检索结果-内蒙古大学图书馆

1st International Conference on Computer, Power and Communications, ICCPC 2022

作者： Vidhya, R.G. Seetha, J. Ramadass, Sudhir Dilipkumar, S. Sundaram, Ajith Saritha, G. Hkbk College of Engineering Department of Ece Bangalore India Panimalar Engineering College Department of Computer Science and Business Systems Chennai India Data Analyst Sterck Systems Chennai India Vit Department of Analytics Scope Vellore India School of Business Selection Grade Kochi India Sri Sai Ram Institute of Technology Department of Ece Tamilnadu Chennai India

ISBN: (纸本)9798350397840

Cancer that originates in the breast tissue then spreads to the chest wall is called breast cancer. Doctors routinely examine mammograms for signs of cancer;however, aberrant macrocalcifications and microcalcifications might appear on mammograms when the picture quality is subpar. Always get checked out if you see anything out of the ordinary, especially if it involves your breasts, such abnormal calcium deposits. For this mammographic deposit to be properly interpreted, top-notch picture quality is necessary. Many different breast cancer screening methods and the many breast cancer phases are still the subject of active study. In order to construct effective medical image processing systems, experts use methods including the Ant Colony Algorithm (ACA), the Improved Adaptive Fuzzy C-Means (IAFCM), and TNM (the size of the breast tumor (T), the lymph nodes around the tumor, and metastasized). Classes were determined using an MPIG, or a modified Poisson inverse gradient classifier. More than five hundred picture modalities are used across all methods. Medical professionals that rely on images to establish diagnoses or treatments might find the results of this research useful. © 2022 IEEE.

关键词： Deposits

来源：评论

学校读者我要写书评

暂无评论

Quantum-Inspired Distributed Memetic Algorithm

引用

Complex System Modeling and Simulation 2022年第4期2卷 334-353页

作者： Guanghui Zhang Wenjing Ma Keyi Xing Lining Xing Kesheng Wang the School of Information Science and Technology and the Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China the School of Information Science and Technology Hebei Agricultural UniversityBaoding 071001China. the State Key Laboratory for Manufacturing System Engineering and the Systems Engineering Institute Xi’an Jiaotong UniversityXi’an 710049China the School of Electronic Xidian UniversityXi’an 710071China the Department of Production and Quality Engineering Norwegian University of Science and TechnologyTrondheim 7491Norway

This paper proposed a novel distributed memetic evolutionary model,where four modules distributed exploration,intensified exploitation,knowledge transfer,and evolutionary restart are coevolved to maximize their strengths and achieve superior global *** exploration evolves three independent populations by heterogenous *** exploitation evolves an external elite archive in parallel with exploration to balance global and local *** transfer is based on a point-ring communication topology to share successful experiences among distinct search *** restart adopts an adaptive perturbation strategy to control search diversity *** computation is a newly emerging technique,which has powerful computing power and parallelized ***,this paper further fuses quantum mechanisms into the proposed evolutionary model to build a new evolutionary algorithm,referred to as quantum-inspired distributed memetic algorithm(QDMA).In QDMA,individuals are represented by the quantum characteristics and evolved by the quantum-inspired evolutionary optimizers in the quantum *** QDMA integrates the superiorities of distributed,memetic,and quantum *** experiments are carried out to evaluate the superior performance of *** results demonstrate the effectiveness of special designs and show that QDMA has greater superiority compared to the compared state-of-the-art algorithms based on Wilcoxon’s rank-sum *** superiority is attributed not only to good cooperative coevolution of distributed memetic evolutionary model,but also to superior designs of each special component.

关键词： distributed evolutionary algorithm memetic algorithm quantum-inspired evolutionary algorithm quantum distributed memetic algorithm

来源：评论

学校读者我要写书评

暂无评论

IoT-Based Smart Home Energy Management System (SHEMS) Using Networking and Automation

IoT-Based Smart Home Energy Management System (SHEMS) Using ...

