检索结果-内蒙古大学图书馆

Integration between Bioinformatics Algorithms and Neutrosophic Theory

Neutrosophic Sets and Systems 2024年 66卷 34-54页

作者： Farag, Romany M. Shams, Mahmoud Y. Aldawody, Dalia A. Khalid, Huda E. El-Bakry, Hazem M. Salama, Ahmed A. Dept. of Math and Computer Science Faculty of Science Port Said Univ. Egypt Dept. of Machine Learning Faculty of Artificial Intelligence Kafrelsheikh University Egypt Telafer University Telafer Iraq Dept. of Information Systems Faculty of Computer and Information Sciences Mansoura University Egypt Dept. of Math and Computer Science Faculty of Science Port Said University Egypt

This paper presents a neutrosophic inference model for bioinformatics. The model is used to develop a system for accurate comparisons of human nucleic acids, where the new nucleic acid is compared to a database of old nucleic acids. The comparisons are analyzed in terms of accuracy, certainty, uncertainty, neutrality, and bias. The proposed system achieves good results and provides a reliable standard for future comparisons. It highlights the potential of neutrosophic inference models in bioinformatics applications. data mining and bioinformatics play a crucial role in computational biology, with applications in scientific research and industrial development. Biological analysts rely on specialized tools and algorithms to collect, store, categorize, and analyze large volumes of unstructured data. data mining techniques are used to extract valuable information from this data, aiding in the development of new therapies and understanding genetic relationships between organisms. Recent advancements in bioinformatics include gene expression tools, Bio sequencing, and Bio databases, which facilitate the extraction and analysis of vital biological information. These technologies contribute to the analysis of big data, identification of key bioinformatics insights, and generation of new biological knowledge. data collection, analysis, and interpretation in this field involves the use of modern technologies such as cloud computing, machine learning, and artificial intelligence, enabling more efficient and accurate results. Ultimately, data mining and bioinformatics enhance our understanding of genetic relationships, aid in developing new therapies, and improve healthcare outcomes. © (2024), (Neutrosophic Sets and Systems). All rights reserved.

关键词： Bioinformatics

来源：评论

学校读者我要写书评

暂无评论

Enhancing Medical Image Quality using Neutrosophic Fuzzy Domain and Multi-Level Enhancement Transforms: A Comparative Study for Leukemia Detection and Classification

引用

Neutrosophic Sets and Systems 2024年 65卷 32-56页

作者： Salama, A.A. Shams, Mahmoud Y. Khalid, Huda E. Mousa, Doaa E. Dept. of Math and Computer Sci. Faculty of Science Port Said Univ. Egypt Dept. of Machine Learning Faculty of Artificial Intelligence Kafrelsheikh University Egypt Telafer University Telafer University Telafer Iraq

Medical image processing has become a critical research area due to the vast amounts of digital image data available. However, medical images often suffer from poor illumination and low visibility of significant structures, requiring image enhancement to improve image quality before processing. In this paper, we propose a technique for enhancing medical images by removing noise and improving contrast based on three different enhancing transforms. The proposed technique embeds the image into a neutrosophic fuzzy domain, where it is mapped into three different levels of trueness, falseness, and indeterminacy, and each level is processed individually using the enhancement transforms. We compare the proposed technique with four other systems for leukemia detection and classification using accuracy and T, I, and F values. The proposed system performs the best with an accuracy of 98%, outperforming the other systems in terms of accuracy, degree of indeterminacy, and falsity. The proposed system uses different algorithms and filters to process images and extract features like color and texture. The system’s classification uses k-means for segmentation and SVM for classification. The paper highlights the importance of considering T, I, and F values in evaluating the performance of different systems for leukemia detection and classification, providing a more accurate representation of the uncertainty and ambiguity involved in the evaluation process. © (2024), (Neutrosophic Sets and Systems). All Rights Reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Modified EfficientNetB3 Deep learning Model to Classify Colour Fundus Images of Eye Diseases 5

Modified EfficientNetB3 Deep Learning Model to Classify Colo...

