Browsing HVL Open by Author "Belhadi, Asma"

Now showing items 1-19 of 19

    • A Survey on Urban Traffic Anomalies Detection Algorithms 

      Djenouri, Youcef; Belhadi, Asma; Lin, Chun Wei; Djenouri, Djamel; Cano, Alberto (Journal article; Peer reviewed, 2019)
      This paper reviews the use of outlier detection approaches in urban traffic analysis. We divide existing solutions into two main categories: flow outlier detection and trajectory outlier detection. The first category groups ...

    • Adapted k-Nearest Neighbors for Detecting Anomalies on Spatio-Temporal Traffic Flow 

      Djenouri, Youcef; Belhadi, Asma; Lin, Chun Wei; Djenouri, Djamel; Cano, Alberto (Journal article; Peer reviewed, 2019)
      Outlier detection is an extensive research area, which has been intensively studied in several domains such as biological sciences, medical diagnosis, surveillance, and traffic anomaly detection. This paper explores advances ...

    • Cluster-based information retrieval using pattern mining 

      Djenouri, Youcef; Belhadi, Asma; Djenouri, Djamel; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      This paper addresses the problem of responding to user queries by fetching the most relevant object from a clustered set of objects. It addresses the common drawbacks of cluster-based approaches and targets fast, high-quality ...

    • A data-driven approach for twitter hashtag recommendation 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Cano, Alberto (Journal article; Peer reviewed, 2020)
      This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ...

    • Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Djenouri, Djamel; Lin, Jerry Chun-Wei; Fortino, Giancarlo (Peer reviewed; Journal article, 2021)
      This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can ...

    • Emergent Deep Learning for Anomaly Detection in Internet of Everything 

      Djenouri, Youcef; Djenouri, Djamel; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This research presents a new generic deep learning framework for anomaly detection in the Internet of Everything (IoE). It combines decomposition methods, deep neural networks, and evolutionary computation to better detect ...

    • Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Zhang, Chongsheng; Cano, Alberto (Journal article; Peer reviewed, 2020)
      Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information ...

    • Fast and Accurate Deep Learning Framework for Secure Fault Diagnosis in the Industrial Internet of Things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Ghosh, Uttam; Chatterjee, Pushpita; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper introduced a new deep learning framework for fault diagnosis in electrical power systems. The framework integrates the convolution neural network and different regression models to visually identify which faults ...

    • A general-purpose distributed pattern mining system 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Cano, Alberto (Journal article; Peer reviewed, 2020)
      This paper explores five pattern mining problems and proposes a new distributed framework called DT-DPM: Decomposition Transaction for Distributed Pattern Mining. DT-DPM addresses the limitations of the existing pattern ...

    • Hybrid intelligent framework for automated medical learning 

      Belhadi, Asma; Djenouri, Youcef; Diaz, Vicente Garcia; Houssein, Essam H.; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper investigates the automated medical learning and proposes hybrid intelligent framework, called Hybrid Automated Medical Learning (HAML). The goal is the efficient combination of several intelligent components in ...

    • Intelligent blockchain management for distributed knowledge graphs in IoT 5G environments 

      Djenouri, Youcef; Srivastava, Gautam; Belhadi, Asma; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This article introduces a new problem of distributed knowledge graph, in IoT 5G setting. We developed an end-to-end solution for solving such problem by exploring the blockchain management and intelligent method for producing ...

    • Intelligent deep fusion network for urban traffic flow anomaly identification 

      Djenouri, Youcef; Belhadi, Asma; Chen, Hsing-Chung; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This paper presents a novel deep learning architecture for identifying outliers in the context of intelligent transportation systems. The use of a convolutional neural network with an efficient decomposition strategy is ...

    • Privacy reinforcement learning for faults detection in the smart grid 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Jolfaei, Alireza; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Recent anticipated advancements in ad hoc Wireless Mesh Networks (WMN) have made them strong natural candidates for Smart Grid’s Neighborhood Area Network (NAN) and the ongoing work on Advanced Metering Infrastructure ...

    • A recurrent neural network for urban long-term traffic flow forecasting 

      Belhadi, Asma; Djenouri, Youcef; Djenouri, Djamel; Lin, Jerry Chun-Wei (Journal article; Peer reviewed, 2020)
      This paper investigates the use of recurrent neural network to predict urban long-term traffic flows. A representation of the long-term flows with related weather and contextual information is first introduced. A recurrent ...

    • Secure Collaborative Augmented Reality Framework for Biomedical Informatics 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Augmented reality is currently a great interest in biomedical health informatics. At the same time, several challenges have been appeared, in particular with the rapid progress of smart sensors technologies, and medical ...

    • Sensor data fusion for the industrial artificial intelligence of things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Houssein, Essam H.; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      The emergence of smart sensors, artificial intelligence, and deep learning technologies yield artificial intelligence of things, also known as the AIoT. Sophisticated cooperation of these technologies is vital for the ...

    • Space-time series clustering: Algorithms, taxonomy, and case study on urban smart cities 

      Belhadi, Asma; Djenouri, Youcef; Nørvåg, Kjetil; Ramampiaro, Heri; Masseglia, Florent; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      This paper provides a short overview of space–time series clustering, which can be generally grouped into three main categories such as: hierarchical, partitioning-based, and overlapping clustering. The first hierarchical ...

    • SS-ITS: secure scalable intelligent transportation systems 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper introduces a secure and scalable intelligent transportation and human behavior system to accurately discover knowledge from urban traffic data. The data is secured using blockchain learning technology, where the ...

    • A sustainable deep learning framework for fault detection in 6G Industry 4.0 heterogeneous data environments 

      Mezair, Tinhinane; Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      The integration of 5G and Beyond 5G (B5G)/6G in Machine-to-Machine (M2M) communications, is making Industry 4.0 smarter. However, the goal of having a sustainable self-monitored industry has not been reached yet. ...