Network Information System Research Articles

Assessment of Maternal and Infant Health Status in Durham Region

I completed my practicum as a Student Epidemiologist at the Durham Region Health Department with the Health Analytics and Research Team (HART). HART is tasked with conducting population health assessments in the Durham Region. As a member of HART, I played a critical role in assessing the maternal and infant health status of the local population using data from the Better Outcome Registry and Network (BORN) information system (BIS), a database that contains critical reproductive and child health data in Ontario. Specifically, my primary responsibilities included data extraction and data coding, which encompassed a series of tasks, spanning from data cleaning to data analysis in STATA. By analyzing BORN data, I was able to refine my statistical and programming skills. Moreover, I collaborated with public health program staff to develop infographics that disseminated critical maternal and infant health information to various communities. The infographics I assisted with covered a wide range of maternal and infant health topics, including issues such as gestational diabetes and maternal mental health concerns. From here, I was able to effectively communicate health information in a concise and understandable manner. In addition, I had the opportunity to attend various public health workshops and group meetings during my practicum. These experiences not only expanded my knowledge of diverse public health topics but also afforded me greater familiarity with public health practice. In summary, my time at the Durham Region provided me with an exceptional opportunity to apply the knowledge I gained in school to real-world practice. It was a valuable and enriching experience that significantly contributed to my professional development in the field of public health.

Land surface temperature trends derived from Landsat imagery in the Swiss Alps

Abstract. The warming of high mountain regions caused by climate change is leading to glacier retreat, decreasing snow cover, and thawing permafrost, all of which have far-reaching effects on ecosystems and societies. Landsat Collection 2 provides multi-decadal land surface temperature (LST) data, principally suited for large-scale monitoring at high spatial resolution. In this study, we assess the potential to extract LST trends using Landsat 5, 7, and 8 time series. We conduct a comprehensive comparison of both LST and LST trends with data from 119 ground stations of the Intercantonal Measurement and Information System (IMIS) network, located at high elevations in the Swiss Alps. The direct comparison of Landsat and IMIS LST yields robust satellite data with a mean accuracy and precision of 0.26 and 4.68 K, respectively. For LST trends derived from a 22.6-year record length, as imposed by the IMIS data, we obtain a mean accuracy and precision of −0.02 and 0.13 K yr−1, respectively. However, we find that Landsat LST trends are biased due to unstable diurnal acquisition times, especially for Landsat 5 and 7. Consequently, LST trend maps derived from 38.5-year Landsat data exhibit systematic variations with topographic slope and aspect that we attribute to changes in direct shortwave radiation between different acquisition times. We discuss the origin of the magnitude and spatial variation of the LST trend bias in comparison with modeled changes in direct shortwave radiation and propose a simple approach to estimate the LST trend bias. After correcting for the LST trend bias, the remaining LST trend values average between 0.07 and 0.10 K yr−1. Furthermore, the comparison of Landsat- and IMIS-derived LST trends suggests the existence of a clear-sky bias, with an average value of 0.027 K yr−1. Despite these challenges, we conclude that Landsat LST data offer valuable high-resolution records of spatial and temporal LST variations in mountainous terrain. In particular, changes in the mountain cryosphere, such as glacier retreat, glacier debris cover evolution, and changes in snow cover, are preserved in the LST trends and potentially contribute to improved prediction of permafrost temperatures with large spatial coverage. Our study highlights the significance of understanding and addressing biases in LST trends for reliable monitoring in such challenging terrains.

Visualising and mapping historical networks of international diplomatic training

AbstractWhat might methodological approaches drawing on Geographical Information Systems (GIS) and Social Network Analysis (SNA) offer to sub‐disciplines in geography which have traditionally been dominated by qualitative and often micro‐scale research, such as historical or political geography? How might these approaches—often understood as opposing—be brought together to advance transnational research in particular? This article responds to these questions through a reflection on a recent project on the geopolitics of diplomatic training in the mid‐twentieth century. Building on the established use of biography to focus transnational analyses within a complex abundance of sources, the project complemented such close‐reading with computational methods of distant‐reading, able to analyse large datasets to produce prosopographies and network visualisations that help identify diffuse and larger scale political and geographical relationships. The article concludes with a consideration of how such methods might be effectively integrated in the historical or political geographer's toolkit.

