检索结果-内蒙古大学图书馆

IEEE Conference on Nanotechnology

作者： Ping Bai Ken Chang R. S. Kajen Erping Li Ganesh Samudra Engineering Software and Applications Institute of High Performance Computing Singapore Department of Electrical & Computer Engineering National University of Singapore Singapore

We predict the impact ionization in a 13 nm gate length double-gate MOSFET structures using full-band self- consistent ensemble Monte Carlo method with quantum correction. The effects of various design parameters such as gate oxide thickness, body thickness and channel length on the impact ionization onset voltages are investigated. The studies show that the reduction of channel length reduction remains as the major contributor to the impact ionization phenomena. On analyzing the distribution of impact ionization events in the structure, impact ionization induced hot carrier activity is shown to be largely confined to the channel-drain interface region. This allows for possible gate oxide hot carriers reliability issues to be greatly reduced through an optimal design.

关键词： Impact ionization Logic gates Breakdown voltage Electric breakdown Mathematical model MOSFET circuits Hot carriers

来源：评论

学校读者我要写书评

暂无评论

Improving Transfer Learning Performance for Abnormality Detection in Brain MRI Images Using Feature Optimization Techniques

Improving Transfer Learning Performance for Abnormality Dete...

引用

International Conference on Soft Computing and Measurements (SCM)

作者： Yasser A. Nizamli Anton Yu. Filatov Department of Software Engineering and Computer Applications Saint Petersburg Electrotechnical University “LETI” Saint Petersburg Russian Federation

ISBN: (数字)9798350363708

ISBN: (纸本)9798350363715

Accurate and early diagnosis of brain tumors plays a vital role in determining appropriate treatment and increasing survival rates. Manual diagnosis using MRI images is often prone to errors and can be a tedious and time-consuming procedure. As a result, automated computer-aided systems that utilize artificial intelligence and machine learning techniques are widely used. However, accurately diagnosing the type of brain tumor remains a significant and complex challenge for today’s medical imaging research community. In this paper, we present an enhanced transfer learning approach that aims to differentiate brain tumor types using MRI scans while achieving state-of-the-art performance. In the proposed approach, the pre-trained VGG-19 network with fixed weights is used to map MRI scans to a high-level numerical representation. The extracted features are then passed to a support vector machine algorithm to classify brain tumors into one of three major categories: glioma, meningioma, and pituitary. To further improve the performance of the model, the effectiveness of utilizing feature optimization techniques based on the radial basis similarity function and L1-penalty logistic regression was investigated. For evaluation, the benchmark Figshare dataset containing 3064 MRI images was used after a series of processing operations. The proposed system achieved a high overall accuracy of 98.53%, outperforming other analogues.

关键词： Logistic regression Accuracy Magnetic resonance imaging Computational modeling Transfer learning Feature extraction Brain modeling

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach for Predicting Air Quality Index in Smart Cities 5

A Machine Learning Approach for Predicting Air Quality Index...

引用

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Swamynathan, S. Sneha, N. Ramesh, S.P. Niranjana, R. Ponkumar, D. David Neels Saravanakumar, R. Karpagam Academy of Higher Education Department of Computer Applications Tamil Nadu Coimbatore India School of Computer Science & Engineering Department of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida India Sri Krishna College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Iconix Software Solution Tamil Nadu Tirunelveli India

ISBN: (纸本)9798331518097

One essential natural resource, the air quality index has been deteriorated by economic activities. Many studies have been conducted about the forecasting of periods of unsafe atmospheric conditions;however, the majority of these studies are limited in their capacity to include seasonal and other factors due to insufficient longitudinal data. India noise pollution has compiled a 6-year dataset that has been used to build several prediction models. There are encouraging outcomes when AQI levels are predicted using machine learning methodologies such as support vector machines (SVMs) artificial neural networks (ANNs), and Naive Bayes (NB). However, in several tests involving datasets from three different locations, NB, ANN, and SVM performed well to maximize prediction performance. When it comes to mean absolute error (MAE), R-squared (R2), and Root-mean-square deviation (RMSE), the combined performance of stacks is unsurpassed. In the related work section, summarize the limitations of existing models, such as inadequate data preprocessing, low spatialtemporal resolution, limited feature selection, or overfitting in complex models. Highlight gaps in scalability, real-time adaptability, and generalization across regions, emphasizing the need for robust, efficient models tailored to air quality prediction. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Research of Dimension Reduction Algorithms of Feature Space in Data Analysis Task

Research of Dimension Reduction Algorithms of Feature Space ...

