Operational Framework Research Articles

Prevalence of Oral Potentially Malignant Lesions, Tobacco use, and Effect of Cessation Strategies among Solid Waste Management workers in Northern India: a pre-post intervention study

BackgroundIndia bears the highest global burden of oral cancer, despite having an operational tobacco cessation framework. Occupational groups like solid waste management personnel face significant health challenges due to prevalent tobacco use, leading to oral potentially malignant lesions and oral cancer. Enhanced tobacco control strategies are essential for these groups.MethodsA pre-post interventional, community-based study enrolled 1200 municipal workers in Varanasi, India, from July 2022 to August 2023. 858 tobacco users underwent screening and were randomly assigned to one of three interventions: Very Brief Advice, Individual Behavioral Counseling, or Group Behavioral Therapy. Follow-up was conducted one year after the baseline interventions Effectiveness was measured by nicotine dependence reduction using the Fagerstrom Test for Nicotine Dependence (FTND) scores and cessation rates defined as at least 6-month abstinence. Appropriate statistical tests assessed the burden of tobacco use, oral potentially malignant lesions, and pre-post differences in FTND scores within and between groups. A p-value of < 0.05 was considered statistically significant.ResultsMunicipal workers exhibited a high prevalence (71.5%) of smokeless tobacco (SLT) use. One-third (32.9%) of the participants screened positive for oral potentially malignant lesions and oral cancer. Leukoplakia was the most common lesion. Screened positivity correlated with significant nicotine dependence. Among 494 follow-up participants, 47.1% reported a significant reduction in nicotine dependence across all intervention groups. Quade’s ANCOVA indicated significant differences in post-test FTND scores, with individual behavioral counselling showing the greatest reduction. However, no cessation was achieved in any group despite the significant decline in dependence.ConclusionSolid waste management personnel in Varanasi show heightened SLT use and associated oral potentially malignant lesions. The persistent tobacco use in these high-risk occupational populations undermines government tobacco control efforts and highlights the need for robust policy and implementation strategies. The study demonstrated a significant reduction in nicotine dependence following interventions, though tobacco cessation was not achieved. More frequent interventions and addressing quitting barriers—such as cultural norms, lack of awareness, easy accessibility, and adverse working conditions—are crucial. Developing a tailored workplace model to tackle tobacco use in occupational settings may facilitate cessation.Clinical trial registration numberTrial registration Clinical Trials Registry India CTRI/2020/07/026479. Date of registration 10/07/2020.

Quantum nature of black hole and the superposition of fermionic field

The operational framework for the superposition of spacetime is fundamentally important in developing a comprehensive description of quantum gravity (Foo et al. in Phys Rev Lett 129:181301, 2022). As a “bottom-up” unifying theory of quantum gravity, it allows us to investigate how mass superposition of spacetime influences the performance of quantum information processing. In this paper, we study how the quantum-gravitational effects produced by the mass superposition of a black hole influence the quantum coherence of fermionic fields. It is shown that the spacetime effects associated with a classical black hole lead to inevitable decoherence. Notably, compared to classical black hole spacetime scenarios, fermionic fields near a black hole with superposed masses can retain more quantum coherence. This suggests that the quantum properties of spacetime may serve as resources to mitigate coherent degradation caused by gravitational effects. The bottom-up perspective on spacetime superposition proposed in this work serves as an indication of quantum-gravitational effects and holds significant theoretical implications.

Hazard Identification and Risk Assessment During Simultaneous Operations in Industrial Plant Maintenance Based on Job Safety Analysis

The risk of accidents during simultaneous operations (SIMOPS) in plant maintenance has been increasing. However, research on methods to prevent such accidents has been limited. This study aims to develop a novel framework, hazard identification and risk assessment of simultaneous operations (HIRAS), for identifying and evaluating potential hazards during concurrent tasks. The framework developed herein is expected to be an effective safety management tool that can help prevent accidents during these operations. To this end, the job location and hazard information in job safety analysis (JSA) were standardized into four attributes. The standardized information was then synchronized spatially and temporally to develop a HIRAS model that identifies and assesses the impact of hazards between operations. The model was tested using 40 JSA documents corresponding to maintenance operations at Company P, a South Korean steel-making company. The model was tested in two scenarios: one with planned operations and the other with unplanned operations in addition to planned operations. The performance evaluation results of the first scenario showed an F1-score of 98.33%. In this case, a recall of 97.52% means that the model identified 97.52% of the hazard-inducing factors. The second scenario was compared with the results of a review by six subject matter experts (SMEs). The comparison of the results identified by the SMEs and the model showed an accuracy of 89.3%. This study demonstrates the potential of JSA, which incorporates the domain knowledge of workers and can be used not only for individual tasks but also as a safety management tool for surrounding operations. Furthermore, by improving the plant maintenance work environment, it is expected to prevent accidents, protect workers’ lives and health, and contribute to the long-term sustainable management of companies.