Determining optimal parameters of algebraic fractals in zero-knowledge authentication protocols

Most information systems, especially on the Internet, have a distributed architecture with remote access and an insecure communication channel. In such systems, the tasks of permanent authorization mean implementing time intervals of user work without re-authentication are especially actual. The problem is that repeatedly sending a password increases the likelihood of it corruption. One solution is to use zero-knowledge protocols. In these protocols, passwords are not transmitted over the channel but are included in the algorithms as parameters. However, the computational complexity, as well as the finite number of passwords, limit their use, ensuring the relevance of further research. Focusing on object of the exchange protocols security, the use of algebraic fractal sets has been proposed as a potentially infinite source of data for passwords. In this work, algorithms were developed, implemented, and tested, which proved the higher reliability of fractal protocols in comparison with the reference generator of random bits (with an error probability of 0.5). It was also noted that the calculation operations have an insignificant influence on the overall time complexity of the exchange protocol as a whole. Practical recommendations for the use of fractals with a Hausdorff dimensionally of about 1.6 on the boundary of the Mandelbrot set are given. The paper also highlights the advantages of including color information in fractal sets, which gives about 3 times improving of confidential security indicators of communication protocol. The proposed algorithms do not require specialized software and can be implemented in the majority of network information systems as an additional module.

Update on Vaccine-Derived Poliovirus Outbreaks - Worldwide, January 2023-June 2024.

Circulating vaccine-derived polioviruses (cVDPVs) can emerge and lead to outbreaks of paralytic polio as well as asymptomatic transmission in communities with a high percentage of undervaccinated children. Using data from the World Health Organization Polio Information System and Global Polio Laboratory Network, this report describes global polio outbreaks due to cVDPVs during January 2023-June 2024 and updates previous reports. During the reporting period, 74 cVDPV outbreaks were detected in 39 countries or areas (countries), predominantly in Africa. Among these 74 cVDPV outbreaks, 47 (64%) were new outbreaks, detected in 30 (77%) of the 39 countries. Three countries reported cVDPV type 1 (cVDPV1) outbreaks and 38 countries reported cVDPV type 2 (cVDPV2) outbreaks; two of these countries reported cocirculating cVDPV1 and cVDPV2. In the 38 countries with cVDPV2 transmission, 70 distinct outbreaks were reported. In 15 countries, cVDPV transmission has lasted >1 year into 2024. In Nigeria and Somalia, both countries with security-compromised areas, persistent cVDPV2 transmission has spread to neighboring countries. Delayed implementation of outbreak response campaigns and low-quality campaigns have resulted in further international spread. Countries can control cVDPV outbreaks with timely allocation of resources to implement prompt, high-quality responses after outbreak confirmation. Stopping all cVDPV transmission requires effectively increasing population immunity by overcoming barriers to reaching children.

Social network analysis approach to identify agricultural key communicators

Aim: This paper employed Social Network Analysis approach to visualize and calculate different social network metrics. It identifies key communicators who play pivotal roles in information flow. Methodology: Research was conducted at Jammulapalem and Perali villages of Bapatla district, Andhra Pradesh, India, during 2022-23 using an exploratory research design. A total of 120 farmers Eigen vector were selected using simple random technique, and data was collected using a well-developed interview schedule. Network metrics such as Degree centrality, betweenness centrality, and eigen vector centrality were computed to evaluate the network structure using R software (version 4.3.1). R packages, namely igraph, statnet and network D3, were used for network creation, analysis and visualization to identify the influential nodes. Results: The study revealed a complex web of relationships among various stakeholders within the agricultural network through a network graph, identifying key communicators with the highest Degree centrality. Interpretation: The focal points identified through Social Network Analysis represent a specific demographic and socio-economic group, typically aged between 35 and 55, primarily medium-scale farmers,with landholdings spanning 10 to 25 acres and high annual income, with educational backgrounds ranging from high school to pre-university college, and wield significant influence within their local communities. They require sensitization, training, practical demonstrations, and personalized support to effectively disseminate agricultural information. Key words: Agricultural Information System Network, Centrality measures, Information Sources, Key Communicators, Network visualization, Social Network Analysis

