检索结果-内蒙古大学图书馆

2nd IEEE International Conference on Data science and Network Security, ICDSNS 2024

作者： Ferdous, Kazi Hassanul Arman, Md.Shohel Ahmed, Kazi Rifat Tasnim, Nusrat Mahmud, Imran Revathi, P. Daffodil International University Diu Data Science Lab Department of Software Engineering Dhaka Bangladesh Holy Cross College Department of Computer Science Tamilnadu Tiruchirapalli India

ISBN: (纸本)9798350373110

As the importance of sustainable practices in the automobile sector grows, it's critical to anticipate motorcycle prices and offerings. With so many variables to consider when buying a secondhand motorcycle-condition, mileage, brand reputation, model characteristics, etc.-accurate pricing prediction is essential for both customers looking for good values and sellers hoping to maximize profits. This study investigates the effectiveness of four machine learning techniques Decision Tree models, Support Vector Regression (SVR), K-Nearest Neighbors (KNN), and Stochastic Gradient Descent (SGD) Regressions-in predicting motorcycle prices using a dataset obtained from motorcycle merchants. It's noteworthy that these methods are used with a hybrid architecture to improve prediction accuracy. Different approaches are compared and contrasted to find the best fit for the given dataset, and the difficulties and roadblocks that come with them are also discussed. After extensive testing, the decision tree model's effectiveness is shown with an amazing 97% accuracy rate, providing accurate price estimates that are essential for encouraging sustainable habits in the ever-changing Internet of Things environment. With an impressive accuracy rate, this methodology provides precise pricing estimations, which are critical for supporting sustainable practices in the automotive industry. © 2024 IEEE.

关键词： Motorcycles

来源：评论

学校读者我要写书评

暂无评论

SO(3) Equivariant Framework for Spatial Networks

SO(3) Equivariant Framework for Spatial Networks

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Xia, Tian Aykent, Sarp Microsoft CambridgeMA United States Auburn University Computer Science and Software Engineering Department AuburnAL United States

ISBN: (纸本)9798350362480

Representation learning on spatial networks is emerging as a distinct area in machine learning and is attracting much attention in diverse domains. Some applications include molecular graphs for drug discovery and screening, brain networks for neuroscience, social networks for recommender systems, etc. However, most proposed approaches either use only spatial or network data that cannot distinguish certain types of graphs and limit their network expressivity or are tied to specific input data domains and network architectures. To address this gap, we introduce an equivariant message-passing network architecture that simultaneously leverages the spatial and network properties. In addition, we propose to take advantage of the geometric representations and extend the classical scalar features with 3D vectors. To exploit the spatial and network features, we present a Spatial Vector Neuron, which can be easily incorporated into the existing graph neural network architectures and allow the model to scale up by stacking more layers for larger receptive fields. A comprehensive set of experiments on both synthetic and real-world datasets demonstrate the strength of our proposed method and the potential of geometric representation learning for Spatial Networks. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

SE(3) Equivariant Neural Network for 3D Graphs

SE(3) Equivariant Neural Network for 3D Graphs

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Aykent, Sarp Xia, Tian Auburn University Computer Science and Software Engineering Department AuburnAL United States Microsoft CambridgeMA United States

ISBN: (纸本)9798350362480

Three-dimensional (3D) graph representations have gained significant importance in numerous scientific domains, such as molecular dynamics and astrophysics. In these applications, a precise and effective representation of 3D graphs is crucial. Although various neural network architectures have been proposed to encapsulate the intricate relationships inherent to these graphs, many remain sensitive to challenges such as reflection variances observed in molecular structures. In this paper, we present an SE(3) equivariant neural network architecture tailored for 3D graphs. Our approach uniquely integrates equivariance to both rotations and translations, ensuring robustness against these spatial variances. Distinctively, our model leverages an innovative message passing mechanism, endowing it with an intrinsic understanding of reflection variances. This mechanism not only facilitates superior 3D graph representation but also promotes computational efficiency. Unlike many existing methods, our architecture sidesteps the need for computationally demanding higher-order representations in intermediary layers while still achieving competitive or superior performance metrics. Empirical evaluations conducted on synthetic and real-world datasets underscore the superior performance of our approach in comparison to prevalent models in terms of both accuracy and efficiency. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Leveraging Ensemble Learning for Dry Beans Classification

Leveraging Ensemble Learning for Dry Beans Classification

引用

2024 International Conference on engineering and Computing, ICECT 2024

作者： Jahanzaib, Muhammad Zaheer, Qasim Rehman, Attique Ur Javed, Sabeen Ali, Tahir Muhammad Mir, Azka University of Sialkot Department of Software Engineering Sialkot Pakistan GULF University for Sciences and Technology Department of Computer Science Mubarak Al-Abdullah Kuwait

