Integrity Monitoring Research Articles

Exploring EFL Students' Creativity and Engagement with AI Chatbot in Web-Based English Course

This research explores the role of AI-based chatbot tools in promoting creativity and engagement among English as a Foreign Language (EFL) students in web-based English material development course. A qualitative research design was employed, involving in-depth interviews and observation checklists. The research was conducted at the English Education Faculty in Parangtambung of Universitas Negeri Makassar, with data collection spanning from May 12, 2024, to June 9, 2024. Participants included five undergraduate students from the 6th semester based on their familiarity with AI chatbots. The subjects of this research were undergraduate students enrolled in the English web-based material development course. Specifically, five students with prior experience or familiarity with AI chatbots were chosen to provide detailed insights through interviews and observations. The findings indicate that AI chatbots significantly encourage creativity among EFL students by providing a safe space for language experimentation and immediate feedback. Students reported increased engagement and enjoyment in their learning process. The research concludes that while AI chatbots can effectively foster creativity and engagement, careful integration and continuous monitoring are necessary to maximize their educational benefits.

Overbounding the Model Uncertainty for Kalman Filter-Based Advanced Receiver Autonomous Integrity Monitoring in the Presence of Time Correlation by the Hybrid Evolutionary Algorithm

Overbounding the Model Uncertainty for Kalman Filter-Based Advanced Receiver Autonomous Integrity Monitoring in the Presence of Time Correlation by the Hybrid Evolutionary Algorithm

Effect of ultrasound-guided internal branch of superior laryngeal nerve block on postoperative sore throat induced by a NIM-EMG-ETT: study protocol for a double-blinded randomized controlled trial

BackgroundPostoperative sore throat (POST) is a common complaint after general anaesthesia. The prevalence of POST caused by a neural integrity monitor electromyography endotracheal tube (NIM-EMG-ETT) is high. This study aimed to determine whether ultrasound-guided internal branch of superior laryngeal nerve block (iSLNB) could alleviate POST associated with a NIM-EMG-ETT.MethodsThis randomized controlled trial plans to enroll 182 patients scheduled to undergo general anaesthesia with a NIM-EMG-ETT. Patients will be randomly allocated into the iSLNB group or the control group according to randomized numbers generated by Excel. After induction, patients in the iSLNB group will undergo ultrasound-guided iSLNB with ropivacaine, and patients in the control group will undergo the same procedure with normal saline. The prevalence, severity, visual analogue scale score of POST, and postoperative acoustic analysis will be recorded.DiscussionTo the best of our knowledge, this is the first study to evaluate the effect of ultrasound-guided iSLNB with ropivacaine on the mitigation of POST induced by NIM-EMG-ETT. Our study will provide clinical answers to alleviate POST induced by NIM-EMG-ETT. The results of this study may provide a safe method to prevent POST caused by NIM-EMG-ETT.Trial registrationChinese Clinical Trial Registry, ChiCTR2300076393. Registered on October 24, 2023, http://www.chictr.org.cn/index.aspx.

Heart Shape to Fracture Distance: Characterizing Hydraulic Fracture Propagation before Hits

Summary Estimating the distance from the hydraulic fracture tip to the monitor well can be useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. A heart-shaped signal is referred to as the extensional precursor of a fracture hit recorded by crosswell strain measurements and can serve as a vital tool for such estimation. This study incorporates the 3D displacement discontinuity method (DDM) to understand the impact of fracture geometry and monitor well offset on the heart-shaped signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of the heart-shaped signal and the fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2 (HFTS2). A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and enhanced geothermal system reservoir development, as well as caprock integrity monitoring for carbon sequestration projects.

Wazuh SIEM for Cyber Security and Threat Mitigation in Apparel Industries

Security of IT infrastructure is critical in the modern digital environment, particularly for industries that manufacture clothing. The application of the Wazuh Security Information and Event Management (SIEM) system to improve security monitoring and compliance for an IT system in the apparel industry is the main topic of this study. To improve the apparel industry cyber threat monitoring system in real-time monitoring, detecting the threat vectors that support the centralized management system, to meet these objectives of the company, an SIEM security management system has been installed and configured with the components of Wazuh manager, indexer, Wazuh agent, and Wazuh dashboard as well. An Oracle virtual lab environment was created to install and configure the Wazuh system a robust Linux operating system was installed at the server level and Windows 10 was installed on the client end to the authenticity failure of the security system. To implement the Wazuh system, the project management guideline was followed which ensured the planning and implementation of the project, testing phases, and along with review and maintenance. Wazuh security management system successfully identified the authentical failure reports and vulnerabilities and generated automated reports from the system that showed the result of 1 critical, 19 high, and 5 medium levels of vulnerabilities shown in Figure 6, and the necessary patch recommended to solve the critical issues. On the other hand, the system also generated security events as well as integrity monitoring system reports. The deployment of the Wazuh security management system ensured the robust cost-effective security management system with high quality for detecting cyber threats which supports the regulatory and compliance requirements and is a viable tool for the apparel industry to protect the stakeholders’ interest.