Information protection and cyber security in the public and financial sectors

The public sector faces increasing challenges in the field of cyber security and information protection, stimulated by the rapid development of digital technologies. A significant increase in the need for reliable protection of state data and information systems requires state institutions to implement complex information protection measures. The purpose of the study is to analyze modern approaches and technologies in the field of cyber security and the use of encryption, cryptography, and the use of cloud technologies that can be used in the public sector for effective information protection. The research methodology involves consideration of strategies that allow to increase the level of security and ensure the protection of critical infrastructure. The results of the study emphasize the need to adapt to the rapidly changing digital environment and involve modern technological solutions to create a reliable information network system in the public sector. The findings of the study draw attention to the importance of global cooperation and increased investment in the field of countering digital attacks, demonstrating examples of effective international cooperation and support in this direction. The need for the integration of international standards and practices in order to create a global digital space has been revealed. A promising area of research is the analysis of the impact of the latest technologies on data storage strategies, which contributes to the identification of ways for further innovations in the industry and the creation of flexible information network systems capable of effectively responding to changing conditions and challenges of modern cyberspace.

Functional features of well-known means of network shielding

The work briefly reviews the history, types, and capabilities of the main types of firewalls (FW). Firewalls are an important tool for protecting network resources from various information security threats. With the development of technology and the changing nature of attacks, especially those involving artificial intelligence (IoT), firewalls have also evolved, acquiring new functions and capabilities. This work provides a short survey of the main types, and capabilities of firewall technology, providing solutions to issues of comprehensive protection of network equipment and information resources from modern security threats. Different types of firewalls are used depending on the conditions of operation and purpose of the basic information and communication system (ICS), as well as on the place of their (FW) integration into the network or virtual infrastructure of modern information systems. For integrated networks that require a high level of their security, productivity and flexibility, firewalls of the business segment of generation «Next-generation» and «Threat-focused NGFW» are definitely the best choice. Attention was drawn to the fact that mobile firewalls should in every way contribute to the maintenance of resource consensus and eliminate a possible disparity in the performance of networked mobile applications. Adaptability to mobility of current communication systems (Wi-Fi, GSM and others) determines the specificity of security threats for mobile devices and It defines their key feature. This feature is based on permanent readiness for seamless transitions (reconnections) between different networks in conditions of constant energy shortage and limited available computing resources (meaning gadgets). Highlights the main trends, prospects for the development and implementation of different types of firewalls, including the impact of artificial intelligence, machine learning, cloud technologies and the Internet of Things as well as important aspects of their (FW) scope. It is emphasized that the introduction of FW does not replace other security technologies and tools, but effectively expands the existing arsenal of countering new security threats (primarily as an instrument of proactive countermeasures and rapid response to complex network incidents). The article may be useful for students, researchers, and information security professionals who seek to expand their competencies related to the development and operation of modern means of network protection.

ANALISIS TRANSFER DATA PADA JARINGAN TERDAMPAK ARP SPOOFING MENGGUNAKAN METODE ARP POISONING DAN STATISTIK DESKRIPTIF

This Computer network security issues are very important and need to be considered in the development of computer networks. Networks connected to network devices are usually vulnerable to hacking. Hacking is an activity that allows a person or group to change or take data for personal gain. The aim of this research is to carry out testing and analysis to determine the condition and measure the level of security of the ITDA Yogyakarta intra-campus information system and computer network. Describe security gaps and measure the level of security that needs to be immediately repaired so that it can help correct failures in maintaining the security of ITDA Yogayakarta intra-campus information systems and networks. This research uses descriptive statistics with 20 PC units as samples. There were four tests in this study with a total success of 16 out of 20 samples. From the results of Arp spoofing on the local network, it can be concluded that after the local network is infiltrated by an attacker using the ARP spoofing method, the target traffic will be redirected to the attacker's device. This can allow attackers to monitor and understand the contents of data traffic on the local network. Changing the attacker's MAC address is very necessary because if the MAC is not replaced then network traffic will not be redirected to the attacker's device.

