Security System Research Articles

Labor market dynamics in developing countries: analysis of employment transformation at the macro-level

Understanding labor market dynamics remains a pivotal aspect within contemporary economic discourse, as necessitates the pursuit of effective employment models to ensure steady progress in the conditions of changes in the economic structure. The aim of the research is to examine the dynamics of the labor market in developing countries, with particular emphasis on China and Kazakhstan, taking into account economic, social, and technological trends. The methodology includes the analytic and comparison of trends in the labor market in developing countries, such as China and Kazakhstan over the past 20 years, and also monitoring the socio-economic nature of the labor process. The study identified changes in the labor market and provided empirical evidence for new forms of employment, utilizing comparative analysis and data visualization of the sectoral structure of the economy and global labor market trends up to 2027. The obtained results provide three main conclusions: a decrease in demand for low-skilled workers and an increase in demand for highly qualified individuals; the emergence of jobs with low levels of social protection; new forms of employment-oriented towards workers outside the social security system, domestic workers, and self-employed individuals. These types of employment can fill jobs in platform and piecework economies, cooperativism, and the sharing economy, which allows employers in developing markets to optimize employment. The findings of the study can contribute to understanding the functioning of the labor market in developing countries including the development of small and medium-sized businesses, startups, and innovative projects, and may be applicable in the development of economic and social policies for sustainable economic growth and social stability.

Who (actually) gets the farm? Intergenerational farm succession in the United States

AbstractFarm succession is a central issue in agricultural policy. Yet although many studies explore succession planning, little is known about how farms are actually transferred. We provide the first population‐level evidence on intergenerational farm succession by linking US census records for millions of farmers' children in 1900 and 1910 to identify which children own and operate the family farm up to 40 years later. We first show that daughters are rarely successors. Using a within‐family identification strategy, we find that first‐born sons are slightly more likely than their younger brothers to be successors while their parents are working aged. However, birth order is not predictive of who receives the farm when parents are older or deceased. For later farm transfers, sons who were previously tenant farmers are much more likely than their brothers to be successors, possibly because they are better prepared. Fewer than one‐fifth of farmers transfer their farm to any son. Our study relies on rich historical data because current policy prevents the necessary data linkages for studying intergenerational farm succession. Providing a secure system for researchers to link modern agricultural data to population microdata, similar to what has been achieved with other data sources, would yield crucial insights into long‐term agricultural policy issues in the US.

Caged AIEgens: Multicolor and White Emission Triggered by Mechanical Activation.

Aggregation-induced emission luminogens (AIEgens) that respond to mechanical force are increasingly used as force probes, memory devices, and advanced security systems. Most of the known mechanisms to modulate mechanoresponsive AIEgens have been based on changes in aggregation states, involving only physical alterations. Instances that employ covalent bond cleavage are still rare. We have developed a novel mechanochemical uncaging strategy to unveil AIEgens with diverse emission characteristics using engineered norborn-2-en-7-one (NEO) mechanophores. These NEO mechanophores were covalently integrated into polymer molecules and activated in both the solution and solid states. This activation resulted in highly tunable fluorescence upon immobilization through solidification or aggregation, producing blue, green, yellow, and orange-red emissions. By designing the caged and uncaged forms as donor-acceptor pairs for Förster resonance energy transfer (FRET), we achieved multicolor mechanofluorescence, effectively broadening the color spectrum to include white emission. Additionally, we computationally explored the electronic structures of activated NEOs, providing insights into the observed regiochemical effects of the substituents. This understanding, together with the novel luminogenic characteristics of the caged and activated species, provides a highly tunable reporter that traces progress with continuous color evolution. This advancement paves the way for future applications of mechanoresponsive materials in areas like damage detection and bioimaging.

The Institution of the Right to State Self-defence in the State Security System

The Institution of the Right to State Self-defence in the State Security System

Applications of blockchain technology in peer-to-peer energy markets and green hydrogen supply chains: a topical review

Countries all over the world are shifting from conventional and fossil fuel-based energy systems to more sustainable energy systems (renewable energy-based systems). To effectively integrate renewable sources of energy, multi-directional power flow and control are required, and to facilitate this multi-directional power flow, peer-to-peer (P2P) trading is employed. For a safe, secure, and reliable P2P trading system, a secure communication gateway and a cryptographically secure data storage mechanism are required. This paper explores the uses of blockchain (BC) in renewable energy (RE) integration into the grid. We shed light on four primary areas: P2P energy trading, the green hydrogen supply chain, demand response (DR) programmes, and the tracking of RE certificates (RECs). In addition, we investigate how BC can address the existing challenges in these domains and overcome these hurdles to realise a decentralised energy ecosystem. The main purpose of this paper is to provide an understanding of how BC technology can act as a catalyst for a multi-directional energy flow, ultimately revolutionising the way energy is generated, managed, and consumed.

