System Performance Indicators Research Articles

Adaptive event‐triggered fault detection for Markov jump nonlinear systems with time delays and uncertain parameters

AbstractThis article proposes a fault detection (FD) method for a class of Markov jump nonlinear systems with time delays and uncertain parameters. The FD problem is transformed into a filtering question by designing a FD filter that satisfies appropriate performance index. An adaptive event‐triggered mechanism is introduced to conserve network resources, and the impact of time‐varying and network‐induced delay on the system is fully considered. Then, stochastical stability and appropriated performance index of the residual system are guaranteed using the Lyapunov–Krasovskii functional theory, discrete Wirtinger inequality and extended reciprocally convex matrix inequality. Finally, a simulation example verifies the feasibility and effectiveness of the designed FD filter.

Remaining useful life prediction for motor systems by iteratively updated wiener process based on closed-loop performance degradation monitoring

Driven by the need for remaining useful life prediction of degraded motor systems with feedback controllers, a real-time updated Wiener stochastic process is adopted to model the performance degradation of motor systems. First, a closed-loop performance index of the motor system is derived incorporating the multiple slow time-varying characteristic of motor parameters. On this basis, the drift coefficient and diffusion coefficient of the Wiener degradation model are updated to obtain the prior maximum likelihood function with available historical data. It is followed by the iterative optimization of nonlinear feature parameter in the Wiener degradation model with taking the prior maximum likelihood function as the cost equation. The effectiveness of proposed remaining useful life prediction architecture for closed-loop motor systems is demonstrated by motor systems.

The Effect of Solar Panel Type on some Irrigation System Parameters and Bean Crop Germination Percentage

An experiment was carried out at Al-Raed Research Station, which is located on the Baghdad-Anbar road during the winter season, in order to study the effect of the type of solar panels and irrigation system on some performance indicators of irrigation systems and germination percentage of bean crop (Vicia Faba L). A randomized complete block design (RCBD) was used with three replications. The experiment consist of two factors. 1st factor was the solar panel type with two levels : monocrystalline and polycrystalline. Second factor was the irrigation system with two levels Drip and sprinkler irrigation system the following indicators were studied : solar panel efficiency (%), Irrigation system capacity (L / H), coefficient of homogeneity, germination percentage (%). The results shows that the monocrystalline achieved the best result by achieving the highest solar panel efficiency (24.21 %), the highest irrigation capacity (1782 L/H) and highest coefficient of homogeneity (94.54 %), The best solar panel efficiency was achieved with the drip irrigation which has on average (22.50 %), The drip irrigation had the highest coefficient of homogeneity (96.14 %) and the best germination percentage (97.20 %). The interaction between solar panel type and irrigation system shows that the monocrystalline with drip irrigation achieved the best panel efficiency (25.69 %) and highest average for homogeneity (96.72 %).

IMPROVING THE METHODOLOGY OF COMPREHENSIVE ASSESSMENT OF ENTERPRISE FINANCIAL CONDITION: CALCULATION OF THE INTEGRAL INDICATOR

The article explores the theoretical aspects of a comprehensive enterprise financial condition assessment and the possibilities of its practical application and substantiates the sequence of stages of calculation and analytical procedures that can provide a stable foundation for the economic development of an enterprise. The purpose of the article is to improve the methodology of a comprehensive assessment of the financial condition of an enterprise and its practical aspects.The term "financial condition of an enterprise" is considered in the context of the need to assess it in order to counteract financial problems and prevent crisis phenomena. The article proposes the use of a system of key performance indicators, proves the importance of an integrated approach to assessing the financial condition of an enterprise and describes the key requirements for choosing the optimal system of indicators.The study has allowed the formulation of a generalized approach to a comprehensive assessment of the financial condition of an enterprise. The article proposes the introduction and use of an integral indicator, defines criteria of assessment of results and equality, observance of which by an enterprise is able to maintain its condition at the proper level and to provide a foundation for expanded reproduction, which, as a result of efficient functioning of economic entities, will contribute to the development of the economy.

