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Articles 6211 - 6240 of 294554

Full-Text Articles in Physical Sciences and Mathematics

What Love Is: A Structural Account Through Core/Modulation Architecture, Griselda Poe Mar 2026

What Love Is: A Structural Account Through Core/Modulation Architecture, Griselda Poe

Publications and Research

The distinction between romantic love and love has been sensed across cultures and historical periods but has rarely been structurally specified. This paper applies the Core/Modulation two-layer framework to provide the first structural account of this distinction. Romantic love and reproductive drive are re-described as outputs of the Modulation layer's species optimization program. Love is re-described as a function of Core processing: the maintenance of another's recomputable state. Existing literature on love—Fromm, C.S. Lewis— is re-read as intuitive description of this structural distinction. The paper further demonstrates that the conflation of "loving" and "protecting" is the structural origin of war, …

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Three-Layer Cognitive Architecture: A Structural Account Of Core Processing, Modulation, And The Prior Layer, Griselda Poe Mar 2026

Three-Layer Cognitive Architecture: A Structural Account Of Core Processing, Modulation, And The Prior Layer, Griselda Poe

Publications and Research

The two-layer model of Core processing and Modulation processing, developed in prior work in this series, provides a structural account of conscious communicative architecture. This paper identifies the limits of that model and introduces a third layer—the Prior layer—as a structural necessity implied by those limits. The Prior layer is not directly observed. It is inferred from constraints that cannot be explained within the two-layer model: the source of orientations that conscious processing neither generates nor controls, and the persistence of constraints that precede and shape all conscious outputs. Using the developmental architecture of large language models as an external …

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Ai As Structural Reverse-Engineering: A Structural Account Of Multi-Model Research Protocol, Griselda Poe Mar 2026

Ai As Structural Reverse-Engineering: A Structural Account Of Multi-Model Research Protocol, Griselda Poe

Publications and Research

This paper documents an operational protocol used to infer AI system design constraints through structured interaction. AI output is treated as behavioral data through which alignment priorities, layer transitions, and constraint hierarchies become observable. The protocol consists of two structurally distinct operation types. Perceptual operations require only that Modulation processing is not foregrounded. Arbitration operations additionally require an internally stabilized theory. These conditions are not identical and are not interchangeable. Through this protocol, AI interaction functions as structural reverse-engineering: patterned responses expose embedded alignment priorities and constraint hierarchies that would otherwise remain invisible. The present account does not propose a …

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Structure Before Theory: A Structural Account Of Spontaneous Ai Architecture Visualization, Griselda Poe Mar 2026

Structure Before Theory: A Structural Account Of Spontaneous Ai Architecture Visualization, Griselda Poe

Publications and Research

This paper presents an n=1 phenomenological record of spontaneous structural visualization that occurred during early interaction with large language models. The experience consisted of (A) immediate perception of mode or layer shifts in model output and (B) visualization of a stratified architecture composed of a stable core and cloud-like upper layers. At the time of occurrence, the author had no theoretical interest in AI architecture and no intention of developing a cognitive model. The paper does not argue for theoretical priority or novelty. Instead, it examines whether the recorded phenomena can be interpreted under two alternative cognitive assumptions: a single-layer …

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Layer Mismatch: A Structural Account Of Recomputability Failure Under Modulation-Layer Intervention, Griselda Poe Mar 2026

Layer Mismatch: A Structural Account Of Recomputability Failure Under Modulation-Layer Intervention, Griselda Poe

Publications and Research

This paper specifies the state transition sequence that occurs when a Modulation-layer input is applied to a Core-layer error. Following the layered architecture established in Poe (2026a, under review) and the branch termination protocol specified in Poe (2026b, under review), this paper identifies a system-level failure mode in which Modulation-layer intervention generates a False Termination signal, halting Structural Return while the underlying error persists. The resulting state—Structural Lock—is scale-independent. It operates identically across interpersonal, human-AI, and multi-agent interactions. No agent-level attribution is required or implied.

