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Exploring the Impact of Word Embedding Dimensions on Depression Data Classification Using BiLSTM Model

Procedia Computer Science 2023年 227卷 298-306页

作者： Merinda Lestandy Abdurrahim Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Malang Malang 65144 Indonesia Informatics Master Program Faculty of Industrial Technology Universitas Islam Indonesia Yogyakarta 55584 Indonesia

Depression is a mental health issue that impacts over 300 million individuals worldwide. Daily anxiety impacts the relationships of depressed individuals with their family and friends, affects their health, and, in the worst-case scenario, leads to suicide. Due to the an increase of social networks, a vast majority of people now express their thoughts, feelings, and emotions via social media. The researchers mainly focused on features and building predictions, making it difficult for them to detect depression via social media. Word embedding offers a potential solution for processing and transforming unstructured data into meaningful representations. Embedded words represent textual data as numeric numerals with equivalent meaning. Using the Bidirectional Long Short-Term Memory (Bi-LSTM) paradigm, this investigation attempts to experiment with various weighting dimensions using the Word2Vec and GloVe methods. The data used is Depression: Reddit Dataset labelled: depressed and non-depressed. The experimental results of word weight dimensions using Word2Vec with a dimension of 500 are better than Glove. The results of accuracy, precision, recall and f1-score for the Word2Vec method were 96.22%, 97.02%, 95.30% and 96.15%, while the Glove method was 95.91%, 96.40%, 95.30% and 95.85% with a dimension of 200. Overall, Word Embedding Dimensions influences the results of this study. Based on these findings, it is concluded that the proposed Word2Vec method is a significant approach.

关键词： Social Media Depression Word Embedding BiLSTM

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Efficient Utilization of Metaheuristic Techniques for Profit Maximization in Combinatorial Production Planning: A Comparative Study

Efficient Utilization of Metaheuristic Techniques for Profit...

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International Conference on Control, Instrumentation, Energy and Communication (CIEC)

作者： Arijit Mukherjee Surojit Mukherjee Deptartment of Electrical Engineering Future Institute of Technology Kolkata India Post-Graduate Program in Management Great Lakes Institute of Management Chennai India

Efficient production planning requires well-structured models compatible with metaheuristic and other optimization techniques. This study compares three established metaheuristic methods - sanitized-teaching-learning-based optimization (s-TLBO), Particle Swarm Optimization (PSO), and Differential Evolution (DE) with a termination criterion of equal number of functional evaluations - for profit-maximizing production planning. The focus is on a single-level problem involving complex constraints, non-linear costs, budget and raw material limitations. The paper presents two solution strategies: a penalty-based and a correction-based approach. Analyzing 300 unique instances of the problem reveals that s-TLBO implemented with correction-based approach consistently outperforms the other methods in devising optimal production plans for two Saudi Arabian petrochemical industries with 24 products, 54 processes, and three raw materials for plant 1 and two raw materials for plant 2.

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Optimal Integration of Metaheuristic Techniques with Correction-Based Approaches for Profit Maximization in Combinatorial Production Planning: A Comparative Analysis

Optimal Integration of Metaheuristic Techniques with Correct...

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International Conference on Control, Instrumentation, Energy and Communication (CIEC)

To enhance production planning efficiency, it’s crucial to have well-structured models that align with metaheuristic and other optimization techniques. This research conducts a comparative analysis of three unique metaheuristic methods: sanitized-teaching-learning-based optimization (sTLBO), Particle Swarm Optimization (PSO), and Differential Evolution (DE) with a termination criterion of equal number of functional evaluations. The primary focus lies on profit-maximizing production planning within a single-level framework, encompassing intricate domain constraints, nonlinear costs, budget limitations and raw material constraints. The paper introduces three correction-based solution approaches. Upon evaluating 300 distinct instances of the problem, the study reveals that s-TLBO integrated with correction-based approach 1 and 3 consistently outperforms the other methods when it comes to devising optimal production plans for a Saudi Arabian petrochemical industry. This industry scenario involves 24 products, 54 processes, and three raw materials.

