approach for Monte Carlo simulations in statistical physics, in particular for the simulation of systems with complex free-energy landscapes. It is a hybrid method, combining importance sampling through Markov chains with elements of sequential Monte Carlo in the form of population control. While it appears to provide algorithmic capabilities for the simulation of such systems that are roughly comparable to those of more established approaches such as parallel tempering, it is intrinsically much more suitable for massively parallel computing. Here, we tap into this structural advantage and present a highly optimized implementation of the population annealing algorithm on GPUs that promises speed-ups of several orders of magnitude as compared to a serial implementation on CPUs. While the sample code is for simulations of the 2D ferromagnetic Ising model, it should be easily adapted for simulations of other spin models, including disordered systems. Our code includes implementations of some advanced algorithmic features that have only recently been suggested, namely the automatic adaptation of temperature steps and a multi-histogram analysis of the data at different temperatures. Program Files doi:http://dx.doi.org/10.17632/sgzt4b7b3m.1 Licensing provisions: Creative Commons Attribution license (CC BY 4.0) Programming language: C, CUDA External routines/libraries: NVIDIA CUDA Toolkit 6.5 or newer Nature of problem: The program calculates the internal energy, specific heat, several magnetization moments, entropy and free energy of the 2D Ising model on square lattices of edge length L with periodic boundary conditions as a function of inverse temperature β. Solution method: The code uses population annealing, a hybrid method combining Markov chain updates with population control. The code is implemented for NVIDIA GPUs using the CUDA language and employs advanced techniques such as multi-spin coding, adaptive temperature
Firefly Mating Algorithm for Continuous Optimization Problems
Directory of Open Access Journals (Sweden)
Amarita Ritthipakdee
2017-01-01
Full Text Available This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA, for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i the mutual attraction between males and females causes them to mate and (ii fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima.
Improved Heat-Stress Algorithm
Teets, Edward H., Jr.; Fehn, Steven
2007-01-01
NASA Dryden presents an improved and automated site-specific algorithm for heat-stress approximation using standard atmospheric measurements routinely obtained from the Edwards Air Force Base weather detachment. Heat stress, which is the net heat load a worker may be exposed to, is officially measured using a thermal-environment monitoring system to calculate the wet-bulb globe temperature (WBGT). This instrument uses three independent thermometers to measure wet-bulb, dry-bulb, and the black-globe temperatures. By using these improvements, a more realistic WBGT estimation value can now be produced. This is extremely useful for researchers and other employees who are working on outdoor projects that are distant from the areas that the Web system monitors. Most importantly, the improved WBGT estimations will make outdoor work sites safer by reducing the likelihood of heat stress.
Scheduling theory, algorithms, and systems
Pinedo, Michael L
2016-01-01
This new edition of the well-established text Scheduling: Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as important scheduling problems that appear in the real world. The accompanying website includes supplementary material in the form of slide-shows from industry as well as movies that show actual implementations of scheduling systems. The main structure of the book, as per previous editions, consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped, streamlined, and extended. The reference...
Stochastic simulation algorithms and analysis
Asmussen, Soren
2007-01-01
Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value.
[A simple algorithm for anemia].
Egyed, Miklós
2014-03-09
The author presents a novel algorithm for anaemia based on the erythrocyte haemoglobin content. The scheme is based on the aberrations of erythropoiesis and not on the pathophysiology of anaemia. The hemoglobin content of one erytrocyte is between 28-35 picogram. Any disturbance in hemoglobin synthesis can lead to a lower than 28 picogram hemoglobin content of the erythrocyte which will lead to hypochromic anaemia. In contrary, disturbances of nucleic acid metabolism will result in a hemoglobin content greater than 36 picogram, and this will result in hyperchromic anaemia. Normochromic anemia, characterised by hemoglobin content of erythrocytes between 28 and 35 picogram, is the result of alteration in the proliferation of erythropoeisis. Based on these three categories of anaemia, a unique system can be constructed, which can be used as a model for basic laboratory investigations and work-up of anaemic patients.
Anaphora Resolution Algorithm for Sanskrit
Pralayankar, Pravin; Devi, Sobha Lalitha
This paper presents an algorithm, which identifies different types of pronominal and its antecedents in Sanskrit, an Indo-European language. The computational grammar implemented here uses very familiar concepts such as clause, subject, object etc., which are identified with the help of morphological information and concepts such as precede and follow. It is well known that natural languages contain anaphoric expressions, gaps and elliptical constructions of various kinds and that understanding of natural languages involves assignment of interpretations to these elements. Therefore, it is only to be expected that natural language understanding systems must have the necessary mechanism to resolve the same. The method we adopt here for resolving the anaphors is by exploiting the morphological richness of the language. The system is giving encouraging results when tested with a small corpus.
Hierarchical matrices algorithms and analysis
Hackbusch, Wolfgang
2015-01-01
This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...
Formal algorithmic elimination for PDEs
Robertz, Daniel
2014-01-01
Investigating the correspondence between systems of partial differential equations and their analytic solutions using a formal approach, this monograph presents algorithms to determine the set of analytic solutions of such a system and conversely to find differential equations whose set of solutions coincides with a given parametrized set of analytic functions. After giving a detailed introduction to Janet bases and Thomas decomposition, the problem of finding an implicit description of certain sets of analytic functions in terms of differential equations is addressed. Effective methods of varying generality are developed to solve the differential elimination problems that arise in this context. In particular, it is demonstrated how the symbolic solution of partial differential equations profits from the study of the implicitization problem. For instance, certain families of exact solutions of the Navier-Stokes equations can be computed.
DEVELOPMENT OF A NEW ALGORITHM FOR KEY AND S-BOX GENERATION IN BLOWFISH ALGORITHM
Directory of Open Access Journals (Sweden)
TAYSEER S. ATIA
2014-08-01
Full Text Available Blowfish algorithm is a block cipher algorithm, its strong, simple algorithm used to encrypt data in block of size 64-bit. Key and S-box generation process in this algorithm require time and memory space the reasons that make this algorithm not convenient to be used in smart card or application requires changing secret key frequently. In this paper a new key and S-box generation process was developed based on Self Synchronization Stream Cipher (SSS algorithm where the key generation process for this algorithm was modified to be used with the blowfish algorithm. Test result shows that the generation process requires relatively slow time and reasonably low memory requirement and this enhance the algorithm and gave it the possibility for different usage.
Genetic algorithms and fuzzy multiobjective optimization
Sakawa, Masatoshi
2002-01-01
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...
Principal component analysis networks and algorithms
Kong, Xiangyu; Duan, Zhansheng
2017-01-01
This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
Relative Pose Estimation Algorithm with Gyroscope Sensor
Directory of Open Access Journals (Sweden)
Shanshan Wei
2016-01-01
Full Text Available This paper proposes a novel vision and inertial fusion algorithm S2fM (Simplified Structure from Motion for camera relative pose estimation. Different from current existing algorithms, our algorithm estimates rotation parameter and translation parameter separately. S2fM employs gyroscopes to estimate camera rotation parameter, which is later fused with the image data to estimate camera translation parameter. Our contributions are in two aspects. (1 Under the circumstance that no inertial sensor can estimate accurately enough translation parameter, we propose a translation estimation algorithm by fusing gyroscope sensor and image data. (2 Our S2fM algorithm is efficient and suitable for smart devices. Experimental results validate efficiency of the proposed S2fM algorithm.
Modified BTC Algorithm for Audio Signal Coding
Directory of Open Access Journals (Sweden)
TOMIC, S.
2016-11-01
Full Text Available This paper describes modification of a well-known image coding algorithm, named Block Truncation Coding (BTC and its application in audio signal coding. BTC algorithm was originally designed for black and white image coding. Since black and white images and audio signals have different statistical characteristics, the application of this image coding algorithm to audio signal presents a novelty and a challenge. Several implementation modifications are described in this paper, while the original idea of the algorithm is preserved. The main modifications are performed in the area of signal quantization, by designing more adequate quantizers for audio signal processing. The result is a novel audio coding algorithm, whose performance is presented and analyzed in this research. The performance analysis indicates that this novel algorithm can be successfully applied in audio signal coding.
A new chaotic algorithm for image encryption
International Nuclear Information System (INIS)
Gao Haojiang; Zhang Yisheng; Liang Shuyun; Li Dequn
2006-01-01
Recent researches of image encryption algorithms have been increasingly based on chaotic systems, but the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper presents a new nonlinear chaotic algorithm (NCA) which uses power function and tangent function instead of linear function. Its structural parameters are obtained by experimental analysis. And an image encryption algorithm in a one-time-one-password system is designed. The experimental results demonstrate that the image encryption algorithm based on NCA shows advantages of large key space and high-level security, while maintaining acceptable efficiency. Compared with some general encryption algorithms such as DES, the encryption algorithm is more secure
An Improved Robot Path Planning Algorithm
Directory of Open Access Journals (Sweden)
Xuesong Yan
2012-12-01
Full Text Available Robot path planning is a NP problem; traditional optimization methods are not very effective to solve it.Traditional genetic algorithm trapped into the local minimum easily. Therefore, based on a simple genetic algorithm and combine the base ideology of orthogonal design method then applied it to the population initialization, using the intergenerational elite mechanism, as well as the introduction of adaptive local search operator to prevent trapped into the local minimum and improve the convergence speed to form a new genetic algorithm. Through the series of numerical experiments, the new algorithm has been proved to be efficiency. We also use the proposed algorithm to solve the robot path planning problem and the experiment results indicated that the new algorithm is efficiency for solving the robot path planning problems and the best path usually can be found.
The ethics of algorithms: Mapping the debate
Directory of Open Access Journals (Sweden)
Brent Daniel Mittelstadt
2016-11-01
Full Text Available In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.
Algorithms for worst-case tolerance optimization
DEFF Research Database (Denmark)
Schjær-Jacobsen, Hans; Madsen, Kaj
1979-01-01
New algorithms are presented for the solution of optimum tolerance assignment problems. The problems considered are defined mathematically as a worst-case problem (WCP), a fixed tolerance problem (FTP), and a variable tolerance problem (VTP). The basic optimization problem without tolerances...... is denoted the zero tolerance problem (ZTP). For solution of the WCP we suggest application of interval arithmetic and also alternative methods. For solution of the FTP an algorithm is suggested which is conceptually similar to algorithms previously developed by the authors for the ZTP. Finally, the VTP...... is solved by a double-iterative algorithm in which the inner iteration is performed by the FTP- algorithm. The application of the algorithm is demonstrated by means of relatively simple numerical examples. Basic properties, such as convergence properties, are displayed based on the examples....
Normalization based K means Clustering Algorithm
Virmani, Deepali; Taneja, Shweta; Malhotra, Geetika
2015-01-01
K-means is an effective clustering technique used to separate similar data into groups based on initial centroids of clusters. In this paper, Normalization based K-means clustering algorithm(N-K means) is proposed. Proposed N-K means clustering algorithm applies normalization prior to clustering on the available data as well as the proposed approach calculates initial centroids based on weights. Experimental results prove the betterment of proposed N-K means clustering algorithm over existing...
Particle detection algorithms for complex plasmas
Mohr, D. P.; Knapek, C. A.; Huber, P.; Zaehringer, E.
2018-01-01
The micrometer-sized particles in a complex plasma can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are required to accurately determine their positions to sub-pixel accuracy from the recorded images. Here, we combine the algorithms with common techniques for image processing, and we study several algorithms, pre- and post-processing methods, and the impact of the choice of threshold parameters.
Dynamic Programming Algorithms in Speech Recognition
Directory of Open Access Journals (Sweden)
Titus Felix FURTUNA
2008-01-01
Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.
Testing algorithms for critical slowing down
Directory of Open Access Journals (Sweden)
Cossu Guido
2018-01-01
Full Text Available We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among physical observables thus tackling the critical slowing down towards the continuum limit. We present a comparison of costs of the new algorithms with the standard HMC evolution for pure gauge fields, studying the autocorrelation times for various quantities including the topological charge.
The global Minmax k-means algorithm
Wang, Xiaoyan; Bai, Yanping
2016-01-01
The global k-means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k-means to minimize the sum of the intra-cluster variances. However the global k-means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k-means algorithm. In this pape...
Lyapunov Function Synthesis - Algorithm and Software
DEFF Research Database (Denmark)
Leth, Tobias; Sloth, Christoffer; Wisniewski, Rafal
2016-01-01
In this paper we introduce an algorithm for the synthesis of polynomial Lyapunov functions for polynomial vector fields. The Lyapunov function is a continuous piecewisepolynomial defined on simplices, which compose a collection of simplices. The algorithm is elaborated and crucial features...... are explained in detail. The strengths and weaknesses of the algorithm are exemplified and a new way of sub-dividing the simplices is presented....
Dynamic training algorithm for dynamic neural networks
International Nuclear Information System (INIS)
Tan, Y.; Van Cauwenberghe, A.; Liu, Z.
1996-01-01
The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper
A Modified Particle Swarm Optimization Algorithm
Jie He; Hui Guo
2013-01-01
In optimizing the particle swarm optimization (PSO) that inevitable existence problem of prematurity and the local convergence, this paper base on this aspects is put forward a kind of modified particle swarm optimization algorithm, take the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, and at the same time use to attenuation wall (Damping) approach to make fly off the search area of the particles of size remain unchanged and avoid t...
An Efficient Algorithm for Unconstrained Optimization
Directory of Open Access Journals (Sweden)
Sergio Gerardo de-los-Cobos-Silva
2015-01-01
Full Text Available This paper presents an original and efficient PSO algorithm, which is divided into three phases: (1 stabilization, (2 breadth-first search, and (3 depth-first search. The proposed algorithm, called PSO-3P, was tested with 47 benchmark continuous unconstrained optimization problems, on a total of 82 instances. The numerical results show that the proposed algorithm is able to reach the global optimum. This work mainly focuses on unconstrained optimization problems from 2 to 1,000 variables.
