Journal articles: 'Dynamic programming. Data structures (Computer science)'

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KELLY, PAUL H. J., and OLAV BECKMANN. "GENERATIVE AND ADAPTIVE METHODS IN PERFORMANCE PROGRAMMING." Parallel Processing Letters 15, no. 03 (September 2005): 239–55. http://dx.doi.org/10.1142/s0129626405002192.

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Performance programming is characterized by the need to structure software components to exploit the context of use. Relevant context includes the target processor architecture, the available resources (number of processors, network capacity), prevailing resource contention, the values and shapes of input and intermediate data structures, the schedule and distribution of input data delivery, and the way the results are to be used. This paper concerns adapting to dynamic context: adaptive algorithms, malleable and migrating tasks, and application structures based on dynamic component composition. Adaptive computations use metadata associated with software components — performance models, dependence information, data size and shape. Computation itself is interwoven with planning and optimizing the computation process, using this metadata. This reflective nature motivates metaprogramming techniques. We present a research agenda aimed at developing a modelling framework which allows us to characterize both computation and dynamic adaptation in a way that allows systematic optimization.

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Ahn, Kook Jin, Graham Cormode, Sudipto Guha, Andrew McGregor, and Anthony Wirth. "Correlation Clustering in Data Streams." Algorithmica 83, no. 7 (March 13, 2021): 1980–2017. http://dx.doi.org/10.1007/s00453-021-00816-9.

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AbstractClustering is a fundamental tool for analyzing large data sets. A rich body of work has been devoted to designing data-stream algorithms for the relevant optimization problems such as k-center, k-median, and k-means. Such algorithms need to be both time and and space efficient. In this paper, we address the problem of correlation clustering in the dynamic data stream model. The stream consists of updates to the edge weights of a graph on n nodes and the goal is to find a node-partition such that the end-points of negative-weight edges are typically in different clusters whereas the end-points of positive-weight edges are typically in the same cluster. We present polynomial-time, $$O(n\cdot {{\,\mathrm{polylog}\,}}n)$$ O ( n · polylog n ) -space approximation algorithms for natural problems that arise. We first develop data structures based on linear sketches that allow the “quality” of a given node-partition to be measured. We then combine these data structures with convex programming and sampling techniques to solve the relevant approximation problem. Unfortunately, the standard LP and SDP formulations are not obviously solvable in $$O(n\cdot {{\,\mathrm{polylog}\,}}n)$$ O ( n · polylog n ) -space. Our work presents space-efficient algorithms for the convex programming required, as well as approaches to reduce the adaptivity of the sampling.

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ALDINUCCI, MARCO. "${\mathsf{eskimo}}$: EXPERIMENTING WITH SKELETONS IN THE SHARED ADDRESS MODEL." Parallel Processing Letters 13, no. 03 (September 2003): 449–60. http://dx.doi.org/10.1142/s0129626403001410.

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We discuss the lack of expressivity in some skeleton-based parallel programming frameworks. The problem is further exacerbated when approaching irregular problems and dealing with dynamic data structures. Shared memory programming has been argued to have substantial ease of programming advantages for this class of problems. We present the [Formula: see text] library which represents an attempt to merge the two programming models by introducing skeletons in a shared memory framework.

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MUKHOPADHYAY, RISHI, STEPHANIE IRAUSQUIN, CHRISTOPHER SCHMIDT, and HOMAYOUN VALAFAR. "DYNAFOLD: A DYNAMIC PROGRAMMING APPROACH TO PROTEIN BACKBONE STRUCTURE DETERMINATION FROM MINIMAL SETS OF RESIDUAL DIPOLAR COUPLINGS." Journal of Bioinformatics and Computational Biology 12, no. 01 (January 28, 2014): 1450002. http://dx.doi.org/10.1142/s0219720014500024.

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Residual Dipolar Couplings (RDCs) are a source of NMR data that can provide a powerful set of constraints on the orientation of inter-nuclear vectors, and are quickly becoming a larger part of the experimental toolset for molecular biologists. However, few reliable protocols exist for the determination of protein backbone structures from small sets of RDCs. DynaFold is a new dynamic programming algorithm designed specifically for this task, using minimal sets of RDCs collected in multiple alignment media. DynaFold was first tested utilizing synthetic data generated for the N – H , C α– H α, and C – N vectors of 1BRF, 1F53, 110M, and 3LAY proteins, with up to ±1 Hz error in three alignment media, and was able to produce structures with less than 1.9 Å of the original structures. DynaFold was then tested using experimental data, obtained from the Biological Magnetic Resonance Bank, for proteins PDBID:1P7E and 1D3Z using RDC data from two alignment media. This exercise yielded structures within 1.0 Å of their respective published structures in segments with high data density, and less than 1.9 Å over the entire protein. The same sets of RDC data were also used in comparisons with traditional methods for analysis of RDCs, which failed to match the accuracy of DynaFold's approach to structure determination.

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BLIEM, BERNHARD, MICHAEL MORAK, and STEFAN WOLTRAN. "D-FLAT: Declarative problem solving using tree decompositions and answer-set programming." Theory and Practice of Logic Programming 12, no. 4-5 (July 2012): 445–64. http://dx.doi.org/10.1017/s1471068412000129.

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AbstractIn this work, we propose Answer-Set Programming (ASP) as a tool for rapid prototyping of dynamic programming algorithms based on tree decompositions. In fact, many such algorithms have been designed, but only a few of them found their way into implementation. The main obstacle is the lack of easy-to-use systems which (i) take care of building a tree decomposition and (ii) provide an interface for declarative specifications of dynamic programming algorithms. In this paper, we present D-FLAT, a novel tool that relieves the user of having to handle all the technical details concerned with parsing, tree decomposition, the handling of data structures, etc. Instead, it is only the dynamic programming algorithm itself which has to be specified in the ASP language. D-FLAT employs an ASP solver in order to compute the local solutions in the dynamic programming algorithm. In the paper, we give a few examples illustrating the use of D-FLAT and describe the main features of the system. Moreover, we report experiments which show that ASP-based D-FLAT encodings for some problems outperform monolithic ASP encodings on instances of small treewidth.

