Specific File Research Articles

Mapping Hierarchical File Structures to Semantic Data Models for Efficient Data Integration into Research Data Management Systems

Although other methods exist to store and manage data in modern information technology, the standard solution is file systems. Therefore, keeping well-organized file structures and file system layouts can be key to a sustainable research data management infrastructure. However, file structures alone lack several important capabilities for FAIR data management: the two most significant being insufficient visualization of data and inadequate possibilities for searching and obtaining an overview. Research data management systems (RDMSs) can fill this gap, but many do not support the simultaneous use of the file system and RDMS. This simultaneous use can have many benefits, but keeping data in RDMS in synchrony with the file structure is challenging. Here, we present concepts that allow for keeping file structures and semantic data models (in RDMS) synchronous. Furthermore, we propose a specification in yaml format that allows for a structured and extensible declaration and implementation of a mapping between the file system and data models used in semantic research data management. Implementing these concepts will facilitate the re-use of specifications for multiple use cases. Furthermore, the specification can serve as a machine-readable and, at the same time, human-readable documentation of specific file system structures. We demonstrate our work using the Open Source RDMS LinkAhead (previously named “CaosDB”).

Prisoners of the archives: privacy, identity and the history of incarceration

ABSTRACT The archival record of incarceration in the United States presents a substantial challenge for historical research. This becomes particularly acute in those instances where historians seek to use individual patient or prisoner records. Some of these records have been deposited in state archives, but many have not, and the use of specific inmate case files can involve restrictive rules of access. In every instance, complex interplays of power, access and privacy pose challenges for historians who wish to foreground the voices and experiences of the incarcerated, and to better understand the practices and impacts of state power. This paper uses a series of episodes from the author’s own work to highlight these issues.

Bus stop spacing statistics: Theory and evidence

Discussions of bus stop consolidation sometimes refer to average stop spacings, but there are no reliable statistics about spacings, nor methodologies for calculating them. This paper aims to clarify discussions of bus stop spacings by introducing clear definitions, a methodology for creating statistics from General Transit Feed Specification (GTFS) files, and a python package, gtfs-segments, which splits bus networks into isolated ‘segments.’ With the package, we calculate national-level statistics from 539 US transit providers and 83 Canadian providers, as well as agency-level statistics for 30 providers in the US, 10 in Canada, and a sample of 38 providers from other countries. Our estimates of US and Canadian mean spacings are both around 350 m (slightly wider than five stops per mile). US spacings are wider than sometimes claimed but narrower than those in other countries. Finally, the paper gives examples of metrics created by combining GTFS with data from other sources and proposes research ideas and applications to transit planning involving fine-grained stop spacing data.

Experimental evaluation of the possibility of determining bacterial endotoxins in typhoid Vi polysaccharide vaccines using the gel-clot test

Scientific relevance. Currently, only the rabbit pyrogen test is used to test the Vianvac® typhoid Vi polysaccharide vaccine for pyrogenicity. As part of the product specification file, the gel-clot test for bacterial endotoxins (BE) will improve the reliability of quality control, as well as harmonise the requirements for the vaccine with the requirements outlined for this group of medicinal products by leading world pharmacopoeias.Aim. This study aimed at an experimental assessment of the applicability of the gel-clot test to the quantification of BE in the typhoid Vi polysaccharide vaccine.Materials and methods. This study used samples from 5 batches of the typhoid Vi polysaccharide vaccine (0.5 mL/dose, solution for subcutaneous injection), LAL and TAL reagents. The analysis included the gel-clot test and the pyrogenicity test according to the State Pharmacopoeia of the Russian Federation (OFS.1.2.4.0006.15 and OFS.1.2.4.0005.15, respectively).Results. According to calculations, the BE limit for the tested vaccine was 96 EU/mL, and the maximum valid dilution (MVD) was 3200. The authors determined the regulatory requirements for typhoid Vi polysaccharide vaccine quality in terms of BE (not more than 48 EU/dose). The in vitro BE tests were positive at vaccine dilutions of 1/16 to 1/32 and negative at 1/64 to 1/256. The authors selected and validated a working vaccine dilution of 1/128. The BE content measured in the tested samples ranged from 0.24 to 0.48 EU/dose. The in vivo pyrogen tests were positive at dilutions of 1/16 to 1/128 and negative at 1/256 in all experiments with samples from 5 vaccine batches at dilutions ranging from 1/16 to 1/256.Conclusions. This study has experimentally proven that the gel-clot test can quantify BE in the typhoid Vi polysaccharide vaccine. The authors have recommended introducing the gel-clot BE test in the monograph of the State Pharmacopoeia of the Russian Federation on the typhoid Vi polysaccharide vaccine (FS.3.3.1.0012.15).