Information Dynamics in Networks: Models and Algorithms
2016-09-13
Information Dynamics in Networks: Models and Algorithms In this project, we investigated how network structure interplays with higher level processes in...Models and Algorithms Report Title In this project, we investigated how network structure interplays with higher level processes in online social...Received Paper 1.00 2.00 3.00 . A Note on Modeling Retweet Cascades on Twitter, Workshop on Algorithms and Models for the Web Graph. 09-DEC-15
Eigenvalue Decomposition-Based Modified Newton Algorithm
Directory of Open Access Journals (Sweden)
Wen-jun Wang
2013-01-01
Full Text Available When the Hessian matrix is not positive, the Newton direction may not be the descending direction. A new method named eigenvalue decomposition-based modified Newton algorithm is presented, which first takes the eigenvalue decomposition of the Hessian matrix, then replaces the negative eigenvalues with their absolute values, and finally reconstructs the Hessian matrix and modifies the searching direction. The new searching direction is always the descending direction. The convergence of the algorithm is proven and the conclusion on convergence rate is presented qualitatively. Finally, a numerical experiment is given for comparing the convergence domains of the modified algorithm and the classical algorithm.
Decoding Hermitian Codes with Sudan's Algorithm
DEFF Research Database (Denmark)
Høholdt, Tom; Nielsen, Rasmus Refslund
1999-01-01
We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q-polynomial, and a reduct......We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q...
Economic dispatch using chaotic bat algorithm
International Nuclear Information System (INIS)
Adarsh, B.R.; Raghunathan, T.; Jayabarathi, T.; Yang, Xin-She
2016-01-01
This paper presents the application of a new metaheuristic optimization algorithm, the chaotic bat algorithm for solving the economic dispatch problem involving a number of equality and inequality constraints such as power balance, prohibited operating zones and ramp rate limits. Transmission losses and multiple fuel options are also considered for some problems. The chaotic bat algorithm, a variant of the basic bat algorithm, is obtained by incorporating chaotic sequences to enhance its performance. Five different example problems comprising 6, 13, 20, 40 and 160 generating units are solved to demonstrate the effectiveness of the algorithm. The algorithm requires little tuning by the user, and the results obtained show that it either outperforms or compares favorably with several existing techniques reported in literature. - Highlights: • The chaotic bat algorithm, a new metaheuristic optimization algorithm has been used. • The problem solved – the economic dispatch problem – is nonlinear, discontinuous. • It has number of equality and inequality constraints. • The algorithm has been demonstrated to be applicable on high dimensional problems.
Highly Scalable Matching Pursuit Signal Decomposition Algorithm
National Aeronautics and Space Administration — In this research, we propose a variant of the classical Matching Pursuit Decomposition (MPD) algorithm with significantly improved scalability and computational...
Hardware modules of the RSA algorithm
Directory of Open Access Journals (Sweden)
Škobić Velibor
2014-01-01
Full Text Available This paper describes basic principles of data protection using the RSA algorithm, as well as algorithms for its calculation. The RSA algorithm is implemented on FPGA integrated circuit EP4CE115F29C7, family Cyclone IV, Altera. Four modules of Montgomery algorithm are designed using VHDL. Synthesis and simulation are done using Quartus II software and ModelSim. The modules are analyzed for different key lengths (16 to 1024 in terms of the number of logic elements, the maximum frequency and speed.
Quantum learning algorithms for quantum measurements
International Nuclear Information System (INIS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Sedlak, Michal
2011-01-01
We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples. The analysis of the case of three examples reveals that, differently from the learning of unitary gates, the optimal algorithm for learning of quantum measurements cannot be parallelized, and requires quantum memories for the storage of information. -- Highlights: → Optimal learning algorithm for von Neumann measurements. → From 2 copies to 1 copy: the optimal strategy is parallel. → From 3 copies to 1 copy: the optimal strategy must be non-parallel.
Nonlinear Gossip Algorithms for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Chao Shi
2014-01-01
Full Text Available We study some nonlinear gossip algorithms for wireless sensor networks. Firstly, two types of nonlinear single gossip algorithms are proposed. By using Lyapunov theory, Lagrange mean value theorem, and stochastic Lasalle’s invariance principle, we prove that the nonlinear single gossip algorithms can converge to the average of initial states with probability one. Secondly, two types of nonlinear multigossip algorithms are also presented and the convergence is proved by the same methods. Finally, computer simulation is also given to show the validity of the theoretical results.
Algorithms and Data Structures (lecture 1)
CERN. Geneva
2018-01-01
Algorithms have existed, in one form or another, for as long as humanity has. During the second half of the 20th century, the field was revolutionised with the introduction of ever faster computers. In these lectures we discuss how algorithms are designed, how to evaluate their speed, and how to identify areas of improvement in existing algorithms. An algorithm consists of more than just a series of instructions; almost as important is the memory structure of the data on which it operates. A part of the lectures will be dedicated to a discussion of the various ways one can store data in memory, and their advantages and disadvantages.
Algorithms and Data Structures (lecture 2)
CERN. Geneva
2018-01-01
Algorithms have existed, in one form or another, for as long as humanity has. During the second half of the 20th century, the field was revolutionised with the introduction of ever faster computers. In these lectures we discuss how algorithms are designed, how to evaluate their speed, and how to identify areas of improvement in existing algorithms. An algorithm consists of more than just a series of instructions; almost as important is the memory structure of the data on which it operates. A part of the lectures will be dedicated to a discussion of the various ways one can store data in memory, and their advantages and disadvantages.
Algorithms to solve the Sutherland model
Langmann, Edwin
2001-01-01
We give a self-contained presentation and comparison of two different algorithms to explicitly solve quantum many body models of indistinguishable particles moving on a circle and interacting with two-body potentials of $1/\\sin^2$-type. The first algorithm is due to Sutherland and well-known; the second one is a limiting case of a novel algorithm to solve the elliptic generalization of the Sutherland model. These two algorithms are different in several details. We show that they are equivalen...
The Top Ten Algorithms in Data Mining
Wu, Xindong
2009-01-01
From classification and clustering to statistical learning, association analysis, and link mining, this book covers the most important topics in data mining research. It presents the ten most influential algorithms used in the data mining community today. Each chapter provides a detailed description of the algorithm, a discussion of available software implementation, advanced topics, and exercises. With a simple data set, examples illustrate how each algorithm works and highlight the overall performance of each algorithm in a real-world application. Featuring contributions from leading researc
Control algorithms for dynamic attenuators
International Nuclear Information System (INIS)
Hsieh, Scott S.; Pelc, Norbert J.
2014-01-01
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity.
Jet observables without jet algorithms
Energy Technology Data Exchange (ETDEWEB)
Bertolini, Daniele; Chan, Tucker; Thaler, Jesse [Center for Theoretical Physics, Massachusetts Institute of Technology,Cambridge, MA 02139 (United States)
2014-04-02
We introduce a new class of event shapes to characterize the jet-like structure of an event. Like traditional event shapes, our observables are infrared/collinear safe and involve a sum over all hadrons in an event, but like a jet clustering algorithm, they incorporate a jet radius parameter and a transverse momentum cut. Three of the ubiquitous jet-based observables — jet multiplicity, summed scalar transverse momentum, and missing transverse momentum — have event shape counterparts that are closely correlated with their jet-based cousins. Due to their “local” computational structure, these jet-like event shapes could potentially be used for trigger-level event selection at the LHC. Intriguingly, the jet multiplicity event shape typically takes on non-integer values, highlighting the inherent ambiguity in defining jets. By inverting jet multiplicity, we show how to characterize the transverse momentum of the n-th hardest jet without actually finding the constituents of that jet. Since many physics applications do require knowledge about the jet constituents, we also build a hybrid event shape that incorporates (local) jet clustering information. As a straightforward application of our general technique, we derive an event-shape version of jet trimming, allowing event-wide jet grooming without explicit jet identification. Finally, we briefly mention possible applications of our method for jet substructure studies.
The algorithmic origins of life.
Walker, Sara Imari; Davies, Paul C W
2013-02-01
Although it has been notoriously difficult to pin down precisely what is it that makes life so distinctive and remarkable, there is general agreement that its informational aspect is one key property, perhaps the key property. The unique informational narrative of living systems suggests that life may be characterized by context-dependent causal influences, and, in particular, that top-down (or downward) causation-where higher levels influence and constrain the dynamics of lower levels in organizational hierarchies-may be a major contributor to the hierarchal structure of living systems. Here, we propose that the emergence of life may correspond to a physical transition associated with a shift in the causal structure, where information gains direct and context-dependent causal efficacy over the matter in which it is instantiated. Such a transition may be akin to more traditional physical transitions (e.g. thermodynamic phase transitions), with the crucial distinction that determining which phase (non-life or life) a given system is in requires dynamical information and therefore can only be inferred by identifying causal architecture. We discuss some novel research directions based on this hypothesis, including potential measures of such a transition that may be amenable to laboratory study, and how the proposed mechanism corresponds to the onset of the unique mode of (algorithmic) information processing characteristic of living systems.
Petascale algorithms for reactor hydrodynamics
International Nuclear Information System (INIS)
Fischer, P.; Lottes, J.; Pointer, W.D.; Siegel, A.
2008-01-01
We describe recent algorithmic developments that have enabled large eddy simulations of reactor flows on up to P = 65, 000 processors on the IBM BG/P at the Argonne Leadership Computing Facility. Petascale computing is expected to play a pivotal role in the design and analysis of next-generation nuclear reactors. Argonne's SHARP project is focused on advanced reactor simulation, with a current emphasis on modeling coupled neutronics and thermal-hydraulics (TH). The TH modeling comprises a hierarchy of computational fluid dynamics approaches ranging from detailed turbulence computations, using DNS (direct numerical simulation) and LES (large eddy simulation), to full core analysis based on RANS (Reynolds-averaged Navier-Stokes) and subchannel models. Our initial study is focused on LES of sodium-cooled fast reactor cores. The aim is to leverage petascale platforms at DOE's Leadership Computing Facilities (LCFs) to provide detailed information about heat transfer within the core and to provide baseline data for less expensive RANS and subchannel models.
Evolutionary Algorithms for Boolean Queries Optimization
Czech Academy of Sciences Publication Activity Database
Húsek, Dušan; Snášel, Václav; Neruda, Roman; Owais, S.S.J.; Krömer, P.
2006-01-01
Roč. 3, č. 1 (2006), s. 15-20 ISSN 1790-0832 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * information retrieval * Boolean query Subject RIV: BA - General Mathematics
Algorithms for boundary detection in radiographic images
International Nuclear Information System (INIS)
Gonzaga, Adilson; Franca, Celso Aparecido de
1996-01-01
Edge detecting techniques applied to radiographic digital images are discussed. Some algorithms have been implemented and the results are displayed to enhance boundary or hide details. An algorithm applied in a pre processed image with contrast enhanced is proposed and the results are discussed
Boolean Queries Optimization by Genetic Algorithms
Czech Academy of Sciences Publication Activity Database
Húsek, Dušan; Owais, S.S.J.; Krömer, P.; Snášel, Václav
2005-01-01
Roč. 15, - (2005), s. 395-409 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * genetic programming * information retrieval * Boolean query Subject RIV: BB - Applied Statistics, Operational Research
Novel quantum inspired binary neural network algorithm
Indian Academy of Sciences (India)
In this paper, a quantum based binary neural network algorithm is proposed, named as novel quantum binary neural network algorithm (NQ-BNN). It forms a neural network structure by deciding weights and separability parameter in quantum based manner. Quantum computing concept represents solution probabilistically ...
Algorithmic Mechanism Design of Evolutionary Computation.
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.
Fast mutual exclusion by the Triangle algorithm
Hesselink, Willem; Buhr, Peter; Dice, David
2018-01-01
This paper presents a new starvation-free software algorithm for the N-thread mutual-exclusion problem. In the absence of contention, the algorithm requires only eight write operations and four read operations to enter and leave the critical section; to the best of our knowledge, this is optimal.
A quick survey of text categorization algorithms
Directory of Open Access Journals (Sweden)
Dan MUNTEANU
2007-12-01
Full Text Available This paper contains an overview of basic formulations and approaches to text classification. This paper surveys the algorithms used in text categorization: handcrafted rules, decision trees, decision rules, on-line learning, linear classifier, Rocchio’s algorithm, k Nearest Neighbor (kNN, Support Vector Machines (SVM.
A new algorithm for generalized fractional programs
J.B.G. Frenk (Hans); A.I. Barros (Ana); S. Schaible; S. Zhang (Shuzhong)
1996-01-01
textabstractA new dual problem for convex generalized fractional programs with no duality gap is presented and it is shown how this dual problem can be efficiently solved using a parametric approach. The resulting algorithm can be seen as “dual” to the Dinkelbach-type algorithm for generalized
Genetic Algorithms For the Linear Ordering Problem
Czech Academy of Sciences Publication Activity Database
Krömer, P.; Snášel, V.; Platoš, J.; Húsek, Dušan
2009-01-01
Roč. 19, č. 1 (2009), s. 65-80 ISSN 1210-0552 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithm s * genetic algorithm s * linear ordering problem * combinatorial optimization Subject RIV: IN - Informatics, Computer Science Impact factor: 0.475, year: 2009
Conditionally-uniform Feasible Grid Search Algorithm
DEFF Research Database (Denmark)
Dziubinski, Matt P.
We present and evaluate a numerical optimization method (together with an algorithm for choosing the starting values) pertinent to the constrained optimization problem arising in the estimation of the GARCH models with inequality constraints, in particular the Simplied Component GARCH Model (SCGA...... (SCGARCH), together with algorithms for the objective function and analytical gradient computation for SCGARCH....
Model order reduction using eigen algorithm
African Journals Online (AJOL)
DR OKE
to use either for design or analysis. Hence, it is ... directly from the Eigen algorithm while the zeros are determined through factor division algorithm to obtain the reduced order system. ..... V. Singh, Chandra and H. Kar, “Improved Routh Pade approximationss: A computer aided approach”, IEEE Transaction on. Automat ...
