Difficulties In Implementation Research Articles

FUNDAMENTAL PROBLEMS OF POPULATION INCOME DISTRIBUTION AND STATE REGULATION INSTRUMENTS

In the modern world, attempts are continuously being made to comprehensively assess and measure indicators related to the progress of the standard of living and well-being both globally and for individual groups of the population. Assessing and measuring the social condition is a complex process, because the concepts of "living standard of the population" and "quality of life" are multi-vector and difficult to calculate and evaluate. The assessment and measurement of the social progress of each state, individual social groups and territories (states, regions, etc.) with sufficient accuracy is an important factor in determining the indicators of population inequality. It should be the basis for implementing effective social policy through the principles and approaches of the state's social policy, individual groups of the population (especially socially vulnerable), effective management of the population's incomes and expenses. The basis for the formation of such a policy is the identification of social problems and the identification of ways to solve them. Socially oriented programs can be implemented both in the short term and in the long term. The formation of problems of population income distribution and state regulation and the search for tools to achieve it should become one of the key components of the policy implemented by the state. Taking into account the difficulties of social policy implementation and the use of appropriate tools during the development of that policy, the identification and characterization of the general trends in the formation and distribution of incomes of the population becomes a topical issue. As a first step, it is necessary to study the experience of countries with advanced free market relations and analyze the possibilities of their localization in Armenia for the selection and expansion of social policy tools. It is also necessary to evaluate the effectiveness of the tools used to fight against poverty and the implemented policies, comparing the relevant indicators of Armenia and neighboring countries.

Indikative Präventionsprogramme zur Förderung der seelischen Gesundheit im Vor- und Grundschulalter: Teilnahmebereitschaft von Kinderärzt*innen und Familien an einer innovativen Versorgungskette

ZusammenfassungHintergrundPsychische Auffälligkeiten beginnen häufig im Kindesalter und können in psychische Störungen münden. Vorhandene Präventionsangebote werden trotz Wirksamkeit nur spärlich in Anspruch genommen. Ziel war zu prüfen, inwiefern durch die Etablierung einer Versorgungskette Risikokinder frühzeitig identifiziert und Präventionsmaßnahmen zugewiesen werden können, sowie inwieweit indikative Präventionsprogramme schlussendlich in Anspruch genommen werden.MethodenIn einer prospektiven Implementationsstudie wurde während der regulären U9- bis U11-Gesundheitsuntersuchungen (Altersbereich: 5–10 Jahre) der „Strengths and Difficulties Questionnaire“ als Screeninginstrument an Familien ausgegeben. Diese erhielten von ihren Kinderärzt*innen unmittelbar eine Ergebnisrückmeldung und im Falle von grenzwertig auffälligen emotionalen oder Verhaltensproblemen eine Empfehlung für ein indikatives Präventionsprogramm. Vor Programmteilnahme fand im Vorgespräch eine Indikationsprüfung statt.ErgebnisseIm Raum Dresden beteiligten sich n = 46 (38,7 %) Kinderärzt*innen am Projekt. In n = 28 Kinderarztpraxen nahmen n = 3231 (86,4 %) Familien am Screening teil, n = 864 (26,7 %) Kinder, deren Familien eine Ergebnisrückmeldung erhielten, bekamen eine Präventionsempfehlung. Zur Präventionsprogrammteilnahme meldeten sich n = 118/864 (13,7 %) Familien selbstständig. n = 215/624 (35,5 %) zeigten Interesse nach projektinitiierter Kontaktaufnahme. Über andere Zugangswege kamen n = 139 Teilnahmeanfragen. n = 337 (n = 461; über alle Zugangswege) Vorgespräche wurden geführt. Schließlich nahmen n = 237 (n = 337) Kinder ein indikatives Präventionsprogramm in Anspruch.SchlussfolgerungEine Ausweitung der Vorsorgeuntersuchung auf psychische Auffälligkeiten ist umsetzbar, nützlich und erfährt breite Akzeptanz. Um eine Versorgungskette einzurichten, sollte eine Angebotsstruktur etabliert werden, um damit die Zuweisung zu und Inanspruchnahme von Präventionsmaßnahmen zu ermöglichen.