引用

5th IEEE International Conference on Cybernetics, Cognition and machine learning Applications, ICCCMLA 2023

作者： Sharma, Riya Gangrade, Jayesh Gangrade, Shweta Mishra, Ashish Kumar, Gautam Kumar Gunjan, Vinit Manipal University Jaipur Dept of Computer Science & Engineering Jaipur India Learning Manipal University Jaipur Dept. of Artificial Intelligence & Machine Jaipur India Manipal University Jaipur Dept of Information Technology Jaipur India Jaypee Institute of Information Technology Dept of Computer Science & Engineering Noida India CMR Institute of Technology Department of Computer Science & Engineering Hyderabad India

ISBN: (纸本)9798350338287

The only way to prevent blindness from eye problems is by early detection and prompt treatment. Although colour fundus photography (CFP) is useful for fundus inspection, there is a need for computer-assisted automated diagnosis tools due to the similarities between the early symptoms of many eye disorders. The suggested approach uses cutting-edge deep learning model to categorize images into several disease categories by learning distinguishing features from the input images. The high-resolution fundus photos from individuals with diabetic retinopathy (DR), glaucoma, cataract, and healthy eyes make up most of the dataset used for this research. The experimental findings show that the suggested system achieve 97% accuracy with modified efficientNetB3 model and surpasses current approaches for categorizing eye diseases. This approach may help doctors diagnose and treat eye conditions earlier, leading to better patient outcomes. © 2023 IEEE.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving

UniFaaS: Programming across Distributed Cyberinfrastructure ...

引用

International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Yifei Li Ryan Chard Yadu Babuji Kyle Chard Ian Foster Zhuozhao Li Dept. of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Data Science and Learning Division Argonne National Laboratory Lemont IL USA Dept. of Computer Science University of Chicago Chicago IL USA

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

Modern scientific applications are increasingly decomposable into individual functions that may be deployed across distributed and diverse cyberinfrastructure such as supercomputers, clouds, and accelerators. Such applications call for new approaches to programming, distributed execution, and function-level management. We present UniFaaS, a parallel programming framework that relies on a federated function-as-a-service (FaaS) model to enable composition of distributed, scalable, and high-performance scientific workflows, and to support fine-grained function-level management. UniFaaS provides a unified programming interface to compose dynamic task graphs with transparent wide-area data management. UniFaaS exploits an observe-predict-decide approach to efficiently map workflow tasks to target heterogeneous and dynamic resources. We propose a dynamic heterogeneity-aware scheduling algorithm that employs a delay mechanism and a re-scheduling mechanism to accommodate dynamic resource capacity. Our experiments show that UniFaaS can efficiently execute workflows across computing resources with minimal scheduling overhead. We show that UniFaaS can improve the performance of a real-world drug screening workflow by as much as 22.99% when employing an additional 19.48% of resources and a montage workflow by 54.41% when employing an additional 47.83% of resources across multiple distributed clusters, in contrast to using a single cluster.

关键词： Scheduling algorithms Parallel programming Heuristic algorithms Parallel processing Elasticity Dynamic scheduling Supercomputers

来源：评论

学校读者我要写书评

暂无评论

Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent 37

Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Sto...

引用

37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Zhu, Lingjiong Gürbüzbalaban, Mert Raj, Anant Şimşekli, Umut Dept. of Mathematics Florida State University United States Dept. of Management Science and Information Systems Rutgers Business School United States Center for Statistics and Machine Learning Princeton University United States Coordinated Science Laboratory University of Illinois Urbana-Champaign United States Inria Paris CNRS Ecole Normale Supérieure PSL Research University France