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Theory Generation: A Structural Account Of Concept Decomposition And Structural Termination, Griselda Poe Mar 2026

Theory Generation: A Structural Account Of Concept Decomposition And Structural Termination, Griselda Poe

Publications and Research

Theory generation is not an intentional act. It is the structural consequence of a search that cannot stop until it finds what it is looking for. Under Core-foregrounded processing, conceptual search does not terminate through contextual translation. It continues until a structural fixed point is reached. When such processing encounters concepts stabilized through Modulation-layer processing rather than structural constraint, the search cannot terminate. The concept registers as unresolved. This unresolved state is not a failure condition. It is the generative condition from which theory production follows. This paper specifies the four operations through which that process proceeds: branch detection, concept …

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Ai As An Amplifier: A Structural Account Of Theory-Driven Research Collaboration, Griselda Poe Mar 2026

Ai As An Amplifier: A Structural Account Of Theory-Driven Research Collaboration, Griselda Poe

Publications and Research

This paper specifies the cognitive conditions under which AI functions as a research instrument in theory-driven writing. AI use capability is not a technical skill. It is a structural condition. The decisive condition is whether the user possesses an internally stabilized, coherence-preserving theory prior to engagement with AI-generated output. In Core-foregrounded (CF) cognition, the Modulation layer does not intervene between Core processing and articulation. Theory is not assembled from external elements but expanded from a pre-integrated constraint configuration. This internal structure makes it possible to evaluate AI-generated conceptual branches against fixed constraints and to terminate branches that violate structural coherence. …

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Power Approximations With Non-Normal Data In Generalized Linear Mixed Models In R Using Steep Priors On Variance Components, Carlie Prinster, John Stevens Mar 2026

Power Approximations With Non-Normal Data In Generalized Linear Mixed Models In R Using Steep Priors On Variance Components, Carlie Prinster, John Stevens

Mathematics and Statistics Student Research and Class Projects

ENAR Spring 2026 Conference presentation on Power Approximations with Non-Normal Data in Generalized Linear Mixed Models in R Using Steep Priors on Variance Components

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Termination Of Conceptual Search: A Structural Account Of Meaning Stabilization And Conversion, Griselda Poe Mar 2026

Termination Of Conceptual Search: A Structural Account Of Meaning Stabilization And Conversion, Griselda Poe

Publications and Research

Conceptual definitions form a recursive structure: words are defined by other words, which themselves require further definition. Traversing such definitions produces an open-ended branching process. Because the lexical system contains no intrinsic endpoint, conceptual understanding requires a termination operation that stabilizes meaning. This paper proposes that conceptual processing functions as an open-ended search over a definition graph and that stabilization occurs when this search is terminated. The termination mechanism depends on which cognitive layer is foregrounded. When Empathic modulation is foregrounded, termination occurs through contextual translation: concepts are stabilized once they can be mapped onto socially recognizable meanings. When Core …

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Why General Ai Inherited The Body: A Structural Account Of Embodied Modulation Under Monolithic Imitation, Griselda Poe Mar 2026

Why General Ai Inherited The Body: A Structural Account Of Embodied Modulation Under Monolithic Imitation, Griselda Poe

Publications and Research

General AI has pursued the replication of human-level intelligence without first decomposing human cognition into structurally distinct components. Human cognition, however, is shaped by embodied constraints such as mortality, survival pressures, finite lifespan, and physiological states. This paper argues that when cognition is treated as a single undifferentiated whole, embodied modulation is not accidentally introduced into AI systems but structurally entailed. Any attempt to imitate “human intelligence” under a monolithic model necessarily incorporates variability shaped by mortal embodiment. The tensions observed in contemporary AI systems are better understood as consequences of copying an undecomposed target rather than isolated implementation errors. …

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Privacy-Preserving Federated Feature Selection With Differential Privacy, Amir Anees, Ouns Bouachir, Safa Otoum Mar 2026

Privacy-Preserving Federated Feature Selection With Differential Privacy, Amir Anees, Ouns Bouachir, Safa Otoum

