Program Graph Research Articles

Goal programming approach for political districting in Santa Catarina State: Brazil

In the Brazilian judiciary, the Electoral Registry Offices (EROs) are responsible for managing the Brazilian electoral districts. Moreover, not only do they organize elections in their district, but they are also responsible for managing the registration of electors and supervising the political parties. Brazil has a multi-party system with more than 35 political parties competing over the 295 cities of Santa Catarina state, which had over 4.98 million voters in 2017. In this context, we present a mixed integer model, with the concepts of goal programming and contiguity graph, to propose a more equilibrated distribution of political districts to Santa Catarina state. The mathematical model considers the political districting criteria (population balance, spatial contiguity, and compactness), and also considers the particularities of the Brazilian electoral system (minimum number of voters in an electoral district, maximum electoral zones per city, and so forth). The objective of the problem is to determine the optimum set of districts for the most efficient use of public resources and best service to the population. Therefore, there must be a balance of workload among the (EROs), i.e., a steady number of electors and nominating petitions per district. The solution proposed succeeded in presenting a set of districts with a better workload distribution while respecting all the districting criteria and the Brazilian legislation. Compared to the current situation, the model shows a reduction in the standard deviation of the electorate distribution per district of 7520 voters. The solution obtained by the proposed model for the Brazilian electoral system in the state of Santa Catarina may be used by any other of the 26 Brazilian states. The proposed model is a particularization of the classic political districting problem since it inserts complementary constraints to this classic problem from the operational research literature.

COMPUTER MODEL OF VIRTUAL SOCIAL NETWORK WITH RECOMMENDATION SYSTEM

The subject matter of the article is the process of modeling social networks. The goal is to develop a computer model of a social network with a recommendation system. The tasks to be solved are to research the methods of generating social networks, to realize the computer model of a social network with a recommender system. The methods used are graph theory, theory of algorithms, statistics theory, probability theory, object-oriented programming. The following results: the research of existing methods for modeling social networks was conducted, in particular, such social network models as the Barabasi-Albert model, the Erdős-Renyi model and the Bollobаs-Riordan model were considered. The concept of complex networks was considered. The research of the basic properties of graphs of social networks was considered. The social network computer model with a recommender system based on the modified Barabasi-Albert model with using graph database Neo4j and programming language Python was developed. The developed model allows to model a network with users and text posts and may contain following connections friends, follower, published, viewed, like, similar, recommended, and also allows testing of algorithms of recommender systems and conduct research to changes in a social network after creating and proposing recommendations. The testing of the developed computer model of virtual social network with a recommender system was conducted. Conclusions. The research of various methods of modeling social networks was conducted. The concept of complex networks was investigated. The main properties of social network graphs are considered. The computer model of a social network with a recommendation system that contains various types of nodes and connections that allow testing a recommender system algorithm has been developed. The developed model of a social network with a recommender system was tested to check its similarity with real social networks. The developed computer model of a social network has the values of network graph parameters corresponding to the values characteristic of real social networks, which allows using the developed model to research the processes that can occur in real social networks.

BIGGR: Bringing Gradoop to Applications

Analyzing large amounts of graph data, e.g., from social networks or bioinformatics, has recently gained much attention. Unfortunately, tool support for handling and analyzing such graph data is still weak and scalability to large data volumes is often limited. We introduce the BIGGR approach providing a novel tool for the user-friendly and efficient analysis and visualization of Big Graph Data on top of the open-source software KNIME and gradoop. Users can visually program graph analytics workflows, execute them on top of the distributed processing framework Apache Flink and visualize large graphs within KNIME. For visualization, we apply visualization-driven data reduction techniques by pushing down sampling and layouting to gradoop and Apache Flink. We also discuss an initial application of the tool for the analysis of patent citation graphs.

Finding the Transitive Closure of Functional Dependencies using Strategic Port Graph Rewriting

We present a new approach to the logical design of relational databases, based on strategic port graph rewriting. We show how to model relational schemata as attributed port graphs and provide port graph rewriting rules to perform computations on functional dependencies. Using these rules we present a strategic graph program to find the transitive closure of a set of functional dependencies. This program is sound, complete and terminating, assuming that there are no cyclical dependencies in the schema.

