Multimode System Research Articles

Understanding Travel Mode Choice Behavior: Influencing Factors Analysis and Prediction with Machine Learning Method

Building a multimode transportation system could effectively reduce traffic congestion and improve travel quality. In many cities, use of public transport and green travel modes is encouraged in order to reduce the emission of greenhouse gas. With the development of the economy and society, travelers’ behaviors become complex. Analyzing the travel mode choices of urban residents is conducive to constructing an effective multimode transportation system. In this paper, we propose a statistical analysis framework to study travelers’ behavior with a large amount of survey data. Then, a stacking machine learning method considering travelers’ behavior is introduced. The results show that electric bikes play a dominant role in Jinan city and age is an important factor impacting travel mode choice. Travelers’ income could impact travel mode choice and rich people prefer to use private cars. Private cars and electric bikes are two main travel modes for commuting, accounting for 30% and 35%, respectively. Moreover, the proposed stacking method achieved 0.83 accuracy, outperforming the traditional multinomial logit (MNL) mode and nine other machine learning methods.

A multimode detection of silver ions based on peroxidase-like activity and photothermal effect of Prussian blue nanoparticles

Silver ion (Ag+), as a heavy metal ion easily absorbed by organisms, can be enriched through the food chain. This study present a novel multimodal detection system for Ag+ using Prussian blue nanoparticles (PB NPs) with excellent photothermal effect and peroxidase-like activity. The PB NPs undergo a dissolution-precipitation equilibrium, converting blue PB NPs into colourless silver ferrocyanide ions in the presence of Ag+. The color, photothermal effect, and peroxidase-like activity of the PB NPs change with the concentration of Ag+, making them an effective probe for detecting Ag+. The key parameters that affect the performance of multimode detection assay were optimized. Under optimal conditions, the detection limit of visual detection was estimated to be 2.94 μM. Based on catalytic color development and the photothermal effect of PB NPs, the detection limit of color development detection and photothermal analysis were reduced to 0.57 μM and 0.23 μM, respectively. And the detection range was also broadened than visual direct detection. Besides, the multimode detection of Ag+ improves the accuracy of detection by mutual verification. The promising multimode system exhibited good repeatability and specificity of Ag+ in different sample implementations, which has great potential for applications in food safety regulation and environmental monitoring.

Temperature uniformity optimization with power-frequency coordinated variation in multi-source microwave based on sequential quadratic programming

Abstract The focus of this study is to regulate the variation in the input parameters of multiple microwave sources in a high-frequency multimode resonant heating system to achieve uniform heating. First, this study deeply expands the theoretical process of frequency change and proposes a frequency-shifting strategy with hot spot alternation to ensure that the temperature difference range of each hot spot does not continuously expand during the heating process. Then, a sequential quadratic programming algorithm is introduced to reconstruct the input power values to improve the heating efficiency according to the different microwave absorption efficiencies of the heated material at different frequencies. Finally, a numerical calculation model for multi-source microwave power-frequency cooperative heating is established based on the finite-element method, and the temperature uniformity index is effectively calculated. Numerical calculations show that the proposed method can improve the uniformity in single-material heating and multi-material heating cases by 56.8–94.3% and 44.4–76.6%, respectively, over that of fixed-frequency heating while achieving improved heating efficiency on the basis of frequency conversion.

Circularly polarized multimode smart antenna system for micro base station application

Abstract A smart antenna system suitable for micro base stations is proposed, which consists of three left-handed circularly polarized designs operating at 3.5 GHz. The first one is an eight-port cylindrical conformal antenna with both omnidirectional and directional modes. Its maximum omnidirectional realized gain is 5.0 dBic, and its maximum single/dual beam realized gain under the directional mode on the horizontal plane is 9.4/6.9 dBic. In addition, it can achieve elevational scan from 70° to 110°. The second one is based on the first one with a feeding network, therefore reducing the number of ports to four, achieving a maximum omnidirectional and directional realized gain of 4.2 and 7.9 dBic. The third one is also based on the first one, but with two additional omnidirectional antennas added, making it a hybrid system with enhanced omnidirectional radiation. It has a maximum omnidirectional and directional realized gain of 6.4 and 8.2 dBic. To validate the proposed concept, three prototype arrays are designed, fabricated, and measured, showing that the proposed antenna system can achieve the desired radiation patterns according to different targeted applications.

