Large Information Systems Research Articles

Models of data processing and logical access segregation considering the heterogeneity of entities in information systems

The subject of the research is the process of logical access segregation to data in information systems. The aim of the article is to improve the accuracy and reliability of modeling processes for data processing and logical access segregation considering the heterogeneity of entities in information systems. The tasks to be solved include: conducting a comparative analysis of modern data access distribution models, integrating simpler role-based models, synthesizing hierarchical role-based models, developing enforced typing models based on trust relationships, and presenting the main provisions of the security policy integration process. The methods used are: systems analysis, component design, logical and simulation modeling in the form of role-based access segregation models. The results obtained include: development of data processing models and logical access segregation in information systems that take into account the heterogeneity of entities and the multi-level structure of information systems. The models differ from known ones by considering the heterogeneity of entities and the multi-level structure of information systems. This has increased scalability by up to 35% due to a modular approach to defining security policies. Additionally, the developed model demonstrates 25% higher implementation practicality as it easily integrates with existing access control systems and adapts to various platforms and environments. The proposed models are effective for large information systems and distributed environments due to their modularity and ability to adapt to different operational conditions. This ensures reliable access control in systems with numerous subjects and objects. The implementation of multi-level RBAC models has improved the accuracy and reliability of results.

Matrix methods for some new covering-based multigranulation fuzzy rough set models under fuzzy complementary β-neighborhoods

Fuzzy complementary β-neighborhoods (FCNs) are used to find information relevant to the target in data mining. Based on FCNs, there are six types of covering-based multigranulation fuzzy rough set (CMFRS) models have been constructed, which can be used to deal with the problem of multi-criteria information systems. These CMFRS models are calculated by set representations. However, it is time-consuming and error-prone when set representations are used to compute these CMFRS models in a large multi-criteria information system. Hence, it is important to present a novel method to compute them quickly, which is our motivation for this paper. In this paper, we present the matrix representations of six types of CMFRS models on FCNs. Firstly, some new matrices and matrix operations are given in a multi-criteria information system. Then, matrix representations of three types of optimistic CMFRSs on FCNs are proposed. Moreover, matrix approaches are also used for computing three types of pessimistic CMFRSs on FCNs. Finally, some experiments are presented to show the effectiveness of our approaches.

Smartphones and Environmental Sustainability: A Country-Level Analysis

Research suggests that information and communication technologies (ICTs) have a nonlinear relationship with CO2 emissions, specifically an inverted U-shaped curve similar to the environmental Kuznets curve (EKC). While extant research has investigated the relationship using an ICT index, there has been no research looking at smartphones, the use of which has been closely associated with the explosive growth in the use of mobile apps and a build-out of large information systems to support their use. To address this gap, this research examines the relationship of ICTs and smartphones with CO2 emissions by employing a country-level data set for the period from 2009 to 2017. Our results show that the relationship of ICTs with CO2 emissions takes an inverted U-shaped curve form, consistent with the EKC hypothesis. Our results also show that CO2 emissions increase with initial increases in smartphone capital stock but decrease as smartphone stock increases further. These findings imply that carbon emissions go up with the penetration of ICTs in poorer countries but in wealthier countries, ICT penetration and smartphone stock are related to lower CO2 emissions. The results should not be taken as evidence that ICTs cannot lead to greater sustainability in poorer countries but should be seen as a call for the IS community to help all countries apply existing knowledge and develop new knowledge to use ICTs to reduce emissions in response to the immediate challenge of climate change.

Adaptive State Estimation of UAV Information Physical System Under Network Attack

with the idea of information physics system put forward, governments, enterprises and scientific research in-stitutions have joined the research and construction of information physics system. The construction and development of information physics system is bound to be restricted by the security and privacy of information physical system, which provides theoretical reference for clearing the current security threats of information physical system and providing theoretical reference for the security and privacy protection of information physical system. UAV is an intelligent infor-mation physics system which relies on ground communication and flight control system to realize autonomous flight. The concept of IT system was first proposed by NASA in 1992. As a new intelligent system, UAV has emerged and is widely used. It is a complex system of computing, network and physical entity integration and deep cooperation. Thus, the real-time perception, dynamic control and information service of large physical system and information system can be achieved.

