ARROW (Version 2) Commercial Software Validation and Configuration Control

In 1998, the capacity of the BIOSTYR® submerged biofilter at Nyborg WWTP was extended from 48,000 PE to 60,000 PE including advanced sensor based control, post-denitrification in BIOSTYR® and equalization of side flows. The existing configuration with 8 BIOSTYR® DN/N cells is based on pre-denitrification and an internal recirculation of 600–800%. The extended plant comprises 7 BIOSTYR® DN/N cells with 50–225% recirculation followed by 3 BIOSTYR DN cells for post-denitrification. The advanced control loops include blower control, control of the number of active cells (stand-by), automatic switch to high load configuration, control of the side flow equalization, control of the internal recirculation and control of the external carbon source dosing. In this paper, the achieved improvements are documented by comparing influent and effluent data, methanol and energy consumption from comparable periods before and after the extension. Although the nitrogen load to the plant was increased by 20% after the extension, the effluent quality has improved significantly with a reduction of Total-N from 7–8 mg/l to 3–4 mg/l. Simultaneously, the methanol consumption has been reduced by more than 50% per kg removed nitrogen. The energy consumption remained constant although the nitrogen load was increased by 20% and the inflow by 80%.

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Graph-Based Construction of 3D Korean Giwa House Models

Buildings ◽

10.3390/buildings9030068 ◽

2019 ◽

Vol 9 (3) ◽

pp. 68

Author(s):

Mankyu Sung

Keyword(s):

Data Structure ◽

Computer Graphics ◽

Real Time ◽

Texture Image ◽

Time Rate ◽

Commercial Software ◽

Spline Curve ◽

High Level ◽

Complicated Part ◽

Different Parts

This paper proposes a graph-based algorithm for constructing 3D Korean traditional houses automatically using a computer graphics technique. In particular, we target designing the most popular traditional house type, a giwa house, whose roof is covered with a set of Korean traditional roof tiles called giwa. In our approach, we divided the whole design processes into two different parts. At a high level, we propose a special data structure called ‘modeling graphs’. A modeling graph consists of a set of nodes and edges. A node represents a particular component of the house and an edge represents the connection between two components with all associated parameters, including an offset vector between components. Users can easily add/ delete nodes and make them connect by an edge through a few mouse clicks. Once a modeling graph is built, then it is interpreted and rendered on a component-by-component basis by traversing nodes in a procedural way. At a low level, we came up with all the required parameters for constructing the components. Among all the components, the most beautiful but complicated part is the gently curved roof structures. In order to represent the sophisticated roof style, we introduce a spline curve-based modeling technique that is able to create curvy silhouettes of three different roof styles. In this process, rather than just applying a simple texture image onto the roof, which is widely used in commercial software, we actually laid out 3D giwa tiles on the roof seamlessly, which generated more realistic looks. Through many experiments, we verified that the proposed algorithm can model and render the giwa house at a real time rate.

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Algorithm selection for software validation based on graph kernels

Automated Software Engineering ◽

10.1007/s10515-020-00270-x ◽

2020 ◽

Vol 27 (1-2) ◽

pp. 153-186

Author(s):

Cedric Richter ◽

Eyke Hüllermeier ◽

Marie-Christine Jakobs ◽

Heike Wehrheim

Keyword(s):

Software Validation ◽

Algorithm Selection ◽

Graph Kernels ◽

Selection For

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DSM Generation from Single and Cross-Sensor Multi-View Satellite Images Using the New Agisoft Metashape: The Case Studies of Trento and Matera (Italy)

Remote Sensing ◽

10.3390/rs13040593 ◽

2021 ◽

Vol 13 (4) ◽

pp. 593

Author(s):

Lorenzo Lastilla ◽

Valeria Belloni ◽

Roberta Ravanelli ◽

Mattia Crespi

Keyword(s):

Case Studies ◽

Accuracy Assessment ◽

Stereo Pair ◽

Commercial Software ◽

Processing Module ◽

Land Covers ◽

Image Metadata ◽

The Impact ◽

The City ◽

Reliable Software

DSM generation from satellite imagery is a long-lasting issue and it has been addressed in several ways over the years; however, expert and users are continuously searching for simpler but accurate and reliable software solutions. One of the latest ones is provided by the commercial software Agisoft Metashape (since version 1.6), previously known as Photoscan, which joins other already available open-source and commercial software tools. The present work aims to quantify the potential of the new Agisoft Metashape satellite processing module, considering that to the best knowledge of the authors, only two papers have been published, but none considering cross-sensor imagery. Here we investigated two different case studies to evaluate the accuracy of the generated DSMs. The first dataset consists of a triplet of Pléiades images acquired over the area of Trento and the Adige valley (Northern Italy), which is characterized by a great variety in terms of geomorphology, land uses and land covers. The second consists of a triplet composed of a WorldView-3 stereo pair and a GeoEye-1 image, acquired over the city of Matera (Southern Italy), one of the oldest settlements in the world, with the worldwide famous area of Sassi and a very rugged morphology in the surroundings. First, we carried out the accuracy assessment using the RPCs supplied by the satellite companies as part of the image metadata. Then, we refined the RPCs with an original independent terrain technique able to supply a new set of RPCs, using a set of GCPs adequately distributed across the regions of interest. The DSMs were generated both in a stereo and multi-view (triplet) configuration. We assessed the accuracy and completeness of these DSMs through a comparison with proper references, i.e., DSMs obtained through LiDAR technology. The impact of the RPC refinement on the DSM accuracy is high, ranging from 20 to 40% in terms of LE90. After the RPC refinement, we achieved an average overall LE90 <5.0 m (Trento) and <4.0 m (Matera) for the stereo configuration, and <5.5 m (Trento) and <4.5 m (Matera) for the multi-view (triplet) configuration, with an increase of completeness in the range 5–15% with respect to stereo pairs. Finally, we analyzed the impact of land cover on the accuracy of the generated DSMs; results for three classes (urban, agricultural, forest and semi-natural areas) are also supplied.

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