Algorithm for Optimizing Construction and Assembling of Power Equipment with Low Environmental Impact

The main purpose of this paper is to elaborate an algorithm (followed by an adequate software), designed to solve power engineering optimization problems applying critical path method. All the shortcomings are cleared when using the representation of the program via a graph, where the values of the arcs are the durations of the component operations, and applying the critical path method (CPM), which mainly consists in determining a path of a maximum value between two peaks of that graph. For illustrating the algorithm and the computing program we propose an application from power engineering: a 400 kV electrical overhead line section realization. In the first part of the paper we present the application as a critical path problem. In the second part, we determine the critic path in a program graph and time reserves. In the third part, we present a representative numerical application.

Software Application and Algorithm Designed for Power Systems Equipment and Network Construction Optimization

The main goal of this article is to conceive an algorithm for a software application designed to solve many power engineering optimization problems applying the critical path method (CPM). The classical solution for these problems is found via the schedule graph (the Gantt method), which presents a series of shortcomings: it does not highlight clearly the interdependencies between operations, it does not explain the temporal coincidences, it does not indicate the alternatives of declaring the various operations, it does not have a rigorous mathematical foundation, it does not allow any studies of optimization. All the shortcomings are cleared when using the representation of the program via a graph, where the values of the arcs are the durations of the component operations, and applying the critical path method (CPM), which mainly consists in determining a path of a maximum value between two peaks of that graph. Using CPM offers a great number of advantages: it offers a clear image of the evolution in time of the program, it allows the decreasing of the total duration of implementation for the program without condensing the component operation, it highlights the operations that directly determine the duration of implementation of the program, as well as those that allow the redistribution of the resources and the reduction of cost; it offers the alternative of rapid evaluation of the consequences of certain delays in realizing certain operations (without totally rebuilding the graph and the calculations); it can be easily implemented on a computer, having a solid mathematical base. Applying CPM and optimizing the program is achieved via the following steps: a) setting the list of the component operations, of their characteristics and representing the program via graphs; b) setting the graphs in order; c) determining the critical path (CP) and its value; d) calculating the time stocks related to the realization of the component operation (using the Ford and the Bellman-Kalaba algorithms); e) optimizing the program as from the length, the cost and the necessary resources points of view. For illustrating the algorithm and the computing program we propose an application from power engineering: a 400 kV electrical overhead line section construction. In the first part of the paper we present the application as a critical path problem. In the second part, we determine the critic path in a program graph and time reserves. In the third part, we present a representative numerical application. In the fourth part, it is described the computing program.

An Optimization Algorithm of Slab-Design Based on Bipartite Graph and Linear Programming

This paper shows a novel optimization algorithm based on bipartite graph and linear programming for the self-produced slab-design problem with continuous weight and color-constrained. Firstly, we reduce the number of slabs through bipartite graph maximum weight matching. The second step uses linear programming to reduce residual material. Finally, the experimental results show that the algorithm will lead to a good slab-design scheme in a short time, which will provide decision support for the actual scheduling production.

Constructing PLC Binary Program Model for Detection Purposes

Programmable Logic Controller (PLC) programs are vulnerable to tampering attacks with addition of malware, which can substantially cause severe physical destructions. In order to solve the problems, We propose a static analysis method of Binary PLC programs for the detection of PLC malwares. Firstly, disassemble the binary program into STL program. Secondly, constructed the control flow graph of STL program according to the characteristics of STL language. Thirdly, generate the program execution paths according to traverse the control flow graph and analysis loop paths. Finally the PLC program output and input mapping relations are obtained based on the program execution paths. The experiment shows that the proposed method has achieved the analysis of PLC programs and get each path predicate and the mapping relation between output and input.

Static Backward Slicing of Non-deterministic Programs and Systems

A theory of slicing non-deterministic programs and systems is developed. Non-deterministic programs and systems are represented as non-deterministic program graphs (NDPGs) that allow arbitrary non-deterministic branching to be expressed. Structural and semantic relationships that must exist between an NDPG and (1) its non-termination insensitive (weak) slices and (2) its non-termination sensitive (strong) slices are defined. Weak and strong commitment closure are introduced. These are the NDPG equivalents of being closed under non-termination sensitive and non-termination insensitive control dependence; properties defined on subsets of vertices of the equivalent deterministic structure: the control flow graph. It is proved that if a subset of the vertices of an NDPG is both data dependence closed and (weak/strong) commitment closed, then the resulting induced graph will, indeed, satisfy our structural and semantic requirements. O ( n 3 ) algorithms for computing minimal data and weak/strong commitment closed sets are given. The resulting induced graphs are thus guaranteed to be weak and strong slices, respectively. It is demonstrated, with examples, that programs written in Dijkstra's non-deterministic guarded command language (DNGCL) can be converted to NDPGs to which our slicing algorithms can then be applied. It is proved that the resulting slices (NDPGs) can always be converted back to valid DNGCL programs, highlighting the applicability of our approach to slicing at the source code level.