The relationship between audit committees, external auditors, and internal control systems: a literature review and a research agenda

Purpose This paper aims to focus on the relationship between audit committees, external auditors and internal control systems (ICS) and strives to point out mutual influences between the instances to provide an integrated perspective for firms’ multilateral monitoring mechanisms. Furthermore, this study emphasizes the incorporation of sustainability and fraud considerations into the traditional roles of audit committees and auditors. Design/methodology/approach This structured literature review is based on 71 empirical-quantitative studies published in high-quality journals between 2005 and 2022. Considering the classification of ICS into ICS quality and internal audit function, the studies are analyzed with regard to audit committees’ and external auditors’ characteristics, divided into incentives and competencies, as well as their mutual relationships. Findings This study highlights a dynamic trilateral network of relationships between monitoring authorities and primarily shows that audit committees equipped with adequate competencies generate a substitutive effect for external auditors by reducing their efforts, whereas ICS quality serves as a possible mediator in this network of relationships. The establishment of an integrative three-party coalition of competent and adequately incentivized monitoring parties is essential to guarantee sufficient and appropriate ICS and overall corporate governance quality. Practical implications The findings should prompt legislators and firms to ensure a deeper collaboration between audit committees, internal auditors and external auditors to generate synergy effects and economies of scale within the integrative monitoring process. Legislators should develop stricter requirements for competencies of audit committees and auditors. These should include a holistic triad of sustainability, fraud and digital expertise as well as mandatory forensic procedures performed by all monitoring bodies. Originality/value The authors contribute to prior research by highlighting the importance of an integrative three-party coalition of monitoring authorities to ensure corporate governance quality and to generate synergy effects within a dynamic multilateral monitoring process. Furthermore, the authors offer cutting-edge implications by stressing the need for consideration of sustainability and fraud aspects in the traditional work and profiles of audit committees and auditors.

Missed detection probability evaluation for the RAIM based on worst-case fault magnitude searching

Missed detection probability is a critical metric for the integrity performance of receiver autonomous integrity monitoring (RAIM) in the presence of faults. The traditional missed detection probability evaluation method for RAIM is limited by impractical time consumption because of the absence of accurate searching interval for the magnitude of a worst-case fault. To address this issue, the searching interval for the magnitude of a worst-case fault is constructed by the combination of minimum detectable magnitude and minimum hazardous magnitude, and the searching interval adjustment is designed to avoid the absence of worst-case fault magnitude so that the maximum missed detection probability can be accurately evaluated. The simulation result indicates that the proposed method can achieve higher accuracy for the worst-case fault magnitude searching. Furthermore, the accuracy of worldwide evaluated missed detection rate can achieve an improvement of 57·66% at most by the proposed method for the different classical RAIM algorithms.

High-performance PANI sensor on silicon nanowire arrays for sub-ppb NH3 detection

For industrial production and disease diagnosis, real-time detection of low concentrations of NH3 is crucial, necessitating a gas-sensitive sensor compatible with integrated processes and exhibiting excellent performance. Herein, we employed wet etching and rapid in-situ polymerization on silicon nanowire substrates to grow polyaniline fibers, thereby fabricating NH3 gas sensors with p-p heterojunction and three-dimensional network structures. Characterization and gas sensing performance testing were conducted. The results demonstrate the outstanding NH3 detection capabilities of the sensor, providing stable responses down to concentrations as low as 1 ppb, which indicates its LOD is one to two orders of magnitude lower than current similar products. It also exhibits verified selectivity and long-term reliability. The excellent sensing performance is attributed to the high surface area from the silicon nanowire structure and efficient synergy of p-p heterojunction. Additionally, the influence of doping types of the substrates and annealing process were explored. This work serves as a reference for the design of silicon-based gas sensors with high sensitivity, low detection limits, and extended operational lifetimes, suitable for deployment in commercial integrated monitoring systems.

