Cost Control Research Articles

Consensus and attack-decomposition of switched one-sided Lipschitz multi-agent systems via event-triggered intermittent control

This paper considers the exponential consensus of nonlinear switched multi-agent systems (MASs) subject to random attacks. The proposed model is enhanced by introducing the concept of mode-dependent average dwell time (MDADT) and the one-sided Lipschitz (OSL) condition, making it more practical and versatile with relaxed restrictions. Due to the unavailability of direct access to the states of MASs and the vulnerability of their output signals to unknown random attacks, achieving consensus through traditional methods becomes challenging. Hence, a novel attack-decomposition approach is proposed to extract the attack-free output signals from the attacked output signals. Then, the observer is constructed by utilizing attack-free output signals and employed to estimate the states of MASs. A mode-dependent event-triggering mechanism is presented to conserve resources for the observer-controller channels. In order to save control costs, the intermittent control scheme is designed for different switching modes whose control width depends on the minimum dwell time. Finally, an illustrative example is used to showcase the advantages of the theoretical method.

Cost Control Strategies in the Pre-Construction Period of Highway Construction

Effective cost control in the investment and design phases of highway construction is crucial for managing project expenses. However, current management practices often overlook pre-construction cost management, leading to budget overruns and project delays during later stages. To ensure the smooth execution and cost control of highway construction projects, this paper examines the significance of cost control, evaluates the current state and challenges of highway construction, and proposes strategies for cost management. These strategies aim to establish a robust foundation for cost management in highway projects.

Emergency coordinated control of multiple VSC‐HVDC for improving power system transient frequency and steady‐state frequency

AbstractWith the penetration of the high proportion of power electronics interfaced energy resources, the frequency stability issue in power systems is becoming increasingly prominent. This paper proposes a coordinated control strategy of multiple voltage source converter based high voltage direct current transmission (VSC‐HVDC) to simultaneously improve the transient frequency and steady‐state frequency after a severe disturbance. Firstly, a modified average system frequency response (MASFR) model is constructed with reserve power limitation, which takes into account the frequency responses of different types of generators (thermal, hydro and new energy resources). Secondly, according to the frequency stability requirements, the corresponding constraints, which consider the overload capacity of VSC‐HVDC, the AC transmission capacity and the frequency of AC grids on both sides of VSC‐HVDC, are formulated. Thirdly, for the transient frequency control, the coordinated optimization control model of multiple VSC‐HVDC is established, which aims to minimize the control energy considering the transient frequency threshold. For the steady‐state frequency control, the coordinated optimization control model is fomulated, which aims to minimize the control cost while considering the steady‐state frequency threshold. The two control schemes achieve seamless and smooth switching. Finally, the correctness and effectiveness of the proposed control strategy are verified in the improved IEEE 39 bus system.

Analysis of Inventory Control of Green Spinach (Amaranthus Tricolor l) Seeds With Economic Order Quantity Method in CV. AMATTA MULYA BARIZI

Purpose: This study aims to identify inventory control and costs incurred by the company, analyze inventory cost control for green spinach seeds using the EOQ model VII method, and analyze cost efficiency for green spinach seed inventory. Methodology: The analysis used the EOQ method to determine the optimal order quantity for green spinach seeds at CV Amatta Mulya Barizi. Results: The EOQ method resulted in an optimal order quantity of 2,280 grams per order. The inventory costs for green spinach seeds amounted to IDR 273,642.00 per order or IDR 3,283,704.00 per year. Findings: The study found that the EOQ method is more efficient compared to the company’s current method, allowing the company to save IDR 586,296.00 annually on green spinach seed inventory costs. Novelty: This research provides new insights into the application of the EOQ model VII for seed inventory management, highlighting significant cost savings. Originality: The study offers a detailed analysis of inventory control and cost efficiency for green spinach seeds, contributing to better inventory management practices. Conclusions: The EOQ method is more efficient for inventory management of green spinach seeds at CV Amatta Mulya Barizi, resulting in considerable cost savings. Type of Paper: Empirical Research Article

Population structure and risk assessment of invasive species Asystasia gangetica in urban area of Bandung, West Java, Indonesia

