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  • Open Access

    ARTICLE

    PARE: Privacy-Preserving Data Reliability Evaluation for Spatial Crowdsourcing in Internet of Things

    Peicong He, Yang Xin*, Yixian Yang

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3067-3084, 2024, DOI:10.32604/cmc.2024.054777 - 15 August 2024

    Abstract The proliferation of intelligent, connected Internet of Things (IoT) devices facilitates data collection. However, task workers may be reluctant to participate in data collection due to privacy concerns, and task requesters may be concerned about the validity of the collected data. Hence, it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing (SC) data collection tasks with IoT. To this end, this paper proposes a privacy-preserving data reliability evaluation for SC in IoT, named PARE. First, we design a data uploading format using blockchain More >

  • Open Access

    ARTICLE

    Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

    Uddagiri Sirisha1,, Parvathaneni Naga Srinivasu2,3,*, Panguluri Padmavathi4, Seongki Kim5,, Aruna Pavate6, Jana Shafi7, Muhammad Fazal Ijaz8,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2301-2330, 2024, DOI:10.32604/cmc.2024.053132 - 15 August 2024

    Abstract Fetal health care is vital in ensuring the health of pregnant women and the fetus. Regular check-ups need to be taken by the mother to determine the status of the fetus’ growth and identify any potential problems. To know the status of the fetus, doctors monitor blood reports, Ultrasounds, cardiotocography (CTG) data, etc. Still, in this research, we have considered CTG data, which provides information on heart rate and uterine contractions during pregnancy. Several researchers have proposed various methods for classifying the status of fetus growth. Manual processing of CTG data is time-consuming and unreliable.… More >

  • Open Access

    ARTICLE

    Sec-Auditor: A Blockchain-Based Data Auditing Solution for Ensuring Integrity and Semantic Correctness

    Guodong Han, Hecheng Li*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2121-2137, 2024, DOI:10.32604/cmc.2024.053077 - 15 August 2024

    Abstract Currently, there is a growing trend among users to store their data in the cloud. However, the cloud is vulnerable to persistent data corruption risks arising from equipment failures and hacker attacks. Additionally, when users perform file operations, the semantic integrity of the data can be compromised. Ensuring both data integrity and semantic correctness has become a critical issue that requires attention. We introduce a pioneering solution called Sec-Auditor, the first of its kind with the ability to verify data integrity and semantic correctness simultaneously, while maintaining a constant communication cost independent of the audited… More >

  • Open Access

    ARTICLE

    Blockchain-Enabled Federated Learning for Privacy-Preserving Non-IID Data Sharing in Industrial Internet

    Qiuyan Wang, Haibing Dong*, Yongfei Huang, Zenglei Liu, Yundong Gou

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1967-1983, 2024, DOI:10.32604/cmc.2024.052775 - 15 August 2024

    Abstract Sharing data while protecting privacy in the industrial Internet is a significant challenge. Traditional machine learning methods require a combination of all data for training; however, this approach can be limited by data availability and privacy concerns. Federated learning (FL) has gained considerable attention because it allows for decentralized training on multiple local datasets. However, the training data collected by data providers are often non-independent and identically distributed (non-IID), resulting in poor FL performance. This paper proposes a privacy-preserving approach for sharing non-IID data in the industrial Internet using an FL approach based on blockchain… More >

  • Open Access

    ARTICLE

    Improving Diversity with Multi-Loss Adversarial Training in Personalized News Recommendation

    Ruijin Xue1,2, Shuang Feng1,2,*, Qi Wang1,2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3107-3122, 2024, DOI:10.32604/cmc.2024.052600 - 15 August 2024

    Abstract Users’ interests are often diverse and multi-grained, with their underlying intents even more so. Effectively capturing users’ interests and uncovering the relationships between diverse interests are key to news recommendation. Meanwhile, diversity is an important metric for evaluating news recommendation algorithms, as users tend to reject excessive homogeneous information in their recommendation lists. However, recommendation models themselves lack diversity awareness, making it challenging to achieve a good balance between the accuracy and diversity of news recommendations. In this paper, we propose a news recommendation algorithm that achieves good performance in both accuracy and diversity. Unlike… More >