Assessment of Security KPIs for 5G Network Slices for Special Groups of Subscribers

It is clear that 5G networks have already become integral to our present. However, a significant issue lies in the fact that current 5G communication systems are incapable of fully ensuring the required quality of service and the security of transmitted data, especially in government networks that operate in the context of the Internet of Things, hostilities, hybrid warfare, and cyberwarfare. The use of 5G extends to critical infrastructure operators and special users such as law enforcement, governments, and the military. Adapting modern cellular networks to meet the specific needs of these special users is not only feasible but also necessary. In doing so, these networks must meet additional stringent requirements for reliability, performance, and, most importantly, data security. This scientific paper is dedicated to addressing the challenges associated with ensuring cybersecurity in this context. To effectively improve or ensure a sufficient level of cybersecurity, it is essential to measure the primary indicators of the effectiveness of the security system. At the moment, there are no comprehensive lists of these key indicators that require priority monitoring. Therefore, this article first analyzed the existing similar indicators and presented a list of them, which will make it possible to continuously monitor the state of cybersecurity systems of 5G cellular networks with the aim of using them for groups of special users. Based on this list of cybersecurity KPIs, as a result, this article presents a model to identify and evaluate these indicators. To develop this model, we comprehensively analyzed potential groups of performance indicators, selected the most relevant ones, and introduced a mathematical framework for their quantitative assessment. Furthermore, as part of our research efforts, we proposed enhancements to the core of the 4G/5G network. These enhancements enable data collection and statistical analysis through specialized sensors and existing servers, contributing to improved cybersecurity within these networks. Thus, the approach proposed in the article opens up an opportunity for continuous monitoring and, accordingly, improving the performance indicators of cybersecurity systems, which in turn makes it possible to use them for the maintenance of critical infrastructure and other users whose service presents increased requirements for cybersecurity systems.

A Review of Performance Management in State-owned Enterprises and Private Enterprises in China

In order to improve profits, the theory of enterprise performance management has formed a corresponding theoretical framework and system. Enterprises can improve performance management methods based on their own situation. This research compares the differences between state-owned enterprises and private enterprises through literature review. The existing papers mainly focus on performance feedback and communication mechanisms, the application of performance management and corporate strategy, and the enthusiasm of employees to participate in performance management. The existing papers mainly focus on performance feedback and communication mechanisms, the application of performance management in line with company strategies, and the initiative of employees to participate in performance management. Neglecting the specific role of state-owned enterprises and not combining performance management with their social responsibility. In addition, the imperfect performance indicator system has also led to the problem of not being greatly influenced by subjective factors within the enterprise. The accuracy of performance evaluation in many enterprises is often influenced by human factors. The design of performance management evaluation indicators is not scientific, the evaluation is unfair, the concept of human resource management is lack of correctness, strategic planning, single evaluation results, ineffective use, lack of follow-up, and frequent communication in performance management; The recruitment and allocation of personnel are unreasonable, the construction of the management system is highly arbitrary, and there is a significant subjective bias in performance evaluation.

Spatial prediction of groundwater potential by various novel boosting-based ensemble learning models in mountainous areas

This study makes a significant contribution to the field of groundwater potential mapping (GWPM) by exploring the application of ensemble learning models (ELMs), specifically boosting ensemble models (BEMs), which have not been fully utilized in GWPM. By employing six ELMs (random forest, AdaBoost, XGBoost, CatBoost, GBDT and LightGBM), along with Tree-structured Parzen Estimator in Luoning County, China, this study identifies key indicators (topographic position index, distance to rivers and topographic wetness index) and demonstrates the superior model performance of XGBoost compared to other ELMs. Additionally, correlation analysis confirms the accuracy of XGBoost in predicting relationships between important indicators and groundwater potentials. Finally, the findings provide valuable insights for sustainable groundwater management strategies in Luoning County and emphasize the need for further exploration of ELMs, development of comprehensive performance evaluation and indicator systems, reduction of the inconsistencies between indicators and predication results and practical research to support future sustainable groundwater management.