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Merrell, David, and Anthony Gitter. "Inferring signaling pathways with probabilistic programming." Bioinformatics 36, Supplement_2 (December 2020): i822—i830. http://dx.doi.org/10.1093/bioinformatics/btaa861.

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Abstract Motivation Cells regulate themselves via dizzyingly complex biochemical processes called signaling pathways. These are usually depicted as a network, where nodes represent proteins and edges indicate their influence on each other. In order to understand diseases and therapies at the cellular level, it is crucial to have an accurate understanding of the signaling pathways at work. Since signaling pathways can be modified by disease, the ability to infer signaling pathways from condition- or patient-specific data is highly valuable. A variety of techniques exist for inferring signaling pathways. We build on past works that formulate signaling pathway inference as a Dynamic Bayesian Network structure estimation problem on phosphoproteomic time course data. We take a Bayesian approach, using Markov Chain Monte Carlo to estimate a posterior distribution over possible Dynamic Bayesian Network structures. Our primary contributions are (i) a novel proposal distribution that efficiently samples sparse graphs and (ii) the relaxation of common restrictive modeling assumptions. Results We implement our method, named Sparse Signaling Pathway Sampling, in Julia using the Gen probabilistic programming language. Probabilistic programming is a powerful methodology for building statistical models. The resulting code is modular, extensible and legible. The Gen language, in particular, allows us to customize our inference procedure for biological graphs and ensure efficient sampling. We evaluate our algorithm on simulated data and the HPN-DREAM pathway reconstruction challenge, comparing our performance against a variety of baseline methods. Our results demonstrate the vast potential for probabilistic programming, and Gen specifically, for biological network inference. Availability and implementation Find the full codebase at https://github.com/gitter-lab/ssps. Supplementary information Supplementary data are available at Bioinformatics online.

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Silapachote, Piyanuch, and Ananta Srisuphab. "Engineering Courses on Computational Thinking Through Solving Problems in Artificial Intelligence." International Journal of Engineering Pedagogy (iJEP) 7, no. 3 (September 29, 2017): 34. http://dx.doi.org/10.3991/ijep.v7i3.6951.

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Computational thinking sits at the core of every engineering and computing related discipline. It has increasingly emerged as its own subject in all levels of education. It is a powerful cornerstone for cognitive development, creative problem solving, algorithmic thinking and designs, and programming. How to effectively teach computational thinking skills poses real challenges and creates opportunities. Targeting entering computer science and engineering undergraduates, we resourcefully integrate elements from artificial intelligence (AI) into introductory computing courses. In addition to comprehension of the essence of computational thinking, practical exercises in AI enable inspirations of collaborative problem solving beyond abstraction, logical reasoning, critical and analytical thinking. Problems in machine intelligence systems intrinsically connect students to algorithmic oriented computing and essential mathematical foundations. Beyond knowledge representation, AI fosters a gentle introduction to data structures and algorithms. Focused on engaging mental tool, a computer is never a necessity. Neither coding nor programming is ever required. Instead, students enjoy constructivist classrooms designed to always be active, flexible, and highly dynamic. Learning to learn and reflecting on cognitive experiences, they rigorously construct knowledge from collectively solving exciting puzzles, competing in strategic games, and participating in intellectual discussions.

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POOLSAP, UNYANEE, YUKI KATO, KENGO SATO, and TATSUYA AKUTSU. "USING BINDING PROFILES TO PREDICT BINDING SITES OF TARGET RNAs." Journal of Bioinformatics and Computational Biology 09, no. 06 (December 2011): 697–713. http://dx.doi.org/10.1142/s0219720011005628.

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Prediction of RNA–RNA interaction is a key to elucidating possible functions of small non-coding RNAs, and a number of computational methods have been proposed to analyze interacting RNA secondary structures. In this article, we focus on predicting binding sites of target RNAs that are expected to interact with regulatory antisense RNAs in a general form of interaction. For this purpose, we propose bistaRNA, a novel method for predicting multiple binding sites of target RNAs. bistaRNA employs binding profiles that represent scores for hybridized structures, leading to reducing the computational cost for interaction prediction. bistaRNA considers an ensemble of equilibrium interacting structures and seeks to maximize expected accuracy using dynamic programming. Experimental results on real interaction data validate good accuracy and fast computation time of bistaRNA as compared with several competitive methods. Moreover, we aim to find new targets given specific antisense RNAs, which provides interesting insights into antisense RNA regulation. bistaRNA is implemented in C++. The program and Supplementary Material are available at .

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Li, Jin, Chengzhen Xu, Lei Wang, Hong Liang, Weixing Feng, Zhongxi Cai, Ying Wang, Wang Cong, and Yunlong Liu. "PSRna: Prediction of small RNA secondary structures based on reverse complementary folding method." Journal of Bioinformatics and Computational Biology 14, no. 04 (August 2016): 1643001. http://dx.doi.org/10.1142/s0219720016430010.

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Prediction of RNA secondary structures is an important problem in computational biology and bioinformatics, since RNA secondary structures are fundamental for functional analysis of RNA molecules. However, small RNA secondary structures are scarce and few algorithms have been specifically designed for predicting the secondary structures of small RNAs. Here we propose an algorithm named “PSRna” for predicting small-RNA secondary structures using reverse complementary folding and characteristic hairpin loops of small RNAs. Unlike traditional algorithms that usually generate multi-branch loops and 5[Formula: see text] end self-folding, PSRna first estimated the maximum number of base pairs of RNA secondary structures based on the dynamic programming algorithm and a path matrix is constructed at the same time. Second, the backtracking paths are extracted from the path matrix based on backtracking algorithm, and each backtracking path represents a secondary structure. To improve accuracy, the predicted RNA secondary structures are filtered based on their free energy, where only the secondary structure with the minimum free energy was identified as the candidate secondary structure. Our experiments on real data show that the proposed algorithm is superior to two popular methods, RNAfold and RNAstructure, in terms of sensitivity, specificity and Matthews correlation coefficient (MCC).