PROTECTION OF ATMOSPHERIC AIR AND AIRSPACE OF UKRAINE: LEGAL, REGULATORY, ENVIRONMENTAL AND ECONOMIC ASPECTS

The study uses general scientific and special methods, the main of which are: abstract-logical, deductive, inductive, historical, modelling and forecasting, methods of system-structural, system-functional analysis, economic and statistical (grouping, comparison, etc.). The use of system analysis methods made it possible to structure the constituent elements of the regulatory and legal support of public administration in the field of protection of atmospheric air and airspace of Ukraine. The purpose of the article is to characterise the protection of atmospheric air and airspace of Ukraine in the regulatory, legal, environmental and economic aspects. It is determined that the regulatory framework for regulating the principles of atmospheric air safety is a component of the mechanism for ensuring environmental safety. The article emphasises that for the first time the principles of environmental safety were enshrined in the Declaration of State Sovereignty of Ukraine, where the principles of environmental safety were established at the level of a separate section. It is emphasised that the functional content of the administrative and legal protection of atmospheric air includes: ensuring air pollution within the limits of the maximum permissible emission standards in order to ensure the right of a person to a safe and quality environment; greening of production; introduction of ecological fuel quality standards; greening of the energy cluster of the economy, including through the introduction of the principles of decentralisation of the country's energy system; establishment of information interaction between the participants of legal relations in order to ensure the transparency of economic activities related to environmental pollution; formation of a high level of environmental legal awareness, etc. The article draws a conclusion that ensuring proper quality of atmospheric air is a component of the mechanism for ensuring environmental safety. The authors underline that the understanding of the system of regulatory and legal regulation of atmospheric air and airspace protection should be functionally aimed at ensuring compliance with environmental standards for the operation of such facilities in accordance with economic feasibility and social justification. The paper concludes that atmospheric air safety and airspace safety are part of the national security system, where the former is a component of environmental safety and the latter is a component of state security, and should be understood as the state of atmospheric air and the integrity of the air environment, for which physical, chemical and biological properties are established which create favourable and sufficient conditions for the vital activity of people and settlements.

OPTIMIZED DEEP LEARNING FOR CYBER INTRUSION DETECTION AND SECURED COMMUNICATION IN MANET

The popularity of the Mobile Ad-Hoc Network increases with low expense solutions to the real time applications. The dynamic nature, limited centralized system with low bandwidth often susceptible to the security threads and became the hot topic. To protect the MANET system it is essential to implement a secured system. The purpose of this work is to design an intelligent Cyber Security System (CSS) by collecting the threads data from the MANET system. Initially, the data is pre-processed using the Min-Max normalization technique, followed by the feature selection with the newly approached Mother Optimization algorithm (MOA). The feature selection is effectuated for speedy classification of intrusions and prevent the attacks and therein significantly enhances the security. To provide the security to the MANET system the work proposes a novel Adaptive Deep Belief Network (ADBN). This classifies the attacks and normal data and prevents the system from falling for the threat. Simulation is performed in NS2 and analyzed the effectiveness of the proposed work with existing systems. Our proposed work effectively enhances the security of the MANET system and surpasses all the other works.

A Review on Molecular Mechanism of Plant Immunity against Fungal Pathogens

The molecular mechanisms of plant immunity, with a particular focus on how plants defend themselves against fungal pathogens. Plant immunity is a complex, multi-layered system involving pattern-triggered immunity (PTI) and effector-triggered immunity (ETI), which together form a robust defense against a wide array of pathogens. Advances in genomics and transcriptomics have significantly enhanced our understanding of these immune mechanisms by identifying key resistance (R) genes and uncovering the transcriptional networks that regulate immune responses. Proteomics and metabolomics further elucidate the functional aspects of immunity, revealing how proteins and metabolites are mobilized during pathogen attack. The advent of gene editing technologies, particularly CRISPR-Cas9, has opened new avenues for enhancing plant immunity by enabling precise modifications of genes associated with disease resistance. The ever-evolving nature of fungal pathogens, driven by genetic diversity and environmental changes, poses ongoing challenges. Emerging pathogens and the breakdown of existing resistance in crops underscore the need for durable resistance strategies, which can be achieved through the pyramiding of multiple R genes, susceptibility gene knockouts, and the harnessing of beneficial plant microbiomes. As climate change exacerbates the spread and virulence of fungal pathogens, developing climate-resilient crops that can withstand both abiotic stresses and pathogen pressures is becoming increasingly important. Future research should prioritize understanding the molecular dynamics of plant-pathogen interactions, leveraging new technologies for crop improvement, and fostering interdisciplinary collaboration to address these challenges. Ultimately, translating these scientific advances into practical applications will be crucial for ensuring global food security and sustainable agricultural systems in the face of mounting environmental and biological threats.

