Cultural Magnitude: Interactive visual mapping - A hybrid network for indigenous data

<p>This research has been undertaken in response to the limitations of standard mapping techniques, in particular, those that use ESRI-based technology and delivery. The work argues that our ability to understand the complex nature of indigenous ontologies and spatial models are affected by the available tools and their ontological frameworks. It sets out to visualise, in a tool, traditionally non-physical, but inherently spatial, data and information. The map, in a traditional sense, now becomes a fluid, open, self-referential virtual topography or ‘space’, challenging the rational top-down fixity of western cartographic representation. As an architectural thesis, it seeks to create holistically structured space as a virtual edifice and is concerned with that which is not represented and concludes that the most important aspect of creating a mapping framework for an indigenous ontology is to understand the inseparable relationship between people, knowledge and land. The research describes a tool designed and built by the author that contributes to cultural and spiritual health (whai ora) and wellbeing of Māori. Through its ontological framework, it aims to provide an alternate map that enables users to navigate and share cultural knowledge. The central concept is to ‘re-connect’, in particular, urban and disenfranchised Māori, through the creation of a virtual space that can be customised and inhabited in various ways by its users. It questions and challenges what is included and what is excluded, what can be represented, asking where might culture have a ‘place’? How might people and their environments effect change in themselves? In others? Cultural Magnitude is the exploration of the development of a tool that acts as a digital representation and storage place of whakapapa and taonga, and as a cultural resource for Māori to understand their spiritual bounds to physical locations - a tangible foundation for a digital marae.</p>

Cultural Magnitude: Interactive visual mapping - A hybrid network for indigenous data

<p>This research has been undertaken in response to the limitations of standard mapping techniques, in particular, those that use ESRI-based technology and delivery. The work argues that our ability to understand the complex nature of indigenous ontologies and spatial models are affected by the available tools and their ontological frameworks. It sets out to visualise, in a tool, traditionally non-physical, but inherently spatial, data and information. The map, in a traditional sense, now becomes a fluid, open, self-referential virtual topography or ‘space’, challenging the rational top-down fixity of western cartographic representation. As an architectural thesis, it seeks to create holistically structured space as a virtual edifice and is concerned with that which is not represented and concludes that the most important aspect of creating a mapping framework for an indigenous ontology is to understand the inseparable relationship between people, knowledge and land. The research describes a tool designed and built by the author that contributes to cultural and spiritual health (whai ora) and wellbeing of Māori. Through its ontological framework, it aims to provide an alternate map that enables users to navigate and share cultural knowledge. The central concept is to ‘re-connect’, in particular, urban and disenfranchised Māori, through the creation of a virtual space that can be customised and inhabited in various ways by its users. It questions and challenges what is included and what is excluded, what can be represented, asking where might culture have a ‘place’? How might people and their environments effect change in themselves? In others? Cultural Magnitude is the exploration of the development of a tool that acts as a digital representation and storage place of whakapapa and taonga, and as a cultural resource for Māori to understand their spiritual bounds to physical locations - a tangible foundation for a digital marae.</p>

Knowledge-infused Learning for Entity Prediction in Driving Scenes

Scene understanding is a key technical challenge within the autonomous driving domain. It requires a deep semantic understanding of the entities and relations found within complex physical and social environments that is both accurate and complete. In practice, this can be accomplished by representing entities in a scene and their relations as a knowledge graph (KG). This scene knowledge graph may then be utilized for the task of entity prediction, leading to improved scene understanding. In this paper, we will define and formalize this problem as Knowledge-based Entity Prediction (KEP). KEP aims to improve scene understanding by predicting potentially unrecognized entities by leveraging heterogeneous, high-level semantic knowledge of driving scenes. An innovative neuro-symbolic solution for KEP is presented, based on knowledge-infused learning, which 1) introduces a dataset agnostic ontology to describe driving scenes, 2) uses an expressive, holistic representation of scenes with knowledge graphs, and 3) proposes an effective, non-standard mapping of the KEP problem to the problem of link prediction (LP) using knowledge-graph embeddings (KGE). Using real, complex and high-quality data from urban driving scenes, we demonstrate its effectiveness by showing that the missing entities may be predicted with high precision (0.87 Hits@1) while significantly outperforming the non-semantic/rule-based baselines.

A New S-Box Generation Method and Advanced Design Based on Combined Chaotic System

The construction of substitute box (S-box) has always been an important research direction in cryptography. This paper proposes a new S-box generation method and advanced design based on combined chaotic system. Firstly, our paper proposes a new combined chaotic system and analyze its dynamic behavior. Next, we construct S-box by combining the generated pseudo-random sequence with the linear congruence random number generator, and the standard mapping is introduced to scramble the initial S-box. Then, the S-box optimization method based on advanced genetic algorithm is proposed in this paper. We design adaptive of S-box coding, selection operator, crossover operator and mutation operator to avoid the shortcomings of low calculation efficiency and non-convergence of optimization results in traditional genetic algorithm. Finally, through a lot of security analysis experiments and comparison with other papers, the optimized S-box has better cryptography characteristics and can resist linear attacks and differential attacks.