Abstract. Rosleine D, Khalishah AR. 2024. Population structure and risk assessment of invasive species Asystasia gangetica in urban area of Bandung, West Java, Indonesia. Biodiversitas 25: 2374-2381. Asystasia gangetica (L.) T. Anderson is a weed from Africa that has a high adaptation to wide ecological conditions. This research aims to assess the population structure of A. gangetica in Bandung City, West Java, Indonesia and to conduct risk assessment to determine management decisions. This research was conducted from January to February 2023 by establishing a total of 106 plots with size of 1 m2 to measure the population structure at adult and juvenile stages, and number of fruits. Plot sized 0.4 m2 was used to count the seed in a 10 cm soil depth. A risk assessment was conducted, which consisted of 12 questions of risk analysis (invasiveness, impact, and potential distribution) and 20 questions of management feasibility (control cost, distribution, and persistence). The results of principal component analysis and clustering analysis show three groups based on population structure (PC1 49.12% and PC2 28.44%). The first cluster consists of three sub-districts and shows a set of early colonized populations indicated by low juvenile stage, while the second cluster (14 sub-districts) and third cluster (13 sub-districts) show more established population yet still recently colonized, which is indicated with medium-high juvenile and reproductive (fruit) stage. The risk assessment results in 91.2 of the risk analysis score (medium) and 169.7 of the management feasibility score (negligible), implying the need to manage the site. Nevertheless, its wide-range of habitat tolerant and population characteristics potentially threaten biodiversity and harm the agricultural sector at once. Therefore, early countermeasure is needed as an effort to minimize greater risks in the future.

Exploring macro-environmental catalysts and barriers of healthcare 4.0 transformation in Central-Eastern European countries: A comprehensive study in Hungary

The pursuit of a secure, efficient healthcare system responsive to patient needs remains a crucial goal for developed countries. Governments, grappling with rising healthcare demands, are increasingly turning to technological innovation as a transformative solution. Healthcare 4.0, integrating cutting-edge industrial technologies, aims to enhance patient experience, promote health, control costs, and boost clinical satisfaction. The COVID-19 pandemic has catalysed investments in digitalisation, but the promises of Healthcare 4.0 are still seemingly unrealized. This is especially true in the Central-Eastern European (CEE) region, particularly in Hungary, where substantial Industry 4.0 innovation potential intersects with shrinking financial resources, a challenging political environment, a transitioning healthcare system hindering the widescale transition to Healthcare 4.0. Thus, this paper aims to explore the macro-environmental factors influencing Healthcare 4.0 adoption in Hungary. Leveraging qualitative content analysis of interviews with 21 Hungarian healthcare technology startup founders, we aim to map the catalysts and barriers of a Healthcare 4.0 transition using a PESTLE framework. This explorative study contributes to the literature with valuable insights from the innovators' perspective, serving as a foundation for future policy interventions in the quest for widespread Healthcare 4.0 implementation.

Fixed/Preassigned-time synchronization of quaternion-valued BAM neural networks: An event-based non-separation control method

Quaternions provide expressive power beyond real numbers, allowing neural networks to capture and process correlations and patterns in data with greater complexity. Besides, event-triggering mechanism has significant advantages in reducing redundant data transmission and control costs, since the sampling instant is determined by preset trigger conditions. Based on these fact, this article investigates the fixed-time and preassigned-time synchronization of quaternion-valued Bidirectional Associative Memory (BAM) neural networks via event-triggered control. Firstly, based on a dual-layer network structure with different number of nodes, a type of BAM neural network with generalized time-varying delays is established in the quaternion domain. Secondly, four kinds of Zeno-free dynamic event-triggered control mechanisms are designed, and the trigger condition can be dynamically adjusted according to the changing requirements. In the framework of non-separation analysis, the synchronization the controlled network can be guaranteed within a fixed time, and the upper bound of the setting time is provided explicitly. Furthermore, to better meet practical needs, the above event-triggered mechanism and the criteria are extended to the PAT synchronization. Two illustrate examples are presented at last to validate the developed event-triggered mechanism and synchronization results.

Brazil’s Economic Potential with Carbon Credits: A Study of the “Mata Do Buraquinho” – Brazil

