检索结果-内蒙古大学图书馆

8th International Conference on Information Technology and Multimedia, ICIMU 2020

作者： Subramainan, Latha Mahmoud, Moamin A College of Graduate Studies Universiti Tenaga Nasional Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia

ISBN: (数字)9781728173108

ISBN: (纸本)9781728173108

Although researchers from across the field of social sciences have highlighted the importance of academic emotions, it has mostly been neglected as a crucial factor to promote active and meaningful communication in a classroom. To tackle this issue, this paper provides a clear vision to understand the current state of research in this area. To do so, a comprehensive review is conducted on academic emotions to map the studies in the literature to a coherent taxonomy. This paper examines the literature on academic emotions to provide a systematic presentation to the concept and subsequently provides a baseline and recommendations for further research on students' engagement based on academic emotions. © 2020 IEEE.

关键词： Academic Emotions Emotional Experiences in Classroom Emotional States Emotional Triggers and Reactions

来源：评论

学校读者我要写书评

暂无评论

Use of Faceted Search: The Effect on Researchers

Use of Faceted Search: The Effect on Researchers

引用

7th International Conference on Advances in Visual informatics, IVIC 2021

作者： Mahdi, Mohammed Najah Ahmad, Abdul Rahim Qassim, Qais Saif Subhi, Mohammed Ahmed Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Selangor Malaysia Universiti Tenaga Nasional Kajang Selangor Malaysia Ibri College of Technology Ibri Oman Al Hikma University College Department of Computer Engineering Baghdad Iraq

ISBN: (纸本)9783030902346

The extensive amount of results obtained from any Web search operation and loads of related and/or irrelevant hits presented on the user’s screen are still poses challenges in the information retrieval field of study;especially if the user is an academic researcher and is looking for reliable and focused results. Therefore, improving the performance of Web search engines continues to be an active research topic. One of the biggest challenges to search engine optimization is when a user submits incomplete query statements or fragmented keywords. Using broken or fragmented keywords the semantic correlation will fail to result in inconsistent and outsized search results. This oversized (or overloaded) problem can be mitigated by utilizing the Exploratory Search technique with a faceted search refining mechanism. This study’s main goal is to present a short review of the existing Exploratory Search techniques and faceted search implementations and shed light on the main limitations and shortcomings. © 2021, Springer Nature Switzerland AG.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Integrating machine learning and experimental data in modeling optical behaviors of neodymium oxide nanoparticle-doped glasses

引用

The European Physical Journal Special Topics 2025年 1-24页

作者： Nazrin, S. N. Burhanuddin, Liyana Adilla Zaman, Halimah Badioze Fudzi, Faznny Mohd Shaaban, Ibrahim A. Institute of Informatics and Computing in Energy (IICE) College of Engineering Universiti Tenaga Nasional Kajang Malaysia Department of Electronic Systems Engineering (ESE) Malaysia–Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia Johor Bahru Malaysia Centre for Pre-University Studies Universiti Malaysia Sarawak Kota Samarahan Malaysia Department of Chemistry College of Science King Khalid University Abha Saudi Arabia

Zinc tellurite doped with neodymium oxide nanoparticles (Nd2O3 NPs) glass series has been fabricated using conventional melt-quenching technique to explore the respective optical, structural, and physical properties of the glass material. Fourier-transform infra-red (FTIR) spectra and the respective deconvolution revealed changes in the amount of TeO3 and TeO4 structural units related to the concentration of neodymium oxide nanoparticles, which directly influences the amount of bridging oxygen and non-bridging oxygen in the glass system. The density of the prepared glasses possesses increasing trend with values that rose from 5346 to 5606 kg m−3 as more Nd2O3 NPs are incorporated in the glass matrix. The parameters for optical properties have also been determined, assisted and trained the chosen model in order to predict the data for optical properties of glass material with different chemical compositions via the machine learning approach. To enhance the experimental results, machine learning models were developed using linear regression (LR) and artificial neural networks (ANN). ANN model with its ability to capture both linear as well as non-linear interactions has outperformed the simulation and LR model as the ANN model had managed to accurately predict the values for the optical properties of glass material based on the compositional parameters. This underscores the effectiveness of ANN in modeling having intricate relationships between dopant concentrations and optical behaviors while at the same time providing critical insights for future advancements in doped glass technology.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Transient Analysis of Electrical Circuits using Block Backward Differentiation Formula 2020

Transient Analysis of Electrical Circuits using Block Backwa...

