Compliant System Research Articles

Development and Initial Evaluation of a Digital Phenotype Collection System for Adolescents: Proof-of-Concept Study.

The growing concern on adolescent mental health calls for proactive early detection and intervention strategies. There is a recognition of the link between digital phenotypes and mental health, drawing attention to their potential use. However, the process of collecting digital phenotype data presents challenges despite its promising prospects. This study aims to develop and validate system concepts for collecting adolescent digital phenotypes that effectively manage inherent challenges in the process. In a formative investigation (N=34), we observed adolescent self-recording behaviors and conducted interviews to develop design goals. These goals were then translated into system concepts, which included planners resembling interfaces, simplified data input with tags, visual reports on behaviors and moods, and supportive ecological momentary assessment (EMA) prompts. A proof-of-concept study was conducted over 2 weeks (n=16), using tools that simulated the concepts to record daily activities and complete EMA surveys. The effectiveness of the system was evaluated through semistructured interviews, supplemented by an analysis of the frequency of records and responses. The interview findings revealed overall satisfaction with the system concepts, emphasizing strong support for self-recording. Participants consistently maintained daily records throughout the study period, with no missing data. They particularly valued the recording procedures that aligned well with their self-recording goal of time management, facilitated by the interface design and simplified recording procedures. Visualizations during recording and subsequent report viewing further enhanced engagement by identifying missing data and encouraging deeper self-reflection. The average EMA compliance reached 72%, attributed to a design that faithfully reflected adolescents' lives, with surveys scheduled at convenient times and supportive messages tailored to their daily routines. The high compliance rates observed and positive feedback from participants underscore the potential of our approach in addressing the challenges of collecting digital phenotypes among adolescents. Integrating observations of adolescents' recording behavior into the design process proved to be beneficial for developing an effective and highly compliant digital phenotype collection system.

Design, simulation and feasibility of the innovative agricultural warehouse receipt system through dynamic programming and agent-based models.

To address marketing challenges in the agricultural sector, provide financial support for small-scale farmers over marketing seasons, manage price risks of agricultural products, and enhance the functioning of agricultural mercantile exchanges, it is attainable to implement an efficient and compliant warehouse receipt system (WRS) that aligns with the legal, institutional, social, and economic-financial conditions of a country. The aim of this study is to design, simulate, and assess the feasibility of an innovative WRS in the agricultural sector. To achieve this, a WRS was designed and evaluated for maize crop in Iran. The research methodology of this study is divided into three main parts: design, simulation, and feasibility assessment of the WRS. The design process incorporated the FAO-provided (2009) warehouse receipt system development, considering the experiences of various countries and the institutional and financial regulations specific to Iran. Additionally, a dynamic programming model was used to simulate the system, and an agent-based model was utilized for system feasibility assessment. The study results demonstrated that it is possible to design an innovative and efficient WRS by involving five key actors, including farmers, buyers (maize traders), banks, mercantile exchange market, and the warehouse (governmental institution), and establishing clear communications among them. Based on simulation results using dynamic programming model, it was evident that four parameters, namely the annualized loan interest rate, the valuation coefficient for loan collateral, price volatility of the product over the marketing season, and the warehouse cost-to-product value ratio, significantly impact the adoption of the WRS by farmers. In conclusion, the findings from the agent-based model revealed that setting the annualized loan interest rate at 8%, a collateral valuation coefficient of 85%, price fluctuations over the non-harvest time at 60%, and a warehouse cost-to-product value ratio of 2% can result in the participation of nearly 100% of farmers in the proposed WRS.

Kineto-static analysis of a hybrid manipulator consisting of rigid and flexible limbs with locking function for planar shape morphing

The incorporation of lockable passive backbones into active compliant morphing systems efficiently results in lightweight, high-load, and large deformation systems. However, there exist challenges in kineto-static analysis due to the interaction between rigid reconfigurable kinematic constraints and the nonlinear deformation of actuated flexible limbs. This paper addresses these issues by developing a kineto-static method to analyze the motion in a novel planar 3-DOF shape-morphing manipulator. The manipulator features two actuated flexible limbs with a lockable variable geometry truss (LVGT). In this study, two isostatic topologies are selected for reconfigurable motion control under external tip loads. A multi-step sequential control strategy is proposed to maneuver the manipulator's platform for desired poses. Then, a constrained-trajectory-based kinematic model is proposed for an inverse kinematic solution considering motion planning. Subsequently, a kineto-static model is introduced, considering constraints from rigid and flexible limbs, aiming to distribute distributing redundant actuation forces. Finally, nonlinear finite element analysis (FEA) and experiments are carried out to validate the effectiveness of the proposed method.

