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Advances in Machine Learning and Data Science 1

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丛书名： Advances in Intelligent Systems and computing

1000年

作者： Damodar Reddy Edla Venkatanareshbabu K. Pawan Lingras

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Preparing Software Quality Assurance Professionals: Metamorphic Exploration for Machine Learning

Preparing Software Quality Assurance Professionals: Metamorp...

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2019 IEEE International Conference on engineering, technology and Education, TALE 2019

作者： Yang, Sen Towey, Dave Zhou, Zhi Quan Chen, T.Y. University of Sydney Faculty of Engineering Information Technologies Australia University of Nottingham Ningbo School of Computer Science China University of Wollongong School of Computing and Information Technology Australia Swinburne University of Technology Department of Computer Science and Software Engineering Australia

ISBN: (纸本)9781728126654

Computer science (CS) subjects have been rapidly growing in popularity, and demand for CS education and training has put increasing pressure on teaching resources in higher education (HE) and elsewhere. HE in the People's Republic of China (PRC) has also been developing, with one product of this evolution being Sino-foreign HE institutions (SfHEIs). Much of the popularity growth for CS can be linked to the growth of CS-based technology and innovation, especially in the form of Artificial Intelligence (AI) and Machine Learning (ML). AI/ML-based innovation has been forecast to offer increases in quality of life for consumers. However, AI/ML systems face a challenge for software quality assurance (SQA): They are so-called 'untestable systems' - identifying the correctness of AI/ML system outputs or behaviour may not be feasible. Preparing SQA professionals to be able to ensure AI/ML SQA will require innovative and creative education and training. An SQA approach called metamorphic testing (MT) has a proven track record of alleviating the oracle problem, and has great potential as a testing methodology for AI/ML systems. Metamorphic exploration (ME) is a new addition to the MT literature, and involves developing the user's understanding of the system under study. This paper reports on experiences at an SfHEI of using ME and MT to test an AI/ML system. © 2019 IEEE.

关键词： Machine learning

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Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4027-4041页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Fadwa Alrowais Sunil Kumar Abdelhameed Ibrahim Abdelaziz A.Abdelhamid 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 School of Computer Science University of Petroleum and Energy StudiesDehradun248001India 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

In data mining and machine learning,feature selection is a critical part of the process of selecting the optimal subset of features based on the target *** are 2n potential feature subsets for every n features in a dataset,making it difficult to pick the best set of features using standard ***,in this research,a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm(ASSOA)has been *** using metaheuristics to pick features,it is common for the selection of features to vary across runs,which can lead to *** of this,we used the adaptive squirrel search to balance exploration and exploitation duties more evenly in the optimization *** the selection of the best subset of features,we recommend using the binary ASSOA search strategy we developed *** to the suggested approach,the number of features picked is reduced while maximizing classification accuracy.A ten-feature dataset from the University of California,Irvine(UCI)repository was used to test the proposed method’s performance *** other state-of-the-art approaches,including binary grey wolf optimization(bGWO),binary hybrid grey wolf and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hybrid GWO and genetic algorithm 4028 CMC,2023,vol.74,no.2(bGWO-GA),binary firefly algorithm(bFA),and *** results confirm the superiority and effectiveness of the proposed algorithm for solving the problem of feature selection.

关键词： Metaheuristics adaptive squirrel search algorithm optimization methods binary optimizer

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Low-Cost Sensor-Based Irrigation System for Efficient Water Management in Remote Agricultural Regions

Low-Cost Sensor-Based Irrigation System for Efficient Water ...

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2023 Intelligent computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Ashok, P. James, T. Prabahar Godwin Pathmanaban, J. Ranjith, P. Ragunthar, T. Baranidharan, K. Sri Sai Ram Institute of Technology Department of Computer Science and Engineering Tamilnadu India Sri Sai Ram Institute of Technology Department of Science and Humanities Tamilnadu India Srm Institute of Science and Technology Department of Computing Technologies Tamilnadu India Sri Sai Ram Institute of Technology Department of Master of Business Administration Tamilnadu India

ISBN: (纸本)9798350394580

Irrigation system with lower cost is considered to be increasingly significant, based on rising growth of human population, demand for food and global warming. This investigation attempts to provide a low cost sensor based irrigation system for monitoring and controlling from remote regions and to optimize water use for farming irrigation. A sensor based irrigation system that monitors and controls the supply of water uses sensors and actuators. It is specifically designed to automate the water supply from reservoirs and to crops over irrigation system. System lifecycle and waterfall model has been considered in development factor. The protocol suite, ardunio are integrated to provide the system model. Here, pumping approach has been utilized to provide water supply to soils. This system design offers sensing, power supply, monitoring and controlling factors and internet sources. Experimentation was carried out in MATLAB environment and simulation outcomes demonstrate practical and effectual way of implementing the anticipated system model. This irrigation system is need not only for farmers and also for increasing the economic functionalities. Moreover, this may diminish manual supervision that is needed for water supply by invoking remote monitoring and control system. © 2023 IEEE.

