School of Engineeringhttp://hdl.handle.net/1803/55492024-03-29T12:56:25Z2024-03-29T12:56:25ZDataset of "Evaluation of Traffic Signal Control at Varying Demand Levels: A Comparative Study"http://hdl.handle.net/1803/183142023-08-14T22:55:41Z2023-01-01T00:00:00ZDataset of "Evaluation of Traffic Signal Control at Varying Demand Levels: A Comparative Study"
Repository for the simulation output dataset associated with the paper "Evaluation of Traffic Signal Control at Varying Demand Levels: A Comparative Study" in IEEE ITSC 2023.
2023-01-01T00:00:00ZOn-chip integrated quantum emitter with 'trap-enhance-guide': a simulation approachSaha, SamprityFomra, DhruvOzgur, UmitAvrutin, VitalyNdukaife, Justus C.Kinsey, Nathanielhttp://hdl.handle.net/1803/179952023-02-13T20:08:21Z2022-12-19T00:00:00ZOn-chip integrated quantum emitter with 'trap-enhance-guide': a simulation approach
Saha, Samprity; Fomra, Dhruv; Ozgur, Umit; Avrutin, Vitaly; Ndukaife, Justus C.; Kinsey, Nathaniel
To address the challenges of developing a scalable system of an on-chip integrated quantum emitter, we propose to leverage the loss in our hybrid plasmonic-photonic structure to simultaneously achieve Purcell enhancement as well as on-chip maneuvering of nanoscale emitter via optical trapping with guided excitation-emission routes. In this report, we have analyzed the feasibility of the functional goals of our proposed system in the metric of trapping strength (-8KBT), Purcell factor (>1000-), and collection efficiency (-10%). Once realized, the scopes of the proposed device can be advanced to develop a scalable platform for integrated quantum technology.
2022-12-19T00:00:00ZAdsorption of methylene blue on papaya bark fiber: Equilibrium, isotherm and kinetic perspectivesNipa, Sumaya TarannumShefa, Nawrin RahmanParvin, ShahanazKhatun, Most AfrozaAlam, Md JahangirChowdhury, SujanKhan, M. Azizur R.Shawon, Sk Md Ali ZakerBiswas, Biplob K.Rahman, Md Wasikurhttp://hdl.handle.net/1803/179882023-02-08T23:20:54Z2022-12-21T00:00:00ZAdsorption of methylene blue on papaya bark fiber: Equilibrium, isotherm and kinetic perspectives
Nipa, Sumaya Tarannum; Shefa, Nawrin Rahman; Parvin, Shahanaz; Khatun, Most Afroza; Alam, Md Jahangir; Chowdhury, Sujan; Khan, M. Azizur R.; Shawon, Sk Md Ali Zaker; Biswas, Biplob K.; Rahman, Md Wasikur
Rapid population growth and industrial expansion lead us to be habitat of a polluted planet. One of the major pollutants that badly affect the ecosystem being organic dyes released from various chemical industries where cleaner production concept is straightway adopted. Papaya (Carica papaya) bark fiber (PBF) is a natural product used for Methylene Blue (MB) dye removal as a cost-effective adsorbent from aqueous solution by batch method. Several parameters as the effect of pH, initial dye concentration, contact time, and adsorbent dosage were studied and optimized for maximum dye recovery. Reaction kinetics of the process and Langmuir and Freundlich adsorption isotherms were investigated. Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) were used to confirm the surface properties of the PBF adsorbent. The maximum MB uptake capacity of PBF adsorbent was found to be 66.67 mg/g. Based on the results, the papaya bark fiber might be employed as a cost-effective bio-sorbent for the exclusion of dyestuffs from industrial effluent for cleaner production.
2022-12-21T00:00:00ZCapsule robot pose and mechanism state detection in ultrasound using attention-based hierarchical deep learningLiu, XiaoyunEsser, DanielWagstaff, BrandonZavodni, AnnaMatsuura, NaomiKelly, JonathanDiller, Erichttp://hdl.handle.net/1803/179822023-02-03T19:46:09Z2022-12-07T00:00:00ZCapsule robot pose and mechanism state detection in ultrasound using attention-based hierarchical deep learning
Liu, Xiaoyun; Esser, Daniel; Wagstaff, Brandon; Zavodni, Anna; Matsuura, Naomi; Kelly, Jonathan; Diller, Eric
Ingestible robotic capsules with locomotion capabilities and on-board sampling mechanism have great potential for non-invasive diagnostic and interventional use in the gastrointestinal tract. Real-time tracking of capsule location and operational state is necessary for clinical application, yet remains a significant challenge. To this end, we propose an approach that can simultaneously determine the mechanism state and in-plane 2D pose of millimeter capsule robots in an anatomically representative environment using ultrasound imaging. Our work proposes an attention-based hierarchical deep learning approach and adapts the success of transfer learning towards solving the multi-task tracking problem with limited dataset. To train the neural networks, we generate a representative dataset of a robotic capsule within ex-vivo porcine stomachs. Experimental results show that the accuracy of capsule state classification is 97%, and the mean estimation errors for orientation and centroid position are 2.0 degrees and 0.24 mm (1.7% of the capsule's body length) on the hold-out test set. Accurate detection of the capsule while manipulated by an external magnet in a porcine stomach and colon is also demonstrated. The results suggest our proposed method has the potential for advancing the wireless capsule-based technologies by providing accurate detection of capsule robots in clinical scenarios.
2022-12-07T00:00:00Z