Implementation Of Approach Research Articles

The vertical-velocity skewness in the inertial sublayer of turbulent wall flows

Empirical evidence is provided that within the inertial sublayer (i.e. logarithmic region) of adiabatic turbulent flows over smooth walls, the skewness of the vertical-velocity component $S_w$ displays universal behaviour, being a positive constant and constrained within the range $S_w \approx 0.1\unicode{x2013}0.16$ , regardless of flow configuration and Reynolds number. A theoretical model is then proposed to explain this behaviour, including the observed range of variations of $S_w$ . The proposed model clarifies why $S_w$ cannot be predicted from down-gradient closure approximations routinely employed in large-scale meteorological and climate models. The proposed model also offers an alternative and implementable approach for such large-scale models.

Landslide Thickness Estimated from InSAR-Derived 2D Deformation: Application to the Xiongba Ancient Landslide, China

The thickness estimation of landslides is crucial for better landslide evaluation. Traditional non-contact mass conservation methods using 3D deformation may be unsuitable due to observation limitations. This study proposes a more feasible approach based on 2D deformation from two-track Interferometric Synthetic Aperture Radar (InSAR) observations, applied to the Xiongba landslide. The comparison with geological and drilling measurements confirms the reliability of this method. The mapped InSAR LOS deformation rate fields reveal two regions: a significantly deformed frontal zone and a relatively stable zone. Analysis suggests that surface uplift at the Xiongba-H2 landslide’s front edge results from rock–soil mass pushing in high-deformation areas. The estimated thickness ranges from 10 to 100 m, with an active volume of 6.17 × 107 m3. A thicker region is identified at the front edge along the Jinsha River, posing the potential for further failure. This low-cost, easily implemented approach enhances InSAR’s applicability for landslide analysis and hazard assessment.

Realisation of an Application Specific Multispectral Snapshot-Imaging System Based on Multi-Aperture-Technology and Multispectral Machine Learning Loops

Multispectral imaging (MSI) enables the acquisition of spatial and spectral image-based information in one process. Spectral scene information can be used to determine the characteristics of materials based on reflection or absorption and thus their material compositions. This work focuses on so-called multi aperture imaging, which enables a simultaneous capture (snapshot) of spectrally selective and spatially resolved scene information. There are some limiting factors for the spectral resolution when implementing this imaging principle, e.g., usable sensor resolutions and area, and required spatial scene resolution or optical complexity. Careful analysis is therefore needed for the specification of the multispectral system properties and its realisation. In this work we present a systematic approach for the application-related implementation of this kind of MSI. We focus on spectral system modeling, data analysis, and machine learning to build a universally usable multispectral loop to find the best sensor configuration. The approach presented is demonstrated and tested on the classification of waste, a typical application for multispectral imaging.

An unobserved lava fountain deciphered in real-time by high-precision borehole strainmeter and contribution to hazard evaluation: the Etna 21 May 2023 eruption

A powerful lava fountain took place on 21 May 2023 at Mt. Etna after a year of repose, preceded a few days earlier by a shallow seismic swarm. The main critical issue with the eruption was the difficulty to track this eruptive event with conventional remote sensing devices, such as webcams and satellite instruments, due to the bad weather conditions and especially the dense cloud cover. Despite the sophisticated monitoring available at the volcano, the eruption effectively remained “hidden”. It was here that the borehole dilatometers excelled: as with all recent lava fountains at Etna, these high-precision instruments detected significant strain changes and proved a valuable contribution to real-time monitoring of the event. Through recently implemented approaches, the analysis of the strain data allowed us to decipher the eruption: namely identify the timing of the events, evaluate the “size” of the fountain (i.e. its eruptive intensity), and also estimate the erupted volumes in near real-time. This provided a useful support during the Civil Protection emergency meeting at the Prefecture of Catania, where these results were presented and jointly discussed. Overall, the 21 May 2023 lava fountain was an important showcase, demonstrating the strategic contribution that real-time high-precision strain signals may have in defining and assessing the hazard associated with an eruptive event even in adverse weather conditions, when remote sensing systems may be unable to furnish direct information on the ongoing phenomenon.

