Validation of purdue engineering shape benchmark clusters by crowdsourcing

The effective organization of CAD data archives is central to PLM and consequently content based retrieval of 2D drawings and 3D models is often seen as a "holy grail" for the industry. Given this context, it is not surprising that the vision of a "Google for shape", which enables engineers to search databases of 3D models for components similar in shape to a query part, has motivated numerous researchers to investigate algorithms for computing geometric similarity. Measuring the effectiveness of the many approaches proposed has in turn lead to the creation of benchmark datasets against which researchers can compare the performance of their search engines. However to be useful the datasets used to measure the effectiveness of 3D retrieval algorithms must not only define a collection of models, but also provide a canonical specification of their relative similarity. Because the objective of shape retrieval algorithms is (typically) to retrieve groups of objects that humans perceive as "similar" these benchmark similarity relationships have (by definition) to be manually determined through inspection

Geometric reasoning via internet crowdsourcing

The ability to interpret and reason about shapes is a peculiarly human capability that has proven difficult to reproduce algorithmically. So despite the fact that geometric modeling technology has made significant advances in the representation, display and modification of shapes, there have only been incremental advances in geometric reasoning. For example, although today's CAD systems can confidently identify isolated cylindrical holes, they struggle with more ambiguous tasks such as the identification of partial symmetries or similarities in arbitrary geometries. Even well defined problems such as 2D shape nesting or 3D packing generally resist elegant solution and rely instead on brute force explorations of a subset of the many possible solutions. Identifying economic ways to solving such problems would result in significant productivity gains across a wide range of industrial applications. The authors hypothesize that Internet Crowdsourcing might provide a pragmatic way of removing many geometric reasoning bottlenecks.This paper reports the results of experiments conducted with Amazon's mTurk site and designed to determine the feasibility of using Internet Crowdsourcing to carry out geometric reasoning tasks as well as establish some benchmark data for the quality, speed and costs of using this approach.After describing the general architecture and terminology of the mTurk Crowdsourcing system, the paper details the implementation and results of the following three investigations; 1) the identification of "Canonical" viewpoints for individual shapes, 2) the quantification of "similarity" relationships with-in collections of 3D models and 3) the efficient packing of 2D Strips into rectangular areas. The paper concludes with a discussion of the possibilities and limitations of the approach

Ethyl 7-oxo-3,5-diphenyl-1,4-diazepane-2-carboxyl­ate

The title compound, C20H22N2O3, crystallizes with two independent mol­ecules in the asymmetric unit. In both mol­ecules, the diazepane rings adopt chair conformations. The mean planes of the diazepane rings in the two molecules form dihedral angles of 71.6 (4)/40.3 (5) and 75.9 (5)/58.6 (7)° with the neighbouring benzene rings. The carbonyl-group O atoms deviate significantly from the diazepane rings, by 0.685 (14) and 0.498 (13) Å. The eth­oxy­carbonyl groups show conformational difference between two mol­ecules, as reflected in the orientation of the carbonyl O atoms and the C—C—O—C torsion angle of −179.0 (2)° in one mol­ecule and 73.2 (2)° in the other. In one molecule there is a short N—H⋯O contact that generates an S(5) ring motif. In the crystal, N—H⋯O inter­actions generate R 2 2(8) graph-set motifs and C—H⋯O inter­actions generate R 2 2(10) and R 2 2(14) graph-set motifs. C—H⋯π inter­actions also occur

A novel hybrid intelligence approach for 2D packing through Internet crowdsourcing

Packing problems on its current state are being utilized for wide area of industrial applications. The aim of present research is to create and implement an intelligent system that tackles the problem of 2D packing of objects inside a 2D container, such that objects do not overlap and the container area is to be maximized. The packing problem becomes easier, when regular/rectangular objects and container are used. In most of the practical situations, the usage of irregular objects comes to existence. To solve the packing problem of irregular objects inside a rectangular container, a hybrid intelligence approach is introduced in our proposed work. The combination of machine intelligence and human intelligence is referred as the hybrid intelligence or semi-automated approach in the proposed methodology. The incorporation of human intelligence in the outcome of machine intelligence is possible to obtain using the internet crowdsourcing as we wish to handle the packing problem through internet crowdsourcing involving rural people. The proposed methodology is tested on different standard data sets and it is observed that it has clear advantage over both manual as well as fully automated heuristic based methods in terms of time and space efficiency

Ethyl 2-(7-oxo-3,5-diphenyl-1,4-diaze­pan-2-yl)acetate

In the title compound, C21H24N2O3, the diazepane ring adopts a chair conformation. The central diazepane ring forms dihedral angles 67.80 (7) and 72.29 (5)° with the two benzene rings. The eth­oxy­carbonyl group is disordered over two conformations with site-occupancy factors of 0.643 (5) and 0.357 (5). In the crystal, inversion dimers linked by pairs of N—H⋯O hydrogen bonds generate R 2 2(8) loops

Geometric Reasoning With a Virtual Workforce (Crowdsourcing for CAD/CAM)

This paper reports the initial results of employing a commercial Crowdsourcing (aka Micro-outsourcing) service to provide geometric analysis of complex 3D models of mechanical components. Although Crowdsourcing sites (which distribute browser based tasks to potentially large numbers of anonymous workers on the Internet) are well established for image analysis and text manipulation there is little academic work on the effectiveness or limitations of the approach. The work reported here describes the initial results of using Crowdsourcing to determine the 'best' canonical, or characteristic, views of complex 3D models of engineering components. The results suggest that the approach is a cheap, fast and effective method of solving what is a computationally difficult problem

A Non-Commutative Extension of MELL

We extend multiplicative exponential linear logic (MELL) by a non-commutative, self-dual logical operator. The extended system, called NEL, is defined in the formalism of the calculus of structures, which is a generalisation of the sequent calculus and provides a more refined analysis of proofs. We should then be able to extend the range of applications of MELL, by modelling a broad notion of sequentiality and providing new properties of proofs. We show some proof theoretical results: decomposition and cut elimination. The new operator represents a significant challenge: to get our results we use here for the first time some novel techniques, which constitute a uniform and modular approach to cut elimination, contrary to what is possible in the sequent calculus

Studies on soil fertility status of coffee growing regions in Wayanad district

Top soil in Wayanad region is prone to disturbance and erosion, as the coffee growers’ practice scraping, scuffling and cover digging. It isnecessary to conserve the inherent fertility of top soil by minimum disturbance during farming operations. Otherwise soil deterioration can become one of the major constraints for crop production in the present day exploitative cultivation of plantation crops. It is well known that nutrient availability is influenced by their distribution in the soil as well as other soil characteristics. Soil fertility is the key to meet the nutrient requirement of the crops. Soil test based nutrient management will increase the crop productivity there by helping to save the fertility. The study, carried out to understand the fertility status of the coffee soils, revealed a higher acidity (98%) with deficiencies of calcium (32%), magnesium (96%) and boron (31%) limiting the coffee productivity in the district. The coffee area in the district is strongly acidic (69%) due to lack of liming and continuous use of acid producing fertilizers. Fifty per cent of soil sampleswere high in phosphorus which in turn impair the nutrient balance and affects micronutrient absorption by plants. Deficiency of calcium and magnesium affects uptake of other nutrients which upsets cellular functions. In coffee, boron deficiency will reduce the productivity by affecting flowering and fruit set. Amelioration of soil acidity and optimal use of major, secondary and micronutrients are must to enhance coffee productivity in the district. Application of manures and fertilizers based on soil test values will save the fertilizers and also sustain the soil health. Integrated management of plant nutrients is essential to achieve sustainable coffee crop production