Evaluation of patients' perception of a blockchain system for prescription management

The management of medical prescriptions without computational system can result in errors and security issues. This study, conducted in Monclova, Coahuila, evaluates the perception and disposition of patients from public and private health services towards implementing a secure computational system to improve prescription and medical record management. A survey of 68 adults, using a mixed research methodology. The results indicate that a secure and low-cost computational system would have positive acceptance among the population, thereby validating the researcher's hypothesis. In conclusion, it was determined that a secure computational system is a feasible solution to improve the management of medical prescriptions, would be accepted by most of the patients, and could serve as a basis for future developments in other areas of the healthcare sector. The literature on blockchain in prescription management supports the system’s benefits. A 10% margin of error was used to maintain validity with a smaller sample size.

Twisted industrial structure, land financing mode and social security

This paper explains the disparities in the level of social security across different regions in China from the perspective of industrial structure distortions and discusses the moderating effect of land financing models. The results show that industrial structure distortions have a significant negative impact on social security expenditures; the lower the intensity of land investment, and the higher the intensity of land finance and land-based finance, the stronger the negative impact of industrial structure distortions on social security expenditures. The research conclusion of this paper has the reference significance for the government's sound and sustainable multi-level social security system.

Urban community security system model from the perspective of resilience: a study on Chinese cities

To enhance urban governance and bolster community disaster resilience, it is urgent to innovate and develop an urban community security system to cope with the complex and volatile social security situation. From the perspective of resilience, the concept, layout, and structure of the security system are organized. Considering the current situation and development trend of the social security system, and based on the constructed cost-capability model, the cost and benefit of the two modes are analyzed and compared. Subsequently, from the perspective of multi-agent participation, a game model between governments and enterprises is constructed. The evolutionary stability strategies of enterprises are analyzed, and simulation analysis is conducted on the factors influencing enterprises. Finally, to propose targeted improvement measures based on the community security capabilities of different communities, a grey fuzzy comprehensive evaluation method is employed. The community security comprehensive capabilities of the top 10 cities in China are quantitatively analyzed and evaluated. The results indicate that the urban community security system from a resilience perspective is more comprehensive compared to the traditional security system. Adopting mode 2 is relatively effective to improving government emergency management capability. In a certain range, reducing C, increasing F, reducing R2, and increasing h can achieve the effect of promoting enterprise to participate in construction. The urban community security capability is within the upper-medium level in general, close to the level of good. The urban community security system constructed in this paper can provide a theoretical basis for the government to formulate policies of the urban community security system and serve as a reference for strengthening the comprehensive capability of the urban community security.

Impacts of sampling on the artificial noise-assisted terahertz secure communication systems

In this paper, we investigate an artificial noise (AN)-assisted terahertz (THz) secure communication system. Different from previous studies, we consider a non-ideal analog-to-digital converter (ADC) in the AN-THz system. Specifically, both synchronization noise and quantization noise in ADC are investigated. The normalized distortion matric is employed to calculate synchronization noise power and the Bellman’s theory is introduced for quantization noise power. Under the constrain of limited ADC power, the secrecy performance presents a ‘U-shaped’ curve versus the sampling rate and therefore the optimal sampling rate is derived. Moreover, we validate our theoretical model in the experiment, and our experimental results in 102 GHz show the synchronization noise power varies with the square of timing error, and the quantization noise power is affected by the total data length, which agree well with the model predictions.

