High Level Of Detail Research Articles

Fractal dimension, lacunarity, and Shannon entropy of self-assembled macroscopic copper dendrites

Macroscopic copper dendrites are self-assembled in a porous hydrogel without the application of an external potential. The copper dendrites possess fractal characteristics. The impact of the medium thickness, the initial concentration of copper (II) ions, and the solvent polarity on the evolving copper dendrites are addressed by investigating the fractal dimension, lacunarity, and Shannon entropy (SE) of the structures. The analysis gives a quantitative description of the copper dendritic morphology and its connection to the mechanism of self-assembly. The fractal dimension of the dendrites falls in the range of 1.75–1.85. High self-similar complex systems show low lacunarity and high Shannon entropy, reflecting the low density of gaps and the high level of detail.

Cultural heritage characteristics and damage analysis based on multidimensional data fusion and HBIM–taking the former residence of HSBC bank in Xiamen, China as an example

In the context of digitalizing cultural heritage, HBIM is garnering increasing attention from heritage conservationists for its advantages. In conservation practices for cultural heritage, expressing regional characteristics and documenting in HBIM has become increasingly crucial, and these needs are inextricably linked to the need for models with a high level of detail (LOD). This paper presents a combination of Terrestrial Laser Scanning surveys, UAV photogrammetry, and handheld laser scanning to scan cultural heritage. The scan data obtained from multiple digital surveys serves as the foundation for modelling HBIM. For the regional characteristics, the HBIM model was built with detailed geometric shapes, configurations, materials, and colors of each element, as well as complex patterns and damage using the parametric models and mesh models. The information of the building and its components stored in the HBIM model. Consequently, obtained a highly detailed HBIM that not only captures the intricate details of the ideal state and real-world damage and degradation with minimal error but also serves as a repository for a multitude of information types. It has been concluded that a high LOD is essential to representing the regional geometric feature of a building and recording the damage of cultural heritage.

Methodology for the Integration of Structural Health Assessment of Masonry Bridges into HBIM

ABSTRACT A methodology is proposed to efficiently develop BIM models of masonry arch bridges, with the objective of generating databases (Level of Information, LoI) associated with 3D geometrical models, incorporating different levels of detail (LoD). The use of parametric libraries is implemented to develop the models. The first step is to perform an experimental campaign to obtain initial data. With these data and the parametric library previously created, a parametric model of the structure is generated (low LoD). A map of the vulnerable areas of the structure is created on this model and the available information is linked to it. A structural model (high LoD) is also created and calibrated. With all this information, an HBIM file is generated. A second experimental campaign is performed on the structure using non-destructive techniques. Point clouds, OMA data, photographs, and visual inspections from the different experimental campaigns are compared to the original HBIM file. In addition, to validate the usefulness of the parametric library, its implementation is carried out on three other historic masonry structures. This comprehensive and technologically advanced approach proves to be a promising strategy for the conservation and sustainable management of architectural heritage.

FoodEx2 Harmonization of the Food Consumption Database from the Italian IV SCAI Children's Survey.

Estimating the habitual food and nutrient intakes of a population is based on dietary assessment methods that collect detailed information on food consumption. Establishing the list of foods to be used for collecting data in dietary surveys is central to standardizing data collection. Comparing foods across different data sources is always challenging. Nomenclatures, detail, and classification into broad food groups and sub-groups can vary considerably. The use of a common system for classifying and describing foods is an important prerequisite for analyzing data from different sources. At the European level, EFSA has addressed this need through the development and maintenance of the FoodEx2 classification system. The aim of this work is to present the FoodEx2 harmonization of foods, beverages, and food supplements consumed in the IV SCAI children's survey carried out in Italy. Classifying foods into representative food categories predefined at European level for intake and exposure assessment may lead to a loss of information. On the other hand, a major advantage is the comparability of data from different national databases. The FoodEx2 classification of the national food consumption database represented a step forward in the standardization of the data collection and registration. The large use of FoodEx2 categories at a high level of detail (core and extended terms) combined with the use of descriptors (facets) has minimized information loss and made the reference food categories at country level comparable with different food databases at national and international level.

