Graph-based Procedure Research Articles

PrISM-Tracker

A user often needs training and guidance while performing several daily life procedures, e.g., cooking, setting up a new appliance, or doing a COVID test. Watch-based human activity recognition (HAR) can track users' actions during these procedures. However, out of the box, state-of-the-art HAR struggles from noisy data and less-expressive actions that are often part of daily life tasks. This paper proposes PrISM-Tracker, a procedure-tracking framework that augments existing HAR models with (1) graph-based procedure representation and (2) a user-interaction module to handle model uncertainty. Specifically, PrISM-Tracker extends a Viterbi algorithm to update state probabilities based on time-series HAR outputs by leveraging the graph representation that embeds time information as prior. Moreover, the model identifies moments or classes of uncertainty and asks the user for guidance to improve tracking accuracy. We tested PrISM-Tracker in two procedures: latte-making in an engineering lab study and wound care for skin cancer patients at a clinic. The results showed the effectiveness of the proposed algorithm utilizing transition graphs in tracking steps and the efficacy of using simulated human input to enhance performance. This work is the first step toward human-in-the-loop intelligent systems for guiding users while performing new and complicated procedural tasks.

Graph-Based Taxonomic Semantic Class Labeling

We present a graph-based method for the lexical task of labeling senses of polysemous lexemes. The labeling task aims at generalizing sense features of a lexical item in a corpus using more abstract concepts. In this method, a coordination dependency-based lexical graph is first constructed with clusters of conceptually associated lexemes representing related senses and conceptual domains of a source lexeme. The label abstraction is based on the syntactic patterns of the x is_a y dependency relation. For each sense cluster, an additional lexical graph is constructed by extracting label candidates from a corpus and selecting the most prominent is_a collocates in the constructed label graph. The obtained label lexemes represent the sense abstraction of the cluster of conceptually associated lexemes. In a similar graph-based procedure, the semantic class representation is validated by constructing a WordNet hypernym relation graph. These additional labels indicate the most appropriate hypernym category of a lexical sense community. The proposed labeling method extracts hierarchically abstract conceptual content and the sense semantic features of the polysemous source lexeme, which can facilitate lexical understanding and build corpus-based taxonomies.

DBIG-US: A two-stage under-sampling algorithm to face the class imbalance problem

The class imbalance problem occurs when one class far outnumbers the other classes, causing most traditional classifiers perform poorly on the minority classes. To tackle this problem, a plethora of techniques have been proposed, especially centered around resampling methods. This paper introduces a two-stage method that combines the DBSCAN clustering algorithm to filter noisy majority class instances with a graph-based procedure to overcome the class imbalance. We then experimentally evaluate the behavior of the proposed method on a collection of two-class imbalanced data sets. The experimental results show an improvement in the classification performance measured by the geometric mean of the accuracy on each class and also a higher reduction in the imbalance ratio when compared to several state-of-the-art under-sampling techniques.

Graph-Based Registration and Blending for Undersea Image Stitching

SummaryImage stitching is important for the perception and manipulation of undersea robots. In spite of a well-developed technique, it is still challenging for undersea images because of their inevitable appearance ambiguity caused by the limited light in the undersea environment, and local disturbance caused by moving objects, ocean current, etc. To get a clean and stable background panorama in the undersea environment, this paper proposes an undersea image-stitching method by introducing graph-based registration and blending procedures. Specifically, in the registration procedure, matching the features in each undersea image pair is formulated and solved by graph matching, to incorporate the structural information between features. In the blending procedure, an energy function on the indirect graph Markov random field is proposed, which takes both image consistency and neighboring consistency into consideration. Coincidentally, both graph matching and energy minimization can be mathematically formulated by integer quadratic programming problems with different constraints; the recently proposed graduated nonconvexity and concavity procedure is used to optimize both problems. Experiments on both synthetic images and real-world undersea images witness the effectiveness of the proposed method.

Improving Combinational Circuit Reliability Against Multiple Event Transients via a Partition and Restructuring Approach

Traditionally, increasing logical masking probability has been used to improve the circuit reliability against single-event transients (SETs). As the very first work, this paper presents a new approach to increase the reliability of digital circuits against soft errors caused by multiple event transients (METs) by taking advantages of circuit partitioning and local logical restructuring techniques. In the proposed approach, the circuit is partitioned into various subcircuits and, then, several structures of each subcircuits which satisfy the area constraints are extracted by using a graph-based procedure. In order to select the suitable alternative between various subcircuit structures, we introduce a novel metric named global failure probability in the presence of METs (GFPM). This parameter provides an evaluation of each subcircuits contribution in the soft error rate (SER) of the given circuit making it possible to estimate the impacts of changing the structure of the subcircuits on the circuit SER. Hence, it prevents from repeatedly calculating the SER of the circuit that is very time-consuming leading to significant improvements in the optimization runtime. Experimental studies on ISCAS benchmark circuits show that the proposed approach, on average, achieves 18.4% SER reduction with 11.9% area overhead and 8.2% delay overhead comparing to the original circuit while the global SET-based SER mitigation approach and the global MET-based SER mitigation approach achieve 8.46% and 21.8% SER reduction, respectively. Besides, the proposed technique is about $580 \times $ faster than the global MET-based method.

