Infrastructure Protection Research Articles

COMBINED DECISION SUPPORT MODEL FOR DEVELOPMENT PRIORITIES OF THE KYIV CAR TUNNEL NETWORK

An analysis is conducted for the opportunities to reduce climate (ecological), technogenic and safety risks in the Kyiv transport infrastructure in case of construction of the car tunnel system envisioned in the Kyiv city General plan. The involved structural and functional factors included district type in the potential tunnel’s area, downtown factor, population density, daily pendular movement, arterial network density, aver-age traffic speed at peak hours, surface connectivity of the exits (portals) of the tunnel by automobile roads, surface road throughput, criticalness of the transport infrastructure object, and vulnerability in case of military attacks or terrorist acts. The modified morphological analysis method was applied in the research, that con-sidered groups of climate (ecological) and techogenic risks, and also the military (terrorist) threats. This be-came the basis for construction of the decision support model regarding the evaluation of priorities and rank-ings (rational order) of tunnel construction. Additionally, a combination of morphological analysis with analyt-ical hierarchy process was proposed that provided alternative viewpoints with a different ranking compared to the basic model, depending on the given priorities (weights) of risk factors during decision making. This approach may be useful for development of the transport policy with the goal of approaching climate neutrality for big cities, as well as maximum protection of urban transport infrastructure in conditions of wartime threats.Using the developed system tools and combined models, the urban society can become safer and more resilient, managing transport policies on the basis of the system approach, and multi-criteria analysis of im-pact factors.

Concepts of infrastructure development in Latin American countries

For the first time in the domestic and international scientific literature, the article analyzes the evolution of concepts of infrastructure development in Latin American countries (LAC), recommendations of international and regional economic organizations. It is noted that conceptual approaches to solving problems of infrastructure development in LAC have changed from dirigiste to neoliberal and from the latter to a combination of various doctrines in the concept of neostructuralism and the theory of sustainable development. All the concepts considered contributed to development of many practical recommendations and to creation of a wide arsenal of state economic policy tools for the development of infrastructure sectors. The attitude of regional organizations and the governments of LAC countries to the infrastructure has changed almost radically: from inattention in the 50s—60s of the last century to understanding its importance as one of the key elements of economic development and social progress. The recommendations concerning infrastructure for protection against natural disasters, transport and logistics, telecommunications and digitalization of the economy are most in demand from Latin American governments.

Development of algorithms for early detection of cyberattacks on networks using machine learning

Critical infrastructure protection and national security are enhanced by the security and reliability of networks. Various types of information circulate on these networks, ranging in classification from open to closed. The consequences of cyberattacks on these networks can be severe, including reputational damage, financial loss, operational disruption and data leakage. Traditional security methods, such as firewalls and anti-virus software, are becoming less effective against modern and ever-changing cyber threats. As a result, powerful network intrusion detection systems (IDS) have become indispensable for proactive detection and mitigation of cyber attacks. Machine learning has become a viable method for creating adaptive intrusion detection tools that can detect new and complex attack patterns. By learning from huge labelled network traffic datasets, ML models can understand the subtle patterns and differentiating features of normal and abnormal or malicious traffic flows. This allows them to detect possible cyber threats and intrusions that traditional signature-based IDSs cannot detect. Extracting discriminative features and training appropriate classification models from such data is a challenging task. In the presented study, we analyse the effectiveness of ML algorithms for detecting cyberattacks, in particular distributed denial of service (DDoS) attacks, in network traffic data. In the presented study, a network attack detection system is developed using ML and deep learning (DL) models and experimented on the CICIDS2017 dataset. The main objectives of the study are to develop a strategy for extracting valuable information from raw network streams; to study the impact of data preparation on the false positive rate; and to conduct a comparative analysis of ML models for cyberattack detection. The main goal of the study is to provide an understanding of the development of a reliable adaptive network intrusion detection system using ML approaches that increase cybersecurity capabilities and protect against future cyberattacks.