Through-Window Home Aerial Delivery System with In-Flight Parcel Load and Handover: Design and Validation in Indoor Scenario

Abstract This paper presents the design, development, and validation in indoor scenario of an aerial delivery system intended to conduct the delivery of light parcels directly to the user through the window of his/her home, motivated by the convenience of facilitating the access to medicines to people with reduced mobility.The system consists of a fully-actuated multi-rotor (FAMR) equipped with a front basket where the parcel to be delivered is loaded by a lightweight and compliant anthropomorphic dual arm system (LiCAS) located at the supply point, using one of the arms to drop the parcel in the basket while the other arm holds its base to support the sudden moment exerted at the FAMR. The paper analyses four types of physical interactions raised during the operation on flight: (1) sudden changes in the mass distribution of the FAMR during the load/unload phase, affecting the multi-rotor position-attitude controllers, (2) impact and impulsive forces exerted by the human on the FAMR to demonstrate the reliability and robustness of conventional cascade controllers, (3) passive accommodation of the LiCAS while holding the FAMR during the parcel load, relying on the mechanical joint compliance, and (4) compliant human–FAMR interaction, interpreting the multi-rotor pose control error as a Cartesian/angular deflection to implement an admittance controller that allows the user guiding the platform. Experimental results allow the identification and characterization of these effects for different payload masses. The execution of the complete operation, involving the parcel load with the LiCAS and handover by the user through a window, is validated in a representative indoor scenario. Graphical Abstract

Soft Electromagnetic Sliding Actuators for Highly Compliant Planar Motions Using Microfluidic Conductive Coil Array.

We propose a soft electromagnetic sliding actuator that provides various planar motions to construct highly compliant actuation systems. The actuator is composed of a fully soft actuation base (stator) for generating electromagnetic and magnetic forces and a rigid neodymium magnet (slider) that slides on the actuation base. A parallel liquid-metal coil array in the stator is designed based on theoretical modeling and an optimization process to maximize the electromagnetic field density. The stretchable magnetic components in the stator allow the slider to retain its position stably without additional constraints. By incorporating an untethered structure in which the slider is mechanically decoupled from the stator, the actuator can be operated with reduced power consumption, attributed to the absence of a restoring force. The trajectory of the slider can be programmed by selectively applying the input current to the liquid-meal coil array, and the location of the slider can be estimated by measuring the change in inductance of each coil. Moreover, the proposed actuator demonstrates the capability of operating on curved surfaces through its physical compliance as well as on inclined surfaces thanks to the holding force generated by the magnetic components of the stator. Taking advantage of the unique characteristics of our actuator, robotic applications, including shape morphing systems and sensor-actuator integrated systems, are demonstrated.

Finding the rhythm: Humans exploit nonlinear intrinsic dynamics of compliant systems in periodic interaction tasks.

Activities like ball bouncing and trampoline jumping showcase the human ability to intuitively tune to system dynamics and excite motions that the system prefers intrinsically. This human sensitivity to resonance has been experimentally supported for interactions with simple linear systems but remains a challenge to validate in more complex scenarios where nonlinear dynamics cannot be predicted analytically. However, it has been found that many nonlinear systems exhibit periodic orbits similar to the eigenmodes of linear systems. These nonlinear normal modes (NNM) are computable with a recently developed numerical mode tool. Using this tool, the present resarch compared the motions that humans excite in nonlinear systems with the predicted NNM of the energy-conservative systems. In a user study consisting of three experiment parts, participants commanded differently configured virtual double pendula with joint compliance through a haptic joystick. The task was to alternately hit two targets, which were either aligned with the NNM (Experiments 1 and 2) or purposefully arranged offset (Experiment 3). In all tested experiment variations, participants intuitively applied a control strategy that excited the resonance and stabilized an orbit close to the ideal NNM of the conservative systems. Even for increased task accuracy (Experiment 2) and targets located away from the NNM (Experiment 3), participants could successfully accomplish the task, likely by adjusting their arm stiffness to alter the system dynamics to better align the resonant motions to the task. Consequently, our experiments extend the existing research on human resonance sensitivity with data-based evidence to nonlinear systems. Our findings emphasize the human capabilities to apply control strategies to excite and exploit resonant motions in dynamic object interactions, including possibly shaping the dynamics through changes in muscle stiffness.