Perturbation resilience and superiorization of iterative algorithms
International Nuclear Information System (INIS)
Censor, Y; Davidi, R; Herman, G T
2010-01-01
Iterative algorithms aimed at solving some problems are discussed. For certain problems, such as finding a common point in the intersection of a finite number of convex sets, there often exist iterative algorithms that impose very little demand on computer resources. For other problems, such as finding that point in the intersection at which the value of a given function is optimal, algorithms tend to need more computer memory and longer execution time. A methodology is presented whose aim is to produce automatically for an iterative algorithm of the first kind a 'superiorized version' of it that retains its computational efficiency but nevertheless goes a long way toward solving an optimization problem. This is possible to do if the original algorithm is 'perturbation resilient', which is shown to be the case for various projection algorithms for solving the consistent convex feasibility problem. The superiorized versions of such algorithms use perturbations that steer the process in the direction of a superior feasible point, which is not necessarily optimal, with respect to the given function. After presenting these intuitive ideas in a precise mathematical form, they are illustrated in image reconstruction from projections for two different projection algorithms superiorized for the function whose value is the total variation of the image
The history of the LLL-algorithm
Smeets, I.; Lenstra, A.; Lenstra, H.; Lovász, L.; van Emde Boas, P.
2010-01-01
The 25th birthday of the LLL-algorithm was celebrated in Caen from 29th June to 1st July 2007. The three day conference kicked off with a historical session of four talks about the origins of the algorithm. The speakers were the three L’s and close bystander Peter van Emde Boas. These were the
Mechanical verification of Lamport's Bakery algorithm
Hesselink, Wim H.
2013-01-01
Proof assistants like PVS can be used fruitfully for the design and verification of concurrent algorithms. The technique is presented here by applying it to Lamport's Bakery algorithm. The proofs for safety properties such as mutual exclusion, first-come first-served, and absence of deadlock are
An efficient algorithm for weighted PCA
Krijnen, W.P.; Kiers, H.A.L.
1995-01-01
The method for analyzing three-way data where one of the three components matrices in TUCKALS3 is chosen to have one column is called Replicated PCA. The corresponding algorithm is relatively inefficient. This is shown by offering an alternative algorithm called Weighted PCA. Specifically it is
QPSO-Based Adaptive DNA Computing Algorithm
Directory of Open Access Journals (Sweden)
Mehmet Karakose
2013-01-01
Full Text Available DNA (deoxyribonucleic acid computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO. Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1 parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2 adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3 numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm.
Modeling and Engineering Algorithms for Mobile Data
DEFF Research Database (Denmark)
Blunck, Henrik; Hinrichs, Klaus; Sondern, Joëlle
2006-01-01
In this paper, we present an object-oriented approach to modeling mobile data and algorithms operating on such data. Our model is general enough to capture any kind of continuous motion while at the same time allowing for encompassing algorithms optimized for specific types of motion. Such motion...
Exact algorithms for the Steiner tree problem
Wang, Xinhui
2008-01-01
The Steiner tree problem is one of the original 21 NP complete problems, which has wide application in theorey and industry. There are no polynomial time algorithms for it, and exact (acceptable exponential time) algorithms are the best we can obtain for pursuing the exact solution for the all these
Optimal Power Flow Using the Jaya Algorithm
Directory of Open Access Journals (Sweden)
Warid Warid
2016-08-01
Full Text Available This paper presents application of a new effective metaheuristic optimization method namely, the Jaya algorithm to deal with different optimum power flow (OPF problems. Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. In this work, three goal functions are considered for the OPF solution: generation cost minimization, real power loss reduction, and voltage stability improvement. In addition, the effect of distributed generation (DG is incorporated into the OPF problem using a modified formulation. For best allocation of DG unit(s, a sensitivity-based procedure is introduced. Simulations are carried out on the modified IEEE 30-bus and IEEE 118-bus networks to determine the effectiveness of the Jaya algorithm. The single objective optimization cases are performed both with and without DG. For all considered cases, results demonstrate that Jaya algorithm can produce an optimum solution with rapid convergence. Statistical analysis is also carried out to check the reliability of the Jaya algorithm. The optimal solution obtained by the Jaya algorithm is compared with different stochastic algorithms, and demonstrably outperforms them in terms of solution optimality and solution feasibility, proving its effectiveness and potential. Notably, optimal placement of DGs results in even better solutions.
The Light Scattering and Fast Mie Algorithm
Gliwa, Pawel
2001-01-01
The main topics of this paper is to shown a Fast Mie Algorithm FMA as the best way to use the Mie scattering theory for cross section calculation. This fast algorithm used recursion for summing a long timed sum of cylindrical functions.
Novel algorithm for management of acute epididymitis.
Hongo, Hiroshi; Kikuchi, Eiji; Matsumoto, Kazuhiro; Yazawa, Satoshi; Kanao, Kent; Kosaka, Takeo; Mizuno, Ryuichi; Miyajima, Akira; Saito, Shiro; Oya, Mototsugu
2017-01-01
To identify predictive factors for the severity of epididymitis and to develop an algorithm guiding decisions on how to manage patients with this disease. A retrospective study was carried out on 160 epididymitis patients at Keio University Hospital. We classified cases into severe and non-severe groups, and compared clinical findings at the first visit. Based on statistical analyses, we developed an algorithm for predicting severe cases. We validated the algorithm by applying it to an external cohort of 96 patients at Tokyo Medical Center. The efficacy of the algorithm was investigated by a decision curve analysis. A total of 19 patients (11.9%) had severe epididymitis. Patient characteristics including older age, previous history of diabetes mellitus and fever, as well as laboratory data including a higher white blood cell count, C-reactive protein level and blood urea nitrogen level were independently associated with severity. A predictive algorithm was created with the ability to classify epididymitis cases into three risk groups. In the Keio University Hospital cohort, 100%, 23.5%, and 3.4% of cases in the high-, intermediate-, and low-risk groups, respectively, became severe. The specificity of the algorithm for predicting severe epididymitis proved to be 100% in the Keio University Hospital cohort and 98.8% in the Tokyo Medical Center cohort. The decision curve analysis also showed the high efficacy of the algorithm. This algorithm might aid in decision-making for the clinical management of acute epididymitis. © 2016 The Japanese Urological Association.
New algorithm for extreme temperature measurements
Damean, N.
2000-01-01
A new algorithm for measurement of extreme temperature is presented. This algorithm reduces the measurement of the unknown temperature to the solving of an optimal control problem, using a numerical computer. Based on this method, a new device for extreme temperature measurements is projected. It
Supervised learning algorithms for visual object categorization
bin Abdullah, A.
2010-01-01
This thesis presents novel techniques for image recognition systems for better understanding image content. More specifically, it looks at the algorithmic aspects and experimental verification to demonstrate the capability of the proposed algorithms. These techniques aim to improve the three major
Analysis and Improvement of Fireworks Algorithm
Directory of Open Access Journals (Sweden)
Xi-Guang Li
2017-02-01
Full Text Available The Fireworks Algorithm is a recently developed swarm intelligence algorithm to simulate the explosion process of fireworks. Based on the analysis of each operator of Fireworks Algorithm (FWA, this paper improves the FWA and proves that the improved algorithm converges to the global optimal solution with probability 1. The proposed algorithm improves the goal of further boosting performance and achieving global optimization where mainly include the following strategies. Firstly using the opposition-based learning initialization population. Secondly a new explosion amplitude mechanism for the optimal firework is proposed. In addition, the adaptive t-distribution mutation for non-optimal individuals and elite opposition-based learning for the optimal individual are used. Finally, a new selection strategy, namely Disruptive Selection, is proposed to reduce the running time of the algorithm compared with FWA. In our simulation, we apply the CEC2013 standard functions and compare the proposed algorithm (IFWA with SPSO2011, FWA, EFWA and dynFWA. The results show that the proposed algorithm has better overall performance on the test functions.
6. Algorithms for Sorting and Searching
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. Algorithms - Algorithms for Sorting and Searching. R K Shyamasundar. Series Article ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...
Termination Criteria in Evolutionary Algorithms: A Survey
DEFF Research Database (Denmark)
Ghoreishi, Newsha; Clausen, Anders; Jørgensen, Bo Nørregaard
2017-01-01
Over the last decades, evolutionary algorithms have been extensively used to solve multi-objective optimization problems. However, the number of required function evaluations is not determined by nature of these algorithms which is often seen as a drawback. Therefore, a robust and reliable...
Experiments with parallel algorithms for combinatorial problems
G.A.P. Kindervater (Gerard); H.W.J.M. Trienekens
1985-01-01
textabstractIn the last decade many models for parallel computation have been proposed and many parallel algorithms have been developed. However, few of these models have been realized and most of these algorithms are supposed to run on idealized, unrealistic parallel machines. The parallel machines
Parallelization of TMVA Machine Learning Algorithms
Hajili, Mammad
2017-01-01
This report reflects my work on Parallelization of TMVA Machine Learning Algorithms integrated to ROOT Data Analysis Framework during summer internship at CERN. The report consists of 4 impor- tant part - data set used in training and validation, algorithms that multiprocessing applied on them, parallelization techniques and re- sults of execution time changes due to number of workers.
The Porter Stemming Algorithm: Then and Now
Willett, Peter
2006-01-01
Purpose: In 1980, Porter presented a simple algorithm for stemming English language words. This paper summarises the main features of the algorithm, and highlights its role not just in modern information retrieval research, but also in a range of related subject domains. Design/methodology/approach: Review of literature and research involving use…
Local simulation algorithms for Coulombic interactions
Indian Academy of Sciences (India)
At the moment of annihilation the total weight of the generated path or cluster is compared with its time reversed version and the update is either globally accepted or refused [10]. The algorithm is very reminiscent of the creation of virtual pairs of particles in quantum mechanics. In the original version of the algorithm [10] the.
A Clustal Alignment Improver Using Evolutionary Algorithms
DEFF Research Database (Denmark)
Thomsen, Rene; Fogel, Gary B.; Krink, Thimo
2002-01-01
Multiple sequence alignment (MSA) is a crucial task in bioinformatics. In this paper we extended previous work with evolutionary algorithms (EA) by using MSA solutions obtained from the wellknown Clustal V algorithm as a candidate solution seed of the initial EA population. Our results clearly sh...
A highly parallel algorithm for track finding
International Nuclear Information System (INIS)
Dell'Orso, M.
1990-01-01
We describe a very fast algorithm for track finding, which is applicable to a whole class of detectors like drift chambers, silicon microstrip detectors, etc. The algorithm uses a pattern bank stored in a large memory and organized into a tree structure. (orig.)
A Decomposition Algorithm for Parametric Design
Jauregui Becker, Juan Manuel; Schotborgh, W.O.; van Houten, Frederikus J.A.M.; Culley, T.C.; Hicks, B.J.; McAloone, T.C.; Howard, T.J.; Dong, A.
2011-01-01
This paper presents a recursive division algorithm to decompose an under constraint parametric design problem. The algorithm defines the separation of the problem at the hand of two complexity measures that are calculated for each parameter in the problem, namely, the effort E and the influence Inf.
A highly parallel algorithm for track finding
International Nuclear Information System (INIS)
Dell'Orso, M.
1988-01-01
We describe a very fast algorithm for track finding, which is applicable to a whole class of detectors like drift chambers, silicon microstrip detectors etc. The algorithm uses a pattern bank stored in a large memory and organized into a tree structure. (author). 1 ref., 5 figs
Approximation algorithms for guarding holey polygons ...
African Journals Online (AJOL)
Guarding edges of polygons is a version of art gallery problem.The goal is finding the minimum number of guards to cover the edges of a polygon. This problem is NP-hard, and to our knowledge there are approximation algorithms just for simple polygons. In this paper we present two approximation algorithms for guarding ...
Smoothed Analysis of Local Search Algorithms
Manthey, Bodo; Dehne, Frank; Sack, Jörg-Rüdiger; Stege, Ulrike
2015-01-01
Smoothed analysis is a method for analyzing the performance of algorithms for which classical worst-case analysis fails to explain the performance observed in practice. Smoothed analysis has been applied to explain the performance of a variety of algorithms in the last years. One particular class of
A New Algorithm for the Subtraction Games
He, Guanglei; Qin, Zhihui
2012-01-01
Subtraction games is a class of combinatorial games. It was solved since the Sprague-Grundy Theory was put forward. This paper described a new algorithm for subtraction games. The new algorithm can find win or lost positions in subtraction games. In addition, it is much simpler than Sprague-Grundy Theory in one pile of the games.
Parallelization of game theoretic centrality algorithms
Indian Academy of Sciences (India)
of a class of node centrality algorithms based on cooperative game theory. These were proposed earlier as an efficient alternatives to traditional measure of information diffusion centrality. We present here distributed versions of these algorithms in a Map-. Reduce framework, currently the most popular distributed computing ...
Top Tagging by Deep Learning Algorithm
Akil, Ali
2015-01-01
In this report I will show the application of a deep learning algorithm on a Monte Carlo simulation sample to test its performance in tagging hadronic decays of boosted top quarks and compare what we get with the results of the application of some other algorithms.
A novel algorithm for Bluetooth ECG.
Pandya, Utpal T; Desai, Uday B
2012-11-01
In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.
A Parametric k-Means Algorithm
Tarpey, Thaddeus
2007-01-01
Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692
Bit Loading Algorithms for Cooperative OFDM Systems
Directory of Open Access Journals (Sweden)
Gui Bo
2008-01-01
Full Text Available Abstract We investigate the resource allocation problem for an OFDM cooperative network with a single source-destination pair and multiple relays. Assuming knowledge of the instantaneous channel gains for all links in the entire network, we propose several bit and power allocation schemes aiming at minimizing the total transmission power under a target rate constraint. First, an optimal and efficient bit loading algorithm is proposed when the relay node uses the same subchannel to relay the information transmitted by the source node. To further improve the performance gain, subchannel permutation, in which the subchannels are reallocated at relay nodes, is considered. An optimal subchannel permutation algorithm is first proposed and then an efficient suboptimal algorithm is considered to achieve a better complexity-performance tradeoff. A distributed bit loading algorithm is also proposed for ad hoc networks. Simulation results show that significant performance gains can be achieved by the proposed bit loading algorithms, especially when subchannel permutation is employed.
