Frequency Dimensions Research Articles

A Precision Marketing Strategy of e-Commerce Platform Based on Consumer Behavior Analysis in the Era of Big Data

In order to develop a more efficient and accurate marketing strategy for consumers’ purchase behavior, this paper establishes a user value model by modeling and learning the user historical data of e-commerce enterprises. The improved K-means algorithm is used to cluster the purchase behavior of users, and the customer value matrix is constructed from two dimensions of consumption frequency and average consumption amount. Finally, e-commerce users are classified into four categories by marking points. The test results show that the improved K-means algorithm is stable and efficient, and the analysis of user clustering characteristics is helpful to develop more accurate marketing strategies.

Disaster-risk communication, perceptions and relocation decisions of rural residents in a multi-disaster environment: Evidence from Sichuan, China

Existing studies on disaster-risk management from the humanistic perspective have focused on disaster-risk perception as the starting point and ignored the important role of risk communication in shaping individual risk perception and changing behavioural responses. Taking Sichuan Province―a typical disaster-prone province in China―as an example and selecting rural residents in mountainous areas threatened by multiple disasters as interviewees, this study measured the characteristics of interviewees’ disaster-risk communication in the four dimensions of content preference, channel selection, communication frequency and communication form, and appraised the levels of their disaster-risk perceptions in the four dimensions of possibility, threat, self-efficacy and response efficacy. Additionally, econometric models were used to explore the chain of disaster-risk communication, perceptions and relocation decisions in different scenarios in the context of multiple disasters. The results revealed two main findings. (1) In the scenario where social relations promoted the relocation decision, interviewees derived their relocation decisions by two action paths: disaster-risk communication indirectly influenced relocation decisions through risk perception and disaster-risk communication directly influenced relocation decisions. For the indirect action path, the disaster-risk communication of interviewees had a significant impact on their risk perceptions, and self-efficacy and response efficacy played effective roles in their relocation decisions. For the direct action path, some channels of access to information and indicators of the communication form were significantly correlated with the relocation decision. (2) In the relocation-decision scenario promoted by the government, interviewees derived their relocation decision only by their disaster-risk communication. In risk communication, some channels of access to information and the communication forms of residents were significantly correlated with their relocation decisions, while the role of disaster-risk perceptions was ineffective.

Photonic-assisted space-frequency two-dimensional compressive radar receiver for high-resolution and wide-range detection.

Existing photonic compressive receivers have the problem of resolution deterioration when applied in wide-range radar detection. In this study, we propose a photonic-assisted space-frequency two-dimensional (2D) compressive radar receiver capable of achieving high-resolution detection in wide-range scenarios. For the space dimension, the compression process is realized by employing a spatially adaptive photonic projection basis, which guarantees complete mapping of arbitrarily delayed echoes-the key to high-resolution wide-range detection. For the frequency dimension, photonic compressive sensing is employed to further compress the bandwidth of the projected sparse signal. Therefore, the proposed system can achieve wide-range radar detection without resolution deterioration with compressed output. Herein, with two channels of 630 MHz outputs, high-resolution distance detection within a range of 21 km with a resolution of up to 2.3 cm is achieved. Moreover, inverse synthetic aperture radar (ISAR) imaging of two sets of four-point turntables distributed within the range of 21 km with a resolution of 2.3 cm × 5.7 cm is realized. The proposed photonic-assisted 2D compressive radar receiver is a viable solution to overcome the tradeoff between detection resolution and range of existing photonic compressive receivers, which indicates a path for the further development of high-resolution wide-range radar detection.

Data repository of the paper "Programmable large-scale simulation of lattices with photonic synthetic frequency dimensions"

Data repository of the paper "Programmable large-scale simulation of lattices with photonic synthetic frequency dimensions"

Analytical study of MgZnO/ZnO heterostructure field effect transistor for power switching

AbstractWe investigate the power switching mechanism to evaluate the power loss (PD) and efficiency (ɳ) in MgZnO/ZnO (MZO)‐based power heterostructure field effect transistor (HFET), and physical parameters responsible for PD in molecular beam epitaxy (MBE) and dual ion beam sputtering (DIBS) grown MZO HEFT and compare the performance with the group III‐nitride HFETs. This work extensively probes all physical parameters such as two‐dimensional electron gas (2DEG) density, mobility, switching frequency, and device dimension to study their impact on power switching in MZO HFET. Results suggest that the MBE and DIBS grown MZO HFET with the gate width (WG) of ~205 and ~280 mm at drain current coefficient (k) of 11 and 15, respectively, will achieve 99.96% and 99.95% of ɳ and 9.03 and 12.53 W of PD, respectively. Moreover, WG value for DIBS‐grown MZO HFET is observed to further reduce in the range of 112–168 mm by using a Y2O3 spacer layer leading to the maximum ɳ in the range of 99.98%–99.97% and the minimum PD in the range of 5–7 W. This work is significant for the development of cost‐effective HFETs for power switching applications.