ISBN: (纸本)9798350349719

For dietary and commercial purposes, dry beans are significant. Dry beans offer many advantages, such as energy and protein. It is crucial to the fight against malnutrition and ensuring food security. The most crucial element in the manufacturing of dry beans is the condition of the seed. As the quality of the seed is so important, seed verification is crucial for dry bean farmers and marketplaces. Choosing high-quality seeds is essential to achieving optimal yield. This research uses a variety of machine-learning techniques to classify different varieties of dry beans. For this research work, a dataset from the UCI machine learning repository is used. The outcomes of model evaluation have been compared, and various classifiers have been trained. In the process, the k-fold cross-validation technique is applied with k = 10 as a parameter. This research aims to differentiate between the seven different types of dry beans by using classification algorithms. An accuracy of 82.01%, 93.46%, 94.67%, and 94.64% has been achieved with the k-nearest neighbor, decision tree, naïve Bayes, and random forest classifiers respectively. Also, the voting ensemble classifier has an accuracy of 95.46%. After the experiments, it was observed that the voting ensemble classifier has the highest accuracy. Future research can examine the performance of new algorithms for better results. Additionally, the dataset can be increased to improve the model's accuracy. © 2024 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

A First Look at the Inheritance-Induced Redundant Test Execution 24

A First Look at the Inheritance-Induced Redundant Test Execu...

引用

44th ACM/IEEE International Conference on software engineering, ICSE 2024

作者： Kim, Dong Jae Chen, Tse-Hsun Peter Yang, Jinqiu Lab Concordia University MontrealQC Canada Concordia University Department of Computer Science and Software Engineering MontrealQC Canada

ISBN: (纸本)9798400702174

Inheritance, a fundamental aspect of object-oriented design, has been leveraged to enhance code reuse and facilitate efficient software development. However, alongside its benefits, inheritance can introduce tight coupling and complex relationships between classes, posing challenges for software maintenance. Although there are many studies on inheritance in source code, there is limited study on using inheritance in test code. In this paper, we take the first step by studying inheritance in test code, with a focus on redundant test executions caused by inherited test cases. We empirically study the prevalence of test inheritance and its characteristics. We also propose a hybrid approach that combines static and dynamic analysis to identify and locate inheritance-induced redundant test cases. Our findings reveal that (1) inheritance is widely utilized in the test code, (2) inheritance-induced redundant test executions are prevalent, accounting for 13% of all execution test cases, (3) bypassing these redundancies can help reduce 14% of the test execution time, and finally, (4) our study highlights the need for careful refactoring decisions to minimize redundant test cases and identifies the need for further research on test code quality. © 2024 ACM.

关键词： software testing

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Prediction Model for T20 and Test Match Outcomes Using Machine Learning

A Comprehensive Prediction Model for T20 and Test Match Outc...

引用

2024 International Conference on engineering and Computing, ICECT 2024

作者： Ahsan, Zoha Ghumman, Shahwaiz Rehman, Attique Ur Javaid, Sabeen Ali, Tahir Muhammad Mir, Azka University of Sialkot Department of Software Engineering Sialkot Pakistan Gulf University for Sciences and Technology Department of Computer Science Mubarak Al-Abdullah Kuwait

ISBN: (纸本)9798350349719

Cricket is a popular sport worldwide, played with a bat and balls. This paper used classification and regression to predict the T20 and Test matches results and scores because cricket fans and analysts always want to predict which team will win the match and how much score a team will make. We have used a supervised machine learning technique to predict the score and result for T20 and Test matches. Cricket match prediction dataset comprising of 13 features and 7827 instances utilized for training the model. For the prediction of winning and losing, we have used Naïve Bayes, Gradient Boosted Trees, Logistic Regression, Deep learning, Decision Tree, Random Forest, and Generalized Linear Model. For Score Prediction, we have used Decision Trees, Random Forests, Gradient Boosted Trees, Generalized Linear Models, and Deep Learning. We've shown the most accurate model after evaluating the accuracy percentages of the several classifiers listed above. Our introduced model has gained an accuracy rate of 96.15% using the Gradient Boosted Trees classifier for Match Score Prediction and 71.72% accuracy by using the Generalized Linear Model for match result prediction. The Rapid Miner tool has been used to perform machine learning techniques to train models. This paper discusses the effectiveness and use of machine learning methods to develop highly accurate models for Cricket match prediction dataset comprising of 13 features and 7827 instances utilized for training the model. © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

The Impact of Stuttering Event Representation on Detection Performance 2

The Impact of Stuttering Event Representation on Detection P...

引用

2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Banna, Abedal-Kareem Fang, Hui Shubita, Ahmad F. Arafah, Mohammad Eqteeshat, Amani Abuaisheh, Saif B. University Of Petra Department Of Ai And Data Science Jordan Loughborough University Department Of Computer Science United Kingdom University Of Petra Department Of Software Engineering Jordan University Of Petra Department Of Computer Science Jordan Malaya University Department Of Information System Malaysia