Introduction: Public (state) concern about the climate has, in turn, catalyzed the creation between global governments and transnational companies, and these models are subject to risk-consequence type measures, the conduct of which is now known as the voluntary carbon credit market. The article in question deals with one of the most talked-about economic instruments for combating global warming in international politics, the carbon credit market. Objective: The article in question proposes a reflection on this subject, which has been so much talked about in recent years, focusing on its economic perspective and using a case study methodology to support its results. Theoretical framework: The mitigation of greenhouse gas (GHG) emissions is a necessary condition to lead to a low-carbon economy, and the best way to achieve this is through the application of economic instruments. Such as putting a price on carbon, making this transition quicker and less costly from a social point of view. In this way, with a higher relative price for pollution, private agents will choose between paying for or reducing pollution, comparing the marginal cost of control with the price of carbon. Methodology: Initially, a bibliographical review was made of the economic theoretical framework that underpins one of the instruments considered most efficient in combating climate change, the carbon credit market. In another part of this work, a practical application of this mechanism was carried out, using an evaluation methodology for an application of this instrument in the municipality of João Pessoa -PB, which stands out for being one of the most wooded cities in Brazil and for having some conservation units in its territory, such as the one used in the work, the Mata do Buraquinho Wildlife Reserve. Results: The sale of the ecosystem services that the forest offers, in this case its capacity to absorb CO2, could improve the conditions for maintaining the area and perhaps attract more people to visit it. Thus, the value found for “Mata do Buraquinho” was R$61,968.26.

Based on knowledge capital value for disease cost accounting of diagnosis related groups.

The National Health Commission and the other relevant departments in China have initiated testing of the Diagnosis Related Groups (DRGs) system in 30 pilot locations since 2019. In the process of DRG payment reform, accounting for the costs of diseases has become a highly challenging issue. The traditional method of disease accounting method overlooks the compensation for the knowledge capital value of medical personnel. The primary objective of this study is to analyze the cost accounting scheme of China's Diagnosis Related Groups (C-DRG), focusing on the value of knowledge capital. The study initially proposes a measurement index system for the value of knowledge-based capital, including the difficulty of disease treatment, labor intensity of disease treatment, risk of disease treatment, and operation/treatment time for diseases. The Analytic Hierarchy Process (AHP) is then utilized to weigh the features of medical workers' knowledge capital value. First, pairwise comparisons are conducted in this stage to develop a two-pair judgment matrix of the primary indicators. Second, the eigenvectors corresponding to the maximum eigenvalues of the matrix are calculated to generate the weight coefficient of each feature. The consistency test is carried out after this stage. An empirical analysis is conducted by collecting data, including the full costs of treating three types of diseases-hip replacement, acute simple appendicitis, and heart bypass surgery-from one public medical institution. The empirical analysis examines whether this DRG costing accounting can address the issue of neglecting the value of medical workers' knowledge capital. The methods reconfigure the positive incentive mechanism, stimulate the endogenous motivation of the medical service system, foster independent changes in medical behavior, and achieve the goals of reasonable cost control. In the cost accounting system of C-DRG, the value of medical workers' knowledge capital is acknowledged. This acknowledgment not only boosts the enthusiasm and creativity of medical workers in optimizing and standardizing the diagnosis and treatment process but also improves the transparency and authenticity of DRG pricing. This is particularly evident in the optimization and standardization of the diagnosis and treatment processes within medical institutions and in monitoring inadequate medical practices within these institutions.

A Financial Analysis and Valuation on Nike, Inc.

As there are a great number of companies in the market, evaluation of a specific company is vital of importance nowadays. Therefore, this report will give a comprehensive financial analysis of Nike from four aspects: liquidity performance, solvency performance, profitability performance and investment performance. Initially, this analysis will give a brief introduction about Nike’s strategy, operations and some basic information. After that, liquidity performance indicates that Nike did a great job especially in the use of inventory and the discount capacity. Meanwhile, Nike also low financial risks and strong profitability compared with other four companies in the same industry in the solvency performance. Furthermore, Nike has an excellent cost control ability but still some improperly allocated of resources in some areas in the profitability performance. Not only this, Nike has the highest investment value among the four competitors in the same industry in the investment performance. As a whole, it could be seen from the financial analysis that Nike has quite strong competitiveness in this industry.

Dynamic event-triggered mean-square consensus of positive multi-agent systems via impulsive control under false data injection attacks

This paper investigates the mean-square impulsive consensus problem of positive multi-agent systems (MASs) under stochastic sensor false data injection attacks (FDIA). False data injection attacks are mortal to a positive system since the system positivity could be destroyed with ease (by tampering with the sampled positive state value to a negative one, for instance). To deal with this issue, a data compensator is proposed which preprocesses deliberately distorted state values to reduce their adverse impacts on the positivity of the positive MASs. On the other hand, a novel sampled-data-based dynamic event-triggered mechanism (SDB-DETM) is tailored to generate impulsive control time sequences, save control costs, and promise a desired control performance. A maximum event-trigger time interval is introduced as a substitute for the assumption of the average time interval when considering the randomness of FDIA. Furthermore, the dynamics of the auxiliary dynamic variable are improved to adapt the novel SDB-DETM with mixed signals. A sufficient and necessary condition of the positivity of the positive MASs under FDIA is presented. The commonly used positive constraints on the error system are removed. By constructing a quadratic Lyapunov function, a sufficient condition of the mean-square consensus of the positive MASs is derived. Two numerical examples are provided to illustrate the effectiveness of theoretical results.