Survey on the application of external cardiopulmonary resuscitation in Chinese children with sudden cardiac arrest

Objectives: To investigate the current application status and implementation difficulties of extracorporeal cardiopulmonary resuscitation (ECPR) in children with sudden cardiac arrest. Methods: This cross-sectional survey was conducted in 35 hospitals. A Children's ECPR Information Questionnaire on the implementation status of ECPR technology (abbreviated as the questionnaire) was designed, to collect the data of 385 children treated with ECPR in the 35 hospitals. The survey extracted the information about development of ECPR, the maintenance of extracorporeal membrane oxygenation (ECMO) machine, the indication of ECPR, and the difficulties of implementation in China. These ECPR patients were grouped based on their age, the hospital location and level, to compare the survival rates after weaning and discharge. The statistical analysis used Chi-square test and one-way analysis of variance for the comparison between the groups, LSD method for post hoc testing, and Bonferroni method for pairwise comparison. Results: Of the 385 ECPR cases, 224 were males and 161 females. There were 185 (48.1%) survival cases after weaning and 157 (40.8%) after discharge. There were 324 children (84.2%) receiving ECPR for cardiac disease and 27 children (7.0%) for respiratory failure. The primary cause of death in ECPR patients was circulatory failure (82 cases, 35.9%), followed by brain failure (80 cases, 35.0%). The most common place of ECPR was intensive care unit (ICU) (278 cases, 72.2%); ECPR catheters were mostly inserted through incision (327 cases, 84.9%). There were 32 hospitals (91.4%) had established ECMO emergency teams, holding 125 ECMO machines in total. ECMO machines mainly located in ICU (89 pieces, 71.2%), and the majority of hospitals (32 units, 91.4%) did not have pre-charged loops. There were no statistically significant differences in the post-withdrawal and post-discharge survival rates of ECPR patients among different age groups, regions, and hospitals (all P>0.05). The top 5 difficulties in implementing ECPR in non-ICU environments were lack of ECMO machines (16 times), difficulty in placing CPR pipes (15 times), long time intervals between CPR and ECMO transfer (13 times), lack of conventional backup ECMO loops (10 times), and inability of ECMO emergency teams to quickly arrive at the site (5 times). Conclusion: ECPR has been gradually developed in the field of pediatric critical care in China, and needs to be further standardized. ECPR in non-ICU environment remains a challenge.

Instructional design of smart technology use in teacher digital educational environment

Introduction. According to the provisions mentioned in Digital Kazakhstan Programme and Digital Teacher national project, the teacher today is regarded not just as an active user of the novel digital and smart technologies, but as the creator and transmitter of the authors’ digital educational content. The modern teacher is supposed both to adapt to and perform the professional activity within the digital setting of the educational institution and be able to design his/her own digital educational environment to transfer the educational content and organise effective “educator-learner” educational interaction. This situation brings us to the issue of the necessity for the teacher to be aware and master the potential possibilities provided by the smart technologies in realisation of the educational activity in terms of online and mixed learning; this, in its turn, conditions the search for the solutions for the effective instructional design of smart technology application in a teacher digital educational environment.Aim. The present study aims to substantiate the instructional design of the implementation model of smart technologies when designing teacher personal digital educational environment (on the example of the authors’ Smart Assistant software as a means of optimising teacher activities and organising an online and mixed educational process).Methodology and research methods. The following categories of research methods were used to reach the goal set: 1) theoretical: cybernetics method, generalisation, analogy, abstraction, visualisation, modelling, and classification; 2) empirical: surveys and interviews techniques, as well as mathematical and statistical data analysis approaches.During the experimental part of the study an online questionnaire survey on “Implementation of smart technologies in designing a teacher personal digital educational environment in the conditions of distance learning at a university” was conducted among 201 teachers of Karaganda Buketov University (Republic of Kazakhstan) and Dokuz Eylul University (Turkey) from 12 December 2022 to 30 April 2023. The aim of the experiment was to identify problems with the adaptation and implementation of smart technologies in designing a digital educational environment. For this purpose, the respondents answered fifteen questions and made suggestions for improving the university digital educational environment.Results and scientific novelty. The article substantiates the design of smart technology implementation in a teacher digital educational environment as a means of optimising his/her activity in organising online and mixed learning process (on the example of the authors’ software Smart Assistant), and identifies the problems with the adaptation and implementation of professional activities in the context of a digital educational environment. The characteristic features of the problems of teachers’ adaptation in a digital educational environment and the difficulties of smart technologies implementation in their professional activity are defined.Practical significance. The Smart Assistant software product was developed as a means of optimising the teacher’s activities in organising an online and mixed educational process.

