Performance Evaluation Of System Research Articles

Performance evaluation of geothermal assisted VAC systems for residential cooling purposes

Performance evaluation of geothermal assisted VAC systems for residential cooling purposes

Low-complexity detector performance evaluation for cell-free massive MIMO systems

Low-complexity detector performance evaluation for cell-free massive MIMO systems

Performance Evaluation of the Vertical Layered UWOC System With Spatial Diversity

Performance Evaluation of the Vertical Layered UWOC System With Spatial Diversity

Performance evaluation of multi-stage manufacturing systems operating under feedback and feedforward quality control loops

In manufacturing, the essential product characteristics are often created through multiple stages. Coupling product data obtained through inspection and controllers based on decision models with prediction capabilities enables quality control loops, enhancing both feedback and feedforward mechanisms. This paper proposes a methodology to merge the formulation of feedback and feedforward quality control loops into a performance evaluation model for multi-stage manufacturing systems. This approach evaluates quality control loop impacts system-wide, aiding in configuring and reconfiguring quality gates. A case study illustrates how allocating inspection technologies and efficient decision models improves overall system performance through effective feedback and feedforward control loops.

Performance Evaluation of Spatio-temporal Data Retention System Supporting a Floating Cyber-physical System

Performance Evaluation of Spatio-temporal Data Retention System Supporting a Floating Cyber-physical System

Performance and cost evaluation of an adaptive queuing system with customer reneging and retention: steady-state and transient analysis

Performance and cost evaluation of an adaptive queuing system with customer reneging and retention: steady-state and transient analysis

Evaluation of General-Purpose and Real-Time Operating Systems Performance for Multi-Robot Systems Path Planning

Evaluation of General-Purpose and Real-Time Operating Systems Performance for Multi-Robot Systems Path Planning

Production control problem for multi-product multi-resource make-to-stock systems

Most of today's production systems are working with parallel production resources to increase throughput rate due to the increase in high variability in demand and product mix. Effective control and performance evaluation of such systems is of paramount importance to minimize production and inventory-related costs. We examine a production-inventory system featuring parallel production resources capable of producing various products. In many industries such as automotive, white goods, electronics, and paint, multiple/parallel production resources are widely used to produce the ideal amount and satisfy incoming demands for distinct products. In this study, shortage cost is not restricted to only one type and both lost sales and backordering cases are analyzed. In order to analyze the optimal production policies' behavior, we initially formulate dynamic programming models for both lost sales and backordering systems, treating them as Markov Decision Processes. Subsequently, we solve these models using the value iteration algorithm. Given the challenges posed by the curse of dimensionality in the value iteration algorithm, we suggest alternative heuristic production policies. These policies extend the existing ones described for multi-item single-resource make-to-stock (MTS) systems to accommodate multiple resources. We construct simulation models to assess the efficacy of the heuristic policies, conducting comparisons of their performance against both the optimal policy and among one another. To the best of our knowledge, there has been no exploration of scenarios involving multiple production resources concurrently manufacturing distinct products in a MTS environment. Hence, this study serves as an extension to the examination of multi-item, multi-production resource MTS systems.

Performance Evaluation of Strapdown Inertial Navigation and Beidou Satellite Navigation System Based on Intelligent Image Processing Technology

Performance Evaluation of Strapdown Inertial Navigation and Beidou Satellite Navigation System Based on Intelligent Image Processing Technology

Prospects of Digital Twin for Dynamic Life Cycle Assessment of Smart Manufacturing Systems

Smart manufacturing systems are poised to revolutionize industrial processes by leveraging advanced technologies for increased efficiency and productivity. However, alongside these advancements, there is a growing imperative to address environmental sustainability concerns. Conventional static life cycle assessment (LCA) methods often provide valuable insights into the environmental impacts of such manufacturing systems but often fall short in capturing real-time data and dynamic system interactions. Further, using the digital twin technology, physical assets can be virtually replicated in order to monitor, evaluate, and improve the particular manufacturing system. The dynamic properties can be effectively brought to LCA investigations by utilizing this technique. This paper explores the prospects of integrating digital twin technology for facilitating the dynamic LCA to enable comprehensive and timely environmental performance evaluation of smart manufacturing systems. We discuss the concepts, technological components, and potential applications of digital twin-enabled dynamic LCA, along with challenges and future research directions.

Applications and Challenges of AI Technology in Financial Portfolio Management

With the rapid development of artificial intelligence technology, financial portfolio management has entered a new era characterized by data-driven and intelligent decision-making. Based on the customer- centered service philosophy, managers propose intelligent investment strategies that better meet market demand. Based on the dynamic development of AI technology, we build a theoretical analysis framework for intelligent portfolio management according to the internal logic of the financial market, which can explain the intelligent development mechanism consisting of the investment decision mechanism and risk control cycle mechanism of machine learning and quantitative analysis. Furthermore, we explore opportunities to move towards high-quality development goals from the perspective of practical changes and technological applications in financial portfolio management. The role of AI technology in financial portfolio management is to provide investors with investment portfolios that meet their personalized needs. Researchers are committed to continuously improving the quality of investment strategies and enhancing satisfaction. Therefore, it is necessary to strengthen portfolio control based on internal quality data flow, establish an interaction and risk assessment mechanism between investors' preferences and market performance quality perception, and establish a performance and market environment evaluation system to achieve qualitative evaluation and market performance evaluation, to realize the high-quality development of financial portfolio management, promote the stability and prosperity of the financial market, and truly meet the diversifying needs of investors.

