Control Mechanisms Research Articles

Navigating control and performance in emergency NGOs: the pivotal role of accountability

PurposeThis study aims to investigate the pivotal role of accountability in shaping control mechanisms within non-governmental organizations (NGOs) engaged in disaster relief, examining how it influences control practices and operational capacity in resource management.Design/methodology/approachWe conducted a comparative case study based on 65 interviews with NGO experts in emergency crises and more than 300 documents.FindingsOur findings highlight accountability as a driving factor that shapes the formality and coerciveness of control mechanisms, often in response to donor demands. Emergency NGOs apply various forms of formal and informal control, with financial transparency being crucial. While intrinsic NGO characteristics alone could not explain differing control configurations, we found that accountability affects operational capacity within each NGO type through its influence on control formalization and coerciveness.Originality/valueOur findings challenge the belief that NGOs' intrinsic characteristics determine organizational control. Instead, accountability shapes control formalization. Our study offers practical insights for NGOs on how control choices affect operational capacity, examining multiple emergency NGOs in similar contexts rather than focusing on individual organizations.

Modeling the dynamic effects of tariffs on economic variables and trade policies

Tariffs, a key instrument of trade policy, are often viewed as tools to correct trade imbalances or protect domestic industries. However, their effects on an economy extend beyond immediate price changes, triggering complex feedback loops that unfold over time. This study explores tariffs as a feedback control mechanism within an economic system, emphasizing their role in influencing key variables such as inflation, trade balances, consumption, and monetary policy. By modeling these interactions using delayed differential equations (DDEs), the research demonstrates how time lags in economic adjustments — such as the delayed effects of tariffs on inflation and trade volume can amplify or attenuate the initial impact of policy changes. The feedback loop suggests that tariffs, while raising prices and reducing trade volume in the short term, also lead to inflationary pressures, which may prompt central bank responses, such as interest rate adjustments. These adjustments, in turn, affect investment and consumption, further influencing the economy. The research provides both a theoretical and practical framework for understanding the dynamic and delayed nature of tariffinduced economic changes, with insights into how policymakers can better anticipate and manage the consequences of trade policies. This model offers a comprehensive understanding of the broader economic adjustments and the role of time lags in shaping the long-term impact of tariffs on global trade and national economies.

Analysis of Polar and Nonpolar Small Plant Growth Hormones and Quantification by LC/MS.

Plant hormones are small metabolites that regulate all aspects of plant growth and development, including plant defense. The detection and quantification of these hormones are critical to understanding the mechanism of growth regulation in plants. In maize, a wealth of genetic resources has enabled progress on elucidating the genetic mechanisms underlying plant growth. Biochemical studies of growth in maize can provide insight into the physiological mechanisms of growth control by measuring endogenous levels of plant hormones, and this knowledge would be enhanced by the development of a method to analyze several hormones in a single small sample of tissue. We provide here a simple protocol to extract and accurately quantify six classes of plant hormones in a single liquid chromatography/mass spectrometry injection run using maize tissues. Those hormones include abscisic acid (ABA), 1-aminocyclopropane-1-carboxylate (ACC), gibberellic acid (GA), 3-indoleacetic acid (IAA), jasmonic acid (JA), and salicylic acid (SA), as well as an accumulated phytoanticipin of maize, 24-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), which influences the levels of IAA.

Mechanism of Enhanced Control and Technological Application of Surrounding Rock Anchoring in Fully Mechanized Caving Face of Extra-Thick Coal Seams

With respect to the problem of the anchorage failure of a broken roof in the roadway of extra-thick coal seams by using a traditional unconstrained pushing anchoring agent, a new anchoring agent installation technology with a push–pull device was proposed. Many research methods were adopted to study the mechanism of the efficient control of anchoring agent installation technology with a push–pull device on surrounding rock and the application of the technology. The results indicated that an unconstrained pushing anchoring agent exhibited two main morphological types: bending equilibrium and bending instability. The pushing force for the anchoring agent installed using the integrated push–pull method was calculated to be 13.52 N, which was less than that of the unconstrained pushing anchoring agent. An anchoring agent pushing with the push–pull device was able to smoothly pass through borehole delamination and collapse zones. When the pull-out force reached 160 kN and 180 kN, there was no significant slip or failure in the anchored section of the cable. The support system with the push–pull device for installing the anchoring agent reduced rock deformation by nearly 50%. This demonstrated that this technology significantly enhances the control of surrounding rock deformation.

