检索结果-内蒙古大学图书馆

Energy saving slot allocation-based multicast routing in cloud wireless mesh network

International Journal of Cloud Computing 2023年第2-4期12卷 148-162页

作者： Jeyakarthic, M. Subalakshmi, N. Department of Computer and Information Science Annamalai University Tamil Nadu Annamalai Nagar India Computer Science and Engineering Wing Directorate of Distance Education Annamalai University Tamil Nadu Annamalai Nagar India

Many techniques of cloud computing are affected by surge load and time issues. This proposed method for virtual cloud planning utilise simple protocols in a single or multiple data centres. A new load balanced amortised multi-scheduling algorithm (LBAM) is proposed for assigning the task to cloud based on active load in the cloud environment. The proposed system calculates the multiple attribute weight for each workplace and introduces an application source that changes in application virtualisation environment. The system calculates the cloud data weight based upon the allocation of data and its consequence based on the processing efficiency of the cloud machine. This approach works effectively in most configurations, also virtual machines hold the ability to process load with high pace and efficient memory management. A detailed comparative analysis is made with the existing methods namely SLA, FPGGA and DJS algorithms. The obtained results indicated that the LBAM model is superior to compared methods under several aspects. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

引用

computers, Materials & Continua 2023年第2期74卷 2379-2395页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Electrocardiogram(ECG)signal is a measure of the heart’s electrical ***,ECG detection and classification have benefited from the use of computer-aided systems by *** goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization(DTO)and Differential Evolution Algorithm(DEA)into a unified algorithm to optimize the hyperparameters of neural network(NN)for boosting the ECG classification *** addition,we proposed a new feature selection method for selecting the significant feature that can improve the overall *** prove the superiority of the proposed approach,several experimentswere conducted to compare the results achieved by the proposed approach and other competing ***,statistical analysis is performed to study the significance and stability of the proposed approach using Wilcoxon and ANOVA *** results confirmed the superiority and effectiveness of the proposed *** classification accuracy achieved by the proposed approach is(99.98%).

关键词： Electrocardiogram differential evolution algorithm dipper throated optimization neural networks

来源：评论

学校读者我要写书评

暂无评论

Neural Gas Counter Propagation Neural Network (NG CPNN): A Novel Model for Face Recognition

Neural Gas Counter Propagation Neural Network (NG CPNN): A N...

引用

2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Olagunju, Kazeem Michael Samuel Falohun, Adeleye Oke, Alice Oluwafunke Adebiyi, Marion O. Landmark University Directorate of Centre for Systems and Information Services Omu-Aran Nigeria LAUTECH Department of Computer Engineering Ogbomoso Nigeria Landmark University Department of Computer Science Omu-Aran Nigeria

ISBN: (纸本)9798350358155

The advent of biometric technology has enhanced security in various ways, especially by lowering the propensity for circumvention which was obtainable in traditional recognition measures such as the use of passwords, tokens, smart cards, PIN etc. Particularly facial recognition is currently a hot topic, which has evolved over time. A face recognition system is supposed to automatically recognize faces in pictures and videos by receiving a two-dimensional face image as input and comparing it to a predefined database of faces to outputs a discernible face image in the end. Despite the various algorithms used in face recognition, the problems of occlusion, light conditions and facial variation still persist. However, this study has implemented and presented Neural Gas Counter Propagation Neural Network (NG CPNN) as a novel model for face recognition *** implementation of model was carried out using 600 face images, pre-processed by histogram equalization, while face features were extracted by Principal Component Analysis. The novelty of NG CPNN was established by utilizing computational time, sensitivity, and accuracy as performance assessment measures at four distinct threshold values. The result shows computation time of 72.36s, accuracy of 96.25%, sensitivity of 98.33% at 0.8, 0.8, and 0.2 thresholds respectively. Finally, it was concluded based on empirical result and statistical evidence that NG-CPN is a novel model for face recognition. NG CPNN can be employed in access control systems, international borders, smartphone technology, and many more. © 2024 IEEE.

关键词： artificial intelligence biometrics face recognition image processing NG- CPNN pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Code Generation for Collectible Card Games with Complex APIs 36th

Code Generation for Collectible Card Games with Complex APIs

引用

36th International Florida Artificial Intelligence Research Society Conference, FLAIRS-36 2023

作者： Licato, John Fields, Logan Hollis, Brayden Lab Department of Computer Science and Engineering University of South Florida United States Information Directorate Air Force Research Lab United States

Large pre-trained language models (LMs) such as GPT-3 Codex are able to generate code remarkably well given prompts of natural language text. But if we want to use such LMs to generate code compatible with a specific API or library (e.g., an API which provides the environments in which certain rules, laws, or orders are to be carried out), the amount of computational and data resources required to fine-tune such models can be cost prohibitive to most organizations. Given these practical limitations, is it possible to utilize these massive codegeneration LMs to write code compatible with a given API? We develop an algorithm that selects code examples using a smaller LM trained to predict which features of an API are likely to be used in the resulting code, which is a simpler problem than actually generating the code. The selected examples are then used to build a prompt for the larger LM, which in turn generates the final code. We demonstrate our results on a benchmark dataset derived from the collectible card game "Magic: the Gathering," and obtain state-of-the-art results. © 2023 by the authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3384-3392页

