检索结果-内蒙古大学图书馆

2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Shoukat, Maria Ahmad, Khubaib Said, Naina Ahmad, Nasir Hasanuzzaman, Mohammed Ahmad, Kashif Department of Computer Systems Engineering University of Engineering and Technology Peshawar Pakistan Department of Computer Science Munster Technological University Cork Ireland

The recent advancement in Multimedia Analytical, computer Vision (CV), and Artificial Intelligence (AI) algorithms resulted in several interesting tools allowing an automatic analysis and retrieval of multimedia content of users’ interests. However, retrieving the content of interest generally involves analysis and extraction of semantic features, such as emotions and interestingness-level. The extraction of such meaningful information is a complex task and generally, the performance of individual algorithms is very low. One way to enhance the performance of the individual algorithms is to combine the predictive capabilities of multiple algorithms using fusion schemes. This allows the individual algorithms to complement each other, leading to improved performance. This paper proposes several fusion methods for the media interestingness score prediction task introduced in CLEF Fusion 2022. The proposed methods include both a naive fusion scheme, where all the inducers are treated equally and a merit-based fusion scheme where multiple weight optimization methods are employed to assign weights to the individual inducers. In total, we used six optimization methods including a Particle Swarm Optimization (PSO), a Genetic Algorithm (GA), Nelder-Mead, Trust Region Constrained (TRC), and Limited-memory Broyden–Fletcher–Goldfarb–Shanno Algorithm (LBFGSA), and Truncated Newton Algorithm (TNA). Overall better results are obtained with PSO and TNA achieving 0.109 mean average precision @10. The task is complex and generally, scores are low. We believe the presented analysis will provide a baseline for future research in the domain. © 2022 Copyright for this paper by its authors.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Random suppression of ECG artifacts using a NLSRLMMN-based cascaded noise canceller 58

Random suppression of ECG artifacts using a NLSRLMMN-based c...

引用

58th Asilomar Conference on Signals, systems and computers, ACSSC 2024

作者： Faiz, Mohammed Mujahid Ulla Zerguine, Azzedine Kale, Izzet Presidency University Department of Electrical and Computer Engineering Karnataka Bengaluru560064 India Interdisciplinary Research Center for Communication Systems and Sensing Kfupm Electrical Engineering Department Dhahran31261 Saudi Arabia Department of Computer Science and Engineering LondonW1W 6UW United Kingdom

ISBN: (纸本)9798350354058

Normally, the electrocardiogram (ECG) signal artifacts are removed in a particular sequence starting with baseline wander removal at the beginning. In this work, a methodology has been proposed using a novel algorithm called the Normalized Leaky Sign Regressor Least Mean Mixed Norm (NLSRLMMN) algorithm to remove multiple ECG artifacts such as baseline wander, motion artifacts, muscle artifacts, and power line interference randomly without following a particular sequence. Through rigorous simulations we have shown that if we remove multiple ECG artifacts randomly using our proposed approach then an improvement in signal to noise ratio and mean square error is observed as opposed to a conventional method that employs the Least Mean Square (LMS) algorithm in all the cascaded adaptive noise canceller stages. © 2024 IEEE.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Functional ETL Testing Methodologies for Real-World Data 24

Comprehensive Functional ETL Testing Methodologies for Real-...

引用

24th IEEE International Conference on Software Quality, Reliability and Security Companion, QRS-C 2024

作者： Homayouni, Hajar Pourebadi, Maryam Mary Nguyen, Steven T. Hashemi, Mohammad Shirazi, Hossein Department of Computer Sciencc San Diego State University United States University of California Department of Computer Science San Diego United States Hamedan University of Technology Department of Computer Engineering Iran Management Information Systems San Diego State University United States

ISBN: (纸本)9798350365658

In today's data-driven enterprises, data warehouses are crucial for aggregating diverse datasets for analysis and research. The ETL (Extract, Transform, Load) process is central to this, involving data extraction, integration, cleansing, and loading into the warehouse. Challenges in ETL can cause inaccuracies, diminishing the value of high-quality source data. Robust ETL testing methodologies are essential to ensure correct implementation and efficient execution. This paper surveys existing functional ETL testing approaches, categorizing them into data quality and balancing tests. Data quality tests identify issues like missing values and outliers in the target data, while balancing tests verify data consistency between source and target. The research highlights unresolved challenges in completeness and scalability, proposes future research directions, and includes an empirical study of ETL testing on the Our World in Data warehouse, identifying data disparities and abnormalities. © 2024 IEEE.