The Rise of Digital Banking in the UK Financial Sector and Its Impact on Commercial Banks

In the contemporary financial domain, the emergence of digital banks has revolutionized operational models in traditional commercial banking. This article delves into how digital banks, through advanced technology and customer-centric services, compel commercial banks to revaluate their operational and regulatory frameworks. Specifically, it focuses on the digital banking market in the UK, analyzing how digitalization and technological progress are driving the evolution of competitive dynamics within the financial sector. As one of the worlds foremost financial hubs, the UKs trends in financial market development have profound implications for the global financial system. The British government and regulatory bodies have proactively adapted to these shifts, framing policies that facilitate innovation while ensuring security and compliance within digital banking. This backdrop sets the stage for this report to explore the transformative impact of digital banks on traditional banking models in the UK, aiming to understand the regulatory adaptations and the overall influence of digital entities on the conventional banking landscape.

Leveraging Islamic Social Finance for Fair and Sustainable Tertiary Education Funding for Orphans in Malaysia: Insights from Sri Lanka

The primary objective of this paper is to draw lessons from Sri Lanka's experience with OrphanCare utilizing Islamic social finance, while also identifying avenues through which Malaysia could establish a sustainable model for achieving a similar purpose. This study uses a qualitative, exploratory approach to investigate the operational framework of OrphanCare in Sri Lanka and its potential lessons for Malaysia. Due to limited secondary sources, an unstructured interview with OrphanCare representatives was conducted to gather in-depth insights. The research unfolds in two phases: first, data collection from both primary (interviews) and secondary (reports, literature) sources to identify gaps and challenges; and second, the analysis of this data using content analysis. The OrphanCare interview from Sri Lanka offers crucial insights for Malaysia's mission in enabling orphan access to higher education. Challenges, like financial constraints and limited support networks, align with Malaysia's inequality reduction goals. Tertiary education benefits, including employability and personal growth, are highlighted. Islamic social finance lessons stress its transformative potential, while collaboration and long-term commitment are its strengths. Recommendations include education funds, support networks, career guidance, awareness campaigns, and sustainable collaborations. A regulatory framework featuring the Orphans Education Fund with a 2% annual contribution from listed companies, managed by National Higher Education Fund Corporation (PTPTN), is proposed. This paper demonstrates originality by uniquely proposing the utilization of Islamic Social Finance to enhance orphan access to tertiary education. It draws insights from Sri Lanka's OrphanCare model and presents innovative strategies for Malaysia to tackle inequalities through collaborative efforts and a robust regulatory framework.

AMORA: An Advanced Malleable and Operational Framework for Performance Prediction of Big Data Systems

AMORA: An Advanced Malleable and Operational Framework for Performance Prediction of Big Data Systems

Only consciousness truly exists? Two problems for IIT 4.0's ontology.

In this article we present two ontological problems for the Integrated Information Theory of Consciousness 4.0: what we call the (i) the intrinsicality 2.0 problem, and (ii) the engineering problem. These problems entail that truly existing, conscious entities can depend on, and be engineered from, entities that do not objectively exist, which is problematic: if something does not exist in objective reality (i.e., in itself, independently of another entity's consciousness), then it seems that it cannot be part of the material basis and determinants of other entities that do exist on their own. We argue that the core origin of these problems lies in IIT's equation between true existence and phenomenal existence (consciousness), and the corresponding ontological exclusion of non-conscious physical entities (i.e., extrinsic entities) from objective reality. In short, these two problems seem to show that IIT should reconsider the ontological status of these extrinsic entities, because they need to exist objectively to account for the ontological implications of the scenarios we present here, which are permitted by the operational framework of the theory.

