Operational Performance Evaluation Research Articles

Circular Patch Antenna with Quintuple Band Operation Design Analysis and Performance Evaluation for Multi-Frequency Applications

Circular Patch Antenna with Quintuple Band Operation Design Analysis and Performance Evaluation for Multi-Frequency Applications

A machine learning-based algorithm for automated detection of frequency-based events in recorded time series of sensor data

Automated event detection methods, vital for monitoring technical systems via sensor data, are highly sought after in the automotive industry for tracing events in time series data. For assessing the active vehicle safety systems, a diverse range of driving scenarios is conducted. These scenarios involve the recording of the vehicle's behavior using external sensors, enabling the evaluation of operational performance. In such setting, automated detection methods not only accelerate but also standardize and objectify the evaluation by avoiding subjective, human-based appraisals in the data inspection. This study introduces a novel method for identifying frequency-based events in time series data. To this aim, the time series data is mapped to representations in the time-frequency domain, known as scalograms. After filtering scalograms to enhance relevant parts of the signal, an object detection model is trained to detect the desired event objects in the scalograms. By leveraging the accuracy of object detection networks in localizing objects, precise time intervals of events are identified. For the analysis of unseen time series data, events can be detected in their scalograms with the trained object detection model and are thereafter mapped back to the time series data to mark the corresponding time interval. The algorithm, evaluated on unseen datasets, achieves a precision rate of 0.97 in event detection, providing sharp time interval boundaries whose accurate indication by human visual inspection is challenging. Incorporating this method into the vehicle development process enhances the accuracy and reliability of event detection, which holds major importance for rapid testing analysis.

Evaluation of Operating Performance of Listed Companies in Taiwan’s Tourism Industry - Application of Data Envelopment Analysis

Data envelopment analysis is an efficiency measurement method proposed by Charnes, Cooper and Rhodes in 1978, including CCR model efficiency analysis and BCC model efficiency analysis, which is used to evaluate the relative efficiency of decision-making units. The measured efficiency value is the most favorable result of the evaluated unit under objective circumstances. This article applies data envelopment analysis method to evaluate the performance of listed companies in Taiwan's tourism industry. After analysis, it was found that the total efficiency of the six tourism industries including Huayuan, No. 1 Store, Gourmet KY, Wangpin, Xiongshi, and Holaday is effective, while the total efficiency of the three tourism industries including Farglory, Phoenix, and Xintiandi is not Effective, but technical efficiency is still effective. Except for the tourism industry whose total efficiency is effective, its returns to scale remain unchanged. Two tourism industries, such as Guobin and Jinghua, have diminishing returns to scale because their return to scale value is >1 and should reduce their business scale. The returns to scale of other tourism industries are all Increasingly, it is recommended to expand the scale of operations.

Operation optimization and performance evaluation of a ventilated heating floor in a nearly-zero-energy building with mixed power

With the proportion of renewable energy in the construction sector increasing and the structure of energy systems becoming increasingly complex, it is crucial to optimize the operation strategy of building energy systems with thermal energy storage for improving multi-performance. However, conventional heuristic optimization algorithm exhibits low searching speed and converges slowly, which is hard for operation optimization of such systems. In this study, with a binary particle swarm optimization (BPSO) algorithm coupled with experience-based searching guiding strategy, the operation of a ventilated floor heating system in a nearly-zero-energy building was optimized . System performance under different optimization objectives and combinations, including reducing operation cost and carbon emission fee, meanwhile increasing wind power consumption and thermal comfort time, was investigated. Results show that with the experience-based accelerating strategy, the BPSO algorithm converged fast and found more reasonable solutions. In contrast, multi-objective optimization yielded better and diverse feasible solutions were found than single-objective optimization. By optimizing operating costs, wind power consumption, and environmental costs, the best comprehensive solution was obtained. The cost range of energy consumption and carbon emissions within 10 days is 19.24–22.17 yuan and 17.45–20.11 yuan, respectively. The proportion of thermal comfort time is 95.39–95.82%. However, due to high thermal insulation level, thermal comfort time under different optimization objectives showed little difference.