Design of a system for bioinformatics processing of metagenomic data

Advancements in acquiring, storing and processing information have led to a significant accumulation of large databases in the field of metagenomics—a branch of biology that deals with the study of genetic material directly recovered from environmental or clinical samples. The data collected from metagenomic experiments are massive and noisy, often containing fragmented information representing over 10,000 species. Processing and analyzing this data require software installed on supercomputers. In this paper, the authors present the design, development, and creation of a computational server system aimed at processing and analyzing bioinformatics data in metagenomics and 16S rRNA gene studies. They utilized the specialized software product Galaxy Europe for this purpose. The analysis was performed using the metagenomics-based method Targeted Amplicon Sequencing. The data was divided into three test collections in a special fasta file format. These collections were processed using the web-based Galaxy platform and two configuration variants on a high-performance cluster equipped with NVIDIA Tesla V100 32 GB GPU cards. The analysis process was optimized to reduce information processing time, and the parallel performance of the three different system configurations was investigated for the data used.

The Atmospheric Influence on Cosmic-Ray-Induced Ionization and Absorbed Dose Rates

When high-energy particles originating from space penetrate the atmosphere, they may interact with atoms and molecules, initiating air showers composed of secondary and tertiary particles propagating towards the ground. They can cause ionization of the atmosphere and contribute to the radiation dose at low altitudes. This work uses the GEANT-4-based Atmospheric Radiation Interaction Simulator (AtRIS) toolkit to compute these quantities in the Earth’s atmosphere. We take advantage of the unique Planet Specification File (PSF) of the Atmospheric Radiation Interaction Simulator (AtRIS) to investigate the effect of the state of the atmosphere on the resulting induced ionization and absorbed dose rates from the top of the atmosphere (at 100 km) down to the surface. The atmospheric profiles (density, pressure, temperature, and composition) are computed with the NRLMSISE-00 model at various latitudes and for every month of 2014, corresponding to the last maximum of solar activity. The resulting ionization and dose rates present different profiles that vary with latitude in the atmosphere, with the relative difference between equatorial and high latitude ionization rates reaching 68% in the Pfotzer maximum. We obtain differences of up to 59% between the equator and high latitudes observed at commercial flight altitudes for the radiation dose. Both ionization and absorbed dose rates also feature anti-phased seasonal variations in the two hemispheres throughout 2014. Based on these results, we computed global maps of the ionization and dose rates at fixed altitudes in the atmosphere by using precomputed maps of the effective vertical cutoff rigidities and the results of three AtRIS simulations to consider the effect of latitude. While sharing the same general structure as maps created with a single profile, these new maps also show a clear asymmetry in the ionization and absorbed dose rates in the polar regions.