FRAMB: A man-machine cooperation risk assessment method for intelligent network information systems

The intelligent network information systems, such as smart grid systems, face many security problems in the aspects of sensing, communication and computing. Information security risk assessment is an important way to assess the threats faced by information systems before risk events occur and ensure the security of assets. However, a comprehensive risk assessment of the system is a very resource-consuming process. Many existing risk assessment methods rely on a large number of experts and computing resources. Their assessment results are vulnerable to the differences in experts’ subjective judgments. Therefore, we propose FRAMB, a novel man-machine collaborative risk assessment method based on fitting upper and lower bounds. Firstly, we present a risk assessment criterion including four categories and sixteen risk factors following the ISO/IEC 27005:2018 standard. On this basis, we present the DFAHP and CM-NN assessment models to obtain the upper and lower bounds of the risk assessment value, which provides a reference for expert assessment. FRAMB integrates the experts’ assessment value and the values of upper and lower bounds, and adjusts the weights of these values to give the final risk assessment value. We introduce the risk assessment process of FRAMB in detail through a case study of the smart grid system risk assessment. We evaluate the effectiveness and accuracy of FRAMB through experiments. The experimental results show that FRAMB can effectively and accurately assess the security risks of the intelligent network information systems.

Route Planning Algorithms for Fleets of Connected Vehicles: State of the Art, Implementation, and Deployment

The introduction of 5G technologies has enabled the possibility of designing and building several new classes of networked information systems that were previously impossible to implement due to limitations on data throughput or the reliability of transmission channels. Among them, one of the most interesting and successful examples with a highly positive impact in terms of the quality of urban environments and societal and economical welfare is a system of semi-autonomous connected vehicles, where IoT devices, data centers, and fleets of smart vehicles equipped with communication and computational resources are combined into a heterogeneous and distributed infrastructure, unifying hardware, networks, and software. In order to efficiently provide various services (e.g., patrolling, pickup and delivery, monitoring), these systems typically rely on collecting and broadcasting large amounts of data (e.g., sensor data, GPS traces, or maps), which need to be properly collected and processed in a timely manner. As is well documented in the literature, one of the most effective ways to achieve this purpose, especially in a real-time context, is to adopt a graph model of the data (e.g., to model communication networks, roads, or interactions between vehicles) and to employ suitable graph algorithms to solve properly defined computational problems of interest (e.g., shortest paths or distributed consensus). While research in this context has been extensive from a theoretical perspective, works that have focused on the implementation, deployment, and evaluation of the practical performance of graph algorithms for real-world systems of autonomous vehicles have been much rarer. In this paper, we present a study of this kind. Specifically, we first describe the main features of a real-world information system employing semi-autonomous connected vehicles that is currently being tested in the city of L’Aquila (Italy). Then, we present an overview of the computational challenges arising in the considered application domain and provide a systematic survey of known algorithmic results for one of the most relevant classes of computational problems that have to be addressed in said domain, namely, pickup and delivery problems. Finally, we discuss implementation issues, adopted software tools, and the deployment and testing phases concerning one of the algorithmic components of the mentioned real-world system dedicated to handling a specific problem of the above class, namely, the pickup and delivery multi-vehicle problem with time windows.