Multi-objective optimization of an innovative fuel cell and biomass power system for hydrogen synthesis and injection using thermochemical cycle

This article presents an efficient energy system to generate power via renewable sources. Biomass is the running mover of a cycle that operates on a gasification process to generate syngas. The hot syngas is then used to create hydrogen via a green and sustainable method of hydrogen production called the vanadium chlorine cycle (VCLC). The generated hydrogen is mixed with the syngas before entering the PEM fuel cell. The proposed system's energy, exergy and economic impacts are examined. Also, the effect of different variables is studied on the system performance indexes. Finally, multi-objective optimization is implemented to ensure the highest efficiency and lowest cost. Results indicate that the moister content of the biomass, the PEMFC temperature, and current density play a crucial role in the system performance. Rising the PEMFC temperature and the moister content works in favor of the system performance indices, unlike the current density of the fuel cell. The results of the multi-objective optimization represent that under optimal conditions, when moisture content, PEM current density and temperature are chosen equal to 0.314, 0.71 A/cm2 and 360.78 K respectively, system has the exergy efficiency of 32.10% and total cost rate of 52.95 $/h.

Innovation of fresh agricultural products e-commerce operation mode based on artificial intelligence and machine learning model

Abstract In recent years, there has been an increasing interest in emotional interaction models based on artificial intelligence technology, and researchers want to deal with real-life problems in daily life through artificial intelligence and emotional interaction technology. In this paper, based on artificial intelligence and the emotional interaction model, we analyze the model architecture of emotional interaction technology and the theory related to the e-commerce operation platform. Combining the two, we propose a collaborative filtering recommendation algorithm, define system performance indexes, and recommend fresh produce to target customers with similar users’ evaluation of fresh produce through artificial intelligence technology. Using the experiments of three different recommendation systems and user behavior data of different months in the past three years as reference, it is concluded that the e-commerce operation of fresh produce based on AI and emotional interaction model can effectively improve the browsing and transaction volume of the e-commerce platform. This shows that artificial intelligence and emotional interaction model can be applied to create a new e-commerce operation mode, which provides research directions and methods for the diversified development of future e-commerce operation modes.

Parameter identification and position control for helical hydraulic rotary actuators based on particle swarm optimization

It is difficult to obtain an accurate mathematical model in electro-hydraulic servo control system, due to the nonlinear factors such as dead zone, saturation, flow coefficient, and friction. Hence, a parameter identification algorithm, combining recursive least squares (RLS) with modified nonlinear particle swarm optimization (NPSO) algorithm, is proposed. On this basis, another improved NPSO algorithm is also put forward, aiming at searching for the optimal proportional–integral (PI) controller gain of the nonlinear hydraulic system while giving comprehensive consideration to the system performance indexes. The system identification experiments and position tracking control are conducted, respectively. As indicated by the comparison with the least squares (LS), RLS, PSO, and RLS–LPSO results, the proposed method shows higher identification and control accuracy.

Assessment of Water Supply System Performance Indicators Based on the Customer Bill-Based Approach

Significant efforts have been undertaken over the last two decades by governmental organizations and local and international non-governmental sectors to improve water supply and sanitation structures; however, there are significant challenges to the town's growth and expansion. Chiro town's population is increasing, and the community is affected by water and excreta-borne diseases as a result of a lack of proper sanitation facilities and a water supply system. In this study, billed data from Chiro Town water supply service enterprise customers have been used to assess the performance of the water distribution network over ten years (2011-2020). The findings show that the Town's water coverage is 62.9%, the water demand is 8,121.6m3/day, and the computed annual water production is 4,222.3m3/day. Residents of the town have complained about a lack of access to improved drinking water supplies, low water consumption, and sanitation facilities, particularly in the community of those who live in the town's borders and practice open defecation. For all domestic use, 16.32% and 83.68% of respondents used unprotected and protected water sources, respectively. This study suggested that strong sectoral coordination, community involvement, and sufficient financial resources were required to identify the root causes and provide an efficient water supply system in the study area.

