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2024 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2024

作者： Cheng, Wei-Min Chen, Yu-Jen Chen, Tai-Chi Zhuang, Xiang-Yu Chang, Che-Wei Chien, Wei-Ching Wu, Yu-Hsang Chen, Robert Deptment of Information and Communication Engineering Chaoyang University of Technology Taichung Taiwan Deptment of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan Taiwan Tano Secure Inc Taipei Taiwan

ISBN: (纸本)9798350389210

As the saying goes: "Food is the first priority for the people." Agriculture has been a national priority since ancient times. In recent years, due to the severe impacts of extreme climate and the decline in the agricultural workforce in rural areas, many agricultural challenges have become increasingly urgent. To address these challenges, governments worldwide, including ours, have placed great importance on agricultural issues. One of the key strategies to combat the effects of extreme climate on agriculture is the introduction of greenhouses. In addition to traditional large-scale greenhouses, we implemented a mini-greenhouse based on standardized precision planting, making planting accessible to general users and agriculture to every corner. In our implementation, we use the Raspberry Pi board to automate the control mechanism of the mini-greenhouse. Users can customize the planting environment for different crops by accessing a web page where they can set parameters such as lighting, exhaust fan temperature, and water supply. The mini-greenhouse enables automated and precise planting by using sensors to monitor conditions such as light levels, atmospheric temperature and humidity, as well as soil temperature and moisture. To ensure reliability and future scalability, all sensors adhere to industrial standards and are based on the RS485 Modbus protocol. With this simple mini-greenhouse, built on the principles of precision agriculture, we aim to bring agriculture into everyday households. © 2024 IEEE.

关键词： Kyoto Protocol

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A Decentralized Secure Blockchain-based Privacy-Preserving Healthcare Clouds and Applications 3

A Decentralized Secure Blockchain-based Privacy-Preserving H...

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3rd International Conference on Electrical, computer and Communication Engineering, ECCE 2023

作者： Hussen Wadud, Md. Anwar Rahman, Anichur Islam, Md. Jahidul Amir-Ul-Haque Bhuiyan, T.M. Hossain, Md. Jobaer Hossen, Rakib Constituent Institute of the University of Dhaka Green University of Bangladesh Bangladesh University of Business & Technology Bangabandhu Sheikh Mujibur Rahman Digital University Deptment of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350345360

In recent times, Blockchain (BC) technology has been one of the fastest-growing technologies poised to perform a significant role in the near future. In the age of Cloud Computing (CC) solutions, the Internet of Things (IoT), and big data analytics, BC guarantees data safety, transaction security, and self-regulation development. CC solutions initiated its role in the health industry due to its flexibility and efficient energy consumption paradigm. Nevertheless, CC operations have an issue with preserving confidential data and sharing patients' critical medical data with other healthcare facilities. BC provides solutions in regard to cloud protection and privacy issues of such decentralization features coupled with information protection and privacy, while the cloud contributes towards the resolution of BC's measurability and efficiency difficulties, thereby introducing the idea of an innovative BC-Cloud integration to track and preserve the electronic health records of patients in a reliable manner. In this paper, we present a BC-cloud combination for the electronic healthcare service to provide healthcare officials with the impulses following the rise of this most delinquent model, propose an arrangement of surviving structures, and their applicability for more reliable medical healthcare services. We then evaluate the improvement stages and co-operations and focus on the analysis difficulties for the combined BC-cloud structure, potential solutions, and prospective analysis objectives. This paper's outcome will benefit the health service enterprise to create and improve data administration systems to address patient concerns reliably. © 2023 IEEE.

关键词： Access control

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Review of Machine Learning Techniques for Class Imbalance Medical Data Set 2

Review of Machine Learning Techniques for Class Imbalance Me...

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2nd International Conference on Multidisciplinary Engineering and Applied science, ICMEAS 2023

作者： Amshi, Ahmad Hauwa Usman, Asmau Prasad, Rajesh Salihu, Ibrahim Anka Dadile, Abubakar Muhammad Federal University Deptment of Computer Science Gashua Nigeria Abdu Gusau Polytechnic Department of Compter Science Talata Mafara Nigeria African University of Science and Technology Department of Computer Science Abuja Nigeria Nile University of Nigeria Department of Software Engineering Abuja Nigeria Umar Sulaiman College of Education Department of Computer Science Gashua Nigeria

ISBN: (纸本)9798350358834

Data imbalance threatens a medical dataset where the dominant class is typically viewed as unfavorable. In contrast, the minority class is t supposed to be the positive one, affecting the performance of the machine learning prediction. This aims to examine how resampling strategies in Machine Learning (ML) have recently been used in medical data sets. Many researchers used the preprocessing stage's data-level approach to resample the imbalanced medical data. Thirty-two sources were reviewed in which data level techniques of balancing the imbalanced data were applied to medical datasets spanning 2015 to 2022, with oversampling methods outperforming the under-sampling methods. © 2023 IEEE.

