• Acoustic signal processing systems for intelligent beehive monitoring 

      Ardekani, Iman; Varastehpour, Soheil; Sharifzadeh, Hamid (Acoustical Society of New Zealand, 2022)
      Bees, as pollinators and producers of honey and medicinal products, play a crucial role in human life and environmental sustainability. Emerging Smart Beekeeping technologies utilise various methodologies in apiology, ...
    • Aiding forensic investigations using machine learning 

      Sharifzadeh, Hamid; Varastehpour, Soheil; Francis, X.; Keivanmarz, A.; Fleming, R.; Ardekani, Iman; Newton, A. (2022-11-28)
      Advances in machine learning find rapid adoption in many fields ranging from communications, signal processing, and the automotive industry to healthcare, law, and forensics. In this talk, I briefly focus on a couple of ...
    • Bayesian active noise control 

      Ardekani, Iman; Varastehpour, Soheil; Sharifzadeh, Hamid (Acoustical Society of New Zealand, 2022-10)
      Active Noise Control (ANC) is a challenging practical application of adaptive control systems. This paper approaches ANC from the perspective of the Bayesian Inverse Problems theory. The ANC underlying problem is initially ...
    • Integration of heterogeneous software using XML Webservice Middleware: Case study: WorkOS and PSA software 

      Thirunahari, S.; Ramirez Prado, Guillermo; Barmada, Bashar (2022-11-30)
      AGENDA Software integration overview About Monday.com and OpenAir Timesheets Business problem Proposed methodology Software integration approaches Business goals and requirements Software integration method OpenAir ...
    • Smart beekeeping using IoT & ML 

      Ardekani, Iman; Shakiba, Masoud (2022-12-02)
      OUTLINE 1 Introduction 2 Intelligent beehive monitoring 3 Proposed system 4 Data collection 5 Conclusion