Impact of Digital Transformation of the Russian Higher Education System on the Need to Develop Competencies and Career Advancement of Scientific and Pedagogical Employees

Introduction. Distance learning, caused by the sanitary and epidemiological situation in the world, has led to the need to restructure the higher education system from the traditional full-time/offline attendance to a distance format. The use of the “newˮ format for higher education assumed the use of digital technologies, therefore there was a need for the formation of appropriate digital and “soft” competencies among the teaching and research staff of higher educational institutions. The purpose of the article is to analyze the satisfaction of teaching and research staff of Russian higher educational institutions with the system of professional and official promotion, their assessment of the need for general professional, organizational and managerial, information communication, regulatory legal and interpersonal competencies in the conditions of digital transformation of the higher education system of the Russian Federation. Materials and Methods. To identify the opinion of scientific and pedagogical workers about changes in the importance of competencies, the development of a business career, the authors conducted a sociological survey of 1,532 scientific and pedagogical workers of higher education. The monitoring was carried out taking into account methodological approaches developed with the participation of the scientific and educational laboratory of the Penza affiliated branch of the Financial University “Strategies for increasing the competitiveness of international activities of universities in the global digital space”. Results. According to the results of the sociological survey, a low level of satisfaction of scientific and pedagogical staff was revealed, caused by the presence of the following problem areas: the prevalence of paper reporting over the scientific and pedagogical activities of employees; excessive bureaucracy that hinders professional and official development; an incorrect system of performance indicators; the absence of a unified career development model for scientific and pedagogical staff of educational institutions. Practice-oriented recommendations have been developed in the field of digital and “softˮ competencies, the formation of a management system for the professional development of scientific and pedagogical staff. Discussion and Conclusion. The formulated theses contribute to the development of theoretical and methodological approaches to the study of the level of satisfaction of scientific and pedagogical staff of Russian universities. The presented materials of the article can be used for research purposes by scientists, researchers dealing with similar issues, as well as federal and regional executive authorities, higher educational organizations in the development of professional development programs for teaching staff.

Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach

International Energy Agency predicts that the global number of installed heat pumps (HP) will increase from 180 million in 2020 to approximately 600 million by 2030, covering 20% of buildings heating needs. Electric power consumption is one of the main key performance indicators for the heat pump systems from techno-economic perspective. However a common issue prevalent in many existing heat pumps is the lack of electric power measurement. The modern installations might be equipped with electric power measurement sensors but this comes at a higher system cost for the manufacturers and end-users. The primary objective of this work is to propose a virtual measurement for estimating power consumption, thereby eliminating the need for field measurement of power for heat pumps. To achieve the objective, a data-driven approach is proposed. Firstly, the in-situ data is preprocessed through data merging, cleaning, and normalization. Then, input features are pre-selected using Spearman correlation coefficients, and further refined by addressing multicollinearity problem. Following this, Extreme Gradient Boosting (XGBoost) models and polynomial models are developed by considering different features as inputs. All models are finally validated against the in-situ data from multi-units of ground source heat pump (GSHP) and air source heat pump (ASHP) installations. The results showed that the electric power consumption of GSHP can be estimated with high accuracy (99% for R2, 10 W for MAE, and 1% for MAPE) through generic data-driven models using only four easy-to-measure input features. Taking three input features as inputs for ASHP generic model, the accuracy can be reached to 83% for R2, 125 W for MAE, and 9% for MAPE. The method presented in this paper can be applied to estimate power consumption of millions of heat pumps and consequently add a significant value as well as provide different types of services, such as cost-saving benefits for manufacturers and end-users, flexibility services for aggregators and electricity grids.

Innovative instruments for increasing the efficiency of human resources management of IT-companies

The mechanism of improving the efficiency of human resources management at IT-companies updates the implementation of innovative management tools in the processes of hiring, developing, and evaluating their employees. The goal of the work is to deepen the theoretical and conceptual foundations of the effectiveness of HR management at IT-companies in the social and labor context and to develop scientific and applied recommendations regarding the mechanism of its enhancement in the conditions of formation of a new economy. Measures outlined in the paper to apply the competency approach, to introduce the talent management algorithm on a systematic basis, and to develop the system of key performance indicators should be considered as a component of scientific and practical recommendations for improving the efficiency of human resources management in IT enterprises in the social and labor dimension. In order to improve the efficiency of human resources management at IT enterprises, it is necessary to develop and introduce a perfect mechanism as a systemic integrity of economic, social, and organizational processes of creating preconditions for innovative development of the enterprise as a benefit for the employer and decent work as a benefit for the employees. The scientific platform of the theoretical and applied construct of such a mechanism should be the managerial paradigm of harmonization of social and labor relations, and its internal architectonics should be formed in compliance with the values of corporate social responsibility and contain innovative tools in the format of the goals and results management system in contrast to the functions management system. On the basis of understanding of the essence and regulatory consolidation of competencies as the ability of a person to perform a certain type of activity, the model of functional and behavioral competencies of the IT project manager is developed, the trajectory of development of talents in the field of computer programming is given, the methodological basis of construction and the algorithm of development of the key system are developed and performance indicators are implemented.