Improving Lynch syndrome detection: a mixed-methods process evaluation of a hybrid type III effectiveness-implementation trial

IntroductionTranslating evidence-based practices into real-world healthcare settings is challenging, particularly in the rapidly evolving field of genomics. A pragmatic two-arm cluster-randomized clinical trial (Hide and Seek Project – HaSP) tested two implementation approaches for improving hereditary cancer referral practices with one key distinction: implementation strategies that were designed 1) explicitly using psychological theory, or 2) using healthcare professional intuition. This mixed-methods process evaluation aimed to provide insights into how and why change occurred by examining contextual determinants, identifying mechanisms of action, and exploring the role of theory.MethodsPost-implementation interviews were conducted with Implementation Leads and clinicians from participating HaSP sites. Transcripts were analysed using a mixed inductive and deductive approach, guided by the updated Consolidated Framework for Implementation Research (2.0). Findings were triangulated with other HaSP process evaluation data sources, including HaSP focus group observations, HaSP research team focus groups, MDT observations, and Implementation Lead project logs. Logic models and case studies were developed to articulate causal processes underlying strategy effectiveness and conditions necessary for implementation success.ResultsEighteen participants from seven HaSP sites were interviewed. Qualitative analysis identified themes related to Lynch syndrome complexity, pandemic disruptions, operational challenges, information technology constraints, multidisciplinary collaboration, cultural determinants, attitudes towards change, the value of theory, adaptations, and implementation support. Within these themes, a total of 39 contextual determinants were identified, with barriers and facilitators spanning 18 CFIR constructs across five domains. Logic models and case studies highlighted a number of mechanisms of action, producing variable clinical outcomes. Process evaluation findings, interpreted together with HaSP trial outcomes, indicate that theory-based implementation strategies may better support Lynch syndrome detection practices compared to intuition-based strategies.ConclusionsThe information gained from this process evaluation deepens understanding of the factors influencing the success of hospital-specific implementation strategies within the HaSP framework. Potential pathways for optimising the effectiveness of the overall HaSP implementation approach have been identified.Trial registrationAustralian New Zealand Clinical Trials Registry, ACTRN12618001072202. Registered 27 June 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375348&isReview=true.

Phase-field modeling of interfacial fracture in quasicrystal composites

Quasicrystals (QCs) have been used as a particle reinforcement phase in polymer or metal matrix composites to enhance the material strength, hardness and wear resistance while maintaining the lightweight advantages of the composites. In this paper, a phase-field fracture model (PFM) is proposed to predict crack propagation and interfacial debonding in QC composites. The phase-field and interface-field variables are introduced to regularize the cracks and interfaces in the composites, respectively. An equivalent critical energy release rate is introduced to characterize the influence of the interface on crack propagation. The present model is numerically implemented in Comsol Multiphysics based on the Weak Form PDE module. Several numerical examples are simulated to demonstrate the ability of the proposed model to predict crack propagation and interfacial failure of QC composites and to analyze the influence of QC reinforcement phase on fracture behaviors of QC composites. Numerical results indicate that the interface significantly influences the crack propagation paths, and the phason elastic field has a remarkable influence on the peak force and failure displacement in the fracture test of QC composites. The developed phase-field model and numeral implementation approach provide a convenient tool for predicting interfacial failure and assessing the safety of QC composites in engineering.