  • Open Access

    ARTICLE

    Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

    Fang Hu1, Siyi Qiu2, Xiaolian Yang1, Chaolei Wu1, Miguel Baptista Nunes3, Hui Chen4,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2897-2915, 2024, DOI:10.32604/cmc.2024.052570 - 15 August 2024

    Abstract As the volume of healthcare and medical data increases from diverse sources, real-world scenarios involving data sharing and collaboration have certain challenges, including the risk of privacy leakage, difficulty in data fusion, low reliability of data storage, low effectiveness of data sharing, etc. To guarantee the service quality of data collaboration, this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning, termed FL-HMChain. This system is composed of three layers: Data extraction and storage, data management, and data application. Focusing on healthcare and medical data, a healthcare and… More >

  • Open Access

    ARTICLE

    Dynamic Forecasting of Traffic Event Duration in Istanbul: A Classification Approach with Real-Time Data Integration

    Mesut Ulu1,*, Yusuf Sait Türkan2, Kenan Mengüç3, Ersin Namlı2, Tarık Küçükdeniz2

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2259-2281, 2024, DOI:10.32604/cmc.2024.052323 - 15 August 2024

    Abstract Today, urban traffic, growing populations, and dense transportation networks are contributing to an increase in traffic incidents. These incidents include traffic accidents, vehicle breakdowns, fires, and traffic disputes, resulting in long waiting times, high carbon emissions, and other undesirable situations. It is vital to estimate incident response times quickly and accurately after traffic incidents occur for the success of incident-related planning and response activities. This study presents a model for forecasting the traffic incident duration of traffic events with high precision. The proposed model goes through a 4-stage process using various features to predict the… More >

  • Open Access

    ARTICLE

    Development of a Lightweight Model for Handwritten Dataset Recognition: Bangladeshi City Names in Bangla Script

    Md. Mahbubur Rahman Tusher1, Fahmid Al Farid2,*, Md. Al-Hasan1, Abu Saleh Musa Miah1, Susmita Roy Rinky1, Mehedi Hasan Jim1, Sarina Mansor2, Md. Abdur Rahim3, Hezerul Abdul Karim2,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2633-2656, 2024, DOI:10.32604/cmc.2024.049296 - 15 August 2024

    Abstract The context of recognizing handwritten city names, this research addresses the challenges posed by the manual inscription of Bangladeshi city names in the Bangla script. In today’s technology-driven era, where precise tools for reading handwritten text are essential, this study focuses on leveraging deep learning to understand the intricacies of Bangla handwriting. The existing dearth of dedicated datasets has impeded the progress of Bangla handwritten city name recognition systems, particularly in critical areas such as postal automation and document processing. Notably, no prior research has specifically targeted the unique needs of Bangla handwritten city name… More >

  • Open Access

    ARTICLE

    FADSF: A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

    Yan Sun, Caiyun Liu, Jun Li, Yitong Liu*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2351-2362, 2024, DOI:10.32604/cmc.2024.048903 - 15 August 2024

    Abstract With the development of technology, the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal. The data of ICV (intelligent connected vehicles) is the key to organically maximizing their efficiency. However, in the context of increasingly strict global data security supervision and compliance, numerous problems, including complex types of connected vehicle data, poor data collaboration between the IT (information technology) domain and OT (operation technology) domain, different data format standards, lack of shared trust sources, difficulty in ensuring the quality of shared data, lack of data… More >

  • Open Access

    ARTICLE

    Integrative Analysis of Transcriptome and Phenolic Compounds Profile Provides Insights into the Quality of Soursop (Annona muricata L.) Fruit

    Yolotzin Apatzingán Palomino-Hermosillo1, Ángel Elpidio Díaz-Jasso2, Rosendo Balois-Morales1, Verónica Alhelí Ochoa-Jiménez1,3, Pedro Ulises Bautista-Rosales1, Guillermo Berumen-Varela1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1717-1732, 2024, DOI:10.32604/phyton.2024.052216 - 30 July 2024

    Abstract Soursop (Annona muricata L.) is a tropical fruit highly valued for its unique flavor, nutritional value, and health-promoting properties. The ripening process of soursop involves complex changes in gene expression and metabolite accumulation, which have been studied using various omics technologies. Transcriptome analysis has provided insights into the regulation of key genes involved in ripening, while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits. However, the integration of transcriptome and metabolite compound data has not been extensively explored in soursop. Therefore, in this paper, we present a comprehensive analysis… More >

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