A sampling algorithm for segregation analysis
Directory of Open Access Journals (Sweden)
Henshall John
2001-11-01
Full Text Available Abstract Methods for detecting Quantitative Trait Loci (QTL without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated.
Evolutionary algorithms for mobile ad hoc networks
Dorronsoro, Bernabé; Danoy, Grégoire; Pigné, Yoann; Bouvry, Pascal
2014-01-01
Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking. Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms topology management, and mobility models to address challenges in the ...
Algorithms for Graph Rigidity and Scene Analysis
DEFF Research Database (Denmark)
Berg, Alex Rune; Jordán, Tibor
2003-01-01
We investigate algorithmic questions and structural problems concerning graph families defined by `edge-counts'. Motivated by recent developments in the unique realization problem of graphs, we give an efficient algorithm to compute the rigid, redundantly rigid, M-connected, and globally rigid...... components of a graph. Our algorithm is based on (and also extends and simplifies) the idea of Hendrickson and Jacobs, as it uses orientations as the main algorithmic tool. We also consider families of bipartite graphs which occur in parallel drawings and scene analysis. We verify a conjecture of Whiteley...... by showing that 2d-connected bipartite graphs are d-tight. We give a new algorithm for finding a maximal d-sharp subgraph. We also answer a question of Imai and show that finding a maximum size d-sharp subgraph is NP-hard....
Adaptive Filtering Algorithms and Practical Implementation
Diniz, Paulo S R
2013-01-01
In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation. The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes: Analytical and simulation examples in Chapters 4, 5, 6 and 10 Appendix E, which summarizes the analysis of set-membership algorithm Updated problems and references Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Several problems are...
Adiabatic quantum search algorithm for structured problems
International Nuclear Information System (INIS)
Roland, Jeremie; Cerf, Nicolas J.
2003-01-01
The study of quantum computation has been motivated by the hope of finding efficient quantum algorithms for solving classically hard problems. In this context, quantum algorithms by local adiabatic evolution have been shown to solve an unstructured search problem with a quadratic speedup over a classical search, just as Grover's algorithm. In this paper, we study how the structure of the search problem may be exploited to further improve the efficiency of these quantum adiabatic algorithms. We show that by nesting a partial search over a reduced set of variables into a global search, it is possible to devise quantum adiabatic algorithms with a complexity that, although still exponential, grows with a reduced order in the problem size
Gems of combinatorial optimization and graph algorithms
Skutella, Martin; Stiller, Sebastian; Wagner, Dorothea
2015-01-01
Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory? Maybe you need a convenient source of relevant, current topics for a graduate student or advanced undergraduate student seminar? Or perhaps you just want an enjoyable look at some beautiful mathematical and algorithmic results, ideas, proofs, concepts, and techniques in discrete mathematics and theoretical computer science? Gems of Combinatorial Optimization and Graph Algorithms is a handpicked collection of up-to-date articles, carefully prepared by a select group of international experts, who have contributed some of their most mathematically or algorithmically elegant ideas. Topics include longest tours and Steiner trees in geometric spaces, cartograms, resource buying games, congestion games, selfish routing, revenue equivalence and shortest paths, scheduling, linear structures in graphs, contraction hierarchies, budgeted matching problems, and motifs in networks. This ...
Quantum algorithms for testing Boolean functions
Directory of Open Access Journals (Sweden)
Erika Andersson
2010-06-01
Full Text Available We discuss quantum algorithms, based on the Bernstein-Vazirani algorithm, for finding which variables a Boolean function depends on. There are 2^n possible linear Boolean functions of n variables; given a linear Boolean function, the Bernstein-Vazirani quantum algorithm can deterministically identify which one of these Boolean functions we are given using just one single function query. The same quantum algorithm can also be used to learn which input variables other types of Boolean functions depend on, with a success probability that depends on the form of the Boolean function that is tested, but does not depend on the total number of input variables. We also outline a procedure to futher amplify the success probability, based on another quantum algorithm, the Grover search.
MM Algorithms for Geometric and Signomial Programming.
Lange, Kenneth; Zhou, Hua
2014-02-01
This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.
A Direct Search Algorithm for Global Optimization
Directory of Open Access Journals (Sweden)
Enrique Baeyens
2016-06-01
Full Text Available A direct search algorithm is proposed for minimizing an arbitrary real valued function. The algorithm uses a new function transformation and three simplex-based operations. The function transformation provides global exploration features, while the simplex-based operations guarantees the termination of the algorithm and provides global convergence to a stationary point if the cost function is differentiable and its gradient is Lipschitz continuous. The algorithm’s performance has been extensively tested using benchmark functions and compared to some well-known global optimization algorithms. The results of the computational study show that the algorithm combines both simplicity and efficiency and is competitive with the heuristics-based strategies presently used for global optimization.
A Learning Algorithm for Multimodal Grammar Inference.
D'Ulizia, A; Ferri, F; Grifoni, P
2011-12-01
The high costs of development and maintenance of multimodal grammars in integrating and understanding input in multimodal interfaces lead to the investigation of novel algorithmic solutions in automating grammar generation and in updating processes. Many algorithms for context-free grammar inference have been developed in the natural language processing literature. An extension of these algorithms toward the inference of multimodal grammars is necessary for multimodal input processing. In this paper, we propose a novel grammar inference mechanism that allows us to learn a multimodal grammar from its positive samples of multimodal sentences. The algorithm first generates the multimodal grammar that is able to parse the positive samples of sentences and, afterward, makes use of two learning operators and the minimum description length metrics in improving the grammar description and in avoiding the over-generalization problem. The experimental results highlight the acceptable performances of the algorithm proposed in this paper since it has a very high probability of parsing valid sentences.
Particle swarm genetic algorithm and its application
International Nuclear Information System (INIS)
Liu Chengxiang; Yan Changxiang; Wang Jianjun; Liu Zhenhai
2012-01-01
To solve the problems of slow convergence speed and tendency to fall into the local optimum of the standard particle swarm optimization while dealing with nonlinear constraint optimization problem, a particle swarm genetic algorithm is designed. The proposed algorithm adopts feasibility principle handles constraint conditions and avoids the difficulty of penalty function method in selecting punishment factor, generates initial feasible group randomly, which accelerates particle swarm convergence speed, and introduces genetic algorithm crossover and mutation strategy to avoid particle swarm falls into the local optimum Through the optimization calculation of the typical test functions, the results show that particle swarm genetic algorithm has better optimized performance. The algorithm is applied in nuclear power plant optimization, and the optimization results are significantly. (authors)
Learning theory of distributed spectral algorithms
Guo, Zheng-Chu; Lin, Shao-Bo; Zhou, Ding-Xuan
2017-07-01
Spectral algorithms have been widely used and studied in learning theory and inverse problems. This paper is concerned with distributed spectral algorithms, for handling big data, based on a divide-and-conquer approach. We present a learning theory for these distributed kernel-based learning algorithms in a regression framework including nice error bounds and optimal minimax learning rates achieved by means of a novel integral operator approach and a second order decomposition of inverse operators. Our quantitative estimates are given in terms of regularity of the regression function, effective dimension of the reproducing kernel Hilbert space, and qualification of the filter function of the spectral algorithm. They do not need any eigenfunction or noise conditions and are better than the existing results even for the classical family of spectral algorithms.
Transmission dose estimation algorithm for tissue deficit
International Nuclear Information System (INIS)
Yun, Hyong Geun; Shin, Kyo Chul; Chie, Eui Kyu; Huh, Soon Nyung; Woo, Hong Gyun; Ha, Sung Whan; Lee, Hyoung Koo
2002-01-01
Measurement of transmission dose is useful for in vivo dosimetry. In this study, previous algorithm for estimation of transmission dose was modified for use in cases with tissue deficit. The beam data was measured with flat solid phantom in various conditions of tissue deficit. New algorithm for correction of transmission dose for tissue deficit was developed by physical reasoning. The algorithm was tested in experimental settings with irregular contours mimicking breast cancer patients using multiple sheets of solid phantoms. The correction algorithm for tissue deficit could accurately reflect the effect of tissue deficit with errors within ± 1.0% in most situations and within ± 3.0% in experimental settings with irregular contours mimicking breast cancer treatment set-up. Developed algorithm could accurately reflect the effect of tissue deficit and irregularly shaped body contour on transmission dosimetry
Learning theory of distributed spectral algorithms
International Nuclear Information System (INIS)
Guo, Zheng-Chu; Lin, Shao-Bo; Zhou, Ding-Xuan
2017-01-01
Spectral algorithms have been widely used and studied in learning theory and inverse problems. This paper is concerned with distributed spectral algorithms, for handling big data, based on a divide-and-conquer approach. We present a learning theory for these distributed kernel-based learning algorithms in a regression framework including nice error bounds and optimal minimax learning rates achieved by means of a novel integral operator approach and a second order decomposition of inverse operators. Our quantitative estimates are given in terms of regularity of the regression function, effective dimension of the reproducing kernel Hilbert space, and qualification of the filter function of the spectral algorithm. They do not need any eigenfunction or noise conditions and are better than the existing results even for the classical family of spectral algorithms. (paper)
Recent Advancements in Lightning Jump Algorithm Work
Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.
2010-01-01
In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).
Localization Algorithms of Underwater Wireless Sensor Networks: A Survey
Han, Guangjie; Jiang, Jinfang; Shu, Lei; Xu, Yongjun; Wang, Feng
2012-01-01
In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs. PMID:22438752
Energy Technology Data Exchange (ETDEWEB)
Enghauser, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-02-01
The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.
Energy Technology Data Exchange (ETDEWEB)
Enghauser, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-02-01
The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.
Super-Encryption Implementation Using Monoalphabetic Algorithm and XOR Algorithm for Data Security
Rachmawati, Dian; Andri Budiman, Mohammad; Aulia, Indra
2018-03-01
The exchange of data that occurs offline and online is very vulnerable to the threat of data theft. In general, cryptography is a science and art to maintain data secrecy. An encryption is a cryptography algorithm in which data is transformed into cipher text, which is something that is unreadable and meaningless so it cannot be read or understood by other parties. In super-encryption, two or more encryption algorithms are combined to make it more secure. In this work, Monoalphabetic algorithm and XOR algorithm are combined to form a super- encryption. Monoalphabetic algorithm works by changing a particular letter into a new letter based on existing keywords while the XOR algorithm works by using logic operation XOR Since Monoalphabetic algorithm is a classical cryptographic algorithm and XOR algorithm is a modern cryptographic algorithm, this scheme is expected to be both easy-to-implement and more secure. The combination of the two algorithms is capable of securing the data and restoring it back to its original form (plaintext), so the data integrity is still ensured.
Nghia, Nguyen Duc; Binh, Huynh Thi Thanh
2008-01-01
We have introduced the heuristic algorithm for solving BDMST problem, called CBRC. The experiment shows that CBRC have best result than the other known heuristic algorithm for solving BDMST prolem on Euclidean instances. The best solution found by the genetic algorithm which uses best heuristic algorithm or only one heuristic algorithm for initialization the population is not better than the best solution found by the genetic algorithm which uses mixed heuristic algorithms (randomized heurist...
International Nuclear Information System (INIS)
Okumura, Hisashi
2010-01-01
I review two new generalized-ensemble algorithms for molecular dynamics and Monte Carlo simulations of biomolecules, that is, the multibaric–multithermal algorithm and the partial multicanonical algorithm. In the multibaric–multithermal algorithm, two-dimensional random walks not only in the potential-energy space but also in the volume space are realized. One can discuss the temperature dependence and pressure dependence of biomolecules with this algorithm. The partial multicanonical simulation samples a wide range of only an important part of potential energy, so that one can concentrate the effort to determine a multicanonical weight factor only on the important energy terms. This algorithm has higher sampling efficiency than the multicanonical and canonical algorithms. (review)
A novel hybrid algorithm of GSA with Kepler algorithm for numerical optimization
Directory of Open Access Journals (Sweden)
Soroor Sarafrazi
2015-07-01
Full Text Available It is now well recognized that pure algorithms can be promisingly improved by hybridization with other techniques. One of the relatively new metaheuristic algorithms is Gravitational Search Algorithm (GSA which is based on the Newton laws. In this paper, to enhance the performance of GSA, a novel algorithm called “Kepler”, inspired by the astrophysics, is introduced. The Kepler algorithm is based on the principle of the first Kepler law. The hybridization of GSA and Kepler algorithm is an efficient approach to provide much stronger specialization in intensification and/or diversification. The performance of GSA–Kepler is evaluated by applying it to 14 benchmark functions with 20–1000 dimensions and the optimal approximation of linear system as a practical optimization problem. The results obtained reveal that the proposed hybrid algorithm is robust enough to optimize the benchmark functions and practical optimization problems.
Novel and efficient tag SNPs selection algorithms.
Chen, Wen-Pei; Hung, Che-Lun; Tsai, Suh-Jen Jane; Lin, Yaw-Ling
2014-01-01
SNPs are the most abundant forms of genetic variations amongst species; the association studies between complex diseases and SNPs or haplotypes have received great attention. However, these studies are restricted by the cost of genotyping all SNPs; thus, it is necessary to find smaller subsets, or tag SNPs, representing the rest of the SNPs. In fact, the existing tag SNP selection algorithms are notoriously time-consuming. An efficient algorithm for tag SNP selection was presented, which was applied to analyze the HapMap YRI data. The experimental results show that the proposed algorithm can achieve better performance than the existing tag SNP selection algorithms; in most cases, this proposed algorithm is at least ten times faster than the existing methods. In many cases, when the redundant ratio of the block is high, the proposed algorithm can even be thousands times faster than the previously known methods. Tools and web services for haplotype block analysis integrated by hadoop MapReduce framework are also developed using the proposed algorithm as computation kernels.
Fast algorithm of adaptive Fourier series
Gao, You; Ku, Min; Qian, Tao
2018-05-01
Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.
LCD motion blur: modeling, analysis, and algorithm.