New Direction in Antimicrobial Delivery System: Preparation and Applications of Hydrogel Microspheres

Antimicrobial delivery systems have undergone extensive development, yet conventional carriers still exhibit limitations such as low loading capacity, inadequate controlled release mechanisms, and cytotoxicity. Recent studies have increasingly demonstrated the potential of Hydrogel Microspheres (HMSs) for antimicrobial delivery. These microspheres exhibit small dimensions, high drug-loading capacity, and the ability to achieve deep-targeted delivery, complemented by adjustable physicochemical properties and biocompatibility that create favorable conditions for antimicrobial transportation. This review systematically examines HMS preparation strategies, characteristic properties, transported antimicrobials, and therapeutic applications. Particular emphasis is placed on critical preparation parameters governing HMS performance, especially those influencing drug delivery dynamics. We conclude by addressing current challenges and proposing actionable strategies for material optimization and clinical translation. This work aims to advance HMS-based antimicrobial delivery systems for more effective infection control.

Throughput Performance in D2D Communication Networks: Effects of Power, Density and User Distance

Device-to-Device (D2D) communication plays a vital role in enhancing spectral efficiency and data rates in next-generation wireless networks, but interference management and optimal power control remain key challenges. This study aims to address these gaps by developing a modified Power Control Scheme for D2D communication (mPCS-D2D) using a Hierarchical Clustering Algorithm (HCA) to improve throughput while minimizing interference. The scheme combines proximity-based clustering for general D2D users and social relationship-based clustering for mmWave D2D communication. Simulations were conducted to evaluate the throughput performance of mPCS-D2D under varying D2D transmit power levels, user densities, and inter-user distances. Results showed that the proposed scheme significantly outperformed the baseline PCS-D2D model across multiple scenarios. At 10 m and 15 m distances with a pathloss exponent of 4.5, mPCS-D2D improved throughput by 5.15% and 4.42%, respectively. Under varying user densities and pathloss exponents (3.5 and 4.5), throughput gains ranged from 4.33% to 4.77%, while across 10 m, 15 m, and 20 m distances, it achieved improvements of 4.13% to 5.53%. These findings demonstrate that the proposed mPCS-D2D scheme effectively enhances data transmission rates under diverse network conditions. The study concludes that integrating hierarchical clustering into power control mechanisms can significantly improve D2D communication efficiency. The proposed method offers practical implications for designing scalable, interference-aware D2D systems in future wireless networks.

P-I Controlled Transformerless Inverter for Solar PV Systems: A Python-Based Simulation

This project presents the design and implementation of a Buck-Boost Transformer-less Inverter (BBTI) for grid-connected solar photovoltaic systems. Building upon existing research, this study introduces a novel control strategy utilizing a Proportional-Integral (PI) controller to enhance the inverter's performance. The PI controller effectively regulates output voltage and current, improving system stability and minimizing steady-state errors. Implemented in Python, this project leverages extensive libraries for numerical computation and visualization, enabling real-time monitoring and adjustments. The simulation results demonstrate significant improvements in the dynamic response of the inverter, allowing it to adapt quickly to varying load conditions and optimize power delivery to the grid. The enhanced control mechanism leads to a reduction in Total Harmonic Distortion (THD) and improved efficiency, validating the effectiveness of the proposed modifications. Overall, this project contributes to advancing the reliability and performance of transformer-less inverter technology in renewable energy applications.

Paradigm of Pumped Hydro Energy Storage: Comprehensive Review

At present, climate change and anthropogenic impacts have a significant impact on the availability of water resources, hydroelectric power generation and the use of renewable energy sources. Maximizing and improving power utilization and providing balanced power in the national grid and sustainable energy at grid level is very important. It is widely recognized to utilize renewable energy from various sources and improve water resources management and utilization practices by providing PHES. This review paper examines the implication of Pumped Hydro Energy Storage (PHES) systems in fulfilling the nature of variable energy system to meet peak load. The review considers the characteristics, status and various topologies of PHES systems. The review explores that the preferred sites or topologies that varies in practice can be implemented at different sites of PHES. The paper highlights the importance of PHES, the PHES topologies, features, development of PHES. Suggests future directions and gaps may provide good input for researchers specifically focusing on peak load control, optimization and control mechanisms, improving efficiency and performance: environmental impacts, integration of renewable energy sources and optimal PHES sizing.

