Radix Sorting With No Extra Space

It is well known that n integers in the range [1,n^c] can be sorted in O(n) time in the RAM model using radix sorting. More generally, integers in any range [1,U] can be sorted in O(n sqrt{loglog n}) time. However, these algorithms use O(n) words of extra memory. Is this necessary? We present a simple, stable, integer sorting algorithm for words of size O(log n), which works in O(n) time and uses only O(1) words of extra memory on a RAM model. This is the integer sorting case most useful in practice. We extend this result with same bounds to the case when the keys are read-only, which is of theoretical interest. Another interesting question is the case of arbitrary c. Here we present a black-box transformation from any RAM sorting algorithm to a sorting algorithm which uses only O(1) extra space and has the same running time. This settles the complexity of in-place sorting in terms of the complexity of sorting.Comment: Full version of paper accepted to ESA 2007. (17 pages

Optimal sorting of product into fixed weight packaging

Compac Sorting Equipment make very nifty machines for sorting fruit by weight, diameter, colour, density, blemish or even shape. Compac sought solutions to two closely related problems: the boxing problem and the bagging problem. The boxing problem requires graded fruit to be assigned to outlets where boxes are filled with a specified number of fruit to a minimum weight (and a specified tolerance for underweights). The aim is to maximise the number of boxes packed. The decision must be made after all information is known, but before the fruit passes the first outlet - a few seconds total. Further, information about fruit already packed in a given box is incomplete (we don’t know exactly which fruit ended up in a box). The bagging problem requires bags to be filled to a minimum weight - no tolerance for underweights, and no constraints on the number of fruit per bag. In this case complete information is available on fruit already assigned to a bag. Again the aim is to maximise the number of bags packed

Penerapan Metode Pengujian White-box, Black-box dan User Acceptance Testing (UAT) pada website laser.umm.ac.id.

Universitas Muhammadiyah Malang (UMM) developed an application providing efficient search tools and sorting options to help users find the books or information needed quickly, namely the laser.umm.ac.id application or OPAC | Online Public Access Catalog. In this study, software testing techniques were used to evaluate the entire system prototype consisting of white box testing, black box testing, and user acceptance testing (UAT). The purpose of the research is to find out bugs and errors that occur in internal and external systems or structural and functional testing. The testing stages begin with white-box basis path testing by testing the source code / program code of the Advance OPAC search feature on the website, then next with black-box decision table testing by testing the search form on the advance OPAC and the last stage is testing with user acceptance testing (UAT) by distributing questionnaires to students. In white box testing, it is obtained that the source code has a low degree of complexity, meaning that the system shows that this application can run well without any errors. In Black box testing from the sample obtained the test results show a pass where the expected result matches the actual result. In the UAT test which uses a questionnaire with a Likert scale of 5 scales, the respondents agree above 75,3% (116 respondents) that the OPAC | Online Public Access Catalog system is able to facilitate the use and usefulness of finding library materials / information

Speeding up shortest path algorithms

Given an arbitrary, non-negatively weighted, directed graph $G=(V,E)$ we present an algorithm that computes all pairs shortest paths in time $\mathcal{O}(m^* n + m \lg n + nT_\psi(m^*, n))$, where $m^*$ is the number of different edges contained in shortest paths and $T_\psi(m^*, n)$ is a running time of an algorithm to solve a single-source shortest path problem (SSSP). This is a substantial improvement over a trivial $n$ times application of $\psi$ that runs in $\mathcal{O}(nT_\psi(m,n))$. In our algorithm we use $\psi$ as a black box and hence any improvement on $\psi$ results also in improvement of our algorithm. Furthermore, a combination of our method, Johnson's reweighting technique and topological sorting results in an $\mathcal{O}(m^*n + m \lg n)$ all-pairs shortest path algorithm for arbitrarily-weighted directed acyclic graphs. In addition, we also point out a connection between the complexity of a certain sorting problem defined on shortest paths and SSSP.Comment: 10 page

Set-Oriented Mining for Association Rules in Relational Databases

Describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less efficient than special-purpose algorithms. We develop new algorithms that can be expressed as SQL queries, and discuss the optimization of these algorithms. After analytical evaluation, an algorithm named SETM emerges as the algorithm of choice. SETM uses only simple database primitives, viz. sorting and merge-scan join. SETM is simple, fast and stable over the range of parameter values. The major contribution of this paper is that it shows that at least some aspects of data mining can be carried out by using general query languages such as SQL, rather than by developing specialized black-box algorithms. The set-oriented nature of SETM facilitates the development of extension

Single-Shot Clothing Category Recognition in Free-Configurations with Application to Autonomous Clothes Sorting

This paper proposes a single-shot approach for recognising clothing categories from 2.5D features. We propose two visual features, BSP (B-Spline Patch) and TSD (Topology Spatial Distances) for this task. The local BSP features are encoded by LLC (Locality-constrained Linear Coding) and fused with three different global features. Our visual feature is robust to deformable shapes and our approach is able to recognise the category of unknown clothing in unconstrained and random configurations. We integrated the category recognition pipeline with a stereo vision system, clothing instance detection, and dual-arm manipulators to achieve an autonomous sorting system. To verify the performance of our proposed method, we build a high-resolution RGBD clothing dataset of 50 clothing items of 5 categories sampled in random configurations (a total of 2,100 clothing samples). Experimental results show that our approach is able to reach 83.2\% accuracy while classifying clothing items which were previously unseen during training. This advances beyond the previous state-of-the-art by 36.2\%. Finally, we evaluate the proposed approach in an autonomous robot sorting system, in which the robot recognises a clothing item from an unconstrained pile, grasps it, and sorts it into a box according to its category. Our proposed sorting system achieves reasonable sorting success rates with single-shot perception.Comment: 9 pages, accepted by IROS201

The spatial sorting and matching of skills and firms

Using a matched employer-employee database for Italy we look at the spatial distribution of wages across provinces. This rich database allows us to contribute at opening the black box of agglomeration economies exploiting the micro dimension of the interaction among economic agents, both individuals and firms. We provide evidence that firm size and particularly skills are sorted across space, and explain a large portion of the spatial wage variation that could otherwise be attributed to aggregate proxies of agglomeration externalities. Our data further support the assortative matching hypothesis, that we show not to be driven by co-location of "good" workers and firms. Finally, we point out that this assortative matching is negatively related to local market size.Spatial Externalities; Panel-Data; Skills; Firms' Heterogeneity; Sorting; Matching