• The eight class of service model-An improvement over the five classes of service 

  Asaduzzaman, Abu; Kamalakannan, Prasanth; Sibai, Fadi N. (IEEE, 2021-05-10)

  Due to the massive growth in traffic data generation on networks, the existing Five Class of Service (5CoS) model is not adequate to guarantee the required Quality of Service (QoS). In this work, we introduce the 8CoS model ...

• Impact of CUDA and OpenCL on parallel and distributed computing 

  Asaduzzaman, Abu S.; Trent, Alec; Osborne, S.; Aldershof, C.; Sibai, Fadi N. (IEEE, 2021-05-10)

  Along with high performance computer systems, the Application Programming Interface (API) used is crucial to develop efficient solutions for modern parallel and distributed computing. Compute Unified Device Architecture ...

• Deep learning-based advances in protein structure prediction 

  Pakhrin, Subash C.; Shrestha, Bikash; Adhikari, Badri; Kc, Dukka B. (MDPI AG, 2021-05-24)

  Obtaining an accurate description of protein structure is a fundamental step toward understanding the underpinning of biology. Although recent advances in experimental approaches have greatly enhanced our capabilities to ...

• Probing fairness of mobile ocular biometrics methods across gender on VISOB 2.0 dataset 

  Krishnan, Anoop; Almadan, Ali; Rattani, Ajita (Springer, Cham, 2021-02-21)

  Recent research has questioned the fairness of face-based recognition and attribute classification methods (such as gender and race) for dark-skinned people and women. Ocular biometrics in the visible spectrum is an alternate ...

• Transient stability assessment of a power system using multi-layer SVM method. 

  Wang, Qilin; Pang, Chengzong; Alnami, Hashim (IEEE, 2021-04-02)

  With the rapid growth of power systems, more large interconnections and the integration of large renewable energies make the systems more complicated. Therefore, transient stability assessment (TSA) has always been considered ...

• A novel sliding mode control method of interior-mounted PMSM 

  Alnami, Hashim; Pang, Chengzong; Wang, Qilin (IEEE, 2021-04-02)

  Energy efficiency and output uncertainty are two of the most challenges that dynamic conversion is facing. Controlling the dynamic system variables is complicated due to the variability and unpredictability of the parameters, ...

• A comparative study on handcrafted features v/s deep features for open-set fingerprint liveness detection 

  Agarwal, Shivang; Rattani, Ajita; Chowdary, C. Ravindranath (Elsevier, 2021-07)

  A fingerprint liveness detector is a pattern classifier that is used to distinguish a live finger from a fake (spoof) one in the context of an automated fingerprint recognition system. As liveness detectors or presentation ...

• Power-based intrusion detection for additive manufacturing: A deep learning approach 

  Rott, Michal; Monroy, Sergio A.Salinas (Springer, Cham, 2021-03-11)

  Due to the ability of 3D-printers to build a wide range of objects at low costs, many industries are rapidly adopting additive manufacturing. However due to their sensing and communications capabilities, 3D-printers are ...

• VISOB 2.0 - The second international competition on mobile ocular biometric recognition 

  Nguyen, Hoang Mark; Reddy, Narsi; Rattani, Ajita; Derakhshani, Reza R. (Springer, Cham, 2021-02-21)

  Following the success of VISOB 1.0 visible light ocular biometrics competition at IEEE ICIP 2016, we organized VISOB 2.0 competition at IEEE WCCI 2020. The aim of VISOB 2.0 competition was to evaluate and compare the ...

• Studying execution time and memory transfer time of image processing using GPU cards 

  Asaduzzaman, Abu; Jojigiri, Srinivas; Sabu, Thushar; Tailam, Sanath (IEEE, 2021)

  With advancements in technology, the size and quantity of captured images to be analyzed are rapidly increasing. As the number of pixels in an image increases (more than 20 megapixels), additional processing power is ...

• Energy consumption analyses for unmanned aerial systems used in disaster management 

  Asaduzzaman, Abu; Telakapalli, Abhignan; Sibai, Fadi N. (IEEE, 2021)

  Communication technology plays an important role in disaster management to propagate and convey information to the concerned authorities. Considering potential risks and hazards, unmanned aerial systems (UASs) show promise ...

• Hardware acceleration of the STRIKE string kernel algorithm for estimating protein to protein interactions 

  Sibai, Fadi N.; El-Moursy, Ali A.; Asaduzzaman, Abu; Majzoub, Sohaib S. (IEEE, 2021-03-17)

  Protein-protein interaction (PPI) is an important field in bioinformatics which helps in understanding diseases and devising therapy. PPI aims at estimating the similarity of protein sequences and their common regions. ...

• Smart disaster management using software-defined unmanned aerial systems 

  Asaduzzaman, Abu; Telakapalli, Abhignan; Sibai, Fadi N. (IEEE, 2021-03-11)

  In this work, we introduce a software-defined unmanned aerial systems (UAS) model, which can provide access to sensitive places where Wi-Fi communication is most needed for rescue operations. The proposed UAS model is ...

• Investigating the impact of gene cofunctionality in predicting gene mutations of E. coli 

  Okwori, Michael; Eslami, Ali (IEEE, 2020-09-14)

  Machine learning algorithms (MLAs) have recently been applied to predict gene mutations of Escherichia coli (E. coli) under different exposure conditions, with room for improvement in performance. In a bid to improve ...

• Al-based BMI inference from facial images: An application to weight monitoring 

  Siddiqui, Hera; Rattani, Ajita; Kisku, Dakshina R.; Dean, Tanner (IEEE, 2021-02-23)

  Self-diagnostic image-based methods for healthy weight monitoring is gaining increased interest following the alarming trend of obesity. Only a handful of academic studies exist that investigate AI-based methods for Body ...

• Robotic understanding of spatial relationships using neural-logic learning 

  Yan, Fujian; Wang, Dali; He, Hongsheng (IEEE, 2021-02-23)

  Understanding spatial relations of objects is critical in many robotic applications such as grasping, manipulation, and obstacle avoidance. Humans can simply reason object’s spatial relations from a glimpse of a scene based ...

• A survey of biometric and machine learning methods for tracking students' attention and engagement 

  Villa, Maria; Gofman, Mikhail I.; Mitra, Sinjini; Almadan, Ali; Krishnan, Anoop; Rattani, Ajita (IEEE, 2021-02-23)

  The skills of focusing and paying attention are critical to student learning. According to Piontkowski et al. [40], "Educators often talk about attention as a general mental state in which the mind focuses on some special ...

• A brain-inspired framework for evolutionary artificial general intelligence 

  Nadji-Tehrani, Mohammad; Eslami, Ali (IEEE, 2020-12)

  From the medical field to agriculture, from energy to transportation, every industry is going through a revolution by embracing artificial intelligence (AI); nevertheless, AI is still in its infancy. Inspired by the evolution ...

• Learning the truth by weakly connected agents in social networks using multi-Armed Bandit 

  Odeyomi, Olusola T. (IEEE, 2020-11-09)

  This article provides a study into the social network where influential personalities collaborate positively among themselves to learn an underlying truth over time, but may have misled their followers to believe a false ...

• Deep Learning for Optimal Resource Allocation in IoT-enabled Additive Manufacturing 

  Mashhadi, Farshad; Salinas Monroy, Sergio A. (IEEE, 2020-10-13)

  Additive manufacturing is revolutionizing the way that we produce, deliver, and consume objects in many industries. Compared to traditional manufacturing, where large factories mass produce objects far away from consumers, ...

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