Promoting social and emotional learning (SEL) in settings through emotion coaching practice: a model of engagement for practitioner use

ABSTRACT Emotion Coaching (EC) is a universal, relational approach focussed on promoting emotional wellbeing through attuned relationships. Adults coregulate children to understand different emotions they experience, why they occur and how to manage them. EC was introduced into UK educational settings in 2010 to promote children’s social and emotional learning (SEL) and build resiliency. With evidence of child and practitioner benefit, it is an adaptable ‘technique’ to manage dysregulated children and emotional situations. This paper, reports on educational practitioners’ EC experience. An inductive study, using semi-structured interviews, captured experiences and perceptions of 21, EC trained practitioners. Using constructivist grounded theory, analysis identified the fundamental role of the practitioner’s emotional identity and emotional awareness; recognised practice integration was influenced by practice opportunity and reflection with colleagues and acknowledged the need for managerial support to normalise and sustain EC in settings. With use, practitioner emotional awareness increased, suggesting modification in emotional identity, creating the opportunity to reaffirm, reconsider and re-engage in practice. Integration of EC practice was viewed as an ongoing journey, being described as ‘a way of being and a way of becoming’. The model of EC engagement conceptualised practice integration as a recursive cycle, starting and returning to the practitioner, with sequential, incremental stages. Through attuned child and adult interactions, EC confers, normalises and sustains symbiotic advantage. The model proposed is a practical tool, to guide planning, delivery and monitoring of practice integration.

Adaptive Ransomware Detection Using Similarity-Preserving Hashing

Crypto-ransomware is a type of ransomware that encrypts the victim’s files and demands a ransom to return the files. This type of attack has been on the rise in recent years, as it offers a lucrative business model for threat actors. Research into developing solutions for detecting and halting the spread of ransomware is vast, and it uses different approaches. Some approaches rely on analyzing system calls made via processes to detect malicious behavior, while other methods focus on the affected files by creating a file integrity monitor to detect rapid and abnormal changes in file hashes. In this paper, we present a novel approach that utilizes hashing and can accommodate large files and dynamically take into account the amount of change within each file. Mainly, our approach relies on dividing each file into partitions and then performing selective hashing on those partitions to rapidly detect encrypted partitions due to ransomware. Our new approach addresses the main weakness of a previous implementation that relies on hashing files, not file partitions. This new implementation strikes a balance between the detection time and false positives based on the partition size and the threshold of partition changes before issuing an alert.

Quantifying mobile robot localization safety for an EKF-based SLAM estimator: An integrity monitoring approach

The safety of SLAM-based estimation for mobile robots is a challenging research problem, particularly for life- or mission-critical exploratory applications. To address this problem, this work proposes a method to utilize integrity risk, a widely used performance metric in aviation, to quantify SLAM-based mobile robot’s localization safety. More importantly, the approach accounts for sensor measurement faults, unknown deterministic errors that cannot be modeled via Gaussian white noise. The method is tailored for an EKF-based SLAM estimator, a chi-squared failure detector, and a local nearest neighbors data association criterion. The results show that data association errors can cause significant positioning performance degradation that can only be predicted using the proposed integrity risk metric. Furthermore, the study demonstrates that as the map’s landmark density increases, mobile robot localization safety improves, except when the landmark map’s density is too high to make the features indistinguishable, which leads to positioning safety degradation.

Contributions of DNA Sequencing Technologies to the Integrative Monitoring of Karstic Caves

Contributions of DNA Sequencing Technologies to the Integrative Monitoring of Karstic Caves

Revealing the different levels of action monitoring in visuomotor transformation task: Evidence from decomposition of cortical potentials.