Improvement of health performance through clinical risk management: the maternal and child pathway

Purpose To improve the performance both in terms of patient safety and quality of treatments, this research studies one of the most delicate processes of health organizations, that is to say, the clinical risk management in maternal and child pathway. This paper aims to analyze the accidents that occurred in a complex health facility through the standard mapping of this pathway included in the CartoRisk, i.e. a risk assessment tool for the a priori analysis. Design/methodology/approach The research uses the case study methodology, as it explores a complex process in which a lot of variables and actors are involved. It analyzes the accidents occurred in the largest health facility at national and European level. Findings After a presentation of the regulatory framework and the studied health organization, the research analyzes the accidents occurred in maternal and child pathway from 2014 to 2018. It showed the main risks according to the standard mapping of the maternal and child pathway. Furthermore, it identified 11 new risks mainly associated with physiologic birth and Caesarean birth. Originality/value This study presents the regulatory framework, the health facility and the accidents of a health organization. Moreover, besides the accident analysis, the research integrates further risks into the standard mapping adopted to carry out this study and proposes a risk management approach. Therefore, the value of the research for operators will consist of the integration of the standard mapping used for a priori analysis to be reused in the hospitals where they work, while for researchers it will represent a deep knowledge of a real case.

Myocardial Mapping in Systemic Sarcoidosis: A Comparison of Two Measurement Approaches

Purpose To investigate if T1 and T2 mapping is able to differentiate between diseased and healthy myocardium in patients with systemic sarcoidosis, and to compare the standard mapping measurement (measurement within the whole myocardium of the midventricular short axis slice, SAX) to a more standardized method measuring relaxation times within the midventricular septum (ConSept). Materials and Methods 24 patients with biopsy-proven extracardiac sarcoidosis and 17 healthy control subjects were prospectively enrolled in this study and underwent CMR imaging at 1.5 T including native T1 and T2 mapping. Patients were divided into patients with (LGE+) and without (LGE–) cardiac sarcoidosis. T1 and T2 relaxation times were compared between patients and controls. Furthermore, the SAX and the ConSept approach were compared regarding differentiation between healthy and diseased myocardium. Results T1 and T2 relaxation times were significantly longer in all patients compared with controls using both the SAX and the ConSept approach (p < 0.05). However, LGE+ and LGE– patients showed no significant differences in T1 and T2 relaxation times regardless of the measurement approach used (ConSept/SAX) (p > 0.05). Direct comparison of ConSept and SAX T1 mapping showed high conformity in the discrimination between healthy and diseased myocardium (Kappa = 0.844). Conclusion T1 and T2 mapping may not only enable noninvasive recognition of cardiac involvement in patients with systemic sarcoidosis but may also serve as a marker for early cardiac involvement of the disease allowing for timely treatment. ConSept T1 mapping represents an equivalent method for tissue characterization in this population compared to the SAX approach. Further studies including follow-up examinations are necessary to confirm these preliminary results. Key Points: Citation Format

Orthomosaics of Historical Aerial Photographs and Horizontal Accuracy Analysis

&lt;p&gt;Orthomosaics from aerial photographs play a pivotal role in understanding land-use/land cover in broad area and the advent of image processing technology allows us to produce orthoimagery. However, recent advanced technologies are seldom applied to produce historical orthophotos from early or mid 20C old aerial photos in broad extent since they have limited information (e.g. camera position, flying altitude, and yaw) which is critical information for orthomosaics. In this context, this study aims to orthomosaic and georectify historical aerial photographs and validate the horizontal accuracy of orthomosacicked outputs. In order to achieve this, firstly, we collected 117 aerial photographs of 1934 (scale 1:12,000) and 68 of 1951 (scale 1:20,000) from UConn air photo achieve focused on Woodstock town in Connecticut, USA. Secondly, we created GCPs (Ground Control Points) as referenced points where they have not changed over time by overlaying multiple datasets such as LiDAR DEM, hillshade map, recent orthoimagery. Thirdly, we align photos with Control Points (CPs), build a mesh, and build orthomosaics of 1934 and 1951, respectively, using Agisoft Photoscan 1.5. Lastly, calculating RMSE (Root Mean Square Error) and offsets comparing between set of GCPs and CPs from Lidar DEM and set of them digitized from orthomosaics. As a result, RMSE values of GCPs and CPs between 1934 and 1951 mostly show that output of this work is acceptable to use for standard mapping and GIS work or visualization based on ASPRS 1990 horizonal accuracy standard. In addition, we found several factors affect horizontal accuracy of orthomosaics; resolution of aerial photos, spatial distribution of GCPs and CPs, the number of CPs and GCPs, the percentage of lateral overlapping area along flight strips, and margin area. Overall, applying automated orthomosaicking image processing to historical aerial photographs has the potential to represent historical landscape and even detect its change in broad extent.&lt;/p&gt;