Factors Influencing Site Selection for Higher Education Institutes: A Meta-Analysis

Higher education institutions can play an important role in improving society by training productive and committed people through providing knowledge, skills, and necessary values. Studying and conducting research in an optimal location in terms of institute accessibility, resilience against natural and external hazards, and environmental comfort is important for the maximum effectiveness of training. The current study explored which factors contribute to site selection for higher education institutes globally. To do so, a literature review and meta-analysis using secondary data from 1990 to 2024 were conducted to integrate findings from 37 original papers. The results showed that so-called socioeconomic health conditions, student considerations on institute accessibility, and transport services are very important. As such, the socioeconomic health scenarios that affect the improvement of institute location suitability should be given global attention. In addition, we recommend that attention be paid to increasing the level of awareness among individuals about economic features and making necessary interventions for educational infrastructure protection.

Competition and cooperation mechanism of new energy vehicle policies in China’s key regions

New energy vehicles (NEVs) are crucial in addressing environmental pollution and energy shortages. Their widespread adoption has been hindered by challenges such as inadequate infrastructure and limited market competitiveness. To promote the development of NEV, local governments in China have implemented various policies. However, resource constraints within regions have created inherent conflicts among policy objectives, while regional disparities have emerged due to differences in development status and characteristics. This study aims to model the complex competitive and cooperative mechanisms among different NEV policy objectives and compare their variations across three key regions: the Beijing-Tianjin-Hebei (BTH), Guangdong-Guangxi-Fujian (GGF), and Yangtze-River-Delta (YRD). Firstly, topic model Latent Dirichlet Allocation is applied on 857 local NEV policies from 2010 to 2021, identifying six core policy objectives, namely production technology, infrastructure, financial support, demonstration, industrial management and environmental protection. Then, the Lotka-Volterra model is employed to examine competitive and cooperative mechanism among these policy objectives. Key findings are: (1) infrastructure policies prevail across all regions; (2) regulation policies exhibit a comparative advantage in the BTH region, while implementation policies dominate in the GGF region and promotion policies in the YRD region; (3) cooperation among objectives is primarily observed in the BTH region, whereas competition plays a more dominant role in the other regions. This study fills a previous research gap and provides insights for researchers and policymakers, highlighting the development of customized strategies that consider the unique characteristics and requirements of each region.

Towards hydrosocial autonomy within modernity. A long-term analysis (1850–1980) of socio-material fracturing of flood protection infrastructures in an Alpine valley

This paper retraces the history of flood risk infrastructure projects (1850–1980) in the Grésivaudan Valley, located immediately upstream of Grenoble (France). It analyses the persistent gap between the modernist paradigm embedded in flood protection projects and the concrete hydraulic infrastructure built along the river and at confluences, questioning their unexpected effects. In this article, we demonstrate that in spite of their apparent fixity, flood protection infrastructures are constantly reshaped within hydrosocial territories. To support this argument, we analyse socio-material fracturing arising from the implementation of flood infrastructure projects. Four autonomisation processes that produce these socio-material fractures are studied: a) a competition between imaginaries at stake; b) a situation of legal pluralism denied by the State; c) an agency of sediments; and d) a conflict between the everyday practices of beneficiaries and planned practices. By reconstructing these processes, we open the black box of the hydrosocial construction and materialisation of hydraulic infrastructure, and contribute to the development of the concept of socio-material fractures.