Challenges in Public-Private Partnership (PPP) Projects in Malaysia

The Public-Private Partnership (PPP) implementation approach in Malaysia aims to enhance the delivery of public sector infrastructure and services. However, the Auditor General's Report 2012 highlighted several deficiencies in PPP project management, including delays, poor quality, and inefficient resource use. This study seeks to identify the issues in the management of PPP projects in Malaysia that contribute to these ongoing problems and to propose improvements for enhancing PPP practices. Adopting a qualitative approach with an inductive single case study, the research involved semi-structured interviews with 14 participants conducted over one month in May 2024. The data were analyzed using NVivo Version 14 software through thematic analysis, which generated relevant codes, categories, themes, and domains. The findings reveal seven key strategic issues in PPP project management, such as accountability; incentives and assistance; values, norms, and prevalence; standards and procedures; good and moral governance; duties and roles; and laws and regulations. To improve PPP practices in Malaysia, it is essential for both the government and private sector key players in PPP project management to focus on enhancing capacity building and process optimization. This study provides valuable insights for future PPP project management in Malaysia and serves as a guide for strengthening PPP practices.

Dynamic Treatment Regimes on Dyadic Networks.

Identifying interventions that are optimally tailored to each individual is of significant interest in various fields, in particular precision medicine. Dynamic treatment regimes (DTRs) employ sequences of decision rules that utilize individual patient information to recommend treatments. However, the assumption that an individual's treatment does not impact the outcomes of others, known as the no interference assumption, is often challenged in practical settings. For example, in infectious disease studies, the vaccine status of individuals in close proximity can influence the likelihood of infection. Imposing this assumption when it, in fact, does not hold, may lead to biased results and impact the validity of the resulting DTR optimization. We extend the estimation method of dynamic weighted ordinary least squares (dWOLS), a doubly robust and easily implemented approach for estimating optimal DTRs, to incorporate the presence of interference within dyads (i.e., pairs of individuals). We formalize an appropriate outcome model and describe the estimation of an optimal decision rule in the dyadic-network context. Through comprehensive simulations and analysis of the Population Assessment of Tobacco and Health (PATH) data, we demonstrate the improved performance of the proposed joint optimization strategy compared to the current state-of-the-art conditional optimization methods in estimating the optimal treatment assignments when within-dyad interference exists.

Current approaches in development and implementation of medical education strategies among pediatric hematology/oncology fellowship programs

Application of evidenced-based practices is often lacking in medical education. Increased recognition that methods of knowledge delivery based in relevant learning theories are more effective has led to improved ability to meet the needs of adult learners. We designed a study to assess approaches to education for Pediatric Hematology/Oncology (PHO) trainees and identify opportunities for incorporation of evidence-based practices. A national survey was shared with program directors (PDs) of PHO programs to investigate current trends in education design. Respondents were contacted via email, the survey was distributed by REDCap, and data were collected from April-July 2023. Quantitative data were analyzed descriptively and free-text responses using directed content analysis. Of the 77 eligible participants, 46 completed the survey (59.74% response rate), representing various geographic regions and class sizes. Respondents reported a wide range of familiarity with adult learning theory (range 1–5, median 3) and self-regulated learning (range 1–5, median 2). While programs employed active learning strategies to varying degrees, the lecture format was the most used method of education delivery. PDs recognized the need for development in several domains, including incorporation of educational frameworks, support for structure and content of didactics, and implementation of feedback related to education sessions. Differences in approaches were described, revealing a wide range of familiarity with and application of specific educational theories, as well as inconsistent efforts to consider principles of adult learning theory and self-regulated learning. These data demonstrate opportunities for targeted education and curriculum development.

Turning the Page on Hardcopy Risk Management Plan Educational Materials: Digitalization Made Possible.