Innovation platforms in practice: a conceptual framework

ABSTRACT The agricultural innovation systems (AIS) approach holds promise for researchers seeking to gain deeper understanding of how actors, norms, and knowledge interact and drive improvements in the agricultural sector in developing countries. However, use of the AIS framework in empirical research is limited and conceptual and operational frameworks are needed. In this paper we have created a conceptual framework for how innovation platforms (IPs), a unique type of multistakeholder meetings, contribute to the AIS approach by fostering innovation, networking, and performance. The conceptual framework is then applied to a case study of the Feed the Future Innovation Lab for Livestock Systems (LSIL). Findings from the case study analysis showed the meetings fostered innovative thinking, strengthened networks, and shared knowledge among actors. While the generalisability of the case is limited, the study demonstrates how future research could use the conceptual framework for advancing knowledge around AIS and IP meetings.

Assessment of Urban Resilience to Floods: A Spatial Planning Framework for Cities

Urbanization-led economic growth drives infrastructure investments and population accumulation in cities, hence exploiting natural resources at an extreme rate. In this context, coastal cities have become vulnerable to climate change-induced extreme weather events and human-made disasters in recent history, where effective measures to improve the resilience of cities are pivotal for developing sustainable living environments. This study proposes a framework for assessing urban resilience to natural disasters (floods) using bottom-up spatial interactions among natural, physical, and social systems within cities and regions. It is noted that seminal studies focus on either the mitigation or adaptation strategies within urban environments to assess disaster resilience, where limited multidisciplinary and operational models hinder evaluations at the city scale. Therefore, urban system interactions and quantifiable parameters proposed in this framework are essential for policymakers and disaster management agencies in the timely allocation of resources to optimize the recovery process. Moreover, spatial planning agencies can adopt resilience mapping to identify the potential risk zones and orient sustainable land use management. Urban resilience can be embodied in spatial strategies with the operational framework proposed here, and future urban growth scenarios can be tested in multiple disaster conditions.

Partial‐differential‐algebraic equations of nonlinear dynamics by physics‐informed neural‐network: (I) Operator splitting and framework assessment

Partial‐differential‐algebraic equations of nonlinear dynamics by physics‐informed neural‐network: (I) Operator splitting and framework assessment

The Development Model of Educational Management for Special Classrooms of School Under The Secondary Educational Service Area Office Kalasin

Background and Aims: The creation of special classes aimed at helping students with exceptional abilities in academics and other areas reach their full potential, according to the guidelines set forth by the Ministry of Education regarding the decentralization of management and administration of education to the educational Service area office by giving schools the chance to set up special classrooms if they have the staff and finances to do so. According to projects started by the Basic Education Commission, special classrooms are spaces where educational institutions concentrate on teaching and learning activities meant to promote the potential of students with extraordinary abilities. Therefore, the objective of this research is to 1) study the components and indicators of educational management for special classrooms of schools. 2) to study the current situation, desirable condition and needs assessment of educational management for special classrooms of school under the secondary education service area office Kalasin. 3) to create a model for educational management for special classrooms of schools under the secondary education service area office Kalasin. Methodology: The research was divided into 4 phases: Phase 1 studied components and indicators of educational management for special classrooms of the school, the key informant group was 7 experts, and the research tool was an interview form. Phase 1 studied the current situation, desirable condition, and needs assessment of educational management for special classrooms of school, the sample group consisted of 358 people, research tool was a questionnaire with a reliability of .79. Data were analyzed by means and standard deviation. Phase 3 created a model for educational management for special classrooms school, The key informant group was 9 experts to create and evaluate the suitability Feasibility, and usefulness of the model and the evaluating group the manual for using the model was 15 people. The research tool was an interview form evaluation form, data were analyzed by means and standard deviation Results: 1. The components and indicators of educational management for special classrooms of school consisted of 1) management, 2) curriculum and academics, 3) environment that promotes learning, 4) personnel and budget, and 5) learner quality. 2. The overall current condition is at a high average level. The overall desirable condition was at the highest mean level. The necessary needs index was ranked from the highest to the lowest as follows: 1) curriculum and academics, 2) personnel and budget, 3) environment that promotes learning, 4) quality of learners, and 5) management. Respectively. 3. The model consists of components: 1) principles, 2) objectives, 3) content, 4) development process, and 5) measurement and evaluation. There are 4 learning modules: Module 1, Curriculum and Academic Module 2, Personnel and Budget Module 3, Environment that Promotes Learning Module 4, Quality of Learners Module 4, and Management. The model has a suitability assessment result. The model's possibility and overall usefulness were at the highest level. Conclusion: The management of special classrooms in schools currently faces various challenges and suggestions for improvement in several aspects including administration and research into developing management models for more effective governance. School administrators, teachers, parents, and students must all participate in the management process, collaborate in designing operational frameworks in various aspects, and identify areas that require expedited development within the project to achieve efficiency and effectiveness for the students. There are clear and coherent curricula aligned with students' development. There are various supplementary activities in different formats to enhance the curriculum. There is a learning management system that emphasizes both theory and practice, and there should be support systems in place to assist students with their needs and potential.