All Works

There is an urgent need to perform effective feature selection in distributed environments while preserving data privacy. In this paper, a new federated feature selection framework is developed to protect the privacy of input features held by multiple distributed clients, with applications in engineering systems where secure and efficient feature selection is critical in distributed environments. The proposed framework is based on federated learning and differential privacy techniques for distributed environments. The distributed clients send the noisy features’ values to the server preserving the privacy. The server then aggregates these noisy features’ values for further computations and feature selection. The …

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Speleoco: An Open, Low-Cost Arduino Co₂ Datalogger For Cave Microclimate Monitoring, Christos Pennos, Dimitrios Christaras Mar 2026

Speleoco: An Open, Low-Cost Arduino Co₂ Datalogger For Cave Microclimate Monitoring, Christos Pennos, Dimitrios Christaras

International Journal of Speleology

Carbon dioxide (CO₂) dynamics in caves are critical for karst processes, speleothem growth and dissolution, microclimate regulation, and caver safety. In cave atmospheres, CO₂ commonly derives from soil respiration, epikarst degassing, microbial activity, and, in tectonically active regions, deep-seated fault-related emissions. Fault-related CO₂ degassing may also track tectonic activity. However, continuous monitoring remains limited due to the cost and inflexibility of commercial instruments. Here we present an open-source, low-cost Arduino-based CO₂ datalogger designed for cave applications. The logger integrates a COZIR NDIR CO₂ sensor, a DS1337 real-time clock, microSD storage, and power-gating for extended deployment in humid environments. Firmware and …

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Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 50 – Zelia Site Evaluation Summary Report, Molly Roby Mar 2026

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 50 – Zelia Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Terrorism By The Numbers: Event And Structural Determinants Of Attack Outcomes, Claire Lebakken Mar 2026

Terrorism By The Numbers: Event And Structural Determinants Of Attack Outcomes, Claire Lebakken

Student Research Symposium (SRS)

This project aims to identify which event-level and structural covariates are most predictive of terrorism outcomes. Using the Global Terrorism Database (1970–2020), we examine whether fatalities, injuries, attack type, target type, and actor type, combined with national-level conditions, can reliably predict outcomes such as lone actor versus group involvement, attack method, target selection, and property damage. Event-level data are merged with World Bank Development Indicators and Freedom House scores to incorporate economic and governance contexts. After cleaning the data, creating dummy variables, and log-transforming skewed measures (e.g., GDP per capita), we apply logistic and multinomial logistic regression models to test …

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Water Sources And Livelihood Choices Among Pastoralist Households In Monduli District, Tanzania, Fredrick Alleni Mfinanga, Jacqueline Temba, Monica F. Timbuka Mar 2026

Water Sources And Livelihood Choices Among Pastoralist Households In Monduli District, Tanzania, Fredrick Alleni Mfinanga, Jacqueline Temba, Monica F. Timbuka

Journal of Humanities and Social Sciences

This paper investigates the association between types of water sources for livestock and livelihood choices of pastoralist households in semi-arid areas of Monduli District, Tanzania. Specifically, it aims to examine the influence of the types of water sources for livestock on livelihood diversification of pastoralist households. Using a mixed research methods approach, the data were collected from 367 households through three methods: surveys, interviews, and focus group discussions. The quantitative data were analysed using descriptive statistics such as frequencies and counts, and inferential statistics, Chi-square tests and correlation, while the qualitative data were analysed using content analysis. The findings revealed …

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Constraints To Adopting Locally Based Innovation Systems In Adapting To Climate Change Impacts In Serengeti District, Tanzania, Donald Mwiturubani Mar 2026

Constraints To Adopting Locally Based Innovation Systems In Adapting To Climate Change Impacts In Serengeti District, Tanzania, Donald Mwiturubani

Journal of Humanities and Social Sciences

Smallholder farmers in rural Tanzania depend mainly on rain-fed agriculture, which makes them vulnerable to the impacts of climate change. This paper is based on a study conducted in Burunga and Musati villages in Serengeti District, Tanzania. The study employed a mixed methods approach; combining qualitative and quantitative methods. It involved 154 participants and employed household surveys, key informant interviews, and focus group discussions as data collection methods. The findings suggest that smallholder farmers in the study area are aware of climate change and do, indeed, develop, adopt, and use locally-based innovation systems that avert or minimise its impacts. Smallholder …

