• Attention-Based Deep Entropy Active Learning Using Lexical Algorithm for Mental Health Treatment 

      Ahmed, Usman; Mukhiya, Suresh Kumar; Srivastava, Gautam; Lamo, Yngve; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      With the increasing prevalence of Internet usage, Internet-Delivered Psychological Treatment (IDPT) has become a valuable tool to develop improved treatments of mental disorders. IDPT becomes complicated and labor intensive ...
    • cHybriDroid: A Machine Learning-Based Hybrid Technique for Securing the Edge Computing 

      Maryam, Afifa; Ahmed, Usman; Aleem, Muhammad; Lin, Jerry Chun-Wei; Muhammad Arshad, Islam; Iqbal, Muhammad Azhar (Journal article; Peer reviewed, 2020)
      Smart phones are an integral component of the mobile edge computing (MEC) framework. Securing the data stored on mobile devices is very crucial for ensuring the smooth operations of cloud services. A growing number of ...
    • Deep-Attention Model to Analyze Reliable Customers via Federated Learning 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam (Peer reviewed; Journal article, 2021)
      In this research, we propose a collaborative clustering method where the exchange of raw data is not required. The attention-based model is used with a federated learning framework. The edge devices compute the model updates ...
    • Generative Ensemble Learning for Mitigating Adversarial Malware Detection in IoT 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam (Peer reviewed; Journal article, 2021)
      This paper proposes a framework that can be employed to mitigate adversarial evasion attacks on Android malware classifiers. It extracts multiple discriminating feature subsets from a single Android app such that each ...
    • Incrementally updating the high average-utility patterns with pre-large concept 

      Lin, Jerry Chun-Wei; Pirouz, Matin; Djenouri, Youcef; Cheng, Chien-Fu; Ahmed, Usman (Peer reviewed; Journal article, 2020)
      High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utility patterns from databases. Most existing algorithms of HUIM only consider the itemset utility regardless of the length. This ...
    • Linguistic frequent pattern mining using a compressed structure 

      Lin, Jerry Chun-Wei; Ahmed, Usman; Srivastava, Gautam; Wu, Jimmy Ming-Tai; Hong, Tzung-Pei; Djenouri, Youcef (Peer reviewed; Journal article, 2021)
      Traditional association-rule mining (ARM) considers only the frequency of items in a binary database, which provides insufficient knowledge for making efficient decisions and strategies. The mining of useful information ...
    • A load balance multi-scheduling model for OpenCL kernel tasks in an integrated cluster 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam; Aleem, Muhammad (Peer reviewed; Journal article, 2020)
      Nowadays, embedded systems are comprised of heterogeneous multi-core architectures, i.e., CPUs and GPUs. If the application is mapped to an appropriate processing core, then these architectures provide many performance ...
    • A Machine-Learning-Based System for Prediction of Cardiovascular and Chronic Respiratory Diseases 

      Shah, Wajid; Aleem, Muhammad; Iqbal, Muhammad Azhar; Islam, Muhammad Arshad; Ahmed, Usman; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Cardiovascular and chronic respiratory diseases are global threats to public health and cause approximately 19 million deaths worldwide annually. This high mortality rate can be reduced with the use of technological ...
    • A nutrient recommendation system for soil fertilization based on evolutionary computation 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam; Djenouri, Youcef (Peer reviewed; Journal article, 2021)
      In agricultural production, soil characteristics play a vital role in maintaining fertility by allowing crops to develop better through root nutrition with minimal energy inputs. Nitrogen (N), Phosphorus (P), and Potassium ...
    • Privacy-Preserving Deep Reinforcement Learning in Vehicle AdHoc Networks 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam (Peer reviewed; Journal article, 2021)
      The increasing number of road vehicles results in more fatalities and accidents. Thus, the manufacturing industry is working on driver safety to secure and safe transportation in Vehicle Adhoc networks. In addition, the ...