关键词： Data quality

来源：评论

学校读者我要写书评

暂无评论

Artificial Butterfly Optimization based Cluster Head Selection with Energy Efficient Data Aggregation model for Heterogeneous WSN Environment 7

Artificial Butterfly Optimization based Cluster Head Selecti...

引用

7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Venkatasubramanian, S. Vijay, R. HariPrasath, S. Department of Computer Science and Business Systems Saranathan College of Engineering Trichy India Department of Electrical and Electronics Engineering Saranathan College of Engineering Trichy India Department of Electronics and Communication Engineering Saranathan College of Engineering Trichy India

ISBN: (纸本)9781665464086

The WSN is a new and urgent technology with many potential uses, including but not limited to health security, environmental monitoring, etc. Due to lower battery capacity, WSN has a restricted-energy resource. In order to solve the issue of unequal energy consumption among nodes, it is necessary to choose a sensor node from a cluster with more than enough power to make up for the weaker nodes. This paper develops the idea of heterogeneous WSN (H-WSN), which provides supplementary energy to the heterogeneity network. One method that has shown promise in overcoming this difficulty is the clustering technique, which optimizes energy consumption and extends the useful life of a sensor network. Even if the existing approaches function well, the computational complexity may rise due to the usage of a single mobile sink in their studies. As an alternative to communication among each CH and sink through a separate hop, the network uses Multiple Mobile Sinks (MMSs). The combination of the data collection and aggregation mechanism (DCA) and artificial butterfly optimization (ABO) based on CH selection allows for energy-efficient data transfer using MMSs in H-WSN. The CH assortment uses the distance parameter, remaining energy, and regular energy for the suggested energy efficiency model. The NS2 platform hosts the final product of the projected H-WSN. The suggested ABO-CH-DCA approach is superior to the baseline protocols in simulations on various measures, including throughput, network lifespan, remaining energy, dead nodes, and live nodes. © 2023 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

引用

computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

来源：评论

学校读者我要写书评

暂无评论

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Kim, Jung Uk Man Ro, Yong Kaist Image and Video Systems Lab School of Electrical Engineering Korea Republic of Kyung Hee University Department of Computer Science and Engineering Korea Republic of

ISBN: (纸本)9781728163277

Although multispectral pedestrian detection studies have shown remarkable detection performances, they are still vulnerable to adversarial attacks. We see the similarity relations between object candidates were not maintained because of the adversarial attacks, resulting in performance degradation. In this paper, we introduce a new method that can preserve the similarity relation between candidates against adversarial attacks using multispectral knowledge. First, we propose Similarity Relation Generation (SRG) module to generate the optimal similarity relation between clean candidates by referring to the two modalities (color and thermal). Second, we propose Adversarial Similarity Relation Preserving (ASRP) module to guide the similarity relation between adversarial candidates to be similar to that of the clean candidates. By maintaining the relationship between candidates, our multispectral detector can distinguish between pedestrian/background classes even in adversarial attacks. Comprehensive experimental results show that our method conspicuously improves the adversarial robustness. © 2023 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

AggFollower: Aggressiveness Informed Car-Following Modeling

IEEE Transactions on Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Chen, Xianda Yuan, Xinyi Zhu, Meixin Zheng, Xinhu Shen, Shaojie Wang, Xuesong Wang, Yinhai Wang, Fei-Yue Guangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong SAR China School of Transportation Engineering Tongji University Shanghai China Department of Civil and Environmental Engineering University of Washington Seattle WA USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style through pre-defined patterns and failed to encode driving style into data-driven car-following models. To address these limitations, we propose the Aggressiveness Informed Car-Following (AICF) modeling approach, which embeds driving style as a dynamic input feature in data-driven car-following models. In detail, We design driving aggressiveness tokens using four physical quantities (jerk, acceleration, relative speed, and relative spacing) to capture the heterogeneity of driving aggressiveness. These tokens were then embedded into a physics-informed Long Short-Term Memory (LSTM) based car-following model for trajectory prediction. To evaluate the effectiveness of our approach, we conducted extensive experiments based on 12,540 car-following events extracted from the HighD dataset and 24,093 events from the Lyft dataset. Compared to models devoid of considerations for driving aggressiveness levels, AICF exhibits superior efficacy in mitigating the Mean Square Error (MSE) of spacing and collision rate. To the best of our knowledge, this is the first work to directly incorporate real-time driving aggressiveness tokens as input features into data-driven car-following models, enabling a more comprehensive understanding of aggressiveness in car-following behavior. IEEE