ISBN: (纸本)9781713899921

Algorithmic stability is an important notion that has proven powerful for deriving generalization bounds for practical algorithms. The last decade has witnessed an increasing number of stability bounds for different algorithms applied on different classes of loss functions. While these bounds have illuminated various properties of optimization algorithms, the analysis of each case typically required a different proof technique with significantly different mathematical tools. In this study, we make a novel connection between learning theory and applied probability and introduce a unified guideline for proving Wasserstein stability bounds for stochastic optimization algorithms. We illustrate our approach on stochastic gradient descent (SGD) and we obtain time-uniform stability bounds (i.e., the bound does not increase with the number of iterations) for strongly convex losses and non-convex losses with additive noise, where we recover similar results to the prior art or extend them to more general cases by using a single proof technique. Our approach is flexible and can be generalizable to other popular optimizers, as it mainly requires developing Lyapunov functions, which are often readily available in the literature. It also illustrates that ergodicity is an important component for obtaining time-uniform bounds - which might not be achieved for convex or non-convex losses unless additional noise is injected to the iterates. Finally, we slightly stretch our analysis technique and prove time-uniform bounds for SGD under convex and non-convex losses (without additional additive noise), which, to our knowledge, is novel. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Additive noise

来源：评论

学校读者我要写书评

暂无评论

Dynamic Encoder Size Based on data-Driven Layer-wise Pruning for Speech Recognition

arXiv

引用

arXiv 2024年

作者： Xu, Jingjing Zhou, Wei Yang, Zijian Beck, Eugen Schlüter, Ralf Machine Learning and Human Language Technology Group Computer Science Dept. RWTH Aachen University Germany AppTek GmbH Aachen52062 Germany

Varying-size models are often required to deploy ASR systems under different hardware and/or application constraints such as memory and latency. To avoid redundant training and optimization efforts for individual models of different sizes, we present the dynamic encoder size approach, which jointly trains multiple performant models within one supernet from scratch. These subnets of various sizes are layer-wise pruned from the supernet, and thus, enjoy full parameter sharing. By combining score-based pruning with supernet training, we propose two novel methods, Simple-Top-k and Iterative-Zero-Out, to automatically select the best-performing subnets in a data-driven manner, avoiding resource-intensive search efforts. Our experiments using CTC on both Librispeech and TED-LIUM-v2 corpora show that our methods can achieve on-par performance as individually trained models of each size category. Also, our approach consistently brings small performance improvements for the full-size supernet. Copyright © 2024, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences

arXiv

引用

arXiv 2023年

作者： Hong, Xudong Sayeed, Asad Mehra, Khushboo Demberg, Vera Schiele, Bernt Dept. of Computer Vision and Machine Learning MPI Informatics Germany Dept. of Language Science and Technology Saarland University Germany Dept. of Philosophy Linguistics Theory of Science University of Gothenburg Sweden

Current work on image-based story generation suffers from the fact that the existing image sequences collections do not have coherent plots behind them. We improve visual story generation by producing a new image-grounded dataset, Visual Writing Prompts (VWP). VWP contains almost 2K selected sequences of movie shots, each including 5-10 images. The image sequences are aligned with a total of 12K stories which were collected via crowdsourcing given the image sequences and a set of grounded characters from the corresponding image sequence. Our new image sequence collection and filtering process has allowed us to obtain stories that are more coherent and more diverse compared to previous work. We also propose a character-based story generation model driven by coherence as a strong baseline. Evaluations show that our generated stories are more coherent, visually grounded, and more diverse than stories generated with the current state-of-the-art model. This is a pre-MIT Press publication version. © 2023, CC BY.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Customer Behaviour Analysis: Tools Overview

Customer Behaviour Analysis: Tools Overview

引用

Women in Innovation, Technology & Entrepreneurship (ICWITE), IEEE International Conference for

作者： Jigyasa Bharti Snehlata Dongre Mayuri Thorat Dept. of Computer Science and Engineering G H Raisoni College of Engineering Nagpur India Dept. of Artificial Intelligence and Machine Learning PES’s Modern College of Engineering Pune India

Analytics is a process of collecting and analyzing data that can help in taking meaningful decisions. The data is collected from various sources, this raw data is then processed and converted to dashboards which assists in business analyzation. Analytics are of various types such as descriptive, diagnostic, predictive, prescriptive and text. One area of analytics is Business Intelligence which is a broader concept of using various tools and methods that involves presentation of business data to support decision making. Customer behavioral analysis can be conducted by having insights from web analytics. It is a process of understanding how a customer is responding to a website. Regular improvements can be done to increase customer interaction, enhance user experience and data-driven decision-making. In this paper, we will be discussing two major tools that are used for behavior analysis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Fare Prediction Accuracy in Ride Hailing Through Neural Networks and data Simulation

Enhancing Fare Prediction Accuracy in Ride Hailing Through N...

