Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem

Usando um método aprimorado de Mapa Auto-Organizável, fornecemos soluções abaixo do ideal para o Problema do Caixeiro Viajante. Além disso, empregamos o ajuste de hiperparâmetros para identificar os recursos mais críticos do algoritmo. Todas as melhorias no trabalho de benchmark trouxeram resultados consistentes e podem inspirar esforços futuros para melhorar este algoritmo e aplicá-lo a diferentes problemas.

Recovery of Phosphate and Ammonium from Dairy Cow Urine by Struvite Crystallization with Vertical Reactor

Excess phosphate (PO43-) and ammonium (NH4+) in wastewater can cause environmental damages, such as pollutants and eutrophication in water. Dairy cow urine is a dangerous liquid waste that contains high amounts of phosphate and ammonium. The removal of PO4 and NH4 components can be done by crystallizing them into struvite fertilizers. Struvite (MgNH4PO4.6H2O) is a mineral formed from magnesium, ammonium, and phosphate with the equimolar ratio. The crystallization process of struvite is carried out using a vertical reactor. MAP solution (magnesium ammonium phosphate) is prepared by reacting MgCl2, H3PO4, and dairy cow urine with MAP molar ratio of 1 : 1 : 1 and KOH 1N. The study run in pH 8; 8.5; 9; 9.5; 10 and temperature variations of 25, 30, 35, 40, 45˚C in vertical reactor continuously. The struvite precipitate was filtered and dried, it is analyzed by XRF to determine the struvite composition and SEM to determine the morphology of the struvite. The results showed that the best percentage of phosphate and ammonium was at 45˚C and pH 9.5, it was 33.2% and 27.9%.

Interactive Spatial Visualization of Aggregated Non-spatial Coronavirus Data

The article describes the process of aggregation of media-based data about coronavirus pandemic in the Olomouc region, Czech Republic. Originally non-spatially located news from different sources and various platforms (government, social media, news portals) were automatically aggregated into a centralized database. The application “COVID-map” is an interactive web map solution which visualizes records from the database in a spatial way. COVID-map has been developed within Ad hoc online hackathon as an academic project at the Department of Geoinformatics, Palacký University Olomouc, Czech Republic. Alongside spatially localized data, map application collects statistical data from official sources e.g. from the governmental crisis management office.Our approach focuses on cartographical aspects of COVID-map solution. It respects current trends in both development of cartographic oriented outputs and web-based interactive map application. It is fully responsive. Originally, nonspatial data were aggregated, verified, geo-located, and finally visualized in the map environment. The layout combines three main parts: interactive map with spatial data; information panel with updated statistical data; and a sidebar with a filterable list of verified and geo-located news. The main cartographic method used for the visualisation is the choropleth map. It shows the distribution of positively tested people per 10 000 inhabitants for each sub-region. In comparison with similar coronavirus visualisation made during the current pandemic, our solution respects fundamental cartographical rules.Following cartographical topics are discussed in the article: the correct choice of cartographic method and its implementation; determination of a colour scale; recalculation statistics data into relative units by choropleths map method; design of map symbols and legend; searching for a suitable visualization of spatial and non-spatial sources into map layout; discussion on the suitability of using a clustering method.The motivation for this project was both social responsibility and dissatisfaction with the wrong implementation of basic cartographic methods in a variety of alternative solutions. The impact was immediate. Within a few days after the launch, tens of thousands users per day visited the COVID-map. It has been published by regional and national media. The COVID-map solution could be considered as a suitable ad-hoc implementation of the correctly used cartographical method on the example of coronavirus pandemic. The application “COVID-map” is available online at URL: https://gis.upol.cz/covid/mapa/.