The Feasibility and Operational Performance of Implementation Median U-turn Intersections: A CRITIC Method

Currently, a growing number of cities are adopting the Median-U-Turn (MUT) intersection design to enhance road capacity and traffic efficiency. The critical question in selecting the right intersection design is how significantly the implementation of MUT can enhance intersection performance, focusing on three key aspects: intersection efficiency, capacity, and the environmental impact of the design. To address this question, an evaluation of operational performance under various prevailing conditions (roadway and control) was conducted using VISSIM, a microscopic simulation platform. This evaluation involved five scenarios: conventional intersections (with increased cycle length, grade separation with a signalized at-grade intersection, grade separation with a roundabout), MUT, and signalized crossover MUT at a dense urban arterial intersection in Amman, Jordan's capital. The performance was compared using several metrics: average control delay, number of stops, average travel speed and time, average stopped delay, Carbon Monoxide (CO) emissions, fuel consumption, and vehicle safety. The Criteria Importance Through Intercriteria Correlation (CRITIC) technique was subsequently used to select the optimal design. The findings indicate that the existing intersection configuration is the least effective, while the MUT with signals at the crossing U-turn points is the most efficient solution.

Evaluation of operational efficiency and performance for a water treatment plant

The current study presents a comprehensive analysis of the operational efficiency and performance evaluation of the Hazelmere Water Treatment Plant over the period from 1999 to 2018. By focusing on the removal efficiencies of few parameters including iron (Fe), turbidity, and E. coli, the study provides valuable insights into the plant's ability to treat water effectively and produce high-quality drinking water. Leveraging data analysis techniques and computational tools, the research also explores the forecasting of water quality parameters beyond the study period, enhancing predictive capabilities for monitoring and managing water quality in the future. The Hazelmere Water Treatment Plant (WTP) has a daily capacity of 75 Ml it supplies water to the surroundings. Its intricate treatment process, featuring chemical dosing, clarification, filtration, and disinfection, operates harmoniously. The plant consistently exceeded global standards. Effluent turbidity consistently met stringent World Health Organization/South African National (WHO/SANS) discharge standards at ≤ 1 NTU. The turbidity removal efficiencies ranged from 65.88 to 99.61 % on average over the period from 1999 to 2018. Iron removal also adhered to WHO/SANS criteria, registering ≤ 2 mg/L. The removal efficiencies have ranged from 82 to 99% on average for the same period. Most impressively, E. coli removal efficiency maintained a flawless 100 % for the same period, indicating a pathogen-free effluent throughout the period, with a steady annual average of 0 MPN/100 m, some challenges have occurred including the contamination of the freshwater from the dam, the limited data availability, and issues related to sustainability and compliance. These challenges were overcome by using advanced tools for data analyses such as R package, developing a performance evaluation framework and establishing recommendations for the adoption of innovative technologies, and improvements in operation and maintenance practices. Overall, this study makes significant contributions to the field of wastewater treatment and water quality management, advancing our understanding of sustainable water resource management and environmental protection.

Method for Identification of Aberrations in Operational Data of Maritime Vessels and Sources Investigation.

Sensing data from vessel operations are of great importance in reflecting operational performance and facilitating proper decision-making. In this paper, statistical analyses of vessel operational data are first conducted to compare manual noon reports and autolog data from sensors. Then, new indicators to identify data aberrations are proposed, which are the errors between the reported values from operational data and the expected values of different parameters based on baseline models and relevant sailing conditions. A method to detect aberrations based on the new indicators in terms of the reported power is then investigated, as there are two independent measured power values. In this method, a sliding window that moves forward along time is implemented, and the coefficient of variation (CV) is calculated for comparison. Case studies are carried out to detect aberrations in autolog and noon data from a commercial vessel using the new indicator. An analysis to explore the source of the deviation is also conducted, aiming to find the most reliable value in operations. The method is shown to be effective for practical use in detecting aberrations, having been initially tested on both autolog and noon report from four different commercial vessels in 14 vessel years. Approximately one triggered period per vessel per year with a conclusive deviation source is diagnosed by the proposed method. The investigation of this research will facilitate a better evaluation of operational performance, which is beneficial to both the vessel operators and crew.