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WANG, SHENG, and WEI-MOU ZHENG. "CLePAPS: FAST PAIR ALIGNMENT OF PROTEIN STRUCTURES BASED ON CONFORMATIONAL LETTERS." Journal of Bioinformatics and Computational Biology 06, no. 02 (April 2008): 347–66. http://dx.doi.org/10.1142/s0219720008003461.

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Fast, efficient, and reliable algorithms for pairwise alignment of protein structures are in ever-increasing demand for analyzing the rapidly growing data on protein structures. CLePAPS is a tool developed for this purpose. It distinguishes itself from other existing algorithms by the use of conformational letters, which are discretized states of 3D segmental structural states. A letter corresponds to a cluster of combinations of the three angles formed by Cα pseudobonds of four contiguous residues. A substitution matrix called CLESUM is available to measure the similarity between any two such letters. CLePAPS regards an aligned fragment pair (AFP) as an ungapped string pair with a high sum of pairwise CLESUM scores. Using CLESUM scores as the similarity measure, CLePAPS searches for AFPs by simple string comparison. The transformation which best superimposes a highly similar AFP can be used to superimpose the structure pairs under comparison. A highly scored AFP which is consistent with several other AFPs determines an initial alignment. CLePAPS then joins consistent AFPs guided by their similarity scores to extend the alignment by several "zoom-in" iteration steps. A follow-up refinement produces the final alignment. CLePAPS does not implement dynamic programming. The utility of CLePAPS is tested on various protein structure pairs.

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Miyao, Yusuke, and Jun'ichi Tsujii. "Feature Forest Models for Probabilistic HPSG Parsing." Computational Linguistics 34, no. 1 (March 2008): 35–80. http://dx.doi.org/10.1162/coli.2008.34.1.35.

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Probabilistic modeling of lexicalized grammars is difficult because these grammars exploit complicated data structures, such as typed feature structures. This prevents us from applying common methods of probabilistic modeling in which a complete structure is divided into sub-structures under the assumption of statistical independence among sub-structures. For example, part-of-speech tagging of a sentence is decomposed into tagging of each word, and CFG parsing is split into applications of CFG rules. These methods have relied on the structure of the target problem, namely lattices or trees, and cannot be applied to graph structures including typed feature structures. This article proposes the feature forest model as a solution to the problem of probabilistic modeling of complex data structures including typed feature structures. The feature forest model provides a method for probabilistic modeling without the independence assumption when probabilistic events are represented with feature forests. Feature forests are generic data structures that represent ambiguous trees in a packed forest structure. Feature forest models are maximum entropy models defined over feature forests. A dynamic programming algorithm is proposed for maximum entropy estimation without unpacking feature forests. Thus probabilistic modeling of any data structures is possible when they are represented by feature forests. This article also describes methods for representing HPSG syntactic structures and predicate-argument structures with feature forests. Hence, we describe a complete strategy for developing probabilistic models for HPSG parsing. The effectiveness of the proposed methods is empirically evaluated through parsing experiments on the Penn Treebank, and the promise of applicability to parsing of real-world sentences is discussed.

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SOLIMAN, MOSTAFA I., and STANISLAV G. SEDUKHIN. "PERFORMANCE EVALUATION OF BLAS ON THE TRIDENT PROCESSOR." Parallel Processing Letters 15, no. 04 (December 2005): 407–14. http://dx.doi.org/10.1142/s0129626405002325.

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Different subtasks of an application usually have different computational, memory, and I/O requirements that result in different needs for computer capabilities. Thus, the more appropriate approach for both high performance and simple programming model is designing a processor having multi-level instruction set architecture (ISA). This leads to high performance and minimum executable code size. Since the fundamental data structures for a wide variety of existing applications are scalar, vector, and matrix, our research Trident processor has three-level ISA executed on zero-, one-, and two-dimensional arrays of data. These levels are used to express a great amount of fine-grain data parallelism to a processor instead of the dynamical extraction by a complicated logic or statically with compilers. This reduces the design complexity and provides high-level programming interface to hardware. In this paper, the performance of Trident processor is evaluated on BLAS, which represent the kernel operations of many data parallel applications. We show that Trident processor proportionally reduces the number of clock cycles per floating-point operation by increasing the number of execution datapaths.

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Huang, Liang, He Zhang, Dezhong Deng, Kai Zhao, Kaibo Liu, David A. Hendrix, and David H. Mathews. "LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search." Bioinformatics 35, no. 14 (July 2019): i295—i304. http://dx.doi.org/10.1093/bioinformatics/btz375.

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Abstract Motivation Predicting the secondary structure of an ribonucleic acid (RNA) sequence is useful in many applications. Existing algorithms [based on dynamic programming] suffer from a major limitation: their runtimes scale cubically with the RNA length, and this slowness limits their use in genome-wide applications. Results We present a novel alternative O(n3)-time dynamic programming algorithm for RNA folding that is amenable to heuristics that make it run in O(n) time and O(n) space, while producing a high-quality approximation to the optimal solution. Inspired by incremental parsing for context-free grammars in computational linguistics, our alternative dynamic programming algorithm scans the sequence in a left-to-right (5′-to-3′) direction rather than in a bottom-up fashion, which allows us to employ the effective beam pruning heuristic. Our work, though inexact, is the first RNA folding algorithm to achieve linear runtime (and linear space) without imposing constraints on the output structure. Surprisingly, our approximate search results in even higher overall accuracy on a diverse database of sequences with known structures. More interestingly, it leads to significantly more accurate predictions on the longest sequence families in that database (16S and 23S Ribosomal RNAs), as well as improved accuracies for long-range base pairs (500+ nucleotides apart), both of which are well known to be challenging for the current models. Availability and implementation Our source code is available at https://github.com/LinearFold/LinearFold, and our webserver is at http://linearfold.org (sequence limit: 100 000nt). Supplementary information Supplementary data are available at Bioinformatics online.

