• Application of machine learning models and feature engineering to predict genomic phenomena 

  Okwori, Michael (Wichita State University, 2022-05)

  This dissertation investigates two topics towards designing tiny machine learningbased intelligent devices for biomedical applications. In the first section, feature engineering and machine learning models are developed ...

• Differential Privacy in Social Networks Using Multi-Armed Bandit 

  Odeyomi, Olusola T. (IEEE, 2022-01-20)

  There has been an exponential growth over the years in the number of users connected to social networks. This has spurred research interest in social networks to ensure the privacy of users. From a theoretical standpoint, ...

• Guest Editorial: WACV 2020—Presentation attacks on biometric systems 

  Ramachandra, Raghavendra; Damer, Naser; Raja, Kiran; Rattani, Ajita (John Wiley & Sons Ltd, 2021-06-30)

  This special issue focusses on approaches for detecting PAs and morphing attacks on biometric systems. Four papers in this issue discuss in detail PAD, and three other papers focus on image manipulation attacks such as ...

• Density evolution for noise propagation analysis in biological networks 

  Kotiang, Stephen; Eslami, Ali (IEEE, 2022-01-13)

  Accurate prediction of noise propagation in biological networks is key to understanding faithful signal propagation in gene networks as well as for designing noise-tolerant synthetic gene circuits. Knowledge on how ...

• Online localization using only internal sensors on a smartphone 

  Rao, Ranjitha (Wichita State University, 2021-12)

  Despite the omnipresent smartphones and navigation apps, indoor navigation continues to be a challenge for blind and visually impaired individuals (BVI). Global Positioning System (GPS), while being highly reliable outdoors, ...

• Radio emitter localization via doppler frequency shifts using a single receiver 

  Rankin, Andrew (Wichita State University, 2021-12)

  The Doppler effect has been exploited for localization of an electromagnetic interference (EMI) radio source. The differential Doppler (DD) method has been used for many decades. Another method called the direct position ...

• Understanding abstract sketches by reinforcement learning for automated robotic assembly 

  Ogbonda, Chibuike J. (Wichita State University, 2021-12)

  This paper presents a method to understand and reason the spatial configuration of individual parts in an assembled model from a 2D ISO sketch for autonomous small-part assembly. When given disassembled individual parts ...

• Differentially private online learning algorithms for federated optimization 

  Odeyomi, Olusola T. (Wichita State University, 2021-12)

  The exponential growth of the Internet from the last decade till the present has resulted in the generation of big data from billions of connected devices. Yet, big data are not readily available in many application ...

• Preface 

  Li, Haizhou; Ge, Shuzhi Sam; Wu, Yan; Wykowska, Agnieszka; He, Hongsheng (Springer, 2021-11-02)

  The 13th International Conference on Social Robotics (ICSR 2021) was held as a hybrid conference (onsite and online) in Singapore, during November 10–13, 2021, with the theme of “Robotics in our everyday lives”, emphasizing ...

• Distributed network time synchronization: Social learning versus consensus 

  Hulede, Ian Ellis L; Kwon, Hyuck M. (IEEE, 2021-10-15)

  The objective of this paper is to investigate a social learning-based distributed network time synchronization (SLDNTS) and compare it to a classic approach: consensus-based distributed network time synchronization (CDNTS). ...

• Information-theoretic secret sharing from correlated Gaussian random variables and public communication 

  Rana, Vidhi; Chou, Rémi; Kwon, Hyuck M. (IEEE, 2021)

  Abstract—In this paper, we study an information-theoretic secret sharing problem, where a dealer distributes shares of a secret among a set of participants under the following constraints: (i) authorized sets of users ...

• Maximum torque per ampere and maximum power per ampere sliding mode control for interior permanent magnet synchronous motors 

  Alnami, Hashim; Pang, Chengzong; Papineni, Avinash; Wang, Xin (Taylor & Francis, 2021-10-14)

  This paper presents novel maximum torque per ampere (MTPA) and maximum power per ampere (MPPA) sliding mode control (SMC) approaches for interior permanent-magnet synchronous motors (IPMs). We first derive the first-order ...

• 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 ...

• Node voltage estimation of distribution system using artificial neural network considering weather data 

  Pun, Kesh B.; Basnet, Saurav Man Singh; Jewell, Ward T. (IEEE, 2021-04-19)

  Load flow analysis using traditional methods for power flow is becoming complex (reverse power flow and voltage volatility) due to the configuration complexity brought about by renewable energy resource (RER) integration. ...

• Blind detection design for AF two-way relaying over frequency selective channels 

  Ding, Yanwu; Li, Lun (Springer, 2021-09-18)

  This paper considers an amplify-and-forward two-way relay system with frequency selective fading channels. The knowledge of channel state information is assumed not available for all nodes. An efcient transmission and ...

• Differentially-private federated learning with long-term constraints using online mirror descent 

  Odeyomi, Olusola T.; Záruba, Gergely V. (IEEE, 2021-07-12)

  This paper discusses a fully decentralized online federated learning setting with long-term constraints. The fully decentralized setting removes communication and computational bottlenecks associated with a central server ...

• Private classical communication over quantum multiple-access channels 

  Chou, Remi (IEEE, 2021-07-12)

  We study private classical communication over quantum multiple-access channels. For an arbitrary number of transmitters, we derive a regularized expression of the capacity region. In the case of degradable channels, we ...

• Low-complexity secret sharing schemes using correlated random variables and rate-limited public communication 

  Sultana, Rumia; Chou, Remi (IEEE, 2021-07-12)

  We consider secret sharing where a dealer wants to share a secret with several participants such that predefined subsets of participants can reconstruct the secret and all other subsets of participants cannot learn any ...

• Fruit-fly inspired neighborhood encoding for classification 

  Sinha, Kaushik; Ram, Parikshit (Association for Computing Machinery, 2021-08-14)

  Inspired by the fruit-fly olfactory circuit, the Fly Bloom Filter [4] is able to efficiently summarize the data with a single pass and has been used for novelty detection. We propose a new classifier that effectively ...

• Boolean factor graph model for biological systems: The yeast cell-cycle network 

  Kotiang, Stephen; Eslami, Ali (BMC, 2021-08-14)

  Background: The desire to understand genomic functions and the behavior of complex gene regulatory networks has recently been a major research focus in systems biology. As a result, a plethora of computational and modeling ...

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