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An event-driven approach for resources planning in distributed power generation systems

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International Journal of electrical Power and Energy Systems 2022年 137卷 107768-107768页

作者： Maschio, Dierli M.R. Duarte, Bruno Lazzaretti, André E. Lafay, Jean-Marc S. Adzkiya, Dieky da Costa, Jean Patric Teixeira, Marcelo Graduate Program in Electrical Engineering Federal University of Technology Paraná Brazil Graduate Program in Electrical Engineering and Industrial Informatics Federal University of Technology Paraná Brazil Department of Mathematics Institut Teknologi Sepuluh Nopember Indonesia

Renewable Energy Sources (RESs) stand as a straightforward alternative to complement the energy grid and have been recurrently integrated into the generation and distribution matrices. Physically, generation components have distributed nature and they are expected to work coordinately, complementing each other to supply centralised microgrids, which interface them with the main power grid and consumers. As RESs have intermittent nature, engineers are limited to plan resources consumption, fulfil unit commitments, stratify time, cost, environmental impact, and quality of energy. This paper exploits the event-driven behaviour of microgrids to provide ways for them to recognise their context and cooperate towards common goals. Our main result is a Petri net simulation model that estimates customisation policies to be applied back over the microgridvia event-based control. Results show that in some cases it is possible to save effort (and resources) of power generation by replacing reactiveness for a more balanced, context-aware, energy chain. A real photovoltaic plant is modelled by our approach with 86% accuracy. © 2021 Elsevier Ltd

关键词： Renewable energy resources

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Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filtering

arXiv

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arXiv 2024年

作者： Mashkova, Olga Zhapa-Camacho, Fernando Hoehndorf, Robert Computer Science Program Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

Ontology embeddings map classes, relations, and individuals in ontologies into Rn, and within Rn similarity between entities can be computed or new axioms inferred. For ontologies in the Description Logic EL++, several embedding methods have been developed that explicitly generate models of an ontology. However, these methods suffer from some limitations;they do not distinguish between statements that are unprovable and provably false, and therefore they may use entailed statements as negatives. Furthermore, they do not utilize the deductive closure of an ontology to identify statements that are inferred but not asserted. We evaluated a set of embedding methods for EL++ ontologies based on high-dimensional ball representation of concept descriptions, incorporating several modifications that aim to make use of the ontology deductive closure. In particular, we designed novel negative losses that account both for the deductive closure and different types of negatives. We demonstrate that our embedding methods improve over the baseline ontology embedding in the task of knowledge base or ontology completion. © 2024, CC BY.

关键词： Ontology

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A Dynamic Model for Pauses in the Synthesized Speech of Mathematical Expressions in MathML 14

A Dynamic Model for Pauses in the Synthesized Speech of Math...

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14th International Conference on Education technology and Computers, ICETC 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Porto Seguro Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study. © 2022 ACM.

关键词： Dynamic models

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A Comprehensive Review and Evaluation of Classical MPPT Techniques for a Photovoltaic System 8th

A Comprehensive Review and Evaluation of Classical MPPT Tech...

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8th EAI International Conference on Advancement of Science and technology, ICAST 2020

作者： Yetayew, Tefera T. Workineh, Tewodros G. Department of Electrical Power and Control Engineering Adama Science and Technology University Adama Ethiopia Electrical Power and Energy Program Bahirdar Institute of Technology Bahirdar Ethiopia