Application of Lean Manufacturing Principles in Increasing Factory Productivity

This study looks into how a manufacturing company in Indonesia might increase factory productivity by implementing Lean Manufacturing concepts. Employing a mixed-methods approach that blends quantitative surveys and qualitative interviews, the study investigates employee awareness, adoption, and perceptions of the effects of Lean techniques. The quantitative findings show that there is a significant increase in productivity, a high degree of awareness, and partial implementation. Additional correlation analysis demonstrates a strong positive association between increases in important production metrics and the degree of Lean implementation. Qualitative results emphasize the value of cultural adaptation, implementation difficulties, and successful communication outcomes. A comprehensive conversation highlights the relationship between high awareness and implementation status, highlighting the necessity of focused training and change management. The study ends with practical suggestions for maximizing Lean tactics within businesses, emphasizing the need of cultural adaptability and viewing obstacles as chances for growth.

Transforming Organizational Development with AI: Navigating Change and Innovation for Success

Effective change management emerges as a deciding element for an organization's survival and success in the changing terrain of today's fiercely competitive business climate. The variety of change management theories and approaches that are currently available, however, paints a complicated picture that is plagued by inconsistencies, a lack of strong empirical support, and unproven assumptions about contemporary organizational dynamics. This essay seeks to set the basis for a fresh paradigm for effective change administration by critically analyzing popular change management ideas. The gap between theory and practice is addressed in the paper, which concludes with suggestions for more research. In parallel, artificial intelligence (AI) has made incredible progress, giving rise to computers that mimic human autonomy and cognition. Industry-wide excitement has been sparked by the enthusiasm among academics, executives, and the general public, which has resulted in significant investments in utilizing AI's potential through creative business models. However, the lack of thorough academic guidance forces managers to struggle with AI integration issues, increasing the risk of project failure. An in-depth analysis of AI's complexities and its function as a spark for revolutionary business model innovation is provided in this article. A thorough literature assessment, which involves sifting through a sizable library of published works, combines up-to-date information on how AI is affecting the development of new business models. The findings come together to form a roadmap for seamless AI integration that includes four steps: understanding the fundamentals of AI and the skills needed for digital transformation, understanding current business models and their innovation potential, nurturing key proficiencies for AI assimilation, and gaining organizational acceptance while developing internal competencies. This article combines the fields of organizational change management and AI-driven business model innovation with ease, providing a thorough explanation to assist businesses in undergoing a successful transformation and innovation. These disciplines' confluence offers a practical vantage point for successfully adapting to, thriving in, and profiting within a dynamic business environment. Artificial intelligence (AI), a massively disruptive force that is altering international businesses, is at the vanguard of this revolution. The ability of AI to make decisions automatically, based on data analysis and observation, opens up hitherto untapped possibilities for value creation and competitive dominance, with broad consequences spanning several industries. With its quick scaling, ongoing improvement, and self-learning capabilities, this evolutionary invention functions as an agile capital-labor hybrid. Significantly, AI's architecture serves as the cornerstone for data-driven decision support by deftly sifting through large and complicated datasets to extract insights. Thus, the symbiotic marriage of organizational change management and AI-driven business model innovation gives a thorough narrative, directing businesses towards not just surviving, but thriving in an ever-evolving business environment. It is underlined how business models (BMs) interact with technology to affect how well business’s function, underlining the need of taking BMs into account while using AI. Business model innovation (BMI) that AI unlocks may improve goods, streamline processes, and save costs. However, there is a void between technological improvements and their operationalization via BMs. Successful AI integration depends on a well-structured BM, which promotes agility and makes the most of technological resources. BMI is accelerated by AI, which reshapes sectors via innovation. Although interest in AI is high, strategic, cultural, and technological constraints sometimes prevent large investments from producing positive economic results. To fully utilize AI's capabilities, structured BMs are required. Despite an increase in research, there is still little cohesive information about the business uses of AI. In an effort to close this gap, we examine implementation-related AI problems. Analyzing AI-driven BM transformation and risk management is aided by a study on BMI and digital transformation at the same time. The purpose of this study is to further our understanding of AI-driven business model innovation and to provide a useful framework to help practitioners navigate the potential and difficulties of AI implementation. The suggested roadmap aims to identify current knowledge gaps and future research initiatives.