引用

9th International Conference on informatics, Environment, energy and Applications, IEEA 2020

作者： Zawawi, Iskandar Shah Mohd Aris, Hazleen Jørgensen, Bo Nørregaard Universiti Teknologi MARA Shah Alam Selangor Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Malaysia Center for Energy Informatics Mærsk McKinney Moller Institute University of Southern Denmark

ISBN: (纸本)9781450376891

Transient is the time-varying currents and voltages resulting from the sudden change in supply current or voltage. This phenomenon usually occurs due to any switching, interrupting, short-circuiting as well as any rapid changes in the structure of an electrical circuit. To avoid any damage in certain components resulting from the transient, it is important to analyze the change of voltage or current across the circuit elements. This paper studies the transient analysis of a second order RLC circuit that consists of resistors (R) and two energy storage elements, which are inductor (L) and capacitor (C). Such circuit is normally represented in the form of second order ordinary differential equations (ODEs) and such problems are not easily solved analytically. Therefore, a numerical method, namely block backward differentiation formula (BBDF) is applied for solving the ODEs by taking into consideration the damping factor and change in charge with respect to time. This method has the advantage that in each application, the solution is computed at two points simultaneously, which can give faster solutions to the problem. Numerical experiments are carried out to evaluate the capability of the proposed method. It is shown that the numerical solutions approximate the analytical solutions. The performance of the BBDF is compared with the Euler's method, Heun's method and Runge-Kutta method in terms of accuracy. Results obtained show that the proposed method is reliable for transient analysis of electrical circuit due to its comparable degree of accuracy. © 2020 ACM.

关键词： Transient analysis

来源：评论

学校读者我要写书评

暂无评论

Information Storage and Retrieval System for a Molecular Dynamics Based Digital Twin of Materials

Information Storage and Retrieval System for a Molecular Dyn...

引用

2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2022

作者： Topolsky, Dmitry Belyakov, Alexander Pochinskaia, Veronica Topolskaya, Irina Yumagulov, Nikolay Fedorov, Dmitry South Ural State University Dept. of Electronic Computing Machines Chelyabinsk Russia South Ural State University Dept. of Energy and Power Engineering Chelyabinsk Russia Nizhnevartovsk State University Dept. for Education in Physics and Mathematics Name of Organization Nizhnevartovsk Russia Surgut State University Dept. of Informatics and Computer Engineering Surgut Russia

ISBN: (纸本)9781665464802

Digital twin technology becomes an appropriate respond to the new challenge of rapid development in science and industry. Chemical data include the information about structure and properties of materials and compounds. Machine learning technology can help to predict properties of innovative compounds and material, but it takes enormous amount of raw data. The implementation of digital twin technology in spectral and molecular dynamics helps to reduce risks introducing the innovations. Large systems technologies are used in multiscale modeling of materials with computer programs. The world experience of chemical data aggregation and storage is based on specialized databases creation. Disunity of data sources demands a single multiscale data model to operate raw data and amend the accuracy of prediction. To collect and analyze unstructured data full-text search and distributed computing were applied. In respond to perpetual raw data expansion a Data Lake technology is used to store, analyze and search for information of atomic and molecular systems. © 2022 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Deep Neural Networks for Object Classification with Edge TPU 8

Performance Analysis of Deep Neural Networks for Object Clas...

引用

8th International Conference on Information Technology and Multimedia, ICIMU 2020

作者： Asyraaf Jainuddin, Ahmad Ammar Hou, Yew Cheong Baharuddin, Mohd Zafri Yussof, Salman College of Engineering Universiti Tenaga Nasional Selangor Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Selangor Malaysia

ISBN: (纸本)9781728173108

Deep learning becomes a more popular, widespread, and common tool in almost any task that requires information extraction from a large dataset. Hence, the data transmission speed between the data-gathering devices and processing units can be crucial in hardware selection depending on the machine learning application. Generally, the processing unit is usually centralized, and the data transferring time will increase when the data-gathering devices were installed further away from the processing unit. The work aims to provide the performance analysis on Google's new machine learning hardware called Edge TPU that was created specifically for edge devices. Furthermore, the work also reviewed the different types of deep neural network models as current benchmarks in deep learning were tested with different hardware used in edge applications. The review also discussed the comparison of the performance of the edge device using the deep neural networks in Tensorflow. From the results obtained, the performance of the edge device with the Edge TPU is faster than the device without it. © 2020 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Analyzing darknet traffic through machine learning and neucube spiking neural networks

引用

Intelligent and Converged Networks 2024年第4期5卷 265-283页

作者： Iman Akour Mohammad Alauthman Khalid M.O.Nahar Ammar Almomani Brij B.Gupta Information Systems Department College of Computing&InformaticsUniversity of SharjahSharjahUnited Arab Emirates Department of Information Security Faculty of Information TechnologyUniversity of PetraAmman 11196Jordan the Faculty of Computer Studies Arab Open UniversityRiyadh 11681Saudi Arabia Department of Information Technology Al-Huson University CollegeAl-Balqa Applied UniversityIrbid 19117Jordan the Department of Computer Information Science Higher Colleges of TechnologySharjahUnited Arab Emirates the Department of Computer Science and Information Engineering Asia UniversityTaichung 413ChinaSymbiosis Centre for Information TechnologySymbiosis International(Deemed University)Pune 412115India Centre of Inter-disciplinary Research&Innovation University of Petroleum and Energy StudiesDehradun 248007India

The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication *** detection of clandestine darknet traffic is therefore critical yet immensely *** research demonstrates how advanced machine learning and specialized deep learning techniques can significantly enhance darknet traffic analysis to strengthen *** diverse classifiers such as random forest and naïve Bayes with a novel spiking neural network architecture provides a robust foundation for identifying concealed *** on the CIC-Darknet2020 dataset establishes state-of-the-art results with 98%accuracy from the random forest model and 84.31%accuracy from the spiking neural *** pioneering application of artificial intelligence advances the frontiers in analyzing the complex characteristics and behaviours of darknet *** proposed techniques lay the groundwork for improved threat intelligence,real-time monitoring,and resilient cyber defense systems against the evolving landscape of cyber threats.