Critical infrastructure of Ukraine as a subject of scientific knowledge: theoretical aspect

The article is devoted to the study of theoretical aspects of critical infrastructure as a subject of scientific knowledge. The importance of critical infrastructure facilities for ensuring Ukraine’s national security, the stability of its economy and the state’s defense capability is determined. Legislative regulation in this area is analyzed, in particular, the Law of Ukraine «On Critical Infrastructure», «On National Security of Ukraine», the Criminal Procedure Code of Ukraine, the National Security Strategy of Ukraine, etc. normative legal acts that contain definitions of terms. Attention is drawn to the fact that the violation of the functioning of the specified objects in the conditions of martial law may cause socially dangerous consequences for society and the state. According to the result of the comparison with foreign experience (USA, EU, Great Britain, China, Japan), it is proved that Ukraine takes into account international approaches to the protection of critical infrastructure, but has its own unique features caused by national threats and challenges. In the US, for example, critical infrastructure is defined as systems and assets so important that their failure to function or damage would have a devastating impact on security, the national economy, and public health. The European Union approaches this issue through the European Critical Infrastructures Directive, focusing on interconnection and coordination between member states. The UK takes care of cyber security, while China and Japan emphasize national control and resilience of facilities. Based on the analysis, recommendations were made for improving the legislative policy of Ukraine in the field of critical infrastructure. A conclusion was made about the relevance of the task of the Security Service of Ukraine to combat criminal offenses at critical infrastructure facilities, and practical recommendations for further improvement of this area were provided. It has been determined that the perspective areas of scientific research are the analysis of the experience of the countries of the European Union in terms of legal protection against criminal offenses at critical infrastructure facilities.

REAL-TIME GIS FOR MONITORING AND SECURITY

Applications of geographic information systems in the security domain are diverse and cover various aspects such as crisis prevention and management, public safety, national security, critical infrastructure protection and military applications. Real-time GIS is essential for effective emergency response and management because it provides accurate information on the location and dynamics of events.

Planning and Construction Strategies for Infrastructure in Traditional Villages of the Grand Canal from the Perspective of Villager Needs

The traditional villages along the Jiangsu section of the Grand Canal are facing the threat of decline and disappearance due to the decline of the canal transportation function and the advancement of urbanization, and it is urgent to study the protection and renewal of these villages. Based on the needs of villagers, this study aims to explore the planning and construction strategies of traditional village infrastructure in the Jiangsu section of the Grand Canal. Through a literature review, field investigation, and qualitative and quantitative analysis methods, this paper conducts in-depth research and data analysis on the status quo of six types of infrastructure in 29 traditional villages, including road traffic, water supply and drainage, garbage sanitation, energy utilization, postal communication, and ecological disaster prevention. The research results show that, although the infrastructure construction has made some progress, there are still problems such as unreasonable planning, low construction quality, and the lack of cultural characteristics, which cannot fully meet the actual needs of villagers. Through a regional comparative analysis, it is found that the infrastructure condition of the Jiangnan Canal section is better than that of the Huaiyang Canal section and Middle Canal section, but they all face challenges of protection and renewal. Based on the needs of villagers, this study puts forward corresponding protection and optimization strategies, which provide theoretical guidance and practical methods for the sustainable development of traditional village infrastructure, and it has important reference significance for the infrastructure protection and development of traditional villages in other regions.

Importance of Cybersecurity/The Relevance of Cybersecurity to Diabetes Devices: An Update from Diabetes Technology Society.

As medical devices become more integrated with wireless technologies, the risks of cyberattacks and data breaches increase, making stringent cybersecurity measures essential. The implementation of rigorous cybersecurity standards is essential for enhancing the cybersecurity of devices. This article examines the evolving cyber threats faced by the medical technology industry, the role of IEEE 2621 in providing comprehensive security benchmarks for medical devices, and the need for continuous risk assessments and adherence to regulatory standards to mitigate future cyber risks. Adherence to cybersecurity standards establishes ensures the effective protection of sensitive data and critical infrastructure.

