229,489 research outputs found

    Redesigning A Trolley for The Stairs Building Based on Material Aspect

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    In Bandung, some buildings have three levels or more with no escalator and elevator for their daily needs in moving goods. One example is the Telkom University dormitory. As a resident of a building, problems are often found unconsciously and that has not been found a clear solution, for example when moving goods from the ground to the top level. The goods are referred to as suitcases, gallons, dispensers, large bags, etc. Some people will call the services of a porter or friend to help them transport goods. Because of that, a clear solution must be made for goods mobilization activities to be more effective and efficient, therefore, transportation equipment such as trolleys with good material and it can accommodate the load of goods that are usually moved in buildings without elevators is a solution for this problem. Keywords Stairs trolley, Material, Dormitory, Bandun

    Spontaneous Analogy by Piggybacking on a Perceptual System

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    Most computational models of analogy assume they are given a delineated source domain and often a specified target domain. These systems do not address how analogs can be isolated from large domains and spontaneously retrieved from long-term memory, a process we call spontaneous analogy. We present a system that represents relational structures as feature bags. Using this representation, our system leverages perceptual algorithms to automatically create an ontology of relational structures and to efficiently retrieve analogs for new relational structures from long-term memory. We provide a demonstration of our approach that takes a set of unsegmented stories, constructs an ontology of analogical schemas (corresponding to plot devices), and uses this ontology to efficiently find analogs within new stories, yielding significant time-savings over linear analog retrieval at a small accuracy cost.Comment: Proceedings of the 35th Meeting of the Cognitive Science Society, 201

    Modular Termination Verification

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    We propose an approach for the modular specification and verification of total correctness properties of object-oriented programs. We start from an existing program logic for partial correctness based on separation logic and abstract predicate families. We extend it with call permissions qualified by an arbitrary ordinal number, and we define a specification style that properly hides implementation details, based on the ideas of using methods and bags of methods as ordinals, and exposing the bag of methods reachable from an object as an abstract predicate argument. These enable each method to abstractly request permission to call all methods reachable by it any finite number of times, and to delegate similar permissions to its callees. We illustrate the approach with several examples

    An EPTAS for machine scheduling with bag-constraints

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    Machine scheduling is a fundamental optimization problem in computer science. The task of scheduling a set of jobs on a given number of machines and minimizing the makespan is well studied and among other results, we know that EPTAS's for machine scheduling on identical machines exist. Das and Wiese initiated the research on a generalization of makespan minimization, that includes so called bag-constraints. In this variation of machine scheduling the given set of jobs is partitioned into subsets, so called bags. Given this partition a schedule is only considered feasible when on any machine there is at most one job from each bag. Das and Wiese showed that this variant of machine scheduling admits a PTAS. We will improve on this result by giving the first EPTAS for the machine scheduling problem with bag-constraints. We achieve this result by using new insights on this problem and restrictions given by the bag-constraints. We show that, to gain an approximate solution, we can relax the bag-constraints and ignore some of the restrictions. Our EPTAS uses a new instance transformation that will allow us to schedule large and small jobs independently of each other for a majority of bags. We also show that it is sufficient to respect the bag-constraint only among a constant number of bags, when scheduling large jobs. With these observations our algorithm will allow for some conflicts when computing a schedule and we show how to repair the schedule in polynomial-time by swapping certain jobs around

    A contraction-recursive algorithm for treewidth

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    Let tw(G) denote the treewidth of graph G. Given a graph G and a positive integer k such that tw(G) <= k + 1, we are to decide if tw(G) <= k. We give a certifying algorithm RTW ("R" for recursive) for this task: it returns one or more tree-decompositions of G of width <= k if the answer is YES and a minimal contraction H of G such that tw(H) > k otherwise. RTW uses a heuristic variant of Tamaki's PID algorithm for treewidth (ESA2017), which we call HPID. RTW, given G and k, interleaves the execution of HPID with recursive calls on G /e for edges e of G, where G / e denotes the graph obtained from G by contracting edge e. If we find that tw(G / e) > k, then we have tw(G) > k with the same certificate. If we find that tw(G / e) <= k, we "uncontract" the bags of the certifying tree-decompositions of G / e into bags of G and feed them to HPID to help progress. If the question is not resolved after the recursive calls are made for all edges, we finish HPID in an exhaustive mode. If it turns out that tw(G) > k, then G is a certificate for tw(G') > k for every G' of which G is a contraction, because we have found tw(G / e) <= k for every edge e of G. This final round of HPID guarantees the correctness of the algorithm, while its practical efficiency derives from our methods of "uncontracting" bags of tree-decompositions of G / e to useful bags of G, as well as of exploiting those bags in HPID. Experiments show that our algorithm drastically extends the scope of practically solvable instances. In particular, when applied to the 100 instances in the PACE 2017 bonus set, the number of instances solved by our implementation on a typical laptop, with the timeout of 100, 1000, and 10000 seconds per instance, are 72, 92, and 98 respectively, while these numbers are 11, 38, and 68 for Tamaki's PID solver and 65, 82, and 85 for his new solver (SEA 2022).Comment: 17 pages, 2 figures, submitted IPEC 202

    Mayha

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    Me: Where does my nickname come from? My mom: Well, your nickname is Mayha, and, that all originated one Christmas when my grandma, who was your great-grandmother, was writing all of the grandchildren, great- grandchildren’s names on paper bags, um...which was basically the gift wrap for Christmas presents that year. And when we got your bag, it said M-a-y-h-a [spelled out], where your name is actually pronounced – spelled, M-a-y-a-h [spelled out]. So instead of Mayah she had spelled Mayha, and we just that it was so funny that we continued to call you Mayha ever since, and, I don’t know it’s probably been over ten years now and we still call you Mayha, because of your great-grandmother spelling your name wrong on your Christmas present

    Fixed-parameter tractable canonization and isomorphism test for graphs of bounded treewidth

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    We give a fixed-parameter tractable algorithm that, given a parameter kk and two graphs G1,G2G_1,G_2, either concludes that one of these graphs has treewidth at least kk, or determines whether G1G_1 and G2G_2 are isomorphic. The running time of the algorithm on an nn-vertex graph is 2O(k5logk)n52^{O(k^5\log k)}\cdot n^5, and this is the first fixed-parameter algorithm for Graph Isomorphism parameterized by treewidth. Our algorithm in fact solves the more general canonization problem. We namely design a procedure working in 2O(k5logk)n52^{O(k^5\log k)}\cdot n^5 time that, for a given graph GG on nn vertices, either concludes that the treewidth of GG is at least kk, or: * finds in an isomorphic-invariant way a graph c(G)\mathfrak{c}(G) that is isomorphic to GG; * finds an isomorphism-invariant construction term --- an algebraic expression that encodes GG together with a tree decomposition of GG of width O(k4)O(k^4). Hence, the isomorphism test reduces to verifying whether the computed isomorphic copies or the construction terms for G1G_1 and G2G_2 are equal.Comment: Full version of a paper presented at FOCS 201
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