AdSiF: Agent driven simulation framework paradigm and ontological view

AdSiF (Agent driven Simulation Framework) provides a programming environment for modeling, simulation, and programming agents, which fuses agent-based, object-oriented, aspect-oriented, and logic programming into a single paradigm. The power of this paradigm stems from its ontological background and the paradigms it embraces and integrates into a single paradigm called state-oriented programming. AdSiF commits to describe what exists and to model the agent reasoning abilities, which thereby drives model behaviors. Basically, AdSiF provides a knowledgebase and a depth first search mechanism for reasoning. It is possible to model different search mechanism for reasoning but depth first search is a default search mechanism for first order reasoning. The knowledge base consists of facts and predicates. The reasoning mechanism is combined with a dual-world representation, it is defined as an inner representation of a simulated environment, and it is constructed from time-stamped sensory data (or beliefs) obtained from that environment even when these data consist of errors. This mechanism allows the models to make decisions using the historical data of the models and its own states. The study provides a novel view to simulation and agent-modeling using a script-based graph programming structuring state-oriented programming with a multi-paradigm approach. The study also enhances simulation modeling and agent programming using logic programming and aspect orientation. It provides a solution framework for continuous and discrete event simulation and allows modelers to use their own simulation time management, event handling, distributed, and real time simulation algorithms. • AdSiF provides a programming paradigm called state-oriented paradigm combining multi-paradigms and also has an ontological view. • The relation concept as a part of ontological commitment is used as an active programming element. • The approach provides dynamic aspect management for aspect-oriented programming in simulation and agent programming. • AdSiF allows modelers to develop their own simulation management algorithms such as synchronization algorithms, tie-breaking rules etc. • AdSiF provides a reasoning mechanism based on logic programming to manage simulation entity/agent behaviors.

Graph data models, query languages and programming paradigms

Numerous databases support semi-structured, schemaless and heterogeneous data, typically in the form of graphs (often restricted to trees and nested data). They also provide corresponding high-level query languages or graph-tailored programming paradigms. The evolving query languages present multiple variations: Some are superficial syntactic ones, while other ones are genuine differences in modeling, language capabilities and semantics. Incompatibility with SQL presents a learning challenge for graph databases, while table orientation often leads to cumbersome syntactic/semantic structures that are contrary to graph data. Furthermore, the query languages often fall short of full-fledged semistructured and graph query language capabilities, when compared to the yardsticks set by prior academic efforts. We survey features, the designers' options and differences in the approaches taken by current systems. We cover both declarative query languages, whose semantics is independent of the underlying model of computation, as well as languages with an operational semantics that is more tightly coupled with the model of computation. For the declarative languages over both general graphs and tree-shaped graphs (as motivated by XML and the recent generation of nested formats, such as JSON and Parquet) we compare to an SQL baseline and present SQL reductions and extensions that capture the essentials of such database systems. More precisely, rather than presenting a single SQL extension, we present multiple configuration options whereas multiple possible (and different) semantics are formally captured by the multiple options that the language's semantic configuration options can take. We show how appropriate setting of the configuration options morphs the semantics into the semantics of multiple surveyed languages, hence providing a compact and formal tool to understand the essential semantic differences between different systems. Finally we compare with prior nested and graph query languages (notably OQL, XQuery, Lorel, StruQL, PigLatin) and we transfer into the modern graph database context lessons from the semistructured query processing research of the 90s and 00s, combining them with insights on current graph databases.

Algorithms for Algebraic Path Properties in Concurrent Systems of Constant Treewidth Components

We study algorithmic questions wrt algebraic path properties in concurrent systems, where the transitions of the system are labeled from a complete, closed semiring. The algebraic path properties can model dataflow analysis problems, the shortest path problem, and many other natural problems that arise in program analysis. We consider that each component of the concurrent system is a graph with constant treewidth, a property satisfied by the controlflow graphs of most programs. We allow for multiple possible queries, which arise naturally in demand driven dataflow analysis. The study of multiple queries allows us to consider the tradeoff between the resource usage of the one-time preprocessing and for each individual query. The traditional approach constructs the product graph of all components and applies the best-known graph algorithm on the product. In this approach, even the answer to a single query requires the transitive closure (i.e., the results of all possible queries), which provides no room for tradeoff between preprocessing and query time. Our main contributions are algorithms that significantly improve the worst-case running time of the traditional approach, and provide various tradeoffs depending on the number of queries. For example, in a concurrent system of two components, the traditional approach requires hexic time in the worst case for answering one query as well as computing the transitive closure, whereas we show that with one-time preprocessing in almost cubic time, each subsequent query can be answered in at most linear time, and even the transitive closure can be computed in almost quartic time. Furthermore, we establish conditional optimality results showing that the worst-case running time of our algorithms cannot be improved without achieving major breakthroughs in graph algorithms (i.e., improving the worst-case bound for the shortest path problem in general graphs). Preliminary experimental results show that our algorithms perform favorably on several benchmarks.