PIONEER OF INFORMATION SCIENCE AND CYBERNETICS <i>ON THE 100TH ANNIVERSARY OF THE BIRTH OF ACADEMICIAN V.M. GLUSHKOV</i>

The article is devoted to the life and work of the outstanding Soviet scientist, pioneer of informatics and cybernetics, initiator of the development of a nationwide automated management information system, Academician of the Academy of Sciences of the USSR Viktor Mikhailovich Glushkov (1923–1982). The author tells about the main stages of his biography, focusing on the scientific achievements: the solution of the fifth generalized Hilbert problem, the creation of the USSR’s largest Institute of Cybernetics of the Academy of Sciences of the Ukrainian SSR, the development of the theory of digital automata, the first personal computers for engineering calculations, the most powerful supercomputers in the USSR with a new macro-pipeline architecture, contribution to cybernetics and computer science, programming theory and systems of algorithmic algebras, to the creation of artificial intelligence systems. Attention is paid to the role of V.M. Glushkov as an ideologist and one of the creators of the industry of management information systems in the USSR, scientific director of large industrial management information systems. Particular attention is paid to the National Automated System for the Collection and Processing of Information proposed by him for accounting, planning and management of the national economy.

The flow of scientific books as a source for scientific library collection development: The problems of completeness and accessibility

Purpose. The authors analyze the trends in the national flow of book publications in science for the period 2012–2021 and its impact upon scientific library collections.Sources and methods. The study is based on the statistical data of large information systems, i.e. the Russian Book Chamber and scientific electronic library eLibrary.ru), and State Public Scientific and Technological Library of the Russian Academy Siberian Branch (RAS SB SPSTL). The data of the Higher School of Economics characterize scientific focuses of Russian researchers.Findings and conclusions. The data on the flow of scientific book publications were analyzed to confirm that after 2014, the volume of science publications has been continuously decreasing. It is especially true for academic book publishing. The trend for a disproportion in the discipline structure of scientific book flow, and for scattering information on scientific book publications, is revealed. It is due to the lack of coordination between scientific content creators and institutions intended to acquire complete data on scientific document flow. Science information support and knowledge generation require special infrastructure necessarily embracing scientific and academic libraries.

The role of antivirus protection in the formation of the ecosystem and immune system of corporate information systems

The article examines the need for the formation of an ecosystem, a corporate information system with a strong immune system, which, together with antivirus protection, provides a sufficient level of cyber protection of the entire system for the possibility of stable and stable functioning of large corporate information systems. The need to take into account the fact that modern corporate information systems are formed on the basis of neural systems, artificial intelligence and the Internet of Things was also noted. This determines the need for a complex approach to the selection of an antivirus software product, which must be harmoniously integrated into the general architecture of the information system to ensure a high level of antivirus protection. An analysis of available anti-virus software products has shown that the vast majority of them are effective for home use. For corporate information systems, it is necessary to choose an antivirus product based on the recommendation and technical support of the vendor company, which is responsible for the entire software product used in the system being built.

Method for estimating the performance of large information systems with transaction clustering

Method for estimating the performance of large information systems with transaction clustering

Assessment of the Financial Benefits from Wind Farms in US Rural Locations

Rural locations provide limited economic opportunities, mainly relying on agricultural activities, with scarce industrial or commercial investment and employment. This has led to higher risks related to poverty, with a lack of opportunities for education, healthcare, and general services leading to rural migration. On the other hand, wind energy is growing exponentially in the United States (US). Rural locations offer very good siting options for wind farms considering the ever-growing size of their equipment and significant required area. Therefore, wind farms may provide financial opportunities to local rural communities, reducing poverty risks and improving living standards. These financial benefits include rental income for landowners, additional tax collection for public service funding, increased income for school districts, and overall larger local investments. However, the available data are too coarse, broad, and unconnected, not allowing local communities, wind developers, and stakeholders a clear panoramic of the benefits that each individual location, school district, or landowner may receive. This research compiled dispersed big data for its integration into a large Geographic Information System (GIS). This system is capable of performing analysis to provide a much better understanding of the actual benefits that the wind industry provides to each individual rural stakeholder. Data were converted to geospatial layers, when required, to allow for a fuller comprehension of all factors impacting financial benefits and risks from the wind industry. Analyses were expanded to evaluate the lease financial benefits for landowners in Texas, applying the data provided by local and state agencies. The approach developed in this research will allow for its application in diverse geographical locations to explore additional financial benefits that each individual rural stakeholder may receive from the wind industry. This will allow local authorities, landowners, wind developers, and communities to better negotiate for the future expansion of wind energy, providing all parties involved with significant benefits and allowing the continuous growth of renewable energy to overcome the damaging effects from climate change.

A phylogenetic study to assess the link between biome specialization and diversification in swallowtail butterflies.

