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检索条件"机构=dept. of Computer Computer Systems Engineering"

共 66489 条记录，以下是401-410 订阅

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An Ensemble Machine Learning-Based Method to Determine the Presence of Heart Ailment Using Pooled Dataset

An Ensemble Machine Learning-Based Method to Determine the P...

引用

2024 IEEE International Conference on Computing, Applications and systems, COMPAS 2024

作者： Saad, Mirza Nadim Jahan, Esrat Ahmed, Shifat Mohi Uddin, Khandaker Mohammad Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Heart disease remains the leading cause of mortality globally, emphasizing the critical need for better diagnostics. This study used a variety of machine learning methods to forecast cardiac disease, using SVM, Random Forest, Decision Tree, KNN, and LGBM. The evaluation measures include accuracy, ROC, precision, recall, and F1 score. Data pretreatment procedures such as cleansing, transformation, integration, and reduction were used to guarantee reliable analysis. The model's performance was further enhanced by hyperparameter tuning. SVM had the lowest performance of the models examined, with 57.23% accuracy, 86% precision, 89% recall, and an F1 score of 87%. The study used three different datasets, combining their strengths to improve model discrimination, decrease overfitting, and increase overall accuracy. We developed multiple models from the combination of RF, DT and LGBM. We found accuracy of up to 99.54% by merging LGBM and Random Forest. These findings illustrate the efficacy of the ensemble approaches and data integration in improving heart disease prediction skills using machine learning. © 2024 IEEE.

关键词： Adversarial machine learning

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Stock Market Prediction Using Machine Learning - A Survey 3

Stock Market Prediction Using Machine Learning - A Survey

引用

3rd International Conference for Innovation in Technology, INOCON 2024

作者： Amal, P. Rodrigues, Jolan Naik, Rajat R. Kumar, K. M. Chaman Shetgaonkar, Pratiksha Goa University Srieit Dept. of Computer Engineering Goa India

ISBN: (纸本)9798350381931

The stock market scenario currently is very volatile and prone to sudden changes. The market is in such a state due to factors like the pandemic, conflicts between nations, and the overall recession that's been going on. Many indices worldwide are down from their all-time highs, but the market also shows signs of potential growth albeit it is very slow. In such a situation traders and investors must carefully consider their goals and the risks they're willing to take. It is here where stock market prediction techniques could prove to be the determining factor with respect to making suitable investments. This paper's goal is to describe and compare the various algorithms that are being used for the sole purpose of stock market predictions. © 2024 IEEE.

关键词： Investments

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A real-life comparative analysis of an agricultural and wooden pellets 16

A real-life comparative analysis of an agricultural and wood...

引用

16th Electrical engineering Faculty Conference, BulEF 2024

作者： Tomov, Orlin Dept. of Computer Systems and Technologies University of Ruse "Angel Kanchev Ruse Bulgaria

ISBN: (纸本)9798350391671

In the modern world, the topic of energy efficiency and independence is becoming more and more relevant. We are witnessing an unprecedented expansion of new and green solutions in the field of energy. A large part of them have a more pronounced seasonal character. Such, for example, are photovoltaic solutions. At the same time, the issue of household heating during the winter period is particularly painful. One of the already established solutions is the use of biomass pellets. Until now, the most widely used fuel of this type is wood. Technological solutions that successfully deal with the burning of pellets and agro-waste can be found on the market more and more often. The report presents the results of an experiment on the energy density of different types of pellets. Tests were made with wood, straw and sunflower husk pellets. A methodology for conducting the research in real conditions using a water boiler and a water buffer is proposed. © 2024 IEEE.

关键词： Agricultural pellets comparative analysis Energy density real-life experiment

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A Review on Cosmetic Product Recommendation Using Deep Learning 4

A Review on Cosmetic Product Recommendation Using Deep Learn...