Energy Performance Analysis of the Renovation Process in an Italian Cultural Heritage Building

Renovating buildings with cultural heritage significance is an important step toward achieving sustainability in our cities. The benefits are not only energy-related but also encompass social aspects that make these renovations a high apriority. The present work investigates the renovation process of a cultural heritage building in the Municipality of Trento in Italy, specifically focusing on achieving energy savings and renewable energy integration by implementing various renovation actions. These renovation actions include improvements to the building envelope, such as roof insulation and window replacements. Additionally, the renovation actions for active systems involve the installation of a ground-source heat pump for heating/cooling coupled with a borehole thermal energy storage system, which is an innovative technology for the renovation of cultural heritage buildings. The electrical systems of the building are upgraded through the addition of standard rooftop photovoltaics, innovative building-integrated photovoltaics (shingles), and the installation of an LED lighting system. The baseline and the renovation scenarios are studied using the dynamic simulation tool INTEMA.building, written in the programming language Modelica. This tool simulates both the building envelope and the energy systems with a high level of detail, using advanced control systems and adjustable time steps. According to the simulation analysis, the primary energy demand is reduced by 30.49%, the final energy demand by 36.74%, and the net electricity demand by 8.72%. Results from this study can be useful to interested stakeholders (e.g., building owners, architects, construction companies, public agents, and urban planners) dealing with the renovation of cultural heritage and protected buildings. Also, the results can be exploited for estimating energy savings by applying advanced renovation strategies for cultural heritage buildings.

An efficient multi‐scale transformer for satellite image dehazing

AbstractGiven the impressive achievement of convolutional neural networks (CNNs) in grasping image priors from extensive datasets, they have been widely utilized for tasks related to image restoration. Recently, there is been significant progress in another category of neural architectures—Transformers. These models have demonstrated remarkable performance in natural language tasks and higher‐level vision applications. Despite their ability to address some of CNNs limitations, such as restricted receptive fields and adaptability issues, Transformer models often face difficulties when processing images with a high level of detail. This is because the complexity of the computations required increases significantly with the image's spatial resolution. As a result, their application to most high‐resolution image restoration tasks becomes impractical. In our research, we introduce a novel Transformer model, named DehFormer, by implementing specific design modifications in its fundamental components, for example, the multi‐head attention and feed‐forward network. Specifically, the proposed architecture consists of the three modules, that is, (a) multi‐scale feature aggregation network (MSFAN), (b) the gated‐Dconv feed‐forward network (GFFN), (c) and the multi‐Dconv head transposed attention (MDHTA). For the MDHTA module, our objective is to scrutinize the mechanics of scaled dot‐product attention through the utilization of per‐element product operations, thereby bypassing the need for matrix multiplications and operating directly in the frequency domain for enhanced efficiency. For the GFFN module, which enables only the relevant and valuable information to advance through the network hierarchy, thereby enhancing the efficiency of information flow within the model. Extensive experiments are conducted on the SateHazelk, RS‐Haze, and RSID datasets, resulting in performance that significantly exceeds that of existing methods.

Doing more with less: Realistic stereoscopic three-dimensional anatomical modeling from smartphone photogrammetry.

Traditional teaching methods struggle to convey three-dimensional concepts effectively. While 3D virtual models and virtual reality platforms offer a promising approach to teaching anatomy, their cost and specialized equipment pose limitations, especially in disadvantaged areas. A simpler alternative is to use virtual 3D models displayed on regular screens, but they lack immersion, realism, and stereoscopic vision. To address these challenges, we developed an affordable method utilizing smartphone-based 360° photogrammetry, virtual camera recording, and stereoscopic display (anaglyph or side-by-side technique). In this study, we assessed the feasibility of this method by subjecting it to various specimen types: osteological, soft organ, neuroanatomical, regional dissection, and a dedicated 3D-printed testing phantom. The results demonstrate that the 3D models obtained feature a complete mesh with a high level of detail and a realistic texture. Mesh and texture resolutions were estimated to be approximately 1 and 0.2 mm, respectively. Additionally, stereoscopic animations were both feasible and effective in enhancing depth perception. The simplicity and affordability of this method position it as a technique of choice for creating easily photorealistic anatomical models combined with stereoscopic depth visualization.