'Risk Management Plan Educational Materials' (RMP EMs) are additional risk minimization measures (aRMMs) intended to prevent or reduce the occurrence of adverse reactions associated with the exposure to a medicine, or to reduce their severity or impact on the patient. While the healthcare sector is embracing various digital tools and platforms for educational and/or awareness building purposes, paper-based materials have remained the mainstay approach for implementation of aRMMs by pharmaceutical companies. Novartis in Singapore conducted a pilot on the feasibility of distributing electronic copies of RMP EMs (e-RMP). Post-pilot, e-RMP was officially implemented in Novartis Singapore. A year following the launch of e-RMP, a survey was performed with healthcare professionals (HCPs) to understand end-users' experience. The survey responses revealed a general preference by both HCPs and patients towards e-RMP. Digital methods of delivering educational aRMMs offer great benefits over traditional paper-based programs. e-RMP significantly reduces the time needed for updated RMP EMs to reach HCPs and their patients/caregivers. This is important to ensure that HCPs and patients/caregivers are made aware of any updates in key safety messages of the products in a timely manner to ultimately ensure patient safety. The successful transition to digital solutions requires purposeful collaborations between key stakeholders of the healthcare ecosystem including regulatory authorities, pharmaceutical companies, HCPs, patients and caregivers. This article aims to provide insights on the digitalization journey of e-RMP, a case study in Singapore, outlining the value but also some of the challenges faced during this transformation.

Visible Human Project based applications can prompt integrating cross-sectional anatomy into the medical school curriculum when combined with radiological modalities: A three-year cross-sectional observational study

BackgroundCross-sectional anatomy is a challenging yet a vital foundation to clinical practice. The traditional teachings of gross anatomy cadaveric dissections do not cover adequate training of recognizing anatomical structures on CT, MRI and sonographic cross-sections. New modern technologies are emerging as teaching tools in anatomy aiming to deliver visual interactive experience. The Visible Human Project provides a library of cross-sectional images compiled from cryosectioned body donors that was utilized by modern technologies such as the virtual dissection table (Anatomage) in constructing 3D software applications visualizing the internal composition of the human body virtually. Hereby, this article explores an integrative approach utilizing the Visible Human Project based applications and basic radiological modalities. PurposeThe purpose of our newly implemented teaching approach was to test and assure technology fitness to the medical curriculum and its potential influence on students’ performance in learning gross as well as cross-sectional anatomy in much depth. Basic proceduresA three years (2021–2024) observational study was conducted by implanting a practical cross-sectional anatomy optional course by selectively utilizing Anatmage interactively beside CT, MRI and ultrasound practice. The performance of 50 participants was evaluated in the form of a written test comprised of labeling of ten cross-sectional images and drawing of two cross-section schemes. Their optional course test scores were compared to their obligatory anatomy subject test scores; and to a non-participants control group of 50 retrospective obligatory anatomy subject test scores. In addition, the participants’ attitude toward the training lessons was assessed through a survey focused on satisfaction level, competence and ability to recognize structures on radiological images. Main findingsThe participants reported a high level of practical engagement. The test scores in the anatomy obligatory subject were positively influenced by this implemented practical course. Students showed improved test scores in the standardized labeling keyword questions, while the scheme questions showed discrepancy. Principal conclusionsIntegrating Visible Human Project based applications with radiological modalities showed positive efficacy on the students’ engagement and learning performance. Inevitably, cadaveric dissection and prosection remain the cornerstone of gross anatomy education. Integrating both modalities of teaching would excel students’ practical skills in applied clinical anatomy.

Toward a gender transformative change perspective for smallholder agricultural commercialization: building consensus among experts

While smallholder agricultural commercialization has been posited as a catalyst to bring about broad economic benefits, evidence demonstrates that commercialization efforts that are gender blind can exacerbate inequalities. This study employed a consensus-building process for gender and agricultural development experts to formulate a perspective for informing the design and implementation of gender transformative smallholder agricultural commercialization interventions. A three-round Delphi process was used to systematically achieve agreement among 23 experts who address gender issues and implement gender transformative approaches (GTAs) in smallholder agricultural systems. Over the three rounds, the experts systematically generated and prioritized 58 intended changes and conceptual considerations for design and implementation into a final set of 23 statements that were categorized as: GTA design and implementation fundamentals, potential target changes in smallholder agriculture, and standard gender integration measures. Unlike many Delphi studies, we also highlight expert statements that did not achieve consensus in both rounds as well as the qualitative divergence. Key themes based on the agreed upon findings include involving diverse actors in co-development of GTAs, applying an intersectional lens, tackling root causes of power relations in the value chain, addressing constraining norms, increasing women’s access to and control of resources, and strengthening agency and solidarity.