Mechanisms controlling spatial variability of geogenic ammonium in coastal aquifers: Insights from Holocene sedimentary evolution.

Mechanisms controlling spatial variability of geogenic ammonium in coastal aquifers: Insights from Holocene sedimentary evolution.

Director's Accountability in A Limited Liability Company in Relation to Carrying Out His Duties and Authorities

Director accountability in a limited liability company (PT) is a vital aspect of modern corporate governance. Directors are not only responsible for managing the company effectively and efficiently, but also for ensuring compliance with legal regulations and safeguarding the interests of shareholders. This study aims to examine the implementation and challenges in carrying out the duties and authorities of PT directors, with a focus on the legal framework and management practices applied. This study uses a qualitative approach by analyzing related literature, laws and regulations, and case studies to identify the roles and responsibilities inherent in directors. The main findings show that directors have broad responsibilities, including in terms of strategic decision-making, risk management, and compliance with applicable regulations. The use of good corporate governance principles is key to ensuring that directors carry out their duties with integrity and transparency, and are able to face complex challenges in a dynamic business environment. By considering the role of internal and external supervision, this study also identifies several supporting factors and obstacles in the implementation of director accountability. The implication of this study is the importance of strengthening the company's internal control mechanisms and promoting a culture of compliance and accountability at all levels of the organization. Companies in a country, whether local companies, foreign-local mixtures, or foreign companies that run their businesses in a particular country have a role in the economic development of that country. These companies have various forms and types, and operate in all areas of community life. Some of these companies are based in the country where the company was founded, some are branches of other countries that open/expand their businesses in other countries. In Indonesia, there are Limited Liability Companies, CVs, Associations, Firms, and Civil Partnerships. These companies are run by a management that regulates the running of the business itself, regardless of whether it is a large, medium or small company. In running its business, the company needs humans to operate because the company itself is a virtual or abstract form so that in operations humans are still needed for that. Individuals or people who run a business are people who are responsible for the operational activities of the Company. It has been explained above that Companies can be established in various forms and types. In Indonesia, we know 2 (two) types; legal entities and business entities. Both types of businesses are managed by individuals who are responsible for the running of the Company. How far is the individual responsible in running his business. If he is the owner himself or he shares with his partner or he only works in the Company, or he only invests? In a limited liability company, the person responsible for the business operations is one or several directors. What the researcher will examine is the responsibility of a director for his actions in carrying out his work in a limited company.

Properties of standing balance control under noisy galvanic vestibular stimulation

Vestibular sensation contributes to balance control during standing as well as somatosensation and vision. Previous studies have indicated that noisy galvanic vestibular stimulation (nGVS) activates vestibular function and improves standing balance in many subjects. However, the mechanism for improving balance control with the addition of nGVS remains unclear. This study aimed to clarify the balance control mechanism improved by nGVS using detailed motion data during quiet standing. Thirty-two young healthy subjects performed quiet standing tests for 40 s with their eyes closed under sham and optimal intensity stimulation. Detailed data consisting of the center of mass (COM) displacement and acceleration of the body, head acceleration, and lower and upper body accelerations were obtained from measurements using a force platform and a head inertial sensor based on the equations of motion of rigid body models. In addition, our study discusses the contributions of joint strategies for COM control and head acceleration control. The contributions of the ankle and hip strategies were calculated from the COM accelerations of the lower and upper bodies. The results indicated that the more effective group of nGVS suppressed head acceleration using the ankle strategy in the anteroposterior direction. This implies that acceleration feedback from vestibular function affects the quality of the ankle joint strategy control. The findings of this study could contribute to the evaluation of vestibular sensory weighting during standing and development of intervention methods for vestibular function using nGVS.

Privacy-preserving revocable access control for LLM-driven electrical distributed systems

Large Language Models (LLMs) have become transformative tools in natural language processing, significantly advancing the fields of communication, information analysis, and knowledge sharing. However, the vast amounts of sensitive data they handle pose significant challenges for data security and privacy. Traditional cryptographic methods face limitations in efficiently managing access control in LLM-driven electrical distributed systems. This paper introduces a novel Privacy-preserving Revocable Access Control for LLM-driven electrical distributed systems, addressing key concerns such as access policy concealment, user revocation efficiency, and computational overhead. Leveraging an inner-product-based access control mechanism, the proposed scheme achieves complete access policy concealment while supporting flexible access control with wildcard capabilities. Additionally, it facilitates efficient user revocation without requiring costly updates to ciphertexts in such an LLM-driven electrical distributed system. The concise algorithmic structure ensures high efficiency, further enhanced through online/offline encryption and outsourced decryption mechanisms.