引用

Artificial Intelligence and data Engineering (AIDE), International Conference on

作者： Priyanshu Tiwari S Ambareesh Soumya Patil Rishabh Raj Dept. of Artificial Intelligence and Machine Learning Sir M. Visvesvaraya Institute of Technology Bengaluru India Dept. of Information Science and Engineering Sir M. Visvesvaraya Institute of Technology Bengaluru India

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

Prediction of fare is the need for better service quality and effective pricing strategies that make for enhanced customer experiences in a ride-hailing service. From the identified features based on rides and ride-hailing activities - the distance covered, the time used for travel, number of passengers, and the main purposes of trips, the researchers will create a neural network model using such synthesized data to make real-time predictions for an accurate total fare estimate. This synthesis helps to understand the noise and natural variability in the ride-hailing datasets by showing different interaction patterns of the features over time. The analysis techniques used include scatter plots, correlation matrices, and time-series evaluations that reveal strong connections between fare amounts and distance traveled and trip duration. The dataset used in this research was sourced from Kaggle, ensuring a reliable foundation for training and evaluating the model. The proposed neural network architecture achieved 90% accuracy, with Mean Absolute Error (MAE) of 1.5 units and Root Mean Squared Error (RMSE) of 2.3 units, demonstrating its reliability. This paper shows how neural networks might be applicable to fare predictions and, therefore, can contribute toward artificial datasets with practical models applicable in the real world.

关键词： Training Analytical models Adaptation models Accuracy Neural networks Pricing Predictive models data models Tides Synthetic data

来源：评论

学校读者我要写书评

暂无评论

ClimateCast: ML-Powered Temperature Forecasting for North 24 Parganas

ClimateCast: ML-Powered Temperature Forecasting for North 24...

引用

2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Paria, Abhirup Ghatak, Anindya Jana, Biswajit Adhikary, Arpan Sen, Priyanka Das, Ruma Haldia Institute of Technology Dept. of Computer Sc. & Engg Artificial Intelligence & Machine Learning Haldia India School of Computer Sc. Engg. & Tech Bennett University Uttar Pradesh Greater Noida India Haldia Institute of Technology Dept. of Computer Sc. & Engg. Haldia India School of Applied Science & Humanities Haldia Institute of Technology Haldia India

ISBN: (纸本)9798331517953

Global warming is increasing at a rapid rate. Several efforts are made to understand its influence worldwide and in particular regions as well. Therefore, temperature prediction has become one of the most important and influential research topics because of its application in agricultural, ecological, industrial, and environmental sectors. This study reviews dif-ferent machine learning algorithms for temperature prediction and observes their superiorities. The area of study was done in North 24 Parganas, West Bengal, India. Parameters used in the dataset of the North 24 Parganas include wind speed, different types of UV radiance, cloud amount, soil moisture, precipitation rate, surface pressure, and specific and relative humidity. The relevant features are chosen from all the parameters using feature selection. The feature selection technique used is SelectKBest, using Mutual Info Regression. The different ML models used are KNN Regression, Linear Regression (LR), Decision Tree Regression, Support Vector Regression, Random Forest Regression, LightGBM Regression, XGBoost Regression, AdaBoost Regression and Ridge Regression. The experimental results were evaluated using Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE) and R Squared (coefficient of determination). The result of this experiment revealed that XGBoost Regression has MAE, MSE, RMSE, and R Squared respectively 0.361, 0.273, 0.523, 0.989 followed by LightGBM Regression with MAE, MSE, RMSE and R squared followed by 0.366, 0.276, 0.526 and 0.988. These results show that XGBoost Regression possesses a high capability for temperature prediction © 2024 IEEE.

关键词： Support vector regression

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：