What Constitutes the Deployment and Runtime Configuration System? An Empirical Study on OpenStack Projects

Modern software systems are designed to be deployed in different configured environments (e.g., permissions, virtual resources, network connections) and adapted at runtime to different situations (e.g., memory limits, enabling/disabling features, database credentials). Such a configuration during the deployment and runtime of a software system is implemented via a set of configuration files, which together constitute what we refer to as a “configuration system.” Recent research efforts investigated the evolution and maintenance of configuration files. However, they merely focused on a limited part of the configuration system (e.g., specific infrastructure configuration files or Dockerfiles), and their results do not generalize to the whole configuration system. To cope with such a limitation, we aim to better capture and understand what files constitute a configuration system. To do so, we leverage an open card sort technique to qualitatively study 1,756 configuration files from OpenStack, a large and widely studied open source software ecosystem. Our investigation reveals the existence of nine types of configuration files, which cover the creation of the infrastructure on top of which OpenStack will be deployed, along with other types of configuration files used to customize OpenStack after its deployment. These configuration files are interconnected while being used at different deployment stages. For instance, we observe specific configuration files used during the deployment stage to create other configuration files that are used in the runtime stage. We also observe that identifying and classifying these types of files is not straightforward, as five out of the nine types can be written in similar programming languages (e.g., Python and Bash) as regular source code files. We also found that the same file extensions (e.g., Yaml ) can be used for different configuration types, making it difficult to identify and classify configuration files. Thus, we first leverage a machine learning model to identify configuration from non-configuration files, which achieved a median area under the curve (AUC) of 0.91, a median Brier score of 0.12, a median precision of 0.86, and a median recall of 0.83. Thereafter, we leverage a multi-class classification model to classify configuration files based on the nine configuration types. Our multi-class classification model achieved a median weighted AUC of 0.92, a median Brier score of 0.04, a median weighted precision of 0.84, and a median weighted recall of 0.82. Our analysis also shows that with only 100 labeled configuration and non-configuration files, our model reached a median AUC higher than 0.69. Furthermore, our configuration model requires a minimum of 100 configuration files to reach a median weighted AUC higher than 0.75.

Technical, forensic and organisational aspects of work with Monero cryptocurrency

The forensic, organisational and technical features of law enforcement agencies' work with the Monero cryptocurrency in the context of pre-trial investigation and operational search activities are analysed. The development of the Monero system is described. The reasons and trends of Monero use by offenders are identified, and the scheme of operation of this payment system, which ensures its increased confidentiality, is shown. Examples of criminal offences in which Monero is used are presented. The functionality of OpenAlias to facilitate the work with Monero addresses is disclosed. The possibility of identifying participants in Monero transactions is studied. It is stated that there are currently no effective ways of such identification without knowledge of the public address and the corresponding keys, especially if users use additional security mechanisms such as connection to the TOR network.
 The features of forensic investigation of computer equipment used to work with Monero are revealed. It is established that the most effective is the study of traces of work with Monero, which are removed from the relevant computer equipment of the person of interest. Useful information can be stored in RAM, on a disc, and partially in network traffic. The article identifies artefacts that should be taken into account during inspection and search. Atomic Swaps of XMR are modelled to determine the trace pattern and identify artefacts of increased attention during forensic procedures. The fact that an atomic swap was carried out to obfuscate traces may be evidenced by the presence of specific software files on the disc used for this purpose.
 The algorithm for XMR withdrawal using multisig addresses has been proposed, from which funds can be withdrawn only when digital signatures of several persons are superimposed. The work of this algorithm in the test network Stagenet is modelled. It has been concluded that law enforcement agencies should focus on classical investigative measures to identify Monero users of interest. At the same time, there are effective mechanisms for documenting traces of work with the Monero payment system and proven methods for extracting passphrases to crypto-wallets and other sensitive information on the movement of funds in the Monero system from computer equipment.

Recommendations for the Contents of a Product Specification File: Related Substances (HPLC)

This article provides recommendations for documenting an analytical procedure for the determination of related substances by high-performance liquid chromatography in a product specification file (PSF). The article contains a description of specific aspects and a template for the typical contents and layout of the PSF section dedicated to related substances. A unified approach to the PSF content and layout will ensure error-free testing, reliable results, and streamlined regulatory assessments.