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HEUVELINE, VINCENT, and JONAS LATT. "THE OPENLB PROJECT: AN OPEN SOURCE AND OBJECT ORIENTED IMPLEMENTATION OF LATTICE BOLTZMANN METHODS." International Journal of Modern Physics C 18, no. 04 (April 2007): 627–34. http://dx.doi.org/10.1142/s0129183107010875.

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The OpenLB project aims at setting up an open source implementation of lattice Boltzmann methods in an object oriented framework. The code, which is written in C ++, is intended to be used both by application programmers and by developers who may add their own particular dynamics. It supports advanced data structures that take into account complex geometries and parallel program executions. The programming concepts rely strongly on dynamic genericity through the use of object oriented interfaces as well as static genericity by means of templates. This design allows a straightforward and intuitive implementation of lattice Boltzmann models with almost no loss of efficiency. The aim of this paper is to introduce the OpenLB project and to depict the underlying structure leading to a powerful development tool for lattice Boltzmann methods.

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Entzian, Gregor, Ivo L. Hofacker, Yann Ponty, Ronny Lorenz, and Andrea Tanzer. "RNAxplorer: harnessing the power of guiding potentials to sample RNA landscapes." Bioinformatics 37, no. 15 (February 4, 2021): 2126–33. http://dx.doi.org/10.1093/bioinformatics/btab066.

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Abstract Motivation Predicting the folding dynamics of RNAs is a computationally difficult problem, first and foremost due to the combinatorial explosion of alternative structures in the folding space. Abstractions are therefore needed to simplify downstream analyses, and thus make them computationally tractable. This can be achieved by various structure sampling algorithms. However, current sampling methods are still time consuming and frequently fail to represent key elements of the folding space. Method We introduce RNAxplorer, a novel adaptive sampling method to efficiently explore the structure space of RNAs. RNAxplorer uses dynamic programming to perform an efficient Boltzmann sampling in the presence of guiding potentials, which are accumulated into pseudo-energy terms and reflect similarity to already well-sampled structures. This way, we effectively steer sampling toward underrepresented or unexplored regions of the structure space. Results We developed and applied different measures to benchmark our sampling methods against its competitors. Most of the measures show that RNAxplorer produces more diverse structure samples, yields rare conformations that may be inaccessible to other sampling methods and is better at finding the most relevant kinetic traps in the landscape. Thus, it produces a more representative coarse graining of the landscape, which is well suited to subsequently compute better approximations of RNA folding kinetics. Availabilityand implementation https://github.com/ViennaRNA/RNAxplorer/. Supplementary information Supplementary data are available at Bioinformatics online.

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Shehab, Tariq, Reza Haghighat, Kiran K. Sajjan, and Vahid Balali. "Prioritization of K-12 School Maintenance Construction Projects Using Genetic Algorithm and Dynamic Programming Models." Journal of Information Technology in Construction 26 (March 23, 2021): 112–27. http://dx.doi.org/10.36680/j.itcon.2021.007.

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High quality education standards and safe learning environments are the fundamental goals of most educational systems. One step towards achieving these goals is to keep existing school facilities in good working conditions through continues repair and maintenance programs. Due to limited resources, efficient use of allocated funds is necessary. This paper presents an optimization tool using Genetic Algorithm (GA) and Dynamic Programming (DP) that manages the expenses of K-12 school rehabilitation projects. These models help to find the optimum solutions among the given data through mutations and crossover in deriving a possible solution to a multi-layered problem. The proposed optimization tools maximize the benefits of K-12 school repair projects, and focus primarily on serving at-risk students, including those who come from low-income families. To demonstrate the use and capabilities of the proposed tool, a case study is presented. The results revealed by the case study show high potential for better management of school rehabilitation projects and better provision of service to disadvantaged students.

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Glicksberg, Benjamin S., Boris Oskotsky, Phyllis M. Thangaraj, Nicholas Giangreco, Marcus A. Badgeley, Kipp W. Johnson, Debajyoti Datta, et al. "PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model." Bioinformatics 35, no. 21 (June 19, 2019): 4515–18. http://dx.doi.org/10.1093/bioinformatics/btz409.

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AbstractMotivationElectronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge.ResultsWe present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes.Availability and implementationPatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu.Supplementary informationSupplementary data are available at Bioinformatics online.

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Chen, Chun-Chi, Hyundoo Jeong, Xiaoning Qian, and Byung-Jun Yoon. "TOPAS: network-based structural alignment of RNA sequences." Bioinformatics 35, no. 17 (January 10, 2019): 2941–48. http://dx.doi.org/10.1093/bioinformatics/btz001.

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Abstract Motivation For many RNA families, the secondary structure is known to be better conserved among the member RNAs compared to the primary sequence. For this reason, it is important to consider the underlying folding structures when aligning RNA sequences, especially for those with relatively low sequence identity. Given a set of RNAs with unknown structures, simultaneous RNA alignment and folding algorithms aim to accurately align the RNAs by jointly predicting their consensus secondary structure and the optimal sequence alignment. Despite the improved accuracy of the resulting alignment, the computational complexity of simultaneous alignment and folding for a pair of RNAs is O(N6), which is too costly to be used for large-scale analysis. Results In order to address this shortcoming, in this work, we propose a novel network-based scheme for pairwise structural alignment of RNAs. The proposed algorithm, TOPAS, builds on the concept of topological networks that provide structural maps of the RNAs to be aligned. For each RNA sequence, TOPAS first constructs a topological network based on the predicted folding structure, which consists of sequential edges and structural edges weighted by the base-pairing probabilities. The obtained networks can then be efficiently aligned by using probabilistic network alignment techniques, thereby yielding the structural alignment of the RNAs. The computational complexity of our proposed method is significantly lower than that of the Sankoff-style dynamic programming approach, while yielding favorable alignment results. Furthermore, another important advantage of the proposed algorithm is its capability of handling RNAs with pseudoknots while predicting the RNA structural alignment. We demonstrate that TOPAS generally outperforms previous RNA structural alignment methods on RNA benchmarks in terms of both speed and accuracy. Availability and implementation Source code of TOPAS and the benchmark data used in this paper are available at https://github.com/bjyoontamu/TOPAS.