INTERWEAVING DIPLOMACY, DATA, AND TECHNOLOGY FOR SUSTAINABILITY: A CASE STUDY OF BARCELONA’S LOCAL GOVERNANCE

Local governance plays a crucial role in sustainable development. While research has examined diplomacy, data, and technology within local governance, their combined impact still needs to be explored. This study aimed to investigate how the city of Barcelona integrated diplomatic relations, data-driven insights, and technological advancements to propel local sustainability efforts. Employing a qualitative approach with a multi-method design, the study explored the interaction of diplomacy, data, and technology in fostering sustainable community development. The tracing process involved analyzing official reports, city council documents, and academic publications from 2015 to 2023. In-case analysis complemented process tracing and focused on specific policies, programs, and practices that promoted data-driven decision-making and technology use within Barcelona’s sustainability efforts. The detailed examination included documents from the Barcelona city website and other official sources. The Inductive, Descriptive Case Study allowed natural phenomena to emerge; finally, thematic analysis categorized patterns and identified key themes related to diplomacy, data, and digital technologies within Barcelona’s LGSD context. The investigation revealed a compelling three-pronged approach: (i) Cross-sectoral Diplomacy and Engagement: Barcelona fostered a collaborative environment where diverse stakeholders worked in concert. (ii) Data-Driven Decision Making: The city leveraged the power of data to inform strategic policy choices. (iii) Technology-Enhanced Governance: Technology acted as a catalyst, streamlining and optimizing governance processes. The study offers valuable insights for policymakers and stakeholders in other countries seeking to adopt similar strategies. Further research must explore context-specific implementation approaches and diplomatic strategies, considering different regions' diverse social, civic, political, and economic landscapes.

Identifying Positive Practices to Institutionalize Social Innovation in the Malawian Health System.

Governments worldwide are increasingly interested in scaling up effective public health innovations, but it is not always easy to institutionalize innovations, arising outside the public health system, as a part of national delivery. Evidence on how country governments can practically achieve this is limited. This article describes the institutionalization of the Chipatala Cha Pa Foni (CCPF, Health Center by Phone) social innovation into the Malawian public health, and identifies positive institutional practices that local actors drew on to achieve this. A positive-oriented interdisciplinary multi-method qualitative case study design was adopted. Data were collected from key informant interviews, observations, and documents over 18 months. A composite social innovation framework, informed by institutional theory and positive organizational scholarship, guided the thematic content analysis. Four clusters of positive institutional practices aided the institutionalization of the innovation: building high-quality relationships; creating opportunities for experiential interaction; cultivating hope; and logic attunement and awareness. We describe how these four practices operated together as a process of 'everyday creativity' to achieve institutionalization. We illustrate the importance of high-quality relationships, marked by respect, mutuality, and appreciation, as the foundation upon which hope can be built and the creativity needed for institutionalization to flourish. National ownership and sustainability of innovations are enhanced when implementation and institutionalization approaches are attuned to the logics inherent in national identity. In this article, we highlight the importance of institutional and interpersonal dynamics in the institutionalization of social innovation in health systems.

The use of a nursing implementation framework to enhance the uptake of an evidence-based intervention.