COMPREHENSIVE CONDITION ANALYSIS AND PERSPECTIVES OF ENERGY DEVELOPMENT IN UKRAINE ACCORDING TO THE SMART GRID CONCEPT

The article examines development trends of the energy complex of Ukraine, possibility and prospects of creating a modern energy complex through the use of an innovative technical base for energy management in accordance with the Smart Grid concept. The general properties of Smart Grid technology and its main advantages are given by authors. It is shown that within the framework of the Smart Grid concept, the intelligent electric power system is considered as a single network of information and control systems. The process of electric power industry modernization in the direction of the creation of "smart" power supply networks in a number of European countries, which aims to ensure stable development, economic growth, growth of living standards and protection of the natural environment, is considered. The paper describes modernization methods of the electric power complex of Ukraine based on foreign experience. It is shown that from the point of view of energy security and sustainable development, Smart Grid is able to ensure the operation of the power grid even in case of damage or destruction of one segment, which is a key advantage during post-war reconstruction. They will also make it possible to effectively integrate renewable generation and energy storage systems into the grid, as well as provide auxiliary services for forecasting the power system operation. The paper analyzes the problematic issues of implementing the Smart Grid concept in Ukraine. They include the lack of technological solutions and methods that provide an effective algorithm for determining the state of power networks cyber security; large length of power distribution networks and insufficiently developed infrastructure. A comparative description of the existing energy systems functional properties and energy systems based on the Smart Grid concept is presented in general. An analysis of possible ways of electric power industry development was carried out, which showed the presence of serious limitations of electric power industry development within the framework of the former concept, based mainly on the improvement of certain types of equipment and technologies. It is shown that Ukraine is at the initial familiarization and formation stage of the first organizational initiatives for Smart Grid, namely the implementation of the government-approved Concept of the "smart grids" introduction in Ukraine for the period up to 2035. The purpose and expected results of this Concept implementation are considered.

Electrically‐Reconfigurable Extremely‐High Density Physical Unclonable Cryptographic Keys Based on Aurivillius Ferroelectrics

AbstractIn the era of information, emerging hardware security primitives, i.e., hardware random number generators and physically unclonable functions, hold profound promise for the establishment of exceptionally secure network information systems. Nonetheless, these potential solutions are constrained by inherent drawbacks, including the need for additional error correction circuits or algorithms, heightened susceptibility to environmental interference, and limited data density. This paper demonstrates the extremely high‐density, physical‐unclonable cryptographic keys by harnessing stochastically ferroelectric domain polarizations in Aurivillius ferroelectric material CaBi2Nb2O9 (CBNO). Ferroelectric polarization of CBNO nanodomains can serve as a robust source of physical unclonable entropy. Through the application of high‐speed voltage pulses, the inherent randomness of ferroelectric polarizations can be enhanced, thereby yielding cryptographic keys characterized by remarkable uniformity, uniqueness, and negligible environmental sensitivity. More importantly, the voltage pulse operations facilitate the configurability of the ferroelectric cryptographic keys with no correlation. An unprecedented data density of 435 Gbit µm−2 is therefore achievable with a miniaturized CBNO of less than 1 um2. Notably, the reconfigured keys successfully pass the National Institute of Standards and Technology random number tests without requiring additional post‐processing steps. Emanating from the inherent attributes of the material, these high‐density ferroelectric keys confer intrinsic advantages to information security, evincing substantial resistance to duplication or cloning.

Development and validation of thromboembolism diagnostic algorithms in children with cancer from real-world data.

To evaluate the accuracy of diagnostic algorithms developed using the International Classification of Diseases (ICD-9-CM and ICD-10-CA) diagnostic codes and physician billing codes for thromboembolism (TE) from health administrative data compared to chart review diagnoses of TE in children with cancer. Using data linkage between the Pediatric Oncology Group of Ontario Network Information System (Ontario pediatric cancer registry) and various administrative data housed at ICES, eight algorithms were developed including a single reference to one of the billing codes, multiple references with varying time intervals, and combinations of various billing codes during primary cancer therapy for the whole cohort and, for early (<04/2002) and later (≥04/2002, solely ICD-10 codes) periods. Reference standard was chart review data from prior studies (from 1990 to 2016) among children (≤19 years) with cancer and radiologically confirmed TE. Records of 2056 patients diagnosed with cancer at two participating sites during study period were reviewed; 112 had radiologically confirmed TE. The algorithm with addition of anticoagulation utilization codes was the best performing algorithm (sensitivity = 0.76;specificity = 0.85). With use of ICD-10 only codes, sensitivity of the same algorithm improved to 0.84 with specificity of 0.80. This study provides a valid approach for ascertaining pediatric TE using real-world data. Research in pediatric thrombosis, especially cancer-related thrombosis, is limited mainly due to small-sized studies. Real-world data provide ready access to large and diverse populations. However, there are no validated algorithms for identifying thrombosis in real-world data for children. An algorithm based on combination of thrombosis and anticoagulation utilization codes had 76% sensitivity and 85% specificity to identify diagnosis of thrombosis in children in administrative data. This study provides a valid approach for ascertaining pediatric thrombosis using real-world data and offers a good avenue to advance pediatric thrombosis research.