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Le, Phuoc Luong, Thien-My Dao, and Amin Chaabane. "BIM-based framework for temporary facility layout planning in construction site." Construction Innovation 19, no. 3 (July 7, 2019): 424–64. http://dx.doi.org/10.1108/ci-06-2018-0052.

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Purpose This paper aims to propose an innovative building information modelling (BIM)-based framework for multi-objective and dynamic temporary construction site layout design (SLD), which uses a hybrid approach of systematic layout planning (SLP) and mathematical modelling. Design/methodology/approach The hybrid approach, which follows a step-by-step process for site layout planning, is designed to facilitate both qualitative and quantitative data collection and processing. BIM platform is usedto facilitate the determination of the required quantitative data, while the qualitative data are generated through knowledge-based rules. Findings The multi-objective layout model represents two important aspects: layout cost and adjacency score. The result shows that the model meets construction managers’ requirements in not only saving cost but also assuring the preferences of temporary facility relationships. This implies that the integration of SLP and mathematical layout modelling is an appropriate approach to deliver practical multi-objective SLD solutions. Research limitations/implications The proposed framework is expected to serve as a solution, for practical application, which takes the advantage of technologies in data collection and processing. Besides, this paper demonstrates, by using numerical experimentation and applying Microsoft Excel Solver for site layout optimisation, how to reduce the complexity in mathematical programming for construction managers. Originality/value The original contribution of this paper is the attempt of developing a framework in which all data used for the site layout modelling are collected and processed using a systematic approach, instead of being predetermined, as in many previous studies.

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Hains, Gaétan, Frédéric Loulergue, and John Mullins. "Concrete data structures and functional parallel programming." Theoretical Computer Science 258, no. 1-2 (May 2001): 233–67. http://dx.doi.org/10.1016/s0304-3975(00)00010-4.

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Elmasry, Amr, Meng He, J. Ian Munro, and Patrick K. Nicholson. "Dynamic range majority data structures." Theoretical Computer Science 647 (September 2016): 59–73. http://dx.doi.org/10.1016/j.tcs.2016.07.039.

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Leaver-Fay, Andrew, Yuanxin Liu, Jack Snoeyink, and Xueyi Wang. "Faster placement of hydrogens in protein structures by dynamic programming." ACM Journal of Experimental Algorithmics 12 (June 2008): 1–16. http://dx.doi.org/10.1145/1227161.1227167.

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J., Girish Raguvir, Manas Jyoti Kashyop, and N. S. Narayanaswamy. "Dynamic data structures for interval coloring." Theoretical Computer Science 838 (October 2020): 126–42. http://dx.doi.org/10.1016/j.tcs.2020.06.024.

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Donner, Klaus. "Data structures and dynamic programming background for editing highly structured texts." Annals of Operations Research 16, no. 1 (December 1988): 267–80. http://dx.doi.org/10.1007/bf02283748.

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Pucher, Krzysztof, and Dariusz Polok. "Analysis of Timings in Networks that Use TCP/IP or UDP/IP Protocols for Communication with Industrial Controllers in Mechatronic Systems." Solid State Phenomena 144 (September 2008): 94–99. http://dx.doi.org/10.4028/www.scientific.net/ssp.144.94.

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In pace with the technical progress in controllability of mechatronic systems including machines and industrial equipment, the systems of industrial controllers (both PLC and microprocessor ones) more and more frequently use Ethernet-based networks for communication with supervising centres and surveillance systems. The Internet offers unsurpassed opportunities of remote programming as well as remote development, debugging and tuning the existing control software. Nowadays, supporting the remote tools and facilities is the essential requirement that is mandatory when decisions on purchase and implementation of industrial controllers are made. It is the underlying reason to launch more extensive research in that field. The presented paper describes dedicated software that has been developed to enable communication over the Internet within dispersed control systems. The system makes it possible to transmit and to receive short messages to and from the controlled actuators as well as to perform basic tasks related to management of data flow in networks that use TCD and UDP protocols. The special attention was paid to dynamic phenomena of the data exchange process. It is an issue of crucial importance within dispersed systems of industrial controllers and it assures efficient operation of the entire system owing to timely and quick respond to fast-changing control signals. Data exchange was carried out with the use of so-called primitives for Berkeley sockets that serve as primary structures within the network and are capable to perform basic operation such as creation and destruction, assigning network addresses to the sockets, establishing connections, transmission (broadcasting), receiving, etc. To measure time intervals of communication sessions the authors took advantage of functional features of contemporary motherboards of PC computers. In particular, the function of the API counter was used as it allows to readout the fast internal 64-bit counter which, in consequence, enabled measurement of time gaps with accuracy up to single microseconds. The described software performs tests of communication facilities in terms of their applicability to fast data exchange between field control modules of the control system and the CPU, whereas the entire communication is performed via Internet. Therefore the reaction time of a hypothetical field controller in respond to switchovers of the input signals or interrupt events can be measured. The communication and measurements were performed over local and national internet networks as well as for GPRS networks. Measurement results are presented in a compact form of tables that is suitable for further analysis. The presented system is able to transmit diagnostic information therefore it can be also used for integrated diagnostics of mechatronic systems as well as for location and analysis of possible failures within the in-field systems.

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Sakai, Hiroshi, Hiroaki Ishii, and Junzo Watada. "Special Issue on Forum for Interdisciplinary Mathematics 2013." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 6 (November 20, 2014): 927–28. http://dx.doi.org/10.20965/jaciii.2014.p0927.