Multi-Step Ahead Water Level Forecasting Using Deep Neural Networks

Stream gauge height (water level) is a significant indicator for forecasting future floods. Flooding occurs when the water level exceeds the flood stage. Predicting imminent floods can save lives, protect infrastructure, and improve road traffic management and transportation. Deep neural networks have been increasingly used in this domain due to their predictive capabilities in capturing complex features and interdependencies. This study employs four distinct models—Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), transformer, and LSTNet—with MLP serving as the baseline model to forecast water levels. The models are trained using data from 20 distinct river gages across the state of Missouri to ensure consistent performance. Random search optimization is employed for hyperparameter tuning. The prediction intervals are set at 4, 6, 8, and 10 (each interval equivalent to 30 min) to ensure that performance results are robust and not due to random weight initialization or suboptimal hyperparameters and are consistent throughout different prediction intervals. The findings of this study indicate that the LSTNet model leads to a better performance than the other models, with a median RMSE of 0.00724, 0.00959, 0.01204, and 0.01230 for the 4, 6, 8, and 10 intervals, respectively. As climate change leads to localized storms driven by atmospheric shifts, water level fluctuations are becoming increasingly extreme, further exacerbating data drift in real-world datasets. The LSTNet model demonstrates superior performance in terms of RMSE, MAE, and the correlation coefficient across all prediction intervals when forecasting water levels under data drift conditions.

Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations

Extreme rainfall events trigger natural hazards, including floods and debris flows, posing serious threats to society and the economy. Accurately quantifying extreme rainfall return levels in ungauged locations is crucial for improving flood protection infrastructure and mitigating water-related risks. This paper quantifies the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. We assess the performance of CPM-informed estimates of extreme return level against a traditional interpolation techniques. We find that kriging methods with external drift outperform inverse distance weighting for both traditional and CPM-informed approaches. We then assess the effectiveness of the two methods under different scenarios of station density. At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 h. The performance becomes comparable between 6 and 24 h. For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, with average reductions in fractional standard error of 24 %, 13 %, and 8 % for return periods of 2, 10 and 50 years, respectively for a rain gauge density of 1/800 km², and 16 %, 8 %, and 3 % for density of 1/400 km². Information from CPM simulations can thus be useful for estimating sub-daily extreme rainfall events in ungauged sites, particularly in data-scarce areas in which the density of rain gauges is low.

Artificial Intelligence and the Development of “Specialized, Refined, Unique, and Innovative” Small‐ and Medium‐Sized Enterprises

ABSTRACT“Specialized, Refined, Unique, and Innovative” (SRUI) enterprises are a crucial part of the national innovation system and play a significant role in enhancing national core competitiveness by leveraging strengths and addressing weaknesses. Given the limited quantitative analysis on the productivity of SRUI enterprises in the academic field, this paper constructs an enterprise‐level artificial intelligence index based on text analysis and machine learning. Using panel data from 2018 to 2022, we investigate the impact of artificial intelligence on the productivity of SRUI small‐ and medium‐sized enterprises (SMEs). The research findings indicate that (1) artificial intelligence significantly enhances the productivity of SRUI SMEs, and for each one standard deviation increase in artificial intelligence, the productivity level of SRUI enterprises will increase by 6.82%. (2) Mechanism tests reveal that artificial intelligence improves productivity by optimizing labor structure, improving labor resource allocation, stimulating endogenous motivation and innovation vitality within enterprises, and enhancing management level and investment efficiency. (3) Heterogeneity analysis indicates that at the regional level, artificial intelligence significantly boosts the productivity of enterprises with well‐developed network infrastructure and robust intellectual property protection systems. At the industry level, AI has a more pronounced effect on the productivity of technology‐intensive and competitive industries. Additionally, we also find that the impact of AI on productivity is more significant in enterprises with younger executive teams and executives with digital and intelligent education backgrounds. This study expands the research scope of productivity and provides valuable insights for the government to optimize digital economy policies and for enterprises to formulate digital innovation strategies.