ISBN: (纸本)9798350394962

Stuttering or stammering is a common neurogenic, psychogenic fluency disorder wherein people have uncontrolled blocks on the natural flow of speech. Automatic Stuttering Event Detection (SED) is a widely recognised challenge due to the heterogenic and overlapped nature of stuttering speech. Therefore, this comparative study investigates the impact of stuttering event representation on detection performance. The paper evaluates the performance of SED and shows the impact of employing ASR pre-trained feature extractions on each stuttering event. Moreover, the paper provides different groups of experiments that evaluate the impact of three acoustic features, the Zero Crossing Rate (ZCR), the Spectral Flux Onset Strength Envelope (SFO), and Fundamental Frequency (FF) features, on SED performance. The paper demonstrates that the fusion of spectral and ASR features improves SED performance across all stuttering events by 8%. The F1 score of the Block class increased by approximately 10%, from 15% to 25%, while the word repetition and interjection increased by 8%. In addition, our experiments proved that the fusion of temporal features increased the average F1 score of SED by 2% across all stuttering events. The F1 score of the prolongation and sound repetition classes increased by 6% and 3%, respectively. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Analysis of Research Trends in Retransmission Techniques in Data Communications 15

Analysis of Research Trends in Retransmission Techniques in ...

引用

15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Han, Deajin Na, Woongsoo Kongju National University Department of Computer Science and Engineering Cheonan Korea Republic of Kongju National University Department of Software Cheonan Korea Republic of

ISBN: (纸本)9798350364637

In data communications, data retransmission mechanisms are essential to ensure reliable data transmission. In this paper, we analyze various data retransmission algorithms and recent research trends. Traditional algorithms such as ACK and timeout-based retransmission, NACK-based retransmission, and selective repetition are reviewed, and modern retransmission techniques utilizing machine learning and network coding are discussed. These techniques contribute to increasing adaptability to the network environment and maximizing the efficiency of data transmission. This work highlights the importance of retransmission mechanisms in ensuring the reliability of data communication and provides directions for future research. © 2024 IEEE.

关键词： Data assimilation

来源：评论

学校读者我要写书评

暂无评论

A Process Oriented Integration Model for Smart Health Services

引用

Intelligent Automation & Soft Computing 2023年第2期35卷 1369-1386页

作者： Farzana Kausar Gondal Syed Khuram Shahzad Muhammad Arfan Jaffar Muhammad Waseem Iqbal Department of Computer Science Superior UniversityLahore54600Pakistan Department of Informatics and Systems University of Management and TechnologyLahore54000Pakistan Faculty of Computer Science&IT Superior UniversityLahore54600Pakistan Department of Software Engineering Superior UniversityLahore54600Pakistan

Cities are facing challenges of high rise in population number and con-sequently need to be equipped with latest smart services to provide luxuries of life to its *** integrated solutions are also a need to deal with the social and environmental challenges,caused by increasing ***,the development of smart services’integrated network,within a city,is facing the bar-riers including;less efﬁcient collection and sharing of data,along with inadequate collaboration of software and *** to resolve these issues,this paper recommended a solution for a synchronous functionality in the smart services’integration process through modeling *** this integration modeling solution,atﬁrst,the service participants,processes and tasks of smart services are identiﬁed and then standard illustrations are developed for the better understand-ing of the integrated service group *** process modeling and notation(BPMN)language based models are developed and discussed for a devised case study,to test and experiment i.e.,for remote healthcare from a smart *** research is concluded with the integration process model application for the required data sharing among different service *** outcomes of the modeling are better understanding and attaining maximum automation that can be referenced and replicated.

关键词： Process modeling business process business process integration business process modeling and notation

来源：评论

学校读者我要写书评

暂无评论

Modeling belief-desire-intention reasoning agents for situation-aware formalisms

Modeling belief-desire-intention reasoning agents for situat...

引用

作者： Mahfooz Ul Haque, Hafiz Saleem, Kiran Salman Khan, Ahmad Department of Software Engineering University of Lahore Lahore Pakistan Department of Computer Science University of Lahore Lahore Pakistan

A natural disaster is an inevitable situation that can occur at any time and anywhere along with varied forms such as earthquakes, floods, hurricane, wildfire, and so forth, and different level of occurrences has been recorded from mild to an intense level. Timely disaster response plays an important role in reducing its deteriorate after-effects and can save countless lives. Over the years, people have been developing guidelines and processes to cope up with such kinds of hazardous situations. In recent years, with the advent of the pervasive computing paradigm, situation-awareness has been considered to be the most fascinating approach for situation assessment and provides decision support accordingly. Situation-aware systems observe/perceive dynamic changes in the environment, understand/comprehend the situation, and perform actions according to the environment. Although state-of-the-art formalisms have been developed to handle such kinds of hazardous situations intelligently and rescue the victims. However, belief-desire-intention (BDI) reasoning mechanism with the incorporation of situation-awareness is still the thirsty area of research to manage hazardous situations. In this article, we propose a temporal epistemic situation-aware formalism for BDI reasoning agents to model the context-aware decision support system. To demonstrate the work of the proposed formalism, we develop a case study based on a disaster situation, in which BDI agents are modeled and simulated to present the results in terms of agents' reasoning processes. We demonstrate the scalability in temporal aspects of the system using different levels of disasters to monitor the hazardous situations and evaluate the overall behavior of the system. © 2021 John Wiley & Sons Ltd.

关键词： Multi agent systems

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：