background and aims. in order to fabricate prostheses with high accuracy and durability, soldering techniques have been introduced to clinical dentistry. however, these prostheses always fail at their solder joints. the purpose of this study was to evaluate the effect of gap distance on the tensile strength of base metal solder joints. materials and methods. based on ada/iso 9693 specifications...

Measuring the similarity of two polygonal curves is a fundamental computational task. Among alternatives, the Fréchet distance is one of the most well studied similarity measures. Informally, the Fréchet distance is described as the minimum leash length required for a man on one of the curves to walk a dog on the other curve continuously from the starting to the ending points. In this paper we ...

Symmetric disk graphs are often used to model wireless communication networks. Given a set S of n points in R (representing n transceivers) and a transmission range assignment r : S → R, the symmetric disk graph of S (denoted SDG(S)) is the undirected graph over S whose set of edges is E = {(u, v) | r(u) ≥ |uv| and r(v) ≥ |uv|}, where |uv| denotes the Euclidean distance between points u and v. ...

Environmental and sustainability education (ESE) traditionally relies on green teaching environments active participation. Thus, during the lockdown phase, a gap between curricular goals learning outcomes appeared. This study investigates impact of ESE distance 288 Bavarian fifth-graders factors that could bridge this gap. The influence digital preferences progress is examined compared with fas...

In this investigation, the material removal rate, tool wear rate and surface integrity obtained by EDM, ultrasonic vibrations assisted EDM and magnetic field assisted EDM were studied and compared with together to show the quality of the effects of applying each of ultrasonic vibrations to tool and magnetic field around gap distance of EDM process on material removal rate, tool wear rate, and s...

Vectored data frequently occur in a variety of fields, which are easy to handle since they can be mathematically abstracted as points residing in a Euclidean space. An appropriate distance metric in the data space is quite demanding for a great number of applications. In this paper, we pose robust and tractable metric learning under pairwise constraints that are expressed as similarity judgemen...

Distance-based and generalisation-based methods are two families of artificial intelligence techniques that have been successfully used over a wide range of real-world problems. In the first case, general algorithms can be applied to any data representation by just changing the distance. The metric space sets the search and learning space, which is generally instance-oriented. In the second cas...