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This special issue focuses on recent research in interdisciplinary mathematics and mathematical sciences. For the last four decades, the Forum for Interdisciplinary Mathematics (FIM), a society for researchers in mathematical sciences, has focused on mathematics, combinatorics, statistics, operations research, computer science, fuzzy sets, rough sets, bioinformatics, etc. The 22nd International Conference of FIM on Interdisciplinary Mathematics, Statistics and Computational Techniques (IMSCT 2013-FIM XXII) was held in Kitakyushu, Japan, on November 10-12, 2013. This conference was organized by the International Society of Management (ISME international), the Graduate School of Information, Production and Systems, Waseda University, in conjunction with FIM. IMSCT 2013-FIM XXII was attended by faculty members, researchers, specialists, and graduate students from around the world. The 50 papers presented included keynote speeches by Professor Bhu Dev Sharma, Professor Milan Vlach, and Professor Tomonari Suzuki, together with five plenary talks. To promote FIMfs activities, guest editors had also planned to invite public participation in this special issue accepting nine papers, four selected papers from the conference and five papers closely related to this special issue. Each paper underwent strict peer reviews. The first paper, Crisp and Fuzzy Granular Hierarchical Structures Generated from a Free Monoid, by Tetsuya Murai, Sadaaki Miyamoto, Masahiro Inuiguchi, Yasuo Kudo, and Seiki Akama, proposes a granular hierarchy, and characterizes the mathematical structure based on fuzzy multisets, fuzzy sets, and rough multisets. This granular hierarchy includes Yagerfs fuzzy multisets and Zadehfs fuzzy sets, offering a general framework. The second paper, Variable Neighborhood Model for Agent Control Introducing Accessibility Relations Between Agents with Linear Temporal Logic, by Seiki Ubukata, Tetsuya Murai, Yasuo Kudo, and Seiki Akama, discusses a variable neighborhood model based on a Kripke framework, and applies this model to introducing the agentfs personal space. The authorsf research is an attempt to realize the agentfs personality. The third paper, Estimating Writing Neatness from Online Handwritten Data, by Motoki Miura and Takamichi Toda, considers the neatness of handwritten notes in using the authorsf Air-TransNote digital pen technology. The digital pen reports physical information, and authors estimate neatness by using this physical information. Based on experiments, the authors conclude variance in pen speed, average angular point, and average pen speed are the most important features for evaluating handwriting neatness. The fourth paper, Application of Rough Set-Based Information Analysis to Questionnaire Data, by Naoto Yamaguchi, Mao Wu, Michinori Nakata, and Hiroshi Sakai, applies the authorsf rough non-deterministic information analysis (RNIA) to questionnaire data and question-answering. Experimental results indicate the power of the getRNIA software tool developed by the authors and possibilities for new types of data analysis. The fifth paper, Analysis of Consistent Equilibria in a Mixed Duopoly, by Vyacheslav V. Kalashnikov, Vladimir A. Bulavsky, Nataliya I. Kalashnykova, Junzo Watada, and Diego Je Jes?s Hern?ndez-Rodr?guez, investigates a model of partially mixed duopoly with conjectured variations in equilibrium. They establish the existence and the uniqueness for conjectured variations in equilibrium for any set of feasible conjectures, and prove the existence theorem for interior equilibrium. The sixth paper, Mixed Oligopoly: Analysis of Consistent Equilibria, twinned with the fifth paper and by the same authors, deals with a case of an oligopoly. Under condition of the oligopoly, the authors conclude results similar to those of the fifth paper. They also provide numerical experiments illustrating the differences among partially mixed, mixed, and classical oligopoly cases. The seventh paper, Interest Rate Liberalization and Fiscal Policy in China: A New Keynesian DSGE Model, by Bing Xu, Qiuqin He, Xiaowen Hu, and Shangfeng Zhang, studies the relationships between the liberalization of the interest rate and the fiscal policy in China. The authors propose new Keynesian DSGE analysis, that handles many more factors than the previous model. The new model is applied to analyzing economic data, and the modelfs validity is examined based on experiments. The eighth paper, Mutually Dependent Markov Decision Processes, by Toshiharu Fujita and Akifumi Kira, investigates dynamic programming and the Markov decision process. The authors propose a new advanced framework, called a mutually dependent Markov decision process. Each process is precisely formulated in dynamic programming style, and simulated by using a numeric example. This paper develops a framework for complex multi-stage decision processes. The ninth and last paper, Monthly Maximum Accumulated Precipitation Forecasting Using Local Precipitation Data and Global Climate Modes, by Junaida Binti Sulaiman, Herdianti Darwis, and Hideo Hirose, considers the problem of precipitation forecasting in Malaysia, and proposes soft-computing-based analysis methods. In the four methods proposed, multi-neural network-PSO showed the best performance for previous data sets. The development of such an analysis method is expected to make precipitation forecasting more accurate. In closing, the guest editors would like to acknowledge the efforts of all of the authors for their generous and insightful contributions. We are grateful to the reviewers for their incisive on-time reviews. Profs. P.V. Subrahmanyam, D.S. Hooda, Kalpana K. Mahajan, and Tumulesh Solanky, served as co-chairs and guest editors at IMSCT 2013-FIM XXII, and we acknowledge their invaluable work at this conference. We are grateful to Professors Toshio Fukuda and Kaoru Hirota, Chief Editors of JACIII, for inviting us to serve as Guest Editors of this Journal and to Ms. Reiko Ohta of Fuji Technology Press for her ongoing assistance in the publication of this special issue.

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HEDAR, ABDEL-RAHMAN, EMAD MABROUK, and MASAO FUKUSHIMA. "TABU PROGRAMMING: A NEW PROBLEM SOLVER THROUGH ADAPTIVE MEMORY PROGRAMMING OVER TREE DATA STRUCTURES." International Journal of Information Technology & Decision Making 10, no. 02 (March 2011): 373–406. http://dx.doi.org/10.1142/s0219622011004373.

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Since the first appearance of the Genetic Programming (GP) algorithm, extensive theoretical and application studies on it have been conducted. Nowadays, the GP algorithm is considered one of the most important tools in Artificial Intelligence (AI). Nevertheless, several questions have been raised about the complexity of the GP algorithm and the disruption effect of the crossover and mutation operators. In this paper, the Tabu Programming (TP) algorithm is proposed to employ the search strategy of the classical Tabu Search algorithm with the tree data structure. Moreover, the TP algorithm exploits a set of local search procedures over a tree space in order to mitigate the drawbacks of the crossover and mutation operators. Extensive numerical experiments are performed to study the performance of the proposed algorithm for a set of benchmark problems. The results of those experiments show that the TP algorithm compares favorably to recent versions of the GP algorithm in terms of computational efforts and the rate of success. Finally, we present a comprehensive framework called Meta-Heuristics Programming (MHP) as general machine learning tools.