Chan, Stanley H; Nguyen, Truong Q
2011-08-01
Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD model and an efficient deblurring algorithm are needed. However, existing LCD motion blur models are insufficient to reflect the limitation of human-eye-tracking system. Also, the spatiotemporal equivalence in LCD motion blur models has not been proven directly in the discrete 2-D spatial domain, although it is widely used. There are three main contributions of this paper: modeling, analysis, and algorithm. First, a comprehensive LCD motion blur model is presented, in which human-eye-tracking limits are taken into consideration. Second, a complete analysis of spatiotemporal equivalence is provided and verified using real video sequences. Third, an LCD motion blur reduction algorithm is proposed. The proposed algorithm solves an l(1)-norm regularized least-squares minimization problem using a subgradient projection method. Numerical results show that the proposed algorithm gives higher peak SNR, lower temporal error, and lower spatial error than motion-compensated inverse filtering and Lucy-Richardson deconvolution algorithm, which are two state-of-the-art LCD deblurring algorithms.
Modified Decoding Algorithm of LLR-SPA
Directory of Open Access Journals (Sweden)
Zhongxun Wang
2014-09-01
Full Text Available In wireless sensor networks, the energy consumption is mainly occurred in the stage of information transmission. The Low Density Parity Check code can make full use of the channel information to save energy. Because of the widely used decoding algorithm of the Low Density Parity Check code, this paper proposes a new decoding algorithm which is based on the LLR-SPA (Sum-Product Algorithm in Log-Likelihood-domain to improve the accuracy of the decoding algorithm. In the modified algorithm, a piecewise linear function is used to approximate the complicated Jacobi correction term in LLR-SPA decoding algorithm. Construct the tangent by the tangency point to the function of Jacobi correction term, which is based on the first order Taylor Series. In this way, the proposed piecewise linear approximation offers almost a perfect match to the function of Jacobi correction term. Meanwhile, the proposed piecewise linear approximation could avoid the operation of logarithmic which is more suitable for practical application. The simulation results show that the proposed algorithm could improve the decoding accuracy greatly without noticeable variation of the computational complexity.
Basic Algorithms for the Asynchronous Reconfigurable Mesh
Directory of Open Access Journals (Sweden)
Yosi Ben-Asher
2002-01-01
Full Text Available Many constant time algorithms for various problems have been developed for the reconfigurable mesh (RM in the past decade. All these algorithms are designed to work with synchronous execution, with no regard for the fact that large size RMs will probably be asynchronous. A similar observation about the PRAM model motivated many researchers to develop algorithms and complexity measures for the asynchronous PRAM (APRAM. In this work, we show how to define the asynchronous reconfigurable mesh (ARM and how to measure the complexity of asynchronous algorithms executed on it. We show that connecting all processors in a row of an n×n ARM (the analog of barrier synchronization in the APRAM model can be solved with complexity Θ(nlogn. Intuitively, this is average work time for solving such a problem. Next, we describe general a technique for simulating T -step synchronous RM algorithms on the ARM with complexity of Θ(T⋅n2logn. Finally, we consider the simulation of the classical synchronous algorithm for counting the number of non-zero bits in an n bits vector using (k
Heterogeneous architecture to process swarm optimization algorithms
Directory of Open Access Journals (Sweden)
Maria A. Dávila-Guzmán
2014-01-01
Full Text Available Since few years ago, the parallel processing has been embedded in personal computers by including co-processing units as the graphics processing units resulting in a heterogeneous platform. This paper presents the implementation of swarm algorithms on this platform to solve several functions from optimization problems, where they highlight their inherent parallel processing and distributed control features. In the swarm algorithms, each individual and dimension problem are parallelized by the granularity of the processing system which also offer low communication latency between individuals through the embedded processing. To evaluate the potential of swarm algorithms on graphics processing units we have implemented two of them: the particle swarm optimization algorithm and the bacterial foraging optimization algorithm. The algorithms’ performance is measured using the acceleration where they are contrasted between a typical sequential processing platform and the NVIDIA GeForce GTX480 heterogeneous platform; the results show that the particle swarm algorithm obtained up to 36.82x and the bacterial foraging swarm algorithm obtained up to 9.26x. Finally, the effect to increase the size of the population is evaluated where we show both the dispersion and the quality of the solutions are decreased despite of high acceleration performance since the initial distribution of the individuals can converge to local optimal solution.
Updated treatment algorithm of pulmonary arterial hypertension.
Galiè, Nazzareno; Corris, Paul A; Frost, Adaani; Girgis, Reda E; Granton, John; Jing, Zhi Cheng; Klepetko, Walter; McGoon, Michael D; McLaughlin, Vallerie V; Preston, Ioana R; Rubin, Lewis J; Sandoval, Julio; Seeger, Werner; Keogh, Anne
2013-12-24
The demands on a pulmonary arterial hypertension (PAH) treatment algorithm are multiple and in some ways conflicting. The treatment algorithm usually includes different types of recommendations with varying degrees of scientific evidence. In addition, the algorithm is required to be comprehensive but not too complex, informative yet simple and straightforward. The type of information in the treatment algorithm are heterogeneous including clinical, hemodynamic, medical, interventional, pharmacological and regulatory recommendations. Stakeholders (or users) including physicians from various specialties and with variable expertise in PAH, nurses, patients and patients' associations, healthcare providers, regulatory agencies and industry are often interested in the PAH treatment algorithm for different reasons. These are the considerable challenges faced when proposing appropriate updates to the current evidence-based treatment algorithm.The current treatment algorithm may be divided into 3 main areas: 1) general measures, supportive therapy, referral strategy, acute vasoreactivity testing and chronic treatment with calcium channel blockers; 2) initial therapy with approved PAH drugs; and 3) clinical response to the initial therapy, combination therapy, balloon atrial septostomy, and lung transplantation. All three sections will be revisited highlighting information newly available in the past 5 years and proposing updates where appropriate. The European Society of Cardiology grades of recommendation and levels of evidence will be adopted to rank the proposed treatments. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm
Anam, S.
2017-10-01
Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.
Algorithm of Particle Data Association for SLAM Based on Improved Ant Algorithm
Directory of Open Access Journals (Sweden)
KeKe Gen
2015-01-01
Full Text Available The article considers a problem of data association algorithm for simultaneous localization and mapping guidelines in determining the route of unmanned aerial vehicles (UAVs. Currently, these equipments are already widely used, but mainly controlled from the remote operator. An urgent task is to develop a control system that allows for autonomous flight. Algorithm SLAM (simultaneous localization and mapping, which allows to predict the location, speed, the ratio of flight parameters and the coordinates of landmarks and obstacles in an unknown environment, is one of the key technologies to achieve real autonomous UAV flight. The aim of this work is to study the possibility of solving this problem by using an improved ant algorithm.The data association for SLAM algorithm is meant to establish a matching set of observed landmarks and landmarks in the state vector. Ant algorithm is one of the widely used optimization algorithms with positive feedback and the ability to search in parallel, so the algorithm is suitable for solving the problem of data association for SLAM. But the traditional ant algorithm in the process of finding routes easily falls into local optimum. Adding random perturbations in the process of updating the global pheromone to avoid local optima. Setting limits pheromone on the route can increase the search space with a reasonable amount of calculations for finding the optimal route.The paper proposes an algorithm of the local data association for SLAM algorithm based on an improved ant algorithm. To increase the speed of calculation, local data association is used instead of the global data association. The first stage of the algorithm defines targets in the matching space and the observed landmarks with the possibility of association by the criterion of individual compatibility (IC. The second stage defines the matched landmarks and their coordinates using improved ant algorithm. Simulation results confirm the efficiency and
Parallelization of Edge Detection Algorithm using MPI on Beowulf Cluster
Haron, Nazleeni; Amir, Ruzaini; Aziz, Izzatdin A.; Jung, Low Tan; Shukri, Siti Rohkmah
In this paper, we present the design of parallel Sobel edge detection algorithm using Foster's methodology. The parallel algorithm is implemented using MPI message passing library and master/slave algorithm. Every processor performs the same sequential algorithm but on different part of the image. Experimental results conducted on Beowulf cluster are presented to demonstrate the performance of the parallel algorithm.
An Efficient Algorithm for Solving Single Veriable Optimization ...
African Journals Online (AJOL)
Many methods are available for finding x*E Rn which minimizes the real value function f(x), some of which are Fibonacci Search Algorithm, Quadratic Search Algorithm, Convergence Algorithm and Cubic Search Algorithm. In this research work, existing algorithms used in single variable optimization problems are critically ...
Protein Structure Prediction with Evolutionary Algorithms
Energy Technology Data Exchange (ETDEWEB)
Hart, W.E.; Krasnogor, N.; Pelta, D.A.; Smith, J.
1999-02-08
Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.
Cache-Oblivious Algorithms and Data Structures
DEFF Research Database (Denmark)
Brodal, Gerth Stølting
2004-01-01
as standard RAM algorithms with only one memory level, i.e. without any knowledge about memory hierarchies, but are analyzed in the two-level I/O model of Aggarwal and Vitter for an arbitrary memory and block size and an optimal off-line cache replacement strategy. The result are algorithms that automatically...... apply to multi-level memory hierarchies. This paper gives an overview of the results achieved on cache-oblivious algorithms and data structures since the seminal paper by Frigo et al....
Formal verification of a deadlock detection algorithm
Verbeek, Freek; Schmaltz, Julien
2011-01-01
Deadlock detection is a challenging issue in the analysis and design of on-chip networks. We have designed an algorithm to detect deadlocks automatically in on-chip networks with wormhole switching. The algorithm has been specified and proven correct in ACL2. To enable a top-down proof methodology, some parts of the algorithm have been left unimplemented. For these parts, the ACL2 specification contains constrained functions introduced with defun-sk. We used single-threaded objects to represe...
A Noise Removal Algorithm of Color Image
WANG Jianwei
2013-01-01
An algorithm of the color image noise removal algorithm is put forward based on the pixel operations. The idea of the algorithm is to read every pixel in a set order and determine whether the pixel level is consistent with the probability density function of impulse noise or not. If it is similar to noise pixel, the number of impulse noise in a certain mask is counted. If the number is less than the given threshold, the pixel is considered as possible noise. The pixel value is not unchanged. ...
Adaptive Algorithm for Chirp-Rate Estimation
Directory of Open Access Journals (Sweden)
Igor Djurović
2009-01-01
Full Text Available Chirp-rate, as a second derivative of signal phase, is an important feature of nonstationary signals in numerous applications such as radar, sonar, and communications. In this paper, an adaptive algorithm for the chirp-rate estimation is proposed. It is based on the confidence intervals rule and the cubic-phase function. The window width is adaptively selected to achieve good tradeoff between bias and variance of the chirp-rate estimate. The proposed algorithm is verified by simulations and the results show that it outperforms the standard algorithm with fixed window width.
Optimized Bayesian dynamic advising theory and algorithms
Karny, Miroslav
2006-01-01
Written by one of the world's leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. Starting from abstract ideas and formulations, and culminating in detailed algorithms, the book comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modelling by dynamic mixture models
Parallel algorithms for numerical linear algebra
van der Vorst, H
1990-01-01
This is the first in a new series of books presenting research results and developments concerning the theory and applications of parallel computers, including vector, pipeline, array, fifth/future generation computers, and neural computers.All aspects of high-speed computing fall within the scope of the series, e.g. algorithm design, applications, software engineering, networking, taxonomy, models and architectural trends, performance, peripheral devices.Papers in Volume One cover the main streams of parallel linear algebra: systolic array algorithms, message-passing systems, algorithms for p
An algorithm for gluinos on the lattice
International Nuclear Information System (INIS)
Montvay, I.
1995-10-01
Luescher's local bosonic algorithm for Monte Carlo simulations of quantum field theories with fermions is applied to the simulation of a possibly supersymmetric Yang-Mills theory with a Majorana fermion in the adjoint representation. Combined with a correction step in a two-step polynomial approximation scheme, the obtained algorithm seems to be promising and could be competitive with more conventional algorithms based on discretized classical (''molecular dynamics'') equations of motion. The application of the considered polynomial approximation scheme to optimized hopping parameter expansions is also discussed. (orig.)
Algorithms for optimal dyadic decision trees
Energy Technology Data Exchange (ETDEWEB)
Hush, Don [Los Alamos National Laboratory; Porter, Reid [Los Alamos National Laboratory
2009-01-01
A new algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data sets. This paper enhances and extends this algorithm by: introducing an adaptive grid search for the regularization parameter that guarantees optimal solutions for all relevant trees sizes, revising the core tree-building algorithm so that its run time is substantially smaller for most regularization parameter values on the grid, and incorporating new data structures and data pre-processing steps that provide significant run time enhancement in practice.
Sizing algorithm with continuous customizable clipping
Morales, Domingo; Baytelman, Felipe; Araya, Hugo
2008-10-01
Polygon sizing is required during Mask Data Preparation in order to generate derived layers and as process bias to account for edge effects of etching. Two main features are required for polygon sizing algorithms to be useful in Mask Data Preparation software: correctness to avoid data corruption and clipping of the projection of acute angle vertices to limit connectivity modifications. However, current available solutions are either based on heuristics, producing corrupted results for certain input, or based on algorithms which may fail to maintain original design's connectivity for certain input. A novel algorithm including customizable clipping is presented.
System engineering approach to GPM retrieval algorithms
Energy Technology Data Exchange (ETDEWEB)
Rose, C. R. (Chris R.); Chandrasekar, V.
2004-01-01
System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Ground validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do
Stochastic optimization algorithms for barrier dividend strategies
Yin, G.; Song, Q. S.; Yang, H.
2009-01-01
This work focuses on finding optimal barrier policy for an insurance risk model when the dividends are paid to the share holders according to a barrier strategy. A new approach based on stochastic optimization methods is developed. Compared with the existing results in the literature, more general surplus processes are considered. Precise models of the surplus need not be known; only noise-corrupted observations of the dividends are used. Using barrier-type strategies, a class of stochastic optimization algorithms are developed. Convergence of the algorithm is analyzed; rate of convergence is also provided. Numerical results are reported to demonstrate the performance of the algorithm.