Quantifying the impact of modeling fidelity on different substructure concepts for floating offshore wind turbines – Part 1: Validation of the hydrodynamic module QBlade-Ocean

Abstract. To realize the projected increase in worldwide demand for floating offshore wind, numerical simulation tools must capture the relevant physics with a high level of detail while being numerically efficient. This allows engineers to have better designs based on more accurate predictions of the design driving loads, potentially enabling an economic breakthrough. The existing generation of offshore wind turbines is reaching a juncture, where traditional approaches, such as the blade element momentum theory, are becoming inadequate due to the increasing occurrence of substantial blade deflections. QBlade is a tool that includes a higher-fidelity aerodynamic model based on lifting-line theory, capable of accurately modeling such scenarios. In order to enable the simulation of offshore conditions in QBlade and to make use of this aerodynamic capability for novel offshore wind turbine designs, a hydrodynamic module called QBlade-Ocean was developed. In the present work, this module is validated and verified with two experimental campaigns and two state-of-the-art simulation frameworks on three distinct floating offshore wind turbine concepts. The results confirm the implementation work and fully verify QBlade as a tool to be applied in offshore wind turbine simulations. Moreover, a method aimed to improve the prediction of non-linear motions and loads under irregular wave excitation is analyzed in various conditions. This method results in a significant improvement in the surge and pitch degrees of freedom in irregular wave cases. Once wind loads are included, the method remains accurate in the pitch degree of freedom, while the improvements in the surge degree of freedom are reduced. A code-to-code comparison with the industry-designed Hexafloat concept highlights the coupled interactions on floating turbines that can lead to large differences in motion and load responses in otherwise identically behaving simulation frameworks.

Analytical Framework to Understand the Origins of Methyl Side-Chain Dynamics in Protein Assemblies.

Side-chain motions play an important role in understanding protein structure, dynamics, protein-protein, and protein-ligand interactions. However, our understanding of protein side-chain dynamics is currently limited by the lack of analytical tools. Here, we present a novel analytical framework employing experimental nuclear magnetic resonance (NMR) relaxation measurements at atomic resolution combined with molecular dynamics (MD) simulation to characterize with a high level of detail the methyl side-chain dynamics in insoluble protein assemblies, using amyloid fibrils formed by the prion HET-s. We use MD simulation to interpret experimental results, where rotameric hops, including methyl group rotation and χ1/χ2 rotations, cannot be completely described with a single correlation time but rather sample a broad distribution of correlation times, resulting from continuously changing local structure in the fibril. Backbone motion similarly samples a broad range of correlation times, from ∼100 ps to μs, although resulting from mostly different dynamic processes; nonetheless, we find that the backbone is not fully decoupled from the side-chain motion, where changes in side-chain dynamics influence backbone motion and vice versa. While the complexity of side-chain motion in protein assemblies makes it very challenging to obtain perfect agreement between experiment and simulation, our analytical framework improves the interpretation of experimental dynamics measurements for complex protein assemblies.

A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics.

Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.