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Hendren, Laurie J., and Guang R. Gao. "Designing programming languages for the analyzability of pointer data structures." Computer Languages 19, no. 2 (April 1993): 119–34. http://dx.doi.org/10.1016/0096-0551(93)90006-m.

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Jianhong, Wang. "Dynamic Programming in Data Driven Model Predictive Control?" WSEAS TRANSACTIONS ON SYSTEMS 20 (July 21, 2021): 170–77. http://dx.doi.org/10.37394/23202.2021.20.19.

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In this short note, one data driven model predictive control is studied to design the optimal control sequence. The idea of data driven means the actual output value in cost function for model predictive control is identi_ed through input-output observed data in case of unknown but bounded noise and martingale di_erence sequence. After substituting the identi_ed actual output in cost function, the total cost function in model predictive control is reformulated as the other standard form, so that dynamic programming can be applied directly. As dynamic programming is only used in optimization theory, so to extend its advantage in control theory, dynamic programming algorithm is proposed to construct the optimal control sequence. Furthermore, stability analysis for data drive model predictive control is also given based on dynamic programming strategy. Generally, the goal of this short note is to bridge the dynamic programming, system identi_cation and model predictive control. Finally, one simulation example is used to prove the e_ciency of our proposed theory

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Gagie, Travis, Meng He, and Gonzalo Navarro. "Compressed Dynamic Range Majority and Minority Data Structures." Algorithmica 82, no. 7 (February 17, 2020): 2063–86. http://dx.doi.org/10.1007/s00453-020-00687-6.

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Henzinger, Monika R. "Improved Data Structures for Fully Dynamic Biconnectivity." SIAM Journal on Computing 29, no. 6 (January 2000): 1761–815. http://dx.doi.org/10.1137/s0097539794263907.

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32

Kenyon-Mathieu, Claire M., and Jeffrey Scott Vitter. "The Maximum Size of Dynamic Data Structures." SIAM Journal on Computing 20, no. 5 (October 1991): 807–23. http://dx.doi.org/10.1137/0220050.

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Smid, Michiel H. M., Mark H. Overmars, Leen Torenvliet, and Peter van Emde Boas. "Maintaining multiple representations of dynamic data structures." Information and Computation 83, no. 2 (November 1989): 206–33. http://dx.doi.org/10.1016/0890-5401(89)90058-8.

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Seco, João, Ricardo Silva, and Margarida Piriquito. "Component J: A component-based programming language with dynamic reconfiguration." Computer Science and Information Systems 5, no. 2 (2008): 63–86. http://dx.doi.org/10.2298/csis0802063s.

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This paper describes an evolution of the ComponentJ programming language, a component-based Java-like programming language where composition is the chosen structuring mechanism. ComponentJ constructs allow for the high-level specification of component structures, which are the basis for the definition of compound objects. In this paper we present a new language design for ComponentJ which is more flexible and also allows the dynamic reconfiguration of objects. The manipulation of components and composition operations at the programming language level allows for the compile time verification, by a type system, of safety structural properties of ComponentJ programs. This work is based on earlier fundamental results where the main concepts are presented and justified in the form of a core component calculus. .

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35

Moor, Oege De. "Categories, relations and dynamic programming." Mathematical Structures in Computer Science 4, no. 1 (March 1994): 33–69. http://dx.doi.org/10.1017/s0960129500000360.

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Dynamic programming is a strategy for solving optimisation problems. In this paper, we show how many problems that may be solved by dynamic programming are instances of the same abstract specification. This specification is phrased using the calculus of relations offered by topos theory. The main theorem underlying dynamic programming can then be proved by straightforward equational reasoning.The generic specification of dynamic programming makes use of higher-order operators on relations, akin to the fold operators found in functional programming languages. In the present context, a data type is modelled as an initial F-algebra, where F is an endofunctor on the topos under consideration. The mediating arrows from this initial F-algebra to other F-algebras are instances of fold – but only for total functions. For a regular category ε, it is possible to construct a category of relations Rel(ε). When a functor between regular categories is a so-called relator, it can be extended (in some canonical way) to a functor between the corresponding categories of relations. Applied to an endofunctor on a topos, this process of extending functors preserves initial algebras, and hence fold can be generalised from functions to relations.It is well-known that the use of dynamic programming is governed by the principle of optimality. Roughly, the principle of optimality says that an optimal solution is composed of optimal solutions to subproblems. In a first attempt, we formalise the principle of optimality as a distributivity condition. This distributivity condition is elegant, but difficult to check in practice. The difficulty arises because we consider minimum elements with respect to a preorder, and therefore minimum elements are not unique. Assuming that we are working in a Boolean topos, it can be proved that monotonicity implies distributivity, and this monotonicity condition is easy to verify in practice.

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RAUBER, THOMAS, and GUDULA RÜNGER. "A DATA RE-DISTRIBUTION LIBRARY FOR MULTI-PROCESSOR TASK PROGRAMMING." International Journal of Foundations of Computer Science 17, no. 02 (April 2006): 251–70. http://dx.doi.org/10.1142/s0129054106003814.

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Multiprocessor task (M-task) programming is a suitable parallel programming model for coding application problems with an inherent modular structure. An M-task can be executed on a group of processors of arbitrary size, concurrently to other M-tasks of the same application program. The data of a multiprocessor task program usually include composed data structures, like vectors or arrays. For distributed memory machines or cluster platforms, those composed data structures are distributed within one or more processor groups. Thus, a concise parallel programming model for M-tasks requires a standardized distributed data format for composed data structures. Additionally, functions for data re-distribution with respect to different data distributions and different processor group layouts are needed to glue program parts together. In this paper, we present a data re-distribution library which extends the M-task programming with Tlib, a library providing operations to split processor groups and to map M-tasks to processor groups.

