Urban Data Dynamics: A Systematic Benchmarking Framework to Integrate Crowdsourcing and Smart Cities’ Standardization

Urbanization and knowledge economy have highly marked the new millennium. Urbanization brings new challenges which can be addressed by the knowledge economy, which opens up scientific and technical innovation opportunities. The enhancement of cities’ intelligence has heavily impacted city transformation and sustainable decision-making based on urban data knowledge extraction. This work is motivated by the strong demand for robust standardization efforts to steer and measure city performance and dynamics, given the growing tendency of conventional cities’ transformation into smart and resilient ones. This paper revises the earlier so-called “cityDNA” framework, which was designed to detect the interrelations between the six smart city dimensions, such that a city’s profile and capacities are recognized in a systematic manner. The updated framework implements the widely accepted smart city (ISO 37120:2018) standard, along with an adaptive Web service, which processes urban data and visualizes the city’s profile to facilitate decision-making. The proposed framework offers a solid benchmarking service, at which the value of crowdsourced data is exploited for the production of urban knowledge and city transformation empowerment. The proposed benchmarking approach is tested and validated through relevant case studies and a proof-of-concept scenario, in which open data and crowdsourced data are exploited. The outcomes revealed that cities should intensify their KPI-driven data production and exploitation along with a set of solid standards for cities to enable cities with customizable scenarios enriched with indicators that reflect each city’s vibrancy.

Project Management Volume, Velocity, Variety: A Big Data Dynamics Approach

The era of Big Data has provided business organisations opportunities to improve their management processes. This developmental paper is adopting a mixed-method research approach where qualitative data will underpin a quantitative questionnaire. The early insights are based on an initial eleven qualitative interviews and conceptualised in the following three statements: (i) Project practitioners need to increase their data literacy; (ii) Project practitioners are not utilising the available Big Data based on the 3 Vs; Volume, Velocity and Variety; (iii) Project practitioners need to utilise the structured available data to augment the decision-making process to represent the complex environment of Big Data, the study adopts Complexity Theory as a theoretical framework. When completed, the research will demonstrate the results through System Dynamics modelling.

Kidney ultrasound biometric data dynamics in women with gestational hypertension

Introduction: The stable level of morbidity in the Russian Federation of pregnant women with gestational arterial hypertension (GAH) and as a consequence of the disability of women of working age and their offspring actualizes the search for early ultrasound markers of kidney damage as a target organ urgent. Objectives: Despite the variety of publications on ultrasound semiotics of the kidneys, there are no specific biometric parameters of the kidneys in pregnant women without somatic pathology, which actualizes this study. Patients and Methods: A comprehensive clinical examination of 183 outpatients and inpatients (mean age 27.9 ± 4.7 years) with gestational hypertension performed. Results: There is a significant increase in the volume of the right kidney, the left kidney shape index, the diameter of the renal calyces and pelvis, the coefficient of asymmetry, the ratio of the diameter of the renal calyces to the volume of the right kidney with an increase in the degree of gestational hypertension. Conclusion: Structural changes of kidneys are interconnected with hemodynamic parameters observed and can be expressed by mathematical model.

Dynamics-based data science in biology

With the increasingly accumulated bio-data, dynamics-based data-science has been progressing as an efficient way to reveal mechanisms of dynamical biological processes. We review three applications on detecting the tipping-points of diseases, quantifying cell's potency, and predicting time-series, to show the importance of dynamics-based data-science.

Privacy-Preserving Public Auditing and Data Dynamics for Secure Cloud Storage Based on Exact Regenerated Code

Cloud storage allows users to store their data in the cloud to avoid local storage and management costs. Since the cloud is untrusted, the integrity of stored data in the cloud has become an issue. To address this problem, several public auditing schemes have been designed to verify integrity of the data in the cloud. However, these schemes have two drawbacks: public auditing may reveal sensitive data to verifier and does not address the data recovery problem efficiently. This article proposes a new privacy-preserving public auditing scheme with data dynamics to secure the data in the cloud based on an exact regenerated code. This scheme encodes the data for availability, then masks the encoded blocks with randomness for privacy of data and enables a public auditor to verify the integrity of the data. Further, this scheme also supports dynamic data updates. In addition, security and performance analysis proves that proposed scheme is provably secure and efficient.

Phase Analysis of the Data Dynamics from the Tourism Sector

The tourism industry covers various areas of economic activity. Tourism has various areas and directions of its implementation. One of the significant areas of tourism is international tourism. International tourism influences and reflects different spheres of human economic activity. This type of economic activity can have a non-linear nature of the processes that describe it. To analyze and identify such processes, the concept of a phase portrait is used. The paper reveals the features of nonlinear dynamics of processes in the field of tourism. We used real data to construct individual phase portraits in the tourism sector. A number of specific examples of the analysis of indicators from the tourism sector are given.