Altered trunk-pelvis kinematics during load carriage with a compliant versus a rigid system

Load carriage is a key component of hiking and military activity. The design of the load carriage system (LCS) could influence performance and injury risk. This study aimed to compare a traditional and a compliant LCS during walking and a step-up task to quantify differences in oxygen consumption and trunk-pelvis kinematics. Fourteen participants completed the tasks whilst carrying 16 kg in a rigid and a compliant LCS. There were no differences in oxygen consumption between conditions during either task (p > 0.05). There was significantly greater trunk-pelvis axial rotation (p = 0.041) and lateral flexion (p = 0.001) range of motion when carrying the compliant LCS during walking, and significantly greater trunk-pelvis lateral flexion range of motion during the step-up task (p = 0.003). Carrying 16 kg in a compliant load carriage system results in greater lateral flexion range of motion than a traditional, rigid system, without influencing oxygen uptake.

Stiffness optimization design of wheeled-legged rover integrating active and passive compliance capabilities

Compliance capability is one of the most important properties of suspension systems for rough-terrain robots. This imposes specific requirements on system stiffness design, which directly determines the platform's performance in response to external stimuli. To address the challenge of stiffness optimization design in active and passive compliant systems, this paper proposes a novel and practical method for optimizing stiffness for a terrain-adaptive wheel-legged rover. Firstly, the kinematic model of this multi-degree-of-freedom platform is established. Secondly, the deformation capability coefficient, load capacity coefficient, energy efficiency coefficient, and dynamic stability coefficient are derived as performance indices to assess the behavior of the system. By establishing the relationship between joint configuration variation and system stiffness, stiffness parameters could be evaluated through these performance indices. Ultimately, the global optimum stiffness parameters are selected from the refined intersection of the individual performance optimal domains. Thirdly, the optimum parameters are calculated and applicability verified numerically. The designed parameters are verified experimentally on a wheeled-legged rover. The experimental results demonstrate that the proposed algorithm can find the parameter combination that achieves optimal system performance, thereby enhancing the system's terrain adaptability.

An ultraflexible energy harvesting-storage system for wearable applications

The swift progress in wearable technology has accentuated the need for flexible power systems. Such systems are anticipated to exhibit high efficiency, robust durability, consistent power output, and the potential for effortless integration. Integrating ultraflexible energy harvesters and energy storage devices to form an autonomous, efficient, and mechanically compliant power system remains a significant challenge. In this work, we report a 90 µm-thick energy harvesting and storage system (FEHSS) consisting of high-performance organic photovoltaics and zinc-ion batteries within an ultraflexible configuration. With a power conversion efficiency surpassing 16%, power output exceeding 10 mW cm–2, and an energy density beyond 5.82 mWh cm–2, the FEHSS can be tailored to meet the power demands of wearable sensors and gadgets. Without cumbersome and rigid components, FEHSS shows immense potential as a versatile power source to advance wearable electronics and contribute toward a sustainable future.

FlexiStiff: A Variable Tensile Stiffness Element for Modulating the Behavior of Tensegrity Structures

Soft and tensegrity structures are two configurations that have appeared as robots continue to draw inspiration from nature and diversify beyond rigid machines toward compliant systems. One artificial manifestation of a biological attribute that is an active research topic is the body's capacity to calibrate its stiffness for adapting its behavior to a given task. This study brings together these designs spaces and presents a soft tensile element named FlexiStiff for tensegrity structures to enable transitioning between flexible and stiff states for variable load‐bearing capability and compliance. The device's tensile stiffness constant can be increased by 4400% with a change in pressure. It can provide a high blocking force of 535.5 N and can endure elongation up to 184%. It is assembled using four commercially available materials and a two‐step fabrication method consisting of 3D printing and elastomer curing. As opposed to classical tensegrities for which shape change is inexpensive in terms of energy, this work betokens a new stage in their design wherein the arrangement can radically alter the magnitude of its demand for external energy for shape morphing, a crucial characteristic for operation in partially mapped environments that present diverse terrains and disturbances of varying intensities prompting adaptability.