A hybrid autoencoder framework of dimensionality reduction for brain-computer interface decoding

ObjectiveAs the scale of neural recording increases, Brain-computer interfaces (BCIs) are restrained by high-dimensional neural features, so dimensionality reduction is required as a preprocess of neural features. In this context, we propose a novel framework based on deep learning to reduce the dimensionality of neural features that are typically extracted from electrocorticography (ECoG) or local field potential (LFP). ApproachA high-performance autoencoder was implemented by chaining convolutional layers to deal with spatial and frequency dimensions with bottleneck long short-term memory (LSTM) layers to deal with the temporal dimension of the features. Furthermore, this autoencoder is combined with a fully connected layer to regularize the training. Main resultsBy applying the proposed method to two different datasets, we found that this dimensionality reduction method largely outperforms kernel principal component analysis (KPCA), partial least square (PLS), preferential subspace identification (PSID), and latent factor analysis via dynamical systems (LFADS). Besides, the new features obtained by our method can be applied to various BCI decoders, without significant differences in decoding performance. SignificanceA novel method is proposed as a reliable tool for efficient dimensionality reduction of neural signals. Its high performance and robustness are promising to enhance the decoding accuracy and long-term stability of online BCI systems based on large-scale neural recordings.

Bound state in a giant atom-modulated resonators system

It is of fundamental interest in controlling the light–matter interaction for a long time in the field of quantum information processing. Here, we explore a model by coupling a giant atom with the dynamically-modulated coupled-resonator waveguide and find the bound state, where the light shows the localization effect and the atomic decay into resonator modes is inhibited, excited by a propagating photon. An analytical treatment based on the separation of the propagating states and localized states of light has been proposed and provides inspiring explanation of our finding, i.e., there supports a quantum channel where the propagating photon can be converted to the localized state through the quantum interference from light–atom interactions in three resonators at different frequency detunings. Our work therefore shows the potential for actively localizing the photon in a modulated coupled-resonator waveguide system interacting with the giant atom, and also points out a way to study the light–atom interaction in a synthetic frequency dimension that holds the similar Hamiltonian.

Individually experienced heat index in a coastal Southeastern US city among an occupationally exposed population.

Recent studies have characterized individually experienced temperatures or individually experienced heat indices, including new exposure metrics that capture dimensions of exposure intensity, frequency, and duration. Yet, few studies have examined the personal thermal exposure in underrepresented groups, like outdoor workers, and even fewer have assessed corresponding changes in physiologic heat strain. The objective of this paper is to examine a cohort of occupationally exposed grounds and public safety workers (n = 25) to characterize their heat exposure and resulting heat strain. In addition, a secondary aim of this work is to compare individually heat index exposure(IHIE) across exposure metrics, fixed-site in situ weather stations, and raster-derived urban heat island (UHI) measurements in Charleston, SC, a humid coastal climate in the Southeastern USA. A Bland-Altman (BA) analysis was used to assess the level of agreement between the personal IHIE measurements and weather-station heat index (HI) and UrbanHeatIsland (UHI) measurements. Linear mixed-effect models were used to determine the association between individual risk factors and in situ weather station measurements significantly associated with IHIE measurements. Multivariable stepwise Cox proportional hazard modeling was used to identify the individual and workplace factors associated with time to heat strain in workers. We also examined the non-linear association between heat strain and exposure metrics using generalized additive models. We found significant heterogeneity in IHIE measurements across participants. We observed that time to heat strain was positively associated with a higher IHIE, older age, being male, and among Caucasian workers. Important nonlinear associations between heat strain occurrence and the intensity, frequency, and duration of personal heat metrics were observed. Lastly, our analysis found that IHIE measures were significantly similar forweather station HI, although differences were more pronounced for temperature and relative humidity measurements. Conversely, our IHIE findings were much lower than raster-derived UHI measurements. Real-time monitoring can offer important insights about unfolding temperature-health trends and emerging behaviors during thermal extreme events, which have significant potential to provide situational awareness.