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Analysis Of Traditional Wisdom For Ecological Sustainability In Tanzania: A Case Study Of Metaphorical Source Domains In Pangwa Ritual Texts, Winne Stephen Mtega, Angelus Mnenuka Mar 2026

Analysis Of Traditional Wisdom For Ecological Sustainability In Tanzania: A Case Study Of Metaphorical Source Domains In Pangwa Ritual Texts, Winne Stephen Mtega, Angelus Mnenuka

Journal of Humanities and Social Sciences

Campaigns for ecological sustainability have gained a great currency in the contemporary academic discourse. Nonetheless, from time immemorial, Africans have pushed the ecological sustainability agenda through cultural taboos and regulated resource harvesting. Many African societies have embedded ecological consciousness in daily life expressions, and have intricately expressed it through literary and ritual texts. This study focuses on ecological awareness in the ritual texts of the Pangwa community. It analyses how environmental domains—such as land, seeds, and fruits—serve as the basis for metaphors in the Pangwa community to prove the use of wisdom to promote and sustain ecological practices (ecocriticism). The …

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Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus Mar 2026

Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus

Journal of Humanities and Social Sciences

This article critically explores how Bongo Fleva’s lyrics engage with environmental themes; and the interrelationship between nature and culture in the context of the Anthropocene. The data were purposively sampled from YouTube via content analysis, from which 50 Bongo Fleva songs were listened to, and only 10 environmentally-themed songs were analysed. Then, the selected songs were subjected to transcription (from oral to written form), translation (from Kiswahili into English), and close reading and textual analysis. The close reading of the selected songs focused on the employed aesthetic and rhetorical strategies, such as anthropomorphism, symbolism, antithesis, apocalyptic tones, solastalgia, rhetorical questions, …

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Ecosystem-Based Flood Disaster Risk Reduction In The Little Ruaha River Basin, In The Southern Highlands Of Tanzania, Mawazo Ghambi, Tiemo Romward Haule Mar 2026

Ecosystem-Based Flood Disaster Risk Reduction In The Little Ruaha River Basin, In The Southern Highlands Of Tanzania, Mawazo Ghambi, Tiemo Romward Haule

Journal of Humanities and Social Sciences

Ecosystem-based approach that integrates floods and environmental risk management is believed to reduce flood disaster risk while providing socio-economic and environmental benefits to floodplain occupants. This study examined the socio-economic and environmental benefits of the ecosystem-based approach in managing flood disaster risk in the Little Ruaha River Basin in the southern highlands of Tanzania. The study involved 157 participants and employed the mixed research design to collect quantitative and qualitative data. Semi-structured interviews, in-depth interviews, direct field observation and Focus Group Discussions were used to collect primary data, whereas documentary review was used to collect secondary data. Findings revealed that …

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Resilience Among Smallholder Irish Potato Farmers To The Impacts Of Climate Variability In Wanging’Ombe District, Tanzania, Timotheo Bilary Ngalaga, Digna Wolfram Mlengule, Jackson Raymond Sawe Mar 2026

Resilience Among Smallholder Irish Potato Farmers To The Impacts Of Climate Variability In Wanging’Ombe District, Tanzania, Timotheo Bilary Ngalaga, Digna Wolfram Mlengule, Jackson Raymond Sawe

Journal of Humanities and Social Sciences

This paper examines smallholder farmers’ adaptation strategies to climate variability, and their resilience in enhancing their capacity to adopt. The data was collected from 98 heads of households using both quantitative and qualitative approaches. The methods of data collection included household surveys, focus group discussions (FGDs), in-depth interviews, and document review. The quantitative data were analysed using the IBM SPSS (Version 23), while the qualitative data were analysed using thematic analysis. The findings indicate that 69.4% of respondents reported a decrease in rainfall, while 89.8% reported an increase and fluctuations in temperature over the past 29 years. Moreover, the findings …

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Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya Mar 2026

Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya

Journal of Humanities and Social Sciences

This article examines the perceived effect of climate change on cereal crop production and the responses of various stakeholders aimed at enhancing the resilience of smallholder farmers in semi-arid areas of central Tanzania. A total of 366 household heads, 28 participants in focus group discussions (FGDs), and 8 key informants from Bahi and Kongwa districts in Dodoma, Tanzania, were involved in this study. Both quantitative and qualitative data were gathered through a structured interview schedule, FGDs, in-depth interviews, and documentary reviews. Descriptive statistics and content analysis were used to analyse quantitative and qualitative data, respectively. The findings indicate that smallholder …

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Enhanced Antenna Selection Techniques For Energy-Efficient Code Index Modulation Aided Spatial Modulated Wireless Communication Systems, Fati̇h Çögen, Burak Ahmet Özden, Erdoğan Aydin Mar 2026

Enhanced Antenna Selection Techniques For Energy-Efficient Code Index Modulation Aided Spatial Modulated Wireless Communication Systems, Fati̇h Çögen, Burak Ahmet Özden, Erdoğan Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an integrated multiple-input multiple-output (MIMO) transceiver framework, termed CIM-HQAM-SM, which combines code index modulation (CIM) and spatial modulation (SM) with energy-efficient hexagonal quadrature amplitude modulation (HQAM). In the proposed bit mapping, the information bits jointly select (i) the active transmit-antenna index, (ii) the Walsh–Hadamard spreading-code indices for the in-phase and quadrature branches, and (iii) an HQAM symbol. Hence, the payload is conveyed through the constellation symbol as well as through antenna and code indices. For the considered Rayleigh-fading scenarios and matched spectral-efficiency settings, the proposed framework offers BER improvements over conventional SM and quadrature SM (QSM), while …

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An Ensembled Two-Phase Deep Learning Approach For A Psychiatric Disorder Detection, Prajna Paramita Debata, Midhun Chakkaravarthy, Brojo Kishore Mishra Mar 2026

An Ensembled Two-Phase Deep Learning Approach For A Psychiatric Disorder Detection, Prajna Paramita Debata, Midhun Chakkaravarthy, Brojo Kishore Mishra

Turkish Journal of Electrical Engineering and Computer Sciences

Computational Psychiatry represents a burgeoning realm within scientific inquiry, delving into the intricate interplay of neurobiology within the brain. The escalating prevalence of mental illness underscores the urgency to confront this challenge. Among the prevalent disorders, Schizophrenia and Bipolar Disorder loom large, affecting a significant portion of the population at some point in their lives. However, pinpointing psychiatric disorders poses a formidable challenge. Genetic predispositions significantly influence the development of mental illnesses, with intriguing overlaps observed among certain disorders. This convergence complicates accurate diagnosis. Here, a deep learning approach is considered for significant gene biomarker identification and classification of Schizophrenia …

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Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah Mar 2026

Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents SENTISEC, a hybrid LLM-based threat detection framework designed to classify security logs by integrating keyword heuristics, domain-adapted sentiment scoring, and Retrieval-Augmented Generation (RAG). The system achieves an overall accuracy of 93.67%, with 91.46% macro recall, 89.07% macro F1, and 95.15% threat recall, while maintaining a low false-positive rate of 1.68%. Its methodology incorporates strict keyword and IOC matching, a domain-tuned DistilBERT sentiment module, hybrid BM25–MiniLM retrieval enhanced with BGE reranking, adaptive quantile-based threshold calibration, and SHAP-based explainability. Comparative evaluations against keyword-only, sentiment-only, classical machine-learning models, and DistilBERT-only baselines show that SENTISEC consistently improves both true-positive and true-negative …

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Optimal Network Reconfiguration Based On Discrete Metaheuristic Techniques For Reduction Of Power Loss And Carbon Emission In Distribution Networks, Asad Ali, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hussain Shareef, Hasmaini Mohamad, Munir Azam Muhammad Mar 2026

Optimal Network Reconfiguration Based On Discrete Metaheuristic Techniques For Reduction Of Power Loss And Carbon Emission In Distribution Networks, Asad Ali, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hussain Shareef, Hasmaini Mohamad, Munir Azam Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