A multistage graph-based procedure for solving a just-in-time flexible job-shop scheduling problem with machine and time-dependent processing costs

This paper deals with a new flexible job-shop scheduling problem in which the objective function to be minimised is the sum of the earliness and tardiness costs of the jobs and the costs of the operations required to perform the jobs, the latter depending on the machine and the time interval in which they are performed (as happens in many countries with the costs of electric power or those of manpower). We formalise the problem with a mathematical model and we propose a heuristic procedure that is based primarily on constructing a multistage graph and finding in it the shortest path from the source to the sink. We also describe the generation of the data-set used in an extensive computational experiment and expose and analyse the obtained results.

Graph representation and decomposition of ODE/hyperbolic PDE systems

This paper deals with the decomposition of process networks consisting of distributed parameter systems modeled by first-order hyperbolic partial differential equations (PDEs) and lumped parameter systems modeled by ordinary differential equations (ODEs) into compact, weakly interacting subsystems. A structural interaction parameter (SIP) generalizing the concept of relative degree in ODE systems to first-order hyperbolic PDE systems is defined. An equation graph representation of these systems is developed for efficient calculation of SIPs. An agglomerative (bottom-up) hierarchical clustering algorithm and a divisive (top-down) algorithm are used to obtain hierarchical decompositions based on the SIPs. Modularity maximization is used to select the optimal decomposition. A network of two absorbers and two desorbers serves as a case study. The optimal decompositions of this network obtained from both the algorithms illustrate the effectiveness of the graph-based procedure in capturing key structural connectivity properties of the process network.

Acceleration of Binding Site Comparisons by Graph Partitioning.

The comparison of protein binding sites is a prominent task in computational chemistry and has been studied in many different ways. For the automatic detection and comparison of putative binding cavities the Cavbase system has been developed which uses a coarse-grained set of pseudocenters to represent the physicochemical properties of a binding site and employs a graph-based procedure to calculate similarities between two binding sites. However, the comparison of two graphs is computationally quite demanding which makes large-scale studies such as the rapid screening of entire databases hardly feasible. In a recent work, we proposed the method Local Cliques (LC) for the efficient comparison of Cavbase binding sites. It employs a clique heuristic to detect the maximum common subgraph of two binding sites and an extended graph model to additionally compare the shape of individual surface patches. In this study, we present an alternative to further accelerate the LC method by partitioning the binding-site graphs into disjoint components prior to their comparisons. The pseudocenter sets are split with regard to their assigned phyiscochemical type, which leads to seven much smaller graphs than the original one. Applying this approach on the same test scenarios as in the former comprehensive way results in a significant speed-up without sacrificing accuracy.

External Validity: From Do-Calculus to Transportability Across Populations

The generalizability of empirical findings to new environments, settings or populations, often called "external validity," is essential in most scientific explorations. This paper treats a particular problem of generalizability, called "transportability," defined as a license to transfer causal effects learned in experimental studies to a new population, in which only observational studies can be conducted. We introduce a formal representation called "selection diagrams" for expressing knowledge about differences and commonalities between populations of interest and, using this representation, we reduce questions of transportability to symbolic derivations in the do-calculus. This reduction yields graph-based procedures for deciding, prior to observing any data, whether causal effects in the target population can be inferred from experimental findings in the study population. When the answer is affirmative, the procedures identify what experimental and observational findings need be obtained from the two populations, and how they can be combined to ensure bias-free transport.

Fast decision procedure for propositional Dummett logic based on a multiple premise tableau calculus

We present a procedure to decide propositional Dummett logic. Such a procedure relies on a tableau calculus with a multiple premise rule and optimizations. The resulting implementation outperforms the state of the art graph-based procedure.

Building small equality graphs for deciding equality logic with uninterpreted functions

The logic of Equalities with Uninterpreted Functions is used in the formal verification community mainly for proofs of equivalence: proving that two versions of a hardware design are the same, or that input and output of a compiler are semantically equivalent are two prominent examples of such proofs. We introduce a new decision procedure for this logic that generalizes two leading decision procedures that were published in the last few years: the Positive Equality approach suggested by Bryant et al. [Exploiting positive equality in a logic of equality with uninterpreted functions, in: Proc. 11th Intl. Conference on Computer Aided Verification (CAV’99), 1999], and the Range-Allocation algorithm suggested by Pnueli et al. [The small model property: how small can it be? Information and Computation 178 (1) (2002) 279–293]. Both of these methods reduce this logic to pure Equality Logic (without Uninterpreted Functions), and then, due to the small model property that such formulas have, find a small domain to each variable that is sufficiently large to maintain the satisfiability of the formula. The state-space spanned by these domains is then traversed with a BDD-based engine. The Positive Equality approach identifies terms that have a certain characteristic in the original formula (before the reduction to pure Equality Logic) and replaces them with unique constants. The Range-Allocation algorithm analyzes the structure of the formula after the reduction to equality logic with a graph-based procedure to allocate a small set of values to each variable. The former, therefore, has an advantage when a large subset of the terms can be replaced with constants, and disadvantage in the other cases. In this paper we essentially merge the two methods, while improving both with a more careful analysis of the formula’s structure. We show that the new method is provably dominant over both methods, theoretically as well as empirically. 1 An early version of this article appeared in [Y. Rodeh, O. Shtrichman, Finite instantiations in equivalence logic with uninterpreted functions, in: G. Berry, H. Comon, A. Finkel (Eds.), Proc. 13th Intl. Conference on Computer Aided Verification (CAV’01), Lecture Notes in Computer Science, Springer-Verlag, Berlin, 2001.] 1