A pressure-colorimetric multimode system with photothermal activated multiple rolling signal amplification for ovarian cancer biomarker detection

Utilizing the photothermal effect to activate enzyme activity, realize signal conversion and amplification show promising prospects in biosensing. Herein, a pressure-colorimetric multi-mode bio-sensor was proposed through the multiple rolling signal amplification strategy of photothermal control. Under NIR light radiation, the Nb2C MXene labeled photothermal probe caused notable temperature elevation on a multi-functional signal conversion paper (MSCP), leading to decomposition of thermal responsive element and in-situ formation of Nb2C MXene/Ag-Sx hybrid. The generation of Nb2C MXene/Ag-Sx hybrid accompanied with valid color change from pale yellow to dark brown on MSCP. Moreover, the Ag-Sx as a signal amplification element enhanced the NIR light absorption to further improve the photothermal effect of Nb2C MXene/Ag-Sx thereby induce cyclic in situ production of Nb2C MXene/Ag-Sx hybrid with rolling enhanced photothermal effect. Subsequently, the continuously enhanced photothermal effect rolling activated catalase-like activity of Nb2C MXene/Ag-Sx, which accelerated the decomposition of H2O2 and promoted the pressure elevation. Therefore, the rolling-enhanced photothermal effect and rolling activated catalase-like activity of Nb2C MXene/Ag-Sx considerately amplified the pressure and color change. Making full use of multi-signal readout conversion and rolling signal amplification, accurate results can be obtained in a short time, whether in the laboratory or in the patient's homes.

Super-resolution multimode fiber imaging with an untrained neural network.

Multimode fiber endoscopes provide extreme miniaturization of imaging components for minimally invasive deep tissue imaging. Typically, such fiber systems suffer from low spatial resolution and long measurement time. Fast super-resolution imaging through a multimode fiber has been achieved by using computational optimization algorithms with hand-picked priors. However, machine learning reconstruction approaches offer the promise of better priors, but require large training datasets and therefore long and unpractical pre-calibration time. Here we report a method of multimode fiber imaging based on unsupervised learning with untrained neural networks. The proposed approach solves the ill-posed inverse problem by not relying on any pre-training process. We have demonstrated both theoretically and experimentally that untrained neural networks enhance the imaging quality and provide sub-diffraction spatial resolution of the multimode fiber imaging system.

Multimode system condition monitoring using sparsity reconstruction for quality control

<p>In this paper, we introduce an improved multivariate statistical monitoring method based on the stacked sparse autoencoder (SSAE). Our contribution focuses on the choice of the SSAE model based on neural networks to solve diagnostic problems of complex systems. In order to monitor the process performance, the squared prediction error (SPE) chart is linked with nonparametric adaptive confidence bounds which arise from the kernel density estimation to minimize erroneous alerts. Then, faults are localized using two methods: contribution plots and sensor validity index (SVI). The results are obtained from experiments and real data from a drinkable water processing plant, demonstrating how the applied technique is performed. The simulation results of the SSAE model show a better ability to detect and identify sensor failures.</p>

Retraction Note: Artificial intelligence enabled fuzzy multimode decision support system for cyber threat security defense automation

Retraction Note: Artificial intelligence enabled fuzzy multimode decision support system for cyber threat security defense automation

Building Neural Machine Translation Systems for Multilingual Participatory Spaces

This work presents the development of the translation component in a multistage, multilevel, multimode, multilingual and dynamic deliberative (M4D2) system, built to facilitate automated moderation and translation in the languages of five European countries: Italy, Ireland, Germany, France and Poland. Two main topics were to be addressed in the deliberation process: (i) the environment and climate change; and (ii) the economy and inequality. In this work, we describe the development of neural machine translation (NMT) models for these domains for six European languages: Italian, English (included as the second official language of Ireland), Irish, German, French and Polish. As a result, we generate 30 NMT models, initially baseline systems built using freely available online data, which are then adapted to the domains of interest in the project by (i) filtering the corpora, (ii) tuning the systems with automatically extracted in-domain development datasets and (iii) using corpus concatenation techniques to expand the amount of data available. We compare our results produced by the domain-adapted systems with those produced by Google Translate, and demonstrate that fast, high-quality systems can be produced that facilitate multilingual deliberation in a secure environment.