Discrete space-time processing in multifunctional radar systems

In radar systems, all basic tasks, from signal detection to their recognition, are solved under conditions of a priori uncertainty arising, among other things, due to natural or organized interference. The task of maintaining a balance between the speed of the information-measuring and control system and the detail of the assessment of the phase coordinates of targets is of particular relevance in modern on-board multifunctional radar systems of fighter aircraft. In such systems, all basic tasks are solved with strict restrictions on space-time resources. The purpose of the work is to analyze the options for reviewing the airspace that provide the solution of basic tasks in multifunctional radar systems with restrictions on the permissible time of observation of targets and taking into account electronic countermeasures. Based on the analysis performed using performance indicators that ensure the noise immunity of multifunctional radar systems, rational variants of a discrete space-time survey for active phased antenna arrays are proposed. In modern antennas with electromechanical scanning, two space viewing modes are used – continuous direction-finding mode and on-pass tracking. In the continuous direction-finding mode, the detail of the phase coordinate estimates is realized only for a single target, but the secrecy of the actions of the multifunctional radar system is not ensured. In the pass-through tracking mode, a high level of detail is provided for assessing the phase coordinates of targets and the noise immunity of multifunctional radar systems. Therefore, in this mode, it is advisable to evaluate only the noise immunity of multifunctional radar systems against the background of natural interference. The greatest detail of estimates of the phase coordinates of targets and noise immunity are achieved in multifunctional radar systems with active phased antenna arrays, the element base of which allows for a fast discrete space-time overview when all parameters of the electromagnetic wave change, including its polarization, according to pseudo-random laws. The use of modern onboard time standards with stability up to 〖10〗^(-18) in combination with high-speed electromechanical switches will significantly increase the detail of the evaluation of the phase coordinates of targets and noise immunity, including during group actions of aircraft. The proposed review options relate to a new priority scientific and technical direction  correction of techniques (principles, methods and algorithms) for the construction of avionics using technological advances in the development of the element base of active phased antenna arrays.

Technoeconomic characterisation of low-carbon liquid hydrocarbons production

With growing attention on low-carbon fuels and chemicals to meet climate targets, careful cost and performance evaluations become critical. These hydrocarbons can be derived from biomass or hydrogen with captured CO2 via established pathways such as Fischer-Tropsch and methanol synthesis. Techno-economic studies are influential in identifying the economic viability of promising technologies in the absence of reliable industry data. A considerable number of techno-economic studies that represent same technologies exhibit substantial variability in their estimations, posing challenges in decision-making. This work aims to characterise, based on available data, the investment cost and plant performance for the Nth (i.e. mature) low-carbon liquid hydrocarbon plants. The extent of data variabilities across technologies are presented and the factors contributing to differences in data interpretation and normalisation are determined. Through a full assessment of existing values, central tendencies for prospective techno-economic evaluations are identified. Processes utilising biomass have the greatest ranges in the investment cost, with higher costs from studies with the highest level of detail and proximity to real-world plant cost estimations. Energy efficiency variabilities arise when tied to plants with multiple outputs. Demonstration scale hydrogen-to-hydrocarbons in relation to economies of scale should be carefully evaluated.

OCT Images Diagnosis Based on Deep Learning – A Review

The recent advancements in deep learning technology have significantly transformed the field of medical imaging, namely in the diagnosis of ocular illnesses. The progress made in this field has improved the capacity to extract and evaluate intricate characteristics in images, with Optical Coherence Tomography (OCT) playing a crucial role. OCT has become known for its safe qualities and its high level of detail, rendering it an essential instrument in the diagnosis of eye diseases. The interesting improvement in research is centered around the integration of deep learning with OCT for the purpose of automating the detection of eye diseases. We conducted a comprehensive study that explores several diagnostic methods and the wide-ranging uses of OCT. Additionally, it addresses the accessibility of publicly available datasets that are specifically tailored to optical coherence tomography (OCT). The paper provides a detailed review of the most recent advancements in computer-assisted diagnostic methods for diseases of the eye, such as age-related macular degeneration, glaucoma, and diabetic macular edema, with a particular focus on the effective use of OCT. Moreover, the paper systematically analyzes the primary challenges that deep learning faces in OCT image interpretation, emphasizing the intricate nature and possibilities of this field.