This study investigates the cortical correlates of motor response control and monitoring, using the Theory of Event Coding (TEC)as a framework to investigate signals related to low-level sensory processing of motor reafference and high-level response monitoring, including verification of response outcomes with the internal model. We used a visuomotor paradigm with two targets at different distances from the participant. For the recorded movement-related cortical potentials (MRCPs), we analyzed their different components and assessed the movement phases during which they are active. Residual iteration decomposition (RIDE) and multivariate pattern analysis (MVPA) were used for this analysis. Using RIDE, we separated MRCPs into signals related to different parallel processes of visuomotor transformation: stimulus processing (S-cluster), motor response preparation and execution (R-cluster), and intermediate processes (C-cluster). We revealed sequential activation in the R-cluster, with execution-related negative components and positive contralateral peaks reflecting reafference processing. We also identified the motor post-imperative negative variation within the R-cluster, highlighting the response outcome evaluation process included in the action file. Our findings extend the understanding of C-cluster signals, typically associated with stimulus-response mapping, by demonstrating C-activation from the preparatory stages through to response termination, highlighting its participation in action monitoring. In addition, we highlighted the ability of MVPA to identify movement-related attribute encoding: where statistical analysis showed independence of stimulus processing activity from movement distance, MVPA revealed distance-related differences in the S-cluster within a time window aligned with the lateralized readiness potential (LRP). This highlights the importance of integrating RIDE and MVPA to uncover the intricate neural dynamics of motor control, sensory integration, and response monitoring.

Identification of common spatial and temporal trends in the epidemiology of cattle bovine tuberculosis and human extrapulmonary and drug-resistant tuberculosis in Malawi

BackgroundIdentification of common spatial disease trends between cattle bovine tuberculosis (BTB) and human extrapulmonary tuberculosis (EPTB) and drug-resistant tuberculosis (DRTB) can support integrated disease control and monitoring programmes. We employed the recently developed multivariate disease mapping methods to examine whether the diseases exhibited any spatial correlation. MethodsA retrospective study of cattle BTB and human EPTB and DRTB cases from 2018 to 2022 was conducted. Bivariate shared spatiotemporal components models were fitted to a) cattle BTB and human EPTB and b) cattle BTB and human DRTB at the district level in Malawi, with cattle density, human density and climatic variables as independent variables. ResultsDisease specific spatial effects were higher in the southern half of the country, while the shared spatial effects were more dominant in both the south and western parts of the country. The shared temporal effects showed constant trends, while disease specific temporal effects showed an increasing pattern for cattle BTB and a constant pattern for human EPTB and DRTB. The predicted disease incidence pattern for all forms of TB in the period without data showed a constant pattern over the years. Cattle density was positively associated with cattle BTB (β: 0.022; 95% Credible Interval (CI): 0.004, 0.042). Human density was positively associated with human EPTB (β: 0.005; 95% CI: 0.001, 0.009). ConclusionCattle BTB and human EPTB and DRTB have a common spatial pattern in the west and southern parts of Malawi. Integrated interventions targeting high-density areas for cattle and human may have positive impacts on cattle BTB and human EPTB and DRTB.

Методология управления качеством образования на основе интегративной оценки

The article focuses on the study of the theoretical and methodological foundations of education quality management at a technical university, based on fundamental research and key ideas of scientists; theories of vocational, engineering and technical education; conceptual provisions, principles of assessment activities, approaches and research methods; the conceptual-categorical apparatus is clarified. Aim. To identify and generalize the theoretical and methodological foundations of education quality management at a technical university, to find its niche, basis and «foundation». Methods. Analysis of philosophical, sociological, psychological and pedagogical literature, scientific sources; state and regulatory documents on the research problem; analysis of the main concepts of this work. Results. The scientific foundations for creating an education quality management system at a technical university have been developed based on integrative assessment and monitoring of student professional development using digital resources, which ensures continuous correlation of this information with the requirements for a graduate specified in the Federal State Educational Standard and the OPOP (for a specific training profile), and adjustment taking into account these indicators of didactic conditions for the professional and personal development of students. Scientific novelty. Based on a generalization of the experience of fundamental research and key ideas of scientists in the field of pedagogy, sociology, psychology, philosophy a conceptual position is formulated on which the mechanism for managing the quality of education at a technical university is based. The practical significance of the research results is determined by the fact that in the practice of managing the quality of education, it becomes possible to evaluate the professional development of students on an integrative basis, predict changes in the development of students, and plan specific management decisions within the framework of this system.

Vascular bundle-structured polymeric composites with fire-safe, self-detecting and heat warning capabilities for power batteries thermal management

The trend of miniaturization and integration poses challenges to the thermal management of electronic devices, requiring high thermal conductivity and potential fire safety, etc. In this study, inspired by plant vascular structure, we developed a polymer composite with a vertical vascular bundle structure via a sacrificial template method and subsequent assembly of transition metal carbides/nitrides (MXene) nanosheets and phytic acid (PA) coordinated cobalt ions (Co2+) complex. The embedded MXene and PA@Co exhibit multilayer multiscale structural features, forming heat transfer channels and protective cells within the composite. The resultant composites possess high out-of-plane thermal conductivity (∼1.54 W‧m−1‧k−1) and excellent flame retardancy, including self-extinguishing, and significantly reduced heat and smoke release. Interestingly, the MXene vascular bundle structure imparts heat early warning capabilities and intelligent damage self-detection, suggesting an effective means of preventing early-stage fires and real-time monitoring of composite structural and functional integrity. Such biomimetic strategies enable new insights into the designing of multifunctional, intelligent polymer composites.

