Tracking Performance Metrics Research Articles

Enhancing Performance Metrics: A Google Looker Studio Approach to Key Performance Indicator (KPI) Management System for Homecorp Offshore Drafting Team

The Homecorp Offshore Drafting Key Performance Indicator (KPI) Management System is a comprehensive process that aims to improve the management and monitoring of key performance indicators within the drafting department. This system utilizes Google Looker Studio, which provides a user-friendly real-time data analysis and visualization platform. It enables managers to make well-informed decisions and enhance departmental performance. The process begins with collecting daily task data, logged manually or through automated Google Apps Scripts into a Google Sheets database. This data includes task details such as type, status, and completion time. A KPI-pointing system, developed through focus group discussions, also assigns point values to tasks based on their complexity and time requirements. Integrating Google Looker Studio with Google Sheets allows real-time synchronization and web-based monitoring of key performance indicators (KPIs). The dashboard offers detailed insights such as task counts, average KPIs, and monthly performance graphs, providing a comprehensive performance evaluation. The implementation of this system has been well-received by the team, with survey results indicating improvements in tracking performance metrics, ease of use, and enhanced collaboration. While these outcomes are positive, there is still a recognized need for further refinement, particularly in incorporating qualitative data and improving IT support. The KPI Management System has significantly enhanced performance monitoring and management for the drafting team. To keep the system up-to-date and effective, ongoing feedback and iterative improvements must be maintained. Potential future enhancements could include extending the system's use company-wide to foster a culture of continuous improvement and accountability.

Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm

Pneumatic servo systems face challenges such as friction, compressibility, and nonlinear dynamics, necessitating advanced control techniques. Research suggests model-based, model-free, hybrid, and optimization-based methods have their strengths. Therefore, this study presents an optimal control strategy using Adaptive Domain Prescribed Performance Control (AD-PPC) cascaded with PID and optimized using the Evolutionary Mating Algorithm (EMA) for a pneumatic servo system (PSS). The goal is to achieve faster transient control and stable rod-piston positioning with minimal friction through the hysteresis phenomenon of the targeted proportional valve-controlled double-acting pneumatic cylinder (PPVDC) representing the PSS. The novel EMA optimizes the cascaded controller based on the tracking error as its objective function. Simulation studies verify the proposed AD-PPC-PID controller with the PPVDC model plant, iteratively optimized by the EMA. The analytical study compares this setup's control system and optimization model with the same control system model using alternative optimization methods. The testing employs step and multi-step signals for PPVDC's rod-piston position input. Results show that the EMA-tuned AD-PPC-PID outperforms AD-PPC-PID controller with other optimizers. For both input trajectory tests, EMA-tuned AD-PPC-PID shows faster response times, with average improvements of 30 % in settling times and 70 % in tracking performance metrics compared to other optimizers, making it robust for nonlinear system applications like PPVDC rod-piston positioning.

IoUformer: Pseudo-IoU prediction with transformer for visual tracking

Siamese tracking has witnessed tremendous progress in tracking paradigm. However, its default box estimation pipeline still faces a crucial inconsistency issue, namely, the bounding box decided by its classification score is not always best overlapped with the ground truth, thus harming performance. To this end, we explore a novel simple tracking paradigm based on the intersection over union (IoU) value prediction. To first bypass this inconsistency issue, we propose a concise target state predictor termed IoUformer, which instead of default box estimation pipeline directly predicts the IoU values related to tracking performance metrics. In detail, it extends the long-range dependency modeling ability of transformer to jointly grasp target-aware interactions between target template and search region, and search sub-region interactions, thus neatly unifying global semantic interaction and target state prediction. Thanks to this joint strength, IoUformer can predict reliable IoU values near-linear with the ground truth, which paves a safe way for our new IoU-based siamese tracking paradigm. Since it is non-trivial to explore this paradigm with pleased efficacy and portability, we offer the respective network components and two alternative localization ways. Experimental results show that our IoUformer-based tracker achieves promising results with less training data. For its applicability, it still serves as a refinement module to consistently boost existing advanced trackers.