Effects of pertussis toxin and <i>Bordetella pertussis</i> lipo-oligosaccharide on the specific toxicity and potency of whole-cell pertussis vaccines

Scientific relevance. The content of Bordetella pertussis lipo-oligosaccharide (LOS) and the residual levels of active pertussis toxin (PT) are generally accepted to be the primary factors that determine the reactogenicity of whole-cell pertussis vaccines. To improve the quality of whole-cell pertussis vaccines, it is both relevant and necessary to study the relationship between the toxicity of B. pertussis bacterial cell components and the main quality parameters of these vaccines, including their potency and specific toxicity, as termed in the WHO recommendations and the European Pharmacopoeia.Aim. This study aimed to analyse the effects of B. pertussis LOS and residual active PT on the specific toxicity and potency of adsorbed diphtheria, tetanus, and whole-cell pertussis (DTwP) vaccines.Materials and methods. The authors tested 57 commercial batches of adsorbed DTwP vaccines for compliance with the regulatory standards and product specification files. Vaccine batches that failed specific toxicity tests formed Group 1, and the other batches were designated as Group 2. The potency was tested in F1 CBA/Ca×C57BL/6J hybrid mice with experimentally induced meningoencephalitis that were immunised with DTwP and reference vaccines. The authors assessed the specific toxicity of DTwP vaccines by changes in body weight following intraperitoneal administration. The toxic activity was assessed indirectly by changes in body weight in the first 16–24 h (B. pertussis LOS) and on day 7 (PT) after dosing. The authors used Spearman’s rank correlation coefficient to measure the strength of correlation between the toxic activity of vaccine components and the specific toxicity and potency of the vaccine, which were established using the same vaccine batches.Results. The authors measured the toxic activity of LOS and residual active PT in the vaccine batches studied. The correlation coefficients between the specific toxicity and potency of the vaccines and the toxic activity of LOS were 0.113 (p>0.05) and 0.049 (p>0.05), respectively. Similarly, the correlation coefficients between the specific toxicity and potency of the vaccines and the toxic activity of PT accounted for 0.595 (p<0.01) and –0.534 (p<0.01), respectively.Conclusions. The authors studied the toxic activity of B. pertussis LOS and residual active PT in whole-cell pertussis vaccines and found an inverse correlation between the potency of the vaccines and the toxic activity of residual active PT. The study demonstrated that the specific toxicity test for whole-cell pertussis vaccines fails to detect and quantify B. pertussis LOS in the samples. The authors advise to determine the content of LOS in the B. pertussis strains intended for the production of whole-cell pertussis vaccines, which is not yet an accepted practice in the Russian Federation.

Assessment of Hospital-Onset SARS-CoV-2 Infection Rates and Testing Practices in the US, 2020-2022.