Technologically feasible quasi-edge states and topological Bloch oscillation in the synthetic space.

The dimensionality of a physical system is one of the major parameters defining its physical properties. The recently introduced concept of synthetic dimension has made it possible to arbitrarily manipulate the system of interest and harness light propagation in different ways. It also facilitates the transformative architecture of system-on-a-chip devices enabling far reaching applications such as optical isolation. In this report, a novel architecture based on dynamically-modulated waveguide arrays with the Su-Schrieffer-Heeger configuration in the spatial dimension is proposed and investigated with an eye on a practical implementation. The propagation of light through the one-dimensional waveguide arrays mimics time evolution of the field in a synthetic two-dimensional lattice. The addition of the effective gauge potential leads to an exotic topologically protected one-way transmission along adjacent boundary. A cosine-shape isolated band, which supports the topological Bloch oscillation in the frequency dimension under the effective constant force, appears and is localized at the spatial boundary being robust against small perturbations. This work paves the way to improved light transmission capabilities under topological protections in both spatial and spectral regimes and provides a novel platform based on a technologically feasible lithium niobate platform for optical computing and communication.

Observation of flat-band and band transition in the synthetic space

Constructions of synthetic lattices in photonics attract growingly attentions for exploring interesting physics beyond the geometric dimensionality, among which modulated ring resonator system has been proved as a powerful platform to create different kinds of connectivities between resonant modes along the synthetic frequency dimension with many theoretical proposals. Various experimental realizations are investigated in a single ring resonator, while building beyond simple synthetic lattices in multiple rings with different types remains lacking, which desires to be accomplished as an important step further. Here, we implement the experimental demonstration of generating the one-dimensional Lieb lattice along the frequency axis of light, realized in two coupled ring resonators while the larger ring undergoing dynamic modulation. Such synthetic photonic structure naturally exhibits the physics of flat band. We show that the time-resolved band structure read out from the drop-port output of the excited ring is the intensity projection of the band structure onto specific resonant mode in the synthetic momentum space, where gapless flat band, mode localization effect, and flat to non-flat band transition are observed in experiments and verified by simulations. Our work gives a direct evidence for the constructing synthetic Lieb lattice with two rings, which hence makes a solid step towards experimentally constructing more complicated lattices in multiple rings associated with synthetic frequency dimension.

Joint Communication–Motion Planning in Networked Robotic Systems

In the recent decade, many research efforts in robotic society have considered motion planning for maintaining connectivity in networked robotic system (NRS) by exploiting robotic autonomous mobility. On the other hand, cognitive radio (CR) in the communication society aims at fully exploiting the spectrum in a wireless network, while the motion planning is seldom considered, as a wireless device itself may not decide where to go. In this article, joint communication–motion planning (JCMP) is proposed to boost the capability of NRS by exploiting both the adaptive communications and mobility control of autonomous robots. Specifically, we propose a JCMP framework for NRS, which aims at jointly exploiting the degree-of-freedom in mobility, space, time, frequency and power dimensions from both the motion and communication components. Afterward, we design and evaluate JCMP in a conventional and a CR-relay-assisted robot system, which shows the capability of JCMP in improving the performance of NRS. Finally, we summarize the proposed JCMP-enabled NRS framework and provide a series of future research directions.

An adaptive regional model spectrum sensing algorithm based on TD-LTE system

Cognitive radio is an important way to improve spectrum efficiency and spectrum sensing is the key technology of cognitive radio. However, the performance of spectrum sensing only from time–frequency dimension is insufficient. In order to get better sensing performance, an adaptive regional model spectrum sensing algorithm is proposed in this paper. Firstly, an improved region model is proposed through interference analysis. By modifying the boundary calculation method and adjusting the region sensing strategy, the proposed region model can achieve higher spectrum utilization. Secondly, the time-sharing spectrum sensing strategy and cognitive database are proposed to reduce system power consumption, and give full play to the systematic advantages of the regional model. Thirdly, an adaptive spectrum sensing algorithm is designed according to the characteristics of the regional model to realize the time-sharing spectrum sensing strategy, which ensures the consistency of the overall regional sensing performance through the optimal sampling frequency and hyperplane-distance based cooperative sensing. Finally, the spectrum prediction algorithm is used to further optimize the spectrum sensing performance. The simulation results show that the proposed regional model has higher spectrum utilization and better adaptability. Compared with other regional models, the spectrum utilization can be improved by more than 11.12% in the region with high occupancy channel and the activity range of primary users is greater than 2 km. And the control error of model classification performance can be controlled within 2.11% by sampling frequency. At the same time, the combination of spectrum prediction technology can effectively improve the spectrum sensing performance.