An Optimization Strategy for EV-Integrated Microgrids Considering Peer-to-Peer Transactions

The scale of electric vehicles (EVs) in microgrids is growing prominently. However, the stochasticity of EV charging behavior poses formidable obstacles to exploring their dispatch potential. To solve this issue, an optimization strategy for EV-integrated microgrids considering peer-to-peer (P2P) transactions has been proposed in this paper. This research strategy contributes to the sustainable development of microgrids under large-scale EV integration. Firstly, a novel cooperative operation framework considering P2P transactions is established, in which the impact factors of EV charging are regarded to simulate its stochasticity and the energy trading process of the EV-integrated microgrid participating in P2P transactions is defined. Secondly, cost models for the EV-integrated microgrid are established. Thirdly, a three-stage optimization strategy is proposed to simplify the solving process. It transforms the scheduling problem into three solvable subproblems and restructures them with Lagrangian relaxation. Finally, case studies demonstrate that the proposed strategy optimizes EV load distribution, reduces the overall operational cost of the EV-integrated microgrid, and enhances the economic efficiency of each microgrid participating in P2P transactions.

Does disclosing commercial intention benefit brands? Mediating role of perceived manipulative intent and perceived authenticity in influencer hidden advertising

PurposeDespite sponsorship disclosure regulations, many influencers circumvent regulations by posting hidden advertising in covert formats. However, the impact of influencer hidden advertising sponsorship disclosure (IHASD) on brand attitudes is complex and contradictory. To understand the influence mechanism clearly, we introduced the operational transparency framework and investigated the mediating effects of perceived manipulative intent and perceived authenticity as well as the relationship between them. The conditions under which the mediation effect occurs were also analyzed.Design/methodology/approachThe authors conducted three experimental studies. Studies 1 and 2 examined the influence mechanism of sponsorship disclosure (present vs absent) and sponsorship disclosure prominence (explicit vs implicit) of influencer hidden advertising on brand attitudes (i.e. the mediating effect of perceived manipulative intent and perceived authenticity). Study 3 explored the moderating effect of consumers’ thinking styles.FindingsThe results revealed that sponsorship disclosure and sponsorship disclosure prominence of influencer hidden advertising weakened brand attitudes through perceived manipulative intent while enhancing brand attitudes through perceived authenticity. Perceived authenticity and perceived manipulative intent played a bidirectional chain mediating role. When consumers’ thinking style was experiential, the negative mediating effect of perceived manipulative intent was alleviated and the positive mediating effect of perceived authenticity was enhanced; this effect, though, was the opposite when consumers’ thinking style was rational.Originality/valueThis research contributes to influencer sponsorship disclosure literature through providing an enhanced comprehensive, in-depth theoretical explanation of the competing mechanisms of sponsorship disclosure effects.

A Stochastic Dynamic Operator Framework That Improves the Precision of Analysis and Prediction Relative to the Classical Spike-Triggered Average Method, Extending the Toolkit.

Here we test the stochastic dynamic operator (SDO) as a new framework for describing physiological signal dynamics relative to spiking or stimulus events. The SDO is a natural extension of existing spike-triggered average (STA) or stimulus-triggered average techniques currently used in neural analysis. It extends the classic STA to cover state-dependent and probabilistic responses where STA may fail. In simulated data, SDO methods were more sensitive and specific than the STA for identifying state-dependent relationships. We have tested SDO analysis for interactions between electrophysiological recordings of spinal interneurons, single motor units, and aggregate muscle electromyograms (EMG) of major muscles in the spinal frog hindlimb. When predicting target signal behavior relative to spiking events, the SDO framework outperformed or matched classical spike-triggered averaging methods. SDO analysis permits more complicated spike-signal relationships to be captured, analyzed, and interpreted visually and intuitively. SDO methods can be applied at different scales of interest where spike-triggered averaging methods are currently employed, and beyond, from single neurons to gross motor behaviors. SDOs may be readily generated and analyzed using the provided SDO Analysis Toolkit We anticipate this method will be broadly useful for describing dynamical signal behavior and uncovering state-dependent relationships of stochastic signals relative to discrete event times.