CASCADING RANDOM WALKS

In this paper, we discuss a simple, Monte Carlo algorithm for the problem of checking whether a Quantified Boolean Formula (QBF) in Conjunctive Normal Form (CNF), with at most two literals per clause has a model. The term k-CNF is used to describe boolean formulas in CNF, with at most k literals per clause and the problem of checking whether a given k-CNF formula is satisfiable is called the k-SAT problem. A QBF is a boolean formula, accompanied by a quantifier string which imposes a linear ordering on the variables of that formula. The problem of finding a model for a QBF formula in CNF, with at at most k literals per clause is called the QkSAT problem. The QkSAT problem is PSPACE-complete, for k≥3. However, the Q2SAT problem can be decided in polynomial time; the graph-based procedure, discussed in [1], is the first such algorithm for this problem. This procedure requires the construction of a global implication graph, corresponding to the input formula and searching for certain paths in this graph. Hence the complete set of clauses must be part of the input. We propose an incremental, randomized approach for the Q2SAT problem that is essentially local in nature, in that the complete clausal set need not be provided at any time, in the presence of a verifier. We show that the randomized algorithm can be analyzed as a one-dimensional random walk, with one reflecting barrier and one absorbing barrier. On a Q2SAT instance with m clauses on n variables, our coin-flipping algorithm runs in time O(n2 · V(m, n)), where V(m, n) is the time required to verify that a given model satisfies the formula. Additionally, if the instance is satisfiable, the probability that our algorithm fails to find a model is less than one half. The design and analysis of a randomized algorithm for a problem, is important from both the theoretical and the practical perspectives. Randomized approaches tend to be simple and elegant, thereby making the process of checking correctness, effortless as well. The randomized approach discussed in this paper lays the groundwork for analyzing a number of problems related to 2CNF formulas and directed graphs. We remark that our work in this paper is the first randomized algorithm for a class of QBFs.

Graph-based codeword selection for memoryless low-power bus coding

The problem of selecting codewords for memoryless low-power bus coding is considered. A graph-based procedure is proposed to obtain a subset of all possible codewords with minimum average energy consumption. The procedure can be applied to arbitrary cost models.

A Method of Constructing the Mathematical Model of a Discretely Developing Large Space Structure

A new method was proposed to describe the on-orbit mounting of large space constructions that is accompanied by discrete changes in their mechanical structure and dynamic characteristics as controlled plants. Consideration was given to designing the initial (Lagrangian) model for each interval of invariable structure of the discretely developing construction. A graph-based computational procedure of reducing the initial model to the modal-physical one was proposed. Suggested was a method of designing a construction graph model which provides a most compact representation of the changes in the dynamic characteristics of the large space construction that occur in the course of its structural transformation.

Parallel computation of meshless methods for explicit dynamic analysis

A parallel computational implementation of modern meshless methods is presented for explicit dynamic analysis. The procedures are demonstrated by application of the Reproducing Kernel Particle Method (RKPM). Aspects of a coarse grain parallel paradigm are detailed for a Lagrangian formulation using model partitioning. Integration points are uniquely defined on separate processors and particle definitions are duplicated, as necessary, so that all support particles for each point are defined locally on the corresponding processor. Several partitioning schemes are considered and a reduced graph-based procedure is presented. Partitioning issues are discussed and procedures to accommodate essential boundary conditions in parallel are presented. Explicit MPI message passing statements are used for all communications among partitions on different processors. The effectiveness of the procedure is demonstrated by highly deformable inelastic example problems. Copyright © 2000 John Wiley & Sons, Ltd.

Rule-based generation of exploded-views and assembly sequences

AbstractDirect planning of assembly sequences is either very complicated computationally, or requires an ‘expert’ user. This paper presents a new approach to the automatic generation of assembly plans which involves two phases. An ‘exploded’ layout of the assembled product is first found from its topological and geometric description by a graph-based procedure. Then, a knowledge-based technique is used for planning of selected assembly sequences by utilizing theoretical as well as heuristic knowledge of mechanical components and assembly processes. Besides serving the assembly planning phase, automatic generation of exploded-views could also be a most desirable feature of any computer-aided design system. An example demonstrates the application of the method to an actual product.