ISBN: (纸本)9783030806200

Extracting available maximum power is an important component of solar photovoltaic system which can be achieved by an efficient maximum power point tracking algorithm. Up to date review of related works summarized available MPPT algorithms as classical and modern optimization techniques. Among classical algorithms the incremental conductance (InCond) and perturb & observe (P&O) based tracking algorithms with duty ratio control are widely used due to relatively accurate MPP tracking capability and less implementation complexity under uniform radiation. However;steady-state oscillation, wrong perturbation direction for rapid climate change and failure to track the global peak under partial shade/mismatching operating conditions of the photovoltaic system are some of the limitations of these algorithms. Thus, in this work, a succinct review, formulations and evaluations of widely used classical techniques along with a proposed classical improved perturb and observe (IPO) to improve drawbacks of steady state oscillation has been done. The performance evaluation results of widely used classical perturbation based algorithms (InCond, P&O, IPO) using MATLAB/Simulink revealed improved performances of the improved perturbation based algorithm over the widely used classical (InCond, P&O) algorithms in reducing steady-state oscillations of step-change in irradiance without any partial shading condition of the photovoltaic (PV) of the PV system. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Maximum power point trackers

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Joint Modeling of Multivariate Longitudinal and Survival Outcomes with the R package INLAjoint

arXiv

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arXiv 2024年

作者： Rustand, Denis van Niekerk, Janet Krainski, Elias Teixeira Rue, Håvard Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

This paper introduces the R package INLAjoint, designed as a toolbox for fitting a diverse range of regression models addressing both longitudinal and survival outcomes. INLAjoint relies on the computational efficiency of the integrated nested Laplace approximations methodology, an efficient alternative to Markov chain Monte Carlo for Bayesian inference, ensuring both speed and accuracy in parameter estimation and uncertainty quantification. The package facilitates the construction of complex joint models by treating individual regression models as building blocks, which can be assembled to address specific research questions. Joint models are relevant in biomedical studies where the collection of longitudinal markers alongside censored survival times is common. They have gained significant interest in recent literature, demonstrating the ability to rectify biases present in separate modeling approaches such as informative censoring by a survival event or confusion bias due to population heterogeneity. We provide a comprehensive overview of the joint modeling framework embedded in INLAjoint with illustrative examples. Through these examples, we demonstrate the practical utility of INLAjoint in handling complex data scenarios encountered in biomedical research. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational efficiency

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A Preliminary Study on the Collaborative Playing Piano Automatic with Deep Learning

A Preliminary Study on the Collaborative Playing Piano Autom...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Varinya Phanichraksaphong Karuna Yampray Department of Electronic Engineering International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan College of Creative Design and Entertainment Technology Dhurakij Pundit University Bangkok Thailand

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

A great number of deep learning-based models have been recently proposed for automatic piano classification. In this paper, we describe our contribution to the challenge of automatic piano classification when the performer performs at the concert or stage. Among these models in deep learning, we use init-1D-WaveNet and init-2D-MLNet for comparison the accuracy in the piano beginning level of the Christmas song (Jingle bells). Our experimental results show that the assessment using the init-2D-MLNet still achieve high accuracy of 87.5%.

关键词： Deep learning Accuracy Instruments Collaboration Consumer electronics

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Towards Automated Functional Equation Proving: A Benchmark Dataset and A Domain-Specific In-Context Agent

arXiv

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arXiv 2024年

作者： Buali, Mahdi Hoehndorf, Robert Computer Science Program Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

Automated Theorem Proving (ATP) faces significant challenges due to the vast action space and the computational demands of proof generation. Recent advances have utilized Large Language Models (LLMs) for action selection in ATP, but these methods often require substantial computational resources. This study introduces the Functional Equation Automated Solver (FEAS), an agent that builds on the COPRA in-context learning framework within the Lean environment. FEAS innovates by refining prompt generation and response parsing mechanisms, integrating domain-specific heuristics for functional equations, and introducing the FunEq dataset—a rigorously curated collection of functional equation problems categorized into three difficulty levels. The agent’s performance is evaluated against established baselines using this dataset, demonstrating improvements in theorem proving accuracy, particularly with the integration of functional equation-specific heuristics. Our results highlight the effectiveness of FEAS in generating and formalizing high-level proof strategies into Lean proofs, emphasizing the potential of tailored approaches in domain-specific ATP challenges. © 2024, CC BY.

关键词： Theorem proving

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