Mapping pressures on biodiversity: the contribution of thematic detail to decision making

Mapping pressures to species is key to identify where biodiversity is at risk and providing relevant information to direct conservation actions. Decision-making to minimise pressures requires the determination of specific target actions at a high level of detail. However, the trade-off between cost and effort to generate this information often leads to the production of generalised pressure maps, named coarse maps, covering the most relevant pressures and their proxies. Here we aimed to disentangle whether the cost and effort of mapping fine pressures is worthwhile to inform decision making, by comparing how fine and coarse maps identify “where” and “how” management actions should be derived. Comparing the extend of both map types as well as its capacity to identify risk areas. We focused on three main pressures: agricultural intensification, human intensification, and land abandonment. The study was carried out in Catalonia for local decision-making, but the results can be applied in other EU regions or elsewhere, also for local decisions-making. We found that the Jaccard’s similarity index between coarse and fine pressure maps was always below 0.3 indicating low overlap between fine and coarse maps. In particular, the coincidence between coarse and fine thematic maps within protected areas (PAs) was always below 50%. Both maps differed in the identification of risk areas inside three analysed PAs. Moreover, even when there was a total geographical overlap between coarse and fine maps, coarse maps lack information on which concrete pressure was actually present, making decision on actions needed difficult. Thus, we can conclude that fine maps can estimate more accurately both “where” and “how” to target concrete actions than coarser maps. Even in cases where the answer as to “where” to act is the same, fine maps provide more concrete information to provide guidance on “how” to act. Consequently, despite the high cost and effort involved in mapping pressures at a high level of detail, the final trade-off is positive.

THE ROLE OF MARKETING INTERNET COMMUNICATIONS IN THE RE-ENGINEERING OF BUSINESS PROCESSES OF TOURIST ACTIVITIES

Purpose. Research and analyze the significance of marketing internet communications in reengineering business processes within the tourism activities sector. Design/methodology/approach. The following methods were used in research: theoretical generalization (to determine the essence of business processes reengineering of tourism activity subjects), grouping (to identify and generalize the factors that influence business processes reengineering), analysis and synthesis (to determine the features of business processes reengineering in tourism business), system approach (to substant the elements and means of digital communications development of tourism activity subjects). The visibility of the presented results is ensured by the data graphical presentation, the methods of logical generalization and systematic approach were used to form the conclusions. Findings. Reengineering has become a high-quality tool for finding and implementing ways to improve the efficiency of the enterprises and organizations functioning, as it involves the identification of problem areas and the justification of prospective solutions with the highest level of detail. The application of marketing aspects and the development of internet communications system can be particularly promising vector for the business processes reengineering of tourist enterprises. It is important during reengineering, enterprises should make changes not only in problem areas, but also in other areas (marketing, information, etc.), because reengineering covers all spheres of the organization's activity. Nowadays traditional marketing tools are being replaced by digital that use the capabilities of Internet technologies. In recent decades, information technologies have been actively integrated into all spheres of enterprise activity, marketing was no exception. Business processes reengineering should be supported by marketing, information and strategic measures that will enhance the effect of its implementation. Practical implications. The practical significance of the obtained research results lies in the business processes digitalization of tourist enterprises, which will contribute to the growth of their economic and managerial efficiency. Originality/value. The scientific novelty of the research results lies in the study of factors that affect the result of business process reengineering and added to them two new factors (marketing and informational). An analysis of the social media usage by Ukrainian tourism enterprises in their activities was also carried out. Potential mechanisms for using price policy as a lever for targeted demand management in the Internet environment were proposed.

Health policy implications of corporate social responsibility provisions in international investment agreements.

To analyse and classify inclusions of corporate social responsibility in international investment agreements, especially inclusions with reference to public health. We extracted the text of international investment agreements containing corporate social responsibility inclusions from the Electronic Database of Investment Treaties. We conducted a documentary analysis of the corporate social responsibility inclusions, and we developed a typology categorizing inclusions based on level of detail and reference to international commitments. Of the 3816 agreements signed as of October 2023, 127 agreements contain corporate social responsibility inclusions. Since the first inclusion of corporate social responsibility in 2008, the percentage of agreements containing such inclusion signed each year has steadily increased from 4.6% (4/86) in 2008 to 42.8% (21/49) in 2018 and 33.3% (3/9) in 2023. Using the typology we developed, we categorized the level of detail as follows: nine were minimal, 27 were low, 35 were low-medium, 107 were medium, 11 were medium-high and seven were high. Health is mentioned in 36 of these inclusions. This analysis indicates that international investment agreements increasingly incorporate a high level of detail on expectations regarding investors' corporate social responsibility. Such provisions offer a potential tool to increase government guidance and accountability of global corporations, including with respect to governments' public health objectives.