Model Predictive Control of a Multi-Mode Suspension System Using Preview Information and Weight Optimization

Abstract This study examines the effectiveness of a model predictive controller (MPC) on the multimode active suspension concept to reduce driver absorbed power. A multimode suspension uses additional degrees-of-freedom beyond a traditional active suspension. This allows the suspension to address disturbances with multiple frequencies when coupled with a noncausal control scheme such as MPC. A half-car model is developed by placing both active and passive components in series to mitigate high and low frequency disturbances at the tire-road interface. A stepwise MPC with preview information is applied to the model to measure an incoming disturbance. The model includes noise in state feedback and preview information. A Kalman filter addresses process and measurement noise while the preview information is filtered using an exponential moving average. Process and Measurement noise are considered to be known. Four disturbance profiles are examined: step, two-mode, three-mode, and an ISO8608 Class D profile. Weights used for the MPC process are optimized for each profile according to an objective function based on driver absorbed power. For each profile the response for uncontrolled, controlled, and controlled with preview is examined to assess effectiveness of the multimode suspension. Results demonstrate the utility of the multimode suspension supplemented with MPC for each profile. Driver absorbed power decreases by 68%, 99%, 73%, and 89% for the step, two-mode, three-mode, and ISO8608 Class D profile, respectively. Examination of the natural, disturbance, and forcing frequencies suggests that the MPC accounts for the damped natural frequencies of the system in response to incoming disturbances. The system shows potential to improve performance of vehicles traversing extreme terrain or maintaining a stable chassis for a variety of applications. Future work includes examination of the relationship between the damped natural frequencies, the disturbance, and the resulting control law.

2.4-Tb/s/λ*km fundamental mode transmission over OM2 fiber employing Kramers-Kronig receiver.

We propose a digital-carrier Kramers-Kronig (DC-KK) scheme based high-speed multimode fiber short-reach optical interconnect system with fundamental mode transmission. After optimization of the parameters, including the roll-off factor of the root-raised-cosine (RRC) filter, and the guard interval (GI) between signal and carrier tone, as well as the carrier signal power ratio (CSPR), 200-Gb/s 32-quadrature amplitude modulation (32QAM) signal transmission over 12-km OM2 fiber has been experimentally demonstrated with a bit error ratio (BER) below the soft-decision forward error correction (SD-FEC) threshold of 4 × 10-2. To the best of our knowledge, this is the highest experimental record of single lambda bitrate-distance-product (SLBDP) achieved by direct-detection (DD)-based transmission over a standard multimode fiber (MMF). The proposed scheme has potential to improve the system performance without replacing massive deployed legacy MMFs for future large-capacity data center interconnects (DCIs).

A Multimode Control Scheme for Output Regulation and Voltage Balancing in a Stacked-Switch Resonant Converter With Extended High Efficiency for Wide Gain Range Applications

In this article, a new hybrid comprehensive multimode control system is proposed for a stacked-switch bidirectional CLLC resonant converter for wide voltage gain applications. By configuring the presented leg with different switching patterns, the presented leg in the converter can operate in different modes: full-wave (FW), half-wave (HW), or voltage-doubler (VD) through the converter’s built-in circuit redundancy. The proposed hybrid control scheme consists of different control modes: variable frequency modulation, pulse-width modulation (PWM), and asymmetric PWM (APWM) control. Correspondingly, four voltage gain curves are derived from the proposed converter. With the proposed approach, the converter is able to achieve constant voltage regulation while constraining the range of switching frequency, allowing very high efficiencies to be realized for a wide range of input voltages. Soft-switching is achieved for all the semiconductor devices for the entire operating range. The steady-state and dynamic performances of the proposed hybrid comprehensive control system are verified through a proof-of-concept 400-V <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim ~1$ </tex-math></inline-formula> -kV/ 700-V, 1-kW laboratory prototype. Results confirmed that the efficiency is maintained between 95.03% and 96.97% throughout the specified input voltage range.