引用

data science and Business systems (ICDSBS), International Conference on

作者： Arokia Martin N Kirubakaran N Senthil Kumar G Selvaganesan C Jegadeeshwari P Vijayaraja V Department of Computer Science and Business Systems Chennai Institute of Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Dr. MGR Educational and Research Institute (Deemed to be University) Chennai Tamil Nadu India Department of Artificial Intelligence and Data Science RMK College of Engineering and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331585600

ISBN: (纸本)9798331585617

Physical energy meter reading concept is outdated and it is not efficient, leading to lots of wastage of manpower and errors, btaining accurate real-time readings is challenging and complex to achieve consistently. Current implementations of IoT technology allow real-time monitoring and energy management capabilities with the integration of IoT ecosystems, Digital Communication Technology networks, and Machine Learning algorithms to further analyze data as well as enhance user convenience. However, despite their promising potential, these systems face ongoing challenges, including adaptability, scalability, interoperability and enhanced cyber security resilience, particularly in large-scale deployments. This review examines present SHEMS and their capabilities, from strengths such as real-time tracking of energy usage, optimization and consumption of energy at offpeak hours by the application of predictive analytics using Machine Learning. This also elucidates areas for improvement, such as an improved integration of renewable energy technologies, simplification of the complexities surrounding large-scale deployment and sustainability over the long term. Addressing these deficits, this paper further promotes advancements in the design of SHEMS that are more secure, scalable and inter-operable, increasing communication across IoT ecosystems and by using smart grid technology, which could improve effective management of energy and a potential wider uptake. These suggestions are aimed at fine-tuning existing technologies to be easily integrated into modern, automated energy systems for better energy management.

关键词： Renewable energy sources Machine learning algorithms Automation Smart homes Machine learning Predictive models Real-time systems Smart grids Predictive analytics Optimization

来源：评论

学校读者我要写书评

暂无评论

RadonPy:automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics

引用

npj Computational Materials 2022年第1期8卷 2155-2169页

作者： Yoshihiro Hayashi Junichiro Shiomi Junko Morikawa Ryo Yoshida The Institute of Statistical Mathematics(ISM) Research Organization of Information and Systems10-3 Midori-choTachikawaTokyo190-8562Japan Department of Mechanical Engineering The University of Tokyo7-3-1 HongoBunkyoTokyo113-8656Japan Institute of Engineering Innovation The University of Tokyo2-11 YayoiBunkyo-kuTokyo113-0032Japan Department of Materials Science and Engineering School of Materials and Chemical TechnologyTokyo Institute of Technology2-12-1 OokayamaMeguro-kuTokyo152-8552Japan Research and Services Division of Materials Data and Integrated System(MaDIS) National Institute for Materials Science(NIMS)1-2-1 SengenTsukubaIbaraki305-0047Japan Department of Statistical Science School of Multidisciplinary ScienceThe Graduate University of Advanced Studies(SOKENDAI)10-3 Midori-choTachikawaTokyo190-8562Japan

The spread of data-driven materials research has increased the need for systematically designed materials property ***,the development of polymer databases has lagged far behind other material *** present RadonPy,an open-source library that can automate the complete process of all-atom classical molecular dynamics(MD)simulations applicable to a wide variety of polymeric ***,15 different properties were calculated for more than 1000 amorphous *** MD-calculated properties were systematically compared with experimental data to validate the calculation conditions;the bias and variance in the MD-calculated properties were successfully calibrated by a machine learning *** the high-throughput data production,we identified eight amorphous polymers with extremely high thermal conductivity(>0.4 W∙m^(–1)∙K^(–1))and their underlying *** to the advancement of materials informatics since the advent of computational property databases for inorganic crystals,database construction using RadonPy will promote the development of polymer informatics.

关键词： property calculation dynamics

来源：评论

学校读者我要写书评

暂无评论

Exploring Large Language Models for Human Mobility Prediction under Public Events

arXiv

引用

arXiv 2023年

作者： Liang, Yuebing Liu, Yichao Wang, Xiaohan Zhao, Zhan Department of Urban Planning and Design The University of Hong Kong Hong Kong Senseable City Lab Massachusetts Institute of Technology CambridgeMA02139 United States School of Architecture Tsinghua University Beijing China Urban Systems Institute The University of Hong Kong Hong Kong Musketeers Foundation Institute of Data Science The University of Hong Kong Hong Kong

