Naked-eye 3D imaging model using the embedded micro-conjugate mirrors within the medical micro-needle device

Chaiwong, K.; Tamee, Kreangsak; Punthawanunt, S.; Suhailin, F. H.; Aziz, M. S.; Ali, J.; Singh, Ghanshyam; Yupapin, P.

doi:10.1007/s00542-017-3634-z

Cited by 11 publications

(7 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In practice, the power attenuation may be required due to the very small cross‐section area device. However, the conservation of energy is still valid by the squeezing light behavior, where the saturation of the uncertainty energy is maintained. The plot of the optical signals at the electro‐optic circuit with the center wavelength is 1.55 μm as shown in Figure , where (a) the input, (b) add port (c) throughput, and (d) drop port signals.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…In practice, the up and downlink should be the different wavelengths, for the instance, 1.30 and 1.55 μm, which is the convenience to distinguish between the up and downlink in the networks. By using the MCM concept, the 3D transmission of the data can also be available, which can be employed via the electro‐optic conversion circuit. The distributed sensors using the distributed nodes within the network can also be employed, which allows performing the required measurements via the network.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Electro‐optic conversion circuit incorporating a fiber optic loop for light fidelity up‐down link use

Chaiwong

Bahadoran

Amiri

et al. 2018

Micro & Optical Tech Letters

View full text Add to dashboard Cite

We propose the use of the electro‐optic circuit to integrate with the short distance fiber optic loop network, which can be used to form the light fidelity (LiFi) network platform within the building. The electro‐optic conversion circuit is formed by a plasmonic circuit. It is a passive device consisting of an embedded plasmonic island within the microring conjugate mirror (MCM), in which the applied input‐output information can be connected to the fiber optic loop. In this design, all sources of the information can be coupled to the plasmonic transducer and connected to the network. The transducer mobility and two different wavelengths of the input sources are demonstrated and all port signals plotted. The free spectral range and the full‐width at half maximum at the center wavelength of 1.30 μm are ~370.0 and ~0.62 nm, respectively. This is equal to the bandwidth of ~77 PetaHz, from which the output intensity power is ranged between 5 and 15 mW (μm)−2. The linear relationship between the driven mobility and the input power of ~0.75 (cm)2. (Vs)−1 W−1 is achieved at the drop port, with the gold layer length is 600 nm.

show abstract

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Electro‐optic conversion circuit incorporating a fiber optic loop for light fidelity up‐down link use

Chaiwong

Bahadoran

Amiri

et al. 2018

Micro & Optical Tech Letters

View full text Add to dashboard Cite

show abstract

“… R WGM is the reflection output. Here, R WGM , is a coefficient of the reflection or the used material reflectivity 10 …”

Section: Introductionmentioning

confidence: 99%

“…In the manipulation, the input electric field, E in = E Z =

{bold-italicE}_{bold0} {bold-italice}^{- i {bold-italick}_{bold-italicz} - ωt + φ}

, is fed into the system along the z‐axis direction with the wave propagation number k z . E 0 represents the amplitude of the initial electric field, ω and φ represent the angular frequency and the phase of the propagation light, respectively 10

E_{th} = \sqrt{bold1 - γ_{1}} ((), \sqrt{bold1 - κ_{1}} E_{in} + bold-italicj \sqrt{{bold-italicκ}_{bold1}} E_{4} e^{- \frac{α}{2} \frac{{bold-italicL}_{boldD}}{4} - bold-italicj k_{n} \frac{{bold-italicL}_{boldD}}{4}})

E_{dr} = \sqrt{bold1 - γ_{3}} ((), \sqrt{bold1 - κ_{3}} E_{add} + bold-italicj \sqrt{{bold-italicκ}_{bold3}} E_{2} e^{- \frac{α}{2} \frac{{bold-italicL}_{boldD}}{4} - bold-italicj k_{n} \frac{{bold-italicL}_{boldD}}{4}})

E_{out} = \sqrt{...}

…”

Section: Introductionmentioning

confidence: 99%

Thermo‐electro‐optic energy conversion using plasmonic island embedded silicon microring circuit

Bunruangses

Youplao

Punthawanunt

et al. 2020

Micro & Optical Tech Letters

View full text Add to dashboard Cite

We propose the use of the thermo‐electro‐optic energy conversion system for daily sunlight charger. A circuit consists of a modified silicon microring circuit embedded by a plasmonic island at the center. The island materials consist of silicon‐graphene‐gold layers. The thermal expansion of the island materials from the daily sunlight can affect the change in island material lengths and transfer to the plasmon wave path difference, which can perform the energy conversion and a charger. In manipulation, the daily sunlight statistic from South East Asia, the significant daily charging mobility of 4.34 × 10−6 cm2. (V. s)−1/Vs with the input light power of 10 mW can be obtained, which may be useful for one of the selected alternative energy sources.

show abstract

“…The rapid development of wearable devices makes VR video streaming service applications quickly enter people's sights and lives, and is widely used in video live broadcast, immersive games, online exhibition halls, panoramic street scenes and other fields. In particular, the naked-eye 3D video enables each user to view objects from a freely switchable viewpoint, and the viewer can place himself in an immersive scene without any additional accessories, making it ideal for commercial use [17]- [19].…”

Section: Introductionmentioning

confidence: 99%

Network-Assisted Neural Adaptive Naked-Eye 3D Video Streaming Over Wireless Networks

Liu

Wang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

High quality transmission of Virtual Reality (VR) video depends strictly on bandwidth and delay requirements. It becomes possible with the maturity and commercialization of 5G technology. However, to transmit VR video streaming over wireless communication system, we must cope with the challenge that fluctuation exists in the wireless channel conditions. For example, available channel bandwidth, packet loss rate, and interference level may vary with time due to channel fading and user's mobility. The problem is more prominent when transmitting naked-eye 3D video which generally consists of multiple viewpoints with different resolutions. In order to optimize the quality of experience (QoE) of watching naked-eye VR video over wireless networks, this paper proposes a network-assisted neural adaptive video streaming algorithm (NAVSA). Specifically, we present a modified QoE function to describe the quality of naked-eye 3D streaming quantitatively, which not only considers the quality of naked-eye 3D video itself, but also considers the phenomenon of rebuffering and video fluctuation that occurs during video transmission. Next, with the network-assisted feedback, the physical layer information, the buffer occupancy of the video client, and the size of the next video chunk are collected to train a reinforcement learning model. Based on dynamic adaptive streaming over HTTP (DASH), the model can automatically choose appropriate viewpoints and resolutions corresponding to the current condition of the wireless networks such that the network capacity can be fully explored. To verify the performance of our proposed NAVSA, we simulate 3 naked-eye 3D video application scenarios on the NS3 platform. The results show that the performance of NAVSA is about 5∼8% better than some state-of-the-art algorithms in wireless networks.

show abstract

Naked-eye 3D imaging model using the embedded micro-conjugate mirrors within the medical micro-needle device

Cited by 11 publications

References 20 publications

Electro‐optic conversion circuit incorporating a fiber optic loop for light fidelity up‐down link use

Electro‐optic conversion circuit incorporating a fiber optic loop for light fidelity up‐down link use

Thermo‐electro‐optic energy conversion using plasmonic island embedded silicon microring circuit

Network-Assisted Neural Adaptive Naked-Eye 3D Video Streaming Over Wireless Networks

Contact Info

Product

Resources

About