Transnational corporate counterinsurgency in the Colombian conflict and its legacies today

ABSTRACT This study challenges common-sense thinking on internal violent conflicts in two ways: that they are merely domestic, with limited influence from external actors; and that doing business in conflict-ridden places is detrimental to profits. Drawing on empirical research and theoretical lenses from critical security studies and the political ecology of counterinsurgency, the paper explores the transnational dimensions of Colombia’s violent conflict in relation to the extractive sector. Conceptualising two overall generations of counterinsurgency, the article shows how, during the conflict, several transnational corporations, especially those in the extractive and agro-industrial sector, not only established themselves in Colombia and expanded, they also developed their corporate security schemes. Given that energy projects were strategic targets in the guerrilla war, the protection of corporate infrastructure by the state was justified. The paper argues that the internal conflict not only facilitated corporate extractivism, it also provided innovative ways of ensuring corporate security. This ‘social warfare’ approach includes strategic efforts to win hearts and minds, which continue to be pursued today through practices known as ‘corporate social responsibility’ (CSR). The paper relates this to the current challenges to hold economic actors accountable in transitional justice.

Violations Committed by Israel in Armed Conflicts Under International Humanitarian Law

Introductioan: War has various aims and objectives, including under the pretext of self-defense to defend life, family, honor or to defend one's nation, to ideological issues. The wars that occur also often violate international humanitarian law. One of them is between Israel and Hamas.Purposes of the Research: To find out violations of international humanitarian law committed by IsraelMethods of the Research: This research uses an normative juridical research method. Normative Juridical Research is research on Norms, Principles, Rules and Principles based on statutory regulations related to the problem being studied. The approaches used are the statutory approach, the conceptual approach, and case aprroach.Results of the Research: The results of the research show that according to international humanitarian law, violations committed by Israel in armed conflict involve actions that violate the principles of protection of civilians and civilian infrastructure. Humanitarian law, as set out in the Geneva Conventions, prohibits attacks on non-combatants and requires protection of vital facilities such as hospitals and schools, as well as access to humanitarian aid.

A IMPORTÂNCIA DO ATERRAMENTO ELÉTRICO NA SEGURANÇA E EFICIÊNCIA DE SISTEMAS ELÉTRICOS

The following work will propose the electrical grounding, the voltage and the way in which electrical grounding is used and its proper installation tends to promote an impact on user safety, minimizing accidents, as most users do not know what the system is or even what the Fundamentals are for, the general objective of this article is to understand electrical grounding and how its performance contributes to user safety and as a secondary objective: Importance of grounding, types of grounding, materials and devices, basic principles and technical standards. The methodology used was bibliographic research, using sources such as books, magazines, theses, and publications on the internet, allowing the researcher to access existing material on the subject, being of the qualitative type. The results and discussion demonstrate the importance of electrical grounding for the safety and protection of electrical infrastructure, thus providing important details that can improve system efficiency and maintain safety, as well as regulatory standards. The conclusion is that electrical grounding plays a crucial and important role in safety and protection, so it is better to use the TN-S grounding system because the protective conductor will always be at zero potential.

Methodological Approach for the Development of Standard C-UAS Scenarios

The integration of unmanned aircraft systems (UAS), commonly referred to as drones, into various sectors including agriculture, healthcare, and military operations has transformed industries and services. While drones offer numerous benefits, they have also been exploited by terrorists and criminals for illicit activities, such as smuggling and surveillance. Incidents involving drones flying over restricted airspaces or sensitive locations have highlighted the vulnerabilities of critical infrastructure and limitations of current law enforcement capabilities. To address these challenges, there is a growing need for effective counter-UAS (C-UAS) systems including detection, tracking, and identification technologies. However, evaluating the capabilities of these systems poses a significant challenge, leading to the demand for standardized test methodologies. The COURAGEOUS project seeks to fill this gap by developing standardized scenarios covering various use cases, such as airport security, critical infrastructure protection, and border security. These scenarios are informed by a systematic approach involving a literature review, analysis of previous incidents, assessment of current C-UAS frameworks, and gathering feedback from end users. The resulting standardized test methodology aims to enhance the understanding of C-UAS system capabilities, improve preparedness against evolving threats, and facilitate the global dissemination of project results. Through validation trials and feedback from law enforcement agencies, the COURAGEOUS project strives to contribute to a broader network of counter-UAS initiatives, ultimately enhancing the lower airspace security.