Asynchronous Event-Driven Particle Algorithms
Energy Technology Data Exchange (ETDEWEB)
Donev, A
2007-08-30
We present, in a unifying way, the main components of three asynchronous event-driven algorithms for simulating physical systems of interacting particles. The first example, hard-particle molecular dynamics (MD), is well-known. We also present a recently-developed diffusion kinetic Monte Carlo (DKMC) algorithm, as well as a novel stochastic molecular-dynamics algorithm that builds on the Direct Simulation Monte Carlo (DSMC). We explain how to effectively combine event-driven and classical time-driven handling, and discuss some promises and challenges for event-driven simulation of realistic physical systems.
Data structures and algorithm analysis in Java
Shaffer, Clifford A
2011-01-01
With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Java as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis. Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, familiari
Data structures and algorithm analysis in C++
Shaffer, Clifford A
2011-01-01
With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Microsoft C++ as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis.Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, f
Dual format algorithm implementation with gotcha data
Gorham, LeRoy A.; Rigling, Brian D.
2012-05-01
The Dual Format Algorithm (DFA) is an alternative to the Polar Format Algorithm (PFA) where the image is formed first to an arbitrary grid instead of a Cartesian grid. The arbitrary grid is specifically chosen to allow for more efficient application of defocus and distortion corrections that occur due to range curvature. We provide a description of the arbitrary image grid and show that the quadratic phase errors are isolated along a single dimension of the image. We describe an application of the DFA to circular SAR data and analyze the image focus. For an example SAR dataset, the DFA doubles the focused image size of the PFA algorithm with post imaging corrections.
Kernel learning algorithms for face recognition
Li, Jun-Bao; Pan, Jeng-Shyang
2013-01-01
Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new
Space mapping optimization algorithms for engineering design
DEFF Research Database (Denmark)
Koziel, Slawomir; Bandler, John W.; Madsen, Kaj
2006-01-01
-order derivatives between the mapped coarse model and the fine model at the current iteration point. We also consider an enhanced version in which the input SM coefficients are frequency dependent. The performance of our new algorithms is comparable with the recently published SMIS algorithm when applied......A simple, efficient optimization algorithm based on space mapping (SM) is presented. It utilizes input SM to reduce the misalignment between the coarse and fine models of the optimized object over a region of interest, and output space mapping (OSM) to ensure matching of response and first...
Algorithms for Disconnected Diagrams in Lattice QCD
Energy Technology Data Exchange (ETDEWEB)
Gambhir, Arjun Singh [College of William and Mary, Williamsburg, VA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Stathopoulos, Andreas [College of William and Mary, Williamsburg, VA (United States); Orginos, Konstantinos [College of William and Mary, Williamsburg, VA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Yoon, Boram [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gupta, Rajan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Syritsyn, Sergey [Stony Brook Univ., NY (United States)
2016-11-01
Computing disconnected diagrams in Lattice QCD (operator insertion in a quark loop) entails the computationally demanding problem of taking the trace of the all to all quark propagator. We first outline the basic algorithm used to compute a quark loop as well as improvements to this method. Then, we motivate and introduce an algorithm based on the synergy between hierarchical probing and singular value deflation. We present results for the chiral condensate using a 2+1-flavor clover ensemble and compare estimates of the nucleon charges with the basic algorithm.
Non-renormalizability of the HMC algorithm
Lüscher, Martin; Schaefer, Stefan
2011-04-01
In lattice field theory, renormalizable simulation algorithms are attractive, because their scaling behaviour as a function of the lattice spacing is predictable. Algorithms implementing the Langevin equation, for example, are known to be renormalizable if the simulated theory is. In this paper we show that the situation is different in the case of the molecular-dynamics evolution on which the HMC algorithm is based. More precisely, studying the ϕ 4 theory, we find that the hyperbolic character of the molecular-dynamics equations leads to non-local (and thus non-removable) ultraviolet singularities already at one-loop order of perturbation theory.
Non-renormalizability of the HMC algorithm
Lüscher, Martin
2011-01-01
In lattice field theory, renormalizable simulation algorithms are attractive, because their scaling behaviour as a function of the lattice spacing is predictable. Algorithms implementing the Langevin equation, for example, are known to be renormalizable if the simulated theory is. In this paper we show that the situation is different in the case of the molecular-dynamics evolution on which the HMC algorithm is based. More precisely, studying the phi^4 theory, we find that the hyperbolic character of the molecular-dynamics equations leads to non-local (and thus non-removable) ultraviolet singularities already at one-loop order of perturbation theory.
Full QCD algorithms towards the chiral limit
Hasenbusch, M
2003-01-01
I discuss the behaviour of algorithms for dynamical fermions as the sea-quark mass decreases. I focus on the Hybrid-Monte-Carlo (HMC) algorithm applied to two degenerate flavours of Wilson fermions. First, I briefly review the performance obtained in large scale HMC simulations. Then I discuss a modified pseudo-fermion action for the HMC simulation that has been introduced three years ago. I summarize recent results obtained with this pseudo-fermion action by the QCDSF and the ALPHA collaborations. I comment on alternatives to the HMC, like the Multiboson algorithm and variants of it.
An algorithm for online optimization of accelerators
Energy Technology Data Exchange (ETDEWEB)
Huang, Xiaobiao [SLAC National Accelerator Lab., Menlo Park, CA (United States); Corbett, Jeff [SLAC National Accelerator Lab., Menlo Park, CA (United States); Safranek, James [SLAC National Accelerator Lab., Menlo Park, CA (United States); Wu, Juhao [SLAC National Accelerator Lab., Menlo Park, CA (United States)
2013-10-01
We developed a general algorithm for online optimization of accelerator performance, i.e., online tuning, using the performance measure as the objective function. This method, named robust conjugate direction search (RCDS), combines the conjugate direction set approach of Powell's method with a robust line optimizer which considers the random noise in bracketing the minimum and uses parabolic fit of data points that uniformly sample the bracketed zone. Moreover, it is much more robust against noise than traditional algorithms and is therefore suitable for online application. Simulation and experimental studies have been carried out to demonstrate the strength of the new algorithm.
AES ALGORITHM IMPLEMENTATION IN PROGRAMMING LANGUAGES
Directory of Open Access Journals (Sweden)
Luminiţa DEFTA
2010-12-01
Full Text Available Information encryption represents the usage of an algorithm to convert an unknown message into an encrypted one. It is used to protect the data against unauthorized access. Protected data can be stored on a media device or can be transmitted through the network. In this paper we describe a concrete implementation of the AES algorithm in the Java programming language (available from Java Development Kit 6 libraries and C (using the OpenSSL library. AES (Advanced Encryption Standard is an asymmetric key encryption algorithm formally adopted by the U.S. government and was elected after a long process of standardization.
Utilizing Centralized Diamond Architecture for Searching Algorithms
Damrudi, Masumeh; Jadidy Aval, Kamal
2017-09-01
Searching data elements and information in a fraction of time is still an important task for many areas of works. The importance of finding the best answer leads to use different algorithms which consume time. To improve the speed of searching information within mass information, employing parallel processing is inevitable. A search algorithm with constant time(CS) is proposed on centralized diamond architecture. We have optimized this algorithm to find the location and the number of occurrence of data, if there exists any.
Hybridizing Evolutionary Algorithms with Opportunistic Local Search
DEFF Research Database (Denmark)
Gießen, Christian
2013-01-01
There is empirical evidence that memetic algorithms (MAs) can outperform plain evolutionary algorithms (EAs). Recently the first runtime analyses have been presented proving the aforementioned conjecture rigorously by investigating Variable-Depth Search, VDS for short (Sudholt, 2008). Sudholt...... of this new operator is demonstrated on the Rastrigin function encoded for binary hypercubes. Our results provide further insight into the problem of how to prevent local search algorithms to get stuck in local optima from a theoretical perspective. The methods stem from discrete probability theory...
Some multigrid algorithms for SIMD machines
Energy Technology Data Exchange (ETDEWEB)
Dendy, J.E. Jr. [Los Alamos National Lab., NM (United States)
1996-12-31
Previously a semicoarsening multigrid algorithm suitable for use on SIMD architectures was investigated. Through the use of new software tools, the performance of this algorithm has been considerably improved. The method has also been extended to three space dimensions. The method performs well for strongly anisotropic problems and for problems with coefficients jumping by orders of magnitude across internal interfaces. The parallel efficiency of this method is analyzed, and its actual performance on the CM-5 is compared with its performance on the CRAY-YMP. A standard coarsening multigrid algorithm is also considered, and we compare its performance on these two platforms as well.
Amalia; Budiman, M. A.; Sitepu, R.
2018-03-01
Cryptography is one of the best methods to keep the information safe from security attack by unauthorized people. At present, Many studies had been done by previous researchers to generate a more robust cryptographic algorithm to provide high security for data communication. To strengthen data security, one of the methods is hybrid cryptosystem method that combined symmetric and asymmetric algorithm. In this study, we observed a hybrid cryptosystem method contain Modification Playfair Cipher 16x16 algorithm as a symmetric algorithm and Knapsack Naccache-Stern as an asymmetric algorithm. We observe a running time of this hybrid algorithm with some of the various experiments. We tried different amount of characters to be tested which are 10, 100, 1000, 10000 and 100000 characters and we also examined the algorithm with various key’s length which are 10, 20, 30, 40 of key length. The result of our study shows that the processing time for encryption and decryption process each algorithm is linearly proportional, it means the longer messages character then, the more significant times needed to encrypt and decrypt the messages. The encryption running time of Knapsack Naccache-Stern algorithm takes a longer time than its decryption, while the encryption running time of modification Playfair Cipher 16x16 algorithm takes less time than its decryption.
Directory of Open Access Journals (Sweden)
V. E. Marley
2015-01-01
Full Text Available Summary. The concept of algorithmic models appeared from the algorithmic approach in which the simulated object, the phenomenon appears in the form of process, subject to strict rules of the algorithm, which placed the process of operation of the facility. Under the algorithmic model is the formalized description of the scenario subject specialist for the simulated process, the structure of which is comparable with the structure of the causal and temporal relationships between events of the process being modeled, together with all information necessary for its software implementation. To represent the structure of algorithmic models used algorithmic network. Normally, they were defined as loaded finite directed graph, the vertices which are mapped to operators and arcs are variables, bound by operators. The language of algorithmic networks has great features, the algorithms that it can display indifference the class of all random algorithms. In existing systems, automation modeling based on algorithmic nets, mainly used by operators working with real numbers. Although this reduces their ability, but enough for modeling a wide class of problems related to economy, environment, transport, technical processes. The task of modeling the execution of schedules and network diagrams is relevant and useful. There are many counting systems, network graphs, however, the monitoring process based analysis of gaps and terms of graphs, no analysis of prediction execution schedule or schedules. The library is designed to build similar predictive models. Specifying source data to obtain a set of projections from which to choose one and take it for a new plan.
Algorithmic and user study of an autocompletion algorithm on a large medical vocabulary.
Sevenster, Merlijn; van Ommering, Rob; Qian, Yuechen
2012-02-01
Autocompletion supports human-computer interaction in software applications that let users enter textual data. We will be inspired by the use case in which medical professionals enter ontology concepts, catering the ongoing demand for structured and standardized data in medicine. Goal is to give an algorithmic analysis of one particular autocompletion algorithm, called multi-prefix matching algorithm, which suggests terms whose words' prefixes contain all words in the string typed by the user, e.g., in this sense, opt ner me matches optic nerve meningioma. Second we aim to investigate how well it supports users entering concepts from a large and comprehensive medical vocabulary (snomed ct). We give a concise description of the multi-prefix algorithm, and sketch how it can be optimized to meet required response time. Performance will be compared to a baseline algorithm, which gives suggestions that extend the string typed by the user to the right, e.g. optic nerve m gives optic nerve meningioma, but opt ner me does not. We conduct a user experiment in which 12 participants are invited to complete 40 snomed ct terms with the baseline algorithm and another set of 40 snomed ct terms with the multi-prefix algorithm. Our results show that users need significantly fewer keystrokes when supported by the multi-prefix algorithm than when supported by the baseline algorithm. The proposed algorithm is a competitive candidate for searching and retrieving terms from a large medical ontology. Copyright © 2011 Elsevier Inc. All rights reserved.
Flow enforcement algorithms for ATM networks
DEFF Research Database (Denmark)
Dittmann, Lars; Jacobsen, Søren B.; Moth, Klaus
1991-01-01
Four measurement algorithms for flow enforcement in asynchronous transfer mode (ATM) networks are presented. The algorithms are the leaky bucket, the rectangular sliding window, the triangular sliding window, and the exponentially weighted moving average. A comparison, based partly on teletraffic...... theory and partly on signal processing theory, is carried out. It is seen that the time constant involved increases with the increasing burstiness of the connection. It is suggested that the RMS measurement bandwidth be used to dimension linear algorithms for equal flow enforcement characteristics....... Implementations are proposed on the block diagram level, and dimensioning examples are carried out when flow enforcing a renewal-type connection using the four algorithms. The corresponding hardware demands are estimated aid compared...
Guest editorial: Adaptive and natural computing algorithms
Czech Academy of Sciences Publication Activity Database
Kůrková, Věra
2012-01-01
Roč. 96, - (2012), s. 1-1 ISSN 0925-2312 Institutional support: RVO:67985807 Keywords : soft-computing * adaptive algorithms * neural networks Subject RIV: IN - Informatics, Computer Science Impact factor: 1.634, year: 2012
Toward human-centered algorithm design
Directory of Open Access Journals (Sweden)
Eric PS Baumer
2017-07-01
Full Text Available As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems’ results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author’s work designing and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans.