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4th International Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： Chouhan, Ruchika Barde, Snehlata Sage University Dept. of Computer Science Engineering Indore India

ISBN: (纸本)9798331515720

Cosmetic products play an important role in every one's life. Cosmetic products also called as makeup are substance that is applied on the body especially on face. The modern lifestyle can be demanding, leaving little time for self-care. However, it's crucial to prioritize self-care, including skincare, despite hectic schedules. Indeed, relying solely on best-seller products or in-store recommendations may not always be effective in determining compatibility between a skincare product and an individual's skin condition. This is because everyone's skin tone and type of the skin is unique, with varying sensitivities, concerns, and needs. Many people buy their goods online today, using various e-commerce sites. So, to choose the best skincare product during online purchasing is difficult, since it depends entirely on skin type and usage. The main aim of this paper is to survey and explores the existing recommendation systems designed to assist users in selecting cosmetics personalized to their unique skin type, by using advanced algorithms and machine learning. This study has reviewed various methods like face recognition, cosmetic product recognition, tag recommendation, facial skin image classification using convolution neural network, a new examples-rules guided deep neural network approach. Through a comprehensive review of literature and existing research, this paper examines the methodologies, algorithms, and techniques employed in cosmetic recommendation systems. Key factors such as user preferences, skin type, skin concerns, and product attributes are analysed to understand how recommendation systems use this information to generate personalized recommendations. © 2024 IEEE.

关键词： Cosmetics

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Voice Analysis for Detecting Artificial Speech and Predicting Gender

Voice Analysis for Detecting Artificial Speech and Predictin...

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2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Bharadwaj, Rakhi Dugad, Raj Gile, Akshata Patil, Gyaneshwari Hatyalikar, Shrinivas Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350373783

This research paper presents a comprehensive voice analysis system capable of detecting artificial speech and accurately predicting the gender and age of the speaker. Leveraging machine learning, acoustic features, and spectral analysis, the system distinguishes between natural human speech and artificial synthesis with high accuracy. It also excels in predicting the gender and age of the speaker, offering versatile applications in marketing, human-computer interaction, and demographic analysis. The study not only introduces an innovative solution to these challenges but also emphasizes its practical applicability across various domains, underscoring the relevance of voice analysis in today's technology landscape. © 2024 IEEE.

关键词： Prediction models

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Enhancing Translation Quality of English Medical Text Reports into Marathi through integration of Google and Microsoft Bing Transliteration

Enhancing Translation Quality of English Medical Text Report...

引用

2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Surve, Sakshi Manoj Dand, Hiren Shri Jjt University Computer Engineering Dept. Rajasthan India

ISBN: (纸本)9798350373783

Considering various areas of research in the domain NLP, perfect translation of text from a source language to destination language still remains a problem under development. Many a times we get 'transliterated' output instead of expected 'translated' output. Specifically considering good quality translation of English medical text reports into Marathi language is altogether a domain of research. This paper proposes an algorithm where, the first step is to provide the English medical text report to Google translator and Microsoft Bing Translator and receive first level Marathi translated output from these two. As the so received output is many a times loaded with a lot of transliterated words, especially medical terms, the algorithm makes use of the proposed medical dictionary to provide equivalent Marathi words to the transliterated words, so that the readability of the medical text reports is increased. © 2024 IEEE.

关键词： computer aided language translation

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Utilizing Tree-Based Algorithms for Genetic Variant Interpretation 9

Utilizing Tree-Based Algorithms for Genetic Variant Interpre...

引用

9th International Conference on computer Science and engineering, UBMK 2024

作者： Ertürk, Rumeysa Aslihan Baysan, Mehmet Istanbul Technical University Dept. of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350365887

Single Nucleotide Polymorphisms (SNPs) are point mutations of DNA that play an important role in understanding genetic diseases. Determining whether a SNP has the potential to cause disease is a complex and crucial task. Several guidelines exist for the evaluation of the pathogenicity of genomic variation. The ACMG/AMP criteria list is among the widely accepted frameworks. These guidelines consider various biological and clinical features of a variant. Among these, in silico tools-computer-based algorithms that predict variant pathogenicity-play an important role. Various predictor algorithms have been developed in recent years to determine the pathogenicity of variants. However, experiments indicated limited concordance and accuracy among these algorithms. This study compares tree-based machine learning models, including Decision Tree, Random Forest, XGBoost, and CatBoost, for predicting SNP pathogenicity using a benchmark dataset from the ClinVar human variation archive. Our methodology includes the integration of several in silico prediction scores to improve general prediction accuracy. Our experiments demonstrate that combining different tools' predictions with a proper machine learning model, like CatBoost, performs better than stand-alone predictors with an AUPRC of 98.1%. These results indicate that pathogenicity assessment can be very strongly improved by machine learning methods, providing a more reliable tool for genetic disease research and diagnosis. The study underlines the power of combining traditional in silico methods with machine learning models to gain better predictive outcomes. © 2024 IEEE.

