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As the amount of software source code increases, manual approaches for documentation or detection of software design patterns in source code become inefficient relative to the value. Furthermore, typical automatic pattern detection tools are limited to a single programming language. To address this, our Design Pattern Detection using Machine Learning (DPDML) offers a generalized and programming language agnostic approach for automated design pattern detection based on machine learning (ML). The focus of our evaluation was on ensuring DPDML can reasonably detect one design pattern in the structural, creational, and behavioral category for two popular programming languages (Java and C#). 60 unique Java and C# code projects were used to train the artificial neural network (ANN) and 15 projects were then used to test pattern detection. The results show the feasibility and potential for pursuing an ANN approach for automated design pattern detection.
In the present work the influence of industry-standard heat treatment on ultra-high strength aluminium alloys has been investigated under terms of various forming processes. For this purpose, a scaled side impact beam was formed out of AA7075 via Hotforming and W-Temper techniques and subjected to a heat treatment process. The test material was taken from several material suppliers in order to identify any variation of the mechanical properties. Based on uniaxial tensile tests the final material properties were evaluated and compared. Using the W-Temper and Hotforming process, the parts produced without a subsequent heat treatment show no influence concerning the suppliers. A significant difference of the material behaviour can be seen if single-step paint bake cycle is applied. Here, the ultimate tensile strength (UTS) values and those for yield strength vary up to 9% and 16% respectively.
Novel myopia control spectacle lenses induce peripheral contrast reduction via optical diffusion. It is suggested, that the contrast reduction alters retinal processes in the low-level neural circuity, leading to an inhibition of eye growth. The purpose of this thesis is to evaluate the influence of full-field contrast reduction on low-level neural processing of the retina, described by the edge contrast sensitivity.
The digital transformation occurring in enterprises results in an in- creasingly dynamic and complex IT landscape that in turn impacts enterprise architecture (EA) and its artefacts. New approaches for dealing with more com- plex and dynamic models and conveying EA structural and relational insights are needed. As EA tools attempt to address these challenges, virtual reality (VR) can potentially enhance EA tool capabilities and user insight but further investigation is needed in how this can be achieved. This paper contributes a VR solution concept for visualizing, navigating, and interacting with EA tool dynamically-generated diagrams and models using the EA tool Atlas. An im- plementation shows its feasibility and a case study using EA scenarios is used to demonstrate its potential.
Nowadays, businesses with focus on consumer-products are challenged by short production cycles, high pricing pressure, and the need to deliver new features and services in a regular interval. Currently, businesses are tackling these challenges by automating their business pro- cesses, while yet trying to be flexible by introducing methods for process variability modeling. However, for larger processes and variability models, it becomes difficult to consider, maintain, and optimize all process variations in the various execution contexts. In software development, highly agile requirements are usually tackled with a flexible microservice architecture. Nonetheless, the fast-changing service landscape is often not fully reflected in the underlying business processes, leading to inefficiency and loss of profit. With this work, we extend our framework for process variability modeling with concepts of Microflows, allowing agile business process modeling and orchestration while utilizing the full flexibility of underlying microservices. In addition, we present a case study, showing how this approach is used in the context of an IoT application
The direct ophthalmoscope is a retinal screening tool that has been in existence and development for more than 150 years, yet, the rapid influence of technological evolution in screening tools, has left the direct ophthalmoscope untouched. The main purpose of this master thesis is to determine if the direct ophthalmoscope has reached its maximum potential of development and, additionally, to determine if a further development, including a more electronic input, would be feasible.
This research project is of particular importance since there is a lack of adequate data on pediatric eye and vision disorders in Russia, particularly in the Volga region. In the present study, we estimate the prevalence of vision disorders among school-aged children who participated in a vision screening program in Samara, Russia. The relationship between learning-related visual dysfunctions is explored in depth, such to illustrate the connection between vision and learning. Hence, a key feature in this study is the inclusion of binocular vision disorders among the conditions tested.