Silicon photonic integrated circuit for high-resolution multimode fiber imaging system

We propose and demonstrate a silicon photonic integrated circuit (PIC) for exciting different spatial modes launched into a multimode-fiber (MMF) speckle imaging system. The PIC consists of a 45-channel optical phased array and an array of nanoantennas to bridge the PIC and MMF. The nanoantenna array can excite a wide range of spatial modes in the MMF with a mode-group dependent loss of less than 3 dB. A high spatial resolution, which approaches the theoretical limit determined by the number of modes in the MMF, is realized by using the proposed PIC. An equivalent resolution of 1.75 µm is experimentally attained across a field of view of 105 µm. Two different algorithms for image reconstruction are compared. The algorithm based on truncated singular value decomposition is computationally efficient and suitable for real-time image reconstruction, whereas the algorithm based on total-variation regularization produces higher imaging quality. The number of resolvable points is derived to be ∼3000, which is more than the square of the number of phase shifters. These results represent the highest spatial resolution yet demonstrated in a PIC-based MMF imaging system.

Modulation of Steady-State Heat Transport in a Dissipative Multi-Mode Qubit-Photon System

Quantum heat transport is considered as an indispensable branch of quantum thermodynamics to potentially improve performance of thermodynamic devices. We theoretically propose a dissipative qubit-photon system composed of multiple coupled resonators interacting with a single two-level qubit, to explore the steady-state heat transport by tuning both the inter-resonator photon hopping and the qubit-photon coupling. Specifically in the three-mode case, the dramatic enhancement and suppression of the heat current into the central resonator can be modulated by the corresponding frequency, compared to the currents into two edge resonators. Moreover, fruitful cycle current components are unraveled at weak qubit-photon coupling, which are crucial to exhibit the nonmonotonic feature with increase of the reservoir temperature bias. In the one-dimensional case under the mean-field framework, the influence of the photon hopping on heat transport is analyzed. The steady-state heat current is comparatively enhanced to the single-mode limit at weak qubit-photon coupling, stemming from the nonvanishing mean-field photon excitation parameter and the additional cycle current component. We hope these obtained results may have possible applications in quantum thermodynamic manipulation and energy harvesting.

Design and Print Terahertz Metamaterials Based on Electrohydrodynamic Jet

Terahertz metamaterials are some of the core components of the new generation of high-frequency optoelectronic devices, which have excellent properties that natural materials do not have. The unit structures are generally much smaller than the wavelength, so preparation is mainly based on semiconductor processes, such as coating, photolithography and etching. Although the processing resolution is high, it is also limited by complex processing, long cycles, and high cost. In this paper, a design method for dual-band terahertz metamaterials and a simple, rapid, low-cost metamaterial preparation scheme based on step-motor-driven electrohydrodynamic jet technology are proposed. By transforming an open-source 3D printer, the metamaterial structures can be directly printed without complex semiconductor processes. To verify effectiveness, the sample was directly printed using nano conductive silver paste as consumable material. Then, a fiber-based multi-mode terahertz time-domain spectroscopy system was built for testing. The experimental results were in good agreement with the theoretical simulation.

Multi-mode information fusion navigation system for robot-assisted vascular interventional surgery

BackgroundMinimally invasive vascular intervention (MIVI) is a powerful technique for the treatment of cardiovascular diseases, such as abdominal aortic aneurysm (AAA), thoracic aortic aneurysm (TAA) and aortic dissection (AD). Navigation of traditional MIVI surgery mainly relies only on 2D digital subtraction angiography (DSA) images, which is hard to observe the 3D morphology of blood vessels and position the interventional instruments. The multi-mode information fusion navigation system (MIFNS) proposed in this paper combines preoperative CT images and intraoperative DSA images together to increase the visualization information during operations.ResultsThe main functions of MIFNS were evaluated by real clinical data and a vascular model. The registration accuracy of preoperative CTA images and intraoperative DSA images were less than 1 mm. The positioning accuracy of surgical instruments was quantitatively assessed using a vascular model and was also less than 1 mm. Real clinical data used to assess the navigation results of MIFNS on AAA, TAA and AD.ConclusionsA comprehensive and effective navigation system was developed to facilitate the operation of surgeon during MIVI. The registration accuracy and positioning accuracy of the proposed navigation system were both less than 1 mm, which met the accuracy requirements of robot assisted MIVI.