Characterizing the scale and factors associated with hospital-onset SARS-CoV-2 infections could help inform hospital and public health policies regarding prevention and surveillance needs for these infections. To evaluate associations of hospital-onset SARS-CoV-2 infection rates with different periods of the COVID-19 pandemic, hospital characteristics, and testing practices. This cohort study of US hospitals reporting SARS-CoV-2 testing data in the PINC AI Healthcare Database COVID-19 special release files was conducted from July 2020 through June 2022. Data were collected from hospitals that reported at least 1 SARS-CoV-2 reverse transcription-polymerase chain reaction or antigen test during hospitalizations discharged that month. For each hospital-month where the hospital reported sufficient data, all hospitalizations discharged in that month were included in the cohort. SARS-CoV-2 viral tests and results reported in the microbiology files for all hospitalizations in the study period by discharge month were identified. Data analysis was conducted from September 2022 to March 2023. Hospitalizations discharged in an included hospital-month. Multivariable generalized estimating equation negative-binomial regression models were used to assess associations of monthly rates of hospital-onset SARS-CoV-2 infections per 1000 patient-days (defined as a first positive SARS-CoV-2 test during after hospitalization day 7) with the phase of the pandemic (defined as the predominant SARS-CoV-2 variant in circulation), admission testing rates, and hospital characteristics (hospital bed size, teaching status, urban vs rural designation, Census region, and patient distribution variables). A total of 5687 hospital-months from 288 distinct hospitals were included, which contributed 4 421 268 hospitalization records. Among 171 564 hospitalizations with a positive SARS-CoV-2 test, 7591 (4.4%) were found to be hospital onset and 6455 (3.8%) were indeterminate onset. The mean monthly hospital-onset infection rate per 1000 patient-days was 0.27 (95 CI, 0.26-0.29). Hospital-onset infections occurred in 2217 of 5687 hospital-months (39.0%). The monthly percentage of discharged patients tested for SARS-CoV-2 at admission varied; 1673 hospital-months (29.4%) had less than 25% of hospitalizations tested at admission; 2199 hospital-months (38.7%) had 25% to 50% of all hospitalizations tested, and 1815 hospital months (31.9%) had more than 50% of all hospitalizations tested at admission. Postadmission testing rates and community-onset infection rates increased with admission testing rates. In multivariable models restricted to hospital-months testing at least 25% of hospitalizations at admission, a 10% increase in community-onset SARS-CoV-2 infection rate was associated with a 178% increase in the hospital-onset infection rate (rate ratio, 2.78; 95% CI, 2.52-3.07). Additionally, the phase of the COVID-19 pandemic, the admission testing rate, Census region, and bed size were all significantly associated with hospital-onset SARS-CoV-2 infection rates. In this cohort study of hospitals reporting SARS-CoV-2 infections, there was an increase of hospital-onset SARS-CoV-2 infections when community-onset infections were higher, indicating a need for ongoing and enhanced surveillance and prevention efforts to reduce in-hospital transmission of SARS-CoV-2 infections, particularly when community-incidence of SARS-CoV-2 infections is high.

Improving pharmacometrics analysis efficiency using DataCheQC: An interactive, Shiny-based app for quality control of pharmacometrics datasets.

DataCheQC is an interactive application based on the R Shiny framework developed for the purposes of performing quality control (QC) checks on pharmacometric datasets, and thereby supporting the implementation of model-informed drug development. Features include visual inspection of variables and data entries for errors and/or anomalies, and ensuring structural integrity through comparison with a dataset specification file. The app, which requires no programming knowledge to operate, allows the user to collect all findings into a summary report downloadable directly from the app itself. The source code for the app is freely available on GitHub under an open-source license (https://github.com/DotanOr/DataCheQC) and can also be accessed online (https://dotanor.shinyapps.io/DataCheQC/).

LinguaPhylo: A probabilistic model specification language for reproducible phylogenetic analyses.

Phylogenetic models have become increasingly complex, and phylogenetic data sets have expanded in both size and richness. However, current inference tools lack a model specification language that can concisely describe a complete phylogenetic analysis while remaining independent of implementation details. We introduce a new lightweight and concise model specification language, 'LPhy', which is designed to be both human and machine-readable. A graphical user interface accompanies 'LPhy', allowing users to build models, simulate data, and create natural language narratives describing the models. These narratives can serve as the foundation for manuscript method sections. Additionally, we present a command-line interface for converting LPhy-specified models into analysis specification files (in XML format) compatible with the BEAST2 software platform. Collectively, these tools aim to enhance the clarity of descriptions and reporting of probabilistic models in phylogenetic studies, ultimately promoting reproducibility of results.