Governance of Village-Owned Enterprises in Promoting Economic Growth

background: The governance of Village-Owned Enterprises (BUMDes) plays a critical role in fostering sustainable development in rural areas. Specific background: This research explores the governance practices of BUMDes Kerto Emas, emphasizing the principles of transparency, cooperation, participation, and inclusiveness. Knowledge gap: Previous studies have not sufficiently examined how sustainable practices are implemented within the operational framework of BUMDes, especially concerning product management and website functionality. Aims: This study aims to assess the current governance indicators applied in BUMDes Kerto Emas, particularly regarding sustainability and the integration of digital platforms. Results: The findings reveal that while BUMDes Kerto Emas has made significant strides in governance, challenges remain in achieving sustainability, particularly in the underutilization of digital platforms for product display. Novelty: This study introduces a new perspective by linking sustainable business development with the need for improved online presence in village-owned enterprises. Implications: The research suggests that enhancing product offerings and optimizing digital platforms are essential for achieving long-term sustainability, providing a framework for improving governance in similar rural enterprises. Highlights : Governance principles must focus on transparency and cooperation for sustainable BUMDes operations. Digital platforms play a crucial role in enhancing product visibility and sustainability. Continuous evaluation is needed to optimize governance for long-term sustainability. Keywords: Governance, BUMDes, Sustainability, Participation, Digitalization

Advancing justice: The impact of Brazil’s convict genetic profile identification project after 5 years

This comprehensive study analyzed the implementation and impacts of the Convict Genetic Profile Identification Project in Brazil. By examining semiannual reports from the Integrated Network of DNA Databases (RIBPG) alongside a literature review covering the period from January 2018 to February 2024, the study evaluated the project’s relevance. The project’s primary aim was to enhance DNA databases, thereby fortifying crime prevention and resolution efforts. Notably, the results revealed a substantial increase in genetic profiles of convicted offenders included into the Brazilian National DNA Database (from 2,008 in 2017 to 54,657 in 2019) − a development that aligns with legislative goals. Despite legal and ethical debates, the project demonstrated a positive impact on criminal investigations, with a notable rise in database matches (from 376 in 2017 to 1,418 in 2019). Scientific literature had highlighted the project’s effectiveness in resolving crimes. The project has matured into a well-established process, characterized by continuous insertions and advancements, emphasizing a comprehensive operational framework. Beyond quantitative milestones, it has made qualitative contributions to justice. This collaborative model serves as an example for impactful public policies under Brazil’s Ministry of Justice and Public Security.

Multi-period operation of integrated electricity and gas systems with hydrogen blending considering gas composition dynamics

Green hydrogen from renewable sources can be blended with natural gas and serves as a potentially feasible measure for contributing to the net zero energy sector. The time-varying nature of hydrogen injection, influenced by stochastic renewable generations, can result in fluctuations in gas concentrations in the entire network. It poses a potential threat to the secure regulation of integrated electricity and gas systems (IEGS). For managing the operating condition and guaranteeing the security of IEGS during operation, a multi-period operation framework with alternative gas (e.g., hydrogen) blending is developed. First, a convex gas security range is derived using the Dutton method. Then, the multi-period operation framework is devised to mitigate the impacts of alternative gas injection on gas security over the entire operational period. Both the dynamics from gas composition and gas flow are modelled, accurately describing the real-time travel of alternative gas concentrations. The dynamics in the gas mixture properties (e.g., relative density) are fully revealed with time-varying gas concentrations. To tackle the high non-convexities in the optimization problem, second-order-cone relaxation is well-tailored and firstly used in the case of varying gas compositions, making the motion equations and advective transport equations more tractable. An advanced second-order-cone sequential programming is devised to drive the relaxation tight more efficiently. Finally, our operation strategy is illustrated in IEEE and Belgium Electricity and Gas Systems. Results indicate that hydrogen concentrations take about 12.5 h to travel from the injection point to the end of the pipeline route in the Belgium gas system. By incorporating this unique characteristic into the model, operational scheduling and dispatch in IEGS can be more practical when integrating hydrogen in the future.