Algebra preconditionings for 2D Riesz distributed‐order space‐fractional diffusion equations on convex domains

AbstractWhen dealing with the discretization of differential equations on non‐rectangular domains, a careful treatment of the boundary is mandatory and may result in implementation difficulties and in coefficient matrices without a prescribed structure. Here we examine the numerical solution of a two‐dimensional constant coefficient distributed‐order space‐fractional diffusion equation with a nonlinear term on a convex domain. To avoid the aforementioned inconvenience, we resort to the volume‐penalization method, which consists of embedding the domain into a rectangle and in adding a reaction penalization term to the original equation that dominates in the region outside the original domain and annihilates the solution correspondingly. Thanks to the volume‐penalization, methods designed for problems in rectangular domains are available for those in convex domains and by applying an implicit finite difference scheme we obtain coefficient matrices with a 2‐level Toeplitz structure plus a diagonal matrix which arises from the penalty term. As a consequence of the latter, we can describe the asymptotic eigenvalue distribution as the matrix size diverges as well as estimate the intrinsic asymptotic ill‐conditioning of the involved matrices. On these bases, we discuss the performances of the conjugate gradient with circulant and ‐preconditioners and of the generalized minimal residual with split circulant and ‐preconditioners and conduct related numerical experiments.

Comparing performance of neural network frameworks for image recognition: A review

Spiking Neural Networks (SNNs) are increasingly recognized as a promising approach to simulating the biological behavior of neurons. This study conducted an in-depth performance comparison of different SNN models with supervised learning algorithms, particularly in the field of image recognition. Using datasets like MNIST, CIFAR-10, and ImageNet, the research analyzed the performance and accuracy of SNNs compared to traditional Artificial Neural Networks (ANNs). This research contributes to understanding SNNs' performance in supervised learning environments and offers insights into the optimization of SNN architectures, thus influencing future research and the development of next-generation neural network designs. Based on this comparative study, it was found that while SNNs perform admirably with smaller, less complex datasets such as MNIST and CIFAR, they encounter difficulties with larger, more complex datasets like ImageNet. Despite these challenges, advances in conversion techniques have led to models that more closely simulate the behavior of biological neurons. The study identified significant future work areas, including addressing issues of local learning methods, the limited scale of SNNs, hardware implementation difficulties, a lack of substantial benchmark datasets, and limited support for complex computations.

Low-noise phase-sensitive optical parametric amplifier with lossless local pump generation using a digital dither optical phase-locked loop.