High‐order robust control design with optimized parameters based on confidence index

AbstractUnder the theoretical support of fuzzy sets theory and confidence index, the proposed approach involves the development of a high‐order robust control method that incorporates optimization techniques to address uncertain systems. First, the utilization of fuzzy sets theory is employed to establish a fuzzy dynamical model. Second, the design of a high‐order robust controller is performed. Third, the design parameters are optimized based on confidence index, and the values are found that minimize the control cost. The simulation results show that this high‐order robust control has significant advantages in dealing with uncertainty, as well as minimizing the control cost. It can be ensured the uniform boundedness and uniform ultimate boundedness. Thus, this proposed method offers the advantage of achieving both robustness and optimality simultaneously.

Secure intermittent impulsive consensus control for fractional-order multiagent systems under denial-of-service and deception attacks

This article addresses the secure consensus problem of fractional-order multiagent systems (FOMASs) under denial-of-service (DoS) and deception attacks in the intermittent impulsive control framework. Unlike previous cyber attack models, the multiple attacks are considered, which the agent-to-agent communication channels and the controller-to-actuator channels are randomly subjected to deception and DoS attacks, respectively. Some random variables that follow the Bernoulli distribution are proposed, which are related to the communication channels between adjacent agents to describe deceptive attack behavior. To reduce control costs and resist cyber attacks, a novel intermittent impulsive control strategy is designed to make the FOMASs achieve consensus faster, when DoS attacks are sleeping. The designed intermittent impulsive control includes the advantages of discrete sampling control and intermittent control, which means that it can reduce the injection of erroneous data by constraining the frequency of information transmission. Furthermore, some sufficient criteria including the parameters of multiple attacks are yielded to ensure mean-square quasi-consensus of FOMASs. Finally, two examples are provided to validate the rationality for the presented security control method in this study from the perspective of numerical simulation experiments.

Estimating the cost of first-generation rent control in Italy: the case of Florence, 1950–1963

ABSTRACT Among the many costs of rent control, one is the cost imposed upon landlords. This cost is measured as the difference between the controlled rent and the hypothetical free market rent that would prevail in the absence of rent controls. Although recent studies estimate the size of this particular cost in modern contexts, there are relatively few research contributions on pre-1970s European rent controls, largely as a consequence of the absence of easily-accessible data for older rental markets. This study addresses this issue by using original historical data on 362 controlled and uncontrolled housing units in Florence between 1950 and 1963 in order to estimate the hypothetical free market rent of those units, and the cost imposed on landlords by rent control. Analysis of a sample of 4,081 apartments-years, 3,574 of which are controlled apartments-years while 507 are uncontrolled apartments-years, indicates that per-room rents on controlled units were between about €19.5 and €22 lower than those on free-market units, depending on the subsample and the type of analysis. Based on 317 separate five-room housing units, inverse probability weighting approach estimates suggest that the aggregate cost to landlords of rent control is almost €31,000 per month, or about €370,000 per year.

Inventory Management Optimization: Balancing Cost and Service Levels

Efficient management of inventory plays a role, in the success of businesses across sectors. Finding the equilibrium between keeping inventory costs low and meeting customer needs is a challenge that requires constant exploration and creativity. This study delves into the complexities of optimizing inventory management focusing on strategies that effectively handle the trade offs between minimizing expenses and fulfilling customer expectations. By delving into an analysis of existing literature this study consolidates approaches, models and best practices implemented by companies to enhance the efficiency of inventory management. It thoroughly examines aspects such as improving demand prediction accuracy reducing lead times optimizing safety stock levels and integrating supply chains. Additionally it explores how advanced technologies like intelligence data analytics and automation are transforming inventory management processes.Moreover this research delves into how industry landscapes, market dynamics and business goals influence inventory management tactics. Through real world examples and empirical data analysis it offers insights, on how organizations can tailor their strategies to meet needs while balancing the objectives of cost control and service level improvement. In the end this study adds to what we know about improving inventory management by providing advice and tips for companies to gain lasting edges in todays ever changing market. KEYWORDS: Research Paper, Blockchain, Management, Risk Evaluation, Empirical Analysis

The Usage Of Government Formulary For BPJS Inpatients With Ischemic Stroke In Indonesia