All-Optical Control of the Photonic Hall Lattice in a Pumped Waveguide Array

The quantum Hall system possesses topologically protected edge states, which have enormous theoretical and practical implications in both fermionic and bosonic systems. Harnessing the quantum Hall effect in optical platforms with lower dimensionality is highly desirable with synthetic dimensions and has attracted broad interests in the photonics society. Here, we introduce an alternative way to realize the artificial magnetic field in a frequency dimension, which is achieved in a pump-probe configuration with cross-phase modulations in a one-dimensional four-waveguide array. The dynamics of the topological chiral edge state has been studied and the influence from the crosstalk of the pump fields has been explored. Our work shows an all-optical way to simulate the quantum Hall system in a photonic system and holds potential applications in manipulating light in waveguide systems.

Connectedness between nonrenewable and renewable energy consumption, economic growth and CO2 emission in Vietnam: New evidence from a wavelet analysis

The studies exploring inter-relations between non-renewable energy consumption, renewable energy consumption, GDP, and CO2 emission are quite limited in Vietnam due to the limitation of data. Different major players in this market, such as investors, regulators, and other financial actors have different time horizons. By applying innovative multivariate wavelet analysis tools, including partial wavelet coherency and partial wavelet gain, this paper investigates these relations in the time and frequency dimensions in Vietnam during the 1985–2019 period. The multiple coherencies between the non-renewable energy consumption and GDP and CO2 growth suggest that these regions were located at medium frequencies (5–12 years) and concentrated on the 1985–2000 period and the 2003–2019 period. Regarding the relation between renewable consumption and GDP and CO2 growth that the region only concentrated in the high-frequency band (from 2 to 12-year frequency-band) running from 1985 to 2001 and low-frequency band (from 22 to 25-year frequency-band) running from 2011 to 2019. The partial coherency between non-renewable energy consumption and GDP reveals two phases. In the first phase (the beginning of sample to 2000), changes in the non-renewable energy consumption led to changes in GDP, and the relation is negative, while GDP is in-phase with non-renewable energy consumption leading in the second phase (from 2000 to 2015). The partial phase-difference between non-renewable energy consumption and CO2 emission suggests that changes in CO2 emission led to changes in non-renewable energy consumption, and the relation was negative. Regarding the partial coherency between renewable consumption and GDP, most regions were located in the 2–12-year frequency band running from 1985 to 2001, from 2001 to 2003, and from 2005 to 2012. During the 1985–2991 period, the results indicate the anti-phase relation with the GDP growth leading, while changes in renewable energy consumption led to changes in GDP growth, and the association is negative from 2001 to 2003. Since 2003, there was an anti-phase relation with the GDP growth leading. Lastly, the partial wavelet coherency of renewable energy consumption and CO2 emission indicates that regions were found to be statistically significant in the 3-4- and 7-15-year frequency band and there was the anti-phase relation with the CO2 emission leading.

Creating boundaries along a synthetic frequency dimension

Synthetic dimensions have garnered widespread interest for implementing high dimensional classical and quantum dynamics on low-dimensional geometries. Synthetic frequency dimensions, in particular, have been used to experimentally realize a plethora of bulk physics effects. However, in synthetic frequency dimension there has not been a demonstration of a boundary which is of paramount importance in topological physics due to the bulk-edge correspondence. Here we construct boundaries in the frequency dimension of dynamically modulated ring resonators by strongly coupling an auxiliary ring. We explore various effects associated with such boundaries, including confinement of the spectrum of light, discretization of the band structure, and the interaction of boundaries with one-way chiral modes in a quantum Hall ladder, which exhibits topologically robust spectral transport. Our demonstration of sharp boundaries fundamentally expands the capability of exploring topological physics, and has applications in classical and quantum information processing in synthetic frequency dimensions.

Enhanced Nuclear Magnetic Resonance Spectroscopy with Isotropic Mixing as a Pseudodimension.

