Transformer-Based Deep Learning Detector for Dual-Mode Index Modulation 3D-OFDM

In this paper, we propose a deep learning-based signal detector called TransD3D-IM, which employs the Transformer framework for signal detection in the Dual-mode index modulation-aided three-dimensional (3D) orthogonal frequency division multiplexing (DM-IM-3D-OFDM) system. In this system, the data bits are conveyed using dual-mode 3D constellation symbols and active subcarrier indices. As a result, this method exhibits significantly higher transmission reliability than current IM-based models with traditional maximum likelihood (ML) detection. Nevertheless, the ML detector suffers from high computational complexity, particularly when the parameters of the system are large. Even the complexity of the Log-Likelihood Ratio algorithm, known as a low-complexity detector for signal detection in the DM-IM-3D-OFDM system, is also not impressive enough. To overcome this limitation, our proposal applies a deep neural network at the receiver, utilizing the Transformer framework for signal detection of DM-IM-3D-OFDM system in Rayleigh fading channel. Simulation results demonstrate that our detector attains to approach performance compared to the model-based receiver. Furthermore, TransD3D-IM exhibits more robustness than the existing deep learning-based detector while considerably reducing runtime complexity in comparison with the benchmarks

Deep Neural Network-Based Detector for Single-Carrier Index Modulation NOMA

In this paper, a deep neural network (DNN)-based detector for an uplink single-carrier index modulation nonorthogonal multiple access (SC-IM-NOMA) system is proposed, where SC-IM-NOMA allows users to use the same set of subcarriers for transmitting their data modulated by the sub-carrier index modulation technique. More particularly, users of SC-IMNOMA simultaneously transmit their SC-IM data at different power levels which are then exploited by their receivers to perform successive interference cancellation (SIC) multi-user detection. The existing detectors designed for SC-IM-NOMA, such as the joint maximum-likelihood (JML) detector and the maximum likelihood SIC-based (ML-SIC) detector, suffer from high computational complexity. To address this issue, we propose a DNN-based detector whose structure relies on the model-based SIC for jointly detecting both M-ary symbols and index bits of all users after trained with sufficient simulated data. The simulation results demonstrate that the proposed DNN-based detector attains near-optimal error performance and significantly reduced runtime complexity in comparison with the existing hand-crafted detectors

Language-driven Scene Synthesis using Multi-conditional Diffusion Model

Scene synthesis is a challenging problem with several industrial applications. Recently, substantial efforts have been directed to synthesize the scene using human motions, room layouts, or spatial graphs as the input. However, few studies have addressed this problem from multiple modalities, especially combining text prompts. In this paper, we propose a language-driven scene synthesis task, which is a new task that integrates text prompts, human motion, and existing objects for scene synthesis. Unlike other single-condition synthesis tasks, our problem involves multiple conditions and requires a strategy for processing and encoding them into a unified space. To address the challenge, we present a multi-conditional diffusion model, which differs from the implicit unification approach of other diffusion literature by explicitly predicting the guiding points for the original data distribution. We demonstrate that our approach is theoretically supportive. The intensive experiment results illustrate that our method outperforms state-of-the-art benchmarks and enables natural scene editing applications. The source code and dataset can be accessed at https://lang-scene-synth.github.io/.Comment: Accepted to NeurIPS 202

Oxidation of benzyl alcohol to benzaldehyde over MnOx/sepiolite catalysts

MnOx/sepiolite catalysts were synthesized by precipitation method accompanied by the calcination at 4100C. The prepated solids have been characterized by XRD, SEM, TPR-H2. MnOx particles were deposited on the surface of the sepiolite fibers and act as active sites for  the oxidation of benzyl alcohol using tert-butyl hydroperoxide (TBHP) as an oxidizing agent. The catalysts showed a good conversion of benzyl alcohol to benzaldehyde at 60 oC. The influence of the reaction time and reaction temperature was considered. Keywords. MnOx/sepiolite, oxidation, benzyl alcohol conversion, TBHP, benzaldehyde

Change in mode shape nodes of multiple cracked bar: I. The theoretical study

In present paper change in position of mode shape nodes induced by multiple cracks in bar is studied with purpose to use for the multiple crack detection from measured mode shape nodes. First, there is derived an explicit expression for natural modes in axial vibration of multiple cracked bar that allows obtaining exact positions of the node in the case of single and double crack. The change in mode shape nodes induced by multiple cracks provides an important indicator for crack localization in bar. Finally, a procedure for multiple crack detection by using mode shape nodes has been proposed and examined in an example of application

A Novel Parallel Hardware Architecture for Inter Motion Estimation in HEVC

High Efficiency Video Coding (HEVC) standard, generated by ITU, can provide compression ratio twice more than current H.264/ MPEG-4. To date, only a few hardware have been implementated for Integer Motion Estimation (IME) to date. In this paper, a parallel hardware architecture for IME in HEVC encoder is proposed. This design uses Rot-WDiamond (RWD) algorithm to reduce computational load and parallelism to improve processing speed. Therefore, this design can reach 4K (4096×2160) video in real time at 60 frames per second (fps) and achieve the frequency of 125MHz

Design and fabrication of the trapezoidal electrostatic comb-drive actuator

This paper reports the design, fabrication and characterization process of the trapezoidal Electrostatic Comb-drive Actuator (ECA) with the slope angle α=20. Together with the trapezoidal ones, the rectangular ECA with identical dimension was also designed and fabricated for comparison purpose. In order to reduce calculating deviation, the fringing effect was also taken into consider while carrying out theoretical analysis. The obtained results pointed out the fact, that the trapezoidal ECA excels the rectangular ones with the same numbers of teeth in electrostatic force and displacement generation, while requires relatively low driving voltage. But it is also observed that with higher driving voltage (larger than 50V), the trapezoidal ECA starts to lose its stability (the lateral pull-in phenomenon occurs)

Agrobacterium-mediated transformation of Nang Thom Cho Dao, an indica rice variety

Agrobacterium-mediated transformation is the most efficient method to transfer gene of interest into the plant genome. However, the transformation efficiency of this method with indica rice varieties is still low and needs to be improved. In this study, the Agrobacterium-mediated method was used to transfer reporter genes into the Nang Thom Cho Dao, an indica rice variety. Different transformation parameters, such as selection to used hygromycin at concentrations of 0, 25, 30, 40, and 50 mg/L, bacterial density, and infected duration, were tested and optimized. The results showed that 30 mg/L of hygromycin was the most appropriate concentration for selecting transgenic callus in Nang Thom Cho Dao. In addition, the highest transformation efficiency of this Nang Thom Cho Dao rice cultivar was observed at the bacterial suspension density OD600nm of 0.1, the infected duration of 20 minutes, and the 3-day co-culture period. The presence and expression of transgenes were confirmed by gus staining and PCR with specific primers for hptII and gus genes. This transformation procedure should be used for further studies in genetic engineering of Nang Thom Cho Dao and other indica rice varieties