检索结果-内蒙古大学图书馆

An Adjusted Gray Map Technique for Constructing Large Four-Level Uniform Designs

Journal of Systems science & Complexity 2023年第1期36卷 433-456页

作者： ELSAWAH A M VISHWAKARMA G K MOHAMED H S FANG Kai-Tai Department of Statistics and Data Science Faculty of Science and TechnologyBeijing Normal University-Hong Kong Baptist University United International CollegeZhuhai 519087China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International CollegeZhuhai 519087China Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 44519Egypt Department of Mathematics&Computing Indian Institute of Technology DhanbadDhanbad 826004India College of Transportation and Civil Engineering Fujian Agriculture and Forestry UniversityFuzhou 350002China The Key Lab of Random Complex Structures and Data Analysis The Chinese Academy of SciencesBeijing 100190China

A uniform experimental design(UED)is an extremely used powerful and efficient methodology for designing experiments with high-dimensional inputs,limited resources and unknown underlying models.A UED enjoys the following two significant advantages:(i)It is a robust design,since it does not require to specify a model before experimenters conduct their experiments;and(ii)it provides uniformly scatter design points in the experimental domain,thus it gives a good representation of this domain with fewer experimental trials(runs).Many real-life experiments involve hundreds or thousands of active factors and thus large UEDs are *** large UEDs using the existing techniques is an NP-hard problem,an extremely time-consuming heuristic search process and a satisfactory result is not *** paper presents a new effective and easy technique,adjusted Gray map technique(AGMT),for constructing(nearly)UEDs with large numbers of four-level factors and runs by converting designs with s two-level factors and n runs to(nearly)UEDs with 2^(t−1)s four-level factors and 2tn runs for any t≥0 using two simple transformation *** justifications for the uniformity of the resulting four-level designs are given,which provide some necessary and/or sufficient conditions for obtaining(nearly)uniform four-level *** results show that the AGMT is much easier and better than the existing widely used techniques and it can be effectively used to simply generate new recommended large(nearly)UEDs with four-level factors.

关键词： Aberration adjusted Gray map technique Gray map technique Hamming distance moment aberration threshold accepting algorithm uniform design

来源：评论

学校读者我要写书评

暂无评论

Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications

引用

Digital Communications and Networks 2023年第2期9卷 367-382页

作者： Qusay M.Salih Md Arafatur Rahman A.Taufiq Asyhari Muhammad Kamran Naeem Mohammad Patwary Ryan Alturki Mohammed Abdulaziz Ikram Faculty of Computing Universiti Malaysia Pahang26300GambangPahangMalaysia School of Engineering Computing and Mathematical SciencesUniversity of WolverhamptonUK Data Science Program Monash UniversityIndonesiaand Birmingham City UniversityB47XGUK Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Computer Science Department Al Jumoum University CollegeUmm Al-Qura UniversitySaudi Arabia

Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)*** order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed ***,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel ***,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing *** study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT ***,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability ***,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation *** protocol combines lower layer(Physical layer and data Link layer)sensing that is derived from the channel estimation ***,it periodically updates and stores the routing table for optimal route ***,in order to achieve higher throughput and lower delay,a new routing metric is *** evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a *** simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achiev

关键词： Channel selection Cross-layer design Mobile cognitive radio networks Routing protocol IIoT applications

来源：评论

学校读者我要写书评

暂无评论

Shrinkage Estimation for Location and Scale Parameters of Logistic Distribution Under Record Values

引用

Annals of data science 2024年第4期11卷 1209-1224页

作者： Gupta, Shubham Vishwakarma, Gajendra K. Elsawah, A.M. Department of Mathematics & amp Computing Indian Institute of Technology Dhanbad826004 India Department of Statistics and Data Science Faculty of Science and Technology Beijing Normal University-Hong Kong Baptist University United International College Zhuhai519087 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai519087 China Department of Mathematics Faculty of Science Zagazig University Zagazig44519 Egypt