Marketing in a Crisis: Strategies for Resilience and Growth

Economic downturns and uncertainty create a difficult environment for businesses. As consumers become more cautious, many businesses make the mistake of significantly reducing or even pausing marketing efforts in an attempt to cut costs. Marketing isn’t a luxury that needs to be curtailed during a downturn; it’s a strategic tool vital to position the business for future growth. However, maintaining visibility and a strong connection with customers is vital during these times. To weather the storm, firms need to adapt their marketing approach by focusing on value, leveraging empathy, enhancing digital strategies, building customer trust, and carefully tracking performance metrics.

Building Inclusive Work Environments.

A truly inclusive organization cultivates a sense of belonging and value in its members, realizing their contributions are vital to its success. Acknowledging and then dismantling exclusionary systems and policies are essential to creating environments grounded in diversity and equity. This process requires intentionality, accountability, and swift action on the part of leadership. Additionally, the role of organizational accountability, through tracking performance metrics, gauging employee satisfaction and engagement, and routinely assessing identified goals and objectives, is critical to sustaining inclusivity. In this article, we present a review of the literature and offers recommendations to build and sustain an inclusive environment.

Real-Time Multiple Object Visual Tracking for Embedded GPU Systems

Real-time visual object tracking provides every object of interest with a unique identity and a trajectory across video frames. This is a fundamental task of many video analytics applications, such as traffic monitoring or video surveillance in general. The development of real-time multiple object tracking systems on low-power edge devices as IoT nodes, without compromising accuracy, is a challenge due to the limited computing capacity of said devices. This might rule out the best in-class computer vision solutions, which, nowadays, are based on deep learning, and thus, they are very hardware demanding. This article meets this challenge with a multiple object detection and tracking system that employs cutting-edge deep learning architectures on an embedded GPU while operating in real time. For this purpose, a system has been designed that extends a joint architecture of tracking and detection by adding a module comprised of appearance-based and movement-based trackers that allow to maintain the identity of the objects of interest for longer periods of time while alleviating the burden of the detector. Our system is mapped onto an embedded GPU platform, cutting down power consumption significantly with respect to a server GPU. Tracking performance metrics show a 51.1% in multiple object tracking accuracy (MOTA) on the MOT16 data set. This, in conjunction with a real-time processing speed of 25.2 FPS for up to 45 simultaneous objects and low-power consumption of 15 W, make our system an ideal solution for a wide range of video analytics applications.

Model-free adaptive control for the PEMFC air supply system based on interval type-2 fuzzy logic systems

Control aims to avoid oxygen starvation and maximize the net power output by maintaining the optimal oxygen excess ratio (OER), which varies between 1.8 and 2.5. Because of the nonlinearity of the proton exchange membrane fuel cell (PEMFC) air supply system and the different conditions, ensuring an optimal OER is still a challenge. In this study, a model-free adaptive controller is presented for the PEMFC air supply system based on feedback linearization and interval type-2 fuzzy logic systems (IT2 FLSs). Theoretical analysis and experimental results verify the effectiveness of the proposed control scheme. For the theoretical analysis, first, the PEMFC air supply system is transformed into a canonical form with the feedback linearization technique. Then, zero-dynamics stability is discussed in detail to determine the stability of the internal dynamics. Finally, an adaptive interval type-2 fuzzy logic system controller (AIT2FLSC) is designed on the basis of the Lyapunov stability theory, which does not require complete a priori knowledge of the system dynamics. For the experimental results, the root mean square error (RMSE), variance, and standard deviation (SD) of the tracking error are used as tracking performance metrics to evaluate the control accuracy of the proposed AIT2FLSC, which are 0.0968, 0.0093, and 0.0962, respectively. Compared with the traditional proportion integration differentiation controller (RMSE 0.1119, variance 0.0122, and SD 0.1105), this proposed algorithm obtains better adaptability and the RMSE of the tracking error improves 13.48%. Compared with the adaptive type-1 fuzzy logic system controller (AT1FLSC) (RMSE 0.1076, variance 0.0113, and SD 0.1063), this AT2FLSC has a stronger ability to deal with uncertainty and the RMSE of the tracking error improves 10% when the stack temperature is fixed (353.15 K). Furthermore, when the stack temperature is time-varying, the RMSE, variance, and SD of the tracking error under the AIT2FLSC are 0.0966, 0.0092, and 0.0960, respectively, which is less than AT1FLSC (0.1085, 0.0115, and 0.1073) and the RMSE of the tracking error improves 10.99%.