An intersectional feminist analysis of compulsory income management in Australia

Abstract Globally, women experience poverty at disproportionate rates to men, with the situation being worse for Indigenous women and women of colour. Social security systems are one avenue for income redistribution that can alleviate poverty. However, such systems are themselves embedded within and produced by unequal social relations, meaning they can also serve to perpetuate and exacerbate social inequalities. This is exemplified under neoliberal welfare reforms, which have disproportionate negative impacts for women across the world (e.g. increased poverty and stigma, reduced health/wellbeing, and more). Again, this is particularly the case for Indigenous women and women of colour. In this article, we offer an intersectional feminist analysis of an intensive form of neoliberal welfare conditionality, Australia’s ‘compulsory income management’ program (CIM). CIM quarantines social security incomes onto cashless bank cards to restrict expenditure to ‘approved’ items. Drawing on interviews and surveys with 170 individuals who have personally experienced CIM, we show that it has myriad negative impacts that are especially borne by (Indigenous) women. These are not, we argue, unintended policy impacts, but are instead symptomatic of the gendered and racialised violence that is woven into patriarchal capitalism more broadly. Thus, the experience of CIM holds lessons for welfare states internationally.

Artificial Intelligence in the U.S. Military Health System: Forging a New Frontier for Clinical Care and Efficiency

ABSTRACT The Military Health System (MHS) has historically been at the forefront of innovation in medicine and science, but it has also historically struggled to implement battlefield innovations or civilian technologies for wider domestic use. Artificial intelligence (AI) has emerged as a transformative force in health care with civilian health systems and institutions at the forefront of these innovations. While these tools have the potential to support resolution of military health’s most pressing issues, the MHS is behind its civilian counterparts in advancing AI. Adoption of AI could benefit the MHS in such areas as service member and beneficiary access to care; more precise allocation of medical personnel and resources; improved operations of military treatment facilities; early detection of emerging threats to health; and force multiplication of existing telehealth capabilities. This evolving and highly visible technology also presents challenges in the military context above those in the civilian context, such as additional levels of privacy and security, integration with purpose-built secure systems, and additional regulatory obligations. To address these, the MHS should engage in three lines of effort to advance AI: establishing governance, education and training of medical personnel, and engaging in research, development, testing, and piloting of AI applications. This will require dedicated personnel and resources for a substantial initial outlay to be recouped later through more effective administration and care. By leveraging lessons learned from civilian systems, the MHS can design, adopt, and implement AI solutions to improve care for service members in both domestic and operational contexts, and for their beneficiaries.

Security Challenges and Business Opportunities in the IoT Ecosystem

In the growing IoT environment, security seems to be a dominant topic, because of the broad extent of IoT devices functionalities is expressed in the different sectors. This article scrutinizes the elaborate IoT infrastructure, exposing the common flaws and traceable security incidents, which serve as a background in the appreciation of the need of having reliable security frameworks. At the same time, the research paper pinpoints the vast business prospects that will spawn from the issues, highlighting the fact that these can be tapped through the creation and provision of cutting-edge security systems and consultancy services. The study makes a prediction of the future of IoT based on its current rating and empirical evidence by reviewing literature to assess emerging technologies and market trends, which give way for future innovations in IoT security. In general, this paper proposes that interested actors who are proactive and afraid of the emerging security threats have an opportunity to tap into the growth and innovation in building strong IoT systems. Consequently, the insights offered in this paper are appropriate for both the industry stakeholders and the researchers.

Design and implementation of an intelligent building security system using Arduino GIGA R1 Wi-Fi

In the face of evolving security challenges, the integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has become essential for modern building security systems. This paper explores the design and implementation of an intelligent building security system utilizing the Arduino GIGA R1 Wi-Fi, OV7670 camera, and Giga Display Shield, enhanced by Convolutional Neural Networks (CNNs). The system is designed to detect and respond to security threats in real-time, offering a proactive approach to building security. Leveraging the processing power of the Arduino platform and the image recognition capabilities of CNNs, the proposed system distinguishes between authorized and unauthorized access with a demonstrated accuracy of 92%. The study also identifies challenges, including performance in low-light conditions and communication delays, which affect the system's efficiency. Future work will focus on overcoming these limitations and further enhancing the system's functionality. The results indicate that the proposed solution is a promising step toward more intelligent and responsive building security systems, providing a foundation for further innovation in the field.