The low noise figure of phase-sensitive amplifiers (PSAs) is attractive for optically pre-amplified measurement and communication systems. However, a major practical implementation difficulty pertains to the requirement of phase-locked signal, idler, and pump waves. Previously, injection locking to a co-propagating weak pump pilot or tapping portions of the received signal (lossy) for carrier re-generation have been used. Here we present a novel, lossless approach without any pump pilot, that generates a phase-locked receiver-local pump within the PSA using a digital dither-based optical phase-locked loop. We experimentally demonstrate a 2 dB noise figure with a low 0.3 dB penalty due to imperfect locking. By comparing the phase-locking performance in a PSA to that in a 50/50-coupler, we discuss and predict potential performance improvements connected to loop delay and laser phase characteristics.

Formulation of water pollutant discharge limits for malathion based on nonsensitive aquatic organism protection

The “Integrated Wastewater Discharge Standard” was implemented for water pollutant discharge in China’s pesticide industry, which has no control requirements for particular wastewater pollutants in the industry. In the standard, certain pollutants discharge limits are limited strictly or loosely, resulting in practical management implementation difficulties. In view of the highly selective targeting characteristics of organic pesticide active ingredients in fungicides, insecticides, and herbicides, a method for deriving discharge limits based on the water quality criteria for pesticides for the protection of nonsensitive species is established based on the idea of fully protecting aquatic organisms beyond sensitive objects. Through the use of malathion as an example, by screening its toxicity data in different species of aquatic organisms, the sequence point with the most significant change in the acute toxicity sensitivity of the species is taken as the variation point in the cumulative frequency of the sensitive and nonsensitive species to derive the water quality criteria, using the species sensitivity distribution method as the scientific basis for determining the discharge limits. After a comparative analysis of different simulation models, the sigmoid model, with the best fit, is selected to determine that the sensitive species hazard concentration (HCs) of malathion to aquatic organisms in China is 46.4 µg/L, and the discharge limit derived from the HCs based on the relationship between the environmental capacity and emissions is rounded to 250 µg/L. Studies showed that the relationship between the emissions limit derived from the water quality criteria for protecting nonsensitive species and malathion limit stipulated in the “Environmental Quality Standards for Surface Water” conforms to the corresponding relationship of the quality standard and discharge standard, which can be achieved by current pollution control technology, combined with water quality improvement. The discharge limit offers the advantages of technical accessibility and economic rationality.

Умное сельское хозяйство в цепочке поставок сырья для молочной промышленности

The interaction of traceability systems is analyzed. The reasons and difficulties of implementation of some systems are revealed. Proposals are given for the further development and interaction of systems from «smart farming» to the counter.

Sum and difference patterns synthesis with common excitation amplitude

This paper focuses on the joint optimization problem of sum and difference patterns with common excitation amplitudes and separate excitation phases. The objective is to reduce the complexity of the antenna system while still maintaining a certain degree-of-freedom (DoF) in synthesizing dual-patterns. The problem is formulated with angular response and common excitation amplitude constraints, making it a nonconvex optimization problem. To address this, we introduce two groups of auxiliary variables to decouple the excitation vector from the complex nonconvex constraints. This allows the original problem to be effectively solved via alternately determining the closed-form solutions for several single-variable optimization subproblems. Additionally, our approach is extended to scenarios involving dynamic range ratio (DRR) reduction, aiming to lower the cost and difficulty of hardware implementation. Theoretical analysis and simulation results are provided to demonstrate that the proposed algorithm can converge to the Karush-Kuhn-Tucker points of the original problem. It is also observed that our approach is capable of generating desired dual-patterns with common excitation amplitudes, regardless of the presence or absence of DRR control.