The resource‐use hypothesis, proposed by E.S. Vrba, states that habitat fragmentation caused by climatic oscillations would affect particularly biome specialists (species inhabiting only one biome), which might show higher speciation and extinction rates than biome generalists. If true, lineages would accumulate biome‐specialist species. This effect would be particularly exacerbated for biomes located at the periphery of the global climatic conditions, namely, biomes that have high/low precipitation and high/low temperature such as rainforest (warm‐humid), desert (warm‐dry), steppe (cold‐dry) and tundra (cold‐humid). Here, we test these hypotheses in swallowtail butterflies, a clade with more than 570 species, covering all the continents but Antarctica, and all climatic conditions. Swallowtail butterflies are among the most studied insects, and they are a model group for evolutionary biology and ecology studies. Continental macroecological rules are normally tested using vertebrates, this means that there are fewer examples exploring terrestrial invertebrate patterns at global scale. Here, we compiled a large Geographic Information System database on swallowtail butterflies' distribution maps and used the most complete time‐calibrated phylogeny to quantify diversification rates (DRs). In this paper, we aim to answer the following questions: (1) Are there more biome‐specialist swallowtail butterflies than biome generalists? (2) Is DR related to biome specialization? (3) If so, do swallowtail butterflies inhabiting extreme biomes show higher DRs? (4) What is the effect of species distribution area? Our results showed that swallowtail family presents a great number of biome specialists which showed substantially higher DRs compared to generalists. We also found that biome specialists are unevenly distributed across biomes. Overall, our results are consistent with the resource‐use hypothesis, species climatic niche and biome fragmentation as key factors promoting isolation.

Rethinking Project Escalation: An Institutional Perspective on the Persistence of Failing Large-Scale Information System Projects

ABSTRACT Project escalation involves the continued, persistent commitment to a failing project. Through a qualitative meta-analysis of 15 published cases of large information systems (IS) projects in escalation situations, we develop an institutional perspective on IS projects in escalation situations. This perspective describes how project persistence emerges from a plurality of legitimizing institutional logics that decision-makers draw upon at different project stages to maintain and reduce their commitment to the project. Logics related to the project’s approval are not the same logics that guide decisions throughout the project. For example, while we find that innovation and economic logics of return on investment are salient before approval, economic costs tend to be more salient after approval, along with technical impositions and managerial concerns. We further find that managerial logics are particularly salient in reducing commitment to projects, and we detail the differences and point out contextual triggers of external scrutiny and leadership changes that can contribute to reduced commitment to a project and eventual de-escalation.

Packaging Big Data Visualization Based on Computational Intelligence Information Design.

A method based on a computational intelligence information model is proposed to study the visualization of large data packages. Since the CAIM algorithm only considers the distribution of the largest number of classes in an interval, it offers an optimization method and simultaneously determines the appropriate stopping conditions to avoid overcrowding. The effectiveness of the improved algorithm has been experimentally proven. Methods of character reduction and weight determination are used to reduce the index and weight, establishing a large packaging information system. Experimental results show that the improved algorithm in this article produces more classification rules than the CAIM algorithm, because the discrete intervals created by the CAIM algorithm are relatively simple, but the classification rules are few, but less than the number of CAIM algorithms. Classification rules are generated by entropy-based sampling algorithms. This can make the classification rules simple and universal, and it is clear that the optimal sampling algorithm is more accurate than the CAIM algorithm.

Undesirable framing effects in information systems projects: Analysis of adjective usage in IS project business cases

Many information systems (IS) projects encounter significant problems. The literature suggests that decision-makers can be misled by overoptimistic estimates. We argue that such overoptimism may also be present in the choice of language in business cases. In this study, we analyzed the usage of such framing in 20 business cases for large IS projects of the Dutch government. Our findings show that newly proposed systems are systematically framed using positive adjectives, whereas the existing systems are framed using negative adjectives. This pattern of framing may subconsciously bias the decision-makers toward investing in new IS projects.

Long-term preservation of legally significant electronic document

The article discusses the problem of ensuring the long-term preservation of legally significant electronic documents (LSED). An overview of the problem and existing options for solving it are provided in the article. The paper frames a formal problem of ensuring the long-term preservation of legally significant electronic documents as an optimal control problem under conditions of parametric disturbances. This study briefly outlines the problems that arise when organizing the long-term preservation of electronic documents. The author also proposes documents safety indicators through documents and mathematical models for assessmentof the overall document safety. The study has resulted in development of algorithms that allow, being implemented in the form of software and hardware, to control and organize security. Examples of the practical implementation of the proposed approaches within the framework of large information systems are provided alongside with their advantages. Implementation of suggested approaches can potentially make it possible to comprehensively solve the important scientific and technical problem of organizing the long-term preservation of legally significant electronic documents. At the end of the article, further prospects for research aimed at solving the problem of long-term preservation of big data and systems built using distributed ledger technologies are identified.