Rural Banditry and Economic Crimes: Exploring the Perceptions of Male Pastoralists’ Lived Experience in Kwara State, North-Central Nigeria

Armed banditry and insurgency are among the principal insecurity challenges in present-day Nigeria. This study investigated the lived experience of male pastoralists on rural banditry and associated economic crimes in Kwara State, north-central Nigeria to fill identified gaps in the literature. A sample of 20 pastoralists’ hamlets was selected for the study. Data were collected through focus group discussions and key informant interviews. Qualitative content analysis was used to analyse the data. Data analysis showed that study participants were aware of the problem of rural banditry. Major banditry-related economic crimes reported by participants were robbery and burglary, livestock rustling, farmers-herders conflicts with attendant destruction of pastoralists’ assets, among others. Through facilitation by pairwise ranking exercise within focus group sessions, study participants identified livestock rustling as the most important banditry-related economic crime. Participants carried out social profiling of livestock rustlers. Results further suggested that the key factors influencing livestock rustling were economic deprivations and social dislocation in Nigerian society, criminal networks on livestock rustling and illegal trading on rustled livestock, and access to light weapons by the livestock rustlers, among others. Participants reported the immediate and long-term effects of livestock rustling on the crime victims and their communities. The study recommends the rollout of the government-planned National Animal Identification and Traceability System, the enactment of state law that would prohibit indiscriminate livestock transportation and, the creation of a local security system to complement the state-based policing system to reduce armed banditry and livestock rustling among the study population.

Integrating digitization into public administration: Impact on national security and the economy through spatial planning

The evolutionary development of the security sphere, on the one hand, and the rapid involvement of digital technologies (and, as a consequence, changes) on the other, formulate the first level of problematization of this study. The study seeks to provide evidence of how the dynamics of changes in the security sphere are formed by constructing an empirical model of changes and assessing the state security system within the framework of spatial planning under the influence of digital technologies. Particular attention in the study is paid to spatial planning and spatial development in smart cities the main threats to national security are systematized, located in closely intersecting planes of digital technologies, social processes, and economic interests. It is shown that areas covered by spatial planning, and particularly smart cities, pose a serious local threat to national and international security policy at the levels of political, social, technical, and economic governance.

Accounting, Analytical and Information Support for Law Enforcement Activity in Conditions of Ensuring Economic Security in Public Administration

Objective: The objective of this study is to develop an effective model of accounting, analytical, and information support for law enforcement activities in ensuring economic security amidst strong turbulence in the external environment. Theoretical Framework: This research is anchored in the principles of economic security and law enforcement support systems. It utilizes the IDEF0 model as the primary theoretical framework to analyze and structure the accounting, analytical, and informational processes that underpin effective law enforcement in volatile conditions. Method: The research methodology employs the IDEF0 model to construct a comprehensive framework for the accounting, analytical, and information support systems specific to law enforcement activities. Results and Discussion: he study successfully resulted in a detailed decomposition of the IDEF0 model, highlighting innovative ways to bolster the accounting, analytical, and information support for law enforcement. These results are contextualized within the broader framework of maintaining economic security in turbulent environments, underscoring the adaptability and robustness of the proposed model. Research Implications: The practical and theoretical implications of this research are significant for policymakers and law enforcement agencies. The model provides a strategic foundation for enhancing economic security frameworks, which is crucial for adapting to and thriving in dynamic external conditions. Originality/Value: This study contributes original insights into the application of the IDEF0 model in a law enforcement context, particularly in scenarios characterized by significant economic turbulence.

Impact of informal employment on individuals’ psychological well-being: microevidence from China

ObjectiveThe number of workers engaged in informal employment in China has reached 200 million individuals, constituting a substantial contribution to the pursuit of high-quality development and the attainment of stable employment objectives. Nevertheless, the psychological well-being of informal workers cannot be overlooked. Therefore, this study aims to investigate the impact of informal employment on individuals’ psychological well-being.MethodsDrawing on data from the 2020 China Family Panel Studies (CFPS) survey, this work employs ordinary least squares (OLS) models and instrumental variable analysis to empirically examine the impact of informal employment on the psychological well-being. Furthermore, different tests were utilised to analyse the mediating pathway through which informal employment affects the psychological well-being.ResultsInformal employment exhibits a significant negative impact on the psychological well-being, particularly among samples characterised by low educational levels, limited financial resources, and non-agricultural household registration. The exploration of the underlying mechanisms indicates that informal employment negatively affects the psychological well-being of workers through pathways that include reduced access to health entitlements, increased working hours, and decreased job satisfaction, particularly with the work environment.ConclusionA recommendation is proposed; namely, to further establish a social security system that caters to the needs of the informal employment population and supports and regulates the development of flexible employment forms, with the aim of protecting and enhancing the psychological well-being of the informal employment population.