Teaching behavior technicians to create publication-quality, single-case design graphs in graphpad prism 7.

In this investigation, we (a) define the desirable features of publication-quality, single-case design graphs based on recommendations in the scholarly literature, (b) suggest GraphPad Prism as a suitable graphing program for creating graphs with those features, and (c) develop and validate a video-modeling tutorial designed to train behavior technicians to create such graphs. Our review identified nine commonly recommended features, and Prism facilitated the creation of graphs with those features. We evaluated the effects of a video-modeling tutorial on graphing performance in Prism using a multiple-baseline design. All four technicians showed mastery-level graphing accuracy with accompanying increases in efficiency following training, which maintained at follow-up without direct feedback from an expert behavior analyst. Social-validity measures found the posttraining graphs to be significantly better than publication quality. We discuss these findings relative to challenges of developing efficient and effective staff-training tutorials.

A review of different cost-based distributed query optimizers

The paper narrates the review of cost-based query optimizers designed using database strategies, deterministic, stochastic, hybrid and energy efficiency-based techniques. It was endowed that earlier authors have used a different database and deterministic strategy like indexing, query filtering, normalization, query graph, tableau, exhaustive enumeration, query graph and dynamic programming to optimize queries. However, these techniques are not pertinent to the optimization of serpentine database queries. Nonetheless, it can be resourcefully optimized by using divergent individual and hybrid nature-inspired computing techniques. Research divulges that the hybrid approach was and remains effective to unravel the query optimization problem. Moreover, notable work is effectuated to optimize data retrieval queries only; however, little work is carried out to optimize write, delete and update queries. Additionally, energy-efficient query optimization is an emanate area. The copious amount of energy can be defended by using energy-efficient query optimizers. The extensive publication trend of distributed query optimizers has also examined that can be of enormous concern for the researchers who want to publish their article and to pursue their research in this domain area. It is ascertained that momentous volume of query optimization work has been effectuated using genetic algorithm followed by swarm particle optimization. Additionally, the researcher has to use and analyze the performance of different emerging evolutionary techniques (Ant Lion Optimization, Whale Optimization, Monkey Search, Dolphin Echolocation, Chaotic Swarming) in designing cost-based query optimizer.

An Efficient Graph Visualisation Framework for RefactorErl

Graph visualisation is a well-known and researched field of graphical informatics. Several good algorithms were developed and reviewed by our days. However, most of the graph drawing tools mainly focus on static drawing generation. In this paper we present an approach that is efficient enough to visualise the user-requested parts (views) of a relatively large Semantic Program Graphs of Erlang projects in soft real-time. With the presented approach the visualised graphs can be traversed interactively, by changing between different levels of detailed information, which may support code comprehension in the RefactorErl framework.

Encoding watermark numbers as reducible permutation graphs using self-inverting permutations

Several graph theoretic watermark methods have been proposed to encode numbers as graph structures in software watermarking environments. In this paper we propose an efficient and easily implementable codec system for encoding watermark numbers as reducible permutation flow-graphs and, thus, we extend the class of graphs used in such a watermarking environment. More precisely, we present an algorithm for encoding a watermark number w as a self-inverting permutation π∗, an algorithm for encoding the self-inverting permutation π∗ into a reducible permutation graph F[π∗] whose structure resembles the structure of real program graphs, as well as decoding algorithms which extract the permutation π∗ from the reducible permutation graph F[π∗] and the number w from π∗. Both the encoding and the decoding process take, in the worst-case, time and space linear in the length of the binary representation of w. The two main components of our proposed codec system, i.e., the self-inverting permutation π∗ and the reducible permutation graph F[π∗], incorporate the binary representation of the watermark w in their structure and possess important structural properties, which make our system resilient to attacks; to this end, we experimentally evaluated our system under edge modification attacks on the graph F[π∗] and the results suggest that we can detect such attacks with high probability.