Non-Spatial Data towards Spatially Located News about COVID-19: A Semi-Automated Aggregator of Pandemic Data from (Social) Media within the Olomouc Region, Czechia

The article describes the process of aggregation of media-based data about the coronavirus pandemic in the Olomouc region, the Czech Republic. Originally non-spatially located news from different sources and various platforms (government, social media, news portals) were automatically aggregated into a centralized database. The application “COVID-map” is an interactive web map solution which visualizes records from the database in a spatial way. The COVID-map has been developed within the Ad hoc online hackathon as an academic project at the Department of Geoinformatics, Palacký University Olomouc, Czech Republic. Alongside spatially localized data, the map application collects statistical data from official sources e.g., from the governmental crisis management office. The impact of the application was immediate. Within a few days after the launch, tens of thousands users per day visited the COVID-map. It has been published by regional and national media. The COVID-map solution could be considered as a suitable implementation of the correctly used cartographical method for the example of the coronavirus pandemic.

Mass transfer process study of Fe(III) extraction from ammonium dihydrogen phosphate solution

The crystallization of ammonium dihydrogen phosphate (MAP) is largely affected by certain metal ions such as Fe (III), and the influence seems to be pointed at both ends. Therefore, the industrial-grade MAP products can only be obtained by purifying the neutralized MAP solution from wet-process phosphoric acid (WPA). The extraction kinetics of Fe (III) from MAP solution using di-2-ethylhexyl phosphoric acid (D2EHPA) in sulfonated kerosene measured by the Lewis cell. The extraction mechanism is discussed and confirmed on the basis of the dimeric model of D2EHPA in non-polar solution. From the temperature dependence of reaction rate, the value of Ea and Kf are calculated and the extraction regimes are deduced to be mixed controlled with diffusion and chemical reaction for Fe (III). Ultimately, the rate equation for the extraction reaction of Fe (III) with D2EHPA is obtained as follows: Rf = 0.028cFe3+1.2cH2A2 0.81cH+-0.85.

Exploring the Laplace Prior in Radio Tomographic Imaging with Sparse Bayesian Learning towards the Robustness to Multipath Fading

Radio tomographic imaging (RTI) is a technology for target localization by using radiofrequency (RF) sensors in a wireless network. The change of the attenuation field caused by thetarget is represented by a shadowing image, which is then used to estimate the target’s position.The shadowing image can be reconstructed from the variation of the received signal strength (RSS)in the wireless network. However, due to the interference from multi-path fading, not all the RSSvariations are reliable. If the unreliable RSS variations are used for image reconstruction, someartifacts will appear in the shadowing image, which may cause the target’s position being wronglyestimated. Due to the sparse property of the shadowing image, sparse Bayesian learning (SBL) canbe employed for signal reconstruction. Aiming at enhancing the robustness to multipath fading,this paper explores the Laplace prior to characterize the shadowing image under the frameworkof SBL. Bayesian modeling, Bayesian inference and the fast algorithm are presented to achieve themaximum-a-posterior (MAP) solution. Finally, imaging, localization and tracking experiments fromthree different scenarios are conducted to validate the robustness to multipath fading. Meanwhile,the improved computational efficiency of using Laplace prior is validated in the localization-timeexperiment as well.

2D Deconvolution Using Adaptive Kernel

An analysis tool using Adaptive Kernel to solve an ill-posed inverse problem for a 2D model space is introduced. It is applicable for linear and non-linear forward models, for example in tomography and image reconstruction. While an optimisation based on a Gaussian Approximation is possible, it becomes intractable for more than some hundred kernel functions. This is because the determinant of the Hessian of the system has be evaluated. The SVD typically used for 1D problems fails with increasing problem size. Alternatively Stochastic Trace Estimation can be used, giving a reasonable approximation. An alternative to searching for the MAP solution is to integrate using Marcov Chain Monte Carlo without the need to determine the determinant of the Hessian. This also allows to treat problems where a linear approximation is not justified.