Logistic distribution (LogDis) is frequently used in many different applications, such as logistic regression, logit models, classification, neural networks, physical sciences, sports modeling, finance and health and disease studies. For instance, the distribution function of the LogDis has the same functional form as the derivative of the Fermi function that can be used to set the relative weight of various electron energies in their contributions to electron transport. The LogDis has wider tails than a normal distribution (NorDis), so it is more consistent with the underlying data and provides better insight into the likelihood of extreme events. For this reason the United States Chess Federation has switched its formula for calculating chess ratings from the NorDis to the LogDis. The outcomes of many real-life experiments are sequences of record-breaking data sets, where only observations that exceed (or only those that fall below) the current extreme value are recorded. The practice demonstrated that the widely used estimators of the scale and location parameters of logistic record values, such as the best linear unbiased estimators (BLUEs), have some defects. This paper investigates the shrinkage estimators of the location and scale parameters for logistic record values using prior information about their BLUEs. Theoretical and computational justifications for the accuracy and precision of the proposed shrinkage estimators are investigated via their bias and mean square error (MSE), which provide sufficient conditions for improving the proposed shrinkage estimators to get unbiased estimators with minimum MSE. The performance of the proposed shrinkage estimators is compared with the performances of the BLUEs. The results demonstrate that the resulting shrinkage estimators are shown to be remarkably efficient. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

C Programming Skill Levels Determination Using Fuzzy Logic 7

C Programming Skill Levels Determination Using Fuzzy Logic

引用

7th International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational science and Information Management, ICSECS-ICOCSIM 2021

作者： Aiman Al-Falah Muhd Yazid, Muhammad Azida Sahabudin, Noor Farihan Mat Raffei, Anis Akmal Remli, Muhammad Universiti Malaysia Pahang Faculty of Computing Pahang Pekan Malaysia Universiti Malaysia Kelantan Department of Data Science Kota Bahru Kelantan Malaysia

ISBN: (纸本)9781665414074

Programming language is known among computer science students. One should know at least one programming language throughout their studies. However, mastering one programming language is challenging. Most of the new student find challenging to learn and understand the language as they are not familiar with it. This can cause a problem throughout their studies or even in future jobs. Thus, implementing artificial intelligence to identify students' understandability level towards programming skills is expected to improve their knowledge and weakness about that programming language. This paper presents proposed work for designing the level of programming knowledge for new computer science student. The level of programming knowledge is identified and analyzed based on the student input. The fuzzy logic approach is employed in this study to obtain the target result based on several criterion. Several tools are used to develop the platform for collecting user input data. The output of this work shows that the student can identify their element on each spoke and the programming language level with a short description by displaying data visualization as the output to user in the radar chart. © 2021 IEEE.

关键词： Membership functions

来源：评论

学校读者我要写书评

暂无评论

Inventory models for short life cycle clothing products use a logistic growth model 5

Inventory models for short life cycle clothing products use ...

引用

5th International Conference on Mathematics: Pure, Applied and Computation, ICoMPAC 2019

作者： Lukitosari, V. Subriadi, A.P. Mathematics Department Faculty of Mathematics Computing and Data Science Sepuluh Nopember Institute of Technology [ITS Surabaya60111 Indonesia Surabaya60111 Indonesia

Clothes are products that follow short-life fashion and market demand. Products with a short lifetime occur due to technological developments and/or changes in market tastes. The clothing industry is one of the industries that has a short and obsolete sales period in stages. The excess number of products that accumulate in the warehouse due to obsolescence can cause the company to get a profit that is not optimal. One strategy to increase demand for the product is to apply discounts. There are two types of discounts used, namely a single discount and multiple discounts. The demand function of inventory model is considered analogous to the logistic growth model. The results show profit is maximized to get optimal order quantity and optimal discount price. © Published under licence by IOP Publishing Ltd.

关键词： Profitability

来源：评论

学校读者我要写书评

暂无评论

Disturbance compensating model predictive control for warship heading control in missile firing mission 2

Disturbance compensating model predictive control for warshi...

引用

2nd Mathematics, Informatics, science and Education International Conference, MISEIC 2018

作者： Purnawan, Heri Asfihani, Tahiyatul Adzkiya, Dieky Subchan Modeling and Simulation Systems Laboratory Department of Mathematics Faculty of Mathematics Computing and Data Science Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia

One of warship missions is shooting and avoiding enemy attacks, which can be done by missile firing strategy. Due to missile firing, the movement of ship becomes unstable. To overcome this problem, we need a control system that can overcome the disturbance caused by the impact of the missile firing. So, in this paper, we propose a method called disturbance compensating MPC (DC-MPC) control system. This control is chosen, because DC-MPC is a robust method for measurable disturbance. Based on the result of simulation, DC-MPC can overcome disturbance on the system and make ship's actual heading angle to follow the desired reference quickly which is about 10 s. After the system gets disturbance, controller is also able to adjust the value of the ship heading angle to original position. © Published under licence by IOP Publishing Ltd.