关键词： Irrigation system low cost remote monitoring sensor water supply

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Abnormal Image Classification Using Vision Transformer for Smart Agriculture 8

Abnormal Image Classification Using Vision Transformer for S...

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8th IEEE International Conference on engineering Technologies and Applied Sciences, ICETAS 2023

作者： Hafeez, Talha Shahid, Muhammad Farrukh Khanzada, Tariq J.S. Fast School of Computing FAST-NUCES Karachi Pakistan King Abdulaziz University Faculty of Computing and Information Technology Department of Information System Jeddah21589 Saudi Arabia Mehran Uet Computer Systems Engineering Departments Jamshoro Pakistan

ISBN: (纸本)9798350327090

Smart agriculture is an emerging innovative sector that harnesses technological advancements like sensor monitoring, image processing, soil quality evaluation, and automated water systems, all of which contribute towards enhanced crop yields and superior quality of produce. With the progression towards automated systems in smart agriculture, the need for a robust data infrastructure that assures data integrity is critical. This demands an integrated approach with anomaly detection algorithms and a robust classification technique to ensure an error-free data pipeline. This study employs two distinct datasets to achieve abnormal image classification using a vision transformer (ViT) and a convolutional neural network (CNN). The primary dataset, obtained through direct collection from cotton fields in Karachi and Balochistan, Pakistan, comprises high-resolution agricultural images captured using specialised cameras and Unmanned Aerial Vehicles (UAVs). The secondary dataset was sourced from a publicly available database. The two classification models, ViT and CNN, were applied to both datasets. These supervised models are primarily used to classify images as normal or abnormal. The results of the two classification models were also compared, with the ViT model surpassing the CNN model in performance and achieving the highest accuracy on both datasets. The Vision Transformer model proved to be robust for supervised data, showing remarkable accuracy of 96.00% on the public dataset, 99.18% on both camera based images and 97.56% on UAV images of collected dataset as compared to the CNN model's accuracy that are 82.00% on the public dataset and 98.36% on camera and 95.12% on UAV images of collected dataset. © 2023 IEEE.

关键词： Classification (of information)

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Environment Control using Forecasting Algorithm by Real Time Data Analysis for Automatic Cultivation System 7

Environment Control using Forecasting Algorithm by Real Time...

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7th International Conference on engineering, Applied Sciences and technology, ICEAST 2021

作者： Juleang, Pakorn Mitatha, Somsak Ramkhamhaeng University Faculty of Science Electronics Technology Department Bangkok10240 Thailand King Mongkut's Institute of Technology Ladkrabang Hybrid Computing Research Laboratory Faculty of Engineering Bangkok10520 Thailand

ISBN: (纸本)9781665441223

A new automatic cultivation system was proposed using a forecasting algorithm for environmental control. Information used for the forecast was taken from real time data obtained by a wireless sensor system. The objective was the automation of suitable environmental cultivation methods. The proposed forecasting algorithm used historical data to predict future environmental control according to its goals. A real system was implemented and constructed to test the hypothesis. Results showed that the system had the required features. Environmental controls of the original system were compared with the proposed algorithm according to the created thresholds. The proposed forecasting algorithm controlled humidity in the soil at 98.26%, while the original system recorded do 69.33%, with humidity in the air controlled at 93.87% compared to the original system at 48.96%. This algorithm will be very useful to promote sustainable agriculture. © 2021 IEEE.

关键词： Cultivation

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Design and implementation a SOPC for FSB controller

Design and implementation a SOPC for FSB controller

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2nd International Workshop on Computer Science and engineering, WCSE 2009

作者： Tao, Yaodong Lin, Hu Wang, Zhicheng Qin, Chenggang Department of Computer Science and Technology University of Science and Technology of China Hefei China Shenyang Institute of Computing Technology CAS Shenyang Golding NC Tech. Ltd. Co. Shenyang China National Engineering Research Centre for High-end CNC Shenyang China Shenyang Institute of Computing Technology CAS Shenyang China

ISBN: (纸本)9780769538815

This paper presented Fieldbus SOPC-based FSB (Fast Serial Bus)controller using FPGA technology for CNC application, which used H/S(Hardware/Software) Co-Design method. This controller completed control of AL (application layer), DLL(data link layer) and PL(physical layer). In the controller, CAN-compatible hardware designed by VHDL handled with DLL and PL of FSB, while software run in soft processor implemented FSB AL protocol. The experimental results indicate that the SOPC-based controller is efficient and flexible, and the design cycle and cost of CNC system with FSB is reduced by using this fieldbus controller. © 2009 IEEE.