Sensitivity to nuclear data of the design of the IFMIF-DONES beam dump

During the commissioning and start-up phases of IFMIF-DONES, the 40 MeV deuteron beam will be stopped in a conical beam stopper made of copper, giving rise to intense neutron fields. Accurate coupled deuteron-neutron transport simulations are required in order to prevent the potential risks to the workers and equipment involved. However, the experimental data concerning the neutron emission under these circumstances is scarce and limited to a particular range of energies. Different deuteron nuclear data libraries such as JENDL-5 and special files of TENDL-2021 exhibit some differences on the spectrum of the emitted neutrons. The differences are present in the high energy tails, beyond the available experimental data. Calculations of the prompt neutron fields have been performed employing both deuteron data libraries, as well as employing an estimation of the neutron energy-angle distribution derived from experimental data at different irradiation energies. Even though the high energy tails represent a small part of the flux, they have a major impact on the dose rates. The disparity of the results evinces large uncertainties in the IFMIF-DONES beam dump design process. Further experiments are required in order to resolve the differences among nuclear data libraries and reduce the uncertainty.

Packet Chunking for File Detection

Network-based intrusion detection and data leakage prevention systems inspect packets to detect if critical files such as malware or confidential documents are transferred. However, this kind of detection requires heavy computing resources in reassembling packets and only well-known protocols can be interpreted. Besides, finding similar files from a storage requires pairwise comparisons. In this paper, we present a new network-based file identification scheme that inspects packets independently without reassembly and finds similar files through inverted indexing instead of pairwise comparison. We use a content-based chunking algorithm to consistently divide both files and packets into multiple byte sequences, called chunks. If a packet is a part of a file, they would have common chunks. The challenging problem is that packet chunking and inverted-index search should be fast and scalable enough for packet processing. The file identification should be accurate although many chunks are noises. In this paper, we use a small Bloom filter and a two-level threshold strategy to solve the problems. To the best of our knowledge, this is the first scheme that identifies a specific critical file from a packet over unknown protocols. Experimental results show that the proposed scheme can successfully identify a critical file from a packet without packet reassembly.

Development of Cloud Point Data Processing Program for 3D BIM and 2D Cross Section Needs

The need for technological developments is needed to facilitate performance, accuracy, and effectiveness of work, especially in the field of civil engineering, is needed. With the emergence of innovative LiDAR (Light Detection and Ranging) technology scanners that are popularly used for 3D printing, developed into LiDAR Scanners for real field scanning. The result of using a LiDAR Scanner is in the form of point cloud data in a certain format, with a large enough memory. The purpose of this research is to use field point cloud data as 3D BIM data and then form a cross-section of the object. For this purpose, a special program is needed that functions to process cloud point data complexly, and is easy to use to change the shape of cloud point data to 3D data surface and 2D cross sections. The method used in this study is by creating a special program to process data point clouds using script code with the python language and several data point cloud processing libraries. In the program, 2 sub-menus will be created with certain functions: 1) Point Cloud (voxel downsampling, outlier reduction, normalize); 2) 3D model (ball pivoting/poisson surface, reduce vertex, slice mesh, transform mesh). In each data processing, the created program can only process on a specific file format; for point cloud processing in .xyz, .xyzn, .xyzrgb, .pts, .ply, .pcd formats; while for 3D data processing models are in .ply, .stl, .obj, .off , .gltf/glb format. The result of data processing using the created program can be a 3D surface with .ply /.obj format, and for cross-section generated 2D data with .jpg / .png format, and can be in the form of .dxf data for Autocad software. 3D surface data can be used as BIM data, while 2D cross-section data can be used as built 2D.