Assessing Gender and Racial Bias in Large Language Model‐Powered Virtual Reference

ABSTRACTTo examine whether integrating large language models (LLMs) into library reference services can provide equitable services to users regardless of gender and race, we simulated interactions using names indicative of gender and race to evaluate biases across three different sizes of the Llama 2 model. Tentative results indicated that gender test accuracy (54.9%) and racial bias test accuracy (28.5%) are approximately at chance level, suggesting LLM‐powered reference services can provide equitable services. However, word frequency analysis showed some slight differences in language use across gender and race groups. Model size analysis showed that biases did not decrease as model size increased. These tentative results highlight a positive outlook on integrating LLMs into reference services, while underscoring the need for cautious AI integration and ongoing bias monitoring.

Enhancing traffic flow and congestion management in smart cities utilizing SVM-based linear regression approach

With the development of smart cities, it is essential to monitor traffic flow and manage congestion effectively to ensure smooth movement for people and address their social and economic needs. As these needs continue to change, roadside infrastructure faces challenges in meeting the demands of citizens in smart cities. Traffic congestion is a major issue in road networks and occurs when the number of vehicles exceeds the capacity of the roads. Emerging technologies like Vehicular Networks (VN) and Support Vector Machine (SVM)-based linear regression offer promising solutions for vehicle-to-vehicle communication and managing autonomous roadside infrastructure. SVM-based linear regression is a well-known and effective method for addressing various issues related to roadside infrastructure, traffic management, data integration, analytics, and environmental monitoring. The main goal of using SVM-based linear regression in this research is to help citizens and city authorities make informed decisions and better understand and control traffic. This study demonstrates the application of SVM-based linear regression in integrating autonomous roadside infrastructure, achieving a high accuracy rate of 92% and reducing errors by 8%, showing a notable improvement compared to previous methods.

GNSS positioning uncertainty prediction over a planned path considering signal attenuation for urban autonomous driving

Autonomous driving requires path planning to choose an optimal path to destination. Most works on path planning focus on the shortest travelling time, but neglect positioning condition of a path while positioning accuracy is significant for autonomous driving. In this work, we predict GNSS protection level (PL), which is positioning uncertainty upper bound, over planned paths to help choose the optimal path. We propose an improved stochastic model that considers the signal attenuation caused by trees and buildings using laser scanning point cloud. An adaptive strategy is proposed to linearly correlate the improved model and the carrier-to-noise-density ratio to make our stochastic model more practical. Finally, pseudorange-based RTD PL is calculated by advanced receiver autonomous integrity monitoring (ARAIM) using the planned path information and GNSS ephemeris. The experiments demonstrate that our method reduces the misleading rate by over 90% both in horizontal and vertical directions compared to the original stochastic model, with the lowest false alarm rates.

Improving IIoT security: Unveiling threats through advanced side-channel analysis

The widespread deployment of IIoT edge devices makes them attractive victims for malicious activities. Consequently, how to implement trustworthy operations becomes a realistic topic in embedded systems. While most current physical systems for detecting malicious activities primarily focus on identifying known intrusion codes at the block level, they ignore that even an unnoticeable injected function can result in system-wide loss of security. In this paper, we propose a framework called CNDSW built on deep-learning side-channel analysis for function-level industrial control flow integrity monitoring. By collaboratively utilizing correlation analysis and deep-learning techniques, the dual window sliding monitoring mechanism in the proposed CNDSW framework demonstrates a real-time code intrusion tracking capacity on embedded controllers with a 99% detection accuracy on average. Instead of focusing on known block-level intrusions, we experimentally show that our model is feasible to detect function-level code intrusions without knowing the potential threat type. Besides, we further explore how different configurations of the CNDSW framework can help the monitoring process with different emphases and to which extent the model can concurrently detect multiple code intrusion activities. All our experiments are conducted on 32-bit ARM Cortex-M4 and 8-bit RISC MCUs across five different control flow programs, providing a comprehensive evaluation of the framework’s capabilities.