Regional Feature Product Development Management Using Data Management Using Networked Websites in Assisted Villages in Realizing the Tridharma of Politeknik Negeri Medan

This research aims to carry out database management according to market needs and predetermined entities/variables, to be used as data storage for profiles of assisted villages based on superior village products and to redesign a web-based information system that presents profiles of assisted villages based on superior products and village connectivity. the. The research method used in database design and information system design uses descriptive qualitative methods by conducting focus group discussions with P3M Polmed administrators and conducting in-depth interviews with six village heads/secretaries in designing the prototype. This research produces a design for a networked website-based information system with the addition of creating the location and knowing the distance between one village and another, which presents a profile of the target village based on superior products that can be accessed via a network of websites and produces a mandatory output in the form of a book with an ISBN.

Load balancing and topology dynamic adjustment strategy for power information system network: a deep reinforcement learning-based approach

As power information systems play an increasingly critical role in modern society, higher requirements are placed on the performance and reliability of their network infrastructure. In order to cope with the growing data traffic and network attack threats in the power information system, we select the power information system data center network as the research object and design an overall system solution based on software defined network, including the application layer, control layer and infrastructure layer. A typical fat tree network topology is simulated and analyzed. We define the load balancing and network topology dynamic adjustment problem as a Markov decision process, and design a data flow path acquisition method based on breadth-first search to construct the action space of each host. Then, a deep reinforcement learning algorithm based on deep Q-network, priority experience replay and target network is introduced to provide solutions for optimizing the performance of power information systems and responding to network attacks. Simulation results show that the proposed method is better than the traditional equal-cost multi-path algorithm in terms of average bandwidth utilization, average jitter and average packet loss, and can reduce the probability of network nodes being attacked by more than 11%.

Mapping clinical interactions in an Australian tertiary hospital emergency department for patients presenting with risk of suicide or self-harm: Network modeling from observational data.

Reliable assessment of suicide and self-harm risk in emergency medicine is critical for effective intervention and treatment of patients affected by mental health disorders. Teams of clinicians face the challenge of rapidly integrating medical history, wide-ranging psychosocial factors, and real-time patient observations to inform diagnosis, treatment, and referral decisions. Patient outcomes therefore depend on the reliable flow of information through networks of clinical staff and information systems. This study aimed to develop a quantitative data-driven research framework for the analysis of information flow in emergency healthcare settings to evaluate clinical practice and operational models for emergency psychiatric care. We deployed 2 observers in a tertiary hospital emergency department during 2018 for a total of 118.5 h to record clinical interactions along patient trajectories for presentations with risk of self-harm or suicide (n = 272 interactions for n = 43 patient trajectories). The study population was reflective of a naturalistic sample of patients presenting to a tertiary emergency department in a metropolitan Australian city. Using the observational data, we constructed a clinical interaction network to model the flow of clinical information at a systems level. Community detection via modularity maximization revealed communities in the network closely aligned with the underlying clinical team structure. The Psychiatric Liaison Nurse (PLN) was identified as the most important agent in the network as quantified by node degree, closeness centrality, and betweenness centrality. Betweenness centrality of the PLN was significantly higher than expected by chance (>95th percentile compared with randomly shuffled networks) and removing the PLN from the network reduced both the global efficiency of the model and the closeness centrality of all doctors. This indicated a potential vulnerability in the system that could negatively impact patient care if the function of the PLN was compromised. We developed an algorithmic strategy to mitigate this risk by targeted strengthening of links between clinical teams using greedy cumulative addition of network edges in the model. Finally, we identified specific interactions along patient trajectories which were most likely to precipitate a psychiatric referral using a machine learning model trained on features from dynamically constructed clinical interaction networks. The main limitation of this study is the use of nonclinical information only (i.e., modeling is based on timing of interactions and agents involved, but not the content or quantity of information transferred during interactions). This study demonstrates a data-driven research framework, new to the best of our knowledge, to assess and reinforce important information pathways that guide clinical decision processes and provide complementary insights for improving clinical practice and operational models in emergency medicine for patients at risk of suicide or self-harm. Our findings suggest that PLNs can play a crucial role in clinical communication, but overreliance on PLNs may pose risks to reliable information flow. Operational models that utilize PLNs may be made more robust to these risks by improving interdisciplinary communication between doctors. Our research framework could also be applied more broadly to investigate service delivery in different healthcare settings or for other medical specialties, patient groups, or demographics.