Pathology of the Research Sector in Iran's Health System with a Focus on Future

Background: Strengthening the functions of health research and taking a systematic approach to the development of science and technology are essential for overcoming current challenges in health sector. Therefore, the functional pathology of current research plays a crucial role in highlighting the gap between what is and what should be, thereby illuminating the path of scientific development in health sector with a focus on current challenges.
 Methods: This study utilized qualitative exploratory approaches, regarding interviews with experts and expert panel formation, to complement the authors' experiences in the field of research. In this process, relevant national upstream documents, experiences from other countries, and reviews of other documents were used to reinforce and analyze the findings. To adopt a future-oriented approach, the Future Triangle framework was employed to depict the tension between future images, the weight of past experiences, and the pressure of the current time.
 Results: The research functions were categorized into seven groups: leadership and guidance, research coordination and policy-making, translating upstream documents policies into operational programs, resource management, performance evaluation and monitoring, empowering the workforce and policy-making based on evidence and pathology. Under each category, strategies for moving away from the current situation were provided.
 Conclusion: The main solutions to address the current challenges in the country's health research system include agreement on concepts, a unified vision and stable procedures, strengthening the relationship between different levels of management (inter-ministerial, ministerial, and university), enhancing education and research at the level of medical ministry and universities, establishing appropriate structures for knowledge translation, strengthening national funds supporting the research, reforming the evaluation system, and undertaking a fundamental review of human resource empowerment model.

Combustion enhancement of boron-containing fuel-rich mixture by steam reforming in a supersonic flow

In this paper, a novel experimental investigation was conducted to enhance the combustion of boron-containing fuel-rich mixture by steam reforming in a supersonic flow. The ground direct-connected experiments were designed to simulate a flight condition at Mach number 5.9 and an altitude of 25 km. The operating characteristics and performance evaluation of the scramjet combustor were analyzed and discussed. The experimental results demonstrate that steam reforming can enhance the combustion of boron-containing fuel-rich mixtures in the supersonic flow. The performance of the combustor is firstly enhanced and then weakened with the increase of the steam-fuel ratio. The optimal steam-fuel ratio is approximately 0.189, which maximizes performance. At this steam-fuel ratio, combustion efficiency reaches 0.451, which is 9.9 % and 7.4 % higher than steam-fuel ratios of 0 and 0.395, respectively. The possible mechanism of steam reforming promoting boron combustion in the supersonic mainstream is explained. Steam accelerates the removal of the liquid oxide layer surrounding the boron particle, then combines with oxygen to produce hydrogen with good ignition-combustion characteristics and a new oxide layer. The cycle continues until the boron burns out. These conclusions can promote an understanding of enhancing the combustion of boron-containing fuel-rich mixture by steam reforming in the supersonic flow.

Multi-bit MRAM based high performance neuromorphic accelerator for image classification

Binary neural networks (BNNs) are the most efficient solution to bridge the design gap of the hardware implementation of neural networks in a resource-constrained environment. Spintronics is a prominent technology among emerging fields for next-generation on-chip non-volatile memory. Spin transfer torque (STT) and spin-orbit torque (SOT) based magnetic random-access memory (MRAM) offer non-volatility and negligible static power. Over the last few years, STT and SOT-based multilevel spintronic memories have emerged as a promising solution to attain high storage density. This paper presents the operation principle and performance evaluation of spintronics-based single-bit STT and SOT MRAM, dual-level cells, three-level cells (TLCs), and four-level cells. Further, multi-layer perceptron architectures have been utilized to perform MNIST image classification with these multilevel devices. The performance of the complete system level consisting of crossbar arrays with various MRAM bit cells in terms of area, energy, and latency is evaluated. The throughput efficiency of the BNN accelerator using TLCs is 26.6X, and 3.61X higher than conventional single-bit STT-MRAM, and SOT-MRAM respectively.