引用

IEEE NW Russia Young Researchers in Electrical and Electronic engineering Conference (EIConRusNW)

作者： Nikita V. Popov Dmitry M. Klionskiy Department of Software Engineering and Computer Applications Saint Petersburg Electrotechnical University “LETI” St. Petersburg Russia

ISBN: (数字)9781728157610

ISBN: (纸本)9781728157627

Today data describing a particular subject area, often contain a large number of different features that determine the properties of any processes or objects. At the same time, these data sets can reach enormous sizes, so working with data turns into very resource-intensive and long processes. Reducing the dimension of the feature space entails a reduction in the used memory and getting rid of noisy and duplicate information. To reduce the space, various machine-learning algorithms are used, each of which has its own individual degree of efficiency and validity for its area of application. Client databases are no exception, they often contain large amounts of information, some of which are redundant. Therefore, reducing the space of signs in client data is a topic whose relevance is only increasing every day. This paper presents a study of such methods as reduction of features with low variability, Univariate feature selection, recursive feature elimination, selection based on a decision tree, principal component analysis. Based on the results of the study, requirements are formulated for an algorithm for reducing the dimension of the feature space specifically for the task of working with client data.

关键词： Feature extraction Classification algorithms Principal component analysis Decision trees Machine learning algorithms Libraries Machine learning

来源：评论

学校读者我要写书评

暂无评论

Data Analytics for Core Temperature Estimation in Battery Management System for Electric and Hybrid Vehicles 5

Data Analytics for Core Temperature Estimation in Battery Ma...

引用

5th International Conference on Energy, Power, and Environment, ICEPE 2023

作者： Chhetri, Ahilya Surya, Sumukh Mohan Krishna, S. Rao, Vidya Cactus Communications Engineering and Technology Mumbai India Bosch Global Software Technologies Pvt. Limited Bengaluru India Aced Alliance University Department of Electrical and Electronics Engineering Bengaluru India Manipal Institute of Technology Manipal Academy of Higher Education Department of Data Science and Computer Applications Manipal India

ISBN: (纸本)9798350313123

Compared to conventional means of transport thatuse fossil fuels, electric vehicles are known to reduce pollution levels as they take power from renewable sources of energy stored in energy storage devices like batteries and fuel cells. Core temperature estimation of batteriesis extremely important inbattery management systems for preventing thermal runaway and ensuring safe operation. In this study, core temperature is estimated using a Kalman filter for two different battery chemistries viz;lithium polymer and lithium iron phosphate using a second-order thermal model. Further, a linear regression model is applied to verify the prediction over the trained and tested dataset. The lithium iron phosphate prediction curvehad a fit of approximately 82-83%, whilelithium polymerhad a fit of 72-82% during the charging and discharging of OCV-SOC variation. © 2023 IEEE.

关键词： Simulink

来源：评论

学校读者我要写书评

暂无评论

Coupling Trends in Industrial Prototyping Roles: An Empirical Investigation

引用

software Quality Journal 2001年第4期9卷 223-240页

作者： Phalp, Keith Counsell, Steve Empirical Software Engineering Group Bournemouth University Bournemouth United Kingdom Department of Computer Science Birkbeck College University of London Malet Street London WC1E 7HX United Kingdom University of Kent United Kingdom Bournemouth University United Kingdom Inst. of Math. and its Applications United Kingdom

Prototyping in the development cycle claims to improve analyst understanding of system requirements leading to systems which match those requirements more closely. The quality of the end systems, from a user perspective, is thus improved. In this paper, the results of an empirical investigation into the use of prototyping in the development of various systems is described. Nine processes across eight different sites were analysed and data relating to each process was collected. The notation of Role Activity Diagrams (RADs) was used to capture each of the nine processes. Five hypotheses were then investigated: these related the prototyping role to features of other roles such as extent of interaction during the prototyping process, the effect site size had on the prototyping role and the dependence of the prototyping role on other roles in the prototyping process. Two coupling metrics were introduced to quantitatively analyse these RAD features. Results indicated a strong similarity between large and medium-sized sites in terms of interactions and behaviour. The prototyping process in small sites, however, was found to be different to large and medium-sized sites in both respects. The study demonstrates how measures of business models can aid analysis of the process as well as the products of systems development and highlights the need for more empirical investigation into this and other facets of the software development process.

关键词： software design

来源：评论

学校读者我要写书评

暂无评论

XP/Agile education and training

XP/Agile education and training

引用

6th International Conference on Extreme Programming and Agile Processes in software engineering

作者： Martin, A Fraser, S Davies, R Holcombe, M Mugridge, R Pierce, D Poppendieck, T Succi, G Qualcomm's Learning Center Victoria University of Wellington New Zealand Agile Experience Ltd. Department of Computer Science University of Sheffield United Kingdom British Computer Society Inst. Math. and Its Applications United Kingdom Extreme Tuesday Club (XTC) Department of Tenure Free University of Bolzano Bozen Italy Center for Applied Software Engineering Italy

ISBN: (纸本)3540262776

XP/Agile education and training remains a challenge from the perspective of determining relevant content;identifying effective methods for delivery;and maintaining the focus and motivation of students. This panel brings together academic and industry professionals to share their perspectives and experiences. Anticipated points for discussion include: education/training delivery strategies, curriculum definition, certification challenges, marketing issues, collaboration strategies to engage industry sponsorship, value assessments for students and sponsoring organizations, and program success stories. This will be a highly interactive panel and the audience should come prepared to both ask and answer questions. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Education

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Strategic Foresight: Anticipating Future Trends and Modelling Business Strategies

AI-Driven Strategic Foresight: Anticipating Future Trends an...