Exploring Parametric Concepts and Principles for Furniture and Interior Design

This research explores the incorporation of parametric models into the algorithmic design process, specifically focusing on furniture and interior design. It presents a case of an experimental equation centred around a waffle honeycomb structure. The first part of the article reviews three decades of literature on parametric design, which comprises its background, history, theory, and essential concepts and applications. The second part investigates the parametric design process to uncover its potential for interior design applications. The combination of parametric equations with algorithms through the utilisation of multiple steps, such as conditional loops, efficiently designs intricate systems. An intricate system in parametric design comprises various input parameters, rules, mathematical algorithms, and conditional relationships that interact to generate design solutions. This approach is potentially applied in various design scenarios to respond to specific criteria and constraints, facilitating flexibility, adjustments to potential outcomes, and achieving a high level of detail in the final result. This research primarily concentrates on the identification of parametric design methodologies and the utilisation of parametric equations in crafting furniture and interior designs featuring waffle structures. Furthermore, it introduces a versatile parametric design approach that can be applied to various design tasks, highlights the evolutionary trajectory of parametric design, and offers insights into its potential impact on future design practices. The exploration of the parametric method enhances the understanding of complex design approaches in a more accessible and innovative manner with practical applicability.

High Resolution 3D Model of Heritage Landscapes Using UAS LiDAR: The Tajos de Alhama de Granada, Spain

The Tajos de Alhama de Granada, which since ancient times have inspired and surprised locals and strangers, especially foreign travelers, constituted a unique landscape, cultural and ethnological heritage of Spain, linked to water and its old flour mills. And, they are currently at serious risk of degradation. The aim of this research is to obtain a high-resolution 3D model capable of documenting this historical heritage environment with a high level of detail, using a methodology that includes small light weight LiDAR (Light Detection and Ranging) system for UAS (Unmanned Aircraft System). The model obtained should serve, on the one hand, as a valuable tool for knowledge and analysis of all the elements (river, lake, ditches, dams, mills, aqueducts, and paths) that made up this place, registered as a picturesque landscape for its extraordinary beauty and uniqueness, and on the other hand, as a basis for the development of rehabilitation and architectural restoration projects that would have to be undertaken to preserve this cultural and landscape legacy.

Use of GIS and BIM for the integration of tunnel design and construction process in conventional tunneling

This paper presents the development of a framework for the parametric design of tunnels using geographic information system (GIS) mapping and building information modelling (BIM). According to the framework, a parametric representation of each system component (e.g., layers of rock mass, size of excavation, topography, fault geometry, primary lining, secondary lining, rock bolts, etc.) can be incorporated in the GIS model with high levels of detail and used for the automatic generation of numerical models for the design of tunnel construction. This parametric evaluation allows the designer to consider several levels of detail for each component, for the efficient design and process optimization in conventional tunneling. Information between parametric analysis and numerical simulations can be freely exchanged with significantly reduced computational effort while results can be exported into BIM. It is anticipated that the proposed framework could lead to a comprehensive, yet efficient analysis of complex conventional tunneling project using parametric evaluations at the early design stages.

A Dual Evidential Top-View Representation to Model the Semantic Environment of Automated Vehicles

We present a generic evidential grid mapping pipeline designed for imaging sensors such as LiDAR and cameras. Our grid-based evidential model contains semantic estimates for cell occupancy and ground separately. We specify the estimation steps for input data represented by point sets, but mainly focus on input data represented by images such as disparity maps or LiDAR range images. Instead of relying on an external ground segmentation only, we deduce occupancy evidence by analyzing the surface orientation around measurements. We conduct experiments and evaluate the presented method using LiDAR and stereo camera data recorded in real traffic scenarios. Our method estimates cell occupancy robustly and with a high level of detail while maximizing efficiency and minimizing the dependency to external processing modules.