Browsing Electrical Engineering and Computer Science by Title

Now showing items 204-223 of 1121

    • Data caching for enhancing anonymity 

      Bagai, Rajiv; Tang, Bin (IEEE Computer Society, 2011-03-22)
      The benefits of caching for reducing access time to frequently needed data, in order to improve system performance, are already well-known. In this paper, a proposal for employing data caching for increasing the level of ...

    • Data caching in ad hoc networks using Bloom filters 

      Taylor, Julinda (Wichita State University. Graduate School, 2009-05-01)
      Data caching provides efficient data access by maintaining replicas of data in strategic parts of the network. However, current research in this area does not manage memory space of each node efficiently. We propose an ...

    • Data caching in ad hoc networks using game-theoretic analysis 

      Dang, Hoang (Wichita State University, 2011-05)
      There have been researches that studied selfish data caching in ad hoc networks using game-theoretic analysis. However, due to the caching problem’s theoretical root in classic facility location problem and k-median problem, ...

    • Data preservation in intermittently connected sensor network with data priority 

      Xue, Xinyu (Wichita State University, 2013-05)
      In intermittently connected sensor networks, the data generated may have different importance and priority. Different types of data will help scientists analyze the physical environment differently. In a challenging ...

    • Data redistribution problem in data intensive sensor networks 

      Kurkal, Rohini (Wichita State University, 2009-12)
      Data redistribution problem has become a key challenge in the data intensive sensor networks (DISNs), wherein large volume of sensory data are sensed and generated from some sensor nodes about their surrounding physical ...

    • Data replication in data intensive scientific applications with performance guarantee 

      Nukarapu, Dharma Teja (Wichita State University, 2009-12)
      Data replication is well adopted in data intensive scientific applications to reduce the data file transfer time and the bandwidth consumption. However, the problem of data replication in Data Grids, an enabling technology ...

    • Decoupling of large scale systems 

      Shah, Dipak C.; Sawan, M. Edwin; Tran, Minh T. (IEEE, 1984-06-06)
      Linear shift invariant large scale discrete-time multivariable systems whose inputs and outputs are strongly interacted, are considered. The designing of compensators to decouple these systems is presented.

    • Dedicated backup units to alleviate overload on SDN controllers 

      Almohaimeed, Abdulrahman; Asaduzzaman, Abu (IEEE, 2019-03-14)
      Software-Defined Networking (SDN) is a rapidly evolving architecture for computer networking that transforms computer networks into software-driven organizations. The traditional SDN architecture relies on a centralized ...

    • A deep learning based approach for prediction of Chlamydomonas reinhardtii phosphorylation sites 

      Thapa, Niraj; Chaudhari, Meenal; Iannetta, Anthony A.; White, Clarence; Kaushik, Roy; Newman, Robert H.; Hicks, Leslie M.; KC, Dukka B. (Nature, 2021-06-15)
      Protein phosphorylation, which is one of the most important post-translational modifications (PTMs), is involved in regulating myriad cellular processes. Herein, we present a novel deep learning based approach for ...

    • Deep learning for optimal dynamic control of the internet of things 

      Mashhadi, Farshad (Wichita State University, 2020-12)
      In recent years, industrial Internet of Things (IIoT) has gained considerable attention in both industry and academia. In manufacturing sector, factories use the real-time big data collected from their IoT-enabled machines ...

    • 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, ...

    • Deep learning models for mobile and wearable biometrics 

      Almadan, Ali (Wichita State University, 2023-05)
      The mobile technology revolution has transformed mobile devices from communication tools to all-in-one platforms. As a result, more people are using smartphones to access e-commerce and banking services, replacing ...

    • 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 ...

    • 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 ...

    • DeepRMethylSite: a deep learning based approach for prediction of arginine methylation sites in proteins 

      Chaudhari, Meenal; Thapa, Niraj; Roy, Kaushik; Newman, Robert H.; Hiroto, Saigo; KC, Dukka B. (Royal Society of Chemistry, 2020-06-03)
      Methylation, which is one of the most prominent post-translational modifications on proteins, regulates many important cellular functions. Though several model-based methylation site predictors have been reported, all ...

    • DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction 

      Thapa, Niraj; Chaudhari, Meenal; McManus, Sean; Roy, Kaushik; Newman, Robert H.; Hiroto, Saigo; KC, Dukka B. (Springer, 2020-04-23)
      Protein succinylation has recently emerged as an important and common post-translation modification (PTM) that occurs on lysine residues. Succinylation is notable both in its size (e.g., at 100 Da, it is one of the larger ...

    • The Degraded Gaussian many-access wiretap channel 

      Chou, Rémi; Yener, Aylin (IEEE, 2019-07)
      The Gaussian multiple-access wiretap channel when the number of transmitters grows unbounded and at most linearly with the blocklength is studied. Its capacity region is characterized when the eavesdropper channel is ...

    • Delay-based maximum power-weight scheduling with heavy-tailed traffic 

      Lin, Shih-Chun; Wang, Pu; Akyildiz, Ian F.; Luo, Min (IEEE, 2017-08)
      Heavy-tailed (HT) traffic (e.g., the Internet and multimedia traffic) fundamentally challenges the validity of classic scheduling algorithms, designed under conventional light-tailed (LT) assumptions. To address such a ...

    • Demand response and solar to mitigate peak load 

      Sethi, Tushar; Jewell, Ward T. (IEEE, 2019-10)
      Six hundred houses were simulated in this study of the effect of varying solar photovoltaic penetration levels on peak load. In the simulations, demand response (DR) was implemented in the form of air conditioner (AC) load ...

    • Demand response potential in aggregated houses using GridLAB-D 

      Hanumantha Vajjala, Vivek Abhilash (Wichita State University, 2014-12)
      Electrical power consumption or demand varies very significantly from region to region. There are various factors which affect the demand for a particular location; higher the electrical demand higher is the wholesale ...