Enhanced Access Control for Secure Cloud Data Storage and Sharing Using Elliptic Curve Cryptography

This paper presents the development of an advanced access control mechanism for secure cloud data storage and sharing, integrating cryptographic techniques to prevent unauthorized access, insider threats, and economic denial of sustainability (EDoS) attacks. The proposed system, termed "Digital Signature-Based Trio Access Control with Key Shares," ensures three key functionalities: (1) Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to provide fine-grained access control, ensuring that only authorized users can decrypt cloud-stored data, (2) Digital Signature verification using Elliptic Curve Cryptography (ECC) to authenticate and validate user requests, preventing unauthorized access and network-based attacks, and (3) Key Sharing Mechanism to prevent key theft and insider threats by splitting encryption keys between the cloud provider and the data user. Implemented using Java, the system incorporates state-of-the-art cryptographic techniques to enhance security while maintaining computational efficiency. The access control framework effectively mitigates security risks such as excessive download requests and unauthorized key access, making it a robust solution for industries dealing with sensitive cloud-stored data. Performance evaluations, including encryption efficiency, request validation speed, and security impact analysis, demonstrate that the proposed mechanism provides reliable and secure data access control. This study highlights the significance of multi-layered security frameworks in cloud storage environments, offering a scalable and efficient solution for modern cloud-based applications. Index terms: Cloud Security, Access Control, Ciphertext-Policy Attribute-Based Encryption (CP-ABE), Digital Signature, Elliptic Curve Cryptography (ECC), Key Sharing Mechanism, Economic Denial of Sustainability (EDoS) Attacks, Cloud Data Protection, Cryptographic Security, Secure Cloud Storage, Insider Threat Mitigatio

Neurocomputational Mechanisms of Sense of Agency: Literature Review for Integrating Predictive Coding and Adaptive Control in Human–Machine Interfaces

Background: The sense of agency (SoA)—the subjective experience of controlling one’s own actions and their consequences—is a fundamental aspect of human cognition, volition, and motor control. Understanding how the SoA arises and is disrupted in neuropsychiatric disorders has significant implications for human–machine interface (HMI) design for neurorehabilitation. Traditional cognitive models of agency often fail to capture its full complexity, especially in dynamic and uncertain environments. Objective: This review synthesizes computational models—particularly predictive coding, Bayesian inference, and optimal control theories—to provide a unified framework for understanding the SoA in both healthy and dysfunctional brains. It aims to demonstrate how these models can inform the design of adaptive HMIs and therapeutic tools by aligning with the brain’s own inference and control mechanisms. Methods: I reviewed the foundational and contemporary literature on predictive coding, Kalman filtering, the Linear–Quadratic–Gaussian (LQG) control framework, and active inference. I explored their integration with neurophysiological mechanisms, focusing on the somato-cognitive action network (SCAN) and its role in sensorimotor integration, intention encoding, and the judgment of agency. Case studies, simulations, and XR-based rehabilitation paradigms using robotic haptics were used to illustrate theoretical concepts. Results: The SoA emerges from hierarchical inference processes that combine top–down motor intentions with bottom–up sensory feedback. Predictive coding frameworks, especially when implemented via Kalman filters and LQG control, provide a mechanistic basis for modeling motor learning, error correction, and adaptive control. Disruptions in these inference processes underlie symptoms in disorders such as functional movement disorder. XR-based interventions using robotic interfaces can restore the SoA by modulating sensory precision and motor predictions through adaptive feedback and suggestion. Computer simulations demonstrate how internal models, and hypnotic suggestions influence state estimation, motor execution, and the recovery of agency. Conclusions: Predictive coding and active inference offer a powerful computational framework for understanding and enhancing the SoA in health and disease. The SCAN system serves as a neural hub for integrating motor plans with cognitive and affective processes. Future work should explore the real-time modulation of agency via biofeedback, simulation, and SCAN-targeted non-invasive brain stimulation.