Using Electronic Health Record Mortality Data to Promote Goals-of-Care Discussions in Seriously Ill Transferred Patients: A Pilot Study

Abstract Background Mortality prediction data may aid in identifying seriously ill transferred patients at high risk of dying and facilitate early goals-of-care discussions (GOCD); however, this is rarely evaluated. We recently developed a model for predicting 30-day inpatient mortality, which may be useful for promoting early GOCD. Objectives Our objectives were to examine the effects of sharing model-generated mortality risk with hospitalists by assessing (1) if hospitalists agreed with the mortality risk prediction, (2) if they planned to conduct GOCD or consult palliative care within 72 hours of transfer, and (3) if the communication alert affected GOCD timing and other clinical outcomes. We also aimed to measure the association between both the model-generated and hospitalists' stratified risk assessments with patient mortality. Methods This was a nonrandomized quasi-experimental pilot study with a historical control group. On the second day of hospitalization, the model-generated risk was communicated to the hospitalists. Hospitalists were asked to answer questions via a HIPAA (Health Insurance Portability and Accountability Act)-compliant mobile communication system, and clinical outcomes were extracted via chart review. Results Eighty-four patients (42 in the control and 42 in the intervention group) were included in this study. Hospitalists agreed that all patients in the intervention group were at risk for inpatient mortality. Hospitalists were more likely to indicate a plan to conduct GOCD in the intervention group (n = 9) compared with the control group (n = 4, p < 0.001). In this subset of patients, GOCD was completed within 72 hours in 78% of intervention patients (n = 7) as compared with 50% in the control group (n = 2). The greater absolute value of the model-generated mortality risk was significantly associated with deaths (p = 0.01), similar to the hospitalists' prediction of the mortality risk (p = 0.02). Conclusion Communicating model-generated mortality risk to hospitalists is a promising approach to promote timely GOCD.

A Multi-solution Study on GDPR AI-enabled Completeness Checking of DPAs

Specifying legal requirements for software systems to ensure their compliance with the applicable regulations is a major concern of requirements engineering. Personal data which is collected by an organization is often shared with other organizations to perform certain processing activities. In such cases, the General Data Protection Regulation (GDPR) requires issuing a data processing agreement (DPA) which regulates the processing and further ensures that personal data remains protected. Violating GDPR can lead to huge fines reaching to billions of Euros. Software systems involving personal data processing must adhere to the legal obligations stipulated both at a general level in GDPR as well as the obligations outlined in DPAs highlighting specific business. In other words, a DPA is yet another source from which requirements engineers can elicit legal requirements. However, the DPA must be complete according to GDPR to ensure that the elicited requirements cover the complete set of obligations. Therefore, checking the completeness of DPAs is a prerequisite step towards developing a compliant system. Analyzing DPAs with respect to GDPR entirely manually is time consuming and requires adequate legal expertise. In this paper, we propose an automation strategy that addresses the completeness checking of DPAs against GDPR provisions as a text classification problem. Specifically, we pursue ten alternative solutions which are enabled by different technologies, namely traditional machine learning, deep learning, language modeling, and few-shot learning. The goal of our work is to empirically examine how these different technologies fare in the legal domain. We computed F2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} score on a set of 30 real DPAs. Our evaluation shows that best-performing solutions yield F2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} score of 86.7% and 89.7% are based on pre-trained BERT and RoBERTa language models. Our analysis further shows that other alternative solutions based on deep learning (e.g., BiLSTM) and few-shot learning (e.g., SetFit) can achieve comparable accuracy, yet are more efficient to develop.