关键词： Warships

来源：评论

学校读者我要写书评

暂无评论

A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction

Computer Methods and Programs in Biomedicine Update

引用

Computer Methods and Programs in Biomedicine Update 2025年 7卷

作者： Suleiman Daoud Ahmad Nasayreh Khalid M.O. Nahar Wlla k. Abedalaziz Salem M. Alayasreh Hasan Gharaibeh Ayah Bashkami Amer Jaradat Sultan Jarrar Hammam Al-Hawamdeh Absalom E. Ezugwu Raed Abu Zitar Aseel Smerat Vaclav Snasel Laith Abualigah Neurosurgery Department Faculty of Medicine Jordan University of Science and Technology Irbid 22110 Jordan Artificial Intelligence and Data Innovation Office King Hussein Cancer Center Amman Jordan Department of Information Technology and Computer Sciences Yarmouk University Irbid 211633 Jordan Department of Rehabilitation science Faculty of applied medical science Jordan University of Science and Technology King Abdullah University Hospital Irbid Jordan Department of Medical Laboratory Sciences Al Balqa Applied University Salt Jordan Unit for Data Science and Computing North-West University 11 Hofman Street Potchefstroom 2520 South Africa College of Engineering and Computing Liwa University Abu Dhabi United Arab Emirates Faculty of Educational Sciences Al-Ahliyya Amman University Amman 19328 Jordan Computer Technologies Engineering Mazaya University College Nasiriyah Iraq Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava 70800 Poruba-Ostrava Czech Republic Computer Science Department Al al-Bayt University Mafraq 25113 Jordan

A brain tumor, one of the deadliest disorders, is characterized by the abnormal growth of synapses in the brain. Early detection can improve brain tumor diagnosis, and accurate diagnosis is essential for effective treatment. Researchers have developed several deep-learning classification methods to diagnose brain tumors. Moreover, these types of tumorscan significantly impair physical activity, presenting a broad spectrum of symptoms. As a result, each patient requires an individualized physical therapy treatment plan tailored to their specific needs. However, some challenges remain, including the need for a competent expert in classifying brain tumors using deep learning models, as well as the challenge of creating the most accurate deep learning model for brain tumor classification. To address these challenges, we present a highly accurate and efficient methodology based on advanced metaheuristic algorithms and deep learning. To identify different types of pediatric brain tumors, we specifically develop an optimal residual learning architecture. We also present the Spider Wasp Optimization (SWO) algorithm, which aims to improve performance by feature selection. The algorithm enhances the effectiveness of optimization by balancing the speed of convergence and diversity of solutions. We first convert the algorithm from continuous to binary, combine it with the K-Nearest Neighbor (KNN) algorithm for classification, and evaluate it on a dataset of brain MRI images collected from King Abdullah Hospital. Our analysis revealed that in terms of metrics such as accuracy, sensitivity, specificity, and f1-score, it outperformed other conventional algorithms. We demonstrate the overall effectiveness of the proposed model by using it to select the optimal features extracted from the Resnet50V2 model for pediatric brain tumor detection. We compared the proposed SWO+KNN model with other deep learning architectures such as MobileNetV2, Resnet50V2, and machine learning algorithms

关键词： Brain tumor Pediatric Machine learning Rehabilitation Physical therapy Deep learning Metaheuristic optimization Feature selection

来源：评论

学校读者我要写书评

暂无评论

An Optimized Neural Network with Bat Algorithm for DNA Sequence Classification

引用

Computers, Materials & Continua 2022年第10期73卷 493-511页

作者： Muhammad Zubair Rehman Muhammad Aamir Nazri Mohd.Nawi Abdullah Khan Saima Anwar Lashari Siyab Khan Faculty of Computing and Information Technology Sohar UniversitySohar311Sultanate of Oman Soft Computing&Data Mining Centre(SMC) Faculty of Computer Science&Information TechnologyUniversiti Tun Hussein Onn Malaysia(UTHM)Batu Pahat86400Malaysia School of Electronics Computing and MathematicsUniversity of DerbyDerbyDE221GBUnited Kingdom Institute of Computer Sciences and Information Technology The University of Agriculture25120PeshawarPakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia

Recently, many researchers have used nature inspired metaheuristicalgorithms due to their ability to perform optimally on complex problems. Tosolve problems in a simple way, in the recent era bat algorithm has becomefamous due to its high tendency towards convergence to the global optimummost of the time. But, still the standard bat with random walk has a problemof getting stuck in local minima. In order to solve this problem, this researchproposed bat algorithm with levy flight random walk. Then, the proposedBat with Levy flight algorithm is further hybridized with three differentvariants of ANN. The proposed BatLFBP is applied to the problem ofinsulin DNA sequence classification of healthy homosapien. For classificationperformance, the proposed models such as Bat levy flight Artificial NeuralNetwork (BatLFANN) and Bat levy Flight Back Propagation (BatLFBP) arecompared with the other state-of-the-art algorithms like Bat Artificial NeuralNetwork (BatANN), Bat back propagation (BatBP), Bat Gaussian distribution Artificial Neural Network (BatGDANN). And Bat Gaussian distributionback propagation (BatGDBP), in-terms of means squared error (MSE) andaccuracy. From the perspective of simulations results, it is show that theproposed BatLFANN achieved 99.88153% accuracy with MSE of 0.001185,and BatLFBP achieved 99.834185 accuracy with MSE of 0.001658 on *** on WL10 the proposed BatLFANN achieved 99.89899% accuracy withMSE of 0.00101, and BatLFBP achieved 99.84473% accuracy with MSE of0.004553. Similarly, on WL15 the proposed BatLFANN achieved 99.82853%accuracy with MSE of 0.001715, and BatLFBP achieved 99.3262% accuracywith MSE of 0.006738 which achieve better accuracy as compared to the otherhybrid models.

关键词： DNA sequence classification bat algorithm levy flight back propagation neural network hybrid artificial neural networks(HANN)

来源：评论

学校读者我要写书评

暂无评论

Lane Detection Using Deep Learning for Rainy Conditions 9

Lane Detection Using Deep Learning for Rainy Conditions

引用

9th International Conference on Computer and Communication Engineering, ICCCE 2023

作者： Ghani, Hadhrami Ab Daud, Atiqullah Mohamed Besar, Rosli Sani, Zamani Md Kamaruddin, Mohd Nazeri Syahali, Syabeela Universiti Malaysia Kelantan Faculty of Data Science and Computing Kelantan Malaysia Multimedia University Faculty of Engineering and Technology Melaka Malaysia Universiti Teknikal Malaysia Melaka Faculty of Mechatronic Engineering Melaka Malaysia

ISBN: (纸本)9798350325218

Prior research has shown that various road marker classification mechanisms in clear or dry weather conditions have high accuracy performance. However, the performance tends to be lower under rainy driving conditions due to the reduced quality of the road image when detecting the five classes of road markers which are Single, Single-Single, Dashed, Solid-Dashed, and Dashed-Solid. To address this challenging condition, lane marker detection based on deep learning approach is proposed in this paper. The target weather condition is rainy, which is very challenging as it causes the surface of the roads, especially the area which includes the lane marker to become blurry and unclear due to the rainwater. In order to carefully select the right features of the road such that the lane marker can be classified and detected successfully. The lane marker object is captured from the frames of the video clips taken from established published video datasets. With this fast and better lane marker detection, the achievable classification precision is satisfactory although the weather is rainy. © 2023 IEEE.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Two layers of annotation for representing event mentions in news stories 11

Two layers of annotation for representing event mentions in ...

引用

11th Linguistic Annotation Workshop, LAW 2017

作者： Di Buono, Maria Pia Tutek, Martin Šnajder, Jan Glavaš, Goran Bašić, Bojana Dalbelo Milić-Frayling, Nataša TakeLab Faculty of Electrical Engineering and Computing University of Zagreb Croatia Data and Web Science Group University of Mannheim Germany School of Computer Science University of Nottingham United Kingdom

ISBN: (纸本)9781945626395

In this paper, we describe our preliminary study of methods for annotating event mentions as part of our research on highprecision models for event extraction from news. We propose a two-layer annotation scheme, designed to capture the functional and the conceptual aspects of event mentions separately. We hypothesize that the precision can be improved by modeling and extracting the different aspects of news events separately, and then combining the extracted information by leveraging the complementarities of the models. We carry out a preliminary annotation using the proposed scheme and analyze the annotation quality in terms of inter-annotator agreement. © 2017 Association for Computational Linguistics.

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：