An efficient algorithm for color image segmentation
Directory of Open Access Journals (Sweden)
Shikha Yadav
2016-09-01
Full Text Available In field of image processing, image segmentation plays an important role that focus on splitting the whole image into segments. Representation of an image so that it can be more easily analysed and involves more information is an important segmentation goal. The process of partitioning an image can be usually realized by Region based, Boundary based or edge based method. In this work a hybrid approach is followed that combines improved bee colony optimization and Tabu search for color image segmentation. The results produced from this hybrid approach are compared with non-sorted particle swarm optimization, non-sorted genetic algorithm and improved bee colony optimization. Results show that the Hybrid algorithm has better or somewhat similar performance as compared to other algorithms that are based on population. The algorithm is successfully implemented on MATLAB.
The charge-flipping algorithm in crystallography
Czech Academy of Sciences Publication Activity Database
Palatinus, Lukáš
2013-01-01
Roč. 69, Jan (2013), s. 1-16 ISSN 2052-5192 Institutional support: RVO:68378271 Keywords : charge-flipping algorithm * dual-space methods * structure solution Subject RIV: BM - Solid Matter Physics ; Magnetism
Exact Algorithms for Solving Stochastic Games
DEFF Research Database (Denmark)
Hansen, Kristoffer Arnsfelt; Koucky, Michal; Lauritzen, Niels
2012-01-01
Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games....
K-means Clustering: Lloyd's algorithm
Indian Academy of Sciences (India)
First page Back Continue Last page Overview Graphics. K-means Clustering: Lloyd's algorithm. Refines clusters iteratively. Cluster points using Voronoi partitioning of the centers; Centroids of the clusters determine the new centers. Bad example k = 3, n =4.
Algorithmic Finance and (Limits to) Governmentality
DEFF Research Database (Denmark)
Borch, Christian
2017-01-01
In this essay I discuss algorithmic finance, specifically the use of fully automated trading, including high-frequency trading, in the light of Michel Foucault's notion of governmentality. I argue that a governmentality perspective offers a fruitful way of understanding particular aspects of high......-frequency trading, such as how algorithms are designed to govern other market participants' anticipations of market dynamics. However, I also argue that, to fully understand the realm of algorithmic finance and high-frequency trading, it is important to supplement a governmentality approach with an analytical...... lexicon which is not primarily centred on productive forms of power. Specifically, I suggest that, according to media discourses on high-frequency trading, algorithmic finance often works in ways that are better grasped through, e.g. Elias Canetti's work on predatory power and Roger Caillois's work...
Genetic algorithms as global random search methods
Peck, Charles C.; Dhawan, Atam P.
1995-01-01
Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.
Understanding molecular simulation: from algorithms to applications
Frenkel, D.; Smit, B.
2002-01-01
Second and revised edition Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique
Minimising Computational Complexity of the RRT Algorithm
DEFF Research Database (Denmark)
Svenstrup, Mikael; Bak, Thomas; Andersen, Hans Jørgen
2011-01-01
method is Rapidly-exploring Random Trees (RRT's). One problem with this method is the nearest neighbour search time, which grows significantly when adding a large number of vertices. We propose an algorithm which decreases the computation time, such that more vertices can be added in the same amount...... of time to generate better trajectories. The algorithm is based on subdividing the configuration space into boxes, where only specific boxes needs to be searched to find the nearest neighbour. It is shown that the computational complexity is lowered from a theoretical point of view. The result...... is an algorithm that can provide better trajectories within a given time period, or alternatively compute trajectories faster. In simulation the algorithm is verified for a simple RRT implementation and in a more specific case where a robot has to plan a path through a human inhabited environment....
Efficient Implementation Algorithms for Homogenized Energy Models
National Research Council Canada - National Science Library
Braun, Thomas R; Smith, Ralph C
2005-01-01
... for real-time control implementation. In this paper, we develop algorithms employing lookup tables which permit the high speed implementation of formulations which incorporate relaxation mechanisms and electromechanical coupling...
A smoothing algorithm using cubic spline functions
Smith, R. E., Jr.; Price, J. M.; Howser, L. M.
1974-01-01
Two algorithms are presented for smoothing arbitrary sets of data. They are the explicit variable algorithm and the parametric variable algorithm. The former would be used where large gradients are not encountered because of the smaller amount of calculation required. The latter would be used if the data being smoothed were double valued or experienced large gradients. Both algorithms use a least-squares technique to obtain a cubic spline fit to the data. The advantage of the spline fit is that the first and second derivatives are continuous. This method is best used in an interactive graphics environment so that the junction values for the spline curve can be manipulated to improve the fit.
Genetic algorithms at UC Davis/LLNL
Energy Technology Data Exchange (ETDEWEB)
Vemuri, V.R. [comp.
1993-12-31
A tutorial introduction to genetic algorithms is given. This brief tutorial should serve the purpose of introducing the subject to the novice. The tutorial is followed by a brief commentary on the term project reports that follow.
The LLL algorithm survey and applications
Nguyen, Phong Q
2010-01-01
The first book to offer a comprehensive view of the LLL algorithm, this text surveys computational aspects of Euclidean lattices and their main applications. It includes many detailed motivations, explanations and examples.
Frequent Pattern Mining Algorithms for Data Clustering
DEFF Research Database (Denmark)
Zimek, Arthur; Assent, Ira; Vreeken, Jilles
2014-01-01
Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say...... that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed into an independent research field. In this chapter, we discuss how frequent pattern mining algorithms have been extended and generalized towards the discovery of local clusters in high-dimensional data....... In particular, we discuss several example algorithms for subspace clustering or projected clustering as well as point out recent research questions and open topics in this area relevant to researchers in either clustering or pattern mining...
Swarm-based algorithm for phase unwrapping.
da Silva Maciel, Lucas; Albertazzi, Armando G
2014-08-20
A novel algorithm for phase unwrapping based on swarm intelligence is proposed. The algorithm was designed based on three main goals: maximum coverage of reliable information, focused effort for better efficiency, and reliable unwrapping. Experiments were performed, and a new agent was designed to follow a simple set of five rules in order to collectively achieve these goals. These rules consist of random walking for unwrapping and searching, ambiguity evaluation by comparing unwrapped regions, and a replication behavior responsible for the good distribution of agents throughout the image. The results were comparable with the results from established methods. The swarm-based algorithm was able to suppress ambiguities better than the flood-fill algorithm without relying on lengthy processing times. In addition, future developments such as parallel processing and better-quality evaluation present great potential for the proposed method.
Genetic Algorithm Optimized Neural Networks Ensemble as ...
African Journals Online (AJOL)
Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.
Algorithms for Academic Search and Recommendation Systems
DEFF Research Database (Denmark)
Amolochitis, Emmanouil
2014-01-01
are part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. In the third part of the work we present the design of a quantitative association rule mining algorithm. The introduced mining algorithm processes......In this work we present novel algorithms for academic search, recommendation and association rules mining. In the first part of the work we introduce a novel hierarchical heuristic scheme for re-ranking academic publications. The scheme is based on the hierarchical combination of a custom...... implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. On the second part we describe the design of hybrid recommender ensemble (user, item and content based). The newly introduced algorithms...
A Faster Algorithm for Computing Straight Skeletons
Mencel, Liam A.
2014-05-06
We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (log n) log r) time. It improves on the previously best known algorithm for this reduction, which is randomised, and runs in expected O(n √(h+1) log² n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (log n) log r + r^(4/3 + ε)) time for any ε > 0. On degenerate input, our time bound increases to O(n (log n) log r + r^(17/11 + ε))
A Faster Algorithm for Computing Straight Skeletons
Cheng, Siu-Wing
2014-09-01
We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (logn)logr) time. It improves on the previously best known algorithm for this reduction, which is randomized, and runs in expected O(n√h+1log2n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (logn) logr + r 4/3 + ε ) time for any ε > 0. On degenerate input, our time bound increases to O(n (logn) logr + r 17/11 + ε ).
FPGA helix tracking algorithm for PANDA
Energy Technology Data Exchange (ETDEWEB)
Liang, Yutie; Galuska, Martin; Gessler, Thomas; Kuehn, Wolfgang; Lange, Jens Soeren; Muenchow, David [II. Physikalisches Institut, University of Giessen (Germany); Ye, Hua [Institute of High Energy Physics, CAS (China); Collaboration: PANDA-Collaboration
2016-07-01
The PANDA detector is a general-purpose detector for physics with high luminosity cooled antiproton beams, planed to operate at the FAIR facility in Darmstadt, Germany. The central detector includes a silicon Micro Vertex Detector (MVD) and a Straw Tube Tracker (STT). Without any hardware trigger, large amounts of raw data are streaming into the data acquisition system. The data reduction task is performed in the online system by reconstruction algorithms programmed on FPGAs (Field Programmable Gate Arrays) as first level and on a farm of GPUs or PCs as a second level. One important part in the system is the online track reconstruction. In this presentation, an online tracking algorithm for helix tracking reconstruction in the solenoidal field is shown. The VHDL-based algorithm is tested with different types of events, at different event rate. Furthermore, a study of T0 extraction from the tracking algorithm is performed. A concept of simultaneous tracking and T0 determination is presented.
Algorithms for Port-of-Entry Inspection
National Research Council Canada - National Science Library
Roberts, Fred S
2007-01-01
.... The percentage at some ports has now risen to 6%, but this is still a very small percentage. The purpose of this project was to develop decision support algorithms that help to optimally intercept illicit materials and weapons...
Computing Algorithms for Nuffield Advanced Physics.
Summers, M. K.
1978-01-01
Defines all recurrence relations used in the Nuffield course, to solve first- and second-order differential equations, and describes a typical algorithm for computer generation of solutions. (Author/GA)
Seizure detection algorithms based on EMG signals
DEFF Research Database (Denmark)
Conradsen, Isa
Background: the currently used non-invasive seizure detection methods are not reliable. Muscle fibers are directly connected to the nerves, whereby electric signals are generated during activity. Therefore, an alarm system on electromyography (EMG) signals is a theoretical possibility. Objective......: to show whether medical signal processing of EMG data is feasible for detection of epileptic seizures. Methods: EMG signals during generalised seizures were recorded from 3 patients (with 20 seizures in total). Two possible medical signal processing algorithms were tested. The first algorithm was based...... the frequency-based algorithm was efficient for detecting the seizures in the third patient. Conclusion: Our results suggest that EMG signals could be used to develop an automatic seizuredetection system. However, different patients might require different types of algorithms /approaches....
Dual format algorithm for monostatic SAR
Gorham, LeRoy A.; Rigling, Brian D.
2010-04-01
The polar format algorithm for monostatic synthetic aperture radar imaging is based on a linear approximation of the differential range to a scatterer, which leads to spatially-variant distortion and defocus in the resultant image. While approximate corrections may be applied to compensate for these effects, these corrections are ad-hoc in nature. Here, we introduce an alternative imaging algorithm called the Dual Format Algorithm (DFA) that provides better isolation of the defocus effects and reduces distortion. Quadratic phase errors are isolated along a single dimension by allowing image formation to an arbitrary grid instead of a Cartesian grid. This provides an opportunity for more efficient phase error corrections. We provide a description of the arbitrary image grid and we show the quadratic phase error correction derived from a second-order Taylor series approximation of the differential range. The algorithm is demonstrated with a point target simulation.
Algorithms for finite projected entangled pair states
Lubasch, Michael; Cirac, J. Ignacio; Bañuls, Mari-Carmen
2014-08-01
Projected entangled pair states (PEPS) are a promising ansatz for the study of strongly correlated quantum many-body systems in two dimensions. However, due to their high computational cost, developing and improving PEPS algorithms is necessary to make the ansatz widely usable in practice. Here we analyze several algorithmic aspects of the method. On the one hand, we quantify the connection between the correlation length of the PEPS and the accuracy of its approximate contraction and discuss how purifications can be used in the latter. On the other hand, we present algorithmic improvements for the update of the tensor that introduce drastic gains in the numerical conditioning and the efficiency of the algorithms. Finally, the state-of-the-art general PEPS code is benchmarked with the Heisenberg and quantum Ising models on lattices of up to 21×21 sites.
Genetic algorithm for nuclear data evaluation
Energy Technology Data Exchange (ETDEWEB)
Arthur, Jennifer Ann [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-02-02
These are slides on genetic algorithm for nuclear data evaluation. The following is covered: initial population, fitness (outer loop), calculate fitness, selection (first part of inner loop), reproduction (second part of inner loop), solution, and examples.
Practical Parallel Divide-and-Conquer Algorithms
National Research Council Canada - National Science Library
Hardwick, Jonathan
1997-01-01
.... This thesis shows that by restricting the problem set to that of data-parallel divide and conquer algorithms I can maintain the expressibility of full nested data-parallel languages while achieving...
Glowworm swarm optimization theory, algorithms, and applications
Kaipa, Krishnanand N
2017-01-01
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intellige...
New journal: Algorithms for Molecular Biology
Directory of Open Access Journals (Sweden)
Stadler Peter F
2006-02-01
Full Text Available Abstract This editorial announces Algorithms for Molecular Biology, a new online open access journal published by BioMed Central. By launching the first open access journal on algorithmic bioinformatics, we provide a forum for fast publication of high-quality research articles in this rapidly evolving field. Our journal will publish thoroughly peer-reviewed papers without length limitations covering all aspects of algorithmic data analysis in computatioal biology. Publications in Algorithms for Molecular Biology are easy to find, highly visible and tracked by organisations such as PubMed. An established online submission system makes a fast reviewing procedure possible and enables us to publish accepted papers without delay. All articles published in our journal are permanently archived by PubMed Central and other scientific archives. We are looking forward to receiving your contributions.
Genetic algorithm solution for partial digest problem.
Ahrabian, Hayedeh; Ganjtabesh, Mohammad; Nowzari-Dalini, Abbas; Razaghi-Moghadam-Kashani, Zahra
2013-01-01
One of the fundamental problems in computational biology is the construction of physical maps of chromosomes from the hybridisation experiments between unique probes and clones of chromosome fragments. Before introducing the shotgun sequencing method, Partial Digest Problem (PDP) was an intractable problem used to construct the physical maps of DNA sequence in molecular biology. In this paper, we develop a novel Genetic Algorithm (GA) for solving the PDP. This algorithm is implemented and compared with well-known existing algorithms on different types of random and real instances data, and the obtained results show the efficiency of our algorithm. Also, our GA is adapted to handle the erroneous data and their efficiency is presented for the large instances of this problem.