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Communication Protocols for IoT Devices 9

Energy-Efficient Communication Protocols for IoT Devices

引用

9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Rahamathunnisa, U. Vivekanand, Chettiyar Vani Chithras, T. Sreedevi, E. Kiran, Venneti Rajendiran, M. School of Computer Science Engineering And Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Rmk College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Thiruvallur India Veltech Rangarajan Dr.Sagunthala R&d Institute of Science And Technology Department of Electrical And Electronics Engineering Chennai Tamil Nadu Avadi600062 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram India Andhra Pradesh Surampalem India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350365092

The development and optimisation of energy-efficient communication protocols that are specifically adapted for Internet of Things (IoT) devices is the focus of this research. The proliferation of interoperable bias has given rise to the converse girding energy consumption, which has come a consummate concern in the contemporary period. The primary end of this bid is to probe innovative approaches and protocols with the capacity to reduce the energy consumption of Internet of Effects(IoT) connections. As a result, the bias will retain the capability to attain an extended functional lifetime while coincidently producing a lowered environmental footmark. The presented protocols aim to achieve a result that balances the utilisation of energy coffers with the conservation of dependable communication. A thorough examination of the presently employed protocols, coupled with the perpetration of sophisticated optimisation ways, will be the styles employed to achieve this thing. Theprovides a significant donation to the development and prosecution of communication protocols that effectively address the unique energy constraints encountered by Internet of effects(10T)- connected ecosystems. This contributes to the enhancement of effectiveness and sustainability in the world of networked bias, which is expanding at an accelerated rate. © 2024 IEEE.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm

引用

computers, Materials & Continua 2022年第6期71卷 4719-4736页

作者： Ayman Altameem Sandeep Kumar Ramesh Chandra Poonia Abdul Khader Jilani Saudagar Department of Computer Science College of Applied StudiesKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Department of Computer Science CHRIST(Deemed to be University)Bangalore560029India Information Systems Department Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Since the beginning of time,humans have relied on plants for food,energy,and *** are recognized by leaf,flower,or fruit and linked to their suitable *** methods are used to extract and select traits that are helpful in identifying a *** plant leaf image categorization,each plant is assigned a label according to its *** purpose of classifying plant leaf images is to enable farmers to recognize plants,leading to the management of plants in several *** study aims to present a modified whale optimization algorithm and categorizes plant leaf images into *** modified algorithm works on different sets of plant *** proposed algorithm examines several benchmark functions with adequate *** ten plant leaf images,this classification method was *** proposed model calculates precision,recall,F-measurement,and accuracy for ten different plant leaf image datasets and compares these parameters with other existing *** on experimental data,it is observed that the accuracy of the proposed method outperforms the accuracy of different algorithms under consideration and improves accuracy by 5%.

关键词： Bag-of-features feature optimization plant leaf classification swarm intelligence nature-inspired algorithm

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Graph Construction of Power Flow Graphs for Electric Power Transmission Networks 23

Data-Driven Graph Construction of Power Flow Graphs for Elec...

引用

23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Poole, Benjamin Ratnakumar, Rajan Madurasinghe, Dulip Tharaka Kummerle, Christian Venayagamoorthy, Ganesh Kumar Lee, Minwoo University of North Carolina Department of Computer Science Charlotte United States University of Pretoria Department of Electrical Electronic and Computer Engineering South Africa Clemson University Real-Time Power and Intelligent Systems Laboratory United States

ISBN: (纸本)9798350374889

A comprehensive understanding of the topology of the electric power transmission network (EPTN) is essential for reliable and robust control of power systems. While existing research primarily relies on domain-specific methods, it lacks data-driven approaches that have proven effective in modeling the topology of complex systems. To address this gap, this paper explores the potential of data-driven methods for more accurate and adaptive solutions to uncover the true underlying topology of EPTNs. First, this paper examines Gaussian Graphical Models (GGM) to create an EPTN network graph (i.e., undirected simple graph). Second, to further refine and validate this estimated network graph, a physics-based, domain-specific refinement algorithm is proposed to prune false edges and construct the corresponding electric power flow network graph (i.e., directed multi-graph). The proposed method is tested using a synchrophasor dataset collected from a two-area, four-machine power system simulated on the real-time digital simulator (RTDS) platform. Experimental results show both the network and flow graphs can be reconstructed using various operating conditions and topologies with limited failure cases. © 2024 IEEE.

关键词： Undirected graphs

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：