ЦЕЛОСТНОСТЬ ЛИЧНОСТИ В КОНТЕКСТЕ ЭСТЕТИЧЕСКОЙ ПАРАДИГМЫ

The problem of preserving the personal integrity in a situation of cardinal changes is considered. The complexity of considering the question of the relationship between stability and the transformation of value orientations in the context of personality psychology is shown. The productivity of the analysis of the problem of holism and the dynamic connection of value orientations from the standpoint of the aesthetic paradigm is analyzed. The role of society and cultural values as a large system that changes the perception and internalization of culture by a person is shown. In this context, a large system can be considered as a ratio of culture and subculture, information about which changes not only the content of the subculture, but also the culture as a whole. The options for maintaining harmony between development and sustainability, dynamics-stability of values are considered, in which the space of subculture is created as a subsystem in the general space of the cultural field. At the same time, such a subculture can exist autonomously, without coming into conflict with a large system of values of society, such as, for example, the variant of the subculture created by Dali and Gala. Other versions of information subsystems of culture, both in science and in art, can gradually change the information field of culture as a whole in such a way that it practically merges with the content of a particular subcultural subsystem (quantum physics, atonal music, impressionism). The role of cultural capital in maintaining the integrity of the individual and its variability in a situation of multiple and cardinal transformations of society is revealed. The connection of the constant value of the first level of cultural capital as an investment in the development of subsequent generations with a large information system of culture is shown. An analysis of different levels of cultural capital and their content in different situations and with varying degrees of changes is given. The connection of these levels and the degree of their variability with the motivation of a person and the standards of behavior at different times and in different cultural contexts is shown. It is proved that different variants of behavior in the cultural field can be considered as different types of dynamic stability of the personality.

COVID-19 Mortality Prediction From Deep Learning in a Large Multistate Electronic Health Record and Laboratory Information System Data Set: Algorithm Development and Validation.

BackgroundCOVID-19 is caused by the SARS-CoV-2 virus and has strikingly heterogeneous clinical manifestations, with most individuals contracting mild disease but a substantial minority experiencing fulminant cardiopulmonary symptoms or death. The clinical covariates and the laboratory tests performed on a patient provide robust statistics to guide clinical treatment. Deep learning approaches on a data set of this nature enable patient stratification and provide methods to guide clinical treatment.ObjectiveHere, we report on the development and prospective validation of a state-of-the-art machine learning model to provide mortality prediction shortly after confirmation of SARS-CoV-2 infection in the Mayo Clinic patient population.MethodsWe retrospectively constructed one of the largest reported and most geographically diverse laboratory information system and electronic health record of COVID-19 data sets in the published literature, which included 11,807 patients residing in 41 states of the United States of America and treated at medical sites across 5 states in 3 time zones. Traditional machine learning models were evaluated independently as well as in a stacked learner approach by using AutoGluon, and various recurrent neural network architectures were considered. The traditional machine learning models were implemented using the AutoGluon-Tabular framework, whereas the recurrent neural networks utilized the TensorFlow Keras framework. We trained these models to operate solely using routine laboratory measurements and clinical covariates available within 72 hours of a patient’s first positive COVID-19 nucleic acid test result.ResultsThe GRU-D recurrent neural network achieved peak cross-validation performance with 0.938 (SE 0.004) as the area under the receiver operating characteristic (AUROC) curve. This model retained strong performance by reducing the follow-up time to 12 hours (0.916 [SE 0.005] AUROC), and the leave-one-out feature importance analysis indicated that the most independently valuable features were age, Charlson comorbidity index, minimum oxygen saturation, fibrinogen level, and serum iron level. In the prospective testing cohort, this model provided an AUROC of 0.901 and a statistically significant difference in survival (P<.001, hazard ratio for those predicted to survive, 95% CI 0.043-0.106).ConclusionsOur deep learning approach using GRU-D provides an alert system to flag mortality for COVID-19–positive patients by using clinical covariates and laboratory values within a 72-hour window after the first positive nucleic acid test result.