Implementation of a LC-MS based multi-attribute method (MAM) and intact multi-attribute method (iMAM) workflow for the characterisation of a GLP-Fc fusion protein

Over the past few years, the implementation of mass spectrometry (MS) in QC laboratories has become a more common occurrence. The multi-attribute method (MAM), and emerging intact multi-attribute method (iMAM), are powerful analytical tools utilising liquid chromatography−mass spectrometry (LC-MS) methods that enable the monitoring of critical quality attributes (CQAs) in biotherapeutic proteins in compliant settings. Both MAM and iMAM are intended to replace or supplement several conventional assays with a single LC-MS method utilising MS data in combination with robust, semi-automated data processing workflows. MAM and iMAM workflows can also be implemented into current Good Manufacturing Practices environments due to the availability of CFR 11 compliant chromatography data system software. In this study, MAM and iMAM are employed for the analysis of 4 batches of a glucagon-like peptide-Fc fusion protein. MAM approach involved a first the discovery phase for the identification of CQAs and second, the target monitoring phase of the selected CQAs in other samples. New peak detection was performed on the data set to determine the appearance, absence or change of any peak. For native iMAM workflow both size exclusion and strong cation exchange chromatography were optimized for the identification and monitoring of CQAs at the intact level.

Collision dynamics modelling and testing of compliant buffering adsorption system under microgravity environment

Collision dynamics modelling and testing of compliant buffering adsorption system under microgravity environment

A centroid measurement method of large components for active compliant assembly

In the active compliant assembly system of large components, the centroid parameter is an important factor affecting the dynamic model of the attitude adjustment mechanism. This paper proposes a novel automatic centroid measurement method. Firstly, the contact force calculation method between large components during active compliant assembly was described, and the impact of the centroid of large components on the accuracy of the contact force calculation was analyzed. Secondly, based on the principles of torque balance and rigid body rotation, a novel centroid calculation model considering lateral forces is established, and RANSAC is used to optimize the centroid solution. Then, numerical simulation methods were used to analyze the impact of random errors and weighing strategies on the centroid measurement accuracy, and suggestions were given to improve the centroid measurement accuracy. Finally, a compliant assembly system for large component was built in the laboratory, and centroid measurement and accuracy verification experiments were conducted. The experimental results show that the proposed method can significantly improve the accuracy of centroid measurement and can effectively reduce the contact force calculation error during the compliant assembly process of large components.

Analytical Modeling and Validation of New Prismatic Compliant Joints Based on Zero Poisson’s Ratio Lattice Structures

Abstract The design and analysis of prismatic compliant joints have received less attention compared to that given to revolute compliant joints, thus limiting their implementation in compliant mechanisms beyond translational stages. Lattice structures have been used effectively to increase flexibility and stiffness ratios in compliant joints. Considering these, new prismatic compliant joints based on zero Poisson’s ratio lattice structures (ZP-PCJ) are proposed. Lattices with three different cell arrangements are considered: single cells, 2×2, and 3×3 lattices. Additionally, unit cells with three different geometries are studied: triangular, chamfer, and cosine. The compliance matrices of the ZP-PCJs are assembled analytically using Castigliano’s second theorem and compliance series–parallel simplification. The compliance ratios along the three orthogonal axes of the ZP-PCJs are computed varying their geometric parameters. Finite element models are constructed to validate the analytical results. Experimental tests are performed on additively manufactured ZP-PCJs to corroborate the compliance coefficients. Results showed that analytical models can predict the ZP-PCJ’s elastic properties accurately, differences less than 3% and 12% were obtained when compared to computational and experiments, respectively. Based on the compliance ratios obtained, the ZP-PCJs are suitable for two-dimensional applications. Finally, the ZP-PCJs are implemented in a compliant mechanism to evaluate their behavior, analytically and computationally. The ZP-PCJs have advantages such as eliminating axis drift and high flexibility in motion-direction while maintaining stiffness in other directions. The differences observed when comparing the analytically obtained estimations with simulations and experimental data suggest that ZP-PCJ analytical models are reliable for estimating their performance in compliant systems.