Identification and assessment of the mudflat ecological vulnerability dominated by coastline evolution in Jiangsu

Coastlines have experienced profound alterations due to human disturbances and ocean dynamics against the backdrop of climate change and intensified anthropogenic activities. Significant modifications have occurred within the muddy coastal ecosystem, rendering it extremely susceptible to heightened levels of vulnerability. However, existing studies on coastal eco-environmental vulnerability have often overlooked crucial factors such as coastline erosion and siltation, particularly concerning coastline change. In this study, we assess coastline stability utilizing Landsat remote sensing imagery to investigate the vulnerability of coastal ecology alongside 24 economic and natural parameters, serving as indices for the Coastal Vulnerability Index (CVI) of the coastal eco-environment. Subsequently, we analyze the impact factors to vulnerability and predict trends in coastline change over the next 20 years to propose recommendations for sustainable development to safeguard the coastal eco-environment. Our findings reveal a trend towards coastline stabilization in Jiangsu, with significantly higher stability observed during 2010–2020 compared to 1985–2010. The overall CVI along the Jiangsu coast shows an downward trajectory over the past 15 years, primarily influenced by tidal action and coastal topography and geomorphology. Predictive modeling suggests Jiangsu coastline is bounded by the Sheyang estuary, with the coastline to the north dominated by stabilization and to the south dominated by siltation. Climate change, coupled with intensified human activities and future coastline alterations, may exacerbate vulnerability. Effective protection strategies for coastal ecosystems necessitate a comprehensive understanding of local natural conditions, resource availability, and socioeconomic dynamics. Governmental interventions should focus on reinforcing regulatory frameworks for coastal organism management, implementing coastal protection infrastructure, and enhancing supervision and management protocols for beachfront development, thereby fostering the sustainable management of muddy coastlines.

Resilient Coastal Protection Infrastructures: Probabilistic Sensitivity Analysis of Wave Overtopping Using Gaussian Process Surrogate Models

This paper presents a novel mathematical framework for assessing and predicting the resilience of critical coastal infrastructures against wave overtopping hazards and extreme climatic events. A probabilistic sensitivity analysis model is developed to evaluate the relative influence of hydrodynamic, geomorphological, and structural factors contributing to wave overtopping dynamics. Additionally, a stochastic Gaussian process (GP) model is introduced to predict the mean overtopping discharge from coastal defences. Both the sensitivity analysis and the predictive models are validated using a large homogeneous dataset comprising 163 laboratory and field-scale tests. Statistical evaluations demonstrate the superior performance of the GPs in identifying key parameters driving wave overtopping and predicting mean discharge rates, outperforming existing regression-based formulae. The proposed model offers a robust predictive tool for assessing the performance of critical coastal protection infrastructures under various climate scenarios.

Analysis of Spatiotemporal Evolution of Coordinated Development Between Transportation Infrastructure and Ecological Environment in the Yangtze River Economic Belt

The coupling and coordinated development of transportation infrastructure and ecological environment is an important way to achieve win-win economic, social, and ecological benefits. This study analyzes the coupling and coordinated development between transportation infrastructure and ecological environment in the Yangtze River Economic Belt. Based on panel data from 11 provinces in the Yangtze River Economic Belt from 2007 to 2022, establish their respective indicator systems and use entropy method to measure the comprehensive level of the two. Through the perspective of spatiotemporal differentiation, this study analyzes the changes in the coupling and coordinated development level of transportation infrastructure and ecological environment in 11 provinces. It is found that the overall coupling and coordinated development level of each province has significantly improved, but there are obvious regional differences. In the future, each province should formulate more precise and effective policy measures based on its own actual situation, strengthen regional cooperation and communication, and jointly promote the coupling and coordinated development of transportation infrastructure and ecological environment protection in the Yangtze River Economic Belt.