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Zhang, Nan, Benjamin D. Leibowicz, and Grani A. Hanasusanto. "Optimal Residential Battery Storage Operations Using Robust Data-Driven Dynamic Programming." IEEE Transactions on Smart Grid 11, no. 2 (March 2020): 1771–80. http://dx.doi.org/10.1109/tsg.2019.2942932.

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LAUER, TOBIAS, THOMAS OTTMANN, and AMITAVA DATTA. "UPDATE-EFFICIENT DATA STRUCTURES FOR DYNAMIC IP ROUTER TABLES." International Journal of Foundations of Computer Science 18, no. 01 (February 2007): 139–61. http://dx.doi.org/10.1142/s0129054107004607.

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We show that two data structures, min-augmented range tree and priority search pennant, efficiently support all the required operations for updatable IP router tables and argue that both structures are better suited for the one-dimensional dynamic IP lookup problem than the priority search tree (PST) used in a previous solution. It is possible to maintain both structures in time O(1) after a rotation, while PST with n elements may require Ω( log n) steps for a single rotation. Therefore, the proposed structures can be balanced using a larger class of rebalancing schemes compared to PST. Both structures are also of interest independently of the IP lookup problem and may be used as attractive implementations of priority search queues in other contexts as well.

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LAUER, TOBIAS, THOMAS OTTMANN, and AMITAVA DATTA. "UPDATE-EFFICIENT DATA STRUCTURES FOR DYNAMIC IP ROUTER TABLES." International Journal of Foundations of Computer Science 18, no. 02 (April 2007): 295–317. http://dx.doi.org/10.1142/s0129054107004693.

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We show that two data structures, min-augmented range tree and priority search pennant, efficiently support all the required operations for updatable IP router tables and argue that both structures are better suited for the one-dimensional dynamic IP lookup problem than the priority search tree (PST) used in a previous solution. It is possible to maintain both structures in time O(1) after a rotation, while PST with n elements may require Ω( log n) steps for a single rotation. Therefore, the proposed structures can be balanced using a larger class of rebalancing schemes compared to PST. Both structures are also of interest independently of the IP lookup problem and may be used as attractive implementations of priority search queues in other contexts as well.

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40

Ben-Amram and Galil. "Lower Bounds for Dynamic Data Structures on Algebraic RAMs." Algorithmica 32, no. 3 (March 2002): 364–95. http://dx.doi.org/10.1007/s00453-001-0079-6.

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Elhenawy, Mohammed, Hao Chen, and Hesham A. Rakha. "Dynamic travel time prediction using data clustering and genetic programming." Transportation Research Part C: Emerging Technologies 42 (May 2014): 82–98. http://dx.doi.org/10.1016/j.trc.2014.02.016.

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Li, Guoqiang, Daniel Görges, and Chaoxu Mu. "Integrated adaptive dynamic programming for data-driven optimal controller design." Neurocomputing 403 (August 2020): 143–52. http://dx.doi.org/10.1016/j.neucom.2020.04.095.

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GAVA, FRÉDÉRIC. "A MODULAR IMPLEMENTATION OF DATA STRUCTURES IN BULK-SYNCHRONOUS PARALLEL ML." Parallel Processing Letters 18, no. 01 (March 2008): 39–53. http://dx.doi.org/10.1142/s0129626408003211.

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A functional data-parallel language called BSML has been designed for programming Bulk-Synchronous Parallel algorithms. Many sequential algorithms do not have parallel counterparts and many non-computer science researchers do not want to deal with parallel programming. In sequential programming environments, common data structures are often provided through reusable libraries to simplify the development of applications. A parallel representation of such data structures is thus a solution for writing parallel programs without suffering from disadvantages of all the features of a parallel language. In this paper we describe a modular implementation in BSML of some data structures and show how those data types can address the needs of many potential users of parallel machines who have so far been deterred by the complexity of parallelizing code.

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Tang, Wentao, and Prodromos Daoutidis. "Distributed adaptive dynamic programming for data-driven optimal control." Systems & Control Letters 120 (October 2018): 36–43. http://dx.doi.org/10.1016/j.sysconle.2018.08.002.

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Guessarian, Irène. "Some Fixpoint Techniques in Algebraic Structures and Applications to Computer Science." Fundamenta Informaticae 10, no. 4 (October 1, 1987): 387–413. http://dx.doi.org/10.3233/fi-1987-10405.

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This paper recalls some fixpoint theorems in ordered algebraic structures and surveys some ways in which these theorems are applied in computer science. We describe via examples three main types of applications: in semantics and proof theory, in logic programming and in deductive data bases.

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Golin, Mordecai, Rajeev Raman, Christian Schwarz, and Michiel Smid. "Randomized Data Structures for the Dynamic Closest-Pair Problem." SIAM Journal on Computing 27, no. 4 (August 1998): 1036–72. http://dx.doi.org/10.1137/s0097539794277718.

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Zhao, Hui, Meikang Qiu, Min Chen, and Keke Gai. "Cost-aware optimal data allocations for multiple dimensional heterogeneous memories using dynamic programming in big data." Journal of Computational Science 26 (May 2018): 402–8. http://dx.doi.org/10.1016/j.jocs.2016.06.002.

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Zhang, Wei, Tingjun Hou, Xuebin Qiao, and Xiaojie Xu. "Some Basic Data Structures and Algorithms for Chemical Generic Programming." Journal of Chemical Information and Computer Sciences 44, no. 5 (September 2004): 1571–75. http://dx.doi.org/10.1021/ci049938s.

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Xie, Junjie, Lijun Lyu, Yuhui Deng, and Laurence T. Yang. "Improving Routing Performance via Dynamic Programming in Large-Scale Data Centers." IEEE Internet of Things Journal 2, no. 4 (August 2015): 321–28. http://dx.doi.org/10.1109/jiot.2014.2386326.

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Bishop, J. "Introduction to Pascal and Structured Design; Pascal plus Data Structures, Algorithms and Advanced Programming." Computer Journal 35, no. 3 (June 1, 1992): 255. http://dx.doi.org/10.1093/comjnl/35.3.255.

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Journal articles on the topic 'Dynamic programming. Data structures (Computer science)'

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