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RecGuard: An efficient privacy preservation blockchain-based system for online social network users

Blockchain(Research and Applications) 2023年第1期4卷 36-47页

作者： Samuel Akwasi Frimpong Mu Han Edward Kwadwo Boahen Rexford Nii Ayitey Sosu isaac Hanson Otu Larbi-Siaw isaac baffour senkyire Department of Computer Science and Technology Jiangsu University212013ZhenjiangChina Department of Computer Engineering Ghana Communication Technology UniversityGhana Department of Computer Science Ghana Communication Technology UniversityGhana Department of Telecom Engineering Ghana Communication Technology UniversityGhana School of Finance and Economics Jiangsu University 212013ZhenjiangChina

Recommendation systems provide ease and convenience for users to address information overload problems while interacting with online platforms such as social media and ***,it raises several questions about privacy,especially for users who prefer to remain anonymous,especially on online social networks(OSNs).Moreover,due to the commercialization of online users'data,some service providers sell users'data to third parties at the blind side of the users,which leads to trust issues between users and service *** matters call for a system that gives online users much-needed control and autonomy of their *** the advancement of blockchain technology,many research institutions are experimenting with decentralized technologies to resolve the OSN user dilemma of privacy intrusion against third parties and *** resolve these limitations,we propose RecGuard,a privacy preservation blockchain-based network *** developed two smart contracts,RG-SH and RG-ST,to ensure the security and privacy of user *** RG-SH manages user data,whereas the RGST stores data.A graph convolutional network(GCN)was integrated with the blockchain-based system to detect malicious ***,we implemented our framework prototype on a locally simulated *** analysis and experiment results show that the proposed scheme demonstrates the effectiveness and privacy of users in our framework.

关键词： Blockchain Privacy Online social network Recommender system

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Supervised and Semi-supervised Methods for Abdominal Organ Segmentation: A Review

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International Journal of Automation and computing 2021年第6期18卷 887-914页

作者： isaac baffour senkyire Zhe Liu School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang 212013China Computer Science Department Ghana Communication Technology UniversityAccraGhana

Abdominal organ segmentation is the segregation of a single or multiple abdominal organ(s) into semantic image segments of pixels identified with homogeneous features such as color and texture, and intensity. The abdominal organ(s) condition is mostly connected with greater morbidity and mortality. Most patients often have asymptomatic abdominal conditions and symptoms, which are often recognized late;hence the abdomen has been the third most common cause of damage to the human body. That notwithstanding,there may be improved outcomes where the condition of an abdominal organ is detected earlier. Over the years, supervised and semi-supervised machine learning methods have been used to segment abdominal organ(s) in order to detect the organ(s) condition. The supervised methods perform well when the used training data represents the target data, but the methods require large manually annotated data and have adaptation problems. The semi-supervised methods are fast but record poor performance than the supervised if assumptions about the data fail to hold. Current state-of-the-art methods of supervised segmentation are largely based on deep learning techniques due to their good accuracy and success in real world applications. Though it requires a large amount of training data for automatic feature extraction, deep learning can hardly be used. As regards the semi-supervised methods of segmentation, self-training and graph-based techniques have attracted much research attention. Self-training can be used with any classifier but does not have a mechanism to rectify mistakes early. Graph-based techniques thrive on their convexity, scalability, and effectiveness in application but have an out-of-sample problem. In this review paper, a study has been carried out on supervised and semi-supervised methods of performing abdominal organ segmentation. An observation of the current approaches, connection and gaps are identified, and prospective future research opportunities are enu

关键词： Abdominal organ supervised segmentation semi-supervised segmentation evaluation metrics image segmentation machine learning

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A Six-Year Review of Head and Neck Cancers at the Komfo Anokye Teaching Hospital, Kumasi, Ghana

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International Journal of Otolaryngology and Head & Neck Surgery 2014年第5期3卷 271-278页

作者： Rita Larsen-Reindorf Osei Owusu-Afriyie Alexander Oti Acheampong isaac Boakye baffour Awuah Department of ENT Komfo Anokye Teaching Hospital Kumasi Ghana Department of Pathology Komfo Anokye Teaching Hospital Kumasi Ghana Department of Oral and Maxillofacial Unit Komfo Anokye Teaching Hospital Kumasi Ghana Research & Development Unit Komfo Anokye Teaching Hospital Kumasi Ghana Directorate of Oncology Komfo Anokye Teaching Hospital Kumasi Ghana

Background: In Ghana, information on the prevalence and pattern of Head and Neck Cancers (HNCA) is scarce. There are few publications based on specific sub-sites of the head and neck, however, literature on the prevalence and pattern of HNCA in general is lacking. The present study aimed to describe the pattern of HNCA among patients seen at the multidisciplinary HNCA clinic of Komfo Anokye Teaching Hospital. Methods: This is a retrospective review of all consecutive patient records seen at the multidisciplinary clinic from 2004 to 2009. Results: There were 149 males and 103 females giving a male to female ratio of 1.45:1. The age range was 2 - 95 years with a mean of 48.1 years. The commonest type of HNCA in this review is cancers of the oral cavity (29.4%), followed by accessory sinuses (13.9%) and larynx (13.5%). Nasopharyngeal cancer affected young people, with 34.5% of affected patients aged between 10 and 19 years. The commonest histopathological type was squamous cell carcinoma (49.6%). Majority (47.6%) of patients presented at stage IV. Conclusion: The commonest HNCA is oral cancer. Majority of patients with HNCA are presenting late calling for public health education to raise awareness and promote early detection.

关键词： Head and Neck Cancer Oral Cavity Squamous Cell Carcinoma

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