Research on optimization strategies for urban park green space planning in Nanjing based on GIS from the perspectives of network analysis and Thiessen polygon theory

Urban Park green space is an essential carrier and form of urban recreation space, playing an important role in improving the ecological environment and enhancing the image of the city. With the process of urbanization and the continuous improvement of residents’ living standards, urban park construction has become increasingly important to meet people’s growing needs for a better life. However, the evaluation indicators for urban park green space in China mostly consider macroscopic levels, such as the area, number and per capita green area of parks. This cannot fully reflect the level of park green space services. Accessibility can reflect the convenience of residents to reach the park, provide guidance for the reasonable layout of parks and have various evaluation methods relying on geographic information technology. Therefore, it is necessary to quantitatively study the layout and accessibility of park green space. Taking the central urban area of Nanjing as the research object, this paper summarizes existing research and focuses on evaluating the accessibility of park green space while analyzing the layout of parks from multiple perspectives, combined with the existing pressure appraisal of park green space services. Relevant data on Nanjing, including overall planning and statistical yearbooks, were collected and analyzed using geographic information system (GIS) tools, network analysis and Thiessen polygon theory to analyze the service pressure, demand and accessibility of park green space in the central urban area under different transportation methods. Based on the results, targeted optimization strategies are proposed.

Optimizing Data Traffic: Effective Management of Physical Processes in Networked Information Systems

Optimizing Data Traffic: Effective Management of Physical Processes in Networked Information Systems

Зарубежный опыт организации архивного хранения электронных документов

The article attempts to analyze what organizational and technological solutions are used by archivists of different countries to organize archival storage of electronic documents in state archives. The widespread introduction of document management information systems in the activities of organizations has led to the accumulation of significant volumes of electronic documents that represent value. The most significant documents are subject to long-term storage in state archives. Archivists are called upon to answer the questions of how organizationally and technologically archival electronic documents should be stored, ensuring that professional procedures are followed in accordance with current legal standards. In the USA, a special division has been created within the structure of the National Archives and Records Management, which performs the whole range of functions to organize the storage of electronic documents. The Federal Republic of Germany has a two-stage system of organizing archival storage of electronic documents. From federal institutions, electronic documents are deposited in the Intermediate Archive of Electronic Documents, from where they are transferred to the Federal Archive for permanent storage. The creation of special state archives for the preservation of electronic documents in some countries has not become an effective form of organizing archival preservation of electronic documents due to the lack of their own sources of acquisition and uncertainty of the legal basis for their functioning. On the example of the Republic of Kazakhstan and the Republic of Slovenia, a network information system for electronic documents storage is considered, which is based on a single technological solution for archives of all levels, both individual organizations and state archives, providing automation of the main functions of the archive and their interaction. Based on the conducted research, three main approaches to the organization of electronic documents storage can be distinguished: as part of national archives; in specialized archives; through the creation of a network infrastructure for electronic documents storage. In any case, it is necessary to create a full-fledged regulatory framework, to ensure the integration of information systems in management and in the archive. It is also necessary to harmonize the conceptual apparatus of various normative acts regulating the procedures of organization and technologies of archival preservation of electronic documents. The study of foreign experience will make it possible to use the best organizational and technological solutions for archival storage of electronic documents in the Russian Federation.