关键词： Machine learning

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Implementation of Mini-Greenhouse Based on Precision Agriculture

Implementation of Mini-Greenhouse Based on Precision Agricul...

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Wei-Min Cheng Yu-Jen Chen Tai-Chi Chen Xiang-Yu Zhuang Che-Wei Chang Wei-Ching Chien Yu-Hsang Wu Robert Chen Deptment of Information and Communication Engineering Chaoyang University of Technology Taichung Taiwan Deptment of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan Taiwan Tano Secure Inc. Taipei Taiwan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

As the saying goes: “Food is the first priority for the people.” Agriculture has been a national priority since ancient times. In recent years, due to the severe impacts of extreme climate and the decline in the agricultural workforce in rural areas, many agricultural challenges have become increasingly urgent. To address these challenges, governments worldwide, including ours, have placed great importance on agricultural issues. One of the key strategies to combat the effects of extreme climate on agriculture is the introduction of greenhouses. In addition to traditional large-scale greenhouses, we implemented a mini-greenhouse based on standardized precision planting, making planting accessible to general users and agriculture to every corner. In our implementation, we use the Raspberry Pi board to automate the control mechanism of the mini-greenhouse. Users can customize the planting environment for different crops by accessing a web page where they can set parameters such as lighting, exhaust fan temperature, and water supply. The mini-greenhouse enables automated and precise planting by using sensors to monitor conditions such as light levels, atmospheric temperature and humidity, as well as soil temperature and moisture. To ensure reliability and future scalability, all sensors adhere to industrial standards and are based on the RS485 Modbus protocol. With this simple mini-greenhouse, built on the principles of precision agriculture, we aim to bring agriculture into everyday households.

关键词： Temperature sensors Temperature measurement Smart agriculture Precision agriculture Clouds Crops Greenhouses Soil Monitoring Intelligent sensors

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Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure

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computers, Materials & Continua 2023年第3期74卷 5267-5281页

作者： Muhammad Javaid Iqbal Muhammad Waseem Iqbal Muhammad Anwar Muhammad Murad Khan Abd Jabar Nazimi Mohammad Nazir Ahmad Department of Information Technology The Superior UniversityLahorePakistan Department of Software Engineering The Superior UniversityLahorePakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Department of Computer Science Government College UniversityFaisalabadPakistan Deptment of Oral and Maxillofacial Surgery Faculty of DentistryUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia

The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their *** brain tumour masses occur due to malignant *** tissues must die so that new tissues are allowed to be born and take their *** segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance *** finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and *** could not work for large volume images simultaneously,and many errors occurred due to overwhelming image *** main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning *** research study proposed an automatic model for tumor segmentation in MRI *** proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics technology Initiative(NIFTI)volumes into the 3D NumPy *** the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated *** the third step,the proposed model uses state-of-the-art Medical Image Computing and computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour *** of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and *** proposed model is evaluated and gets the Dice Coefficient(DSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively.

关键词： Brain tumour segmentation magnetic resonance images modalities dice coefficient low-grade glioma U-Net

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Quality Enhancement for Uninvited Content of Social Media Using Support Vector Machine and Alexnet

Quality Enhancement for Uninvited Content of Social Media Us...

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2023 International Conference on Data science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Saravanan, M.S. Suresh, Devanolla Sudha, I. Nandhini, T.J. Sivashankar, S. Kalyani, K. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai India Madanapalle Institute of Technology & Science Department of Computer Science & Technology Madanapalle India Institute of Cse Saveetha School of Engineering Saveetha Institute of Medical and Technical Science-SIMATS Tamilnadu Chennai India Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Computer Science Engineering Tamilnadu Chennai India Deptment of Computer Science Tamil Nadu Thanjavur India

ISBN: (纸本)9798350348910

The objective of the work is to identify the uninvited content like Spam and Ham data in Reddit using Support Vector Machine over AlexNet. To acquire the accuracy, an innovative SVM Classifier function was used. The assortment of information and its pre-processing are examined. For the review, almost 20 samples were taken and 10 for each group to assess, look at and figure out the exactness of proposed calculations. For accuracy expectation, a G power of 80 % and the parameters Confidence Interval of 0.95, alpha 0.05 and beta 0.2 is utilized. From observation, the support vector machine with accuracy of 95.72 % is inferred to have higher accuracy in identifying the unsolicited content and avoid data theft, and its threshold is higher than the AlexNet method with an accuracy of 93.47 %, and with a statistical significance of p is 0.003 (p © 2023 IEEE.

关键词： Support vector machines

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Review of Machine Learning Techniques For Class Imbalance Medical Data Set

Review of Machine Learning Techniques For Class Imbalance Me...