Public events, such as concerts and sports games, can be major attractors for large crowds, leading to irregular surges in travel demand. Accurate human mobility prediction for public events is thus crucial for event planning as well as traffic or crowd management. While rich textual descriptions about public events are commonly available from online sources, it is challenging to encode such information in statistical or machine learning models. Existing methods are generally limited in incorporating textual information, handling data sparsity, or providing rationales for their predictions. To address these challenges, we introduce a framework for human mobility prediction under public events (LLM-MPE) based on Large Language Models (LLMs), leveraging their unprecedented ability to process textual data, learn from minimal examples, and generate human-readable explanations. Specifically, LLM-MPE first transforms raw, unstructured event descriptions from online sources into a standardized format, and then segments historical mobility data into regular and event-related components. A prompting strategy is designed to direct LLMs in making and rationalizing demand predictions considering historical mobility and event features. A case study is conducted for Barclays Center in New York City, based on publicly available event information and taxi trip data. Results show that LLM-MPE surpasses traditional models, particularly on event days, with textual data significantly enhancing its accuracy. Furthermore, LLM-MPE offers interpretable insights into its predictions. Despite the great potential of LLMs, we also identify key challenges including misinformation and high costs that remain barriers to their broader adoption in large-scale human mobility analysis. © 2023, CC BY.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

FedMonitor: An Implementation Architecture for Monitoring of Resources and Events'Notifications on Federated Cloud Computing Infrastructures 4

FedMonitor: An Implementation Architecture for Monitoring of...

引用

4th International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024

作者： Adetiba, Emmanuel Nnaji, Uche Wejin, John S. Ojesanmi, Festus Akanle, Matthew B. Ajayi, Priscilla O. Sweetwiliams, Faith O. Thakur, Surendra C. Adebiyi, Ezekiel F. Department of Electrical and Information Engineering and Covenant Applied Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Covenant University Department of Computer and Information Science & CApIC-ACE Ota Nigeria Covenant University Department of Electrical and Information Engineering & CApIC-ACE Jalingo Nigeria Tareba State University Department of Computer Science Jalingo Nigeria Ota Nigeria Covenant University & CApIC-ACE Covenant University Department of Electrical and Information Engineering Ota Nigeria Covenant University Center for Systems and Information Services & CApIC-ACE Ota Nigeria Durban University of Technology e-Skills Co-Laboratory Department of Information Technology and KZN Durban4001 South Africa Covenant University Ogun State Ota Nigeria Makerere University African Center of Excellence in Bioinformatics & Data Intensive Science Kampala10218 Uganda

ISBN: (纸本)9798350353266

In the evolving landscape of cloud computing, federated cloud infrastructures present unique challenges and opportunities for resource and application monitoring. Monitoring the diverse array of cloud resources and applications within a federated cloud environment is crucial for delivering consistent Quality of Service (QoS) and continuous oversight across various cloud applications and infrastructure. Despite the various successes documented in the literature on multi-cloud monitoring, existing frameworks have not fully explored or provided enough insights into centralized monitoring of resources, applications, and network devices in a federated cloud environment. This paper introduces FedMonitor, an implementation architecture designed to enhance the monitoring and notification capabilities in federated cloud environments by building on the theoretical ideals in our earlier work (i.e. FEDARGOS-V1). FedMonitor leverages Prometheus and Grafana to crawl, manage and visualize metrics from diverse software services, hardware resources, and network devices within a federated cloud environment. The results demonstrate hat FedMonitor improves the effectiveness of resource and application monitoring in federated cloud environments. © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

引用

Congress on Evolutionary Computation

作者： Wenjing Hong Cheng Chen Zexuan Zhu Ke Tang National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA Design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design.

关键词： Measurement Design methodology Evolutionary computation Search problems Linear programming Stability analysis Vaccines

来源：评论

学校读者我要写书评

暂无评论

Leveraging Large Language Models for Biomedical Knowledge Graph Construction and Querying: An Advanced NLP Approach 25

Leveraging Large Language Models for Biomedical Knowledge Gr...