关键词： darknet traffic machine learning deep learning spiking neural network PCA

来源：评论

学校读者我要写书评

暂无评论

A Ground Fault Location Method for DC Railway Systems

A Ground Fault Location Method for DC Railway Systems

引用

International Conference on Environment and Electrical Engineering (EEEIC)

作者： José M. Guerrero Daniel Serrano-Jiménez Kumar Mahtani Carlos A. Platero Electronic and Computing Department Mondragon University Arrasate/Mondragon Spain Energy and Fuels Department Universidad Politécnica de Madrid Madrid Spain Automatic Electric and Electronic engineering and Industrial Informatics Department Universidad Politécnica de Madrid Madrid Spain

The application of Direct Current (DC) railway systems is more and more noticeable as they conform most of urban tram feeding systems and, step-by-step, it is being introduced in high-speed train power systems. Despite of their high efficiency, the risk of ground faults is latent due to environmental problems and aging in the catenary. These faults can interrupt the service for hours until it is repaired, then a quick maintenance is needed. In order to help in this issue, this paper proposes a ground fault location method for catenaries in DC railway systems based on the DC voltage and earth current measurement in each DC traction substation (TS). The normalized currents respecting the global fault current are compared with a model-based data pool allowing the method to locate the fault along the protected catenary. To corroborate the method, simulations have been performed in a three-TS DC railway model in Matlab-Simulink obtaining promising results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

energy Usage Prediction for Smart Home with Regression Based Ensemble Model 8

Energy Usage Prediction for Smart Home with Regression Based...

引用

8th International Conference on Information Technology and Multimedia, ICIMU 2020

作者： Hoque, Mohammad Shamsul Jamil, Norziana Saharudin, Sharul Azim Amin, Nowshad College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia Institute of Sustainable Energy Universiti Tenaga Nasional Kajang Malaysia

ISBN: (纸本)9781728173108

Residential sectors using energy mainly though lighting and HV AC (Heating, Ventilation and Air-Conditioning) have become a significant consumer of world energy and it is expected to grow especially with the trend of increasing smart homes. To provide an optimum, accurate and reliable electricity distribution, load prediction is a prerequisite policy and operational implementation. Smart homes with the use of various sensors create big data that gives a favorable opportunity for developing data-driven energy usage prediction models. In this paper, a novel regression-based ensemble prediction model with inbuilt automated optimization for parameters is proposed to predict the demand of electricity. The model explains the 0.998 correlation between the features and their label, and achieved root mean squared error (RMSE) and Normalized Absolute Error as low as 5.508 and 0.0508 respectively. We have also proposed a novel data-driven classification of the energy usage by unsupervised learning through clustering. © 2020 IEEE.

关键词： K-means clustering

来源：评论

学校读者我要写书评

暂无评论

A parametric analysis of electroosmotic and magnetohydrodynamic flows with homogeneous-heterogeneous reactions between squeezing plates

引用

The European Physical Journal Special Topics 2024年 1-26页

作者： Jan, Wajid Ullah Farooq, Muhammad Shah, Rehan Ali Khan, Aamir Jan, Rashid Ahmad, Imtiaz Idris, Sahar Ahmed Department of Mathematics Abdul Wali Khan University Mardan Mardan Pakistan Department of Basic Sciences and Islamiat University of Engineering and Technology Peshawar Peshawar Pakistan Department of Pure and Applied Mathematics The University of Haripur Haripur Pakistan Institute of Energy Infrastructure (IEI) Department of Civil Engineering College of Engineering Universiti Tenaga Nasional (UNITEN) Kajang Malaysia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Kajang Malaysia Faculty of Engineering Department of Industrial Engineering King Khalid University Abha Saudi Arabia

The Poisson–Boltzmann equation characterizes the internal electric potential in electroosmotic and magnetohydrodynamic (MHD) processes, under the assumptions of thermodynamic equilibrium and negligible fluid flow effects. However, for significant convective ion transport, the Nernst–Planck equation is requisite. This study develops predictive models for electroosmotic and MHD flows between squeezing plates, where convective ion transport is minimal. The partial differential equations (PDEs) are transformed into ordinary differential equations (ODEs) using similarity transformations and solved analytically via the homotopy analysis method (HAM). The HAM results, validated against the numerical solver BVP4c, exhibit strong concordance. Various physical effects are elucidated through graphical and tabular representations, revealing that squeezing the plates reduces electroosmotic flow profiles while increasing the magnetic Reynolds number in both homogeneous and heterogeneous reactions.

关键词：

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：