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Multidisciplinary Engineering and Applied science (ICMEAS), International Conference on

作者： Ahmad Hauwa Amshi Asmau Usman Rajesh Prasad Ibrahim Anka Salihu Abubakar Muhammad Dadile Deptment of Computer Science Federal University Gashua Nigeria Department of Compter Science Abdu Gusau Polytechnic Talata Mafara Nigeria Department of Computer Science African University of Science and Technology Abuja Nigeria Department of Software Engineering Nile University of Nigeria Abuja Nigeria Department of Computer Science Umar Sulaiman College of Education Gashua Nigeria

ISBN: (数字)9798350358834

ISBN: (纸本)9798350358841

关键词： Machine learning

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Human-imperceptible, Machine-recognizable Images

arXiv

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arXiv 2023年

作者： Hao, Fusheng He, Fengxiang Wang, Yikai Wu, Fuxiang Zhang, Jing Cheng, Jun Tao, Dacheng Shenzhen Institute of Advanced Technology CAS China The Chinese University of Hong Kong Hong Kong AIAI School of Informatics University of Edinburgh United Kingdom JD Explore Academy *** Inc China Deptment of Computer Science and Technology Tsinghua University China School of Computer Science The University of Sydney Australia

Massive human-related data is collected to train neural networks for computer vision tasks. A major conflict is exposed relating to software engineers between better developing AI systems and distancing from the sensitive training data. To reconcile this conflict, this paper proposes an efficient privacy-preserving learning paradigm, where images are first encrypted to become "human-imperceptible, machine-recognizable" via one of the two encryption strategies: (1) random shuffling to a set of equally-sized patches and (2) mixing-up sub-patches of the images. Then, minimal adaptations are made to vision transformer to enable it to learn on the encrypted images for vision tasks, including image classification and object detection. Extensive experiments on ImageNet and COCO show that the proposed paradigm achieves comparable accuracy with the competitive methods. Decrypting the encrypted images requires solving an NP-hard jigsaw puzzle or an ill-posed inverse problem, which is empirically shown intractable to be recovered by various attackers, including the powerful vision transformer-based attacker. We thus show that the proposed paradigm can ensure the encrypted images have become human-imperceptible while preserving machine-recognizable information. The code is available at https://***/FushengHao/PrivacyPreservingML. © 2023, CC BY-NC-ND.

关键词： Object detection

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A Decentralized Secure Blockchain-based Privacy-Preserving Healthcare Clouds and Applications

A Decentralized Secure Blockchain-based Privacy-Preserving H...

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International Conference on Electrical, computer and Communication Engineering (ECCE)

作者： Md. Anwar Hussen Wadud Anichur Rahman Md. Jahidul Islam T. M. Amir-Ul-Haque Bhuiyan Md. Jobaer Hossain Rakib Hossen Deptment of Computer Science and Engineering Bangladesh University of Business & Technology Bangabandhu Sheikh Mujibur Rahman Digital University Mawlana Bhashani Science and Technology University National Institute of Textile Engineering and Research (NITER) constituent institute of the University of Dhaka Green University of Bangladesh

关键词： Cloud computing Privacy computer architecture Oral communication Safety Reliability Internet of Things

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Priority-based Traceability in Crude Oil Refined Products Supply Chain Through Blockchain

Priority-based Traceability in Crude Oil Refined Products Su...

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Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Md. Jahidul Islam Md Naimul Pathan Anichur Rahman Shamima Islam Abida Sultana Saurav Chandra Das Deptment of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh National Institute of Textile Engineering and Research (NITER) Constituent Institute of the University of Dhaka Bangladesh Bangladesh University of Business & Technology Bangabandhu Sheikh Mujibur Rahman Digital University Bangladesh

ISBN: (数字)9798331531973

ISBN: (纸本)9798331531980

The oil industry lacks traceability of crude oil and its refined products as they still maintain their traditional systems without any digital ledger. The absence of proper tracking mechanisms also results in fraudulent activities where people store large amounts of oil, causing artificial crises and price hikes. The industry needs to adopt modern technology to increase transparency and prevent fraudulent activities. To tackle the issues faced by the oil industry, the authors propose a distributed and decentralized Blockchain-based architecture. Our proposed system provides a solution to track every transaction, leaving no room for changes to the ledger and ensuring transparency. The smart ledger system records all transaction history immutably, preventing fraudulent activities like cyber-attacks. The system also has a history tracker, increasing transparency and traceability from the movement of mineral crude oil to the refinery system and distributing the oil as per requests. Moreover, this approach ensures that the system maintains a full record of who is taking the oil, so it is difficult to create an artificial crisis and hike the prices. Furthermore, the system has proposed an algorithm for refining and distribution which reduces to the cost of tracing and gas consumption, providing an efficient and cost-effective approach to traceability and transparency in the oil industry. Finally. the proposed system is evaluated based on parameters like gas consumption, gas cost, and transaction cost. The analysis showed that the system had lower consumption and transaction cost, making it an efficient alternative to traditional systems.

关键词： Costs Tracking Oils Supply chains Smart contracts Blockchains Minerals Petroleum industry History Security

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