引用

Companion Proceedings of the ACM on Web Conference 2025

作者： Suramya Jadhav Suki Perumal Yasmin Tadavi Bikshita Dash Srinivasan Parthiban Computer Engineering Department Pune Institute of Computer Technology Pune India Department of CSE (AI & ML) PES University Bangalore India Department of Data Science and Engineering Indian Institute of Science Education and Research Bhopal India Aarupadai Veedu Medical College & Hospital Centre for AI in Medicine Vinayaka Missions Research Foundation Puducherry India

ISBN: (纸本)9798400713316

This paper introduces a novel methodology for constructing a comprehensive biomedical knowledge graph by applying advanced Natural Language Processing (NLP) techniques. By leveraging Large Language Models (LLMs) and a multifaceted prompt engineering approach, we effectively perform Named Entity Recognition (NER) and Relation Extraction (RE) on biomedical literature, targeting entities such as diseases, drugs, proteins, procedures, and symptoms. Our methodology incorporates eight distinct prompt engineering strategies for NER and a standardized approach for RE, facilitating the extraction of intricate inter-entity relationships. The resulting knowledge graph amalgamates diverse data sources into a unified framework, enabling efficient querying, visualization, and analysis of biomedical information. Furthermore, we present an innovative query processing pipeline that integrates GPT-3.5 turbo with the knowledge graph, allowing users to interact with the graph through natural language. This integrated system empowers the discovery of novel correlations, accelerating scientific research and fostering interdisciplinary collaboration. This represents a substantial contribution to the field of biomedical knowledge graph construction, offering a robust platform for accelerating scientific discovery and informing clinical decision-making.

关键词： knowledge graphs

来源：评论

学校读者我要写书评

暂无评论

Analyzing α-divergence in Gaussian Rate-Distortion-Perception Theory

Analyzing α-divergence in Gaussian Rate-Distortion-Percepti...

引用

IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Martha V. Sourla Giuseppe Serra Photios A. Stavrou Marios Kountouris School of Electrical & Computer Engineering Technical University of Crete Chania Greece Communication Systems Department EURECOM France Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Spain

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

The problem of the estimation of the information rate-distortion-perception function (RDPF), which is a relevant information-theoretic quantity in goal-oriented lossy compression and semantic information reconstruction, is investigated here. Specifically, we study the RDPF tradeoff for Gaussian sources subject to a mean-squared error (MSE) distortion and a perception measure that belongs to the family of α-divergences. Assuming a jointly Gaussian RDPF, which forms a convex optimization problem, we characterize an upper bound for which we find a parametric solution. We show that evaluating the optimal parameters of this parametric solution is equivalent to finding the roots of a reduced exponential polynomial of degree α. Additionally, we determine which disjoint sets contain each root, which enables us to evaluate them numerically using the well-known bisection method. Finally, we validate our analytical findings with numerical results and establish connections with existing results.

关键词： Wireless communication Upper bound Semantics Measurement uncertainty Estimation Distortion Polynomials Convex functions Distortion measurement Information theory

来源：评论

学校读者我要写书评

暂无评论

Auto capture on drug text detection in social media through NLP from the heterogeneous data

引用

Measurement: Sensors 2022年 24卷

作者： Lavanya, P.M. Sasikala, E. Department of Computer Science and Engineering SRM Institute of Science & Technology Kattankulathur India Department of Information Technology Easwari Engineering College Ramapuram India Department of Data Science & Business Systems SRM Institute of Science & Technology Kattankulathur India

Auto Capture Drug Text detects (ACDTD) that textual content has currently gained important activities in Pharmaceutical drugs research. The recent studies focused on the different resources of textual content-related messages including social networks. Where a huge quantity of consumers posted information about the usage of pharmaceutical drugs and it's combined and cleared neatly. Our textual content classification strategies depend on regenerating the features of a large set of designs;it represents the semantic rules from the short textual nuggets. Significantly use the detailed structured files and it is combined by instruction data from the various collections to regulate the classification approach. Social Media Online Natural Language Processing (SMONLP) with ACDTD class achieves the F-scores of 0.90, 0.738, and 0.878 for the three information files. Integrating the instruction messages from various compatible files enhances the ACDTD F-scores for the in-house information files to 0.797 and 0.854 respectively. The heterogeneous textual content training using the cases where information sets are maintained may reduce the cost and time in the future. © 2022 The Authors

关键词： Natural language processing systems

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：