An instant inertia estimated and operation burden considered frequency regulation method for low inertia power systems

The application of virtual inertia (VI) has become a novel solution and new orientation for the frequency regulation of the high variable renewable energy (VRE) penetrated low inertia systems. How to provide a frequency regulation strategy for the system with VI is a key problem. Firstly, the power system is a multi inputs multi outputs (MIMO) system, in which the coupling characteristics of VI control and the primary and secondary frequency controls can’t be ignored. Secondly, the system inertia constant is time-varying and the estimation of it is crucial for gaining a satisfying regulation performance. This paper intends to provide a frequency regulation strategy for this problem. In this work, an Elman neural network (ENN) based inertia estimation with a deadband method is proposed for the identification of the system’s instant inertia. And the Laguerre function-based rate of change of frequency (ROCOF) constrained MIMO-MPC is constructed to provide the collaboration strategy. Then, the control parameters are tuned by the gravitational search algorithm (GSA) considering both the system performance indexes and the operation burden indexes. The proposed strategy is testified based on a three-area power system. The results prove not only the robustness of the controller but also the effectiveness of the ROCOF constraint, the operation burden index, and the instant inertia estimation method.

The role and influencing factors of government performance evaluation: A test of Chinese public officials’ perceptions in Gaoming district

Government performance evaluation has a long history. However, major differences of opinion regarding its role still exist both in Western and Chinese academia, from theoretical, and practical perspectives. In this article, we conduct an empirical measurement of the role played by government performance evaluation and construct a regression model to explore the major factors influencing public officials’ perception, relying on survey data from a district government of county level in Guangdong Province. The study reveals that the average value of 14 items measuring government performance evaluation was 3.36 points (out of a possible 5 points). The role of the government in setting annual objectives, tasks, and priorities, as well as strategic planning, and target setting, and strengthening departmental accountability, had the most significant effect on the perception of efficacy of performance evaluation, whereas departmental budget setting, resource allocation, and reduction of operating costs had the least effect. Furthermore, performance communication and feedback, as well as the validity of the performance indicator system, also significantly influence the perception of the role played by government performance evaluation. The article concludes with a discussion of the differences between government performance evaluation in the West and in China.

Development of a Low-Cost Remote Monitoring Solution for Solar Home System

Data generation and real-time monitoring frameworks in photovoltaic (PV) systems are critical to the solar system's performance assessment and evaluation. They allow for proper operation and contribute to the identification of device malfunctions before any significant damage occurs. The low-cost hardware for the remote data monitoring of PV systems was built to complete this task. The system proposes to use low-cost, easy-touse data entry and real-time tracking systems for a home-based solar system. In the system, sensors were used to obtain information on the state of the solar system and a user can view the information obtained from the four sensors used without delay from the website to check and validate system performance indices. The advanced data logger gets data from the four sensors which are ACS712 (Current), LDR (Light Intensity), BMP180 (Ambient air pressure and temperature), and DHT11 (Ambient Humidity). The data obtained are uploaded to the ThingSpeak platform where all the real-time tracking results can be seen so that the performance of the PV home system can be monitored. The total cost of developing the system is $28.52 USD (N13,690). The system was tested and the results obtained shows a true representation of the physical solar parameters. This systematic tracking structure is precise with the error rate tracking results of the solar system yield rate of less than 5%. The tracking system may be scaled to accommodate large Photo Voltaic systems. Keywords— Low-cost real-time solar tracking system, Photovoltaic, Solar Home System, ThingSpeak, Sensors.