作者： Alkhouri, Ismail R. Jha, Sumit Beckus, Andre Atia, George Jha, Susmit Ewetz, Rickard Velasquez, Alvaro OrlandoFL32816 United States Michigan State University Computational Mathematics Science and Engineering Department East LansingMI48824 United States University of Michigan Electrical Engineering and Computer Science Department Ann ArborMI48109 United States Florida International University Knights Foundation School of Computing and Information Sciences MiamiFL33199 United States Air Force Research Laboratory Rome Information Directorate NY13441 United States Department Computer Science Department OrlandoFL32816 United States SRI International Computer Science Laboratory Menlo ParkCA94025 United States Electrical and Computer Engineering Department OrlandoFL32816 United States University of Colorado Computer Science Department BoulderCO80309 United States

Protein folding neural networks (PFNNs) such as AlphaFold predict remarkably accurate structures of proteins compared to other approaches. However, the robustness of such networks has heretofore not been fully explored. This is particularly relevant given the broad social implications of such technologies and the fact that biologically small perturbations to noncritical residues of a protein sequence do not typically lead to drastic changes in the protein structure. Our study demonstrates that, similar to adversarial methods in machine learning, small changes to protein sequences can result in significant differences in the predicted protein structures using AlphaFold as determined by large distance measures. Despite this, our findings using multiple protein sequences suggest that AlphaFold is able to accurately predict the domain structure and folding regions of a protein. To gauge structural differences, we employ two alignment-based measures [root-mean-square deviation (RMSD) and the global distance test (GDT) similarity], and one alignment-free measure, which is an effective graph-based structure representation (GraSR) method. We prove that the problem of minimally perturbing protein sequences is NP-complete. Based on the well-established block substitution matrices (BLOSUM62) sequence alignment scoring matrix, we generate adversarial sequences. In our experimental evaluation, we consider 111 proteins (including 29 COVID-19 sequences) in the Universal Protein resource (UniProt), a central resource for protein data. Our findings suggest that, despite the high RMSD values returned by AlphaFold, it is capable of handling the BLOSUM adversarial sequences considered in our analysis, as evidenced by the preservation of the folded regions and the GraSR results. © 2020 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Developing a Breast Cancer Resistance Protein Substrate Prediction System Using Deep Features and LDA

引用

computers, Materials & Continua 2023年第8期76卷 1643-1663页

作者： Mehdi Hassan Safdar Ali Jin Young Kim Muhammad Sanaullah Hani Alquhayz Khushbakht Safdar Department of Computer Science Air UniversitySector E-9PAF ComplexIslamabad44000Pakistan Department of ICT Convergence System Engineering Chonnam National UniversityGwangjuKorea Directorate of National Repository IslamabadPakistan Department of Computer Science Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Pakistan Atomic Energy Commission General HospitalIslamabadPakistan

Breast cancer resistance protein(BCRP)is an important resistance protein that significantly impacts anticancer drug discovery,treatment,and *** identification of BCRP substrates is quite a challenging *** study aims to predict early substrate structure,which can help to optimize anticancer drug development and clinical *** this study,a novel intelligent approach-based methodology is developed by modifying the ResNet101 model using transfer learning(TL)for automatic deep feature(DF)extraction followed by classification with linear discriminant analysis algorithm(TLRNDF-LDA).This study utilized structural fingerprints,which are exploited by DF contrary to conventional molecular *** proposed in silico model achieved an outstanding accuracy performance of 98.56%on test data compared to other state-of-the-art approaches using standard quality ***,the model’s efficacy is validated via a statistical *** is demonstrated that the developedmodel can be used effectively for early prediction of the substrate *** pipeline of this study is flexible and can be extended for in vitro assessment efficacy of anticancer drug response,identification of BCRP functions in transport experiments,and prediction of prostate or lung cancer cell lines.

