Now showing items 1-18 of 18

    • Applying machine learning approach in recycling 

      Erkınay Özdemir, Merve; Ali, Zaara; Subeshan, Balakrishnan; Asmatulu, Eylem (Springer Nature, 2021-02-17)
      Waste generation has been increasing drastically based on the world’s population and economic growth. This has signifcantly afected human health, natural life, and ecology. The utilization of limited natural resources, ...
    • CGN-MPred: Cofunctional gene network-based mutation prediction from exposure conditions 

      Okwori, Michael; Eslami, Ali (IEEE, 2021-12-09)
      The prediction of gene mutation of bacteria when exposed to different conditions is beneficial in the development of drugs and vaccines. However, the existing prediction models are suboptimal in their performance. In this ...
    • Comparison of machine learning and deep learning models for network intrusion detection systems 

      Thapa, Niraj; Liu, Zhipeng; KC, Dukka B.; Gokaraju, Balakrishna; Roy, Kaushik (MDPI AG, 2020-09-30)
      The development of robust anomaly-based network detection systems, which are preferred over static signal-based network intrusion, is vital for cybersecurity. The development of a flexible and dynamic security system is ...
    • Complex and entangled public policy: Here be dragons in Emergence, Entanglement, and Political Economy 

      Devereaux, Abigail (Springer, Cham, 2020-12-05)
      The tools and concepts of the emerging field of complexity science—like agent-based modeling, network theory, and machine learning—can offer powerful insights to economists and crafters of public policy. Complexity science ...
    • Deep Learning–Based Advances 

      Pakhrin, Subash C.; Pokharel, Suresh; Saigo, Hiroto; KC, Dukka B. (Humana Press Inc., 2022-06-14)
      Posttranslational modification (PTM ) is a ubiquitous phenomenon in both eukaryotes and prokaryotes which gives rise to enormous proteomic diversity. PTM mostly comes in two flavors: covalent modification to polypeptide ...
    • DeepQA: improving the estimation of single protein model quality with deep belief networks 

      Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin (BioMed Central Ltd, 2016-12-05)
      Background: Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality ...
    • Health diagnostics using multi-attribute classification fusion 

      Wang, Pingfeng; Tamilselvan, Prasanna; Hu, Chao (Elsevier Ltd., 2014-06)
      This paper presents a classification fusion approach for health diagnostics that can leverage the strengths of multiple member classifiers to form a robust classification model. The developed approach consists of three ...
    • Ibeaconmap: Automated indoor space representation for beacon-based wayfinding 

      Cheraghi, Seyed Ali; Namboodiri, Vinod; Sinha, Kaushik (Springer, 2020-09)
      Traditionally, there have been few options for navigational aids for the blind and visually impaired (BVI) in large indoor spaces. Some recent indoor navigation systems allow users equipped with smartphones to interact ...
    • Image analysis with machine learning algorithms to assist breast cancer treatment 

      Asaduzzaman, Abu; Sibai, Fadi N.; Kanaya, Shigehiko; Altaf-Ul-Amin, Md; Jashim, Uddin M.; Chidella, Kishore K. (Springer, Cham, 2021-06-06)
      Real-time imaging technology has the potential to be applied to many complex surgical procedures such as those used in treating people with breast cancer. Key delaying factors for the successful development of real-time ...
    • Image analysis with machine learning algorithms to assist breast cancer treatment 

      Asaduzzaman, Abu; Sibai, Fadi N.; Kanaya, Shigehiko; Altaf-Ul-Amin, Md; Jashim Uddin, Md; Chidella, Kishore K.; Mitra, Parthib (Springer, Cham, 2021-06-06)
      Real-time imaging technology has the potential to be applied to many complex surgical procedures such as those used in treating people with breast cancer. Key delaying factors for the successful development of real-time ...
    • Machine learning applied to programming quantum computers 

      Steck, James E.; Behrman, Elizabeth C.; Thompson, Nathan L. (American Institute of Aeronautics and Astronautics, 2019-01-06)
      We apply machine learning to “program” quantum computers, both in simulation and in experimental hardware. A major difficulty in quantum computing is developing effective algorithms that can be programmed on a quantum ...
    • A machine-learning based approach to privacy-aware information-sharing in mobile social networks 

      Bilogrevic, Igor; Huguenin, Kevin; Agir, Berker; Jadliwala, Murtuza Shabbir; Gazaki, Maria; Hubaux, Jean-Pierre (Elsevier B.V., 2016-01)
      Contextual information about users is increasingly shared on mobile social networks. Examples of such information include users' locations, events, activities, and the co-presence of others in proximity. When disclosing ...
    • Prediction of airline delays based on machine learning algorithms 

      Dand, Alok; Saeed, Khawaja A.; Yildirim, Mehmet Bayram (Association for Information Systems, 2019)
      Every year around 20% of all flights are delayed or canceled. The costs of these events to the airline companies and passengers are in billions of dollars each year. According to a report published in 2010 by UC Berkeley, ...
    • Solar power prediction in different forecasting horizons using machine learning and time series techniques 

      Pun, Kesh B.; Basnet, Saurav Man Singh; Jewell, Ward T. (IEEE, 2021-07-01)
      Solar power generation is highly intermittent, nonlinear, and variable in nature. The increase in penetration level of solar energy resources poses technical challenges. An accurate forecasting model is crucial to minimizing ...
    • Supervised machine learning approach for effective supplier classification 

      Harikrishnakumar, Ramkumar; Dand, Alok; Nannapaneni, Saideep; Krishnan, Krishna K. (IEEE, 2019-12)
      Supplier assessment plays a critical role in the supply chain management, which involves the flow of goods and services from the initial stage (raw material procurement) to the final stage (delivery). Supplier assessment ...
    • 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 survey on machine and deep learning models for childhood and adolescent obesity 

      Siddiqui, Hera; Rattani, Ajita; Woods, Nikki Keene; Cure, Laila; Lewis, Rhonda K.; Twomey, Janet M.; Smith-Campbell, Betty; Hill, Twyla J. (IEEE, 2021-11-25)
      Childhood and adolescent obesity is a serious health problem that is on the rise at the global level. Earlier, certain diseases such as Type 2 diabetes, high blood pressure, and heart disease affected only adults, but now ...
    • Wind power prediction in different months of the year using machine learning techniques 

      Pun, Kesh; Basnet, Saurav M.S.; Jewell, Ward T. (IEEE, 2021-04-19)
      Integration of wind power into the grid has been rapidly increasing at both the transmission as well as distribution levels. Wind power generation is variable, nonlinear, and intermittent in nature. The monthly average and ...