A Risk-Based Approach to Planning the Elaboration of Pharmacopoeial Monographs

Scientific relevance. This article describes a risk-based analysis of the need for elaborating pharmacopoeial requirements for 6 therapeutic groups of medicines, including an evaluation of the range and number of batches of these medicines put into the stream of commerce in the Russian Federation and a comparison of the corresponding product specification files and quality standards. The article presents a set of criteria for planning the elaboration of monographs for the State Pharmacopoeia of the Russian Federation according to a risk-based approach, which is used in a variety of other fields.Aim. The study aimed to develop a comprehensive multivariate risk-based system providing criteria for planning the elaboration of monographs for the State Pharmacopoeia of the Russian Federation.Materials and methods. This study focused on medicines for human use under a range of international non-proprietary names. The authors analysed entries in the Russian State Register of Medicines, data on the number of batches released to the pharmaceutical market, and product specification files and quality standards. The study was conducted using literature search, data analysis, and system-oriented methods.Results. According to the results, a multivariate risk-based analysis is needed for planning the elaboration of monographs for the State Pharmacopoeia of the Russian Federation and the subsequent prioritisation of therapeutic groups or individual medicines for their standardisation.Conclusions. The suggested risk-based system for planning the elaboration of monographs for the State Pharmacopoeia of the Russian Federation includes the following criteria: the social significance of a medicinal product and its value for the health care system; the percentage of medicinal products not tested by the national regulatory authority at the level of active pharmaceutical ingredients; the substantial number of batches and the significant range of medicinal products and the respective active pharmaceutical ingredients by different manufacturers present in the pharmaceutical market; and the analytical procedures and requirements established in product specification files and quality standards.

SISTEM INFORMASI PENGOLAHAN ASET DESA PADA KANTOR DESA MANDIANGIN TUO

Village assets are village assets originating from the village's original assets, purchased orobtained at the expense of the Village Revenue and Expenditure Budget (APBDesa), Village Asset Management at the Mandiangin Tuo Village Office is carried out by recording it on paper and storing it in a special village file cabinet. This causes many errors to occur, and spend a lot of time searching for the data. In order for inventoryrecords and goods mutations to be more precise and accurate and easier to do in recording the existence of these goods,the Mandiangin Tuo Village Officer equires an application in the form of a website.

Secure cloud file sharing scheme using blockchain and attribute-based encryption

This paper presents a novel collaboration scheme for secure cloud file sharing using blockchain and attribute-based encryption(ABE). Blockchain enables us to implement access control as a smart contract between data owner and users. Each data owner creates its own smart contract where in a data user can request to access a specific file by registering a transaction. In response transaction, the data owner sends the required credential to the user thereby enabling her/him to decrypt the intended file on the cloud storage. This scheme is decentralized, fault tolerant and secured against DoS attacks. The cipher-key, which is used for file encryption, is embedded into a set of coefficients of a polynomial so-called access polynomial. It is attached to the encrypted file on the cloud storage as a metadata. The data user can restore the cipher-key by means of the credential receiving in response transaction and access polynomial. The data owner uses ABE scheme in response transaction to impose her/him access policy to the file as well as preserving user anonymity. This scheme supports fast revocation of the user access by means of updating the access polynomial coefficients and without any communication overhead to non-revoked users. Through formal verification, we show that the scheme is secure in terms of secrecy of credential information and authentication of participants. Finally, the evaluation results show that our scheme is scalable with acceptable performance up to 20,000 users.

DEVELOPMENT OF A RESOURCE MANAGEMENT METHODOLOGY FOR A SERVICE COMPANY

This article discusses the specifics of managing a service-related company. It shows how the preparation of input data and their transformation takes place. Peculiarities of model preparation for training and testing are demonstrated. The general scheme of interaction between customer end-users and project and third-party technical support taking into account the conditions of service maintenance is given. The scheme of logic of processing incoming incidents between support lines is shown. The logic diagram of the prediction module for determining the support team is given. After the work has received the trained model that allows to carry out prediction of a support team on the basis of methods of logistic regression, by means of language Python it can be saved as a special file, it can then be connected as an independent module.
 Purpose. Determination of methods and techniques of analysis used in the analysis of export operations.
 Methodology the article used systems analysis and enterprise management methods.
 Results: an example of resolved incident data for a specific support team with engineers is considered, as well as an example of numerical feature calculations to adjust the support team engineer’s baseline prediction. A logic diagram of the improved software solution model is shown.
 Practical implications can be used with the improvement of IT service management in terms of incident coordinator activities.