Chemical analysis based on liquid-state nuclear magnetic resonance spectroscopy exploits numerous observables, mainly chemical shifts, relaxation rates, and internuclear coupling constants. Regarding the latter, the efficiencies of internuclear coherence transfers may be encoded in spectral peak intensities. The dependencies of these intensities on the experimental parameter that influences the transfer, for example, mixing time, are an important source of structural information. Yet, they are costly to measure and difficult to analyze. Here, we show that peak intensity build-up curves in two-dimensional total correlation spectroscopy (2D TOCSY) experiments may be quickly measured by employing nonuniform sampling and that their analysis can be effective if supported by quantum mechanical calculations. Thus, such curves can be used to form a new, third pseudodimension of the TOCSY spectrum. Similarly to the other two frequency dimensions, this one also resolves ambiguities and provides characteristic information. We show how the approach supports the analysis of a fragment of protein Tau Repeat-4 domain. Yet, its potential applications are far broader, including the analysis of complex mixtures or other polymers.

HIV Testing Patterns Among Recently Self-Tested Russian Men Who Have Sex With Men: A Qualitative Study.

Most qualitative research to date on HIV self-testing (HIVST) has been devoted to questions related to perceptions of HIVST among various groups of men who have sex with men (MSM) in different countries. However, little is known about HIV testing patterns of HIVST testers. Thrity-two Russian MSM, 10 with HIV and 22 without, from five cities were interviewed about their HIV testing and risk behaviors. Five types of testers "maintenance testers," "risk-based testers," "convenience testers," "test avoiders," and "HIVST-only testers" were identified in the study. Three dimensions of HIV testing patterns-testing motive, frequency, and mode-were proposed to improve existing typifications. Almost all informants practiced condomless sex with their primary partners; HIV testing or condom negotiation in primary partnerships before proceeding to condomless sex was rare. Increase in HIVST availability at no cost for MSM and targeted prevention efforts for MSM on both individual and dyadic level are urgently needed.

Dual residual attention network for remaining useful life prediction of bearings

Rolling bearing is a critical component of rotating machines and it is indispensable to accurately predict the remaining useful life (RUL) of bearings to realize predictive maintenance. To extract degradation-sensitive features from complex vibration signals, this paper proposes a new dual residual attention network (DRAN) to improve prediction performance. A frequency band residual attention (FBRA) block is first designed to automatically discover important frequency bands related to bearing degradation. Then, a spatio-temporal residual attention (STRA) block is proposed to sequentially learn high-level representations from frequency and temporal dimensions with a hybrid dilated convolution neural network (HDCNN) and then adaptively identify important features contributing to bearing RUL prediction via a residual attention mechanism. Finally, a weighted RUL estimation block is used to smooth the predicted RUL and provide a more reliable prediction. Experimental results on a public bearing dataset demonstrate the superiority of our DRAN against several state-of-the-art methods.

Coupled electromagnetic heat transfer model for cemented tailings backfill cured by microwave energy

Cemented tailings backfill (CTB) is a composite material containing binder, tailings and water, and it is commonly made available for filling mine-out areas and managing waste tailings. When backfilled, the CTB strength and its gain rate should be guaranteed for safe and efficient mining. It is acknowledged that increasing the CTB temperature is beneficial to its strength development. For this reason, microwave heating is introduced and applied to raise the CTB temperature quickly and thus accelerate its strength gain. To date, no numerical research has been conducted to investigate the electromagnetic and thermal properties of microwave cured CTB. Therefore, the present study proposes a coupled electromagnetic heat transfer model for the CTB heated by microwave energy. This proposed model considers the conversion of energy (electrical to electromagnetic and then to thermal), courses of heat conduction and convection, and relevant temperature variation. Two groups of experimental data are used to verify the prediction ability of the model simulation, and this model can accurately describe the thermal properties of the microwave heated CTB. Based on the validated model, the effects of input power, frequency and sample dimension on the distribution of heat and electromagnetic field are discussed. This study can be a contribution to the optimization of microwave parameters and sample dimension, for higher temperature development, less energy consumption and more uniform heating, in future laboratory experiments and field applications.

Giant Atoms in a Synthetic Frequency Dimension.

Giant atoms that interact with real-space waveguides at multiple spatial points have attracted extensive attention due to their unique interference effects. Here we propose a feasible scheme for constructing giant atoms in a synthetic frequency dimension with, e.g., a dynamically modulated superconducting resonator and a tailored three-level artificial atom. Both analytical and numerical calculations show good agreement between our scheme and real-space two-level giant atoms. In particular, the symmetry of the model in momentum space can be broken by tuning the phase of the external field applied on the atom, enabling chiral interactions between the atom and the frequency lattice. We further demonstrate the possibility of simulating cascaded interaction and directional excitation transfer in the frequency dimension by directly extending our model to involve more such effective giant atoms.