引用

2024 International Conference on Decision Aid Sciences and applications, DASA 2024

作者： Qader Ismail Alnajem, Ahmed Abdel Ibrahim, Amer Abdulrahman, Mayasa M. Abdulrazak Al-Kubaisi, Abdulrazak A. Tawfeq, Jamal Fadhil Khishe, Mohammad Saeed, Ali Baghdad College of Economic Sciences Business Administration Department Iraq College of Information Technology Department of Computer Science and Software Engineering United Arab Emirates College of Engineering Computer Engineering Department University of Baghdad Baghdad Iraq Medical Technical College Department of Medical Instrumentation Technical Engineering Al-Farahidi University Baghdad00965 Iraq Yuan Ze University Innovation Center for Artificial Intelligence Applications Taiwan Jadara University Jadara Research Center Jordan Northern Technical University Computer Center Ninevah Iraq

ISBN: (纸本)9798350369106

In a generation characterized with the aid of speedy technological advancements, socio-monetary shifts, and environmental challenges, groups need to undertake proactive strategies to stay aggressive and resilient. Strategic foresight, which entails expecting destiny tendencies and modeling enterprise techniques, accordingly, emerges as a vital device in navigating this uncertainty. The trouble this have a look at addresses is the growing trouble groups face in predicting and making ready for destiny disruptions the use of conventional forecasting techniques. The number one goals of this have a look at are to discover the important thing methodologies and gear of strategic foresight, display how those techniques may be implemented to assume destiny tendencies, and offer insights on integrating foresight into enterprise approach formulation. This has a look at contributes to the present frame of information with the aid of using providing a complete evaluation of strategic foresight techniques, which includes environmental scanning, situation planning, the Delphi method, fashion evaluation, SWOT and PESTLE evaluation, and era street mapping. Research findings show that forward-looking strategies provide an organization with the ability to identify potential risks and opportunities, develop adaptive strategies, and achieve long-term growth Specifically, strategic organizations using anticipation reports a 30% increase in the ability to anticipate market fluctuations, a 25% improvement in strategic haste and a 20% reduction in unexpected disruptions, of consumer goods etc. Case studies of various industries demonstrate the practical application and usefulness of forecasting in real-world situations The study concludes that incorporating forward-looking strategies into business planning does not that it not only prepares organizations for future challenges but empowers them to shape their future and ensure sustainable competitive advantage. © 2024 IEEE.

关键词： Competition

来源：评论

学校读者我要写书评

暂无评论

Client Segmentation and Customization in E-Commerce: applications of Machine Learning from a Management Perspective

Client Segmentation and Customization in E-Commerce: Applica...

引用

2024 International Conference on Communication, computer Sciences and engineering, IC3SE 2024

作者： Sriprasadh, K. Palit, Shamik Pravallika, B. Manjunatha Lenka, Reena Singla, Atul Srm Institute Of Science And Technology Faculty Of Science And Humanities Department Of Computer Science And Applications Chennai Vadapalani India University Of Stirling Rak Campus Department Of Computing Science And Software Engineering United Arab Emirates Institute Of Aeronautical Engineering Dundigal Hyderabad India New Horizon College Of Engineering Department Of Mechanical Engineering Bangalore India University Pune India Lovely Professional University Phagwara India

ISBN: (纸本)9798350366846

A machine learning-based e-commerce personalised recommendation system helps address the issue of information overload that inevitably arises when consumers have more and more options in e-commerce, leading to an increasingly complex structure. Customer segmentation is a crucial component of contemporary marketing strategy since it enables companies to effectively adjust their advertising campaigns and customise their communications with customers. Through the analysis of enormous quantities of consumer behaviour data and the discovery of trends that can be utilised for dividing customers into segments, ML algorithms provide a potent tool for automating the procedure of customer segmentation. We report our research and results for identifying a customer's segment. In order to perform machine learning, we integrate the Python Tensorflow library with Pandas for manipulating data frames. To address any discrepancies or gaps in the collected client data, it is refined. Key features are found, and to find hidden patterns and relationships, an exploratory analysis of the data is done. After that, we decide on a suitable machine learning technique to divide the clientele into various groups. We also experiment with several clustering models, including conventional machine learning techniques. © 2024 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

Demonstration of the SALUS semantic interoperability framework for case series characterization studies 6

Demonstration of the SALUS semantic interoperability framewo...

引用

6th International Workshop on Semantic Web applications and Tools for Life Sciences, SWAT4LS 2013

作者： Yuksel, Mustafa Gonul, Suat Erturkmen, Gokce Banu Laleci Sinaci, Ali Anil Depraetere, Kristof De Roo, Jos Bergvall, Tomas SRDC Software Research and Development and Consultancy Ltd. Ankara Turkey Department of Computer Engineering Middle East Technical University Ankara Turkey Agfa HealthCare Advanced Clinical Applications Research Group Gent Belgium Uppsala Monitoring Centre Uppsala Sweden

This work aims to demonstrate the interoperability framework devel-oped in the SALUS project which enables effective integration and utilization of EHR data to reinforce post-market safety activities.

关键词： Commerce

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：