Database Replication for Disconnected Operations with Quasi Real-Time Synchronization

Database replication is a way to improve system throughput or achieve high availability. In most cases, using an active-active replica architecture is efficient and easy to deploy. Such a system has CP properties (from the CAP theorem: Consistency, Availability and network Partition tolerance). Creating an AP (available and partition tolerant) system requires using multi-primary replication. This approach, because of many difficulties in implementation, is not widely used. However, deployment of CCDB (experiment conditions and calibration database) needs to be an AP system in two locations. This necessity became an inspiration to examine the state-of-the-art in this field and to test the available solutions. The tests performed evaluate the performance of the chosen replication tools: Bucardo and EDB Replication Server. They show that the tested tools can be successfully used for continuous synchronization of two independent database instances.

Kripto Para Merkezli Kara Para Aklama Senaryolarının Adli Bilişim Açısından İncelenmesi

One of the biggest innovations brought by the digitalized world is undoubtedly the invention of crypto money, which is decentralized, anonymous and complex, and connected to blockchain technology. This relatively new technology has attracted the attention of many people with its revolutionary changes in payment systems and great price movements in the market, as well as the economic balances it has changed around the world. In addition to this interest, it also attracted the attention of crime and crime organizations in a short time, and over time it turned into a tool used by illegal organizations such as laundering the proceeds of crime. Although this structure was initially exposed to the reaction of some states at the level of nation states, on the other hand, it managed to get the support of many states. However, although the spread of blockchain-based money laundering methods is an undeniable problem for all states, a significant cooperation has not been achieved by international collaborations and organizations to prevent this situation. On the other hand, it is of great importance for law enforcement and forensic analysts to clarify this situation and to fight against these structures in order to protect national interests. In this study; In this study, an approach that will detect money laundering is tried to be presented through sample scenarios by bringing a broad perspective to crypto money-based money laundering methods, which are very difficult to trace due to their nature. In addition, it is expected that the difficulties in implementation of the proposed approach will be clearly addressed and will shed light and inspire further study.

시나리오 분석 및 위험도 평가에 의한 자율주행자동차 검증방법

In this study, we propose an autonomous vehicle safety validation method to address the limitations of existing vehicle safety validation methods. Using scenario analysis and risk assessment of the autonomous vehicle safety validation scenario, the proposed method determines the significance of scenario validation, difficulty of scenario implementation, and critical nature of accidents that occur during validation testing. Then, it calculates the autonomous vehicle test level based on these results. Various safety validation tests, such as audits, simulation tests, proving ground tests, and real road tests, were performed according to the calculated level. Based on the validation results, the proposed method enables authorities to request improvement in the original equipment manufacturer address areas and is expected to contribute to providing safe autonomous vehicles to consumers.

Research on the Implementation Difficulties and Optimization Measures of Project-based Teaching in Maritime English

In recent years, project-based teaching has become the focus of national vocational education curriculum reform, and has also become an important teaching form in the curriculum reform of major maritime vocational colleges. The project-based teaching reform of maritime English has achieved significant breakthroughs and results after implementation, but there are still many problems in teaching practice. This article analyzes the implementation difficulties of project-based teaching in maritime English and proposes corresponding optimization measures to address these difficulties, providing reference for effectively deepening the reform of maritime English teaching in vocational colleges.

Drivers and Barriers to Implementing the Internet of Things in the Health Care Supply Chain: Mixed Methods Multicase Study.