Doubly Constrained Robust Blind Beamforming Algorithm
Directory of Open Access Journals (Sweden)
Xin Song
2013-01-01
Full Text Available We propose doubly constrained robust least-squares constant modulus algorithm (LSCMA to solve the problem of signal steering vector mismatches via the Bayesian method and worst-case performance optimization, which is based on the mismatches between the actual and presumed steering vectors. The weight vector is iteratively updated with penalty for the worst-case signal steering vector by the partial Taylor-series expansion and Lagrange multiplier method, in which the Lagrange multipliers can be optimally derived and incorporated at each step. A theoretical analysis for our proposed algorithm in terms of complexity cost, convergence performance, and SINR performance is presented in this paper. In contrast to the linearly constrained LSCMA, the proposed algorithm provides better robustness against the signal steering vector mismatches, yields higher signal captive performance, improves greater array output SINR, and has a lower computational cost. The simulation results confirm the superiority of the proposed algorithm on beampattern control and output SINR enhancement.
Immersive Algorithms: Better Visualization with Less Information
DEFF Research Database (Denmark)
Bille, Philip; Gørtz, Inge Li
2017-01-01
Visualizing algorithms, such as drawings, slideshow presentations, animations, videos, and software tools, is a key concept to enhance and support student learning. A typical visualization of an algorithm show the data and then perform computation on the data. For instance, a standard visualization......” the full sorted array, but only the single position that it accesses during each step of the computation. To fix this discrepancy we introduce the immersive principle that states that at any point in time, the displayed information should closely match the information accessed by the algorithm. We give...... several examples of immersive visualizations of basic algorithms and data structures, discuss methods for implementing it, and briefly evaluate it....
The variance of two game tree algorithms
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yanjun [Southern Methodist Univ., Dallas, TX (United States)
1997-06-01
This paper studies the variance of two game tree algorithms {alpha}-{beta} search and SCOUT, in the stochastic i.i.d. model. The problem of determining the variance of the classic {alpha}-{beta} search algorithm in the i.i.d. model has been long open. This paper resolves this problem partially. It is shown, by the martingale method, that the standard deviation of the weaker {alpha}-{beta} search without deep cutoffs is of the same order as the expected number of leaves evaluated. A nearly-optimal upper bound on the variance of the general {alpha}-{beta} search is obtained, and this upper bound yields an optimal bound if the current upper bound on the expected number of leaves evaluated by {alpha}-{beta} search can be improved. A thorough treatment of the two-pass SCOUT algorithm is presented. The variance of the SCOUT algorithm is determined.
Blind distributed estimation algorithms for adaptive networks
Bin Saeed, Muhammad O.; Zerguine, Azzedine; Zummo, Salam A.
2014-12-01
Until recently, a lot of work has been done to develop algorithms that utilize the distributed structure of an ad hoc wireless sensor network to estimate a certain parameter of interest. However, all these algorithms assume that the input regressor data is available to the sensors, but this data is not always available to the sensors. In such cases, blind estimation of the required parameter is needed. This work formulates two newly developed blind block-recursive algorithms based on singular value decomposition (SVD) and Cholesky factorization-based techniques. These adaptive algorithms are then used for blind estimation in a wireless sensor network using diffusion of data among cooperative sensors. Simulation results show that the performance greatly improves over the case where no cooperation among sensors is involved.
Autonomous intelligent vehicles theory, algorithms, and implementation
Cheng, Hong
2011-01-01
Here is the latest on intelligent vehicles, covering object and obstacle detection and recognition and vehicle motion control. Includes a navigation approach using global views; introduces algorithms for lateral and longitudinal motion control and more.
Infrastructure system restoration planning using evolutionary algorithms
Corns, Steven; Long, Suzanna K.; Shoberg, Thomas G.
2016-01-01
This paper presents an evolutionary algorithm to address restoration issues for supply chain interdependent critical infrastructure. Rapid restoration of infrastructure after a large-scale disaster is necessary to sustaining a nation's economy and security, but such long-term restoration has not been investigated as thoroughly as initial rescue and recovery efforts. A model of the Greater Saint Louis Missouri area was created and a disaster scenario simulated. An evolutionary algorithm is used to determine the order in which the bridges should be repaired based on indirect costs. Solutions were evaluated based on the reduction of indirect costs and the restoration of transportation capacity. When compared to a greedy algorithm, the evolutionary algorithm solution reduced indirect costs by approximately 12.4% by restoring automotive travel routes for workers and re-establishing the flow of commodities across the three rivers in the Saint Louis area.
VLSI PARTITIONING ALGORITHM WITH ADAPTIVE CONTROL PARAMETER
Directory of Open Access Journals (Sweden)
P. N. Filippenko
2013-03-01
Full Text Available The article deals with the problem of very large-scale integration circuit partitioning. A graph is selected as a mathematical model describing integrated circuit. Modification of ant colony optimization algorithm is presented, which is used to solve graph partitioning problem. Ant colony optimization algorithm is an optimization method based on the principles of self-organization and other useful features of the ants’ behavior. The proposed search system is based on ant colony optimization algorithm with the improved method of the initial distribution and dynamic adjustment of the control search parameters. The experimental results and performance comparison show that the proposed method of very large-scale integration circuit partitioning provides the better search performance over other well known algorithms.
A segmentation algorithm for noisy images
Energy Technology Data Exchange (ETDEWEB)
Xu, Y.; Olman, V.; Uberbacher, E.C.
1996-12-31
This paper presents a 2-D image segmentation algorithm and addresses issues related to its performance on noisy images. The algorithm segments an image by first constructing a minimum spanning tree representation of the image and then partitioning the spanning tree into sub-trees representing different homogeneous regions. The spanning tree is partitioned in such a way that the sum of gray-level variations over all partitioned subtrees is minimized under the constraints that each subtree has at least a specified number of pixels and two adjacent subtrees have significantly different ``average`` gray-levels. Two types of noise, transmission errors and Gaussian additive noise. are considered and their effects on the segmentation algorithm are studied. Evaluation results have shown that the segmentation algorithm is robust in the presence of these two types of noise.
Seismogeochemical algorithms for earthquake prediction: an overview
Directory of Open Access Journals (Sweden)
F. Quattrocchi
1997-06-01
Full Text Available While the literature abounds with case histories related to geochemical precursory phenomena, only a few studies on definite seismogeochemical algorithms have been published so far. Currently, available theoretical algorithms are based on obsolete views of fluid migration processes that do not take into account the possibility of rapid and long-distance gas migration from the focal zone. Empirical algorithms are often based on a limited number of data and need validation for several geostructural environments. The algorithms of Sardarov (1981 and Rikitake (1987, for Rn and other geochemical elements, suggest that a definite relationship exists between geochemical parameters and seismic events. Their validation must be based on the verification of independence (maintained by the former author or dependence (maintained by the latter of the precursor time on the seismic data.
Genetic algorithms for air traffic assignment
Delahaye , Daniel; Alliot , Jean-Marc; Schoenauer , Marc; Farges , Jean-Loup
1994-01-01
International audience; In this paper, we show how genetic algorithms can be used to compute automatically a traffic assignment of aircraft on the air network to increase Air Traffic Control capacity in high density areas.
A Cooperative Framework for Fireworks Algorithm
Zheng, Shaoqiu; Li, Junzhi; Janecek, Andreas; Tan, Ying
2015-01-01
This paper presents a cooperative framework for fireworks algorithm (CoFFWA). A detailed analysis of existing fireworks algorithm (FWA) and its recently developed variants has revealed that (i) the selection strategy lead to the contribution of the firework with the best fitness (core firework) for the optimization overwhelms the contributions of the rest of fireworks (non-core fireworks) in the explosion operator, (ii) the Gaussian mutation operator is not as effective as it is designed to b...
Adaptive sensor fusion using genetic algorithms
International Nuclear Information System (INIS)
Fitzgerald, D.S.; Adams, D.G.
1994-01-01
Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ''fuzzy'' sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion
Optimal tracking algorithm: a DSP approach
Salvatti, Fred; Meshkat, Sy; Stufflebeam, Joseph L.
1995-05-01
This paper investigates the problem of tracking highly dynamic targets in real-time. The advantages and disadvantages of various control and interpolation techniques are discussed. Algorithms appropriate for real- time tracking are compared with algorithms that are common in applications with a priori knowledge of the trajectory. A unique command interpolation technique combined with a state feedback control structure, implemented on a commercial DSP controller, demonstrates a significant performance improvement.
Simulated annealing algorithm for optimal capital growth
Luo, Yong; Zhu, Bo; Tang, Yong
2014-08-01
We investigate the problem of dynamic optimal capital growth of a portfolio. A general framework that one strives to maximize the expected logarithm utility of long term growth rate was developed. Exact optimization algorithms run into difficulties in this framework and this motivates the investigation of applying simulated annealing optimized algorithm to optimize the capital growth of a given portfolio. Empirical results with real financial data indicate that the approach is inspiring for capital growth portfolio.
Improving the Performance of AI Algorithms.
1987-09-01
integration of artificialintelligence algorithms may provide significant enhancements in the behavior of BM/C 3 systems. The history of poor performance...The "operating .rstem computer", for example, is .-...- generally sub-stratified into a library program level, a utility level, and .erhaps a...interprets or simulates the input program through the use of library routines, which provide the low-level algorithms necessary to carry out each
A Parametric k-Means Algorithm
Tarpey, Thaddeus
2007-01-01
The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data...
Dynamic Uniform Scaling for Multiobjective Genetic Algorithms
DEFF Research Database (Denmark)
Pedersen, Gerulf; Goldberg, David E.
2004-01-01
Before Multiobjective Evolutionary Algorithms (MOEAs) can be used as a widespread tool for solving arbitrary real world problems there are some salient issues which require further investigation. One of these issues is how a uniform distribution of solutions along the Pareto non-dominated front can......, the issue of obtaining a diverse set of solutions for badly scaled objective functions will be investigated and proposed solutions will be implemented using the NSGA-II algorithm....
Rules Extraction with an Immune Algorithm
Directory of Open Access Journals (Sweden)
Deqin Yan
2007-12-01
Full Text Available In this paper, a method of extracting rules with immune algorithms from information systems is proposed. Designing an immune algorithm is based on a sharing mechanism to extract rules. The principle of sharing and competing resources in the sharing mechanism is consistent with the relationship of sharing and rivalry among rules. In order to extract rules efficiently, a new concept of flexible confidence and rule measurement is introduced. Experiments demonstrate that the proposed method is effective.
Some experiences with the Eigensystem Realization Algorithm
Pappa, Richard S.; Juang, Jer-Nan
1988-01-01
The Eigensystem Realization Algorithm (ERA) is a multiinput/multioutput time-domain algorithm for minimum-order system realization and modal parameter identification. It has been used for structural dynamics data analysis at the Langley Research Center for several years. Some of the practical experiences encountered in these projects are discussed in this paper. Three examples are used: the Galileo spacecraft, the Solar Array Flight Experiment, and a laboratory space-truss model. Several techniques for assessing identification accuracy are illustrated.
The mathematics behind PageRank algorithm
Spačal, Gregor
2016-01-01
PageRank is Google's algorithm for ranking web pages by relevance. Pages can then be hierarchically sorted in order to provide better search results. The MSc thesis considers functioning, relevance, general properties of web search and its weaknesses before the appearance of Google. One of the most important questions is, if we can formally explain the mathematics behind PageRank algorithm and what mathematical knowledge is necessary. Finally, we present an example of its implementation i...
Self-organization and clustering algorithms
Bezdek, James C.
1991-01-01
Kohonen's feature maps approach to clustering is often likened to the k or c-means clustering algorithms. Here, the author identifies some similarities and differences between the hard and fuzzy c-Means (HCM/FCM) or ISODATA algorithms and Kohonen's self-organizing approach. The author concludes that some differences are significant, but at the same time there may be some important unknown relationships between the two methodologies. Several avenues of research are proposed.
SAW Classification Algorithm for Chinese Text Classification
Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang
2015-01-01
Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...
Evolving Shepherding Behavior with Genetic Programming Algorithms
Brulé, Joshua; Engel, Kevin; Fung, Nick; Julien, Isaac
2016-01-01
We apply genetic programming techniques to the `shepherding' problem, in which a group of one type of animal (sheep dogs) attempts to control the movements of a second group of animals (sheep) obeying flocking behavior. Our genetic programming algorithm evolves an expression tree that governs the movements of each dog. The operands of the tree are hand-selected features of the simulation environment that may allow the dogs to herd the sheep effectively. The algorithm uses tournament-style sel...
Spectral Representations of Uncertainty: Algorithms and Applications
Energy Technology Data Exchange (ETDEWEB)
George Em Karniadakis
2005-04-24
The objectives of this project were: (1) Develop a general algorithmic framework for stochastic ordinary and partial differential equations. (2) Set polynomial chaos method and its generalization on firm theoretical ground. (3) Quantify uncertainty in large-scale simulations involving CFD, MHD and microflows. The overall goal of this project was to provide DOE with an algorithmic capability that is more accurate and three to five orders of magnitude more efficient than the Monte Carlo simulation.
Algorithms, architectures and information systems security
Sur-Kolay, Susmita; Nandy, Subhas C; Bagchi, Aditya
2008-01-01
This volume contains articles written by leading researchers in the fields of algorithms, architectures, and information systems security. The first five chapters address several challenging geometric problems and related algorithms. These topics have major applications in pattern recognition, image analysis, digital geometry, surface reconstruction, computer vision and in robotics. The next five chapters focus on various optimization issues in VLSI design and test architectures, and in wireless networks. The last six chapters comprise scholarly articles on information systems security coverin
Dimensionality reduction in Bayesian estimation algorithms
G. W. Petty
2013-01-01
An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm. For this dataset, algorithm performance is found to be poor owing to an irreconcilable conflict between the need to find matches in the dependent database versus the need to exclude inappropriate matches. It is argued that the likelihood of such conflicts increase...