Value Stacking of a Customer-Sited BESS for Distribution Grid Support: A Utility Case

This paper proposes a value stacking strategy for a utility-owned, customer-sited battery energy storage system for distribution grid support. The proposed strategy includes three steps: application identification, performance evaluation, and battery system planning. Outage mitigation, non-wires-alternative solution, and voltage support are identified as the primary, secondary, and tertiary applications for the proposed storage system. Reliability performance and economic benefit are calculated and compared for each application in five locations in the Commonwealth of Virginia. Planning results including placement, sizing and scheduling of the battery system are presented with real utility experience and constraints. This work contributes to providing a general and ready-to-use planning methodology for distribution system planners to deploy battery storage systems within service territories, strengthen system reliability performance, and achieve sustainability goals.

Rescue and safety system development and performance evaluation by network reliability

Rescue and safety system development and performance evaluation by network reliability

Real-Time Monitoring of Neonatal Incubator Parameters Via Iot-Integrated Device: Design, Implementation, and Evaluation

The Internet of Things (IoT) has revolutionized healthcare solutions’ design, construction, and deployment. This research project focuses on developing an external device incorporating Internet of Things (IoT) technology for real-time monitoring of neonatal incubator parameters in sub-Saharan Africa. This IoT is intended to monitor real-time vital signs such as body temperature, humidity, pulse rate, oxygen concentration, air quality, and the sound level of the immediate environment and transmit the data via a mobile application. The Internet of Things has a micro controller for storing temporal sensor data. Temperature, humidity, and heart rate sensors monitor temperature, humidity, pulse oximetry, and heart rate, respectively, and a gas sensor detects harmful gases. The mic sensor detects abnormal sound levels around the incubator, while the Wi-Fi module provides the micro controller access to a Wi-Fi network. The sensor data is sent to a cloud-based platform that houses the data, analysis, and retrieval. This research paper contains the details of system design, implementation, and performance evaluation. The evaluation findings reveal the device to be trus table and accurate, providing neonate caregivers with valuable information.

A Mathematical Approach to Ullmann Reaction: ANFIS Computing of a Chemical Retrial Queue Model under Hybrid Vacation

Herein, we developed the first report on the chemical retrial queue and hybrid vacation process for the significant Ullmann coupling for enhanced high-throughput reaction discovery. The problem of controlling the waiting time for chemical retrials is addressed here. We incorporated the supplementary variables method (SVT) and generated the steady-state probability generating function (PGF) for system size and orbit size. Important cases are outlined, and a few key metrics are utilized to evaluate system performance. Additionally, the impact of changing certain system parameters has also been analyzed via numerical examples. One particularly interesting aspect of this research is the comparison of neuro-fuzzy technique results with validation results utilizing the "adaptive neuro-fuzzy inference system" (ANFIS).

Performance assessment of a modified air-gap and water-gap membrane distillation systems

This work experimentally evaluates and compares the performance of four membrane distillation (MD) units with and without an internal gap rotating impeller blade. The novelty of the current study lies in the installed impeller within the condensation cavity and the impeller design parameters. The investigated MD units include a novel modified water-gap MD (M-WGMD) system featuring an internal impeller blade; a novel modified air-gap MD (M-AGMD) system with an internally rotating impeller blade; a regular water-gap MD (WGMD) process; and a conventional air-gap MD (AGMD) system. The evaluated system performance index includes gained output ratio (GOR) and vapor flux. The performance of the four MD systems is assessed and compared against each other under the same test conditions for various system design and operating variables, including impeller blade material, impeller blade angle, saline feed temperature, coolant temperature, and saline feed flowrate. Findings indicate that M-WGMD and WGMD systems (modified and conventional) produce higher flux than M-AGMD and AGMD units. Meanwhile, air-gap MD units (AGMD and M-AGMD) exhibits better energy efficient (higher GOR) than WGMD and M-WGMD systems. Furthermore, modified MD systems recorded superior performance compared to conventional MD systems and the blade angle effect is more influential than the blade material. At 80 °C feed temperature and 3200 mg/L feed salinity, the M-WGMD reaches a maximum flux of 128.39 kg/m2h and a GOR of 0.7702. On the other hand, the WGMD attained a flux of 67.32 kg/m2h and a GOR of 0.6199. The M-AGMD recorded a flux of 30.20 kg/m2h and a GOR of 0.8696. For the AGMD system, the GOR and the flux values are 0.7357 and 15.58 kg/m2h, respectively.