EBPA: A Novel Framework for the Analysis of Process Performance on the Basis of Real-Time NASA Application

Background: Workflow extraction is the connecting link between process modelling and data mining. Extraction of information and make insight from it using event log is the primary objective of workflow mining. The learning got along these logs can build comprehension about the workflow of procedures and association of different processes. That can help with upgrading them if necessary. Objective: The aim of this paper is to display a process performance based framework where we compare reference model with extracted model (from a large information system) on the basis of key performance indices. Methods: Proposed approach perform extraction of workflow model using workflow mining. This process is effective and efficient as compare with building work flow model from scratch. This shows a logic about how to program event log data gathered from different sensors (Internet of Events). How we process and investigates to handle and propel the item work process by using the course of action. Results: Proposed approach displays a process based framework for the legacy system that ensures the effective and efficient working. So that accordingly extracted model behave like referenced model and results are validated by Key Performance Indices (KPI) for evaluating process performance. Conclusion: In this experimental data centric approach, our progressing work is to research a metric to quantify the nature of reference models and extracted model. On the basis of metric values, we take the decision on legacy information system process management.

On the concept of RNPLS&amp;T’s Open Archive

The authors examine the principles and technologies of RNPLS&amp;T’s Open Archive development. Special attention is given to the urgency of the task under the circumstances of digitalization. The main goal is seen as building the Single Open Archive of Information (SOAI) of the Russian National Public Library for Science and Technology that is to accumulate every digital full-text resources designed or acquired legally by the Library. The key principles of SOAI as an integrated information system are specified. The functionalities and protocol table structure for RNPLS&amp;T’s SOAI soft- and hardware are discussed. The projected functional structure of the archive is described and explained. Possible software and hardware solutions for SOAI application and metadata server are discussed along with the interaction with large related information systems like the National Electronic Library (NEL). The system implementation will become the next important stage in building the typical model of e-library as a player in the open archive system. This is to facilitate the technology of data exchange in library information systems, units of science information within research organizations, universities, general educational institutions, and to support information retrieval via the single access point at web-portals. The article is prepared within the framework of the State Order № 075-01300-20-00 “Design and development of RNPLS&amp;T’s Open Archive of Integrated Information Library Resources as a modern system of knowledge management within the digital environment: On the way to Open Science” for the years 2020–2022.

Simulation of resource distribution in large information systems based on multiagent approach

Traditional planning theory considers the general problem of division of labor on computing devices. A fairly large class of planning tasks is included in the described task of resource allocation. The only type of resources in such tasks are computing resources. The article considers the tasks of resource allocation in multi-agent systems, options for their applicability and existing methods of solving these problems. The task of allocating resources is one of the fundamental tasks: from the efficient allocation of one's own time to the distribution between different activities and the tasks of allocating resources in large information systems. The article considers different approaches to resource allocation in large information systems: resource allocation within non-stationary tasks, stationary tasks and in multi-agent systems. These approaches help to solve various applications in real time. In the case of resource allocation in multi-agent systems, their decentralization must be taken into account: agents are directly responsible for themselves and do not have complete information about the system, which changes the very essence of the task. Thus, the development of multi-agent models is possible. The multi-agent scheduling methods used in the system can be used in real-time decentralized systems compared to the previously mentioned traditional methods. Their application provides management of planning and execution of tasks, they can be used to manage groups of objects consisting of a large number of devices and able to quickly process large-scale tasks. Thus, in a short time it is possible to design and commission based on the use of multi-agent technologies for planning new-generation software and hardware systems that can interact and work in a group and applicable to a wide range of tasks in various fields.

Applying an MDA-based approach for enhancing the validation of business process models

Abstract Business process modeling is a key activity during the development of complex and large information systems, such as enterprise management systems. These systems deal with a wide number of business processes; thus, the modeling and validation of processes becomes a challenging task. This entails dealing with issues such as the precedence between tasks and activities within a process, as well as resources, roles and enterprise assets involved. Moreover, undetected mistakes in this phase will be propagated to the system design phase and consequently will have a negative effect in the final system quality. On the other hand, the scientific literature advocates the suitability of formal models to address some issues during the process modeling. However, the adoption of formal models leads to new problems because formal languages are difficult to understand and process stakeholders usually lack of knowledge about them. In that direction, the Model-Driven Architecture (MDA) paradigm includes specifications that may alleviate some difficulties in the adoption of formal languages. Hence, in this paper we introduce an approach which combines MDA-specifications and ontologies to support process modeling. These technologies have great acceptance between both software researchers and developers. The use of ontologies permits to semantically validate the models. Furthermore, the application of MDA-guidelines could facilitate the integration of BPMN, a graphical notation for describing business process models widely accepted among business analysts, with a formal language to automate the analysis of business process models.