关键词： Controllers

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Digital Twins in Healthcare: Applications, Challenges, and Future Directions 4

Digital Twins in Healthcare: Applications, Challenges, and F...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Sharma, Neha Panwar, Arvind Sugandh, Urvashi Jain, Vishal Singh Kaswan, Kuldeep Bharati Vidyapeeth's College of Engineering New Delhi India Galgotias University School of Computing Science and Engineering Greater Noida India Sharda University Sharda School of Engineering and Technology Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350364729

The leading industry's transformation, powered by digital twin technology, is the healthcare lifecycle. Digital twins - virtual replicas of people, animals, and objects - represent an increasingly dominant force in the promotion of recently accessible opportunities for personalized cures, cutting end diagnostics, and patient outcomes overall. The current paper provides a comprehensive review of how digital twins are already being used in healthcare, the issues obstructing further progress, and which direction these technologies might develop in the future. They have already been used in various areas of healthcare, from modeling the patient's specific organ to plan for surgery to measuring their vital signs using connected gadgets. Doctors can now predictably modify medical matters thanks to computer stimulations. Of course, the increased usage of digital twins in healthcare also brings particular problems. This paper focuses on the challenges, including privacy, ethical concerns, and a lack of interoperability standards, and addresses the solutions - guaranteeing secured data exchange, acquiring the patient's consent, and developing a suitable regulatory structure to ensure accountable integration of digital twin technologies in healthcare. Finally, the digital twin technologies advancements that use them in the future are considered. AI-based diagnostic tools, improved mental health application, and the incorporation of patient-derived data sources for more extensive health profiles are all possibilities discussed in this paper. At the same time, the role of digital twins in telemedicine, the optimization of treatment programs, and collaboration between healthcare professionals is highlighted. Ultimately, this paper gives a summary of digital twin healthcare. By carefully examining the technology's potential and limitations, we will be able to scale its results afterward. © 2024 IEEE.

关键词： Electronic health record

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Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors

Building Scalable Cyber-Physical-Social Networking Infrastru...

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作者： Lenka, Rakesh Kumar Rath, Amiya Kumar Tan, Zhiyuan Sharma, Suraj Puthal, Deepak Simha, N.V.R. Prasad, Mukesh Raja, Rohit Tripathi, Shankar Sharan Department of Computer Science and Engineering International Institute of Information Technology at Bhubaneswar Bhubaneswar751003 India Department of Computer Science and Engineering Veer Surendra Sai University of Technology Burla768018 India School of Computing Edinburgh Napier University EdinburghEH14 1DJ United Kingdom Faculty of Engineering and IT University of Technology Sydney UltimoNSW2007 Australia CSE Department Sreyas Institute of Engineering and Technology Hyderabad500068 India Department of Computer Science and Engineering Shri Shankaracharya College of Engineering and Technology Bhilai491001 India

Wireless sensors are an important component to develop the Internet of Things (IoT) Sensing infrastructure. There are enormous numbers of sensors connected with each other to form a network (well known as wireless sensor networks) to complete the IoT Infrastructure. These deployed wireless sensors are with limited energy and processing capabilities. The IoT infrastructure becomes a key factor to building cyber-physical-social networking infrastructure, where all these sensing devices transmit data toward the cloud data center. Data routing toward cloud data center using such low power sensor is still a challenging task. In order to prolong the lifetime of the IoT sensing infrastructure and building scalable cyber infrastructure, there is the requirement of sensing optimization and energy efficient data routing. Toward addressing these issues of IoT sensing, this paper proposes a novel rendezvous data routing protocol for low-power sensors. The proposed method divides the sensing area into a number of clusters to lessen the energy consumption with data accumulation and aggregation. As a result, there will be less amount of data stream to the network. Another major reason to select cluster-based data routing is to reduce the control overhead. Finally, the simulation of the proposed method is done in the Castalia simulator to observe the performance. It has been concluded that the proposed method is energy efficient and it prolongs the networks lifetime for scalable IoT infrastructure. © 2013 IEEE.

关键词： Routing protocols

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State Feedback Stabilization of the Linearized Bilayer Saint-Venant Model

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IFAC-PapersOnLine 2016年第8期49卷 130-135页

作者： Diagne, Ababacar Tang, Shuxia Diagne, Mamadou Krstic, Miroslav Division of Scientific Computing Department of Information Technology Uppsala University Box 337 Uppsala75105 Sweden Department of Mechanical & Aerospace Engineering University of California La Jolla San DiegoCA92093-0411 United States Department of Mechanical Engineering University of Michigan G.G. Brown Laboratory 2350 Hayward Ann ArborMI48109 United States

We consider the problem of stabilizing the bilayer Saint-Venant model, which is a coupled system of two rightward and two leftward convecting transport partial differential equations (PDEs). In the stability proofs, we employ a Lyapunov function in which the parameters need to be successively determined. To the best of the authors’ knowledge, this is the first time this kind of Lyapunov function is employed, and this result is the first one on the stabilization of the linearized bilayer Saint-Venant model. Numerical simulations of the bilayer Saint-Venant problem are also provided to verify the result. © 2016

关键词： Stabilization Linearization Lyapunov functions State feedback Back stepping controls Coupled PDEs Saint Venant State feedback stabilization Varying coefficients

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