Evidence-based practices (EBPs) are instrumental in improving patient outcomes and ensuring high-quality nursing care, yet their implementation often encounters substantial barriers. The Iowa Implementation for Sustainability Framework and the Precision Implementation Approach© offer systematic strategies for overcoming barriers and enhancing EBP implementation and sustainability in health care settings. This project aimed to use the Iowa Implementation for Sustainability Framework and the Precision Implementation Approach© to support the use of an evidence-based maternal depression intervention within Iowa's Title V Maternal Health Program that serves mothers of young children living in poverty. This practice-based implementation was accomplished in three steps: (1) hold intervention-focused staff meetings, (2) identify barriers to using the intervention, and (3) identify and deliver implementation strategies. Collected data included barriers identified, selected implementation strategies, and evaluation of meeting attendance and impact on confidence. Four of the monthly virtual staff meetings focused on Listening Visits (LV) use. The 7 strategies comprising our approach to supporting LV use addressed three categories of identified barriers: lack of confidence, logistical issues, and not understanding intervention procedures. In the LV-focused meetings, representation of the 14 maternal health clinics was high, although attendance by individual staff was inconsistent. Post-meeting polls indicated that 40% to 65% of attendees felt more confident using intervention skills. This practical nursing-implementation framework facilitated EBP adoption, and our well-structured targeted strategies effectively increased staff confidence. Nursing managers and educators should consider using this framework to enhance their organizations' capacity to implement EBPs sustainably.

Implementing Reform: Approaches to Alter the Use of Local Jail for People with Behavioral Health Conditions.

To reduce the overrepresentation of people with behavioral health conditions in jails, jurisdictions have implemented evidence-based programs/policies (EBPPs) and treatments (EBTs). Using survey data from 519 U.S. counties, the present study classifies and evaluates the impact of strategies used to implement EBPPs and EBTs. Exploratory factor analysis identified four implementation approaches (i.e., clusters of strategies) which counties utilize to different extents depending on their population size: Relationship-Building among agencies (α = .911), infrastructural Capacity-Building (.788), developing Quality Programming (.880), and establishing Shared Definitions of key terms (.913). Relationship-Building and Shared Definitions were significant predictors of increased county-level availability of EBPPs and EBTs. These findings indicate that approaches focusing on interagency collaboration appear especially impactful. However, strategies that require more resources (viz. Capacity-Building) are underutilized. For smaller and/or rural counties with limited resources, an initial emphasis on interagency collaboration approaches can yield positive outcomes, as these require less initial investment and appear especially versatile.

AI and Ethics: Moral Considerations of Automated Rumor Detection Technology

Abstract: As digital society continues to develop, social media and information distribution have experienced significant changes, leading to challenges with accessing credible information and identifying misinformation. In response, the use of AI automation technology has been advocated as a solution to identifying fake news and improving information credibility. However, implementing this technology raises ethical concerns related to data privacy protection, transparency in information monitoring, and maintaining a balance between free speech and censorship. This paper examines ethics associated with using AI automation techniques for identifying misinformation, and proposing relevant laws and ethical guidelines to address these concerns. Through a literature review and case analysis, this study provides guidance for the ethical implementation of AI automation techniques for identifying misinformation. Our research aims to contribute to the development of sound ethical practices in the use of AI automation techniques in misinformation identification. Furthermore, this study highlights the need for an integrated approach in AI automation technology implementation and the significant role of transparency and accountability in mitigating ethical concerns. Additionally, this paper explores the potential benefits and pitfalls associated with using AI automation techniques to identify misinformation. While such technology can improve information credibility and protect the democratic process, it also poses risks to the quality of information and public trust in technology. In conclusion, this study underscores the importance of ethical considerations in implementing AI automation techniques for identifying misinformation and provides guidance for policymakers and practitioners working in the field of AI and information governance.