关键词： BCRP drug response deep learning transfer learning LDA In silico

来源：评论

学校读者我要写书评

暂无评论

Landslide susceptibility assessment along the major transport corridor using decision tree model: a case study of Kullu-Rohtang Pass

引用

International Journal of Business Intelligence and Data Mining 2023年第1期24卷 1-24页

作者： Nirbhav Malik, Anand Maheshwar Prasad, Mukesh Department of Geography Delhi School of Economics University of Delhi Delhi India Swami Shraddhanand College University of Delhi Delhi India TGT Computer Science Directorate of Education Delhi Government Delhi India Faculty of Engineering and Information Technology School of Computer Science Australian Artificial Intelligence Institute University of Technology Sydney Sydney Australia

To lessen damages from landslides, the key challenge is to predict the events precisely and accurately. The objective of this study is to assess landslide susceptibility in the study area. To achieve this objective, a detailed landslide inventory has been prepared based on imagery data and frequent field visits of 153 rock slides and 44 debris slides. Nine landslide factors were prepared initially and their relationships with each other and with the type of landslide was analysed. information gain ratio measure is used to eliminate triggering factors with least score. Train_test_split method was used to classify the dataset into training and testing groups. Decision tree classification model of machine learning was applied for landslide susceptibility model (LSM). The performance was evaluated using classification report and receiver operating characteristic (ROC) curve. Results obtained have proven that the decision tree classification model performed well with good accuracy in forecasting landslide susceptibility. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Landslides

来源：评论

学校读者我要写书评

暂无评论

AVIG: A Real-Time Visual Inspection for Guava Grading System Using computer Vision and XGBoost 23

AVIG: A Real-Time Visual Inspection for Guava Grading System...

引用

8th International Conference on Sustainable information engineering and Technology, SIET 2023

作者： Setyawan, Raden Arief Perdana, Rizal Setya Harilegawa, Made Wena Balantimuhe, Alan Stevrie Basuki, Achmad Department of Electrical Engineering Faculty of Engineering Brawijaya University Malang Indonesia Department of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia Directorate of Information Technology Brawijaya University Malang Indonesia

ISBN: (纸本)9798400708503

The conventional approach to manual inspection can be described by its considerable time and labor demands and the unavoidable occurrence of human error when faced with the inspection of a large number of products. Therefore, the application of an automated visual inspection system is frequently employed. The camera(s) can easily capture visual features for automatic visual inspection. However, it is essential to note that there are limitations when using this method to estimate the size-based grading system. The volume measurement is an essential feature in the field of automatic image analysis for fruit and vegetable grading, specifically guava. In this study, we propose a novel image analysis approach that utilizes a dual-view camera system to enhance the accuracy of volume approximation, particularly in scenarios involving non-perfect spherical objects. Hence, this research presents the training process of a comprehensive model for estimating the volume of objects with irregular shapes, named AVIG (Automatic Visual Inspection for Grading). The model utilizes the ellipsoid approximation technique, a dual-view camera, and XGBoost algorithm. The results from the accuracy comparison demonstrate that XGBoost shows the highest degree of accuracy, specifically 86%, thereby outperforming the performance of other algorithms. The comprehensive experiment conducted in this study has shown that the proposed architecture, AVIG, exhibits superior performance compared to previous research in terms of automatic evaluation of moving objects. © 2023 ACM.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

引用

computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

来源：评论

学校读者我要写书评

暂无评论

The Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks 3rd

The Effects of Weather Conditions on Data Transmission in Fr...

引用

3rd International Conference on Computing and Communication Networks, ICCCN 2023

作者： Kadhim, Aqeel A. Naif, Jolan R. Salman, Muna M. Hoomod, Haider K. Computer Techniques Engineering Department Imam AlKadhim University College Baghdad Iraq Informatics Institute for Postgraduate Studies Iraqi Commission for Computers and Informatics Baghdad Iraq Information Technology Directorate Ministry of Science and Technology Baghdad Iraq College of Education Computer Science Department Al-Mustansiriya University Baghdad Iraq

ISBN: (纸本)9789819708918

It is necessary to collect data measured in open lands, whether for example for monitoring purposes or for border protection. The process of data transmission from active nodes and its next level to the cluster head (CH), followed by follow-up to arrive at the base station (BS), with safety and acceptability, are the main objectives of wireless sensor networks (WSNs). The key benefits of wireless systems are low-cost system installation and loss-free data transfer. Weather conditions in the spacious area affect wireless data transmission that is done between sensor nodes in free space. This study attempted to ascertain the influence of atmospheric and meteorological conditions on the loss of data when utilizing the wireless data transmission systems in a wireless sensor network. For this reason, the volume of data transfer losses that happen in free space because of three types of weather conditions is the main discussion point. The meteorological criteria that can be considered in this research are temperature, clear weather, dust, and rain as the weather elements that affect the Iraqi climate. The correlation analysis's outcomes show that the amount of precipitation and the size of raindrops have a main effect on the losses of data transmission. From a practical point of view, there is no confirmed statistical evidence of the amount of loss in the volume of transmitted data as a result of the amount of rainfall with the use of different transmission frequencies. In this research, we designed an objective routing protocol called Fuzzy Clustering with Ant Colony System FCACS, which has been utilized as a simulation program using the MATLAB 2018b application. The practical results of the proposed protocol for data transmission in free space and under different weather conditions were examined, and the simulation results were compared with those of two well-known routing protocols, which are DEEC and Z-SEP. In terms of the quantity of data received from the CH or BS a

关键词： Data transfer

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：