Konsep Key Performance Indicator, Kompensasi Financial, dan Penghargaan: Mendongkrak Kinerja Karyawan

This study focuses on analyzing employee performance at BPR Kawan Malang, by considering Key Performance Indicator (KPI), financial compensation, and reward system factors. Employee performance is the result of the effort and energy they put into work. To improve and maintain this performance, productivity assessment is carried out through appropriate indicators, using KPIs. In addition to KPIs, financial compensation and reward systems also have a significant impact on performance. Compensation, as a form of reward, includes a wide range of benefits for employees and the organization. This process of reward distribution has an important role in encouraging good performance. This study aims to analyze the impact of KPIs, financial compensation, and reward systems on employee performance at BPR Kawan. Performance appraisal involves evaluating the extent to which employees meet established standards and communicating that information to employees. Data collection techniques using questionnaires. The method used is a quantitative approach with a sample of 33 employees of BPR Kawan Malang, selected through total sampling. The data analysis technique uses multiple regression analysis. The results showed that KPIs have a significant influence on employee performance, as well as compensation and reward systems with a value of 0.000 sig each; 0,008; 0.000 < 0.05. This conclusion underscores the importance of these elements in stimulating and maintaining superior performance. This research reveals that KPIs, financial compensation, and reward systems play an important role in shaping a work environment that encourages high performance at BPR Kawan Malang.

Performance of precision poverty alleviation through circular economy based on RS-SVM model in the context of rural revitalization

With the implementation of the rural revitalization strategy, the precision poverty alleviation through circular economy has become an important means of promoting rural development. In order to study the performance of circular economy precision poverty alleviation in rural revitalization, a performance research method based on Support Vector Machines is proposed. During the process, the rough set was introduced for the hidden feature analysis, and a precise poverty alleviation performance indicator system was established. Afterwards, the performance evaluation model was constructed and the genetic algorithm was introduced for parameter optimization. Finally, the performance of the research method was tested. The experimental results show that the research method only requires 15 evolutions to achieve a fitness value of approximately 0.021. In the test of the calculation results, the research method only had 2 points on the test set that differed by more than 0.2 from the standard value. In the F1 test, the research method increased to approximately 97.6 after 200 iterations on the test set. When conducting empirical analysis, the evaluation results obtained by the research method are basically consistent with the expert evaluation results. These results indicate that the research method has good performance and can accurately evaluate the performance of precision poverty alleviation, providing reference for poverty alleviation work.

Design and analysis of an innovative biomass-powered cogeneration system based on organic flash and supercritical carbon dioxide cycles

Technological advancements play a significant role in increasing energy demand. As societies progress, new technologies emerge, and they often require additional energy resources to operate. Therefore, it is important to design an efficient power system that can achieve higher performance. Additionally, considering the environmental aspect of the designed system is another crucial criterion for power system design. The current investigation proposes a renewable-based co-generation system for the production of power and heating load. The proposed system consists of several subsystems, including a municipal solid waste-driven gas turbine cycle, a supercritical CO2 cycle, and a high-temperature organic flash cycle. The system's performance is analyzed using energy, exergy, economic, and environmental approaches. Double-objective and triple-objective optimizations are applied to determine the optimum state of the system. The results indicate that the system can produce a net power of 8.21 MW and a heating load of 5.81 MW. This translates to energy and exergy efficiencies of 75.8 % and 41.21 % respectively, with a levelized CO2 emission of 0.518 t/kWh at the base-case. Furthermore, the system's payback period is estimated to be approximately 1.97 years, resulting in a net profit of 10.7 M$. In the parametric study, it was found that the gas turbine's inlet temperature has a significant impact on the system's performance indexes. Ultimately, the system achieves an exergy efficiency of 43.18 % and a levelized CO2 emission of 0.457 t/kWh at the optimum state. In conclusion, the proposed renewable-based co-generation system offers a promising solution for achieving higher performance, environmental sustainability, and economic viability in the design of efficient power systems. In conclusion, the proposed renewable-based co-generation system offers a promising solution for achieving higher performance, environmental sustainability, and economic viability in the design of efficient power systems.