The research of touch screen usability in civil aircraft cockpit.

With the advancement of touch screen technology, the application of touch screens in civil aircraft cockpits has become increasingly popular. However, further analysis and research are required to fully promote its applications. The paper researched the usability of touch screens in aircraft cockpit considering the operation performance and subjective NASA-TLX workload evaluation, conducted experimental research on three touch gestures: click, drag, and zoom. Additionally, a comparative analysis was conducted on the touch performance under different layouts, positions, touch sizes, dragging direction angles, and zoom multiples. The touch performance indicators include operation time, error rate, operation speed, and workload. The experimental results show that the 21 mm size has the minimum operation time and workload, and 18 mm size has the lowest error rate in the clicking tasks. Additionally, the performance and workload of the captain's layout are better than those of the co-pilot's layout, and the performance of the center console position is best. The operation speed of the dragging tasks is faster when performed at position R3 compared to other positions. The dragging moving angles with better operation speed are 80°-190° and 250°-290°. The operation performance and workload of the zooming tasks vary depending on the zoom multiples. As the multiple increases, the operation time and workload also increase. There is no difference in operation performance or workload between zooming in and zooming out. The paper provides experimental support and suggestions based on human operation and subjective NASA-TLX workload evaluation for the application of touch screens in civil aircraft cockpits.

Enhanced LogTODIM-TOPSIS framework for interval-valued intuitionistic fuzzy MAGDM and applications to intangible assets operational management performance evaluation of commercial sporting events

The effective operation of intangible assets in commercial sports events can bring long-term, sustainable, and large-scale economic benefits to sports events. However, currently, in the operation of commercial sports events, the lack of experience in hosting events often hinders the development of intangible assets that should have created higher profits, and cannot achieve the expected value. The intangible assets operational management performance (IAOMP) evaluation of commercial sporting events is the multiple-attribute group decision-making (MAGDM). The Logarithmic TODIM (LogTODIM) and TOPSIS technique was brought forward the MAGDM. The interval-valued intuitionistic fuzzy sets (IVIFSs) are brought forward as the useful technique for coping with uncertain and fuzzy information during the IAOMP evaluation of commercial sporting events. In this study, the interval-valued intuitionistic fuzzy number Logarithmic TODIM-TOPSIS (IVIFN-LogTODIM-TOPSIS) technique is brought forward the MAGDM under IVIFSs circumstances. Finally, the numerical example for IAOMP evaluation of commercial sporting events is brought forward to verify the IVIFN-LogTODIM-TOPSIS technique. The main contribution of this study is brought forward: (1) the LogTODIM-TOPSIS was extended to IVIFSs in light with MEREC model; (2) the MEREC model is brought forward to derive weight in light with score information values under IVIFSs circumstances. (3) the IVIFN-LogTODIM-TOPSIS is brought forward for MAGDM under IVIFSs circumstances; (4) the numerical example for IAOMP evaluation of commercial sporting events and several different comparative analysis is brought forward to verify the IVIFN-LogTODIM-TOPSIS model.

Assessing the Impact of Metrics on the Choice of Prognostic Methodologies

Over the past years, advanced prognostic models and approaches have been developed. Most existing approaches are tailored to one specific system and cannot adaptively be used on different systems. This can lead to years of research and expertise being put into implementing prognostic models without the capacity to predict system failures, either because of a lack of data or data quality or because failure behavior cannot be captured by data-driven models. In addition, prognostic models are often evaluated using metrics only related to the correctness of predictions, preventing meaningful evaluation of operational performance. This paper makes use of a framework that can automatically choose prognostic settings based on specific system data. It simultaneously optimizes the choice of methodologies using metrics that capture multiple aspects of prediction quality. We apply this framework to both a simulated data set and a real aircraft data set to characterize the impact of metrics on the choice of prognostic methodologies. The results show that the choice of optimization metric greatly impacts the output of the generic prognostic framework and the overall performance. In addition, a definition for data suitability is provided and assessed on the aircraft system data sets.