Comparison of Surface Current Measurement Between Compact and Square-Array Ocean Radar

High-frequency (HF) ocean radars have become essential tools for monitoring surface currents, offering real-time, wide-area coverage with cost-effectiveness. This study compares the compact CODAR system (MABT, 13 MHz) and the square-array phased-array radar (KNTN, 8 MHz) deployed at Cape Maobitou, Taiwan. Radial velocity measurements were evaluated against data from the Global Drifter Program (GDP), and a quality control (QC) mechanism was applied to improve the data’s reliability. The results indicated that KNTN provides broader spatial coverage, whereas MABT demonstrates higher precision in radial velocity measurements. Baseline velocity comparisons between MABT and KNTN revealed a correlation coefficient of 0.77 and a root-mean-square deviation (RMSD) of 0.23 m/s, which are consistent with typical values reported in previous radar performance evaluations. Drifter-based velocity comparisons showed an initial correlation of 0.49, with an RMSD of 0.43 m/s. In more stable oceanic regions, the correlation improved to 0.81, with the RMSD decreasing to 0.24 m/s. To clarify, this study does not include multiple environmental scenarios but focuses on cases where both radar systems operated simultaneously and where surface drifter data were available within the overlapping area. Comparisons are thus limited by these spatiotemporal conditions. Radar data may still be affected by environmental or human factors, such as ionospheric variations, interference from radio frequency management issues, or inappropriate parameter settings, which could reduce the accuracy and consistency of the observations. International ocean observing programs have developed quality management procedures to enhance data reliability. In Taiwan, the Taiwan Ocean Research Institute (TORI) has established a data quality management mechanism based on international standards for data filtering, noise reduction, and outlier detection, improving the accuracy and stability of radar-derived velocity measurements.To eliminate the effects caused by different center frequencies between MABT and KNTN, this study used the same algorithms and parameter settings as much as possible in all steps, from Doppler spectra processing to radial velocity calculation, ensuring the comparability of the data. This study highlights the strengths and limitations of compact and phased-array HF radar systems based on co-observed cases under consistent operational conditions. Future research should explore multi-frequency radar integration to enhance spatial coverage and measurement precision, improving real-time coastal current monitoring and operational forecasting.

CORRUPTION AS A FACTOR OF INEFFICIENT ADMINISTRATIVE MANAGEMENT IN PUBLIC AUTHORITIES

The article analyses the forms of corruption in public authorities, investigates the causes of its emergence and spread. It is substantiated that various manifestations of corruption in state and local authorities persist precisely because of the indifferent attitude of society to this phenomenon. It has been established that an ineffective administrative management system in public authorities creates conditions for abuse due to insufficient transparency of decision-making processes, excessive bureaucracy, weak control and accountability mechanisms, which allows individual officials to use their official position to obtain undue benefit. A set of measures has been developed to prevent and combat corruption in state authorities, which include: clear regulation of administrative processes and an effective system of accountability of officials for decisions and actions taken, which will ensure legal certainty, prevent abuse of power, and promote the honest performance of state functions; in-depth development of e-government and e-democracy tools, which will help reduce corruption risks by minimizing direct contact between officials and citizens, transparency and convenience of obtaining public services; introducing regular independent audits of state institutions, creating effective anti-corruption mechanisms, developing a system of state and public monitoring, introducing effective sanctions for violations of ethics and legislation, which will allow for a comprehensive assessment of the work of state bodies and ensure the inevitability of punishment for abuse; introduction of a system of continuous training, professional development and advanced training of civil servants, which will allow the formation of competent, responsible managers, will contribute to the development of a culture of integrity, business ethics and orientation towards the interests of citizens; clear and objective criteria for evaluating the performance of civil servants, which will allow forming a system of promotions based on professional achievements, competence and personal integrity, making it impossible to promote through corrupt connections or informal agreements.

Predictive modeling of 3D reconstruction trajectories for potential programmable materials

IntroductionShape-morphing programmable materials, capable of dynamically adjusting their properties in response to external stimuli, hold significant potential in adaptive design and smart manufacturing. However, accurately predicting their 3D reconstruction trajectories remains a challenge due to the complex interactions between material behavior and environmental factors.MethodsTo address this, we propose a computational framework, the Dynamic Morphology Engine (DME), designed to enhance predictive modeling of shape-morphing programmable materials by integrating advanced control mechanisms and optimization strategies. The DME framework consists of three key components: Stimulus Mapping, Property Optimization, and Structural Adaptation, enabling efficient trajectory prediction in dynamic environments. Additionally, we introduce the Stimulus-Informed Design Paradigm (SIDP), which leverages data-driven modeling to refine the interplay between external stimuli and material responses.Results and discussionExperimental results demonstrate that our approach improves robustness, scalability, and computational efficiency, offering a promising tool for modeling shape-morphing programmable materials in applications such as soft robotics, reconfigurable structures, and intelligent materials.