ETAP software based power flow analysis of 225/60/11KV substation in Tinghir

Through technological advances, such as computer-based software, it is now possible to study and analyze complex electrical system problems and identify potential solutions. This analysis typically includes Load flow analysis (LFA), or power flow analysis (PFA). LFA is a crucial tool in power system engineering used for modeling and designing electrical power networks. It aims to determine the steady-state operating conditions of a power system to ensure a stable and efficient power balance between generation and load demands. LFA helps design robust power networks, maintains system stability, plans maintenance activities, and assists in the economic dispatch of power generation. This study focuses on modelling the 225/60/11 kV substation in Tinghir, a predominantly rural subdivision of the Drâa-Tafilalet region of Morocco. The model used data obtained from SPIE Maroc, specialists in industrial and tertiary electricity. AC and DC load flow analysis is performed on the Tinghir substation auxiliary services under two scenarios: one where the service equipment is powered by the auxiliary service transformer (AST) as the primary source, and another where the equipment supplied by a generator set due to a failure in the main power supply. ETAP software is selected for the simulation due to its advanced real-time power management capabilities and is widely used in power generation, transmission, and distribution systems. The Newton-Raphson method, known for its fast convergence and accuracy, is used for power flow analysis, making it ideal for complex systems. The results evaluate system performance under both normal and backup conditions, ensuring reliable operation of the auxiliary service installation at Tinghir’s substation.

Internal Audit Evaluation and its Optimization in Universities under the Great Intelligence and Cloud Technology

Abstract This study delves into the critical role of Dazhimian technology in enhancing the evaluation of internal audit in universities and its optimization process. Firstly, a balanced scorecard-based internal audit performance evaluation system for universities was constructed, which covers four dimensions, namely, functional performance, service object, internal management process, learning and growth, and is further refined into 25 evaluation indexes. Then, the entropy weight-TOPSIS evaluation model was used and combined with actual data for empirical analysis, thus effectively measuring internal audit performance. Specifically for the case study, College F as a research subject shows significant performance improvement. The functional performance weight is as high as 0.3574, significantly higher than other dimensions, reflecting its outstanding performance in improving internal audit performance. Comprehensively analyzing the horizontal and vertical comparisons, HEI F has been improving its internal audit performance and its relative closeness is leading in all dimensions. In addition, we find that the quality of internal auditing in HEIs has a significant positive impact on profitability, operational capability and sustainable Development, further confirming the importance of optimizing the internal audit system. This study provides an effective technical tool for evaluating internal audit and its optimization in universities and valuable references and lessons for other universities.

Designing a Human Resource Development Model in Iran's National Football with a Grounded Theory Approach

The aim of this research was to design a human resource development model in Iran’s national football using a grounded theory approach. The research method was analytical, and qualitative methodology was employed for this purpose. The research strategy involved the use of grounded theory. The participants in the study consisted of 15 individuals from the target population, including experts in sports management, managers and officials from the Football Federation, and researchers in the field of human resource performance management. The sampling strategy in the qualitative section was purposeful, with maximum diversity or heterogeneity. Data analysis was carried out through content analysis of interviews and coding. The research tool was open interviews, and the results were analyzed based on three stages of open, axial, and selective coding. The findings indicated that a development-oriented federation, securing benefits, having a proper structure, and the managerial characteristics of the federation were the indicators of causal factors. Contextual factors included an efficient administrative structure, ethical orientation, standardization of the federation's statute, creating and utilizing appropriate infrastructure, fostering organizational health, and monitoring and controlling performance. Moreover, intervening factors included social changes, attention to grassroots and cultural foundations, controlling corruption, and adhering to Islamic and ethical principles. The core phenomenon was future-oriented, merit-based, and people-centered. The research strategies included improving the monitoring process, moving toward legal compliance, establishing a performance evaluation system for employees, developing human resource competencies, and empowering the workforce. Ultimately, the outcomes of the research were citizen satisfaction, productivity, sustainable sports economy, federation efficiency, and promoting responsibility.

Construction of Intelligent Financial Management Platform Based on Industry-Finance Integration

Abstract Exploring the Construction of intelligent financial management platform based on integrating industry and finance is aimed at improving enterprises’ financial efficiency and management level and realizing the efficient Integration of finance and business. This study centers on an in-depth discussion on the Construction of an intelligent financial management platform that integrates industry and finance. The study finds that integration problems between enterprise finance and business management, such as separation of information systems and insufficient performance evaluation system, lead to interdepartmental cooperation and coordination problems. The proposed intelligent financial management platform is based on ERP and CRM systems and processes data through ETL tools to achieve information sharing. The functional Construction of the platform relies on value correction and knowledge transformation of financial big data, and uses multiple linear regression models to optimize data processing. Empirical studies show that Group T has significantly improved its financial efficiency and management level through the implementation of the platform, which is reflected in the reduction of accounting personnel by 60.22% and the significant shortening of the average audit time of finance. Furthermore, fund management capability was improved, management expenses and expenses were decreased, and performance assessment was more comprehensive. The study concludes that the effective implementation of the intelligent financial management platform can significantly improve the effect of the enterprise’s industry-finance Integration, and promote the enterprise’s overall operational efficiency and competitiveness.