Cost Dependent QoS-based Discovery of Web Services

The role of the web services for development of distributed applications steadily increases over time. However, the rising number of available web services with the same functionality embarrasses clients during selection of such a one that fits best their requirements. To solve this problem, web service selection process needs to concern not only functional but also nonfunctional (QoS) properties of web services. The clients need to know the quality of the offered web services as well as what will be the price that they should pay for that quality. This paper contributes to this challenge by presenting an algorithm that allows clients to select the web service with an optimal correlation between quality and price.This paper has been supported by the Project Creative Development Support of Doctoral Students, Post-Doctoral and Young Researches in the Field of Computer Science (No. BG 051PO001-3.3.04/13) of the HR Development OP of the European Social Fund 2007-2013

Evaluation of social facilities coverage: A case study of Sofia city

In order to aid the decision making process related to the provision of public services as to maximize the benefits for society, it is crucial to evaluate the current social facilities demand in terms of spatial distribution and access. The paper aims to solve this problem by proposing a method for automated assessment of the coverage of public services within an urban region using a capacitated graph. The methodology abstracts residential buildings into demand nodes and public service buildings into supply nodes within a graph and then uses shortest distance calculations in order to balance the two, while prioritizing residential buildings based on distance. The paper is focused on creating a general pipeline that can be used on any type of public services, as long as a certain geospatial and demographic data are available. The method is described without referencing specific tools, but focusing on the general procedure. The procedure is then applied to the whole city of Sofa, focusing on assessing the coverage of kindergartens using the 15 minutes walking distance, followed by a brief discussion of results

Towards a Unifying View of QoS-Enhanced Web Service Description and Discovery Approaches

The number of web services increased vastly in the last years. Various providers offer web services with the same functionality, so for web service consumers it is getting more complicated to select the web service, which best fits their requirements. That is why a lot of the research efforts point to discover semantic means for describing web services taking into account not only functional characteristics of services, but also the quality of service (QoS) properties such as availability, reliability, response time, trust, etc. This motivated us to research current approaches presenting complete solutions for QoS enabled web service description, publication and discovery. In this paper we present comparative analysis of these approaches according to their common principals. Based on such analysis we extract the essential aspects from them and propose a pattern for the development of QoS-aware service-oriented architectures

Planning walkable cities:Generative design approach towards digital twin implementation

The idea of a walkable city refers to the extent to which the built environment encourages people to walk by establishing comfortable pedestrian routes, which allows people to connect to numerous services with reasonable effort and time. Walkability is currently regarded as a “good to know about” rather than a “must-have” factor for sustainable development. A combination of walkability with a standard design strategy, such as generative design, may result in a more efficient way of planning a walkable city. Interestingly, the sole indicator taken into account for walkability in the generative design domain is “distance to amenities”, while in reality, other parameters, such as the comfort factor, could also influence walkability. Therefore, in this research, we developed a workflow based on the generative design, which considers the comfort dimension in combination with distance to amenities and street-level greeneries. We also included the human perspective, given that walkability is always personal. This research successfully generated three different scenarios of walkability-optimal urban plans, where the highest walkability is 82.43 (very walkable). Furthermore, the baseline scenario of two different locations also aligns with people’s perspectives when compared. In addition, we found that the inclusion of a temporal dimension, enhanced 3D-related indicators, and constraints should benefit future research

Automatic Building Roof Plane Extraction in Urban Environments for 3D City Modelling Using Remote Sensing Data

Delineating and modelling building roof plane structures is an active research direction in urban-related studies, as understanding roof structure provides essential information for generating highly detailed 3D building models. Traditional deep-learning models have been the main focus of most recent research endeavors aiming to extract pixel-based building roof plane areas from remote-sensing imagery. However, significant challenges arise, such as delineating complex roof boundaries and invisible boundaries. Additionally, challenges during the post-processing phase, where pixel-based building roof plane maps are vectorized, often result in polygons with irregular shapes. In order to address this issue, this study explores a state-of-the-art method for planar graph reconstruction applied to building roof plane extraction. We propose a framework for reconstructing regularized building roof plane structures using aerial imagery and cadastral information. Our framework employs a holistic edge classification architecture based on an attention-based neural network to detect corners and edges between them from aerial imagery. Our experiments focused on three distinct study areas characterized by different roof structure topologies: the Stadsveld–‘t Zwering neighborhood and Oude Markt area, located in Enschede, The Netherlands, and the Lozenets district in Sofia, Bulgaria. The outcomes of our experiments revealed that a model trained with a combined dataset of two different study areas demonstrated a superior performance, capable of delineating edges obscured by shadows or canopy. Our experiment in the Oude Markt area resulted in building roof plane delineation with an F-score value of 0.43 when the model trained on the combined dataset was used. In comparison, the model trained only on the Stadsveld–‘t Zwering dataset achieved an F-score value of 0.37, and the model trained only on the Lozenets dataset achieved an F-score value of 0.32. The results from the developed approach are promising and can be used for 3D city modelling in different urban settings