Over the past 2 years, the COVID-19 pandemic has placed enormous pressure on the health care industry. There has been an increase in demand and, at the same time, a shortage of supplies. This has shown that supply chain management in the health care industry cannot be taken for granted. Furthermore, the health care industry is also facing other major challenges, such as the current labor market shortage. In the literature, the Internet of Things (IoT) is highlighted as an effective tool to build a more resilient and efficient supply chain that can manage these challenges. Although using IoT in supply chain management has been extensively examined in other types of supply chains, its use in the health care supply chain has largely been overlooked. Given that the health care supply chain, compared to others, is more complex and is under growing pressure, a more in-depth understanding of the opportunities brought by IoT is necessary. This study aims to address this research gap by identifying and ranking the drivers of and barriers to implementing IoT in the health care supply chain. We conducted a 2-stage study. In the first, exploratory stage, a total of 12 semistructured interviews were conducted to identify drivers and barriers. In the second, confirmatory stage, a total of 26 health care supply chain professionals were asked in a survey to rank the drivers and barriers. The results show that there are multiple financial, operational, strategy-related, and supply chain-related drivers for implementing IoT. Similarly, there are various financial, strategy-related, supply chain-related, technology-related, and user-related barriers. The findings also show that supply chain-related drivers (eg, increased transparency, traceability, and collaboration with suppliers) are the strongest drivers, while financial barriers (eg, high implementation costs and difficulties in building a business case) are the biggest barriers to overcome. The findings of this study add to the limited literature regarding IoT in the health care supply chain by empirically identifying the most important drivers and barriers to IoT implementation. The ranking of drivers and barriers provides guidance for practitioners and health care provider leaders intending to implement IoT in the health care supply chain.

Universal Basic Income: The Foreseeable Future of Social Welfare Systems in the Post-Pandemic Era

The unconditional and regular payment of a certain amount of cash income to the entire population is a claim to universal basic income and a system that is distinct from the existing social welfare systems. Policy experiments on universal basic income have been going on since the end of the 20th century and have been seen by some scholars as a solution to major social problems such as technological development, economic downturn, and poverty. Especially under the impact of the 2020 pandemic, the world's development is once again hampered, and how to better solve the problems of low-income people is an important issue to be addressed by the social welfare system. It is worth noting that the policies introduced by governments under the pandemic have some degree of universal basic income characteristics. This article will analyze the merits and importance of universal basic income in the context of the welfare policies introduced by governments under the pandemic. Considering the economic difficulties in the post-pandemic era, it is worthwhile for countries to explore universal basic income as a basis for new social welfare systems, despite the potential difficulties in implementation.

Application Status of Engineering Management in the Construction Field

With the development of the real estate industry, the take-off of the construction industry has also caused more and more capital to pour into the construction industry, driving the rapid development of the construction industry, but also causing the construction industry to face great competitive pressure. In order to achieve effective management of construction projects, this article aims to point out the main problems in Chinas construction management and improve the construction project management system and improve construction technology, which is conducive to improving the operational level and construction quality of construction projects. Currently, there is a lack of effective information communication and coordination mechanisms within the construction units of construction projects, which can lead to slow progress and low efficiency in the construction of construction projects, which will greatly increase the implementation difficulty of construction projects and restrict the improvement of enterprise construction project management level. Thus, it is important to improve the role of construction project management in the construction industry, and it is necessary to figure out the inner problems and strengthen the management of construction projects. The articles main purpose is to focus on the current situation and development reality of construction project management, specific research is conducted on its management and control optimization from the perspective of engineering management, to provide a reference for modern management and optimization of construction projects management.

A Non-Invasive Circuit Breaker Arc Duration Measurement Method with Improved Robustness Based on Vibration–Sound Fusion and Convolutional Neural Network

Previous studies have shown that the contact wear estimation of circuit breakers can be based on the accumulative arc duration. However, one problem that remains unresolved is how to reliably measure the arc duration. Existing methods encounter difficulties in implementation and suffer from limited accuracy owing to the impact of the substation environment. To overcome these issues, this article presents a novel, non-invasive method for measuring arc duration that combines vibration–sound fusion and convolutional neural network. The proposed method demonstrates excellent performance, achieving errors below 0.1 ms under expected noise conditions and less than 1 ms in the presence of various forms of noise, transient interference, and even sensor failure. Its advantages include its ability to accurately measure arc duration and its robustness against noise and interference with unknown patterns and varying intensity as well as sensor failure. These features make it highly suitable for practical deployment in substation environments.