Adaptive Interval Type-2 Fuzzy Logic Control of a Three Degree-of-Freedom Helicopter

This paper combines interval type-2 fuzzy logic with adaptive control theory for the control of a three degree-of-freedom (DOF) helicopter. This strategy yields robustness to various kinds of uncertainties and guaranteed stability of the closed-loop control system. Thus, precise trajectory tracking is maintained under various operational conditions with the presence of various types of uncertainties. Unlike other controllers, the proposed controller approximates the helicopter’s inverse dynamic model and assumes no a priori knowledge of the helicopter’s dynamics or parameters. The proposed controller is applied to a 3-DOF helicopter model and compared against three other controllers, i.e., PID control, adaptive control, and adaptive sliding-mode control. Numerical results show its high performance and robustness under the presence of uncertainties. To better assess the performance of the control system, two quantitative tracking performance metrics are introduced, i.e., the integral of the tracking errors and the integral of the control signals. Comparative numerical results reveal the superiority of the proposed method by achieving the highest tracking accuracy with the lowest control effort.

Association of Visual Tracking Metrics With Post-concussion Symptomatology.

Attention impairment may provide a cohesive neurobiological explanation for clusters of clinical symptoms that occur after a concussion; therefore, objective quantification of attention is needed. Visually tracking a moving target is an attention-dependent sensorimotor function, and eye movement can be recorded easily and objectively to quantify performance. Our previous work suggested the utility of gaze-target synchronization metrics of a predictive visual tracking task in concussion screening and recovery monitoring. Another objectively quantifiable performance measure frequently suggested for concussion screening is simple visuo-manual reaction time (simple reaction time, SRT). Here, we used visual tracking and SRT tasks to assess changes between pre- and within-2-week post-concussion performances and explore their relationships to post-concussion symptomatology. Athletes participating in organized competitive sports were recruited. Visual tracking and SRT records were collected from the recruited athlete pool as baseline measures over a 4-year period. When athletes experienced a concussion, they were re-assessed within 2 weeks of their injury. We present the data from a total of 29 concussed athletes. Post-concussion symptom burden was assessed with the Rivermead Post-Concussion Symptoms Questionnaire and subscales of the Brain Injury Screening Questionnaire. Post-concussion changes in visual tracking and SRT performance were examined using a paired t-test. Correlations of changes in visual tracking and SRT performance to symptom burden were examined using Pearson's coefficients. Post-concussion changes in visual tracking performance were not consistent among the athletes. However, changes in several visual tracking metrics had moderate to strong correlations to symptom scales (r up to 0.68). On the other hand, while post-concussion SRT performance was reduced (p < 0.01), the changes in the performance metrics were not meaningfully correlated to symptomatology (r ≤ 0.33). Results suggest that visual tracking performance metrics reflect clinical symptoms when assessed within 2 weeks of concussion. Evaluation of concussion requires assessments in multiple domains because the clinical profiles are heterogeneous. While most individuals show recovery within a week of injury, others experience prolonged recovery periods. Visual tracking performance metrics may serve as a biomarker of debilitating symptoms of concussion implicating attention as a root cause of such pathologies.

An ad hoc distributed systems approach for industrial wireless sensor network management

Abstract This paper reports on an ad hoc wireless sensor network architecture for industrial sensing and control applications. This approach is tested using a large-scale (400–676 node) agent-based simulation of a factory environment that is subject to noise and blockage. The basic problem tackled by the distributed system is mobile node tracking. To support this work, we introduce two classes of metrics: (1) a set of tracking performance metrics, and (2) a set of network architecture efficiency metrics. The results of our experiments show that the proposed distributed system adapts readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.

Visual Tracking in Development and Aging.