Future City: A Pilot Project of GATE Center of Excellence

Citizens and cities’ government meet several challenges due to urbanization. The well-being of the citizens depends on the cities’ government, while the citizens apply information and communication technologies (ICTs) to improve society’s quality of life. The cities’ government and citizens need to work together to provide a “smart” living environment. The modern ICTs, including Big Data, IoT and Cloud, enable cities to become smart. They are a successful factor for development of smart solutions that provide information about what is happening in the city, timely response to citizen needs and better control of operations needed to increase the quality of life. In such a context, this paper presents a pilot project in the area of smart and sustainable cities. The pilot project is planned to be implemented as a part of research and development activities of the future BiG DAta for SmarT SociEty (GATE) Center of Excellence that will be established as a joint initiative between Sofia University, Bulgaria and Chalmers University of Technology, Sweden. The concept of the pilot project is described, including its main objectives and reference architecture. The possible application scenarios, covering different city dimensions, are discussed. ACM Computing Classification System (1998): D.2.2, H.4.2

Cognitive Impairment and Dementia Data Model: Quality Evaluation and Improvements

Recently, datasets with various factors and indicators of cognitive diseases have been available for clinical research. Although the transformation of information to a particular data model is straightforward, many challenges arise if data from different repositories have to be integrated. Since each data source keeps entities with different names and relationships at different levels of granularity and format, the information can be partially lost or not properly presented. It is therefore important to have a common data model that provides a unified description of different factors and indicators related to cognitive diseases. Thus, in our previous work, we proposed a hierarchical cognitive impairment and dementia data model that keeps the semantics of the data in a human-readable format and accelerates the interoperability of clinical datasets. It defines data entities, their attributes and relationships related to diagnosis and treatment. This paper extends our previous work by evaluating and improving the data model by adapting the methodology proposed by D. Moody and G. Shanks. The completeness, simplicity, correctness and integrity of the data model are assessed and based on the results a new, improved version of the model is generated. The understandability of the improved model is evaluated using an online questionnaire. Simplicity and integrity are also considered as well as the factors that may influence the flexibility of the data model

Cognitive Impairment and Dementia Data Model: Quality Evaluation and Improvements

Recently, datasets with various factors and indicators of cognitive diseases have been available for clinical research. Although the transformation of information to a particular data model is straightforward, many challenges arise if data from different repositories have to be integrated. Since each data source keeps entities with different names and relationships at different levels of granularity and format, the information can be partially lost or not properly presented. It is therefore important to have a common data model that provides a unified description of different factors and indicators related to cognitive diseases. Thus, in our previous work, we proposed a hierarchical cognitive impairment and dementia data model that keeps the semantics of the data in a human-readable format and accelerates the interoperability of clinical datasets. It defines data entities, their attributes and relationships related to diagnosis and treatment. This paper extends our previous work by evaluating and improving the data model by adapting the methodology proposed by D. Moody and G. Shanks. The completeness, simplicity, correctness and integrity of the data model are assessed and based on the results a new, improved version of the model is generated. The understandability of the improved model is evaluated using an online questionnaire. Simplicity and integrity are also considered as well as the factors that may influence the flexibility of the data model

Modeling Buildings in CityGML LOD1: Building Parts, Terrain Intersection Curve, and Address Features

3D city models integrate heterogeneous urban data from multiple sources in a unified geospatial representation, combining both semantics and geometry. Although in past decades they have predominantly been used for visualization, today they are used in a large range of tasks related to exploration, analysis, and management across multiple domains. The complexity of urban processes and the diversity of urban environments bring challenges to the implementation of 3D city models. To address such challenges, this paper presents the development process of a 3D city model of a single neighborhood in the city of Sofia based on the CityGML 2.0 standard. The model represents the buildings in LOD1, focusing on CityGML features, including building parts, the terrain intersection curve, and the address. Similar building models of 18 cities provided as open datasets are explored and compared to extract good modeling practices. As a result, workflows for the generation of 3D building models in LOD1 are elaborated on and improvements in the feature modeling are proposed. Two building model options are examined: (1) the modeling of a building as a single solid with differentiated rooftops and (2) the modeling of a building with separate building parts. The developed 3D building model contains 471 buildings and 198 addresses in both cases of building parts modeling. In addition, the terrain intersection curve (TIC) is modeled and a method for removing the duplicating TIC features is applied. Consequently, the overall count of vertices of the TIC is lowered from 12,112 to 8042. Finally, the possibilities for visualization of the model in popular platforms such as ArcGIS Pro and Cesium Ion are explored