Pragmatic online obesity treatment in primary care: a hybrid randomized clinical trial of implementation strategies

Online behavioral weight loss (BWL) in primary care is effective and disseminable. This trial compared two implementation approaches on program uptake, use, and weight loss via a pragmatic hybrid type 2 implementation-effectiveness design to evaluate online BWL implementation (Rx Weight Loss [RxWL]) and effectiveness. This manuscript presents the implementation results. RxWL was implemented across a state-wide network of primary care clinics using lower- and higher-intensity implementation strategies (Basic [base program] and Enhanced [base plus enhanced training and dashboard], respectively) between 2018 and 2022. Nurse care managers (NCMs; N = 23) were recruited and block-randomized to implementation condition. Adult primary care patients (body mass index [BMI] > 25 kg/m2, internet-connected device access) were referred and enrolled by their NCMs. Outcomes were the proportion of eligible patients who enrolled in and completed RxWL by NCM condition, initial weight loss and regain over 12 and 24 months by NCM condition, and clinician acceptability and feasibility. NCMs (N = 12 Enhanced, N = 11 Basic) in Enhanced enrolled more patients (N = 490) than in Basic (N = 164). Although the proportion of patients who completed RxWL and mean weight loss did not differ by condition, different enrollment rates resulted in the Enhanced condition engaging more patients. NCMs rated RxWL as acceptable and feasible with no difference by condition. Findings support connecting primary care patients with technology-based health behavior change programs. Clinical trial registration number: ClinicalTrials.Gov identifier NCT03488212: https://clinicaltrials.gov/ct2/show/NCT03488212. Trial registration: clinicaltrials.gov Identifier: https://clinicaltrials.gov/study/NCT03488212.

Terrain Analysis According to Multiscale Surface Roughness in the Taklimakan Desert

Surface roughness, interpreted in the wide sense of surface texture, is a generic term referring to a variety of aspects and scales of spatial variability of surfaces. The analysis of solid earth surface roughness is useful for understanding, characterizing, and monitoring geomorphic factors at multiple spatiotemporal scales. The different geomorphic features characterizing a landscape exhibit specific characteristics and scales of surface texture. The capability to selectively analyze specific roughness metrics at multiple spatial scales represents a key tool in geomorphometric analysis. This research presents a simplified geostatistical approach for the multiscale analysis of surface roughness, or of image texture in the case of images, that is highly informative and interpretable. The implemented approach is able to describe two main aspects of short-range surface roughness: omnidirectional roughness and roughness anisotropy. Adopting simple upscaling approaches, it is possible to perform a multiscale analysis of roughness. An overview of the information extraction potential of the approach is shown for the analysis of a portion of the Taklimakan desert (China) using a 30 m resolution DEM derived from the Copernicus Glo-30 DSM. The multiscale roughness indexes are used as input features for unsupervised and supervised learning tasks. The approach can be refined both from the perspective of the multiscale analysis as well as in relation to the surface roughness indexes considered. However, even in its present, simplified form, it can find direct applications in relation to multiple contexts and research topics.

An approach for real-time implementation of cyber security in power system network

Abstract In this era of Web World-3, usage of the Internet of Things (IoT) in power system networks has attained scalable altitude. By using this technology, data can be transferred and monitored from the far end. Further, the suggested corrective actions are also executed. However, recently, many cyber-attacks have been observed on the power system in which activities such as injection of false data, unwanted switching operations, formation of sub-system layers, and false indication of failure of cyber-physical components (CpC) are experienced. In the worst case, it leads to invite cascade tripping of the power system. Utmost care is taken for the selection of CpC for the power system. However, it is observed that the cyber attackers mostly take entry into the network using the CpC of the power system. Cyber attackers perform false switching operations and false data injection. This article suggests a cyber security concept to minimize the false switching operations and false data injection in the power system network. A hardware model is prepared and the working scheme is implemented using IoT technology. The hardware result suggests that the un-authentic attempt/cyber-attack has been identified and the alarm is generated. It also does not permit the un-authentic person to access the real-time data. A wide range of applicability of the suggested scheme has been verified by hardware results. In addition to this, the power factor correction algorithm also works satisfactorily in the hardware along with the cyber security constraints. In order to prove wide range of applicability of the suggested scheme, additional features such as controlling of multiple switching devices and interlock between CB and earthing switch has been successfully implemented in developed hardware.