Operational performance evaluation of a container terminal using data mining and simulation

The efficient operation of container terminals facilitates the seamless flow of goods across borders. New technologies such as big data, data mining, and simulation models, have emerged in the maritime industry, enabling optimization and performance evaluation. This study investigated how data science using operational data can improve container terminal operations, drive efficiency, enhance throughput, and bolster competitiveness in the shipping sector. Decision-making within container terminals, particularly in determining optimal container stacking locations, poses a significant challenge owing to the multitude of factors at play. By analyzing the datasets, new strategies and policies can be simulated to minimize container rehandling operations. This study focuses on the Hakata International Container Terminal in Japan, where daily operational data from rubber-tired gantry equipment are used to investigate container movements. A significant reduction in the total number of movements required to perform container-handling operations was demonstrated by implementing data-driven strategies and simulation modeling.

Manufacturing Process and System Sustainability Analysis Tool: A Proof-of-Concept for Teaching Sustainable Product Design and Manufacturing Engineering

Abstract Decision support methods and tools have been developed to aid in improving product sustainability performance during design. However, these approaches are often developed for domain experts and not well-suited for non-expert decision makers (e.g., engineering students and engineering practitioners), who do not possess specialized knowledge in sustainability analysis of product designs and manufacturing processes. The objective of this research is to facilitate the sustainability performance analysis of manufacturing processes and systems through unit manufacturing process (UMP) modeling within an easy-to-use, publicly-available product design, and manufacturing analysis tool. To achieve this objective, a sustainability assessment framework is developed that considers a cradle-to-gate life cycle scope and has four phases: (1) product development, (2) supply chain configuration, (3) manufacturing process design, and (4) manufacturing process and system (MaPS) sustainability analysis. To implement this framework and to address the identified limitations of existing tools, a proof-of-concept MaPS sustainability analysis tool is developed as a spreadsheet software tool. The tool supports the evaluation of environmental (energy and associated carbon footprint), economic (the cost of goods sold), and social (worker safety) impacts. While this study focuses on the technical aspects of the research, the authors investigate associated educational aspects in a separate study and report tool operational performance evaluation by undergraduate and graduate engineering students. Study participants found the tool easy to use and useful in completing sustainability assessment tasks in product design and manufacturing. To build upon this research, the developed framework and tool can be expanded to consider other phases of the product life cycle. Moreover, key software tool operational characteristics and graphical user interfaces should be investigated to improve efficiency, effectiveness, satisfaction, and learnability of the MaPS sustainability analysis tool.

Evaluation of Operational Performance of Intersection and Optimizing Signal Timing: A Case Study of the Buspark Intersection in Birgunj Metropolitan

Evaluation of Operational Performance of Intersection and Optimizing Signal Timing: A Case Study of the Buspark Intersection in Birgunj Metropolitan

Research on a new-designed Venturi ejector and dazomet particle motion characteristics for dilute-phase pneumatic conveying systems based on CFD-DEM