Spectrally encoded dual-mode interferometry with orthogonal scanning.

Spectrally encoded confocal microscopy (SECM) is a high-speed reflectance confocal microscopy technique. Here, we present a method to integrate optical coherence tomography (OCT) and SECM for complementary imaging by adding orthogonal scanning to the SECM configuration. The co-registration of SECM and OCT is automatic, as all system components are shared in the same order, eliminating the need for additional optical alignment. The proposed multimode imaging system is compact and cost-effective while providing the benefits of imaging aiming and guidance. Furthermore, speckle noise can be suppressed by averaging the speckles generated by shifting the spectral-encoded field in the direction of dispersion. Using a near infrared (NIR) card and a biological sample, we demonstrated the capability of the proposed system by showing SECM imaging at depths of interest guided by the OCT in real time and speckle noise reduction. Interfaced multimodal imaging of SECM and OCT was implemented at a speed of approximately 7 frames/s using fast-switching technology and GPU processing.

Resolution Analysis of Coincidence Imaging Based on OAM Beams With Equal Divergence Angle

The multi-mode orbital angular momentum (OAM) beams can be effectively applied in target detection when the divergence angles are equal. The resolution threshold of the coincidence imaging system with multi-mode OAM is analyzed assisted by the subspace projection method. First, the relationship between the imaging resolution and the correlation function (CF) of the measurement mode is obtained based on the first-order correlation algorithm for the multi-mode OAM-based coincidence imaging (MM-OAMCI). Then, the feature vector of each imaging unit is extracted to distinguish the imaging point in the discretized imaging plane. Finally, the resolution threshold is given based on three factors, i.e., the feature vector, the noise, and the reconstruction algorithm. Specifically, the resolution of the MM-OAMCI system is determined by the deployment of the transmitting array, the reconstruction algorithm and the noise caused by the system design, the imaging modeling, and the environment noise. The super-resolution capability of the multi-mode OAM coincidence imaging system is validated by the simulations and experiments. The imaging results show that the resolutions in elevation and azimuth of the reconstructed image can be improved largely compared with the traditional microwave coincidence imaging (TMCI) methods, which is consistent with the theoretical analysis results.

Multi-functional terahertz metamaterials based on nano-imprinting.

This paper reports a multi-functional terahertz (THz) metamaterial based on a nano-imprinting method. The metamaterial is composed of four layers: 4 L resonant layer, dielectric layer, frequency selective layer, and dielectric layer. The 4 L resonant structure can achieve broadband absorption, while the frequency selective layer can achieve transmission of specific band. The nano-imprinting method combines electroplating of nickel mold and printing of silver nano-particle ink. Using this method, the multilayer metamaterial structures can be fabricated on ultrathin flexible substrates to achieve visible light transparency. For verification, a THz metamaterial with broadband absorption in low frequency and efficient transmission in high frequency is designed and printed. The sample's thickness is about 200 µm and area is 65 × 65 mm2. Moreover, a fiber-based multi-mode terahertz time-domain spectroscopy system was built to test its transmission and reflection spectra. The results are consistent with the expectations.

Design of a Broadband Fiber Optic Mode Coupler for Multimode Optical Coherence Tomography

In this paper, we propose an optical fiber-based broadband mode coupler for multimode optical coherence tomography (OCT) in the O-band (1.26–1.36 μm). The proposed device uses a tapered few-mode fiber (FMF) to lower the effective mode index of the selected higher-order mode, which can be phase matched to the fundamental mode of the single-mode fiber (SMF). The tapered FMF and the SMF are side polished to reduce the core-to-core separation to achieve efficient mode coupling. Key design parameters such as the tapering ratio of the FMF, FMF core to SMF core separation, coupler length, and coupling ratio in the O-band are studied thoroughly. Higher-order modes of the FMF will be effectively coupled from the fundamental mode of SMF in the sample arm of the multimode OCT system. The reflected signals of the higher-order modes from the sample will be separated into several single-mode signals using the same fiber device before interfering with the reference light, which was not possible before. The proposed fiber device will be a key component to efficiently achieve multimode OCT operation with better signal collection efficiency and improved penetration depth for deep tissue imaging.