Colonial Scout: A Powerful Web Map Solution Designed As the Data Messenger for Colonial Pipeline Company

Colonial pipeline’s asset data management team maintains large volumes of data, CAD facility drawings, and historical records. Organizing and encapsulating this data has been a historical challenge. Frequent requests for data relevant to individual projects was time-consuming and laborious. Colonial Scout was designed to be a simple self-help tool that allows employees to locate data quickly. Further, it was constructed to provide a one-stop shop for accessing Colonial data in its most current and up to date forms. Design of the Colonial Scout application took approximately six months to complete. The final result is an intuitive web map application connected to a versioned enterprise geodatabase. Within the application, relevant tools interact with live data, providing immediate access to Colonial’s most up to date information. Integration with FME server, adept document management and Esri’s ArcGIS enterprise have advanced colonial scout’s efficiency in locating data. These software products enhance colonial scout’s power as a help-yourself product for accessing current information through means of helpful data visualization. Colonial Scout is the go to source for alignment sheets, CAD drawings, property and easement records, locating tank assets, and Colonial’s 5,500 miles of pipeline assets. Users also have the ability to download data in a variety of file formats for project specific analysis and reports. Colonial Scout has significantly reduced the number of work orders related to searching for data, drawings and records. Employees are better informed by acquiring the latest information and no longer rely on outdated paper hardcopies. Colonial Scout is an innovative and expandable solution for Colonial’s ever-growing data needs.

A 3D Relative-Motion Context Constraint-Based MAP Solution for Multiple-Object Tracking Problems

Multi-object tracking (MOT), especially by using a moving monocular camera, is a very challenging task in the field of visual object tracking. To tackle this problem, the traditional tracking-by-detection-based method is heavily dependent on detection results. Occlusion and mis-detections will often lead to tracklets or drifting. In this paper, the tasks of MOT and camera motion estimation are formulated as finding a maximum a posteriori (MAP) solution of joint probability and synchronously solved in a unified framework. To improve performance, we incorporate the three-dimensional (3D) relative-motion model into a sequential Bayesian framework to track multiple objects and the camera’s ego-motion estimation. A 3D relative-motion model that describes spatial relations among objects is exploited for predicting object states robustly and recovering objects when occlusion and mis-detections occur. Reversible jump Markov chain Monte Carlo (RJMCMC) particle filtering is applied to solve the posteriori estimation problem. Both quantitative and qualitative experiments with benchmark datasets and video collected on campus were conducted, which confirms that the proposed method is outperformed in many evaluation metrics.

Developing a better Common Operating Picture (COP) using open source data in a web map solution.

ABSTRACT How can the responders of an oil spill operation make sure that the Common Operating Picture (COP) gives the situational awareness that is needed? How can the response personnel avoid producing and consuming so much data that the COP gets overloaded with information? How can the users differentiate the “need to have” from the “nice to have” data? And what type of information do response personnel need offshore, and is that same information relevant for the Incident Command Post? These are some of the questions that NOFO has discussed with the Norwegian Coastal Administration, our partner in the project “Web based map solution”. The project has so far developed a shoreline response tool, consisting of a web map solution and a mobile application (App). With the “Shoreline App” you can collect data in the field, take pictures and video, view oil contamination, and quickly communicate this to the web map-solution. This new technology enables the response organisation to document and act faster, more efficient with increased accuracy. The shoreline clean-up module includes SCAT, work assignments and daily reports from the field, as well as statistics and analysing tools. Inspired by IOGP-IPIECA (2015), NOFO have started to improve the NOFO COP OSR (oil spill response) to cover offshore, nearshore and shoreline operations. The scope for this work is to create a seamless integration of the different data that we receive, especially the surveillance sensor data such as aerial overflights, satellite images, images from ships and UAVs (unmanned aerial vehicles). All the data registered in the system are given a predefined timeframe in which they will automatically be deactivated from the COP. This aids us in managing the data flow, presenting the latest information available, and avoid taking action based on outdated information. A timeline gives either predictions, real time information or historical data, and enables the user to “play off” the incident from Day 1 until the end, or even for a specific period. The Adaptive interface, which is the platform the NOFO COP OSR uses, features the possibility to build different COP viewpoints for different levels in the response organisation. The NOFO COP OSR may also be used for communication externally during and after clean-up efforts. The public and press can get limited insight through role-based access. Based on the collected data, statistics and graphs are easily generated for use in the preparation of reports and presentations.