To disperse dazomet, a commonly used soil fumigant for soil disinfection, over large soil surfaces, dilute-phase pneumatic conveying can be utilized. Currently, most research has focused on pneumatic conveying systems for large particles, such as coal conveying or pneumatic seeding However, there has been almost no research on the dilute-phase pneumatic conveying of dazomet particles. Therefore, a coupled simulation model based on computational fluid dynamics and discrete element method (CFD-DEM) was established to study the effect of the structural parameters of the Venturi ejector on the motion of particles and airflow fields variation characteristics for the pneumatic conveying system of dazomet particles. Based on the Box–Behnken experimental design method, a 3-factor and 3-level response surface simulation experiment was carried out by selecting the contraction angle, throat diameter, and diffusion angle of the Venturi ejector as factors. The suction-flow ratio, average velocity of particles, average coordinates of particles in the vertical direction, and corresponding standard deviation at the outlet of the pipeline were chosen as response indexes. Multiple linear regression models were established between each factor and response index. The simulation results showed that the impact of factors on the 4 response indexes from strong to weak were throat diameter, contraction angle, and diffusion angle. With decreasing throat diameter, the suction flow ratio and average velocity of the particles increased. The average coordinates of the particles in the vertical direction decreased, while the standard deviation increased, indicating that the pneumatic conveying performance of the system increased. The optimal structural parameters for the contraction angle, throat diameter, and diffusion angle were 34.5°, 15 mm, and 12.0°, respectively. The experimental results demonstrated that the application precisions of the optimised Venturi ejector were 99.23%, 98.46%, and 98.56% at application rates of 15, 20, and 25 g/s, respectively. The results provide a theoretical reference for the structural optimisation of the Venturi ejector and operational performance evaluation of the pneumatic conveying system for dazomet particles.

Evaluation of long-term operational and production performance of biofloc technology (BFT) system within various particle size

Biofloc technology (BFT) is a promising technique, but there has been ongoing debate between biofloc's properties and particle size. This study investigated the relationship between long-term particle size variation and the production performance of BFT aquaculture systems. External shearing force introduction could keep bioflocs at a smaller size level chronically, and 97% of smaller bioflocs were below 181.97 μm which was obviously lower than the normal size group (Control). No significant difference in the daily water treatment capacity for bioflocs within different particle size was detected (p > 0.05), but the activity of Soil-Dehydrogenase (S-DHA), Ammonia Monooxygenase (AMO), Hydroxylamine Oxidase (HAO) and Nitrite Oxidase (NOR) were all higher in smaller bioflocs. Smaller bioflocs were better enriched heavy metal elements and less damage to the gill lamellae was also detected in smaller size group. The survival rate and final mean weight of tilapia (Oreochromis niloticus) cultured in the BFT system based on smaller size bioflocs were significantly higher than the control (p < 0.05). The microbial compositions of varying particle sizes bioflocs demonstrated remarkable distinctions, and higher abundance of particle-attached bacteria (e.g., Flavobacteriaceae, Rhodobacteraceae) was detected in normal size bioflocs. Overall, this study comprehensively evaluated the long-term application of various particle size bioflocs and provided a practical basis for the sustainable BFT development.

우리나라 지방자치단체 운영성과 제고방안에 관한 연구

In order to improve more reasonably and productively in a series of administrative operations and policy processes in Korean local governments, systematic operational performance evaluation of administrative work execution results was recognized as an important management function. It will be possible to promote the development of local administration and enhance administrative autonomy and accountability by checking the productivity of local governments' administrative operations and conducting a rigorous and accurate evaluation of leadership and administrative performance. In this context, this study will review the evaluation areas and measurement indicators of local government operation performance for local government evaluation, extract the determinants of local government evaluation through a review of previous studies, present a performance evaluation model and seek policy directions to improve operational performance. This study on efficient local government operation plans and the role and leadership direction of local government heads can recognize their importance from a political, social, economic, and customer (resident)-oriented perspective. Only when the evaluation system for local government's operational performance is established and utilized under mutual connection with local residents will the local government increase its efforts to improve the quality of life and maximize residents' satisfaction, and regional development policies can also be implemented from a long-term perspective.

Environmental Remediation of Agrochemicals and Dyes Using Clay Nanocomposites: Review on Operating Conditions, Performance Evaluation, and Machine Learning Applications

Environmental Remediation of Agrochemicals and Dyes Using Clay Nanocomposites: Review on Operating Conditions, Performance Evaluation, and Machine Learning Applications