Soft Monolithic Shielded Sensors to Measure Shear and Normal Forces for Local Slip Detection

AbstractSoft force sensors enable closed loop control or autonomous operation of compliant robot systems. A stretchable force sensing surface containing an array of independent sensor units is reported. This design allows for the measurement of local shear and normal forces at multiple locations, independently, providing real‐time, multi‐axis force information at each unit. The sensor array is based on capacitive strain sensing, using liquid metal electrodes and air microchannel for high sensitivity. Electromechanical interference between adjacent sensor units is addressed and eliminated through design optimization and the use of compliant electrical shield layers. A 1D sensor array is applied to gripping tasks, where the independent sensor readings enable detecting local and partial slipping. This study illustrates how the device can be used to explore the dynamics of local forces during the stages of pick up, slip, and release.

Design and Testing of a Compliant ZTTΘ Positional Adjustment System with Hybrid Amplification.

This article presents the design, analysis, and prototype testing of a four-degrees-of-freedom (4-DoFs) spatial pose adjustment system (SPAS) that achieves high-precision positioning with 4-DoFs (Z/Tip/Tilt/Θ). The system employs a piezoelectric-driven amplification mechanism that combines a bridge lever hybrid amplification mechanism, a double four-bar guide mechanism, and a multi-level lever symmetric rotation mechanism. By integrating these mechanisms, the system achieves low coupling, high stiffness, and wide stroke range. Analytical modeling and finite element analysis are employed to optimize geometric parameters. A prototype is fabricated, and its performance is verified through testing. The results indicate that the Z-direction feed microstroke is 327.37 μm, the yaw motion angle around the X and Y axes is 3.462 mrad, and the rotation motion angle around the Z axis is 12.684 mrad. The x-axis and y-axis motion magnification ratio can reach 7.43. Closed-loop decoupling control experiments for multiple-input-multiple-outputs (MIMO) systems using inverse kinematics and proportional-integral-derivative feedback controllers were conducted. The results show that the Z-direction positioning accuracy is ±100 nm, the X and Y axis yaw motion accuracy is ±2 μrad, and the Z-axis rotation accuracy is ±25 μrad. Due to the ZTTΘ mechanism, the design proved to be feasible and advantageous, demonstrating its potential for precision machining and micro-nano manipulation.

Analysis of compliant mechanisms with series and parallel substructures through the ellipse of elasticity theory

Compliant mechanisms with complex hybrid configurations have been designed to meet the requirements of specific applications demanding high performance. Kinetostatic analysis, fundamental at the early stage of design, can become difficult for compliant systems characterized by series and parallel substructures. In the present paper, the ellipse of elasticity method is implemented for the analysis of a compliant mechanism with hybrid topology. Firstly, the ellipses associated to the different flexure hinges, characterized by uniform or non-uniform cross-sections, and by constant or variable initial curvature, are determined. Then, the unique ellipse representing the compliant mechanism is obtained by means of series and parallel compositions. By exploiting the antiprojective polarity properties of the ellipse, the kinetostatic analysis of the compliant system is reduced to a geometric problem with a straightforward solution. Linear and nonlinear finite element analyses and experimental tests are performed to verify the theoretical results.

Enhancing HR Technology Through Traceability and Auditing: Navigating Challenges and Legal Complexities for Operational Efficiency

This comprehensive study emphasizes the crucial need for holistic Human Resources (HR) management systems. These systems should ensure transparency, traceability, and alignment with strict regulatory standards, promoting organizational growth. The study highlights the essential role of time and attendance systems in managing hourly employees, ensuring compliance with wage laws and efficient payroll processes. By examining recent legal issues, including class-action lawsuits and key Supreme Court decisions, it illuminates the complex legal framework surrounding HR technology. The study promotes a solution-focused approach, advocating for improvements in data integrity, user interface design, and system interoperability. Additionally, it underlines the importance of including robust reporting and analytics features in time and attendance systems. These suggested strategic changes aim to reduce compliance liabilities, increase productivity, improve data retention practices, and promote a streamlined, legally compliant HR operational framework. This research plays a pivotal role in contributing to the ongoing discourse about enhancing technological infrastructures within Human Resources (HR). It provides insightful perspectives and robust data, serving as a valuable resource for HR professionals, leaders, and decision-makers. The ultimate objective of this study is to attain unparalleled operational excellence and rigorous legal compliance. This not only elevates the standard of HR management systems to new heights but also paves the way for future advancements in this critical field. By fostering a culture of continuous improvement and innovation, this research can inspire the development of more efficient, effective, and legally compliant HR management systems.