A moving target is visually tracked with a combination of smooth pursuit and saccades. Human visual tracking eye movement develops through early childhood and adolescence, and declines in senescence. However, the knowledge regarding performance changes over the life course is based on data from distinct age groups in isolation using different procedures, and thus is fragmented. We sought to describe the age-dependence of visual tracking performance across a wide age range and compare it to that of simple visuo-manual reaction time. We studied a cross-sectional sample of 143 subjects aged 7–82 years old (37% male). Eye movements were recorded using video-oculography, while subjects viewed a computer screen and tracked a small target moving along a circular trajectory at a constant speed. For simple reaction time (SRT) measures, series of key presses that subjects made in reaction to cue presentation on a computer monitor were recorded using a standard software. The positional precision and smooth pursuit velocity gain of visual tracking followed a U-shaped trend over age, with best performances achieved between the ages of 20 and 50 years old. A U-shaped trend was also found for mean reaction time in agreement with the existing literature. Inter-individual variability was evident at any age in both visual tracking and reaction time metrics. Despite the similarity in the overall developmental and aging trend, correlations were not found between visual tracking and reaction time performances after subtracting the effects of age. Furthermore, while a statistically significant difference between the sexes was found for mean SRT in the sample, a similar difference was not found for any of the visual tracking metrics. Therefore, the cognitive constructs and their neural substrates supporting visual tracking and reaction time performances appear largely independent. In summary, age is an important covariate for visual tracking performance, especially for a pediatric population. Since visual tracking performance metrics may provide signatures of abnormal neurological or cognitive states independent of reaction time-based metrics, further understanding of age-dependent variations in normal visual tracking behavior is necessary.

A Wireless Intelligent Network for Industrial Control

In this paper, we describe a distributed clustering technique for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective assessment of the cluster management approach both in terms of its tracking performance and its use of network resources. To support this work, we introduce two classes of metrics: a set of three tracking performance metrics, and a set of three network efficiency metrics. The results of our experiments show that the proposed distributed system adapts readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.

Implementation of performance metrics to assess pharmacists' activities in ambulatory care clinics.

The development and implementation of performance metrics for assessing the impact of pharmacists' activities in ambulatory care clinics are described. Ambulatory care clinic pharmacists within an integrated health system were surveyed to ascertain baseline practices for documenting and tracking performance metrics. Through literature review and meetings with various stakeholders, priorities for metric development were identified; measures of care quality, financial impact, and patient experience were developed. To measure the quality of care, pharmacists' interventions at five ambulatory care clinics within the health system were assessed. Correlation of pharmacist interventions with estimated cost avoidance provided a measure of financial impact. Surveys were distributed at the end of clinic visits to measure satisfaction with the patient care experience. An electronic system for metric documentation and automated tabulation of data on quality and financial impact was built. In a 12-week pilot program conducted at three clinic sites, the metrics were used to assess pharmacists' activities. A total of 764 interventions were documented (a mean of 24 accepted recommendations per pharmacist full-time equivalent each week), resulting in estimated cost avoidance of more than $40,000; survey results indicated high patient satisfaction with the services provided by pharmacists. Biweekly report auditing and solicitation of feedback guided metric refinement and further training of pharmacists. Tools and procedures were established for future metric expansion. Development and implementation of performance metrics resulted in successful capture and characterization of pharmacists' activities and their impact on patient care in three ambulatory care clinics.

05/01240 Improving building operation by tracking performance metrics throughout the building lifecycle (BLC)

In this study, nucleate boiling heat transfer coefficients (HTCs) of five flammable refrigerants of propylene (R1270), propane (R290), isobutane (R600a), butane (R600), and dimethylether (RE170) were measured at the liquid temperature of 7 °C on a low fin tube of 1023 fins per meter, Turbo-B, and Thermoexcel-E tubes. All data were taken from 80 to 10 kW m−2 with an interval of 10 kW m−2 in the decreasing order of heat flux. Flammable refrigerants' data showed a typical trend that nucleate boiling HTCs obtained on enhanced tubes also increase with the vapor pressure. Fluids with lower reduced pressure such as DME, isobutene, and butane took more advantage of the heat transfer enhancement mechanism of enhanced tubes than those with higher reduced pressure such as propylene and propane. Finally, Thermoexcel-E showed the highest heat transfer enhancement ratios of 2.3–9.4 among the tubes tested due to its sub-channels and re-entrant cavities.

Improving building operation by tracking performance metrics throughout the building lifecycle (BLC)

An industry foundation class based building product model of University College Cork’s “to be constructed” Environmental Research Institute will be developed. This paper discusses combining such a building product model with a building management system and other tools and technologies to create a framework for monitoring, analysing and controlling a building throughout its building lifecycle based on a set of performance metrics. The framework will be known as the building energy monitoring, analysing and controlling (BEMAC) framework. Current building performance assessment practices lack standardisation/continuity throughout the building lifecycle. An environment such as the BEMAC framework described in this paper offers a means to achieving such standardisation/continuity by documenting and communicating performance metrics data such that these data can provide value across the complete lifecycle of a building project, from planning through design and construction into occupancy and operation.