Energy management with control parameter optimization for a PV/FC/Battery islanded DC microgrid

Abstract The integration of renewable energy resources (RERs) and the need for reliable and efficient power distribution in emerging power systems has driven growing interest in microgrids. This has led to challenges like uneven load distribution, overloading, less usage of power, and unstable operations that may lead to damage to power electronic devices connected. The existing metaheuristic-based control mechanisms struggle to manage fluctuating sources and demands effectively, often leading to suboptimal energy management. Therefore, with such constraints, this research work proposes a method utilizing Sparrow Search Optimization (SSA) and optimizes the control parameters for more effective EMS functionality. To support efficient power management and balancing of generation versus load demands, the proposed system integrates dispatchable distributed generators such as fuel cells (FC) and battery storage systems (BSS) with non-dispatchable distributed generators such as solar photovoltaic (PV) source. The method uses SSA optimization of controller parameter estimation ensuring better stability and reliability, compared to conventional PI and other metaheuristic methods. The intended system was tested under various operating scenarios with the use of MATLAB Simulink, to validate the efficacy of this system in the regulation of renewable energy fluctuations and optimization of battery performance. The performance of the developed system was compared with systems optimized through Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Harris Hawk Optimization (HHA). Simulation results show that the system optimized using the SSA method results in better efficiency with faster execution time than other optimization-based systems.

Using Internet of Things to Deal with Pandemic: A Use Case Based Framework.

The objective of this study is to develop a conceptual framework for use cases applicable to the development of an Internet of Things (IoT) system, designed for intelligent environments capable of managing the pandemic. To achieve this objective, a comprehensive content analysis of scholarly articles from MDPI, PubMed, and Google Scholar was conducted. Best practices were identified, and various application examples were synthesized to establish an IoT-based framework. The study proposes measures for the implementation of technologically advanced environments and services while ensuring public compliance with these developments. Based on the identified use cases and enabled applications, a conceptual framework was formulated. The key use cases for IoT applications include traffic management, patient health monitoring, early virus detection, remote work facilitation, smart hygiene solutions, tracking infected individuals, monitoring social distancing, enhancing health care facilities, and ensuring quarantine compliance. To ensure rapid and effective implementation of policies, regulations, and government orders, robust architecture, applications, and technological infrastructures must be developed. This study explores new architectural frameworks, potential use cases, and avenues for future advancements in IoT-based applications. The use cases are categorized as near-field measures, hybrid measures, centralized control mechanisms, and their integration in the defense against COVID-19.

Computational similarities between social and nonsocial processing in cognitive control.

It is widely accepted that upright faces are processed more holistically than inverted faces, but there is limited evidence on how face orientation affects holistic processing in conflict tasks and how this differs in arrow and gaze processing. To address these gaps, we devised a novel arrow-gaze Stroop task involving both arrow and gaze judgments. Our results show that face orientation does not influence the congruency effect in this Stroop task. However, the congruency effect is significantly stronger for gaze judgments than for arrow judgments. We used hierarchical Bayesian estimation to evaluate three conflict drift-diffusion models-the diffusion model for conflict tasks, the dual-stage two-phase model, and the shrinking spotlight model (SSP)-to examine holistic cognitive control mechanisms. Our model-based analysis reveals that the SSP outperforms the diffusion model for conflict and dual-stage two-phase models. Representational similarity analysis of the SSP model parameters between gaze and arrow judgments suggests two key findings: (a) Feature-based processing of both arrow and gaze tasks, along with conflict-related factors, explains the similar congruency effects observed across both face orientations, while the processing speed of relevant stimulus attributes impacts overall performance, and (b) there are both shared and dissociable attentional effects between gaze and arrow processing. These findings provide new insights into the shared computational mechanisms underlying social and nonsocial cognitive control processes. (PsycInfo Database Record (c) 2025 APA, all rights reserved).