Introduction: Ischemic stroke patients tend to use some medicine. In National Health Security (JKN), the government has created a government formulary as quality control and cost control. The study aims to determine the percentage of government formulary in Hospitals and the affected factors. Method: It was cross sectional quantitative research. It used retrospective data from medical record and prescription of ischemic stroke inpatients from January to June 2019. The data collected include hospital characteristics, patient characteristics, supporting characteristics and treatment costs. Result: The data cames from 17 hospitals. Based on the inclusion and exclusion criteria, 257 medical records were analyzed. The average percentage of drug use was 73.22%. Its was influenced by the hospital class, the number of supporting examinations, the number of drug items. Type B and C hospitals used non government formulary. There were citicolin, mecobalamin, piracetam, neurotropic multivitamin, flunarizine. Conclusion: The average percentage of drug use was still less than 100%. There were still non government formulary drugs used for the therapy of inpatient ischemic stroke. The use of non government formulary drugs was influenced by the hospital class, the number of supporting examinations, the number of drug items.

Optimal design of robust control for belt conveyor systems based on fuzzy dynamic model and Nash game

An optimized robust control method is proposed in this paper to deal with the disturbances of nonlinear factors such as uncertainty in belt conveyor and to realize the speed control of belt conveyor. By controlling the subsystems to track the same desired speed, belt breaks and overlaps caused by varying belt speeds from one section to another are limited. First, a fuzzy model is developed by applying fuzzy set theory to describe uncertainties of belt conveyor such as masses, stiffness, damping and frictions. Second, a robust control is designed for the nominal system and compensating for the uncertainty. With the robust control, the belt conveyor system is proved to be uniformly bounded and uniformly ultimately bounded by the Lyapunov approach. Third, the parameters of controller are optimized based on a non-cooperative game approach. The optimal solution is the Nash equilibrium. Optimal solution allows the controller system to perform better and decrease the cost of control. Finally, by comparing with LQR control and different parameters, the feasibility of robust control and the rationality of the optimal parameters are proven.

Finite-time master–slave synchronization for implicit hybrid neural networks under event-triggered guaranteed cost control and random deception attacks

This paper researches the finite-time master–slave synchronization for implicit hybrid neural networks under event-triggered guaranteed cost control and random deception attacks. By developing Lyapunov–Krasovskii functional and exploiting singular value decomposition technique, the finite-time boundedness of synchronization error closed-loop system is achieved under deception attacks and event-triggered scheme, then the finite-time master–slave synchronization of implicit Markovian jump neural networks is realized. The desired gains of state feedback synchronization guaranteed cost controller are designed by solving a set of linear matrix inequalities. The availability of the given approach is confirmed by an artificial neural network and a numerical example.

Environmental Accounting and Sustainable Development of Firms in Rivers State, Nigeria

Within the scope of the research, environmental accounting and sustainable development were explored in relation to oil and gas firms located in Rivers State, Nigeria. There was a correlational survey research design used for the investigation. A total of six oil and gas businesses that were active in the Rivers State Region of Nigeria were included in the study's research population. For this particular investigation, secondary data served as the instrument. Statistical Package for the Social Sciences (SPSS) Version 22 was used in order to do the analysis on the data. A simple bivariate regression analysis was performed at a significance level of.05. The research issues were evaluated using the mean and standard deviations, and hypotheses were assessed using the analysis. The data indicated that there is no substantial connection between the cost of waste management and the ecologically sustainable growth of oil and gas businesses in Rivers State, Nigeria. Additionally, there is a strong significant association between the cost of pollution control and the development of ecological sustainability, as well as a strong significant relationship between the cost of pollution control and the development of economic sustainability for oil and gas businesses in Rivers State, Nigeria. By adhering to social responsibility in waste management, oil and gas firms should put a premium value on initiatives that are focused towards reducing their ecological footprint and promoting sustainable growth while also reducing their environmental impact.

Finite-time annular domain robust guaranteed cost control of interval positive linear systems

The issue of finite-time annular domain robust guaranteed cost control of positive linear systems with interval uncertainties is investigated in this paper. First, by using the linear copositive Lyapunov function, a sufficient condition for the existence of state feedback controller is given to ensure the positivity and finite-time annular domain robust stability of the closed-loop system, and guarantee the cost function is no more than a given upper bound. The corresponding controller design method is derived based on linear programming technique. Then, an optimisation algorithm is further developed to obtain the optimal guaranteed cost controller, which is convenient to be computed. Finally, a numerical example and an application example are given to demonstrate the effectiveness of theoretical results.