Coordinated planning and operation of PV- hydrogen integrated distribution network incorporating daily-seasonal green hydrogen storage and EV charging station

The current study introduces an optimal planning and operational framework for a Distribution Network (DN) that integrates Photovoltaic (PV)-green Hydrogen (H2)-based energy system with Electric Vehicle Charging Station (EVCS). An efficient operational strategy is proposed considering both short-term H2 storage (STHS) and long-term H2 storage (LTHS), ensuring uninterrupted power supply. Besides, a novel Improved Harris Hawk Optimization method is developed to enhance the global search capabilities and convergence rate in optimizing the capacity of Solar module, Electrolyzer, and Fuel cells. The objective of the proposed model is to minimize the device costs, energy loss, and carbon emissions, adhering to all operational constraints. The proposed work is tested on 33-bus radial DN and 51-bus real Indian DN considering the time frame of 10 years. The analysis reveals that the PV-STHS-LTHS configuration, reduces total planning costs by 12% and 15% as compared to the base case in the 33-bus and 51-bus systems, respectively. Additionally, the integration of both daily and seasonal storage facilities with PV systems leads to a reduction in carbon emissions by 76% and 81% in the 33-bus and 51-bus systems, respectively. Besides the carbon reduction, the incorporation of daily and cross-seasonal H2 storage increases oxygen release into the environment by 13% for the 33-bus system and 15% for the 51-bus system.

Risk Analysis on Autonomous Vessels based on Systems Theory – Application of NET-HARMS method

Abstract The shift towards Maritime Autonomous Surface Ships is a significant development in the maritime logistics industry, with the potential to enhance efficiency, safety, and environmental sustainability. However, the integration of autonomous systems also presents new challenges and risks, particularly in the absence of empirical data for traditional risk assessment methodologies. This research tackles this problem by utilizing the Net-worked Hazard Analysis and Risk Management System (Net-HARMS) method, a systems thinking method that hasn’t been previously employed in examining MASS. The method analyses the risks associated with the EC-funded, H2020, MOSES Project, which included a concept for automating the manoeuvring and docking processes with autonomous tugboats. The Net-HARMS method offers a comprehensive and holistic approach to risk assessment, overcoming the limitations of conventional probabilistic models. By constructing a Hierarchical Task Analysis and a task network, the research maps the system’s operational framework and explores task interdependencies. The use of a risk mode taxonomy allows for the identification of task-specific and emergent risks, which are then assessed by utilising the risk matrix of the Risk-Based Assessment Tool developed by DNV, to assess the final risk as a function of the effectiveness of each risk mitigation layer and the severity of the identified task consequences. The findings provide valuable insights into critical tasks requiring enhanced risk control measures and contribute to the development of safety constraints necessary for the successful implementation of autonomous shipping technologies. By applying Net-HARMS method to the realm of autonomous ships, this research not only fills a significant gap in maritime risk analysis but also sets a precedent for future studies in this rapidly evolving field.

Real-time lithology identification from drilling data with self & cross attention model and wavelet transform

Accurate lithology identification during drilling operations is pivotal for optimizing drilling efficiency and informed decision-making. Traditional methods, such as mud logging, Logging While Drilling (LWD), and Measurement While Drilling (MWD), often face challenges such as delays and inaccuracies, lacking consistent utilization of real-time engineering data across all drilling sites. Consequently, these methods frequently overlook the complex interactions of influencing factors, resulting in underutilized geological information that could significantly enhance operational outcomes. This paper introduces the SelfAttention-CrossWT (SACWT) model, an innovative approach that integrates self-attention and cross-attention mechanisms with Wavelet Transform (WT) to utilize real-time drilling parameters, including Weight on Bit (WOB) and Rate of Penetration (ROP). The SACWT model effectively harnesses both temporal and frequency-domain characteristics of drilling data, facilitating comprehensive extraction of latent patterns and dynamics, which substantially improves lithology identification accuracy. The output of the model is the real-time lithology classification at the drill bit's depth. The performance of the SACWT model is compared with Long Short-Term Memory (LSTM) networks and a Self-Attention (SA) model that does not utilize frequency-domain data. When applied to a dataset from the Volve oil field, the SACWT model achieved identification accuracies of 87% and 91% in two separate test wells, outperforming traditional methods. These results underscore the model's efficacy and the significant potential of utilizing real-time drilling data for enhanced lithological characterization. This breakthrough offers a robust framework for future exploration and development operations, providing a more precise, efficient, and cost-effective approach to geological analysis.