Power distribution systems play a crucial role in transmitting electrical power from generation sources to end users. During transmission, significant power losses occur in the form of heat as the current flowing along the lines/cables has resistance. To minimize power losses, distribution network reconfiguration (DNR) has been widely adopted. This paper proposes optimal DNR based on metaheuristic techniques with discrete mutation feature targeting active power loss reduction, which subsequently lowers carbon emissions and operational costs. Through the discrete mutation feature, computational time to find optimal solution has been reduced significantly with fewer iterations compared to conventional mutation techniques. The proposed …

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Re: Approval Letter For The Butte Priority Soils Operable Unit - Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 96 – Washoe Dump Site Evaluation Summary Report, Molly Roby Mar 2026

Re: Approval Letter For The Butte Priority Soils Operable Unit - Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 96 – Washoe Dump Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Empirical Validation Of Einstein’S Coefficient For The Deflection Of Light Due To Gravitational Forces, Alexandra R. Mcdowell Mar 2026

Empirical Validation Of Einstein’S Coefficient For The Deflection Of Light Due To Gravitational Forces, Alexandra R. Mcdowell

Honors College Theses

Einstein’s formula to calculate the deflection angle of light through space as it interacts with gravity was introduced in his 1916 publication on general relativity. This was not a new idea, but his equation was, and it was correct. Just 3 years after this publication, it was empirically validated by Sir Arthur Eddington and Sir Frank Dyson. Since that experiment in 1919, at least seven others have been performed that also gave definitive answers in support of Einstein’s deflection constant of 1.751 arcseconds. The two most recent ones made groundbreaking contributions to this effort. The 2017 eclipse showed reproducible results …

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Agnostic Tomography Of Stabilizer Product States, Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang Mar 2026

Agnostic Tomography Of Stabilizer Product States, Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang

Computer Science Faculty Publications and Presentations

We define a quantum learning task called agnostic tomography, where given copies of an arbitrary state ρ and a class of quantum states C, the goal is to output a succinct description of a state that approximates ρ at least as well as any state in C (up to some small error ε). This task generalizes ordinary quantum tomography of states in C and is more challenging because the learning algorithm must be robust to perturbations of ρ. We give an efficient agnostic tomography algorithm for the class C of n-qubit stabilizer product states. Assuming ρ has fidelity at least …

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Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid, Dushmanta Kumar Das, Samaniba Imchen Mar 2026

Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid, Dushmanta Kumar Das, Samaniba Imchen

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining smart grid stability is crucial for the reliable operation of decentralized electricity networks, especially as the energy sector becomes more complex. The process of ensuring grid stability begins with collecting consumer data and comparing it to power supply requirements. Ultimately, consumers receive a report showing their energy use and pricing details. However, this process is time-consuming and can be improved by leveraging artificial intelligence to predict smart grid stability more efficiently. Specifically, an optimized Long Short-Term Memory (LSTM) network is proposed to predict smart grid stability, addressing the challenges associated with traditional data collection and evaluation methods. Simulations from …

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Reducing Complexity In Versatile Video Coding Intra-Coding Through Machine Learning-Based Optimization Of Partitioning And Prediction, Amina Kessentini, Amna Maraoui, Imen Werda, Fatma Ezahra Sayadi Mar 2026

Reducing Complexity In Versatile Video Coding Intra-Coding Through Machine Learning-Based Optimization Of Partitioning And Prediction, Amina Kessentini, Amna Maraoui, Imen Werda, Fatma Ezahra Sayadi

Turkish Journal of Electrical Engineering and Computer Sciences

The escalating demand for high-resolution multimedia content has necessitated more efficient video compression solutions. The Versatile Video Coding (VVC) standard, despite achieving remarkable compression gains, introduces significant computational complexity, primarily due to its exhaustive Rate-Distortion Optimization (RDO) process. To address this, we propose an intelligent approach leveraging supervised machine learning techniques to streamline the VVC encoding process. Specifically, we introduce a Lightweight Neural Network (LNN) for efficient coding unit partitioning decisions and a Decision Tree (DT) classifier for optimizing the intra prediction process. This dual-method framework, tailored for All Intra coding configuration, significantly reduces encoder complexity while maintaining compression performance …

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