A Study Optical and Physical Properties of Soda Lime Silica Glass Doped with ZnO

A new set of soda lime glasses doped with ZnO were prepared by melt quenching technique. The aim of this work is to investigate physical and optical properties of prepared glasses using Archimedes’ method, and UV-VIS-NIR spectrometer. The data were analyzed by Origin Graph Program (version 8.6). The results shows that the density of glasses increases in rang 2.486 ~ 2.5656g/cm3, with increasing of concentration of ZnO because of higher molecular weight of ZnO compared with SiO2. The molar volume of glasses decreases, in range 24.1255 ~ 23.4019 cm3/mol, with increasing of concentration of ZnO, this indicates that the structures of glasses more compacted with addition of ZnO. The refractive index and optical energy band gap of glasses change in range 1.314 ~ 1.504 and 3.049 ~ 3.253 eV respectively, because of change of non-bridging oxygen. The absorbance of UV-VIS rays shows that ZnO have a good effect on glass transparency.

Tigr

Graph analytics delivers deep knowledge by processing large volumes of highly connected data. In real-world graphs, the degree distribution tends to follow the power law -- a small portion of nodes own a large number of neighbors. The high irregularity of degree distribution acts as a major barrier to their efficient processing on GPU architectures, which are primarily designed for accelerating computations on regular data with SIMD executions. Existing solutions to the inefficiency of GPU-based graph analytics either modify the graph programming abstraction or rely on changes to the low-level thread execution models. The former requires more programming efforts for designing and maintaining graph analytics; while the latter couples with the underlying architectures, making it difficult to adapt as architectures quickly evolve. Unlike prior efforts, this work proposes to address the above fundamental problem at its origin -- the irregular graph data itself. It raises a critical question in irregular graph processing: Is it possible to transform irregular graphs into more regular ones such that the graphs can be processed more efficiently on GPU-like architectures, yet still producing the same results? Inspired by the question, this work introduces Tigr -- a graph transformation framework that can effectively reduce the irregularity of real-world graphs with correctness guarantees for a wide range of graph analytics. To make the transformations practical, Tigr features a lightweight virtual transformation scheme, which can substantially reduce the costs of graph transformations, while preserving the benefits of reduced irregularity. Evaluation on Tigr-based GPU graph processing shows significant and consistent speedup over the state-of-the-art GPU graph processing frameworks for a spectrum of irregular graphs.

Symbolic checking of Fuzzy CTL on Fuzzy Program Graph

Few fuzzy temporal logics and modeling formalisms are developed such that their model checking is both effective and efficient. State-space explosion makes model checking of fuzzy temporal logics inefficient. That is because either the modeling formalism itself is not compact, or the verification approach requires an exponentially larger yet intermediate representation of the modeling formalism. To exemplify, Fuzzy Program Graph (FzPG) is a very compact, and powerful formalism to model fuzzy systems; yet, it is required to be translated into an equal Fuzzy Kripke model with an exponential blow-up should it be formally verified. In this paper, we introduce Fuzzy Computation Tree Logic (FzCTL) and its direct symbolic model checking over FzPG that avoids the aforementioned state-space explosion. Considering compactness and readability of FzPG along with expressiveness of FzCTL, we believe the proposed method is applicable in real-world scenarios. Finally, we study formal verification of fuzzy flip-flops to demonstrate capabilities of the proposed method.

High-Level Programming Abstractions for Distributed Graph Processing

Efficient processing of large-scale graphs in distributed environments has been an increasingly popular topic of research in recent years. Inter-connected data that can be modeled as graphs arise in application domains such as machine learning, recommendation, web search, and social network analysis. Writing distributed graph applications is inherently hard and requires programming models that can cover a diverse set of problem domains, including iterative refinement algorithms, graph transformations, graph aggregations, pattern matching, ego-network analysis, and graph traversals. Several high-level programming abstractions have been proposed and adopted by distributed graph processing systems and big data platforms. Even though significant work has been done to experimentally compare distributed graph processing frameworks, no qualitative study and comparison of graph programming abstractions has been conducted yet. In this survey, we review and analyze the most prevalent high-level programming models for distributed graph processing, in terms of their semantics and applicability. We identify the classes of graph applications that can be naturally expressed by each abstraction and we also give examples of applications that are hard or impossible to express. We review 34 distributed graph processing systems with respect to their programming abstractions, execution models, and communication mechanisms. Finally, we discuss trends and open research questions in the area of distributed graph processing.