关键词： Adversarial machine learning

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Droop Control of Heat Pumps in Integrated Electricity and District Heating systems in Remote Community Microgrids

Droop Control of Heat Pumps in Integrated Electricity and Di...

引用

2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Abuelhamd, Muhammad Cañizares, Claudio A. University of Waterloo Dept. of Electrical and Computer Engineering Waterloo Canada

ISBN: (纸本)9789531842976

This paper proposes a droop control of Heat Pumps (HPs) in Integrated Electricity and Heating systems (IEHSs) to manage energy exchanges between these networks to provide frequency regulation services in microgrids. Thus, demand management control of HPs is proposed to enhance primary frequency regulation, which facilitates the integration of variable Renewable Energy Sources (RESs). The developed droop control is applied, tested, and validated in a realistic community microgrid based on a remote community Electric Power Network (EPN) located at Kasabonika Lake First Nation (KLFN) in Northern Ontario. It is shown that the District Heating Network (DHN) facilitates the proper integration of RESs in isolated microgrids. © 2024 IEEE.

关键词： Microgrids

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Power Consumption Assessment of Telecommunication Base Stations Harnessing Prototype Energy Models 15

Power Consumption Assessment of Telecommunication Base Stati...

引用

15th International Conference on Information, Intelligence, systems and Applications, IISA 2024

作者： Fevgas, Athanasios Korinthios, John A. Tsompanopoulou, Panagiota Frangogiannis, Nikolaos Tsoumanis, Pelopidas Paliaroutis, Georgios-Ioannis Takou, Alexandra Stamoulis, George University of Thessaly Dept. of Electrical and Computer Engineering Volos Greece

ISBN: (纸本)9798350368833

Energy consumed in telecommunication base stations is a significant part of the cellular network energy footprint. Efficient energy use, renewable energy sources, and infrastructure improvement can generate substantial energy savings. We aim to provide a roadmap to fulfill this objective, and energy modeling plays a crucial role in this direction. We introduce five base station energy models for the state-of-the-art EnergyPlus simulator, and we present the development of an OpenStudio Measure for the parameterization of the proposed models. The prototype models and the Measure provide network operators with a comprehensive tool suite for base station energy simulations. This makes our work apart from previous efforts. We conduct a case study demonstrating different usage scenarios of the proposed models utilizing the OpenStudio Application and the OpenStudio Analysis Framework (OSAF). The simulations indicate that construction materials and methods influence the energy efficiency of base stations, while ventilation and photo-voltaics can reduce consumption. Another merit of simulations is that they reveal the most important parameters for the energy performance of base stations. © 2024 IEEE.

关键词： Base stations

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A Hybrid Method for the Detection and Plucking of Mature Coconut Using an Advanced Object Detection Technique 1

A Hybrid Method for the Detection and Plucking of Mature Coc...

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1st International Conference on Trends in engineering systems and Technologies, ICTEST 2024

作者： Muhammed Ilyas, H. Elayidom, Sudheep School of Engineering Cusat Dept. of Computer Science Cochin India

ISBN: (纸本)9798350307795

Vision is a crucial aspect for both artificial intelligence and automated robots. In the case of an automated coconut harvesting machine, a computerized system linked to the machine plays a key role in real-time identification of ripe coconuts within the coconut tree crown. The project employs AI theory to craft an intelligent system. This system utilizes prior knowledge to predict the maturity of coconuts in the current image of the coconut tree crown. A computational board is then employed to compare the captured image with a dataset, enabling the identification of different coconut growth stages and pinpointing the mature coconuts in the current image capture. © 2024 IEEE.

关键词： Object detection

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